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Volume 14 · Number 3 · September 2011 · ISSN 1139-6709

Spanish Society for Microbiology Volume 14 · Number 3 · September 2011

International Microbiology

INTERNATIONAL MICROBIOLOGY

Volume 14

RESEARCH ARTICLES Köchling T, Lara-Martín P, González-Mazo E, Amils R, Sanz JL Microbial community composition of anoxic marine sediments in the Bay of Cadiz (Spain)

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Starek M, Kolev KI, Berthiaume L, Yeung CW, Sleep BE, Wolfaardt GM, Hausner M A flow cell simulating a surface rock fracture for investigations of groundwater-derived biofilms

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de Toro M, Sáenz Y, Cercenado E, Rojo-Bezares B, García-Campello M, Undabeitia E, Torres C Genetic characterization of the mechanisms of resistance to amoxicillin/clavulanate and third generation cephalosporins in Salmonella enterica from three Spanish hospitals

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pp 121-182

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Marques AP, Duarte AJ, Chambel L, Teixeira MF, San Romão MV, Tenreiro R Genomic diversity of Oenococcus oeni from different winemaking regions of Portugal

2011

Mora A, Herrera A, López C, Dahbi G, Mamani R, Pita JM, Alonso MP, Llovo J, Bernárdez MI, Blanco JE, Blanco M, Blanco J Characteristics of the Shiga-toxin-producing enteroaggregative Escherichia coli O104:H4 German outbreak strain and of STEC strains isolated in Spain

Number 3

REVIEW ARTICLE

INTERNATIONAL MICROBIOLOGY 14(3) 2011

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With the collaboration of the Institute for Catalan Studies

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Ricardo Amils, Autonomous University of Madrid, Madrid, Spain Albert Bordons, Rovira i Virgili University, Tarragona, Spain Albert Bosch, University of Barcelona, Barcelona, Spain Enrico Cabib, National Institutes of Health, Bethesda, MD, USA Victoriano Campos, Pontificial Catholic University of Valparaíso, Chile Josep Casadesús, University of Seville, Sevilla, Spain Yehuda Cohen, The Hebrew University of Jerusalem, Jerusalem, Israel Rita R. Colwell, Univ. of Maryland & Johns Hopkins University, MD, USA Katerina Demnerova, Inst. of Chem. Technology, Prague, Czech Republic Esteban Domingo, CBM, CSIC-UAM, Cantoblanco, Madrid, Spain Mariano Esteban, Natl. Center for Biotechnol., CSIC, Cantoblanco, Spain M. Luisa García López, University of León, León, Spain Steven D. Goodwin, University of Massachusetts-Amherst, MA, USA Juan C. Gutiérrez, Complutense University of Madrid, Madrid, Spain Johannes F. Imhoff, University of Kiel, Kiel, Germany Juan Imperial, Technical University of Madrid, Madrid, Spain John L. Ingraham, University of California-Davis, CA, USA Juan Iriberri, University of the Basque Country, Bilbao, Spain Roberto Kolter, Harvard Medical School, Boston, MA, USA Germán Larriba, University of Extremadura, Badajoz, Spain Paloma Liras, University of León, León, Spain Ruben López, Center for Biological Research, CSIC, Madrid, Spain Juan M. López Pila, Federal Environ. Agency, Dessau-Roßlau, Germany Michael T. Madigan, Southern Illinois University, Carbondale, IL, USA M. Benjamín Manzanal, University of Oviedo, Oviedo, Spain Beatriz S. Méndez, University of Buenos Aires, Buenos Aires, Argentina Diego A. Moreno, Technical University of Madrid, Madrid, Spain Ignacio Moriyón, University of Navarra, Pamplona, Spain José Olivares, Experimental Station of Zaidín, CSIC, Granada, Spain Juan A. Ordóñez, Complutense University of Madrid, Madrid, Spain Eduardo Orías, University of California-Santa Barbara, CA, USA José M. Peinado, Complutense University of Madrid, Madrid, Spain J. Claudio Pérez Díaz, Ramón y Cajal Institute Hospital, Madrid, Spain Antonio G. Pisabarro, Public University of Navarra, Pamplona, Spain Carmina Rodríguez, Complutense University of Madrid, Madrid, Spain Manuel de la Rosa, Virgen de las Nieves Hospital, Granada, Spain Tomás A. Ruiz Argüeso, Technical University of Madrid, Spain James A. Shapiro, University of Chicago, IL, USA John Stolz, Duquesne University, Pittsburgh, PA, USA James Strick, Franklin & Marshall College, Lancaster, PA, USA Jean Swings, Ghent University, Ghent, Belgium Gary A. Toranzos, University of Puerto Rico, San Juan, Puerto Rico Antonio Torres, University of Seville, Sevilla, Spain José A. Vázquez-Boland, University of Edinburgh, Edinburgh, UK Antonio Ventosa, University of Seville, Sevilla, Spain Tomás G. Villa, Univ. of Santiago de Compostela, Santiago de C., Spain Miquel Viñas, University of Barcelona, Barcelona, Spain Dolors Xairó, Biomat, S.A., Grifols Group, Parets del Vallès, Spain

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Books Miller JH (1972) Experiments in molecular genetics. 2nd ed. Cold Spring Harbor Laboratory Press, Cold Spring Harbor, New York, USA Book chapters Lo N, Eggleton P (2011) Termite phylogenetics and co-cladogenesis with symbionts. In: Bignell DE, Yves R, Nathan L (eds) Biology of termites: a modern synthesis, 2nd ed. Springer, Heidelberg, Germany, pp.27-50 Please list the first eight authors and then add “et al.” if there are additional authors. Citation of articles that have appeared in electronic journals is allowed if access to them is unlimited and their URL or DOI number to the full-text article is supplied. Tables and Figures should be restricted to the minimum needed to clarify the text; a total number (F + T) of five is recommended. Neither tables nor figures should be used to present results that can be described with a short statement in the text. They also must not be integrated into the text. Figure legends must be typed double-spaced on a separate page and appended to the text. Photographs should be well contrasted and not exceed the printing area (17.6 × 23.6 cm). Magnification of micrographs should be shown by a bar marker. For color illustrations, the authors will be expected to pay the extra costs of 600.00 € per article. Color figures may be accepted for use on the cover of the issue in which the paper will appear. Tables must be numbered consecutively with Arabic numerals and submitted separately from the text at the end of the paper. Tables may be edited to permit more compact typesetting. The publisher reserves the right to reduce or enlarge figures and tables. Electronic Supporting Information (SI) such as supplemental figures, tables, videos, micrographs, etc. may be published as additional materials, when details are too voluminous to appear in the printed version. SI is referred to in the article’s text and is ported on the journal’s website (www.im.microbios.org) at the time of publication. Abbreviations and units should follow the recommendations of the IUPAC-IUB Commission. Information can be obtained at: http://www.chem.qmw.ac.uk/iupac/. Common abbreviations such as cDNA, NADH and PCR need not to be defined. Non-standard abbreviation should be defined at first mention in the Summary and again in the main body of the text and used consistently thereafter. SI units should be used throughout. For Nomenclature of organisms genus and species names must be in italics. Each genus should be written out in full in the title and at first mention in the text. Thereafter, the genus may be abbreviated, provided there is no danger of confusion with other genera discussed in the paper. Bacterial names should follow the instructions to authors of the International Journal of Systematic and Evolutionary Microbiology. Nomenclature of protists should follow the Handbook of Protoctista (Jones and Bartlett, Boston). Outline of the Editorial Process Peer-Review Process All submitted manuscripts judged potentially suitable for the journal are formally peer reviewed. Manuscripts are evaluated by a minimum of two and a maximum of five external reviewers working in the paper’s specific area. Reviewers submit their reports on the manuscripts along with their recommendation and the journal’s editors will then make a decision based on the reviewersAcceptance, article preparation, and proofs. Acceptance, article preparation, and proofs Once an article has been accepted for publication, manuscripts are thoroughly revised, formatted, copy-edited, and typeset. PDF proofs are generated so that the authors can approve the final article. Only typesetting errors should be corrected at this stage. Corrections of errors that were present in the original manuscript will be subject to additional charges. Corrected page proofs must be returned by the date requested.

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CONTENTS INTERNATIONAL MICROBIOLOGY (2011) 14:121-182 ISSN 1139-6709 www.im.microbios.org

Volume 14, Number 3, September 2011

REVIEW ARTICLE

Mora A, Herrera A, López C, Dahbi G, Mamani R, Pita JM, Alonso MP, Llovo J, Bernárdez MI, Blanco JE, Blanco M, Blanco J Characteristics of the Shiga-toxin-producing enteroaggregative Escherichia coli O104:H4 German outbreak strain and of STEC strains isolated in Spain

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RESEARCH ARTICLES

Köchling T, Lara-Martín P, González-Mazo E, Amils R, Sanz JL Microbial community composition of anoxic marine sediments in the Bay of Cadiz (Spain)

143

Marques AP, Duarte AJ, Chambel L, Teixeira MF, San Romão MV, Tenreiro R Genomic diversity of Oenococcus oeni from different winemaking regions of Portugal

155

Starek M, Kolev KI, Berthiaume L, Yeung CW, Sleep BE, Wolfaardt GM, Hausner M A flow cell simulating a surface rock fracture for investigations of groundwater-derived biofilms

163

de Toro M, Sáenz Y, Cercenado E, Rojo-Bezares B, García-Campello M, Undabeitia E, Torres C Genetic characterization of the mechanisms of resistance to amoxicillin/clavulanate and third generation cephalosporins in Salmonella enterica from three Spanish hospitals

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International Microbiology INTERNATIONAL MICROBIOLOGY is a quarterly, open-access, peer-reviewed journal in the fields of basic and applied microbiology. It publishes two kinds of papers: research articles and complements (editorials, perspectives, books reviews, etc.). Submission Manuscripts must be submitted by one of the authors of the manuscript by e-mail to int.microbiol@microbios.org. As part of the submission process, authors are required to comply with the following items, and submissions may be returned if they do not adhere to these guidelines: 1. The work described has not been published before, including publication on the World Wide Web (except in the form of an Abstract or as part of a published lecture, review, or thesis), nor is it under consideration for publication elsewhere. 2. All the authors have agreed to its publication. The corresponding author signs for and accepts responsibility for releasing this material and will act on behalf of any and all coauthors regarding the editorial review and publication process. 3. The submission file is in Microsoft Word, RTF, or OpenOffice document file format. 4. The manuscript has been prepared in accordance with the journal’s accepted practice, form, and content, and it adheres to the stylistic and bibliographic requirements outlined in “Preparation of manuscripts”. 5. Illustrations and figures are placed separately in another document. Large files should be compressed.

Copyright and license If an article is accepted for publication in INTERNATIONAL MICROBIOLOGY, the authors (or other copyright holders) must transfer the copyright to the journal, which covers the right—not exclusive—to reproduce and distribute the article including reprints, translations, photographic reproductions, microforms, electronic form (offline, online) or any other reproduction of similar nature. All articles in INTERNATIONAL MICROBIOLOGY will be available on the Internet to any reader at no cost. Please read about the Creative Commons Attribution-NonComercial-ShareAlike 3.0 Unported License before submitting your paper. Open Access and article processing charges INTERNATIONAL MICROBIOLOGY’s open access policy enables a far greater distribution and impact of an author’s work and is in the interest of the scientific community worldwide. Currently many research funding agencies not only allow these expenses to be paid from their grants, but also encourage Open Access publication. The journal’s standard cost for the Open Access Fee is 800.00 €. If a manuscript requires extensive editorial work, an extra charge may be requested. The acceptance of a paper, however, will not depend on the authors’ ability to pay these charges. Individual waiver requests must be done during the submission process and will be considered on a case-to-case basis.

Cover legends Front cover CENTER. A phylogenetic tree of Escherichia coli: Phylogeny analysis has shown that E. coli comprises four main phylogenetic groups (A, B1, B2, and D). Shiga toxin (verotoxin)-producing E. coli (STEC/VTEC) normally belong to phylogroups B1 and D, whereas extraintestinal pathogenic E. coli (ExPEC) mainly belong to phylogroups B2 and D. A STEC/VTEC strain belonging to serotype O104:H4, phylogenetic group B1 and sequence type ST678, with virulence features common to the enteroaggregative E. coli (EAEC) pathotype, was reported as the cause of the recent 2011 outbreak in Germany. [See article by Mora et al., pp. 121-141, this issue.]. Red “leaves”: ExPEC; green “leaves”: VTEC. UPPER LEFT. Transmission electron micrograph of negatively stained bacteriophages of the extremely halophilic bacterium Salinobacter ruber. The phages were isolated from brines of a crystallizer pond at the Bras del Port salterns (Santa Pola, Alicante, Spain). Micrograph by Pepa Antón, University of Alicante, Spain, and Inmaculada Meseguer, University Miguel Hernández, Alicante, Spain. (Magnification, ca. 250,000×) UPPER RIGHT. Transmission electron micrograph of two archaeal square cells of Haloquadratum spp. from a crystallizer pond at the Bras del Port salterns (Santa Pola, Alicante, Spain). Gas vacuoles are visible as bright spots around the edges of the cells. An extracellular filamentous structure can be seen as well. By Inmaculada Meseguer, University Miguel Hernández, Alicante, Spain. (Magnification ca. 12,000×) LOWER LEFT. Micrograph of a protist (darkfield microscopy) from the hindgut of an individual of the soldier caste of Reticulitermes grassei, from Cordova, Spain. Termites are eusocial and colonies consist of distinct castes, including sterile workers (pseudergates), soldiers, and the reproductive kings and queens. Preparation by Mercedes Berlanga, University of Barcelona, Spain, and micrograph by Rubén Duro. (Magnification, ca. 2000×). LOWER RIGHT. Fruit bodies of the edible basidiomycete Pleurotus ostreatus (oyster mushroom) growing on a substrate of wheat straw. The mycelium colonizes the wheat straw until the appropriate environmental conditions trigger the change in growth

phase and fruit bodies flush in bunches. The bunch size varies with the strains; the bunches produced by strain N001 (picture) can be formed by up to 20 carpophores and reach a fresh weight of up to 250 g. This strain contains two nuclei whose genome has been sequenced by L. Ramírez and A.G. Pisabarro, and their team, at the Public University of Navarre, Pamplona, Spain in collaboration with the Joint Genome Institute, Walnut Creek, CA, USA. (Magnification, ca. 0.5×)

Back cover Portrait of Néstor Morales Villazón, a pioneer in microbiology in Bolivia. Born in Cochabamba (Bolivia) on February 2, 1879 to Constantino Morales and Aurelia Villazón, he entered the medical school in his hometown, later moving to La Paz to finish his studies. He was a surgeon in the sanitation services of the Federal Army during the early days of the Revolution in 1898, carrying out his work at the Landaeta Hospital and the Public Hospital, with a later appointment as Surgeon to the Army Training School. Soon he was named Assistant Professor of Dissection at the School of Medicine of the University of La Paz, and within a short time Professor of Anatomy. In 1904, Morales was sent to Europe to be trained in bacteriology. Upon his return, he held several positions: Professor of the School of Hygiene, head of the Bacteriology Section at the Board of Health, Dean of the Medical School, and director of the National Institute for Bacteriology. In 1911, he founded the Dental School of La Paz; in 1915, he organized the Pediatrics Section of Landaeta Hospital, even writing a book on childcare. However, he was fascinated by microbiology and most of his professional career was devoted to what was, at that time, a new field of medicine and biology. In 1912, he founded a journal, Revista de Bacteriología e Higiene, which he used as a platform to improve Bolivian hygiene and to promote the prevention of infectious diseases—mainly typhoid fever—through vaccination. Despite his invaluable work and having received many honors both in his country—in 1913 the Senate of Bolivia awarded him a gold medal—and abroad, in 1920 he was forced into exile for political reasons. He began a new life in Argentina but never forgot his beloved Bolivia. During the El Chaco War, he sent vaccines and other products to the Bolivian National Institute of Bacteriology, so that its work could continue.

Front cover and back cover design by MBerlanga & RGuerrero

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REVIEW ARTICLE INTERNATIONAL MICROBIOLOGY (2011) 14:121-141 DOI: 10.2436/20.1501.01.142 ISSN: 1139-6709 www.im.microbios.org

Characteristics of the Shiga-toxin-producing enteroaggregative Escherichia coli O104:H4 German outbreak strain and of STEC strains isolated in Spain Azucena Mora,1 Alexandra Herrera,1 Cecilia López,1 Ghizlane Dahbi,1 Rosalia Mamani,1 Julia M. Pita,2 María P. Alonso,2 José Llovo,3 María I. Bernárdez,1,3 Jesús E. Blanco,1 Miguel Blanco,1 Jorge Blanco1* 1

E. coli Reference Laboratory (LREC), Department of Microbiology and Parasitology, Faculty of Veterinary Science, University of Santiago de Compostela (USC), Lugo, Spain. 2Unit of Microbiology, Lucus Augusti Hospital, Lugo, Spain. 3 Service of Microbiology, University Hospital Complex of Santiago de Compostela (CHUS), Santiago de Compostela, Spain Received 10 July 2011 · Accepted 31 July 2011

Summary. A Shiga-toxin-producing Escherichia coli (STEC) strain belonging to serotype O104:H4, phylogenetic group B1 and sequence type ST678, with virulence features common to the enteroaggregative E. coli (EAEC) pathotype, was reported as the cause of the recent 2011 outbreak in Germany. The outbreak strain was determined to carry several virulence factors of extraintestinal pathogenic E. coli (ExPEC) and to be resistant to a wide range of antibiotics. There are only a few reports of serotype O104:H4, which is very rare in humans and has never been detected in animals or food. Several research groups obtained the complete genome sequence of isolates of the German outbreak strain as well as the genome sequences of EAEC of serotype O104:H4 strains from Africa. Those findings suggested that horizontal genetic transfer allowed the emergence of the highly virulent Shiga-toxin-producing enteroaggregative E. coli (STEAEC) O104:H4 strain responsible for the outbreak in Germany. Epidemiologic investigations supported a linkage between the outbreaks in Germany and France and traced their origin to fenugreek seeds imported from Africa. However, there has been no isolation of the causative strain O104:H4 from any of the samples of fenugreek seeds analyzed. Following the German outbreak, we conducted a large sampling to analyze the presence of STEC, EAEC, and other types of diarrheagenic E. coli strains in Spanish vegetables. During June and July 2011, 200 vegetable samples from different origins were analyzed. All were negative for the virulent serotype O104:H4 and only one lettuce sample (0.6%) was positive for a STEC strain of serotype O146:H21 (stx1, stx2), considered of low virulence. Despite the single positive case, the hygienic and sanitary quality of Spanish vegetables proved to be quite good. In 195 of the 200 samples (98%), <10 colony-forming units (cfu) of E. coli per gram were detected, and the microbiological levels of all samples were satisfactory (<100 cfu/g). The samples were also negative for other pathotypes of diarrheagenic E. coli (EAEC, ETEC, tEPEC, and EIEC). Consistent with data from other countries, STEC belonging to serotype O157:H7 and other serotypes have been isolated from beef, milk, cheese, and domestic (cattle, sheep, goats) and wild (deer, boar, fox) animals in Spain. Nevertheless, STEC outbreaks in Spain are rare. [Int Microbiol 2011; 14(3):121-141] Keywords: enterohemorrhagic Escherichia coli · enteroaggregative E. coli · Shiga toxin · serotypes O104:H4, O157:H7, O146:H21

*Corresponding author: J. Blanco Laboratorio de Referencia de E. coli (LREC) Departamento de Microbiología y Parasitología Facultad de Veterinaria Universidad de Santiago de Compostela 27002 Lugo, Spain Tel. +34-982822108 E-mail: jorge.blanco@usc.es

A brief review of STEC Escherichia coli was first discovered in the gut in 1885 by the German bacteriologist-pediatrician Theodore von Escherich, who called it Bacterium coli commune. Most Escherichia coli strains are nonpathogenic members of the


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intestinal microbiota of humans and other animals, but some strains have acquired virulence factors that enable them to cause important intestinal and extraintestinal diseases, such as diarrhea, hemorrhagic colitis (HC), hemolytic uremic syndrome (HUS), urinary tract infections (UTI), septicemia, and neonatal meningitis. Categories of pathogenic Escherichia coli strains, phylogenetic groups, and typing. Five main categories or pathogroups of diarrheagenic E. coli are recognized: typical enteropathogenic E. coli (tEPEC), enteroinvasive E. coli (EIEC), enterotoxigenic E. coli (ETEC), Shiga toxin (verotoxin)-producing E. coli (STEC/VTEC), and enteroaggregative E. coli (EAEC). In addition, the adherent-invasive E. coli (AIEC) pathovar has been increasingly implicated in the etiopathogenesis of Crohn’s disease. Strains causing extraintestinal infections are included in the pathogroup of extraintestinal pathogenic E. coli (ExPEC) [4,13,14,37,45,65,66,81]. Phylogenetic analysis has shown that E. coli is composed of four main phylogenetic groups (A, B1, B2, and D). ExPEC mainly belong to phylogroups B2 and D, and AIEC to phylogroup B2; diarrheagenic E. coli normally belong to phylogroups A, B1, and D, and the non-pathogenic commensal strains to phylogroups A and B1 [15,18,45,61]. Pathogenic E. coli strains are detected and characterized using phenotypic (biotyping and serotyping) and genetic (PCR, MLST, and PFGE) methods. Identification of the pathogenic potential of a strain is of great importance in determining its O:H serotype and virulence genes. A limited number of E. coli reference laboratories have made available all O (O1 to O185) and H (H1 to H56) antisera necessary for complete serotyping, which is an essential basis for differentiating pathogenic strains and is often the starting point in their characterization. Furthermore, outbreaks can be preliminarily identified by the detection of an increased number of isolates within a particular serotype. Pulsed-field-gel-electrophoresis (PFGE) is a band-based molecular technique with high discriminatory power. It allows the identification of clusters of epidemiologically related isolates within O:H serotypes and is intended for tracing outbreaks in a limited time period. Multi-locus-sequence typing (MLST) is a sequence-based method targeting seven housekeeping genes (adk, fumC, gyrB, icd, mdh, purA, and recA). It has generally less discriminatory power than PFGE but is the most reliable method to determine the genetic relatedness of epidemiologically unrelated isolates. E. coli strains are assigned by MLST to different sequence types (STs), and within each ST

MORA ET AL.

diverse clusters can be observed by PFGE. As of August 2011, the E. coli MLST database consisted of 3942 isolates belonging to 2383 STs [4,9,15,18,37,54,60]. An E. coli genome contains between 4200 and 5500 genes, with <2000 genes conserved among all strains of the species (the core genome). The bacterium’s pan-genome (genetic repertoire of a given species) consists of almost 20,000 genes [50]. Continuous gene flux occurs during E. coli divergence, mainly as a result of horizontal gene transfers and deletions. This genetic plasticity accelerates the adaptation of E. coli to varied environments and lifestyles, as it allows multiple gene combinations that result in phenotypic diversification and the emergence of new hypervirulent (STEC and EAEC O104:H4-B1-ST678) and successful (ExPEC O25b:H4-B2-ST131) strains that combine both resistance and virulence genes, which in classical pathogenic E. coli strains traditionally have been mutually exclusive [14, 15,52,56,68,76]. STEC/VTEC: pathogenic potential, serotypes, prevalence in clinical samples, reservoirs, and routes of transmission. Shiga-toxin-producing E. coli (STEC), also known as verotoxin-producing E. coli (VTEC) or enterohemorrhagic E. coli (EHEC), are important emerging pathogens that cause food-borne infections and severe and potentially fatal illnesses in humans, such as HC and HUS [4,6,9,37,42,65,75]. STEC/VTEC strains produce two powerful cytotoxins, called Shiga toxins or verotoxins (Stx1/VT1 and Stx2/VT2), which are encoded in the genome of prophages. There are three subtypes of Stx1 (a, c, and d) and seven of Stx2 (a, b, c, d, e, f, and g). Stx2/VT2 is the most potent toxin, and producing strains are usually associated with more serious infections [37,59]. STEC have other, additional virulence factors, the most important being a protein called intimin, which is responsible for both the intimate adhesion of bacteria to the intestinal epithelium and the attaching and effacing lesion. Intimin is encoded by the gene eae, which is part of the chromosomal pathogenicity island LEE (locus for enterocyte effacement). Intimin binds to the cell receptor Tir and the complex is translocated by bacteria to the enterocyte via a type III secretion system (TTSS) [32]. Analysis of the variable C-terminal encoding sequence of eae defines at least 29 distinct intimin types (α1, α2, β1, β2, β3, γ1, θ1, κ, δ, ε1, ε2, ε3, ε4, ε5, ζ1, ζ3, η1, η2, ι1-A, ι1-B, ι1-C, ι2, λ, μ, υ, ο, π, ρ, σ) [12,33,55] that have been associated with tissue tropism. Severe diseases in humans are usually associated with eae-positive strains of enterohemorrhagic serotypes (O157:H7; O26:H11;


ESCHERICHIA COLI O104:H4

O103:H2; O111:H8, H– ; O145:H–). However, it has also been shown that intimin is not essential for the virulence of certain STEC strains. In fact, STEC O104:H21 and O113:H21 strains lacking eae were responsible for an outbreak and a cluster of three HUS cases in the USA and in Australia, respectively [4,9,41]. STEC strains that cause human infections belong to a large number of O:H serotypes (a total of 472 serotypes are listed on the authors’ website [http://www.usc.es/ecoli/ SEROTIPOSHUM.htm]. Most outbreaks of HC and HUS have been attributed to strains of the enterohemorrhagic serotype O157:H7. Given the importance of serotype O157:H7 in human disease, it is common to consider STEC serotypes in two major categories, O157 and non-O157 [4,8,37,42]. STEC strains have been classified into five seropathotypes (A to E), according to incidence and association with HUS and outbreaks. Seropathotype A includes strains of the highly virulent serotypes O157:H7 and O157:H–, involved in numerous outbreaks in many countries and frequently associated with HUS cases and HC. Seropathotype B comprises non-O157 serotypes causing occasional outbreaks but it is relatively common in sporadic cases associated with HUS and HC (O26:H11; O103:H2, O111:H8, H–, O121:H19, O145:H–).The non-O157 serotypes of seropathotype C are associated only with sporadic cases, including those of HUS and HC (O5:H–, O91:H21, O104:H21, O113:H21, O121:H–, O165:H25, and others). In seropathotype D are the serotypes associated with diarrhea without severe symptoms, i.e., not linked to outbreaks and HUS sporadic cases (O7:H4, O69:H11, O103:H25, O113:H4, O117:H7, O119:H25, O132:H–, O146:H21, O171:H2, O172:H–, O174:H8, and others). Seropathotype E is composed of many STEC serotypes of strains isolated from animals, foods, and environmental samples but not implicated in disease in humans [37,41]. The five pathogenic categories (seropathotypes A to E) of STEC will surely be expanded by a special category made up of serotype O104:H4, recently emerged in Germany, since never to date has a strain caused so many severe cases of HUS (852 only in Germany by July 26, 2011). Note that strain O104:H4, unlike most strains of categories A and B, does not have the LEE pathogenicity island containing the eae gene. The lack of an adhesin (intimin) encoded by eae is compensated by AAF/I (aggregative adherence fimbria I) and the enteroaggregative character of the strain [68,76]. According to published data, non-O157 STEC were first described as the possible cause of sporadic cases of HUS in 1975 in France, where the hospital historically reported the presence of STEC of serotype O103 in some patients. The

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first reported outbreak caused by serotype O145:H– occurred in 1984, but the vehicle of infection could not be determined. Also in 1975, STEC O157:H7 was first identified as a potential human pathogen in a Californian patient with bloody diarrhea; in 1982, it was associated with a food-based (beef) outbreak [42]. In 2007, the incidence of O157 and non-O157 infections in the USA was 1.19 and 0.59 per 100,000 habitants, respectively. In the European Union (EU), the incidence of STEC infections in 2006 and 2007 was 1.1 and 0.6 per 100,000 habitants, respectively. Over 70% of the cases of human STEC infections in the USA and 50% of those in the EU were attributed to serotype O157:H7. Therefore, among the STEC, E. coli serotype O157:H7 is the most notorious agent, involved in approximately 73,500 cases of infection in the USA each year. The Centers for Disease Control and Prevention (CDC) estimates that approximately 37,000 infections are annually due to non-O157, but with fewer cases of HUS than produced by O157:H7 [42]. Over 500 non-O157 serotypes have been involved in human infections as agents of diarrhea, HUS, and HC, although the true prevalence of nonO157 VTEC infections has been probably underestimated because the standard methods of clinical routine in many laboratories do not include the detection of this group. Recent recommendations from the CDC for the diagnosis of STEC are that laboratories perform both a culture for the specific detection of O157:H7 and an assay for Shiga toxins [35]. A review of laboratory practices in the USA up to the year 2000 reported that while 95% of 388 laboratories tested human stool for E. coli O157:H7 by culture, only 3% used a Shiga toxin immunoassay or a PCR test capable of identifying nonO157:H7 serotypes. Data from 2008 showed that 35% of laboratories participating in a proficiency testing program used a test for Shiga toxins. In Spain and many other European countries, the current situation is similar to that of the USA in the year 2000. During the period 2005-2009, 16,263 confirmed human STEC cases were registered in EU member states [23]. In 2009, a total of 3573 confirmed cases were reported from 18 member states (Austria, 91 cases; Belgium, 96; Denmark, 160; Estonia, 4; Finland, 29; France, 93; Germany, 878; Hungary, 1; Ireland, 237; Italy, 51; Luxembourg, 5; Malta, 8; Netherlands, 313; Slovakia, 14; Slovenia, 12; Spain, 14; Sweden, 228; United Kingdom, 1339). In addition, Iceland, Norway, and Switzerland reported 8, 108, and 42 such cases, respectively. In 2009, the EU notification rate was 0.75 per 100,000 population. Only two to six deaths due STEC infections were reported annually from 2006 to 2009 [23].


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Data from different countries indicate that sporadic cases of non-O157 STEC greatly outnumber outbreak cases. This is also true for STEC O157. From 1984 to 2009, 80 important outbreaks ascribed to non-O157, and from 1982 to 2006, 207 outbreaks ascribed to O157 were reported. Comparing data of outbreaks caused by O157:H7 and non-O157, nonO157 STEC strains are much less often associated with meat, water, and vegetables as outbreak vehicles and much more often attributed to person-person contact or unknown vehicles. These differences might be due, in part, to the better analytical methods available for STEC O157:H7. In addition, STEC O157:H7 is more virulent than some non-O157 strains and thus outbreaks are recognized and investigated in depth much faster [23,42]. Ruminants have been identified as the main reservoir for STEC O157:H7 and non-O157 [1,2,8,29,37]. STEC have been isolated from cattle, sheep, goats, and deer and occasionally from other wild and domestic animals; however, it is believed that in most cases STEC are transiently present in these animals, acquired through food or water contaminated by the feces of ruminants. In any case, these accidental hosts can be vehicles of infection for humans. Cattle is the most important source of human infections (beef, dairy products, bovine fecal contamination). Data on the prevalence of STEC O157 and non-O157 vary widely for both dairy cattle (0.4–74%) and meat cattle (2.1–70.1%) among different countries. Cattle often carry multiple serotypes, some of which do not seem to be of high risk for humans because they do not express any of the most important virulence factors. STEC are not considered pathogenic to ruminants, except when infections occur in young animals before weaning (involved in neonatal diarrhea) [8,23,37]. A study in Germany found a positive association between infections caused by different STEC serotypes and the density of cattle in an area. From data on over 3000 STEC cases, analyses indicated that risk for infection increased by 68% per 100 additional cattle/km2 [29]. A probable source of infection for cattle is food and drink contaminated with feces from infected animals. Studies of these microorganisms document that STEC O26 can survive for long periods in manure: up to three months in manure pits and liquid manure, and one year in fields fertilized with manure, depending on temperature and soil type. The persistence of these pathogens in manure-contaminated environments has health implications for their transmission, not only in farm production but also in other settings, such as county fairs and farm schools, in which children are exposed [23,37,42].

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Fecal material may contaminate meat during slaughter, may be washed into lakes or drinking water sources, or may be deposited in fruits and vegetables when manure is used for fertilization or sewage-contaminated water for irrigation. Humans, therefore, may become infected directly, through contact with an infected person or animal carrier, or indirectly, through the environment, food, drinking water, or surface water contaminated with fecal material containing STEC from human or animal origin [23,37,42].

Shiga-toxin-producing enteroaggregative Escherichia coli O104:H4. An emerging serotype On 26 May 2011, Germany reported a nationwide outbreak of HUS caused by STEC of serotype O104:H4. The German outbreak was declared officially over by the Robert Koch Institute (RKI) of Berlin on July 26, 2011, 3 weeks after the last date (July 4) of onset for a case with an epidemiological link [70]. Between May 1 and July 4, 2011, Germany reported 852 HUS cases and 3469 cases with diarrhea (and/or with HC), of which 50 patients died (including 32 HUS patients). According to the European Centre for Disease Prevention and Control (ECDC), 49 HUS cases and 76 cases with diarrhea were reported in 13 other European countries, including eight HUS cases from the French outbreak and two sporadic cases from Spain. Additional cases related to the outbreak were reported from the USA and Canada [23,27,70]. Several groups concluded that the outbreak was caused by a STEC strain belonging to serotype O104:H4, with virulence features common to the enteroaggregative E. coli (EAEC) pathotype [5,23,76]. This combination is very rare and was previously described in strains of serotype O111:H2 involved in a small outbreak of HUS in children in France [57]. In addition, the German outbreak strain was found to possess several virulence factors of extraintestinal pathogenic E. coli (ExPEC) and to have acquired resistance to numerous antibiotics, including third-generation cephalosporins, owing to several plasmid-borne genes encoding TEM-1 and CTXM-15 β-lactamases [20,23]. Table 1 shows the main virulence factors and characteristics of the O104:H4 outbreak strain. Serotype O104:H4 is very rare and has been diagnosed and reported in humans in a few cases only (Table 2); it has never been reported in animals and food. However, there are a few known animal strains of serogroup O104 with H antigens different from H4 (Table 3) [23].


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Table 1. Properties of the STEAEC O104:H4 outbreak strain Serotype O104:H4 Phylogroup B1 MLST sequence type ST678 (adk 6, fumC 6, gyrB 5, icd 136, mdh 9, purA 7, recA 7) Gene

Location

Virulence factor

Presence

negative

Virulence genes of STEC/VTEC/EHEC stx1/vtx1

Prophage

Shigatoxin 1

stx2a/vtx2a

Prophage

Shigatoxin 2 (variant 2a)

positive

eae

LEE pathogenicity island (chromosome)

Intimin (adhesin)

negative

E-hlyA

Plasmid

Enterohemolysin

negative

lpfAO26

Chromosome

Structural subunit of long polar fimbriae (LPF) of STEC O26

positive

saa

Plasmid

Saa (STEC autoagglutinating adhesin)

negative

ter

Chromosome

Tellurite resistance

positive

aggA

Plasmid (pAA)

Subunit of aggregative adherence fimbria AAF/I

positive

aggR

Plasmid (pAA)

Master regulator of a package of EAEC plasmid (pAA) virulence genes, including AAF/I adherence factor

positive

aatP

Plasmid (pAA)

ABC protein responsible for transporting the dispersin protein out of the outer membrane

positive

aap

Plasmid (pAA)

Secreted protein named dispersin, and is responsible for dispersing EAEC across the intestinal mucosa

positive

sepA

Plasmid (pAA)

SepA. Shigella extracellular protein. May induce mucosal atrophy and tissue inflammation in S. flexneri

positive

sigA

Chromosome

SigA protein, an IgA protease-like homologue

positive

pic

Chromosome

Pic protein with mucinase activity involved in the intestinal colonization

positive

astA

Plasmid

EAEC heat-stable enterotoxin 1 (EAST1)

negative

irp2 and fyuAa

Chromosome

Component of iron uptake system (siderophore yersiniabactin) on high pathogenecity island (HPI)

positive

iha

Chromosome

IrgA homologue adhesin (Iha)

positive

aer

Chromosome or plasmid

Aerobactin siderophore

positive

hlyA

Chromosome or plasmid

Alpha-hemolysin

negative

Virulence genes of EAEC

Virulence genes of ExPEC

Microbiological properties: Lactose fermentation (+), sorbitol fermentation (+) and β-glucuronidase (+). Indole (+), citrate (–) and H2S production (–). Excellent growth in cefixime telurite sorbitol MacConkey (CT-SMAC) agar. Antibiotic resistance: TEM-1 and CTX-M-15 β-lactamases Resistance to: ampicillin, amoxicillin/clavulamic acid, piperacillin/sulbactam, piperacillin/tazobactam, cefuroxim, cefuroxin-axetil, cefoxitin, cefotaxim, ceftazidim, cefpodoxim, streptomycin, nalidixic acid, tetracylin, and trimethoprim/sulfamethoxazol. Sensitive to: imipenem, meropenem, amikacin, kanamycin, gentamicin, tobramycin, ciprofloxacin, norfloxacin, nitrofurantoin, chloramphenicol, and fosfomycin. a

The irp2 and fyuA genes were detected in more of 90% of EAEC and 80% of septicemic ExPEC. Information obtained from: Robert Koch Institut [70], National Reference Laboratory for E. coli (BfR), Bielaszewska et al. [5] and Rasko et al. [68].


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Table 2. Overview of reported human STEC/VTEC and/or EAEC O104:H4 strains Year

Shiga-toxins

HUS

Reference

STEC/VTEC and EAEC strains Germany (2 cases)

2001

stx2a

yes

[46]

Georgia (2 cases)

2009

stx2a

yes

[76]

Italy

2009

stx2a

yes

[85]

Finland

2010

stx2a

no

[76]

Germany (outbreak)

2011

stx2a

yes

[5,76]

France (outbreak)

2011

stx2a

yes

[34,76]

STEC/VTEC confirmed and EAEC strains? (unknown) France

2004

unknown

unknown [76]

2005

stx1and stx2

STEC/VTEC strains Korea

yes

[3,84]

Central African Republic 1995 or 1996 negative

no

[5]

Spain (3 cases)

1996

negative

no

This study

Denmark

2000

negative

no

[76]

Mali (6 cases)

2009

negative

no

[76]

EAEC strains

EAEC is a pathotype of diarrheagenic E. coli defined as E. coli that do not secrete the heat-stable (ST) or heat-labile (LT) toxins of ETEC, and with a characteristic aggregative pattern (AA) of adherence to HEp2-cells in culture. This property is usually due to the presence of AAF/I to AAF/IV, whose expression is regulated by the aggR gene, located on the large EAEC virulence plasmid pAA [18,66,76]. EAEC infections are usually associated with prolonged watery diarrhea, particularly among children and in travelers to developing countries [48,61,66]. However, EAEC is also a significant cause of diarrhea in Europe, including Spain [12,18]. Table 3. STEC/VTEC O104 strains of animal and food origin Serotype

Origin

Country

Year

Reference

O104:H21

Cattle

Spain

1993-1997

[10]

O104:H12

Cattle

Austria

2009

[23]

O104:H21

Cattle

Austria

2009

[23]

O104

Ground meat

Germany

2005

[23]

O104:H7

Ovine

Spain

1997

O104:H7

Lamb meat

India

2001-2002

[23]

O104:H7

Calf

Argentina

1999/2000

[23]

O104

Bovine carcasses USA

1999

[23]

New Zealand 1998

[23]

O104:H7/HNM Ovine meat

[7]

Source: Technical report of ECDC and EFSA, June 2011, completed with data from LREC.

The fact that EAEC has been rarely identified in animals suggests that they are not zoonotic but rather exclusively human pathogens. But what is the origin of the outbreak strain of serotype O104:H4? Mellmann et al. [47] characterized the complete genome of the outbreak isolate LB226692 and a historic STEC/EAEC O104:H4 HUS isolate from 2001 (01-09591) by a rapid next-generation sequencing technology. Phylogenetic analyses of 1144 core E. coli genes indicated that the HUS STEC/EAEC strains are closely related to the previously published sequence of the EAEC strain 55989 isolated in the late 1990s in Africa, but only distantly related to common EHEC serotypes. Despite this close relationship, the outbreak strain differs from the 2001 strain in plasmid content, fimbrial genes, and antibiotic resistance genes. Mellmann et al. [47] proposed a model in which EAEC 55989 and EHEC O104:H4 strains evolved from a common EHEC O104:H4 progenitor; they suggested that, by stepwise gain and loss of chromosomal and plasmid-encoded virulence factors, a highly pathogenic hybrid of EAEC and EHEC emerged as the current outbreak clone (Fig. 1). Due to its hybrid pathogenicity characteristics, Brzuszkiewicz et al. [16] designated the new pathotype â&#x20AC;&#x153;Entero-Aggregative-Hemorrhagic E. coli (EAHEC).â&#x20AC;? Rasko et al. [68] used third-generation, single-molecule, real-time DNA sequencing to determine the complete genome sequence of the German outbreak strain, as well as the genome sequences of seven diarrhea-associated EAEC of serotype O104:H4 strains from Africa (isolated in Mali in 2009) and of four EAEC reference strains belonging to other serotypes. Genome-wide comparisons were performed on the basis of these EAEC genomes as well as those of 40 previously sequenced STEC, ETEC, EPEC, and ExPEC isolates belonging to different serotypes. The EAEC O104:H4 strains were closely related and formed a distinct clade among E. coli and enteroaggregative E. coli strains. However, the genome of the German outbreak strain could be distinguished from that of the other O104:H4 strains because it contains a prophage-encoding Shiga toxin 2 and a distinct set of additional virulence and antibiotic-resistance factors. The findings of Rasko et al. [68] suggest that horizontal genetic exchange allowed the emergence of the highly virulent Shiga-toxin-producing enteroaggregative E. coli (STEAEC) O104:H4 strain that caused the German outbreak (Fig. 1). More broadly, these findings highlight the way in which the plasticity of bacterial genomes facilitates the emergence of new pathogens [50]. The main lesson from this outbreak is that we should be aware of the capacity of E. coli species to accommodate new combinations of genes,


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A

Fig. 1. Evolutionary models of the origin of the German STEAEC O104:H4 outbreak strain. Top (A): common ancestor model and linear ancestry model proposed by Mellmann et al. [47]. Bottom (B): model proposed by Rasko et al. [68], similar to that proposed by Rohde et al. [71] and Brzuszkiewicz et al. [16]. These studies revealed that the outbreak strain belonged to an EAEC lineage that has acquired genes encoding the Stx2a toxin and antibiotic resistance.

Int. Microbiol.

B


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leading to the emergence of highly aggressive strains. Furthermore, antibiotic pressure in human and veterinary medicine should be kept as low as possible, as it will select these strains once they become resistant [20]. Epidemiologic investigations initially supported the hypothesis that the outbreaks in Germany [27] and France [34] were linked and that they were due to fenugreek seeds imported from Egypt [26]. However, there has been no isolation of the causative strain O104:H4 from any of the fenugreek seeds analyzed. In the scientific literature, associations between outbreaks of STEC infection and both vegetable products, particularly contaminated sprouting seeds, and green leafy salad vegetables are increasingly recognized [25,26,28,79,82]. The largest STEC O157:H7 outbreak to date was in 1996 in Sakai City (Osaka, Japan) and was linked to the consumption of white-radish sprouts [49]. It remains unclear why the German STEAEC outbreak strain was so virulent. As noted, a novel suite of adhesion factors might provide an explanation. Alternatively, perhaps this strain is able to exploit more efficient mechanisms for toxin release. It is worth remembering that strains of EAEC have caused large sprout-associated outbreaks before, including one outbreak, caused by serotype ONT:H10, that affected more than 2000 people in Japan in 1993 [39]. Thus, there is clearly an urgent need to understand how the German outbreak strain and other strains of EAEC adhere to and colonize seeds and seedlings. Also, outbreaks of Salmonella infection associated with the consumption of raw seed sprouts are not rare. Thus, sprouts must be acknowledged as high-risk foods in which contamination usually starts with contaminated seeds, as the high humidity required to trigger sprouting provides ideal conditions for bacterial multiplication.

Table 4. STEC/VTEC prevalence in patients from the Lucus Augusti Hospital of Lugo No. of stool samples from adult and children with diarrhea STEC/VTEC

Year

Total assayed

O157:H7 isolated

Non-O157 isolated

Total Detected

1992–1999

5054

24

0.5%

87

1.7%

126

2.5%

2003–2005

3970

12

0.3%

75

1.9%

144

3.6%

2006–2010

4692

27

0.6%

85

1.8%

119

2.5%

May–July 2011 246

0

0%

4

1.6%

4

1.6%

TOTAL

63

0.5%

251

1.8%

393

2.8%

13,962

Results obtained from 1992 to 1999 are already published data [9], whereas results from 2003 to 2011 are unpublished data.

From 2005 to 2011, the LREC-USC also processed, in collaboration with the Microbiology Service of University Hospital Complex of Santiago de Compostela (CHUS), a total of 1479 stool cultures for the presence of STEC O157:H7 and non-O157 (Table 5). Samples were isolated from inpatients and outpatients of all ages, most of whom had bloody diarrhea. STEC were detected in 32 (2.2%) of the stool cultures tested. In total, 13 (0.9%) cases of infection were associated with STEC O157:H7 and 16 (1.1%) with non-O157. Serotype O146:H21 was the most frequently isolated among the non-O157 STEC (unpublished data). Table 5. STEC/VTEC prevalence in patients from the University Hospital Complex of Santiago de Compostela (CHUS)* No. of stool samples STEC/VTEC

STEC/VTEC in Spain STEC in patients with diarrhea and HC. From 1992 to 2011, the LREC-USC, in collaboration with the Microbiology Unit of Hospital Complex Xeral-Calde of Lugo (Lucus Augusti Hospital), processed 13,962 stool cultures for the presence of STEC O157:H7 and non-O157 (Table 4). Samples were isolated from inpatients and outpatients of all ages who mostly had diarrhea or gastroenteritis. STEC were detected in 393 (2.8%) of the stool cultures tested. In total, STEC O157:H7 accounted for 63 (0.5%) cases of infection and non-O157 STEC for 251 (1.8%). Serotype O26:H11 was the most frequently detected among the nonO157 VTEC strains ([9] and unpublished data).

Year

Total assayed

O157:H7 isolated

Non-O157 isolated

Total detected

2005

93

3

3.2%

1

1.1%

4

4.3%

2006

114

1

0.9%

0

0%

1

0.9%

2007

283

3

1.1%

6

2.1%

9

3.2%

2008

329

3

0.9%

3

0.9%

6

1.8%

2009

233

0

0%

3

1.3%

4

1.7%

2010

276

3

1.1%

2

0.7%

6

2.2%

2011

151

0

0%

1

0.6%

2

1.3%

2005–2011

1479

13 0.9%

16

1.1%

32

2.2%

*Unpublished data.


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Table 6. STEC/VTEC serotypes most frequently detected among human strains isolated in Lugo (2003–2011)* Serotype

Phylogenetic group

ST

Seropathotype

Intimin type

O5:H–

A

ST342

C

β1

O26:H11

B1

ST21

B

β1

O103:H2

B1

ST17

B

ε1

O111:H8

B1

ST16

B

θ

O113:H21

B1

ST56

C

O118:H16

B1

ST21

C

β1

O145:H–

D

ST32

B

γ1

O146:H21

B1

ST442

D

O157:H7

D

ST11

A

γ1

*

Unpublished data.

among strains isolated from humans in Spain, together with the phylogenetic group, ST, seropathotype, and intimin-type ([9] and unpublished data). Figure 2 shows a dendrogram of the XbaI macrorestric-

Int. Microbiol.

None of the STEC strains isolated in Galicia from human patients between 1992 and 2011 belonged to serotype O104:H4, the serotype implicated in the German outbreak. Table 6 shows the most frequent STEC serotypes found

Fig. 2. Dendrogram of the XbaI macrorestriction profiles of 21 STEC strains of serotype O157:H7 isolated in Galicia, northwestern Spain. Strain code, stx1, stx2, year of isolation and origin, are shown on the right side of the dendrogram.*O157-809 strain isolated from a patient with HC, O157-816 strain isolated from a sample of frozen beef consumed by the patient, and O157-810 strain isolated from an asymptomatic relative . **O157-718, O157-720 and O157722 strains isolated from two patients and an asymptomatic carrier of the same family, respectively. Unpublished data.


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tion profiles of 20 STEC strains of serotype O157:H7 isolated from 2003 to 2006 in various hospitals of Galicia and of one O157:H7 strain isolated from beef consumed by a patient. All 21 belonged to phagetype 8 and showed high homogeneity, with 15 strains included in a cluster of similarity >85%. Strain O157-809 was isolated from a patient with HC, strain O157-816 from a sample of beef consumed by the patient, and strain O157-810 from an asymptomatic relative. Strains O157-718, O157-720, and O157-722 were isolated from two patients and an asymptomatic carrier of the same family, thus representing a small outbreak ([9] and unpublished data). STEC is the third most frequently identified enteric pathogen in stool cultures at the Lucus Augusti Hospital, after Salmonella and Campylobacter, thus accounting for a significant number of infections in our area [9,12]. Data from Galicia suggest that, per year in Spain, STEC O157:H7 is responsible for more than 500 cases of infection, and non-O157 for more than 2000. Therefore, STEC likely produces 5.0 to 6.0 cases per 100,000 habitants. STEC in beef. In recent years, we have detected a significant decrease in the prevalence of STEC in beef sold in the city of Lugo. Especially important is the absence of positivity for STEC O157:H7 in the period 2005â&#x20AC;&#x201C;2009 (Fig. 3). STEC O157:H7 was detected in eight cases (0.6%), and nonO157 in 146 (10%), among 1445 samples analyzed between the years 1995 and 2009. None of the STEC strains isolated from beef in Lugo belonged to serotype O104:H4, implicated in the German outbreak. However, the level of samples

Fig. 3. Prevalence of STEC in beef sampled in the city of Lugo.

contaminated with non-O157 VTEC is still too high, pointing out the need to improve hygiene, control, and surveillance throughout the food chain ([53] and unpublished data). STEC in chicken and pork. We have also conducted studies on the STEC prevalence in chicken and pork meat. During 2009 and 2010, 200 samples of chicken breast were analyzed. All samples were negative for STEC O157 but two (1%) were positive for non-O157. Among the 110 samples of pork analyzed in 2011, none was positive for STEC O157 but six (5.5%) were positive for non-O157. Although chicken showed a lower prevalence of STEC than beef and pork, it had higher levels of E. coli contamination since only 45% of chicken samples had <10 cfu/g compared to 65% of beef and 71% of pork samples. Clearly, also in these meats it is necessary to decrease the levels of E. coli contamination (unpublished data). STEC in dairy products. Rey et al. [69] examined 502 dairy products from 64 different ovine and caprine flocks and from six dairy plants in Extremadura. Sampling was conducted monthly between March 2003 and June 2004 and yielded 360 samples from unpasteurized milk obtained from the bulk tank, 103 samples from fresh cheese curds, and 39 from cheese. STEC strains were detected in 39 (11%) of the samples from the bulk tank, 4 (4%) of those from fresh cheese curds, and 2 (5%) of those from cheese; O157:H7 serotype was isolated from one (0.3%) bulk tank sample. A total of nine STEC strains (O27:H18, O45:H38, O76:H19, O91:H28,


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O157:H7, ONT:H7, ONT:H9 and ONT:H21) were identified in this study. In another study, Caro et al. [17] characterized 13 STEC strains isolated from sheep dairy products in Castilla y León. Eight strains isolated from milk belonged to serotype O157:H7. Three STEC strains (two of serogroup O14 and one ONT) were detected in two samples (2.4%) of “Castellano” cheese, one with a 2.5- and the other one with a 12-month ripening period. STEC in vegetables. In 2008, 100 lettuces from various commercial establishments in the city of Lugo were analyzed by the LREC-USC for the presence of STEC. An acceptable microbiological quality was determined, since 99% of the lettuces tested had <10 cfu E. coli/g. In addition, the 100 lettuces were negative for the presence of STEC and other types of diarrheagenic E. coli (unpublished data). The so-called cucumber crisis, 2011. On 31 May 2011, our LREC-USC received samples from the organic farm involved in the so-called cucumber crisis and suspected by the German Health authorities. The samples submitted by the Junta de Andalucía consisted of 70 cucumbers organically produced; 13 plates of coliform chromogenic medium (37°C/24 h) obtained by filtration of 100 ml of water for irrigation; and four plates of tryptone bile X-glucuronide medi-

131

um (TBX) obtained from two samples of soil (incubation in duplicate at 37 and 44°C, 24 h, respectively) previously enriched in Mossel EE broth (37°C, 24 h). The type of analysis requested for all samples was the detection and characterization of STEC and EAEC strains. The 17 plates (13 from water samples and four from soils) were sub-plated onto lactose-MacConkey (LMAC) agar and cefixime tellurite sorbitol-MacConkey (CT-SMAC) agar and then incubated at 37°C for 24 h. The 70 cucumbers were analyzed by dividing them into seven pools of ten units each. Additionally, three units of three random pools were analyzed individually. Thus, 10 samples were globally tested (seven pools and three units). Enrichment cultures were established by adding a 25-g test portion of cucumber skin aseptically cut with individual scalpel blades to 225 ml of buffered peptone water (BPW), followed by incubation for 18–24 h at 37°C. The cultures of LMAC, CT-SMAC, and BPW were then analyzed by conventional PCR, aimed at the detection of the stx1 and stx2 genes, typical of STEC, and of pAA, typical of EAEC. All samples were negative by PCR for the three genes tested; therefore, STEC and EAEC were not detected in any of the water, soil, or cucumber samples analyzed. The primers and conditions used are described in the section “Analytical methods for STEC detection in foods.” We also analyzed the most probable number of E. coli per gram of the cucumber samples. In all cases, counts were <10 cfu

Table 7. STEC/VTEC prevalence in vegetables sampled between June and July of 2011* Most Probable Number of Escherichia coli Vegetable

No. samples

<10

10–99

>99

STEC/VTEC

EAEC, ETEC, tEPEC and EIEC

Cucumbers

32

32 (100%)

0

0

0

0

Tomatoes

36

36 (100%)

0

0

0

0

Lettuces

54

50 (93%)

4 (7.4%)

0

1 (1.9%)

0

Bean sprouts

6

6 (100%)

0

0

0

0

Endives

2

2 (100%)

0

0

0

0

Broccoli

7

7 (100%)

0

0

0

0

Leeks

2

2 (100%)

0

0

0

0

Peppers

6

6 (100%)

0

0

0

0

Carrots

1

1 (100%)

0

0

0

0

Onions

1

1 (100%)

0

0

0

0

Packaged salads

53

52 (98%)

1 (1.9%)

0

0

0

TOTAL

200

195 (98%)

5 (2.5%)

0

1 (0.5%)

0

*Unpublished data.


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Fig. 4. Comparison of STEC strains of serotype O146:H21. Dendrogram of the XbaI macrorestriction profiles. Strain code, serotype, origin, and virulence genes are shown at the right side of the dendrogram. Unpublished data.

per gram of sample, which implied that no E. coli colony grew on the Petrifilm Select plates (unpublished data). The analysis report for the samples was closed on June 2, 2011. Vegetable sampling, 2011. As a consequence of the German outbreak, we decided to conduct a large sampling to determine the presence of STEC, EAEC, and other types of diarreagenic E. coli in the vegetables sold in Spain. Between June and July of 2011, 200 vegetables from different geographic origins were analyzed at the LREC-USC (Table 7) (unpublished data). The 200 vegetable samples were negative for the virulent serotype O104:H4 and only one sample (0.6%) was positive for a STEC strain of serotype O146:H21 (stx1 stx2), considered of low virulence (category D). Despite the positive case, the hygienic and sanitary quality of the vegetables offered for sale in the city of Lugo proved to be quite good, since in 195 (98%) of the samples <10 cfu of E. coli per gram were detected. Of concern is the fact that a sample of packaged salad showed a most probable number of E. coli per gram of 10â&#x20AC;&#x201C;99, since this product is sold ready to eat. Special vigilance should be paid to food consumed directly without any previous care. We believe that the 200 samples analyzed were representative of the Spanish situation since 116 of 200 came from superstore centers that distribute throughout the country. These 116 samples were negative for STEC.

The XbaI-PFGE macrorestriction profile of the STEC O146:H21 strain isolated from lettuce was compared with the profiles of 11 STEC strains belonging to the same serotype and isolated from patients (Fig. 4) (unpublished data). The vegetable strain showed a cluster of 87.5% identity with a human strain isolated in 2004. Although serotype O146:H21 is currently included in category D, based on a lack of association to date with outbreaks or severe cases (HUS), we highly believe it should be monitored because some of the patients from whom we isolated O146:H21 developed HC. In addition, strains of serotype O146:H21 have been isolated in Spain from beef, cattle, sheep, goats, deer, wild boars, and foxes. STEC in cattle. In an analysis of the role of cattle as a reservoir of STEC (1993â&#x20AC;&#x201C;1995), we found that one third of the calves and cows of Galicia were carriers. Furthermore, 12% of the calves and 22% of the farms sampled were positive for highly virulent STEC serotype O157:H7. In 1998, we conducted a study in Navarra in two slaughterhouses and five feedlots. The number of STEC O157:H7 carriers detected was very high: 10% at slaughterhouse A, 19% at slaughterhouse B, 23% at feedlot 1, 22% at feedlot 2, 8% at feedlot 3, but 0% in feedlots 4 and 5. These data obtained in Spain are in agreement with those reported in other countries, and confirm that around 10% of cattle are colonized by STEC O157:H7 [8,10,11,44].


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Table 8. STEC/VTEC serotypes most frequently found in Spain Origin

Year, locality [Reference]

Number of strains

eae+ strains

Serotypes most frequently found (number of strains)

Human

1992–1999 Lugo [9]

126

56%

O26:H11, H– (14); O91:H21, H– (4); O111:H8, H– (5); O113:H21 (3); O145:H8, H– (3); O146:H21 (3); O157:H7 (24)

Human

2003–2011 Lugo (UD)a

213

68%

O5:H– (3); O26:H11, H– (43); O103:H2 (7); O111:H8, H– (13); O113:H21 (4); O118:H16 (6); O145:H– (4); O146:H21 (13); O157:H7 (41)

Bovine

1993–1999 Galicia [10]

514

29%

O2:H27 (7); O2:H29 (5); O4:H4 (11); O8:H2 (9); O20:H19 (18); O22:H8 (25); O26:H11, H– (26); O64:H– (4); O77:H41 (21); O82:H8 (7); O91:H21 (8); O103:H2, H– (8); O105:H18 (15); O113:H4 (8); O113:H21 (33); O116:H21, H– (10); O118:H16, H– (4); O126:H20 (4); O128:H– (4); O141:H8 (4); O156:H– (9); O157:H7 (82); O162:H21 (4); O171:H2 (20); O171:H25 (4); O174:H– (5); O174:H2 (8); O174:H21 (6); O177:H11, H– (10); ONT:H19 (16)

Ovine

1997 Extremadura [7]

384

6%

O5:H– (19); O6:H10 (25); O6:H– (3); O52:H45 (3); O91:H– (64); O104:H7 (9); O110:H– (7); O112:H– (7); O117:H– (16); O123:H– (3); O128:H– (46); O128:H2 (14); O136:H20 (11); O146:H8 (14); O146:H21 (27); O156:H– (13); O157:H7 (5); O166:H28 (11); O176:H4 (9); ONT:H21 (17)

Ovine

Madrid [62]

63

3%

O5:H– (13); O6:H10 (3); O26:H11 (2); O91:H– (6); O128:H– (6); O146:H21 (8); O166:H28 (4)

Caprine

2003 Murcia [19]

106

0%

O5:H– (7); O76:H19 (30); O91:H14 (3); O126:H8 (6), O128:H2,H– (4); O146:H21,H– (10); O166:H28 (3); ONT:H4 (3); ONT:H21 (18)

Caprine

Madrid [62]

41

2%

O5:H– (3); O81:H21, H– (11); O128:H2, H– (2); O146:H21 (2); O166:H28 (8)

Wild ruminants

2004–2005 Extremadura [72]

65

0%

O2 (7); O8 (5); O128 (5); O146 (25); O166 (4); O174 (6)

Wild boars

2007–2008 Extremadura [74]

17

35%

O6:H10 (1); O23:H21 (2); O109:H– (1); O127:H2 (1); O142 (1); O146:H21 (1); O157:H7 (5); O157:H21 (2); ONT (3)

Beef

1995–2003 Lugo [53]

96

26%

O1:H10 (2); O8:H21 (4); O22:H8 (4); O26:H11, H– (4); O64:H5 (3); O75:H8 (2); O77:H41 (2); O103:H2, H– (3); O111:H– (2); O113:H21 (2); O157:H7 (8)

Beef

2005–2009 Lugo (UD)

53

30%

O5:H– (2); O26:H11, H– (9); O6:H10 (2); O146:H21 (5); O174:H21 (2)

Milk

2003–2004 Extremadura [69]

9

11%

Ovine: O45:H38 (1); ONT:H7 (2); ONT:H9 (1) Caprine: O27:H18 (1); O76:H19 (1); O91:H28 (1); O157:H7 (1); ONT:H21 (1)

Ovine dairy products

1999 Castilla y León [17]

13

61%

Milk: O71 (2), O157:H7 (8) Cheese: O14 (2), ONT (2)

Vegetables

2011. This study

1

0%

O146:H21 (1)

a

UD: unpublished data.

The serotypes and virulence genes of 514 bovine STEC strains isolated in Spain were also determined. Although they belonged to a wide number of serotypes (66 serogroups and 113 serotypes), 52% of the strains belonged to only 10 serotypes (O4:H4, O20:H19, O22:H8, O26:H11, O77:H41, O105:H18, O113:H21, O157:H7, O171:H2 and ONT:H19). Moreover, the seropathotypes of many bovine strains were

those previously found among STEC causing infections in humans (Table 8) [4,9,10,40,44,83]. None of the STEC bovine strains belonged to serotype O104:H4; however, we did find two O104:H21 stx1 stx2 ST672 strains (Fig. 5). STEC in sheep. In 1997, we conducted a study in collaboration with the Faculty of Veterinary Sciences of Cáceres.


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Fig. 5. Dendrogram of the XbaI macrorestriction profiles of 12 animal STEC strains of serotypes O104:H7 and O104:H21 isolated in Spain. Strain code, serotype, ST, origin, and virulence genes are shown on the right side of the dendrogram. Unpublished data.º

An analysis of 1300 samples from 93 farms in Extremadura showed that 0.4% of the lambs were colonized by STEC O157:H7 and 36% by non-O157 [7]. Among 384 ovine strains, 35 serogroups and 64 serotypes were established, with 72% of the strains belonging to one of the following 12 serotypes: O5:H–, O6:H10, O91:H–, O117:H–, O128:H–, O136:H20, O146:H8, O146:H21, O156:H–, O166:H28, and ONT:H21. The STEC seropathotypes of ovine strains differed from those of bovine strains, but many had also been detected in STEC strains of human origin (Table 8). Importantly, the eae gene was present in only 6% of the ovine strains, compared to 29% of those from cattle and 56% of those from humans. Although none of the ovine STEC strains belonged to serotype O104:H4, ten strains with serotype O104:H7 stx1 (mostly ST1817) were identified (Fig. 5). STEC in goats. In 2003, we conducted a study in collaboration with the Faculty of Veterinary Sciences of Madrid and Murcia [19]. Fecal samples from 222 healthy dairy goats (adults and kids) on 12 farms in Spain were screened for the presence of STEC. Non-O157 STEC strains were isolated in 48% of the animals, more frequently from adults and replacement animals than from kids. STEC O157 was not detected. Among 106 STEC caprine strains, 25 serotypes were determined, with the most common being serotypes O5:H–,

O76:H19, O126:H8, O146:H21, ONT:H–, and ONT:H21. None of the 106 strains carried eae. However, 16% of the caprine STEC strains belonged to serotypes involved in HUS (Table 8). Serotype O104:H4 was not identified among any of the caprine STEC strains. A longitudinal study was conducted on two dairy farms to investigate the pattern of shedding of STEC in goat herds in the Murcia region [63]. Fecal samples were taken from 20 goat kids once weekly during the first 4 weeks of life and then once every month for the next 5 months of life, and from 18 replacement animals and 15 adults once every month for 12 months. The proportion of samples containing STEC was higher for replacement animals and adults (86 and 79%, respectively) than for kids (25%). About 90% of the STEC colonies isolated from healthy goats belonged to five serogroups (O33, O76, O126, O146, and O166) but the most frequent serogroups of these isolates, except one, were different in the two herds studied. STEC O157:H7 was found in three kids on only one occasion. None of the STEC isolates, except the three O157:H7 isolates, was eae-positive. The patterns of STEC shedding in goat kids were variable whereas most of the replacement animals and adults were persistent STEC shedders. The results showed that isolates of STEC O33, O76, O126, O146, and O166 are adapted for colonizing the goat intestine but infection with STEC O157:H7 in goats seems to be transient [63].


ESCHERICHIA COLI O104:H4

STEC in wild animals. In the study of Sánchez et al. [72] fecal samples were collected from 243 wild ruminants, including Cervus elaphus, Capreolus capreolus, Dama dama, and Ovis musimon, and examined for STEC using both phenotypic (Vero cells) and genotypic (PCR and PFGE) methods. Fecal samples were collected from animals killed by hunters during 2004 and 2005 in the Extremadura. STEC were isolated from 58 (24%) of the samples and a total of 65 isolates were characterized. The ehxA gene was detected in 37 (57%) of the isolates but none contained the eae gene. The isolates comprised 12 O serogroups, although 80% were restricted to O2, O8, O128, O146, O166, and O174. The most commonly isolated STEC bacteria, from the O146 serogroup, exhibited a high degree of polymorphism as indicated by PFGE. STEC isolates of serogroups O20, O25, O166, O171, O174, and O176 had not previously been found in wild ruminants. This was the first study to confirm that wild ruminants in Spain are a reservoir of STEC and are thus a potential source of human infection [72]. In another study of Sánchez et al. [74], fecal samples from 212 wild boars were collected (Extremadura, Spain, 2007 and 2008) and examined. STEC O157:H7 and non-O157 were isolated from 7 (3%) and 11 (5%) animals, respectively. E. coli O157:H7 isolates belonged to phage types associated with severe human illness: PT14, PT34, and PT54. Indistinguishable PFGE types were found in E. coli O157:H7 isolates recovered from a wild boar and from a human patient with diarrhea living in the same geographic area. Recently, in the LREC-USC, we studied the presence of STEC in populations of deer, boar, and fox (Galicia, 2009–2010). Of the 179 deer that were sampled, STEC were isolated from 97 (54%) stool samples, while 25 (9.5%) of the 262 boars tested were STEC-positive. Among the 260 fecal samples from foxes, STEC were isolated from six animals (2.3%) (unpublished data). None of the STEC strains isolated from Galician wildlife belonged to serotype O104:H4, nor had the STEC been isolated in previous studies carried out in collaboration with the Faculty of Veterinary Science of Cáceres [72,74]. STEC in aquatic environments. The study of GarcíaAljaro et al. [31] included a phenotypic and genotypic characterization of 144 STEC strains isolated from urban sewage and animal wastewaters in Barcelona, using a stx2-specific DNA colony hybridization method. The STEC strains isolated belonged to 34 different serotypes. Only one O157:H7 strain was positive for the intimin gene eae. Forty-one different seropathotypes were determined. On the basis of the

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occurrence of virulence genes, most non-O157 STEC strains are assumed to be low-virulence serotypes. Shiga-toxin phages. Shiga-toxin phages were detected by TaqMan qPCR in all the beef samples and in 69% of the salad samples obtained from the city of Barcelona by Imamovic and Muniesa [38]. Stx phages from the samples were propagated in E. coli C600, E. coli O157:H7, and Shigella strains and further quantified. The results showed that 50% of the samples carried infectious Stx phages, isolated from plaques generated by lysis. However, despite the apparent abundance of Stx phages in these samples, they showed acceptable microbiological levels for human consumption based on European and US regulations. The origin of the Stx phages found in the food samples could not be determined. However, high densities of Stx phages have been detected in human and animal environments, pointing to an environmental origin. The significance of this study is that infectious free Stx phages are present in commercial food samples. The presence of Stx phages in food can cause stx transduction to the bacterial flora present in the matrices, generating new STEC strains in the samples, perhaps during storage. Similarly, the ingestion of free Stx phages present in food can lead to the conversion of commensal gut bacteria. However there are no reports indicating that stx transduction in food is of relevant concern. Phage typing of STEC O157:H7 strains. Phage typing was used for the epidemiological subtyping of a collection of STEC O157:H7 strains isolated in Spain between 1980 and 1999 [51]. Phage typing was performed using the method of Khakria et al. [43] at the National Center for Microbiology (Madrid, Spain), with the phages provided by The National Laboratory for Enteric Pathogens, Laboratory for Disease Control, Ottawa, Ontario, Canada. The 16 different phages used were capable of identifying 88 phage types. Phage typing distinguished 18 phage types among 171 strains isolated from different sources (67 human, 82 bovine, 12 ovine, and 10 beefproduct samples). However, five phage types, phage type 2 (PT2; 42 strains), PT8 (33 strains), PT14 (14 strains), PT21/28 (11 strains), and PT54 (16 strains), accounted for 68% of the study isolates. PT2 and PT8 were the most frequently occurring among human (51%) and bovine (46%) strains. Interestingly, there was a significant association between PT2 and PT14 and the presence of acute pathologies [51]. In another study [73], 46 E. coli O157:H7 isolates obtained from the feces of different healthy ruminants (sheep, beef cattle, and red deer) and from unpasteurized goat milk over a period of 11 years (1997–2008) were characterized. All of them


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Table 9. Outbreaks of STEC/VTEC in Spain Place

Year

Type

Seropathotype

No. Afected

Ibiza

1986

British tourists

O157:H7 stx2

Balearic Islands

1994

British tourists

O157:H7 stx2 PT2

Álava

1995

Children in countryside

O111:H- stx1

13

Fuerteventura

1997

European tourists in four hotels

O157:H7 stx2 PT2

14 (3 with HUS)

Guipúzcoa

1999

Children in nursery

O157:H7

8 (1 with HUS + 6 asymptomatic)

Guipúzcoa

1999

O157:H7

2 (1 with HUS + 2 asymptomatic)

Barcelona

2000

Children from three schools

O157:H7 stx2 PT2

175 (6 with HUS)

Lugo

2003

Family outbreak

O157:H7 stx1 stx2 PT8

3

Lugo

2003

Family outbreak

O26:H11 vt

4

Cáceres

2007

O157:H7 stx2 PT14

3

3 (+ 3 asymptomatic)

http://www.usc.es/ecoli/BROTES.html

originated from the Extremadura. An atypical E. coli O157:H7 strain (sorbitol-fermenting and β-glucuronidase positive) originating from deer feces was detected. Genes encoding Shiga toxins were present in 69.6% of the isolates, all of which carried only the stx2 gene. The isolates were from nine different phage types, although 67.4% were restricted to only three: PT14, PT34, and PT54. PT54 was the most prevalent phage type and was detected in isolates from cattle, sheep, and deer. The majority of the isolates were from phage types previously found in strains associated with human infection. Outbreaks caused by STEC in Spain. Although the situation in Spain seems worrisome, since many animals are carriers of STEC strains that could contaminate food, human STEC outbreaks in Spain are rare (Table 9) [6,58,64,67]. In fact, the last major outbreak was in 2000 in a school in Barcelona. It was caused by serotype O157:H7 [58].

Analytical methods for STEC detection in foods STEC O157:H7 can usually be readily identified in the laboratory based on its inability to ferment sorbitol or cleave the fluorogenic substrate 4-methylumbelliferyl-β-D-glucuronide within 24 h, which distinguishes it from other E. coli. Some atypical STEC O157:H– can ferment sorbitol but these are rare, except in Germany where they are quite frequent and highly virulent. The detection and identification of non-O157

STEC are, however, more difficult and time-consuming, since these strains do not show special characteristics allowing their ready identification. The best medium for isolating the most virulent STEC strains (including O104:H4, O157:H7, and serotypes belonging to seropathotype B) is cefixime tellurite sorbitol MacConkey agar (CT-SMAC). Once the serotype of the German outbreak strain became known, molecular methods were developed for its detection based on conventional and real-time PCR [5,24,76]. The protocol used by the LREC-USC was immediately improved, including newly designed primers for the specific detection of serotype O104:H4. Our protocol comprises two methods (A and B) (Tables 10 and 11). Method A is specific for the detection of STEC/VTEC O157:H7 and method B for the detection and isolation of any type of STEC/VTEC (O157:H7 and non-O157, including O104:H4 and others such as O26, O103, O111, O145, and O146). Method B also detects other diarrheagenic groups of E. coli. The protocol is based on a PCR using specific primers for the detection of the genes stx1 and stx2, rfb(O104), rfb(O157), fliC(H7), fliC(H4) of STEC/VTEC, and other virulence genes specific for other categories of diarrheagenic E. coli.

General recommendations to consumers and conclusions It is necessary to inform the population of the risk associated with improper food handling and preparation. Specifically,


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Table 10. Protocol used at the LREC-USC for detection of STEC/VTEC in food samples Method A Detection of STEC/VTEC O157:H7

Method B Detection of STEC/VTEC O157:H7 and non-O157 (including O104:H4), EAEC, EPEC, ETEC, EIEC

25 g of food sample 225 ml of buffered peptone water with vancomicine, cefixime and cefsulodin (vccAPT) 37ºC/6 h

25 g of food sample 225 ml of buffered peptone water 37ºC/6 h

Inmunomagnetic separation (IMS) Dynabeads anti-E. coli O157

1 ml to 9 ml of MacConkey broth

Isolation from IMS onto: Cefixime Tellurite Sorbitol MacConkey agar (CT-SMAC) 37ºC/18–24 h Sorbitol MacConkey agar (SMAC) 37ºC/18–24 h

Isolation onto: Lactose MacConkey agar (LMAC) 37ºC/18–24 h CT-SMAC agar 37ºC/18–24 h LMAC agar 44ºC/18–24 h

37ºC/18–24 h and 44ºC/18 h (duplicate)

CT-SMAC agar 44ºC/18-24h Detection by PCR of genes encoding shiga-toxins (verotoxins) stx1/vtx1 and stx2/vtx2, rfb(O157), fliC(H7), from the confluence growth of agar plates

Detection by PCR of genes encoding shiga-toxins (verotoxins) stx1/vtx1

In case of positive PCR for any of the cited genes, selection of 10 colonies

In case of positive PCR for any of the cited genes, selection of 50 colonies.

sorbitol negative and analysis by PCR for genes encoding shiga-toxins

PCR in pools of 10 colonies, and afterwards individually in case

(verotoxins) stx1/vtx1 and stx2/vtx2

of positive pools

In case of positive PCR for individual colony, confirmation of O157 and H7 antigens by serotyping and PCR.

Determination of O:H serotype of all

meat, and especially ground meat, must be sufficiently cooked. It is important to avoid the cross-contamination of foods to be eaten raw with those (meat) that have to be cooked; this is best accomplished by separating the two areas of preparation in the kitchen. Food handlers should wash their hands thoroughly following any contact with meats. The proper distribution of food in the refrigerator is important so as to avoid juices dripping from food to be cooked (meat and fish) onto others that will be consumed without heating (salads). Vegetables to be eaten raw in salads should be thoroughly washed. Only milk subjected to a minimum pasteurization heat treatment should be considered safe for consumption. The discussion in this review allows us to draw the following conclusions: • To date, the recent (2011) EC outbreak in Germany was the largest reported worldwide in terms of the number of HUS cases. • The serotype of the outbreak strain, O104:H4, is very rare and only a few human cases have been reported. Furthermore, this serotype has never been detected in animal/food.

and stx2/vtx2, rfb(O104), fliC(H4) and specific virulence genes of EAEC, EPEC, ETEC and EIEC from the confluence growth of agar plates

STEC/VTEC, EAEC, EPEC, ETEC and EIEC detected and isolated

• The outbreak strain shows a combination of virulence factors from STEC/VTEC and enteroaggregative E. coli (EAEC). • Comparison studies of the complete genome sequence of various isolates of the German outbreak strain and of African EAEC isolates of serotype O104:H4 suggest that the outbreak strain belongs to an EAEC lineage that acquired genes encoding the Stx2a toxin and antibiotic resistance. • Our recent study (from June to July 2001) showed that the microbiological quality of Spanish vegetables is quite good. However, one sample (0.6%) was positive for a STEC strain of serotype O146:H21. • Consistent with data from other countries, STEC belonging to serotype O157:H7 and other serotypes were isolated from beef, milk, cheese, and domestic and wild animals in Spain. • Although the situation may seem worrisome, human STEC outbreaks in Spain are rare. In fact, the last major outbreak was in 2000, in a school in Barcelona. However, our data suggest that, in Spain, STEC O157:H7 is annually responsible for more than 500 sporadic cases of infection, and non-O157 for more than 2000.


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INT. MICROBIOL. Vol. 14, 2011

Table 11. Oligonucleotide primers used for PCR detection of STEC/VTEC and EAEC genes Genes

Primers

Oligonucleotide sequence (5´-3´)

Fragment Size (bp)

Anneling temperature

Reference

539

55ºC

This study

358

55ºC

This study

292

52ºC

This study

630

58ºC

This study

713

66ºC

This study

497

55ºC

[21]

625

55ºC

[30]

532

60ºC

[22]

248

54ºC

[22]

STEC/VTEC stx1/ vtx1

VT1-F VT1-R

TCGCTGAATGTCATTCGCTCTGC

STEC/VTEC stx2/ vtx2

VT2-F1 VT2-F2 VT2-R

TTTCTTCGGTATCCTATTCCC TGTCTTCAGCATCTTATGCAG

VT-F1 VTf-F VT-R-VT1 VT-R1-VT2 VT-R-VT2f

TTGAACAAAATAATTTATATGT TGGAACGGAATAACTTATATGT GCTTCAGCTGTCACAGTAACAA GCTTCTGCTGTGACAGTGACAA

O104-F O104-R

CGTTTAGCCGGAAATGAGAA

H4-F H4-R

GCAGCGTATTCGTGAACTGA

O157-AF O157-AR

AAGATTGCGCTGAAGCCTTTG

H7-F H7-R

GCGCTGTCGAGTTCTATCGAGC

wzx-wzy O26F wzx-wzy O26R

AAATTAGAAGCGCGTTCATC

fliCRH11-1 fliCRH11-2

ACTGTTAACGTAGATAGC

STEC/VTEC EPEC eaeb

EAE-V3F EAE-MBR

CATTGATCAGGATTTTTCTGGT TCCAGAATAATATTGTTATTACG

510

55ºC

This study

eae-â1

B1F B1R

CACAATTAATGCACCGGGT GCTTGATACACCTGATGACT

241

55ºC

[12]

eae-ã1

EAE-FB EAE-C1

AAAACCGCGGAGATGACTTC AGAACGCTGCTCACTAGATGTC

804

55ºC

[12]

EAEC pCDV432

pCVD432/start pCVD432/stop

CTGGCGAAAGACTGTATCAT

630

60ºC

[77]

Typical EPEC bfpA

EP1 EP2

AATGGTGCTTGCGCTTGCTGC

326

60ºC

[36]

EIEC ipaH

EI1 EI2

GCTGGAAAAACTCAGTGCCT

424

55ºC

[80]

ETEC LT-I eltA

LT-A-1 LT-A-2

GGCGACAGATTATACCGTGC

696

55ºC

[78]

ETEC STa est

STA-1 STA-2

ATTTTTATTTCTGTATTGTCTTT

176

48ºC

[12]

STEC/VTECa stx1/ vtx1 stx2/ vtx2

wzx-O104

fliC-H4

O157 rfbE

fliCh7

wzx-wzy O26

fliC-H11

a

TCAGCAGTCATTACATAAGAAC

CTGCTGTCCGTTGTCATGGAA

GCTTCTGCTATCACTGTGACAA

TGAAACGACACCACTTATTGC

GCTGGATAATCTGCGCTTTC

CATTGGCATCGTGTGGACAG

CAACGGTGACTTTATCGCCATTCC

CCCAGCAAGCCAATTATGACT

TCAATTTCTGCAGAATATAC

CAATGTATAGAAATCCGCTGTT

GCCGCTTTATCCAACCTGGTA CCAGTCCGTAAATTCATTCT

CCGAATTCTGTTATATATGTC

GGATTACAACACAGTTCACAGCAGT

Primers for detection of all Shiga-toxin subtypes. Primers for detection of all eae alleles.

b


ESCHERICHIA COLI O104:H4

• The recent outbreak of STEAEC O104:H4 in Germany had international dimensions and illustrated more than ever the urgent need for a National Reference Laboratory in each of the involved countries as a national focal point for the dissemination and sharing of information and methodology. • The epidemiologic surveillance of STEC must be reinforced, focusing efforts on the detection of this new hypervirulent strain O104:H4.

INT. MICROBIOL. Vol.14, 2011

7.

8.

9.

10. Acknowledgements. We thank Prof. Ricardo Guerrero (president of the Spanish Society for Microbiology), Dr. Flemming Scheutz (Head of the WHO Collaborating Centre for Reference and Research on Escherichia coli and Klebsiella, Copenhagen) and Dr. Lothar Beutin (Head of the German National Reference Center for E. coli, Federal Institute for Risk Assessment, BfR, Berlin) for their strong support of the LREC-USC as a National Reference Laboratory (NRL) for Escherichia coli. We thank Monserrat Lamela for skillful technical assistance. This work was partially supported by Red Española de Investigación en Patología Infecciosa (REIPI RD06/0008/1016-1018) and grants PS09/01273 (Spanish Ministry of Science and Innovation, Instituto de Salud Carlos III, Fondo de Investigación Sanitaria), AGL-2008-02129 (Spanish Ministry of Science and Innovation), and 09TAL007261PR, 10MRU261023PR and 2007/000044-0 (Xunta de Galicia and The European Regional Development Fund, ERDF). A. Mora acknowledges the Ramón y Cajal program from the Spanish Ministry of Science and Innovation. Rosalia Mamani acknowledges a grant from the Spanish Agency of International Cooperation (Spanish Ministry of Foreign Affairs and Cooperation).

11.

12.

13.

14. Competing interests. None declared.

15.

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2.

3.

4.

5.

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Refs. added in proofs: 84. Kim J, Oh K, Jeon S, et al. (2011) Escherichia coli O104:H4 from 2011 European outbreak and strain from South Korea. Emerg Infect Dis 17: 1755-1756 85. Scavia G, Morabito S, Tozzoli R, et al. (2011) Similarity of Shiga toxin–producing Escherichia coli O104:H4 strains from Italy and Germany. Emerg Infect Dis 17:1957-1958


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del IRTA-Centre de Tecnologia de la Carn. Generalitat de Catalunya. Monells (Girona) / Biblioteca Montilivi. Facultat de Ciències. Universitat de Girona / Área de Microbiología. Departamento de Ciencias de la Salud. Universidad de Jaén / Microbiologia. Departament de Ciències Mèdiques Bàsiques. Facultat de Medicina. Universitat de Lleida / Facultad de Ciencias. Universidad de Vigo / Laboratorio de Microbiología Aplicada. Centro de Biología Molecular. Universidad Autónoma de Madrid-CSIC. Cantoblanco (Madrid) / Grupo de Investigación de Bioingeniería y Materiales (BIO-MAT). Escuela Técnica Superior de Ingenieros Industriales. Universidad Politécnica de Madrid / Biblioteca. Centro de Investigaciones Biológicas, CSIC. Madrid / Fundación Ciencias Microbianas. Servicio de Microbiología. Hospital Universitario Ramón y Cajal, INSALUD. Madrid / Merck Sharp & Dohme de España, Madrid / Departamento de Microbiología. Facultad de Ciencias. Universidad de Málaga / Grupo de Fisiología Microbiana. Departamento de Genética y Microbiología. Universidad de Murcia. Espinardo (Murcia) / Library. Department of Geosciences. University of Massachusetts-Amherst. USA / Biblioteca de Ciencias. Universidad de Navarra. Pamplona / Grupo de Investigación de Genética y Microbiología. Departamento de Producción Agraria. Universidad Pública de Navarra. Pamplona / Microbiología Ambiental. Departamento de Biología. Universidad de Puerto Rico. Río Piedras. Puerto Rico / Biblioteca General. Universidad San Francisco de Quito. Ecuador / Biblioteca. Facultat de Medicina. Universitat Rovira Virgili. Reus / Instituto de Microbiologia. Universidade Federal de Rio de Janeiro. Brasil / Instituto de Microbiología Bioquímica-Departamento de Microbiología y Genética. CSIC-Universidad de Salamanca / Departamento de Microbiología y Parasitología. Universidad de Santiago de Compostela. Santiago / Laboratorio de Referencia de E. coli (LREC). Facultad de Veterinaria. Universidad de Santiago de Compostela. Lugo / Departamento de Genética. Universidad de Sevilla / General Library. Marine Biological Laboratory. Woods Hole, Massachusetts, USA.


RESEARCH ARTICLE INTERNATIONAL MICROBIOLOGY (2011) 14:143-154 DOI: 10.2436/20.1501.01.143 ISSN: 1139-6709 www.im.microbios.org

Microbial community composition of anoxic marine sediments in the Bay of Cádiz (Spain) Thorsten Köchling,1 Pablo Lara-Martín,2 Eduardo González-Mazo,2 Ricardo Amils,1,3 José Luis Sanz4* 1

Center for Molecular Biology Severo Ochoa, CSIC-UAM, Cantoblanco, Madrid, Spain. 2Department of Physical Chemistry, Faculty of Sciences of the Sea and of the Environment, University of Cádiz, Puerto Real, Cádiz, Spain. 3 Center of Astrobiology, INTA-CSIC, Madrid, Spain. 4Department of Molecular Biology, Autonomous University of Madrid, Cantoblanco, Madrid, Spain Received 30 April 2011 · Accepted 15 June 2011

Summary. The composition of the microbial community inhabiting the anoxic coastal sediments of the Bay of Cádiz (southern Spain) was investigated using a molecular approach consisting of PCR cloning and denaturing gradient gel electrophoresis (DGGE), based on 16S rRNA sequences. The total cell count was 1–5 × 108 cells/g sediment and, as determined by catalyzed reporter deposition–fluorescent in situ hybridization (CARD-FISH), the proportion of Bacteria to Archaea was about 70:30. The analysis of 16S-rRNA gene sequences revealed a wide spectrum of microorganisms, which could be grouped into 111 operational taxonomic units (OTUs). Many of the OTUs showed high phylogenetic similarity to microorganisms living in marine sediments of diverse geographic origin. The phylogenetic groups that were predominantly detected were Firmicutes, Deltaproteobacteria, and Gammaproteobacteria, accounting for 23, 15, and 14% of the clones, respectively. Diversity in the domain Archaea was significantly lower than in the domain Bacteria. The majority of the archaeal OTUs belonged to the Crenarchaeota phylum. Since most of the sequences could not be identified precisely at the genus/species level, the functional roles of the microorganisms in the ecosystem could not be inferred. However, seven OTUs affiliated with the Delta- and Epsilonproteobacteria were identified down to the genus level, with all of the identified genera known to occur in sulfate-rich marine environments. [Int Microbiol 2011; 14(3):143-154] Keywords: microbial community composition · anoxic marine sediments · 16S rDNA gene library

Introduction Prokaryotic organisms (Bacteria and Archaea) that live in marine sediments participate in a variety of biochemical pathways involving both inorganic and organic compounds. *Corresponding author: J.L. Sanz Departamento de Biología Molecular Universidad Autónoma de Madrid 28049 Cantoblanco, Madrid, Spain Tel.+34-914978078. Fax +34-914978300 E-mail: joseluis.sanz@uam.es

Analyses of the microbial community composition of many sediments in different parts of the world have shown that the predominant phylogenetic groups in these habitats are often highly similar. Various studies have determined the presence of Gamma- and Deltaproteobacteria, Flavobacteria, and Planctomycetes in sediments from the North Sea and Arctic Sea [7,24,25,36–38] as well as from the Antarctic Sea [3–5,45]. In sediments from Tokyo Bay, Japan, the predominant bacterial groups are Deltaproteobacteria, Gammaproteobacteria, Epsilonproteobacteria, Gram-positive bacteria, and Verrucomicrobia [43]. In one of the first molecular studies


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of marine sediments from Puget Sound (near Seattle, USA), the analysis of a clone library showed similar phylogenetic affiliations [11]. Recent studies examining sediments from the Mediterranean Sea [14,31–33,40,18] also described an abundance of members of the Deltaproteobacteria and Gammaproteobacteria, as well as Betaproteobacteria, Planctomycetes, Acidobacteria, Bacteroidetes, and Firmicutes. Although these phylogenetic groups are prominently represented in most surveys, and sequences retrieved from very distant habitats often show similarities of over 90% (at the class/phylum level), when examined more closely the clone libraries represent a high level of biodiversity, including many unique ribotypes [3,5]. Similarly, comparisons of the composition of various clone libraries based on sequences obtained from the Mediterranean Sea showed that microbial communities from different regions are highly distinct [32]. Only 14% of the complete set of sequences had a similarity of 92% or higher between libraries. Significantly distinct community compositions were also found between two stromatolites in Shark Bay, Western Australia [29]. These examples show that (i) many of the same phylogenetic groups are detected in sediments independent of their geographic location, and (ii) the level of microbial diversity within each set of sampled sequences can be very high. The purpose of this study was to determine the microbial community composition of the anoxic sediment in the Sancti Petri Channel of the Bay of Cádiz (south of Spain). Since only a fraction of the microorganisms inhabiting soils and sediments are readily culturable, this study made use of a culture-independent approach. Based on PCR and the cloning of total genomic community DNA, eight clone libraries of near full-length 16S rDNA sequences were constructed, allowing a detailed phylogenetic analysis. DGGE was employed as a complementary technique to characterize the microbiota, and CARD-FISH to quantify the Bacteria and Archaea domains.

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diameter. The cores were sealed and immediately transferred to the laboratory, where they were cut into slices of defined thickness, corresponding to depths of 0–2, 6–8, 8–10, 12–14, and 18–20 cm. Sediment samples for genomic DNA extraction were stored at –20ºC until use. Samples to be used for in situ hybridization were fixed for 4 h in 4% formaldehyde, washed twice with PBS, and stored in PBS:ethanol (1:1, v:v). Genomic DNA extraction from sediment samples. Sediment samples (~ 0.6 g wet weight) from the cores of layers 0–2 (layer A), 6–8 (layer B), 12–14 (layer C), and 18–20 cm (layer D) were washed with PBS to eliminate excess salt. The samples were lysed by mechanical disruption in a bead beater (FastPrep FP120, Qbiogene), exposing the samples to five cycles of cell rupture (intensity level 6; 20 s per cycle) with intermittent incubation on ice. Microbial community DNA was extracted using the FastDNA SPIN Kit for Soil (Qbiogene). DNA integrity and yield were examined on 0.8% agarose gels with ethidium bromide staining (0.5 mg/l). PCR. Near full-length bacterial 16S rDNA for clone library construction was PCR-amplified using the primer set 27F/1492R [20]. A shorter fragment was amplified for DGGE using primer set 341F/518R [27]. For the archaeal community, the primer combination 21F/958R was used to construct a clone library [10], and the primer set 344F/518R [27,41] for DGGE. AGC-tag (5′CGCCCGCCGCGCGCGGCGGGCGGGGCGGGGGCACGGGGGG-3′) was attached to the 5′ end of primer 518R to prevent complete dissociation in the gel. Each reaction (50 μl) contained 1× PCR buffer (Promega), 0.5 μM of each primer, 0.25 mM of each dNTP (dATP, dCTP, dGTP, and dTTP), 1.5–3.0 mM MgCl2, and 1 U of Taq polymerase (Promega). PCR product size and yield were estimated by agarose gel electrophoresis using a set of molecular weight markers (φ-29/HindIII).

Materials and methods

DG-DGGE. Five layers of sediment were sampled (0–2, 6–8, 8–10, 12–14, and 18–20 cm). The PCR products were resolved on a DCode Mutation Detection System (Bio-Rad) in double-gradient (DG) gels. A denaturing gradient of 30–60% urea/formamide (with 100% defined as 7 M urea/40% formamide) was superimposed on a porous gradient of 8–12% polyacrylamide. Electrophoresis conditions were 60ºC, 200 V, and a running time of 5 h. The gels were run in 0.5× TAE buffer (40 mM Tris, 20 mM sodium acetate, 1 mM EDTA, pH 7.4), stained in 0.5 mg ethidium bromide/l, and photographed on a UV trans-illuminator (Fotodyne, Hartland, WI, USA). For sequencing, bands were excised from the gel using a scalpel and the DNA then eluted by incubating the acrylamide blocks at 50ºC for 1 h. The supernatant was used for PCR reamplification of the bands with primer pairs 341F/518R (Bacteria) and 344F/518R (Archaea). The resulting products were sequenced on an ABI PRISM 3100 Genetic Analyzer (Applied Biosystems). Cluster analysis of the DGGE banding patterns was performed with the PHYLIP software package (PHYLogeny Inference Package, Joe Felsenstein, http://evolution.genetics.washington.edu/phylip.html), applying the neighbor-joining method. Dendrograms were generated and edited with MEGA software (Molecular Evolutionary Genetics Analysis) [19].

Sampling sites and procedure. Sediment samples were taken at the Sancti Petri Channel (Cádiz, Spain, 36° 28.48′ N, 6° 10.71′ W), a coastal marine area partially polluted by the spillage of untreated municipal sewage (SP16). The physicochemical properties and nutrient profiles of the sediment have been published elsewhere [23]. Samples were taken in 2002, 2003, and 2004. Shortly after sampling in 2002, a domestic wastewater treatment plant began operation, and the sediment site no longer received severely contaminated wastewater input [22]. This allowed us to compare the effect of human contamination on the microbiota of the sediments. To compare the polluted sampling zone SP16 to an area that had not been exposed to domestic sewage, a beach-like zone (SP02) was also analyzed. All the samples were extracted by a diver using PVC cores 50 cm in length and 6 cm in

Clone library construction. Four bacterial and four archaeal gene libraries were constructed with samples from sediment depth layers A–D (described above). The sediment cores were those taken at SP16 in the year 2002. 16S rDNA was PCR-amplified and the products cloned into the TOPO-TA vector (Invitrogen). Competent One Shot E. coli cells (Invitrogen) were transformed with the vector-16S rDNA constructs and grown on LB (Luria-Bertani) agar plates with ampicillin (50 μg/ml), using β-galactosidase blue/white screening. Positive clones were regrown overnight in 5 ml LB medium containing ampicillin, followed by extraction of plasmid DNA by alkaline lysis (plasmid miniprep) [39]. After the amplified ribosomal DNA restriction analysis (ARDRA) of 770 clones, approximately 300 clones were sequenced with the primers M13F and M13R (vec-


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Phylogenetic analysis. Sequencing chromatograms were checked and edited with the programs Chromas (Technelysium) and Genedoc [28]. Comparative analysis of the sequences was done using the BLAST routine from NCBI (National Center for Biotechnology Information) employing the GenBank database (http://www.ncbi.nlm.nih.gov/BLAST/) [1] and the tools Classifier and Sequence Match from the Ribosomal Database Project (RDP) at Michigan State University (http://rdp.cme.msu.edu/). The clone library was examined for possible chimeric sequences using the informatics tool available on the website of the Center for Microbial Ecology [Michigan State University, USA, http://rdp8.cme.msu.edu/cgis/chimera.cgi?su=SSU]. Clone sequences affiliated with the same phylum and class, as determined by BLAST comparison and the Classifier function of RDP, were grouped for the construction of independent phylogenetic trees together with sequences retrieved from the database corresponding to related microorganisms and representative members of the analyzed phylogenetic group. These sets of sequences were aligned with the ClustalX program [42]. Phylogenetic trees were calculated using the PHYLIP software package, applying the maximum-likelihood method. The resulting trees were visualized and edited with MEGA. CARD-FISH. Aliquots of fixed sediment samples were diluted in 1× PBS, sonicated briefly with an UP50H Ultrasonic Processor (Hielscher) at 40% maximum amplitude (100 μm) and 0.5 cycle setting (acoustic power: 300 W/cm2), vortexed, filtered onto a 0.2-μm pore size GTTP polycarbonate membrane (Millipore), and embedded in agarose. These samples were hybridized [30], counterstained with 4′,6′-diamidino-2-phenylindole

Fig. 1. DGGE fingerprints of bacterial amplicons. Samples from three years (2002, 2003, and 2004) and five depth layers (0–2, 6–8, 8–10, 12–14, and 18–20 cm) were analyzed. Numbered bands were excised and sequenced.

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(DAPI), and counted on an epifluorescence microscope (Axioskop, Zeiss) to determine total cell numbers. For each sample, between 800 and 1000 cells (as determined by DAPI staining) were counted. The probes used for domain specific hybridization were EUB338-HRP for Bacteria and ARC915-HRP for Archaea [35]. Nucleotide sequence accession numbers. Clone sequences were deposited in the GenBank database under the accession numbers GQ249466–GQ249661.

Results DGGE. Comparisons of the bacterial community fingerprints over a period of three years and among the five different depth layers in the sediment revealed a similar composition of the dominant microorganisms in nearly all samples (Fig. 1). Cluster analysis of the DGGE band patterns showed that, with the exception of two samples from the deepest sediment layer (18–20 cm, 2002 and 2004), differences between samples were low, ranging between 0.4 and 3%, throughout the different depth layers of the sediment and over the three years of observation (Fig. 3A). Most of the sequences retrieved were equally distributed among the Gamma-, Delta-, and Epsilonproteobacteria. Two other amplicons were affiliated with Bacteroidetes and Firmicutes.

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tor sites near the polylinker). Chimeras, vectors, and short sequences were removed, yielding a total of 170 bacterial and 22 archaeal sequences for phylogenetic analysis.

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Compared to the bacterial domain, the archaeal fingerprints had a higher number of total bands (DGGE Archaea: 39, DGGE Bacteria: 27) and a greater variability between samples (Fig. 2). This can be observed in the length of the interconnecting branches in the corresponding dendrogram, showing differences of 4 to 8% between many samples (Fig. 3B). Forty-four bands were excised from the gel, reamplified, and sequenced successfully. All sequences were affiliated with the phylum Euryarchaeota. Furthermore, most of the sequences were related to environmental clones encountered in saline marine habitats, anoxic coastal sediments, subsurface waters, springs, or salt lakes, and matched microorganisms from diverse geographic locations such as China, Turkey, South Africa, and Mexico. Some of the sequences could be phylogenetically narrowed down to the order level, including those of Halobacteriales. The nearest described relatives to the DGGE bands are Natrinema sp., Haladaptatus paucihalophilus, and Haloterrigena limicola, with similarities to our clones in the range of 90â&#x20AC;&#x201C;98%. Due to the heterogeneity of the band patterns from the 2002 and 2004 samplings, it was difficult to determine the predominant bands in the gel. However, considering the narrow phylogenetic spectrum, with all amplicons belonging to the phylum Euryarchaeota and probably to the class Halobacteria, the level of diversity may have been lower than in Bacteria.

Fig. 2. DGGE fingerprints generated for Archaea with domain-specific primers. The sediment samples were the same as those used for bacterial analysis. Numbered bands were excised, reamplified, and sequenced.

As we did not expect to detect only sequences related to Euryarchaeota, we analyzed the literature describing the use of primers 344F and 518R for archaeal DGGE amplification. Two studies described a bias towards Euryarchaeota detection that was attributed to a mismatch in primer 518R [2,44]. We therefore aligned the sequence of 344F to that of several of the clones from our archaeal library and found a Crenarchaeota-incompatible mismatch in this primer as well (T by C at position 347). Clone libraries. Sequences that showed a similarity of over 97% were grouped together, resulting in 111 different OTUs. Their distribution in the major phylogenetic lineages is shown in Fig. 4. The phylogenetic tree for Bacteria is provided in Fig. 5. The taxonomic affiliation of the cloned sequences following comparative analysis of the 16S rRNA gene revealed a high degree of microbial diversity in the analyzed sediment, as reflected by the presence of microorganisms falling into eight different phyla of the domain Bacteria. The most numerous group of detected Bacteria belonged to the phylum Proteobacteria. With the exception of Betaproteobacteria, members of all described classes of this phylum were encountered, with Gamma- and Deltaproteobacteria representing 14 and 15%, respectively, of the total OTUs. Firmi-


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cutes, comprising 23% of the phylotypes, was the second most abundant phylum. The other phylogenetic groups were less abundant, representing 3–10% of the total OTUs. Microorganisms of the phyla Planctomycetes and Verrucomicrobia were grouped together for analysis [12]. Alphaproteobacteria. OTU 01 was affiliated with the genera Sphingomonas/Sphingopysis, OTU 02 was a member of the order Rhizobiales, and most clones comprising OTUs 03–08 clustered into the family Rhodobacteraceae. In this group, various microorganisms were identified with the genus Loktanella (OTU 03) and Roseobacter/Sulfitobacter (OTUs 04–07).

Fig. 3. Cluster analysis of DGGE banding patterns for domains Bacteria (A), and Archaea (B). (Bar: 1% distance.)

Fig. 4. Percent distribution of bacterial OTUs over the phylogenetic groups.

Deltaproteobacteria. All but one of the sequenced clones related to this class could be assigned to families of sulfate-reducing bacteria: OTUs 26–29 to Desulfuromonadaceae, OTUs 32–36 to Desulfobacteraceae, and OTUs 37–41 to Desulfobulbaceae. Various clones were identified

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Gammaproteobacteria. Most of the clones could not be assigned to described species but showed high sequence similarity to uncultured microorganisms retrieved from aquatic environments. OTUs 09–13, all of them retrieved from the most superficial sediment layer, were related to the Chromatiaceae family. Only the OTUs 09 (Thiorhodococcus), 22 (Haliea), 23 (Klebsiella/Enterobacter), and 24 (Stenotrophomonas) could be assigned to the genus level.


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Fig. 5. Phylogenetic tree for the domain Bacteria.


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Fig. 6. Relative abundance of OTUs belonging to the different phylogenetic lineages throughout the four sediment depth layers.

further as related to the genera Desulfosarcina, Desulfocapsa/Desulfotalea, Desulfuromonas/Pelobacter, and Desulforhopalus. Furthermore, all the retrieved sequences were related to sulfate-reducing bacteria, known to play a key role in marine sediments. Only OTU 25 was phylogenetically distant from the remaining set of clones, as it was related to the genus Anaeromyxobacter (order Myxococcales). Epsilonproteobacteria. OTU 43 could be assigned to the genus Sulfurovum. Our clones in this class were closely related to clone Milano-WF213 [14], retrieved from the deep-sea sediment in the Eastern Mediterranean Sea. OTU42 could not be assigned to a described genus. Sequences with a similarity of 92% have been retrieved from a deep phreatic sinkhole (FJ485585) and from bacterioplankton communities (AY947951) [9]. Firmicutes. After the Proteobacteria, Firmicutes were the most highly represented group in our study, comprising 24 affiliated taxonomic units. The sequenced clones were distributed evenly over the two most relevant environmental subgroups, classes Bacilli and Clostridia. Fifteen OTUs could be identified at the genus level, including members of Clostridium, Sporacetigenium, Ruminococcus, Enterococcus, Streptococcus, and Bacillus.

Actinobacteria. Nine OTUs were assigned to the phylum Actinobacteria, covering the orders Actinomycetales and Rubrobacterales. Five OTUs were further identified as belonging to the genera Propionibacterium, Jiangella, Conexibacter, Rubrobacter, and Blastococcus. Most of the clones were retrieved from the two deepest layers. Bacteroidetes. Two of the three major subgroups of this phylum were represented in the clone library, namely, the classes Flavobacteria and Sphingobacteria, whereas members of the third subgroup, Bacteroidetes, were not detected. Several sequences affiliated with the genera Flavobacterium, Gaetbulibacter, and Psychroserpens belonged to the family Flavobacteriaceae. Chloroflexi. With the exception of one clone, related to the genus Sphaerobacter (OTU 72), the other Chloroflexi (OTUs 73â&#x20AC;&#x201C;77), all retrieved from layer D, could be assigned to the family Anaerolineaceae, a strictly anaerobic non-photosynthetic filamentous bacteria found in anoxic environments rich in organic matter. Acidobacteria. Seven OTUs were associated with this phylum, although all of the clones were phylogenetically situated at considerable distances from the cultured members of


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Table 1. Total cell counts and hybridization rates with specific probes for Bacteria and Archaea. Hybridization values are given as the percentage of the total bacteria (DAPI-stained) counts Hybridization (%) Sampling point

Year

Depth (cm)

Total cells (× 108/g sediment)

EUB338

ARC915

SP02

2002

0–2

2.0 ± 0.3

60.7 ± 14.6

ND

15–17

1.4 ± 0.4

37.0 ± 12.6

ND

27–30

0.7 ± 0.2

20.2 ± 15.4

ND

0–2

5.0 ± 2.0

58.7 ± 13.6

25.8 ± 10.2

6–8

3.3 ± 1.0

52.0 ± 13.6

18.7 ± 10.3

12–14

5.5 ± 2.1

45.5 ± 9.0

9.9 ± 6.2

18–20

1.0 ± 0.1

55.8 ± 21.4

11.4 ± 13.2

38–40

1.6 ± 0.1

NC

NC

0–1

2.5 ± 0.7

81.1 ± 15.1

33.4 ± 7.9

15–16

2.9 ± 0.9

63.7 ± 13.4

16.9 ± 6.0

0–2

1.2 ± 0.2

61.0 ± 16.1

20.7 ± 16.9

6–8

1.3 ± 0.4

33.1 ± 20.6

7.2 ± 12.8

12–14

0.3 ± 0.1

44.7 ± 25.9

9.8 ± 14.0

18–20

0.4 ± 0.1

53.0 ± 18.2

19.2 ± 18.0

25

0.7 ± 0.5

NC

SP16

SP16

SP16

2002

2003

2004

NC

ND: Not detected or <0.5% of the total DAPI stained cells. NC: Not counted.

this group. Five of the OTUs were related to the uncultured “genus Gp21” and the other two OTUs to uncultured genera Gp21 and Gp22. Verrucomicrobia and Planctomycetes. Three OTUs were affiliated with the phylum Verrucomicrobia, clustering in the family Verrucomicrobiacea. Four OTUs belong to the phylum Planctomycetes. OTUs 107–108 were associated with the genera Pirellula/Rhodopirellula. None of the Planctomycetes-affiliated clones were related to the anammox bacteria. Relative distribution of the major phylogenetic groups in the four different depth layers of the sediment. As shown in Fig. 6, there was an almost constant degree of biodiversity, illustrated by the distribution of the OTUs belonging to the different phylogenetic lineages over the four sediment layers (A, B, C, and D). The majority of the detected groups were present in every layer from the surface to the deepest zone (18–20 cm). The proportions, however, differed along the vertical profile. For example, in the surface sediment, the majority of the OTUs were related to Gammaproteobacteria and Firmicutes (two groups present

in all samples), whereas the largest share of the taxonomic units in layers B and C was associated with the Deltaproteobacteria class. In contrast, in the deepest layer, one third of the OTUs were members of Firmicutes; only a small fraction was affiliated with the Gamma- and Deltaproteobacteria. Domain Archaea. Using BLAST, the sequenced amplicons clustered into 17 different OTUs: 14 were assigned to the phylum Crenarchaeota and three to the phylum Euryarchaeota. All Crenarchaeota OTUs showed similarity to uncultured environmental clones of diverse origin (such as soils, marine habitats, and thermal springs) and were distantly related (70–80% according to the Classifier function of RDP) to the class Thermoprotei. With respect to the Euryarchaeota, one of the three OTUs encountered was related to a group of uncultured clones from a hypersaline environment (OTU 15). The phylogenetic affiliation of OTUs 16 and 17 could be established more precisely, with OTU 16 closely related to the family Halobacteriaceae, a group of Archaea also living in high-salinity habitats, and OTU 17 corresponding to the genus Methanococcoides, which is frequently encountered in marine sediments [34,41].


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Total cell counts and CARD-FISH. Table 1 shows the numbers of DAPI-stained cells per gram of sediment (dry weight). Sampling zones SP16 and SP02 differed significantly with respect to the samples collected in 2002, as the biomass of the contaminated sediment SP16 was twice as high as that of SP02, reflected by the total cell numbers. The cell numbers also decreased with depth in the SP16 samples. The notable decrease in the total cell numbers of the samples collected between 2002 and 2004 was consistent with the start of operation of a wastewater treatment plant for effluents of the town of San Fernando. The high standard deviations of almost all counts were due to the pronounced heterogeneity of the subsamples, in which aggregates, microcolonies, and blank areas were observed. The number of cells that hybridized with the Bacteria-specific probe EUB338 tended to be 2–5 times higher than the number that hybridized with ARC915, targeting Archaea, except for the SP02 sediments in which either no Archaea were detected or the hybridization rates were below 0.5%.

Discussion The high degree of bacterial diversity present in the Sancti Petri Channel sediments was reflected by the clone library and DGGE band patterns. Our cloning approach led to the detection of members of 11 major phylogenetic lineages, with the phylum Proteobacteria (mostly the Delta and Gamma classes) represented by the highest number of unique OTUs (39%), followed by Firmicutes (23%). Bacteroidetes, Actinobacteria, Acidobacteria, Planctomycetes/Verrucomicrobia, and Chloroflexi were detected in minor proportions, comprising 3–10% of the total phylotypes. The predominance of one or several of these groups has been described in marine sediments subjected to similar climatic conditions [3,8,12,32] and in more extreme habitats such as the Antarctic Sea [5]. All the genera of the sulfate-reducers identified thus far occur in anoxic marine or brackish sediments [6]. Their abundance in our study was expected, given the reducing conditions and high sulfate content in the Sancti Petri Channel. Indeed, the presence of an efficient sulfatereducing community in the Sancti Petri sediments, as assessed by microcosm tests, had been previously reported by our group [21]. The cloning approach used in the present work revealed many subpopulations of Epsilonproteobacteria. Of the 23 clones, 22 were contained in a single OTU, distributed throughout the sampled depth layers, and showed 97–100% nucleotide sequence similarity, suggesting a phylo-

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genetic diversity of the genus Sulfurovum in our samples. The type species, Sulfurovum lithotrophicum, is a mesophilic, microaerobic sulfur-oxidizing bacterium isolated from the sediment of a hydrothermal system [16]. Most of the Sulfurovum-related sequences reported have been retrieved from deep sea sediments [13,15,25]. Sequences affiliated with Sulfurovum were also found in an anoxic reactor treating sulfide wastewaters. In all cases, the sequences are related to ecosystems/environments that contain reduced-sulfur compounds. Chemolithoautotrophic marine Epsilonproteobacteria have been detected in diverse sulfide-rich environments: sulfide structures at hydrothermal fields [17], sulfidic waters of pelagic redoxclines, where they represent the major portion of chemoautotrophic Bacteria [11,13], and sulfur mats, where a numerical dominance of Epsilonproteobacteria was described [25]. These Epsilonproteobacteria (like the genera Sulfurovum and Sulfurimonas) are sulfur oxidizers and likely play an important role in the marine sulfur cycle and as anaerobic or microaerophilic dark CO2-fixing microorganisms [11]. The other major microbial lineage, the domain Archaea, was much less abundantly represented by the number of different OTUs; indeed, the quantitative CARD-FISH analysis yielded a 70:30 ratio of Bacteria to Archaea. The inability to precisely identify the sequences retrieved from the sediment samples was notable: only one OTU could be identified at the genus level (Methanococcoides) and one other OTU was determined to be related to the order Halobacteriales. The low number of different ARDRA patterns suggests a lower diversity within the Archaea in the analyzed sediments of the Bay of Cádiz. A lower abundance of archaeal microorganisms is commonly encountered in marine sediments [3,26]. Although the DGGE patterns suggested a higher diversity of Archaea than Bacteria, the sequences derived from the different bands were similar, indicative of a low level of diversity. Regarding the low archaeal diversity detected by DGGE, it is noteworthy that primer set 344F/518R produced a distorted picture of the archaeal community by introducing a bias towards templates affiliated with the phylum Euryarchaeota, thus excluding members of Crenarchaeota from the experiment. A similar phenomenon was reported in two publications [2,44], in which the probable cause was suggested to be mismatches in the sequence of the reverse primer 518R. Accordingly, we revised and aligned the 344F sequence, which includes a nucleotide signature that is only compatible with euryarchaeal species; however, the mismatch was located at the 5′ end of the primer and was therefore unlikely to interfere significantly with the results.


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As evidenced by DAPI staining, the total number of microorganisms decreased with the depth of the analyzed sediments. These findings concur with data from studies of other marine environments [19,32]. The phylogenetic diversity of the clones was homogeneous throughout the sediment column when the OTUs were clustered into phylogenetic groups at the class or phylum level, with the exception of the phylum Chloroflexi, whose members appeared exclusively in the clone library sets of the two deepest levels (12–14 and 18–20 cm). A homogeneous microbial community composition was also observed in analyses of the DGGE band patterns of the bacterial fraction of the microorganisms. However, the DGGE results did not necessarily illustrate an identical community composition, because many of the assigned OTUs were exclusive to one of the four depth layers of the SP sediment. In contrast, the archaeal patterns varied significantly between distinct depth layers in two out of the three analyzed sample sets. Thus, DGGE may not be the ideal tool to assess microbial diversity in environmental samples, since probably only a minor fraction of the microbial community can be resolved by this method. Instead, whole 16S rRNA gene cloning is in such cases the more adequate strategy to approach the true level of diversity in any given environmental sample. Although shortly after the first sampling a domestic wastewater treatment plant located nearby began operation, the level of bacterial diversity detected by DGGE was equally high in sample sets from 2002 and 2004. It therefore appears that exposure of the sediment to untreated wastewater effluents did not significantly influence the microbial community in terms of diversity. However, the reduction of these wastewater effluents may have led to the observed decrease in population size (total cell numbers) over the three years (Table 1). A problem that often arises when working with clone sequence databases clearly occurred for the sequences affiliated with Acidobacteria, Chloroflexi, many Gammaproteobacteria, and Crenarchaeota. These clones were similar only to other environmental sequences and did not cluster in the vicinity of any described species, precluding a precise classification of these microorganisms. When the closest related organisms are not described, it is difficult or impossible to infer a metabolic or functional role for a particular phylotype within a given ecosystem. Despite these challenges, the detailed documentation that accompanies most database entries provides some degree of insight into the possible characteristics of a microorganism. In our study, we identified various clones whose 16S rDNA sequences coincided

99% with clones encountered in similar habitats, as published in other surveys. The high proportion of OTUs close to described sulfate-reducing Deltaproteobacteria allowed us to deduce their function in the studied sediments. The Bay of Cádiz sediments showed a high level of bacterial and a lesser degree of archaeal diversity while the quantitative ratio between the two domains was 70:30 (Bacteria:Archaea). Total cell numbers decreased with increasing sediment depth. Since a mismatch in the 518R primer likely resulted in the exclusion of the Crenarchaeota from the archaeal DGGE, this primer should be avoided in future surveys of a complete archaeal community. A cluster of Epsilonproteobacteria exhibiting a high level of microdiversity, probably on sub-species level, was encountered in the sediments. Our analysis provided evidence of a phylogenetically diverse microbial community whose close relatives are encountered in many similar habitats of diverse geographic origin. The massive presence of Deltaproteobacteria could be plausibly linked to sulfate-reducing activity; however molecular methodologies did not yield clear information about the ecological functions of the other detected microorganisms. Our strategy of employing three different 16S rRNA-dependent techniques (PCR cloning, PCR-DGGE, and CARD-FISH) to describe the microbial community structure of the Bay of Cádiz sediments resulted in a more comprehensive picture than obtained by a single approach. However, in environmental microbial community studies aimed at inferring the ecological and metabolic functions of its members, culture-independent methods should be combined with the classical microbiological strategy of isolating and growing microorganisms in pure cultures, as this approach will greatly benefit and complement modern molecular methodologies. Acknowledgments. This work was partially supported by grant REN2001-2980-C02-02 from the Spanish Ministry of Education and Science to J.L.S. We express our gratitude to PETRESA for funding under contract FGUAM 011301. Competing interests. None declared.

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RESEARCH ARTICLE INTERNATIONAL MICROBIOLOGY (2011) 14:155-162 DOI: 10.2436/20.1501.01.144 ISSN: 1139-6709 www.im.microbios.org

Genomic diversity of Oenococcus oeni from different winemaking regions of Portugal Ana P. Marques,1* Ana J. Duarte,1 Lélia Chambel,2 Maria F. Teixeira,3 Maria V. San Romão,1,4 Rogério Tenreiro2 1

Institute of Experimental Biology and Technology (IBET) & Institute of Chemical and Biological Technology (ITQB), New University of Lisbon, Oeiras, Portugal. 2Center for Biodiversity, Functional and Integrative Genomics (BioFIG), Faculty of Sciences, University of Lisbon, Lisbon, Portugal. 3Proenol Biotechnological Industry, Canelas, Portugal. 4 National Institute of Biological Resources, Ex-National Wine Station, Quinta de Almoinha, Dois Portos, Portugal Received 30 May 2011 · Accepted 30 June 2011

Summary. Oenococcus oeni is an alcohol-tolerant, acidophilic lactic acid bacterium that plays an important role in the elaboration of wine. It is often added as a starter culture to carry out malolactic conversion. Given the economic importance of this reaction, the taxonomic structure of this species has been studied in detail. In the present work, phenotypic and molecular approaches were used to identify 121 lactic acid bacteria strains isolated from the wines of three winemaking regions of Portugal. The strains were differentiated at the genomic level by M13-PCR fingerprinting. Twenty-seven genomic clusters represented by two or more isolates and 21 single-member clusters, based on an 85% similarity level, were recognized by hierarchic numerical analysis. M13-PCR fingerprinting patterns revealed a high level of intraspecific genomic diversity in O. oeni. Moreover, this diversity could be partitioned according to the geographical origin of the isolates. Thus, M13-PCR fingerprint analysis may be an appropriate methodology to study the O. oeni ecology of wine during malolactic fermentation as well as to trace new malolactic starter cultures and evaluate their dominance over the native microbiota. [Int Microbiol 2011; 14(3):155-162] Keywords: Oenococcus oeni · lactic acid bacteria (LAB) · Portuguese winemaking regions · genomic diversity · M13-PCR · fingerprinting

Introduction In the mid 1960s, Ellen Garvie [13] isolated, characterized, and named Leuconostoc oenos as the bacterial agent of malolactic fermentation (MLF). This species is a Gram-positive, catalase negative, microaerophilic and heterofermentative coccus [14]. With the introduction of molecular techniques,

*Corresponding author: A.P. Marques Instituto de Biologia Experimental e Tecnológica & Instituto de Tecnologia Química e Biológica (IBET/ITQB) Universidade Nova de Lisboa Apartado 12, 2781-901 Oeiras, Portugal Tel. +351-214469554. Fax +351-214421161 E-mail: amarques@itqb.unl.pt

however, a new genus, Oenococcus, was described, and Leuconostoc oenos was reclassified as Oenococcus oeni [10]. Due to its resistance to high ethanol concentrations (<15% v/v) and tolerance of low pH (as low as 2.9), Oenococcus oeni is the species of lactic acid bacteria (LAB) most frequently associated with MLF in wine. In this reaction, L-malate is converted to L-lactate and carbon dioxide. MLF promotes the deacidification and microbial stability of wines [16,20,27,40]. However, it can either positively or negatively influence the sensorial profiles of wines, with the overall effects largely dependent on the particular strain involved and on the type of wine being produced [4]. In the last 20 years, molecular biology techniques have provided new information on microbial biodiversity. Yet, it is


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difficult to identify strains within species, especially when microorganisms belonging to a genomically homogeneous species are analyzed. Strains belonging to O. oeni are clearly distinguishable from Leuconostoc species by chromosomal DNA-DNA hybridization [9,25,26,36,42], 16S and 23S rRNA sequence analysis [11,32,33,36,42], 16S-23S rDNA intergenic spacer region sequencing (ITS-PCR) [23,52] and ribotyping [6,45,46,50,53]. Several studies on genotyping diversity among O. oeni strains, carried out using molecular techniques including DNA fingerprinting, restriction endonucleases analysis–pulsed field gel electrophoresis (REAPFGE) [19,21,22,28,29,36,41,42,45,50], randomly amplified polymorphic DNA-PCR (RAPD-PCR) [2,6,22,24,36–38, 41,50], and differential display PCR (DD-PCR) [22,36,41] suggest that this species is phylogenetically homogeneous, although physiologically diverse. Delaherche et al. [8], based on sequence analyses of nine genes, claimed that O. oeni is a single bacterial species displaying genomic variation, which may be correlated to malolactic activity. However, recent studies [39] using multilocus sequence typing (MLST) and physiological characterization have again raised the hypothesis of subspecific divisions within this taxon. Given the taxonomic structure of O. oeni, the availability of reliable methods for strain differentiation is crucial for monitoring the survival and contribution of inoculated and autochthonous bacteria and to select individual O. oeni strains with desirable

organoleptic properties. Since the wine dynamics of O.oeni populations are also conditioned [37,38] by the available species and strain diversity (from spontaneous and controlled inoculation) as well as the winemaking conditions (e.g. temperature, wine chemical profile), the identification and typing of MLF-promoting isolates is a reliable approach to assess their ability to dominate the native microbiota and to correlate their dominance/performance with distinct winemaking conditions. In the present work, 121 O. oeni strains were isolated from wines of different winemaking regions of Portugal and identified using a phenotypic and molecular approach. M13PCR fingerprinting analysis was carried out to evaluate the genetic diversity of this collection of O. oeni strains and to search for underlying patterns of regional/geographical strain diversity.

Materials and methods Bacterial strains. The 121 bacterial isolates of Oenococcus oeni used in this work are listed in Table 1. Among them, 100 were isolated from wines, at the end of spontaneous MLF, recovered from four wineries of Dão (Carregal do Sal, Viseu, Mangualde and Mealhada), two wineries of Ribatejo (Dois Portos and Arruda dos Vinhos) and one winery of Alentejo (Reguengos). Additionally, 20 O. oeni isolates from Nelas (Dão) and one O. oeni isolate from Ourém (Ribatejo), previously isolated and identified [PhD thesis, R. Tenreiro, Univeristy of Lisbon, 1995], were obtained from the

Table 1. Oenococcus oeni strains used in this study Region/Sub-region wine

Oenococcus oeni strains

Dão

Nelas

bOg18, bOg20, bOg22, bOg23, bOg27, bOg29, bOg30, bOg31, bOg32, bOg33, bOg34, bOg35, bOg36, bOg39, bOg40, bOg41, bOg42, bOg43, bOg44, bOg45

Carregal do Sal

DS5

Silgueiros

ID4, ID5

Mangualde

ID6, ID38, ID39, ID40, ID42, ID43, ID44, ID45, ID46, ID47, ID48, ID53, ID55, ID56, ID57, ID58, ID62, ID65, ID70

Mealhada

ID41

Dois Portos

EVN1, EVN2, ENV7, E169, IO1, IO2, IO24, IO25, IO27, IO30, IO58, IO59, IO60, IO61, IO62, IO63, IO64, IO66, IO75, Agro1, Agro2, Agro3, Agro4, Agro5, Agro6, Agro7, Agro8, Agro9, Agro10, EVN19, EVN22, EVN26

Ourém

bOg38

Arruda dos Vinhos

IER1, IER2, IER3

Reguengos

IAL7, IAL8, IAL9, IAL10, IAL11, IAL12, IAL13, IAL14, IAL15, IAL16, IAL17, IAL18, IAL19, IAL20, IAL21, IAL22, IAL23, IAL24, IAL25, IAL26, IAL27, IAL28, IAL29, IAL30, IAL31, IAL33, IAL34, IAL35, IAL36, IAL37, IAL49, IAL50, IAL51, IAL52, IAL54, IAL59, IAL60, IAL61, IAL63, IAL64, IAL66, IAL71

Ribatejo

Alentejo


GENOMIC DIVERSITY OF O. OENI

Oenococcus oeni culture collection of the Center of Biodiversity, Functional and Integrative Genomics (BioFIG/FCUL, Lisboa, Portugal). In this study, the type strain O. oeni DSMZ 20252T (Deutsche Sammlung von Mikroorganismen und Zellkulturen, Braunschweig, Germany) was also included as were seven commercial malolactic starters (Viniflora oenos and Viniflora CH35 from Christian Hansen, Hørsholm, Denmark; GM from Microlife Technics, Sarasota, Florida, USA; Alpha, Beta and VP41 from Proenol, Vila Nova de Gaia, Portugal; PSU-1 from Pennsylvania University, Philadelphia, USA). Bacteria isolation. The bacteria were isolated by spreading 100 ml of wine samples onto plates with medium promoting the growth of Leuconostoc oenos [4] (MLO, tryptone 1%, yeast extract 0.5%, glucose 1%, fructose 0.5%, magnesium sulfate 0.02%, manganese sulphate 0.005%, ammonium citrate 0.35%, Tween 80 0.1%, tomato juice 10% and cysteine 0.05%), adjusted to pH 4.8. Cycloheximide (100 mg /l, Sigma-Aldrich, St. Louis, USA) was added to inhibit the growth of yeasts and molds. The plates were incubated anoxically inside jars containing an Anaerocult C system (Merck, Darmstadt, Germany) at 30ºC for 12 days. Colonies were then selected and further isolated as pure cultures by repeated streaking onto plates containing MTJ medium (70% MRS medium, Merck, Darmstadt, Germany; 30% tomato juice broth, Difco & BD, Franklin Lakes, NJ USA). Bacterial strains were maintained as frozen stocks at –80ºC in MTJ broth media and 20% (v/v) glycerol as cryoprotective agent. Working cultures were cultivated at 30ºC in MTJ broth, until stationary phase. Purity was checked by plating on corresponding agar media and microscopic examination. Identification of the bacterial strains. Bacterial isolates were first selected on the basis of their genus-specific Oenococcus characteristics. Catalase-negative and Gram-positive cocci were screened for the release of CO2 from glucose based on the production of gas in inverted Durham tubes containing MRS broth [15]. Since this property is shared by other LAB genera, the API 50 CHL system (bioMérieux, Craponne, France) was also used for species identification, according to manufacturer’s instructions. For DNA isolation, the strains were grown in MTJ broth until stationary phase at 30ºC. Cells were recovered by centrifugation and total DNA was obtained using an UltraClean Microbial DNA isolation kit (MO BIO Laboratories, Carlsbad, CA, USA). The DNA concentration was determined spectrophotometrically at 260 nm. Ethidium bromide staining was used to visualize the DNA after electrophoresis through a 1% (w/v) agarose gel (Seakem, Cambrex Bio Science, Rockland Maine, USA). Molecular identification of O. oeni strains was performed by 16S rRNA gene amplification and restriction analysis with the enzyme FseI as described by Marques et al. [31]. The results were confirmed by partial sequencing of the 16S rRNA genes of several randomly selected isolates and of the type strain O. oeni DSMZ20252T. 16S rDNA was amplified with the universal primers pA and pH [46] and the amplified fragments were purified using a Concert Rapid PCR purification system (Gibco BRL, Carlsbad, CA, USA). The sequencing reactions were performed using the internal primer 907R (5′-CCGTCAATTCMTTTRAGTTT-3′) at the MWG Biotech sequencing service (Ebersberg, Germany). The BLAST algorithm was used to compare the sequences with those of the U.S National Center for Biotechnology Information GenBank entries [1], and an identification at species level was assumed when at least 97% homology with the 16S rDNA sequence of a known species was determined [43]. M13-PCR fingerprinting. Genomic DNA from all O. oeni strains was used as template for PCR fingerprinting using as a primer the M13 minisatellite core sequence (csM13) [17] with the sequence 5′-GAGGGTGGCGGTTCT-3′. Approximately 50 ng of total DNA was subjected to PCR amplification in a reaction mixture containing 1× PCR buffer, 2.5 mM MgCl2, 200 mM of each deoxyribonucleotide (Invitrogen, Carlsbad, CA,

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USA), 50 pmol of primer (Invitrogen), and 1 U of Taq DNA polymerase (Invitrogen) in a final volume of 25 ml. The reaction mixtures were subjected to amplification in a thermocycler (Biometra, Goettingen, Germany). PCR cycling conditions consisted of: 94ºC for 5 min followed by 40 cycles of 94ºC for 1 min, 40ºC for 2 min and 72ºC for 2 min, plus one additional cycle at 72ºC for 7 min for chain elongation. PCR profiles were resolved by agarose (1.2% w/v) gel electrophoresis in 0.5× TBE buffer (50 mM Tris, 45 mM boric acid, 0.5 mM EDTA; Invitrogen), at 90 V for 3 h. DNA was visualized under UV light after ethidium bromide staining and the results photographed with Kodak 1D software (Kodak, USA). Data analysis. The images of the gels were captured using the Kodak electrophoresis documentation software 1D. The images were then saved as TIFF files and exported into the pattern analysis software package BioNumerics version 4.61 (Applied Maths, Kortrijk, Belgium) for processing. To obtain a measure of reproducibility, 12 isolates were randomly selected and analyzed in duplicate. The similarity between each duplicate pair was determined from an analysis based on a dendrogram computed with the Pearson correlation coefficient and the unweighted pair group method with arithmetic average (UPGMA) as the agglomerative clustering [47]. The reproducibility value was determined as the average value for all pairs of duplicates. Strain relationships, based on the molecular characters as determined from the fingerprints, were analyzed by hierarchical numerical methods with Pearson correlation similarity and UPGMA clustering. A cut-off value of 85% similarity was used to distinguish the clusters. The intraregional genomic diversity of O. oeni was evaluated with the indexes of Simpson [18] and Shannon [51]. The Simpson index (D) measures the probability of two non-related strains, taken from the tested population, belonging to two different genomic types and is based on the number of types and isolates for each type. The Shannon index (J’) is an evenness measure, expressing the observed diversity as the proportion of the possible maximum diversity and reflecting the homogeneity/heterogeneity of the distribution of isolates among the genomic types.

Results and Discussion Isolation and identification of the strains. From 81 wines (23 Dão wines, 24 Ribatejo wines and 34 Alentejo wines), a culture collection of 100 bacterial isolates (23 from Dão, 35 from Ribatejo and 42 from Alentejo) was obtained. A primary classification was performed based on cell morphology and cellular arrangement, Gram staining, catalase activity, and CO2 production from glucose. All isolates were Gram-positive, catalase negative, had similar cell arrangements (single, pairs and long chains), and were heterofermentative. The isolates showed the same fermentation pattern in API 50 CHL galleries, producing acid only from arabinose, esculin, fructose, galactose, glucose, and xylose. As six non-matching tests with the most closely related taxon (Lactobacillus brevis) were obtained, no acceptable phenotypic identification was possible using the API database. These results further reinforce the low reliability of this system as an identification tool for wine LAB, especially O. oeni, as described by others [34, and PhD thesis, R. Tenreiro 1995].


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Fig. 1. Representative M13-PCR profiles of several strains of Oenococcus oeni. Lanes 1 and 22: molecular ladder 1 kb plus (Invitrogen); lanes 2–21: O. oeni isolates from wines of different winemaking regions in Portugal.

However, the assays used for the primary classification offer a practical screening strategy and allowed us to conclude that the bacterial isolates belonged to a group of heterofermentative cocci LAB. The bacterial isolates were identified as O. oeni using the molecular methodology described by Marques et al. [31]. This method is based on 16S rRNA gene amplification with universal primers followed by restriction enzyme analysis with the endonuclease FseI, generating two fragments of 326 and 1233 bp. These results were confirmed based on the partial 16S rDNA sequence of some isolates (10%), randomly selected, and that of the type strain O. oeni DSMZ20252T. The DNA sequences were analyzed and compared using the BLAST network service (NCBI). The resulting fragments were approximately 98% similar to the 16S rRNA gene isolated from an O. oeni strain (GenBank accession number X95980), confirming that the isolated strains belonged to O. oeni species (data not shown). M13-PCR fingerprinting. The intraspecific diversity of our culture collection of 121 O. oeni strains obtained from three winemaking regions throughout Portugal was evaluated by M13-PCR fingerprinting analysis. The primer csM13 provided suitable fingerprints, with well defined amplification patterns (Fig. 1). The reproducibility of the fingerprints with primer csM13, estimated by the similarity average value for all pairs of duplicates, was 96 ± 0.4%. The DNA fingerprinting patterns were analyzed on BioNumerics software (v4.61,

Applied Maths) and the genetic similarity between the 121 O. oeni strains was displayed in the form of a dendrogram, depicted in Fig. 2. The cophenetic correlation coefficient was 0.93, which demonstrates the faithfulness of a dendrogram in preserving the pairwise distances between the original unmodeled data points. Although a value of 1.0 means that the concordance (as a linear relation) between the input data and the tree is theoretically perfect, in practice the relationship is unlikely to be totally linear. Romesburg [Cluster Analysis for Researchers. Wadsworth, Inc., USA, 1984] suggested that a cophenetic correlation of 0.8 or above indicates that the dendrogram does not greatly distort the original structure in the input data. However, the cophenetic correlation coefficient is not always a very reliable measure of the distortion due to a hierarchical model [12]. At a similarity level of 85%, the M13-PCR fingerprinting analysis organized the O. oeni strains in 49 genomic groups (27 different genomic clusters, represented by two or more isolates and 22 single-member genomic clusters). Six major genomic clusters (I–VI) were also defined, based on the overall hierarchical relationships, with distinctive composition in terms of the regional origin of the isolates. O. oeni strains from the Dão region were distributed into 19 genomic groups, including seven unique profiles as single-member clusters. Strains from the Ribatejo region were grouped in 22 genomic groups, with ten of them as single-member clusters, while those from the Alentejo region belonged to 14 genomic clusters, with five single-member clusters. Although nine out


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Fig. 2. Dendrogram of the 121 Oenococcus oeni isolates from different winemaking regions in Portugal based on the M13-PCR fingerprint analysis (Pearson correlation coefficient and UPGMA clustering). Alphabetic letters indicate the genomic groups of strains defined at an 85% similarity. The number of isolates from each region is displayed. (D: D達o; R: Ribatejo; A: Alentejo), as is the relative distribution of strains in each major cluster I-VI (as a percentage of the total number per region).


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Table 2. Oenococcus oeni diversity indexes for the isolates in winemaking regions Diversity index* Winemaking region

% Types

D

J’

Dão

47 (20/43)

0.93

0.89

Ribatejo

50 (18/36)

0.92

0.91

Alentejo

43 (18/42)

0.93

0.92

* D: Simpson diversity index; J’: Shannon diversity index; % Types: (number of types/number of isolates)×100, in each winemaking region.

of the 27 genomic clusters (A, D, E, F, H, L, N, O, and R) comprised a mixture of O. oeni isolates from more than one region (9 isolates from Dão, 10 from Ribatejo, and 16 from Alentejo), the remaining 18 genomic clusters were formed only by isolates from the same region (6 from Dão, 5 from Ribatejo, and 7 from Alentejo), pointing to a regional partitioning of the genomic diversity in this species. O. oeni isolates from the same wine were distributed by different clusters, which indicated the presence of different types of O. oeni strains in the same wine. Seven commercial malolactic starters (VP41, Alpha, Beta, Viniflora oenos, Viniflora CH35, GM, and PSU-1) and

the O. oeni type strain (DSMZ 20252T) were also submitted to fingerprint analysis. For each starter, a unique and discriminative DNA fingerprint was obtained, with the exception of the starters Viniflora oenos and Viniflora CH35, which were grouped in the same genomic cluster (data not shown). Each of these commercial O. oeni strains has different winemaking origins. Shannon-Weaver and Simpson diversity indexes were applied to assess the intra-regional genomic diversity of O. oeni strains from the different winemaking regions of Portugal (Table 2). Both the percentage of types and the values of the Simpson and Shannon-Weaver diversity indexes, obtained with M13-PCR fingerprinting, were closely similar and high enough for each winemaking region so as to confirm the high genomic diversity of O. oeni, as previously determined by MLST, macrorestriction, and physiological characterization [35,39,45]. Evaluation of regional distribution of Oenococcus oeni genomic groups. Among the 49 genomic groups defined by M13-PCR fingerprinting analysis (Fig. 2), 40 were unique to a particular winemaking region. Seven genomic groups (A, E, F, H, N, O, and R) were shared by two regions each, while the remaining two (D and L) were

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Fig. 3. Regional distribution of the 49 M13-PCR genomic groups of Oenococcus oeni isolates from Portuguese wines of different winemaking regions.


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the only ones that included isolates from the three regions. When the uniqueness/commonness ratio of genomic groups was analyzed for each winemaking region (Fig. 3), a 2:1 proportion was found between specific genomic profiles unique to that region and genomic profiles shared with at least another region. This pattern of geographically associated diversity is also obvious from the composition of the six major genomic clusters (I–VI; Fig. 2) in terms of the regional origin of the isolates. Overall, these data point to a global partitioning of the genomic diversity of O. oeni according to the geographical origin of the isolates and to the occurrence either of an alopatric or ecological speciation process in this wine species. Similar conclusions have been reached in other bacterial groups subjected to highly selective or heterogeneous environments [49]. During the last several years, the diversity of O. oeni strains within and around wineries has been extensively examined. The results obtained from the application of different techniques, such as studies of the patterns of total soluble cell proteins [9], 16S and 23S sequence analyses [32], RAPD-PCR [53] and DD-PCR [22], suggest that O. oeni is a homogeneous species. More recently, de las Rivas et al. [7] submitted five genes (gyrB, ddl, mleA, pgm, and recP) to MLST in order to evaluate the allelic diversity and population structures of various oenococcal isolates. This analysis was able to completely differentiate 18 strains, suggesting a higher level of genetic heterogeneity among oenococcal isolates. These authors argued that the high level of diversity in O. oeni is an example of a panmictic genetic population, in which the high frequency of recombination among constituents results in the randomization of sequences and the generation of linkage equilibrium. Marcobal et al. [20] showed that high mutation rates in O. oeni explain some of the discordant observations reported for this species. They suggested that the lack of mutS and mutL in O. oeni, combined with the high mutation rate, accounts for the high allelic diversity among strains, as seen from the MLST data. In oenology, biodiversity is strictly correlated to habitat. Consequently, it is conditioned by selective factors that inhibit or favor the presence not only of one species over the other but also of a strain or biotype. The present study aimed to differentiate O. oeni isolates from different winemaking regions of Portugal and to reveal the underlying patterns of regional/geographical strain diversity. Our results confirm the predominance of O. oeni species in the hostile conditions prevailing in wine and the high adaptation capacity of the various strains in the winery environment [53]. M13-PCR fingerprinting allowed the genomic discrimination of O. oeni

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while a cluster analysis of M13-PCR patterns revealed a correlation between strain distribution and geographical area of origin. This approach can be useful in following the evolution of O. oeni populations during malolactic fermentation in wine and in assessments of the O. oeni ecology in wine. Acknowledgements. This work was supported by Agro Medida 8.1 Program, Project No. 33, Agência de Inovação, IDEIA Program, and Project SAFEBACTOWINEBAGS 70/00105. A. P. Marques thanks Fundação para a Ciência e Tecnologia for the PhD grant SFRH/BD/14389/2003. Competing interests. None declared.

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RESEARCH ARTICLE INTERNATIONAL MICROBIOLOGY (2011) 14:163-171 DOI: 10.2436/20.1501.01.145 ISSN: 1139-6709 www.im.microbios.org

A flow cell simulating a subsurface rock fracture for investigations of groundwater-derived biofilms Matthew Starek,1 Konstantin I. Kolev,2 Laura Berthiaume,1 C. William Yeung,1 Brent E. Sleep,2 Gideon M. Wolfaardt,1 Martina Hausner1* 1

Department of Chemistry and Biology, Ryerson University, Toronto, Ontario, Canada. 2 Department of Civil Engineering, University of Toronto, Toronto, Ontario, Canada

Summary. Laboratory scale continuous-flow-through chambers (flow cells) facilitate the observation of microbes in a controlled, fully hydrated environment, although these systems often do not simulate the environmental conditions under which microorganisms are found. We developed a flow cell that mimics a subsurface groundwater-saturated rock fracture and is amenable to confocal laser scanning microscopy while allowing for the simple removal of the attached biomass. This flow cell was used to investigate the effect of toluene, a representative contaminant for non-aqueous phase liquids, on groundwater-derived biofilms. Reduced average biofilm biomass and thickness, and diminished diversity of amplifiable 16S rRNA sequences were observed for biofilms that developed in the presence of toluene, compared to the biofilms grown in the absence of toluene. The flow cell also allowed the detection of fluorescent protein-labelled cells. [Int Microbiol 2011; 14(3):163-171] Keywords: Pseudomonas putida · biofilms · flow cells · groundwater · rock fractures · confocal microscopy

Introduction It is widely accepted that microbes in nature tend to exist in biofilms—aggregates of cells and their extracellular substances—as opposed to a singular, planktonic existence [8]. A key aspect in the study of biofilms is the ability to perform non-invasive analyses on fully hydrated biofilms, in order to preserve their physical characteristics, as well as the spatial relationships of cells within biofilm communities. This is

*Corresponding author: M. Hausner Department of Chemistry and Biology Ryerson University 350 Victoria Street Toronto, ON, Canada, M5B 2K3 Tel. +1-4169795000, ext 6553. Fax +1-4169795044 Email: martina.hausner@ryerson.ca

especially relevant when observing biofilms in flow systems, as perturbations in the surrounding aquatic environment (or furthermore, total removal of a biofilm from its innate aquatic environment) may cause significant changes in biofilm structure and function. The non-invasive observation of biofilms can be achieved by using flow cells, (i.e., laboratory-scale continuous flow-through chambers), which are amenable to microscopic investigation. Confocal laser scanning microscopy (CLSM) is a non-invasive technique that has been used to study both the composition and spatial arrangement of microbial populations within a biofilm [25,27] and the three dimensional architecture of the biofilm [33]. CLSM has also been used to investigate plasmid transfer in biofilms using fluorescent proteins such as green fluorescent protein (GFP) and red fluorescent protein (DsRed) [4–7,12,33,42].


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According to Pamp et al. [34], flow cell technology in combination with CLSM is “the gold standard in biofilm research” because it allows for observations of developmental processes in biofilms (in combination with fluorescent genetic tags), spatial organization and composition of laboratory grown biofilms in real time under continuous, non-invasive and fully hydrated conditions at the single cell level [34]. Flow cells of varying design have been employed for a variety of research purposes. These applications include the growth rate of microbes in a particular region of a biofilm [11], the spatial orientation of biofilm microbes in biofilms exposed to xenobiotics [14,48], the impact of nutrient sources on biofilm morphology [29], the effect of biofilm growth on bulk flow and solute transport [20], the influence of hydrodynamic conditions on biofilm development [43], gravimetric, optical and electrochemical investigations of microbial biofilm formation in aqueous systems [10], analysis of the transfer of plasmids between biofilm microbes [1,12,18,50], and investigations of microbial responses to environmental gradients [46]. The channels in which biofilms develop within flow chambers can be as small as 3 mm × 42 mm [48] or as large as 21 cm × 28 cm [20]; however, most flow cell channels used are closer to 3 mm × 42 mm [48]. Biofilms are ubiquitous in the environment and play an important role in a plethora of processes, including biofouling, transport processes, nutrient cycling and contaminant degradation. Many xenobiotics become adsorbed to biofilms [9,47], where they exert selective pressure on attached microbial communities resulting in the adaptation of microorganisms to the contaminant and their potential degradation. Microbial degradation is of great importance in groundwater environments. Many aquifers are situated in fractured rocks and are vulnerable to contamination from non-aqueous phase liquids (NAPL) such as hydrocarbons and chlorinated solvents. In geographical areas that rely on groundwater as a source of potable water, NAPL contamination of groundwater seriously compromises a safe and satisfactory supply of drinking water [36]. The potential of bioremediation to prevent the spreading of contamination in subsurface soils has been widely accepted. Biologically enhanced dissolution of residual source zones of NAPL in soils has also been the subject of significant interest as a potential remediation technology [38]. However, there are few studies on biodegradation processes in fractured rocks [20]. As the microbial activity in fractured rocks will be primarily associated with biofilms, elucidation of the role of biofilm processes in fractured rocks in the presence of NAPL is paramount.

The main objective of this study was to design, optimise and test a microscopy-amenable laboratory-scale flow cell that would simulate the flow of groundwater through a rock fracture aperture. This flow cell utilized a rock (shale) wafer as an attachment surface for the growth of biofilms and was employed for analysing architecture of groundwater-derived biofilms exposed to toluene—a model NAPL groundwater contaminant. Biofilms associated with the rock attachment surface could be collected for subsequent DNA extraction and fingerprinting of biofilm microbial communities. This flow-through system was subsequently used to evaluate the possibility of detecting fluorescent-protein-labelled strains, such as those of interest in bioaugmentation studies utilising the transfer of plasmids encoding catabolic genes [3–7, 32,42].

Materials and methods Flow cell construction and other apparatus. Flow cells were constructed with the goal of simulating a model rock-fracture aperture (Fig. 1A and 1B). Teflon blocks were used for flow cell construction (outer dimensions: 2.5 cm height, 5 cm width, 7.5 cm length; inner dimensions: 2.5 cm height, 3.25 cm width, 5 cm length) (Fig. 1A). Gutters were milled at both ends of the Teflon block in the vertical plane using a 3-mm end mill piece and a Sherline model 5400 mill (Sherline, Vista, CA, USA) (Fig. 1A). Holes were drilled in both ends in the horizontal plane using a 3.175 mm drill bit and subsequently threaded. Swagelok brass straight male tube connectors (3.175 mm national pipe thread, tapered thread) were inserted into the threaded holes. Shale was used as a rock surface for the flow cells (2 cm height, 2.5 cm width, and 5 cm length). The wafer of shale was secured in the opening of the Teflon block using a two-part epoxy glue (Plastic steel putty [A]) #10110, ITW, Devcon, Danvers, MA, USA). A cover slip (60 mm × 35 mm, Electron Microscopy Sciences, Ft. Washington, PA, USA) was secured over the rock wafer with solvent-resistant liquid viton (Pelseal, Newtown, PA, #2077) in order to prevent the volatilisation of toluene (Fig. 1B). Cover slips were used to allow for non-invasive examination of biofilms on the rock wafer surface by confocal microscopy (Fig. 1B). The complete experimental system set up is illustrated in Fig. 1C. Microorganisms were introduced into the flow cell through a Mininert valve (3.175 mm; Sigma-Aldrich Canada Ltd., Oakville, ON, Canada) in a Swagelok female branch tee (3.175 mm) (Fig. 1C; part 4). Teflon tubing segments were used to connect the branch tee and the straight tube connector and to join the flow cell to the effluent receptacle (Fig. 1C; part 6). A bubble trap (Fig. 1C; part 3) was positioned between the peristaltic pump (Fig. 1C; part 2) and the Swagelok brass female branch tee (Fig. 1C; part 4). Silicon tubing was used to connect the bubble trap with the flow cell. The bubble trap consisted of a 10 ml syringe, a silicon tubing inlet positioned near the top of the syringe and a silicon tubing outlet positioned near the bottom of the syringe. A multi-channel peristaltic pump (Watson-Marlow model 205S, Wilmington, MA) was used to create flow. The flow rate was set to 0.5 rpm, which corresponded to a volumetric flow rate of 3.2 ml/h. Strains, inoculum, and culture conditions. Tryptic soy broth (TSB) (EMD, Brampton, ON) was used for all flow cell experiments.


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Fig. 1. A schematic diagram (A) showing the dimensions (cm) and a photograph (B) of the microscopy-amenable flow cell designed and constructed in this work. The entire experimental system is shown in (C). The flow cell simulated a fractured-rock aperture and allowed the analysis of rock-associated biofilm communities in real time, in situ and under fully hydrated conditions. Gutters (G) were included in the design to ensure uniform flow of medium over the rock surface. Swagelok straight male tube connectors (TC) were inserted into holes drilled in both ends of the flow cell. A cover slip was secured over the rock wafer with solvent-resistant synthetic rubber (SR) in order to prevent toluene volatilisation. Growth medium was pumped from a reservoir vessel (1) using a peristaltic pump (2) through a bubble trap (3); a Mininert valve in a Swagelok brass female branch tee was used to introduce microoganisms into the flow cell and (4) into the flow cell containing a rock wafer (5). Effluent was pumped into an effluent receptacle (6).

Concentrations of TSB used in this study are based on a 100% concentration of 30 g/l dissolved in distilled water as recommended by the manufacturer. Luria Bertani (LB)-agar plates were prepared using 15 g/l of LB powder (Bio Basic Inc., Markham, ON, Canada) in distilled water. The inoculum for flow cell experiments was prepared using a modified dual-dilution method adapted from Caldwell and Lawrence [11]. Briefly, a groundwater sample from an uncontaminated aquifer in Cambridge (ON, Canada) was enriched with TSB in a flow system which had glass beads (2 mm diameter) as an attachment surface. TSB medium (0.1%) was pumped through a sterile 250-ml beaker covered with sterile aluminum foil containing the glass beads at a rate of 3.2 ml/h with a Watson-Marlow 205S peristaltic pump (Watson-Marlow, Wilmington, MA, USA). Microorganisms that did not attach to the glass beads were therefore washed out of the beaker and discarded. After two weeks of flow, the glass beads were harvested and stored at –20°C in a mixture of equal parts glycerol and 0.1% TSB medium. Inoculum for flow cell experiments was prepared by enriching bead-attached microorganisms with 1.0% TSB while shaking overnight at 250 rpm. Strain Pseudomonas putida SM1443::gfp2x-pWW0::dsRed [Bathe S 2004, Ph.D. Thesis, Technical University of Munich] was used to evaluate the detection of GFP-labelled cells against the rock wafer background. This strain carried chromosomally encoded kanamycin resistance and gfp genes

[12] and harboured plasmid pWWO tagged with dsRed, under the control of a lac-promotor [12,40]. The donor strain expressed constitutive GFP fluorescence and fluoresced green upon excitation with blue light. DsRed fluorescence was repressed due to a chromosomally encoded lac-repressor on the lac-promoter controlled dsRed gene [12]. Upon conjugative plasmid transfer to potential recipients, transconjugants lacking the chromosomally encoded lac-repressor gene had red fluorescence. The TOL plasmid pWWO used in these experiments was also modified such that it contained a gentamicin resistance gene. Accordingly, the donor strain was maintained on LB-agar plates amended with kanamycin (50 mg/l) and gentamicin (25 mg/l). A DsRed-expressing transconjugant strain, obtained from plate conjugation experiments [Starek M, 2010, M.Sc. Thesis, Ryerson University, Toronto, Canada], was used to evaluate the detection of DsRed-labelled cells against the rock wafer background. Transconjugant cells were maintained on LBagar plates amended with gentamicin (25 mg/l). Flow cell inoculation and operation. Six flow cells were used in this work. They were in operation at 24 ± 1ºC for 12 days after inoculation. A set of flow cells consisted of a flow cell with toluene-exposed biofilm and another flow cell used as a negative control containing untreated biofilm. One set of flow cells was used for confocal microscopy investigations of


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biofilm architecture. A second set was used for DNA-based investigations of the effect of toluene on microbial diversity. Finally, two additional flow cells were used to evaluate the detection of GFP and DsRed-labelled cells against the rock wafer background. All tubing, media and glassware were autoclaved before use at 121°C for 15 min. Upon assembly, 2% sodium hypochlorite solution (v/v) was pumped through the system for 3 h. Autoclaved distilled water was then pumped through the system for 24 h. Next, 1.0% TSB was pumped through the system for 3 h to condition the attachment surface. The flow cell was inoculated with 1 ml of a previously prepared overnight culture of a groundwater-derived microbial inoculum, as described above. Flow was stopped for 2 h following inoculation and then resumed at 3.2 ml/h with 1.0% TSB. After 24 h of flow, 0.1% TSB was pumped into the flow cell for the remainder of the experiment in order to simulate a low-nutrient groundwater environment. To simulate NAPL contamination, 600 μl of neat toluene was introduced into the flow cell through the Mininert valve in a Swagelok brass female branch tee (Fig. 1C; part 4). Toluene remained in the organic phase as an irregularly shaped globule of approx. 10 mm in diameter in the flow cell between the cover glass and rock surface, simulating a contaminated rock fracture. Biofilm architecture analysis. Medium flow was stopped after 12 days of biofilm development and the biofilms were stained with 500 μl of 50 mM acridine orange (EMD, Mississagaua, ON, Canada) dissolved in sterile water. The flow cells were covered with aluminum foil to avoid photobleaching of the acridine orange signal, and kept for 15 min before flow was resumed for 5 min to remove any unbound stain or stained planktonic cells. Flow cells were then examined with a confocal laser scanning microscope (Zeiss, LSM510, Jena, Germany). Images were obtained using a 488-nm laser and a 505- to 530-nm band-pass emission filter. A 20×/0.75 Fluor objective lens (Zeiss, Jena, Germany), with a working distance of 0.66 mm, was used together with a 2× digital zoom. Image stacks were collected at 2μm increments. Fifteen image stacks were analysed from toluene- and non-toluenetreated microbial cultures using the COMSTAT program [19] for the average quantification of biofilm biomass and biofilm thickness. COMSTAT is an image analysis script that runs in MATLAB (The Math Works, MA, USA). Average biofilm biomass was quantified as the volume of biomass per substratum area (μm3/μm2). Thickness was measured as the mean thickness of the biofilm (μm). A single factor analysis of variance (ANOVA) (p = 0.05) using Excel’s data analysis tool was utilized for statistical analysis of differences in the biofilm biomass of toluene-exposed and untreated biofilms. Detection of GFP or DsRed-expressing cells in the flow cell. To test the limits of detection of donor and transconjugant cells against the heterogeneous rock wafer background, cells expressing GFP or DsRed were injected into the flow cell through the inoculation port. Medium flow was stopped for 1 h, in order to facilitate the attachment of cells, and then resumed. CLSM was then used to examine the flow cells for the presence of fluorescent cells, with the detection of autofluorescence emanating from the rock wafer surface minimised using band pass emission filters. A 505- to 530-nm emission filter was used for the detection of GFP fluorescence, and a 560- to 615-nm emission filter for the detection of DsRed fluorescence. Images were taken 1 h after inoculation and subsequently every third day. The flow cell was in operation for 12 days after inoculation. Biofilm collection and DNA extraction. Biofilm samples from the surface of the rock wafer inside the flow cell were obtained at the end of

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the experiment by clamping the flow system tubing and removing the flow cell from the flow system, followed by aseptic removal of the Viton sealant. A cell scraper (#179707, Thermo Scientific, Rochester, NY, USA) was used to scrape the surface of the rock wafer and cover glass. Collected biomass was placed in saline solution and centrifuged at 5000 ×g to a pellet for DNA extraction. From each flow system, 50 ml of effluent was collected at the end of the experiment and centrifuged at 5000 ×g to a pellet for DNA extraction, performed using a GeneElute Bacterial Genomic DNA kit (#NA2110, Sigma-Aldrich, Oakville, ON, Canada). PCR and denaturing gradient gel electrophoresis (DGGE). Primers U341F-GC (5′-CCTACGGGAGGCAGCAG-3′), which had a GC clamp attached (5′-GGCGGGGCGGGGGCACGGGGGGCGCGGCGG GCGGGGCGGGGG-3′) at the 5′ end [30], and U758R (5′-CTACCA GGGTATCTAATCC-3′) were used to amplify a 418-bp fragment corresponding to positions 341–758 in the Escherichia coli 16S sequence within the variable regions V3 and V4 [35]. Primers were synthesized by The SickKids Centre for Applied Genomics (TCAG) Synthesis Facility (Toronto, ON, Canada). The 50-μl PCR reaction mixture contained 1 μl of template DNA, autoclaved distilled water, 25 pmol of both the forward and reverse primer, 10× BSA (New England BioLabs, Pickering, ON), 200 μM of each dNTP (New England BioLabs, Pickering, ON) and 2.5 units of Taq polymerase (New England BioLabs, Pickering, ON) in 1× Taq buffer (10 mM Tris-HCl pH 9.0, 50 mM KCl, 1.5 mM MgCl2) (New England BioLabs, Pickering, ON). The PCR protocol was as follows: 96°C for 5 min and thermocycling at 94°C for 1 min; an annealing temperature of 65°C with a 1°C decrease every 1 min cycle for 20 cycles, and a 3 min elongation time at 72°C. Additional cycles (15–20) were carried out at annealing temperatures of 55°C [51]. Upon completion of the protocol, the samples were loaded into a 1% agarose gel with SYBR Safe DNA gel stain (Invitrogen, Burlington, ON), visualized using the Invitrogen Safe Imager 2.0 (Invitrogen) and quantified using a serial dilution of a 100-bp molecular weight (MW) ladder (MBI Fermentas, Amherst, NY, USA) to create a standard curve. Each sample was amplified three separate times using the same PCR protocol, to minimize PCR bias. The products were combined, cleaned using the IBI Gel/PCR DNA fragments extraction kit (IBI Scientific, Peosta, IA) , and concentrated, if necessary, using a Savant DNA110 speed vacuum (Fisher Scientific Limited, Nepean, ON, Canada). Quantification was performed using the same agarose gel setup and MW ladder as mentioned previously. The DGGE gel consisted of 8% polyacrylamide with a denaturing gradient of 30–70% (7 M urea and 40% deionized formamide were defined as 100% denaturant) and was cast using a gradient former (BioRad Laboratories, Mississauga, ON, Canada). Approximately 500 ng of the 16S rRNA gene product was loaded into each well of the DGGE gel. The gel was run in a DCode Universal Mutation Detection System (BioRad Laboratories, Mississauga, ON). Electrophoresis was carried out at a constant voltage of 80 V for 16 h at 60°C. All gels were stained for 30 min in SYBR Gold (Invitrogen, Burlington, ON) with gentle agitation followed by brief destaining in 1× TAE. The gel was imaged using a Gel Logic 1500 Imaging System (Kodak, Rochester, NY, USA) and the images then analysed using GelCompar II v6.5 (Applied Maths, Sint-Martens-Latem, Belgium) to generate dendrogram profiles. The genotypes were visually detected based on the presence or absence of bands in the different lanes. A band was defined as present if the ratio of its peak height to the total peak height in the profile was >5%. After conversion and normalisation of the gels using GelCompar, the degrees of similarity of the DNA pattern profiles were calculated using the Dice similarity coefficient [13] and dendrogram patterns were clustered by the unweighted pair group method using arithmetic average (UPGMA) groupings to generate a similarity coefficient (SAB) matrix.


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Fig. 2. Detection of GFP-expressing strain Pseudomonas putida SM1443::gfp2x-pWW0::dsRed and red fluorescent protein-expressing cells within the flow cell. DsRed-expressing transconjugants were visualized using confocal microscopy on the surface of the rock wafer in the flow cell 1 h after inoculation (A) and 12 days after inoculation (B). GFP-expressing cells were detected 4 days after inoculation on the surface of the rock wafer (C). Autofluorescence of the rock wafer was minimised by using band pass detection filters to collect both DsRed and GFP signals. Scale bar: 10 Îźm.

Results and Discussion Flow cell design and construction. The subsurface environment is characterized by low flow and large surface-to-pore volume ratios. Therefore, conventional experimental systems that do not provide comparable flow rates and surfaces for biofilm formation may introduce selection pressure for opportunistic species with little relevance in situ. The inclusion of gutters in the flow cell design ensured uniform flow of the growth medium used to support biofilm growth on the rock wafer surface (Fig. 1A,B). Glass is the most common attachment surface that has been used in conventional flow cells [23,43], while the flow cell body may be manufactured from Teflon [M. Starek. M.Sc. Thesis], plexiglass [49] or stainless steel [18,23,31, 43,50]. For studies of subsurface microorganisms, geological material (e.g., rock or mineral wafers) that simulates the natural environment, as an attachment surface for biofilm development, is preferable to glass. Previous studies of the microbial weathering of sulphide minerals employed flow cells with polished thin sections prepared from sulphide mineralcontaining rocks as microbial attachment surfaces [24]. While these flow cells provide environmental attachment surfaces for biofilm development, they are typically not closed system (a glass cover slide is not sealed to the top of the flow cell), and thus are not suitable for experiments involving volatile substances. In contrast, in the system des-

cribed here (Fig. 1C), Teflon was used for flow cell (Fig. 1B) construction, and Teflon tubing was placed between the medium reservoir and the flow cell, thus allowing the testing of volatile compounds, such as toluene, the model NAPL substrate used in this study. Toluene, together with benzene, ethylbenzene and xylene (BTEX), are aromatic compounds characterized by a relatively low solubility in aqueous solutions. Consequently, they are often present in groundwater as NAPLs [2]. Aerobic degradation of BTEX compounds can be accomplished by microorganisms expressing either monooxygenases or dioxygenases, but other pathways have also been described [41]. The TOL plasmid pWWO [16], initially isolated from Pseudomonas putida-mt2 [45], contains genes that encode monooxygenases that degrade toluene/xylene [16]. In addition, the TOL plasmid pWWO encodes and constitutively expresses genes necessary for the transfer of the plasmid from host to recipient [16]. Other hosts, in addition to Pseudomonas strains, have been reported to successfully receive the TOL plasmid, including members of the genera Erwinia and Serratia [28]. Toluene can be also degraded in the absence of oxygen by different microorganisms, including the beta-proteobacterial species within the Thauera and Azoarcus genera [44]. Microscopic observations. The transfer of catabolic plasmids such as the TOL plasmid can be monitored with the use of fluorescent proteins, including GFP and DsRed


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Fig. 3. Dendrogram of bacterial DGGE with cluster analysis of the banding patterns of fingerprints of toluene-exposed biofilm (B+), untreated biofilm (B–), effluent collected from the untreated biofilm (E–) and effluent collected from the toluene-treated biofilm (E+). A similarity coefficient (SAB) matrix was generated using the unweighted pair group method based on arithmetic average (UPGMA) groupings.

Effect of toluene on microbial diversity. DGGE fingerprinting of biofilm and effluent samples suggested that the differences in biofilm structure detected by confocal microscopy and image analysis were accompanied by changes in community composition. The DGGE profiles (Fig. 3) of amplified 16S rDNA fragments extracted from toluene-exposed biofilm and those from untreated biofilm differed from each other. The DGGE fingerprint of the

untreated biofilm showed greater band diversity. For example, the band corresponding to band 6 in lanes B–, E–, and E+ (Fig. 3) was not detected in the toluene-exposed profile (B+). Similarly, the band corresponding to band 3 in lanes B–, E– and E+ (Fig. 3) was not detected in the toluene-exposed biofilm profile (lane B+, Fig. 3). While three prominent bands (bands 1, 5 and 7, Fig. 3) were clearly visible in the toluene-exposed biofilm profile

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[4–7,32,42]. With the aid of bandpass filters it was possible to minimise rock autofluorescence, thus allowing the detection of red-fluorescing cells (transconjugant cells, Fig. 2A, 2B) and of green-fluorescing cells (donor cells, Fig. 2C) using 560–615 nm and 505–530 nm emission filters, respectively. This is of importance, as fluorescent proteins, among other uses, are employed in the study of gene transfer between bacteria [4–7,32,42]. Horizontal gene transfer (HGT) is a successful mechanism to spread plasmids harbouring genes encoding degradative enzymes in model wastewater and model soil systems, in which a lab-designed donor strain has been introduced into the model system [1, 4–7,32,42]. There is not, however, much information with respect to the transfer of degradative plasmids between bacteria in model groundwater systems [21,39] and, more specifically, in rock-fracture apertures. Therefore, the flow cell system described in this work is a useful tool with which to evaluate the feasibility of gene transfer in rock fracture aquifers [M. Starek. M.Sc. Thesis]. Transconjugant red-fluorescing cells were observed attached to the rock surface 1 h after inoculation (Fig. 2A), indicating the tendency of these groundwater bacteria to associate with and colonise solid surfaces. Furthermore, the transconjugant cells were observed for the duration of the experiment (12 d, Fig. 2B), which is evidence of subsequent biofilm formation. Image analysis revealed that biofilms grown in the presence of toluene occupied an average biovolume of 1.1 μm3 per μm2 footprint area, and were on average 2.6-μm thick while untreated biofilms occupied an average of 1.9 μm3 per μm2 footprint area and were on average 7.1-μm thick. Biovolume is the biomass volume per substratum (rock surface) area and provides an estimate of biofilm biomass [19]. The thickness value reflects the spatial size of the biofilm [19]. In our study, the biovolume and thickness values obtained for toluene-exposed biofilms were significantly different from values obtained for biofilms grown in the absence of toluene, as revealed by a single-factor ANOVA analysis using a p = 0.05.


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(B+), only bands 1 and 7 were clearly visible in the untreated biofilm profile (B–). Band 5 was present in the untreated biofilm profile (B–) but was less intense than the corresponding band in the toluene-treated biofilm profile (B+). Two of the three bands (5 and 7, in lanes B+ and B–, Fig. 3) were not visible in the effluent profiles (lanes E– and E+), suggesting that the microorganisms corresponding to these bands were not frequently shed into the effluents. Effluent sample profiles mostly reflected the unexposed-biofilm profile, except for band 2 in lanes E– and E+ and band 4 in lanes E– and E+ (Fig. 3), which were not visible in the biofilm profiles. This could be explained either by preferential shedding of these particular species into effluents or enhanced proliferation in the effluent reservoir. Since the toluene-exposed biofilm profile differed from the unexposed-biofilm profile, the fact that the effluent profiles were highly similar suggests that the same types of microorganisms detached from both treated and untreated biofilms early in the experiment and then proliferated in the effluent vessels. DGGE profiles from biofilm and effluent samples (Fig. 3) revealed a high similarity, with a binary association coefficient (SAB value) of 93.3% for the two effluent fingerprints. The effluent profiles showed 74.2% similarity to the untreated biofilm profile. The toluene-exposed biofilm profile was the least similar to the other three profiles, with only 66.6% of the SAB value. The DGGE data indicated that no major selection of specific microorganisms occurred due to toluene exposure; however, toluene exposure led to changes in the initial microbial community, as demonstrated by a decrease in the number of bands in the toluene-exposed biofilm profile compared to the unexposed biofilm and effluent sample profiles. Similar observations were made by Hendrickx et al. [17], who investigated the dynamics of bacterial aquifer communities during contact with a toluene-contaminated plume. In that study, the richness of 16S rRNA sequences was lower in the toluene contaminated locations than in the uncontaminated locations, a finding in contrast to the observations made by Shi et al. [37], who observed similar relative abundances of Proteobacteria and gram-positive bacteria in fuel-contaminated and uncontaminated aquifer materials. Lee et al. [26] observed shifts in groundwater community profiles, in addition to the persistence of some members with varying levels of BTEX contamination. They noted that changes in the community profiles were a function of BTEX concentration, dissolved oxygen concentration, and carbon source. Ji et al. [22] recorded changes in the community profile of a microbial

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community in BTEX-contaminated soil and an increase in Actinobacteria and Bacillus populations. They further observed bands that were unique to contaminated and uncontaminated samples. Similarly, Fahy et al. [15] observed a shift from Betaproteobacteria to Actinobacteria in response to benzene exposure. The experimental flow cell described here offers a way to observe and evaluate biofilm architecture and composition as well as the remediation potential of microbes or mixed microbial communities. In our study, the exposure of biofilms in flow cells to toluene led to a reduction of biofilm biomass. Further, DGGE fingerpriniting of PCR-amplified 16S rRNA fragments demonstrated that microbial diversity in the toluene-exposed biofilm was diminished. The flow cell system also allowed for the visualisation of GFP-tagged donor cells and DsRed-expressing transconjugant cells against the background autofluorescence associated with the rock wafer surface, a useful feature for gene transfer studies in simulated rock fracture environments.

Acknowledgements. This work was supported by a National Sciences and Engineering Council of Canada (NSERC) Discovery ProgramIndividual grant to MH (grant no. 355606-2008), by Ryerson University and by funding to BES from the Ontario Ministry of the Environment Best-inScience Program. We are grateful to David Jenkins (Ryerson University) for generating the flow cell and experimental system drawings. Competing interests. None declared.

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47. Wolfaardt GM, Lawrence JR, Headley JV, Robarts RD, Caldwell DE (1994) Microbial exopolymers provide a mechanism for bioaccumulation of contaminants. Microb Ecol 27:279-291 48. Wolfaardt GM, Lawrence JR, Hendry MJ, Robarts RD, Caldwell DE (1993) Development of steady-state diffusion gradients for the cultivation of degradative microbial consortia. Appl Environ Microbiol 59: 2388-2396 49. Wolfaardt GM, Lawrence JR, Robarts RD, Caldwell SJ, Caldwell DE (1994) Multicellular organization in a degradative biofilm community. Appl Environ Microbiol 60:434-446 50. Wuertz S, Hendrickx L, Kuehn M, Rodenacker K, Hausner M. 2001. In situ quantification of gene transfer in biofilms. Method Enzymol 336: 129-143 51. Yeung CW, Lee K, Greer CW (2011) Characterization of the bacterial community structure of Sydney Tar Ponds sediment. Can J Microbiol 57:493-503


RESEARCH ARTICLE INTERNATIONAL MICROBIOLOGY (2011) 14:173-181 DOI: 10.2436/20.1501.01.146 ISSN: 1139-6709 www.im.microbios.org

Genetic characterization of the mechanisms of resistance to amoxicillin/clavulanate and third-generation cephalosporins in Salmonella enterica from three Spanish hospitals María de Toro,1,2 Yolanda Sáenz,1 Emilia Cercenado,3 Beatriz Rojo-Bezares,1 Marta García-Campello,4 Esther Undabeitia,5 Carmen Torres1,2* 1

Molecular Microbiology Area, Center for Biomedical Research of La Rioja (CIBIR), Logroño, Spain. 2Biochemistry and Molecular Biology Area, University of La Rioja, Logroño, Spain. 3Servicio de Microbiología, Hospital General Universitario Gregorio Marañón, Madrid, Spain. 4Microbiology Service, Pontevedra Hospital Complex, Pontevedra, Spain. 5 Microbiology Laboratory, San Pedro Hospital, Logroño, Spain

Summary. The mechanisms of antimicrobial resistance were characterized in 90 Salmonella enterica isolates either resistant or with intermediate resistance to amoxicillin/clavulanate (AMCR/I) or resistant to third-generation cephalosporins (C3GR). These isolates were recovered in three Spanish hospitals during 2007–2009. The C3GR phenotype was expressed by three isolates that carried the following extended-spectrum β-lactamase genes: phage-associated blaCTX M-10 in S. Virchow, blaCTX-M-14a surrounded by ISEcp1 and IS903 in S. Enteritidis, and blaCTX-M-15 linked to ISEcp1 and orf477 in S. Gnesta (first description in this serotype). The AMCR/I phenotype was found in 87 isolates (79 S. Typhimurim, 7 S. Enteritidis, and one S. Thompson). The blaPSE-1 gene, followed by blaOXA-1 was mostly found among S. Typhimurim, and the blaTEM-1 gene among S. Enteritidis. Three different gene combinations [blaPSE-1+floR+aadA2+sul+tet(G); blaOXA-1+catA+aadA1/strA-strB+sul+tet(B) and blaTEM-1+ cmlA1+aadA/strA-strB+sul+tet(A)/tet(B) genes] were associated with the ampicillin-chloramphenicol-streptomycin-sulfonamides-tetracycline phenotype in 68 AMCR/I S. enterica isolates. Class 1 integrons were observed in 79% of the isolates and in most of them (45 isolates) two integrons including the aadA2 and blaPSE-1 gene cassettes, respectively, were detected. The blaOXA-1+aadA1 arrangement was detected in 23 isolates, and the aac(6′)-Ib-cr+blaOXA-1+catB3+arr3 in another one. Non-classic class 1 integrons were found in three isolates: dfrA12+orfF+aadA2+cmlA1+aadA1 (1 isolate), dfrA12+orfF+aadA2+ cmlA1+aadA1+qacH+IS440+sul3 (1 isolate) and dfrA12+orfF+aadA2+cmlA1+aadA1+qacH+IS440+ sul3+orf1+mef(B)Δ-IS26 (1 isolate). Taken together, these results underline the need for clinical concern regarding β-lactam resistance in Salmonella and thus for continuous monitoring. [Int Microbiol 2011; 14(3):173-181] Keywords: Salmonella enterica · β-lactam-resistance · integrons · extended-spectrum β-lactamases (ESBL)

Introduction Salmonella enterica is the second most frequent cause of zoonotic diseases in humans in Europe, and more than

*Corresponding author: C. Torres Área de Bioquímica y Biología Molecular Departamento de Agricultura y Alimentación Universidad de La Rioja 26006 Logroño, Spain Tel. +34-941299750. Fax: +34-941299721 E-mail: carmen.torres@unirioja.es

150,000 cases of human salmonellosis were reported by The European Surveillance System during 2007 [8]. Salmonella Enteritidis and Salmonella Typhimurium are two of the ten most common serotypes confirmed in salmonellosis cases in humans, representing 81% of the isolates [8]. S. Typhimurium is frequently associated with multidrug resistance [3,26], in part due to the worldwide emergence of S. Typhimurium definitive phage type (DT) 104, which contains the chromosomal Salmonella genomic island type I (SGI-1). SGI-1 harbors genes that confer the ACSSuT phenotype (i.e., resistance to ampicillin, chloramphenicol, streptomycin, sul-


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fonamides, and tetracycline) [16]. Although S. Typhimurium DT104 is the main example of multiresistance in S. enterica, many antimicrobial resistance genes have been reported also in isolates of other serotypes [14]. Non-typhoidal Salmonella infections generally result in mild-to-moderate self-limiting gastroenteritis, and antimicrobial treatment is only required in severe cases occurring in vulnerable patient groups or to combat invasive infections. However, due to the increasing resistance of this bacterium to the conventional antimicrobial agents (ampicillin, and trimethoprim/sulfamethoxazole) used in the treatment of salmonellosis, amoxicillin/clavulanate, third-generation cephalosporins, and fluoroquinolones have become further treatment options. Resistance to β-lactams in S. enterica is mainly due to the production of acquired β-lactamases [14]. Among these, TEM-1, PSE-1, and OXA-1 have been described as the enzymes most frequently related to ampicillin and amoxicillin/clavulanate resistance [3,11]. The resistance of Salmonella to third-generation cephalosporins is primarily mediated by the production of extended-spectrum β-lactamases (ESBL) of the TEM, SHV, and CTX-M types, which are associated with different mobile genetic elements [11,14]. ESBL have been described not only in clinical Salmonella isolates but also in isolates from animals and food [6,21]. Mobile genetic elements such as plasmids and transposons, possibly containing integrons, are able to disseminate antimicrobial resistance by horizontal transfer in Enterobacteriaceae. Integrons are genetic elements that capture and incorporate gene cassettes by using a site-specific recombination mechanism [4]. Thus far, class 1 and, less frequently, class 2 integrons have been reported for S. enterica [4]. Class 1 integrons contain a 5′-conserved segment (5′-CS) that includes the integrase intI1 gene, the attI1 recombination site, and the Pc promoter. It is followed by a variable region where one or more gene cassettes are located. This class of integrons also contains a 3′-conserved segment (3′-CS) that includes the sul1 and qacEΔ1 genes, which encode resistance to sulfonamides and ammonium quaternary compounds, respectively [4]. In recent years, resistance to amoxicillin/clavulanate among S. enterica isolated from different Spanish hospitals has become increasingly widespread, accompanied by the emergence of ESBL-producing isolates, detected in human samples. Consequently, there are fewer therapeutic options for the treatment of S. enterica infections, placing these patients at greater risk of serious morbidity and even death.

The aim of the present work was to characterize the mechanisms of resistance to β-lactams and other antimicrobial agents as well as the integrons in all amoxicillin/clavulanateresistant, intermediately resistant (AMCR/I), and third-generation cephalosporin-resistant (C3GR) S. enterica isolates recovered in three Spanish hospitals during the period 2007–2009.

Materials and methods Isolates and antimicrobial susceptibility testing. In this study, 90 S. enterica isolates with the AMCR/I phenotype (87 isolates) or the C3GR phenotype (3 isolates) were recovered in three Spanish hospitals located in geographically distinct areas: Hospital General Universitario Gregorio Marañón of Madrid (HGM, 39 isolates), Hospital San Pedro of Logroño (HSP, 36 isolates), and Complejo Hospitalario of Pontevedra (CHP, 15 isolates). AMCR/I and C3GR phenotypes were detected in 12–23% and <1%, respectively, of all S. enterica isolated in the three hospitals. The 90 isolates were recovered from fecal (73 isolates), blood (2 isolates), urine (1 isolate) and other (14 isolates) samples from different patients during 2007 (29 isolates), 2008 (34 isolates), and 2009 (27 isolates). The serotypes of these isolates were as follows: S. Typhimurium (79 isolates), S. Enteritidis (8 isolates, one of them C3GR), S. Virchow (1 isolate, C3GR), S. Gnesta (1 isolate, C3GR), and S. Thompson (1 isolate). Susceptibility testing to 20 antimicrobial agents (ampicillin, AMC, cefalotin, cefazolin, ceftazidime, cefotaxime, aztreonam, cefoxitin, gentamicin, tobramycin, kanamycin, amikacin, streptomycin, nalidixic acid, ciprofloxacin, tetracycline, chloramphenicol, sulfonamides, trimethoprim, trimethoprim/sulfamethoxazole) was performed by the disc-diffusion [5] and microdilution methods (MicroScan Combo Neg panels, Siemens, Sacramento, CA, USA) according to the Clinical and Laboratory Standards Institute (CLSI) guidelines. The AmpC phenotype was determined by comparison of the inhibition zone of cefoxitin discs (30 μg) in the presence or absence of cloxacillin (200 μg) [29]. The ESBL phenotype was determined using the double-disc synergy test with cefotaxime, ceftazidime, and aztreonam discs placed in the proximity of the AMC disc [13]. Detection of antimicrobial resistance genes. The presence of genes implicated in the resistance to β-lactams (blaTEM, blaSHV, blaCTX-M, blaOXA-1 and blaPSE-1), and the blaCTX-M genetic environment was detected by PCR and sequencing [7,17,31]. In addition, multiplex PCR for the detection of plasmidic AmpC-type β-lactamases was carried out [20]. Tetracycline [tet(A)-tet(E),tet(G)], aminoglycoside [aadA, strA-strB, aac(3)-I, aac(3)-II, aac(3)-IV, ant(2′′), aph(3′)-Ia, aph(3′)-IIa, rmtB, armA and aac(6′)-Ib], sulfonamides [sul1, sul2 and sul3], trimethoprim [dfrA], chloramphenicol [cmlA, catA and floR], and quinolone [qnrA, qnrB, qnrS and qepA] resistance genes were studied by PCR and sequencing [7,24,27]. The genetic enviroments of the sul1, sul2, and sul3 genes were determined as previously reported [32]. Detection and characterization of integrons. The presence of class 1, 2, and 3 integrase-encoding genes and of the 3′-CS of class 1 integrons, qacEΔ1+sul1, was analyzed by PCR. The variable regions of these integrons were PCR-amplified and subsequently sequenced to determine their gene cassette arrangements [24].


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Results Antimicrobial susceptibility in Salmonella enterica isolates. Table 1 shows the antimicrobial susceptibility of the 90 AMCR/I or C3GR S. enterica isolates included in this study. The S. Typhimurium isolates were highly resistant to sulfonamides (100%), tetracycline (91%), chloramphenicol (86%), and streptomycin (80%). Aminoglycosides resistance was found only among isolates of serotype S. Typhimurium. All isolates studied were susceptible to amikacin, cefoxitin and ciprofloxacin. A multiresistant phenotype (resistant to at least three different antimicrobial agent families) was observed among 100% of the S. Typhimurium and 12.5% of the S. Enteritidis isolates. Two S. Typhimurium

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isolates had a heptaresistant phenotype that included the ACSSuT phenotype in addition to resistance to trimethoprim and gentamicin or nalidixic acid (ACGSSuTTm and ACSSuTTmN, respectively). The AmpC phenotype was not identified among the isolates tested. However, the ESBL phenotype was determined in three of them and corresponded to one isolate each of S. Enterica, S. Virchow, and S. Gnesta serotypes (Table 1). All three were resistant to cefotaxime, while S. Gnesta isolate was also resistant to ceftazidime and aztreonam. Antimicrobial resistance genes. Tables 2 and 3 list the resistance genes detected in the 90 S. enterica isolates, according to serotype. The most frequent β-lactamase gene identified among the AMCR/I isolates was blaPSE-1, detected in

Table 1. Number of AMCR/I or C3GR of Salmonella enterica isolates resistant to antimicrobial agents. The isolates were of different serotypes and obtained from three Spanish hospitals Antimicrobial agenta

S. Typhimurium (n = 79)

S. Enteritidis (n = 8)

S. Virchow (n = 1)

S. Gnesta (n = 1)

S. Thompson (n = 1)

All S. enterica tested (n = 90)

AMCb

79

7

0

0

1

87

Cefalotin

7

1

1

1

0

10

Cefazolin

9

1

1

1

0

12

Ceftazidime

0

0

0

1

0

1

Cefotaxime

0

1

1

1

0

3

Aztreonam

0

0

0

1

0

1

Gentamicin

1

0

0

0

0

1

Tobramycin

1

0

0

0

0

1

Kanamycin

2

0

0

0

0

2

Streptomycin

63

0

0

0

0

63

Nalidixic acid

17

2

1

0

0

20

Tetracycline

72

1

1

0

1

75

Chloramphenicol

68

0

0

0

1

69

Sulfonamides

79

3

1

1

1

85

Trimethoprim

5

0

0

0

0

5

SXTc

5

1

0

0

0

6

ESBL phenotype

0

1

1

1

0

3

a

All the isolates were resistant to ampicillin, but susceptible to cefoxitin, amikacin, and ciprofloxacin. AMC: Amoxicillin/clavulanate. c SXT: Trimethoprim-sulfamethoxazole. b


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Table 2. Antimicrobial resistance genes and the resistance phenotype of Salmonella enterica isolates from three Spanish hospitals Number of resistant isolates

Resistance genes

S. Typhimurium

S. Enteritidis

Other serotypes

Total (n = 90)

β-Lactams (n = 90)

blaPSE-1

41

41

blaOXA-1

23

1

24

blaTEM-1b

9

6

15

blaTEM-1c

1

1

3blaPSE-1 + blaOXA-1

1

1

blaPSE-1 + blaTEM-1b

3

3

blaCTX-M-10

1

1

1

1

blaCTX-M-15 + blaTEM-1

1

1

No studied bla genes

1

1

2

tet(A)

5

5

tet(B)

29

1

30

tet(G)

45

45

No studied tet genes

1

1

2

aadA1/aadA2

66

66

strA-strB

5

5

aadA1/aadA2+strA-strB

4

4

No studied genes

1

1

Gentamicin (n = 1)

aac(3)-IV

1

1

Kanamycin (n = 2)

aph(3′)-Ia

1

1

No studied genes

1

1

floR

44

1

45

catA

18

18

cmlA1

3

3

floR + catA

2

2

floR + cmlA

1

1

sul1

54

54

sul2

8

1

9

sul1 + sul2

14

1

15

sul2 + sul3

1

1

sul1+ sul2 + sul3

1

1

No studied sul genes

1

3

1

5

dfrA12

3

3

dfrA14

2

2

blaCTX-M-14a c

Tetracyclinea (n = 82)

Streptomycinb (n = 76)

Chloramphenicol (n = 69)

Sulfonamides (n = 85)

Trimethoprim (n = 5)

a

Seven of the studied isolates with a phenotype of intermediate resistance to tetracycline harbored the tet(G) gene. Twelve of the studied isolates with a phenotype of intermediate resistance to streptomycin harbored the aadA1/aadA2 gene. Three of the isolates with a susceptibility to streptomycin harbored strA-strB genes. c blaTEM-1 variant showed a silent nucleotide change (T→C) at position 735 [28]. b


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51.7% of the 87 AMCR/I isolates including all those belonging to S. Typhimurim. In addition, the gene was associated with other bla genes in four of these isolates (blaTEM-1b or blaOXA-1). The blaOXA-1 gene was identified in 27.6% of the AMCR/I isolates (23 S. Typhimurium and 1 S. Thompson), and only in one case in association with other bla genes. In addition, the blaTEM-1 gene was demonstrated in 21.8% of the AMCR/I isolates (13 S. Typhimurium and 6 S. Enteritidis) and associated with other bla genes in three of them. As shown in Table 2, blaTEM-1 was the most frequent bla gene in S. Enteritidis isolates. The β-lactamase genes identified among the three C3GR isolates with an ESBL-positive phenotype were as follows: blaCTX-M-14a (S. Enteritidis), blaCTX-M-15 (S. Gnesta), and blaCTX-M-10 (S. Virchow). In these isolates, the ISEcp1-blaCTX-M-14a-IS903 and ISEcp1-blaCTX-M-15-orf477 structures were identified. The blaCTX-M-15-positive S. Gnesta isolate also carried a new variant of the blaTEM-1 β-lactamase gene that showed a silent nucleotide change (T→C) at position 735 according to the Sutcliffe nomenclature [28]. Regarding the blaCTX-M-10 genetic environment, the gene’s upstream region included a group of ORFs (orf2, orf3 and orf4) and a phage-related DNA invertase. Downstream, orf7 was identified. All of the S. enterica isolates tested were negative for the plasmid-mediated quinolone resistance genes qnrA, qnrB, qnrS, and qepA. Integron detection and characterization. Seventy-one of the 90 isolates (79%) were positive for the intI1 gene, and six different gene cassette arrangements were determined (Table 3, Fig.1). Class 2 and 3 integrons were absent. All 45 blaPSE-1-positive S. Typhimurium isolates showed two integrons, with variable regions of 1000 and 1200 bp, harboring the aadA2 and blaPSE-1 gene cassettes, respectively. The blaOXA-1 + aadA1 gene array was found in most of the blaOXA-1-positive isolates (23 of 25), whereas the S. Thompson isolate showed the aac(6′)-Ib-cr+blaOXA-1+catB3 +arr3 arrangement. Three non-classic class 1 integrons (lacking the 3′-CS) were found in three isolates (Fig. 1). Genetic environment of sul genes. Of the 90 S. enterica isolates studied, 94.4% were resistant to sulfonamides. At least one sul gene was detected in 80 of them, and more than one sul gene in 17 of them (Table 2). The sul1 gene was associated with class 1 integrons in all 70 sul1-positive isolates (Table 3). The genetic environment of the sul2 gene was determined in 11 of the 26 sul2-positive S. enterica isolates (42.3%). Four different structures were demonstrated (number of iso-

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lates): repC+sul2+strA-strB+tnpB (6), repC+sul2+strAstrB+IS26 (2), repC+sul2+strA-strB (1) and sul2 +strAΔdfrA14 -strB (2). In these two last isolates, the strA gene was truncated by the dfrA14 gene, and a streptomycin-susceptibility phenotype was determined in both isolates. The sul3 gene was associated with the above mentioned non-classic class 1 integrons (lacking the 3′-CS) in the two sul3-positive isolates. In summary, an ACSSuT phenotype (including intermediate resistance) was confirmed in 68 S. enterica isolates (all of them Typhimurium), 15 of which were additionally resistant to nalidixic acid and three others to trimethoprim (Table 3). Three general gene profiles were mostly responsible for the ACSSuT multiresistant phenotype: (i) The blaPSE-1 and aadA2 genes, located within two class 1 integrons (structure A, Fig. 1), were associated with the floR, sul and tet(G) genes in 45 of these isolates. In five of the 45 isolates, one non-classic class 1 integron (dfrA12+orfF+aadA2+cmlA1+aadA1), the blaTEM-1 gene, and the blaOXA-1 gene were additionally detected (one, three, and one isolate, respectively). (ii) The blaOXA-1 and aadA1 (located within a class 1 integron of structure B, Fig. 1), catA, sul, and tet(B) gene profile occurred in 20 isolates. The floR gene was additionally found in two of them. (iii) An association between blaTEM-1b, cmlA1, aadA or strA-strB, sul, and tet(A) or tet(B) genes was detected in three isolates. In one of them, the aac(3)-IV and dfrA12 genes were additionally amplified, confirming this S. Typhimurium isolate’s ACGSSuTTm phenotype (Table 3).

Discussion Antimicrobial resistance in S. enterica is a cause of serious concern in human medicine. The drugs of choice for the treatment of complicated salmonellosis are usually ampicillin, amoxicillin/clavulanate, third-generation cephalosporins, or fluoroquinolones, but the increasing emergence of resistance to these antimicrobials limits the therapeutic choices [9,15,18]. In our study, the AMCR/I phenotype was detected in 12–23% of all S. enterica isolates recovered from human samples obtained from three Spanish hospitals. The β-lactamase-related mechanisms implicated in this AMCR/I phenotype were the production of the enzymes PSE-1, OXA-1 and TEM-1, as previously reported in other series [11]. The high prevalence of blaPSE-1 and blaTEM-1 observed among S. Typhimurium and S. Enteritidis isolates, respectively, was also previously reported [3,11,26]. The detection of more than one β-lactamase gene in the same isolate was infrequent in our study (4 isolates), in contrast to the data from other studies [3,11].


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Table 3. Phenotypes and mechanisms of resistance detected in the 90 AMCR/I and C3GR Salmonella enterica isolates Phenotype of resistance (number of isolates)a,b

S. Typhimurium (n = 79) SUL+TET (1)

Genotype of resistance (number of isolates)c

blaTEM-1c + sul2 + tet(B) (1)

Class 1 integrond –

STR+SUL+TET (7)

blaOXA-1 + aadA + sul1 + tet(B) (2) blaTEM-1b + strA-strB + sul2 + tet(B) (3) blaTEM-1b + strA-strB + sul2 + tet(A) (1) tet(B) (1)

(B) – – –

STR+SUL+TET+NAL (1)

blaOXA-1 + aadA + sul1+ tet(B) (1)

(B)

SUL+TET+TMP+SXT (1)

blaTEM-1b + strAΔdfrA14-strB + sul2+ tet(A) (1)

CHL+STR+SUL+TET+KAN (2)

blaPSE-1 + blaOXA-1 + floR + aadA + sul1+ tet(G) (1) blaPSE-1 + floR + aadA + sul1 + tet(G) + aph(3′)-Ia (1)

(A) (A)

CHL+STR+SUL+TET+NAL (14)f

blaPSE-1 + floR + aadA + sul1 + tet(G) (10) blaOXA-1 + floR + catA + aadA + sul1 + tet(B) (1) blaOXA-1 + catA + aadA + sul1 + tet(B) (3)

(A) (B) (B)

SUL+TET+TMP+SXT+NAL (1)

blaTEM-1b + sul2 + tet(A) + strAΔdfrA14- strB

CHL+STR+SUL+TET+TMP+SXT (1)

blaTEM-1b + cmlA1 + aadA + strA-strB + sul2 + sul3 + tet(A) + dfrA12

CHL+STR+SUL+TET+TMP+SXT+NAL (1)

blaPSE-1 + floR + cmlA1 + aadA + sul1 + tet(G) + dfrA12

CHL+STR+SUL+TET+GEN+TOB+TMP+SXT (1) blaTEM-1b + cmlA1 + aadA + sul1 + sul2 + sul3 + tet(A) + aac(3)-IV + dfrA12

– (E)

(A)+(D) (F)g

None (2)

blaTEM-1b

NAL (1)

– (1)

TET (1)

blaTEM-1b

SUL (2)

blaTEM-1b

CTX+NAL (1)

blaCTX-M-14a

SUL+SXT (1)

blaTEM–1b

S. Gnesta (n = 1)

ATM+CAZ+CTX+SUL (1)

blaCTX-M-15 + blaTEM-1

S. Thompson (n = 1)

CHL+SUL+TET (1)

blaOXA-1 + floR + catB3 + sul1+ sul2 + aac(6′)-Ib-cr

S. Virchow (n = 1)

SUL+TET+CTX+NAL (1)

blaCTX-M-10 + sul2 + tet(B) + strA-strB

S. Enteritidis (n = 8)

a

(C) –

Abbreviations: CAZ: ceftazidime, CTX: cefotaxime, ATM: aztreonam, GEN: gentamicin, TOB: tobramycin, KAN: kanamycin, STR: streptomycin, NAL: nalidixic acid, TET: tetracycline, CHL: chloramphenicol, SUL: sulfonamides, TMP: trimethoprim, SXT: trimethoprim/sulfamethoxazole. b ACSSuT phenotype is marked in bold letters. c Streptomycin resistance genes aadA correspond to aadA1 or aadA2. d Integron structures A-F correspond to those shown in Fig. 1. e Six of these isolates had an intermediate phenotype with respect to tetracycline and nine isolates with respect to streptomycin. f One of these isolates had an intermediate phenotype with respect to tetracycline and two with respect to streptomycin. g This integron contained the putative macrolide efflux gene mef(B), truncated by IS26 such that only 256 bp of mef(B) remained.


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Fig. 1. Gene cassette arrangements among class 1 integrons detected in Salmonella enterica isolates.

The ESBL phenotype in human clinical isolates of S. enterica is of particular interest but in our study it was detected in <1% of the S. enterica isolates obtained from the three hospitals. ESBL are spreading very rapidly among E. coli and Klebsiella spp. isolates whereas their frequency among S. enterica isolates is much lower [2,15,18]. The diversity of ESBL detected among our three ESBL-positive S. enterica isolates (CTX-M-14, CTX-M-15, and CTX-M-10) is noteworthy as is the fact that these genes were identified in unusual serotypes, i.e., S. Gnesta and S. Virchow. The CTX-M-14 β-lactamase-encoding gene, flanked by ISEcp1 and IS903 sequences, has been frequently detected in E. coli isolates of human and animal origin in Spain [6]. In S. enterica, the first description of this enzyme, in a clinical isolate of S. Enteritidis recovered in Spain, was that of Romero et al. [23]. However, the blaCTX-M-14 gene has been identified in Salmonella of different serotypes and in several countries [2,6,9,18]. The genetic element ISEcp1 is a mobile and mobilizing element that may be implicated in the blaCTXM-14 gene mobilization [19]. Similarly, the blaCTX-M-15 gene, flanked by ISEcp1 and orf477 elements, has been shown to be disseminated throughout the world and is mostly detected among E. coli and Klebsiella isolates [6]. In our study, this enzyme was identified in a S. Gnesta isolate. To our knowledge,

this is the first description of the presence of the CTX-M-15 β-lactamase in S. Gnesta, a serotype uncommonly associated with human salmonellosis. The CTX-M-10 enzyme has been described in E. coli, Enterobacter spp., Klebsiella spp., and S. Virchow isolates in Spain [6,9,17,21]. In the present work, this enzyme was also found in a S. Virchow isolate, and the genetic environment of the blaCTX-M-10 gene was associated with a phage-related element, similar to one previously reported [17,21]. The ACSSuT multiresistance phenotype was detected in 68 of the S. Typhimurium isolates. Although this phenotype is usually associated with the widely distributed chromosomal SGI-1 (contains the blaPSE-1, floR, aadA2, sul, and tet(G) genes) [16,30], other gene profiles have also been described [10,12,22]. Indeed, in our study different resistant genotypes were determined; the most common one was the SGI-1 linked profile. The association of the blaOXA-1, catA, [aadA1 / strA-strB], sul, and tet(B) genes, with the blaOXA-1+aadA1 arrangement included within a 2000-bp class 1 integron, was found among 20 S. Typhimurium ACSSuT-resistant isolates. In addition, the gene profile blaTEM-1, cmlA1, [aadA / strAstrB], sul and [tet(A) / tet(B)] was identified in three S. Typhimurium isolates. In previous studies, these latter two resistance-gene profiles were shown to be located on hybrid self-


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transferable plasmids, which also contain virulence genes, such as the pUO-StVR plasmids in S. Typhimurium and the recently reported pUO-SeVR1 in S. Enteritidis [10,12,22]. Further studies of our isolates are needed to determine the plasmid localization of these ACSSuT resistance genes and/or their possible association with virulence genes. Class 1 integrons were present in 79% of the 90 isolates tested. Note the presence of a class 1 integron with the aac(6′) -Ib-cr+blaOXA-1+catB3+arr3 structure in the S. Thompson isolate. While this arrangement has been previously described, it is usually associated with complex integrons containing the ISCR1 elements, double copies of 3′-CS, and qnr genes, among others (e.g., GenBank accession numbers AJ971343 and AY259086). In addition, non-classical integrons (without qacEΔ1+sul1 genes) were found in three isolates (4%). All three included the gene cassette organization dfrA12+orfF +aadA2+cmlA1+aadA1, in two of these three isolates in association with the qacH+IS440+sul3 structure previously reported in Salmonella and E. coli [1,25]. In conclusion, blaPSE-1 and blaOXA-1 were the most frequent bla genes implicated in the AMCR/I phenotype in S. Typhimurium, and blaTEM-1 the most frequent in S. Enteritidis. ESBLpositive isolates, corresponding to non-S. Typhimurium serotypes, were identified in <1% of the S. enterica isolates obtained from the three hospitals. Among the three different ESBL variants detected, ours is the first description of CTXM-15 in S. Gnesta. In addition, the frequent association of the β-lactamase production with nalidixic acid resistance (22%), which precludes the use of fluoroquinolones in the treatment of salmonellosis, is a cause for clinical concern and underlines the need to track the evolution of β-lactamases in S. enterica isolates. Acknowledgements. We thank M. Aurora Echeita from the Centro Nacional de Microbiología, Instituto de Salud Carlos III, Madrid, Spain, for serotyping of the isolates. M. de T. is the recipient of a predoctoral fellowship from the Instituto de Salud Carlos III of Spain (MINCINN) (grant number FI08/00506). Competing interests. None declared.

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Volume 14 · Number 3 · September 2011 · ISSN 1139-6709

Spanish Society for Microbiology Volume 14 · Number 3 · September 2011

International Microbiology

INTERNATIONAL MICROBIOLOGY

Volume 14

RESEARCH ARTICLES Köchling T, Lara-Martín P, González-Mazo E, Amils R, Sanz JL Microbial community composition of anoxic marine sediments in the Bay of Cadiz (Spain)

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Starek M, Kolev KI, Berthiaume L, Yeung CW, Sleep BE, Wolfaardt GM, Hausner M A flow cell simulating a surface rock fracture for investigations of groundwater-derived biofilms

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de Toro M, Sáenz Y, Cercenado E, Rojo-Bezares B, García-Campello M, Undabeitia E, Torres C Genetic characterization of the mechanisms of resistance to amoxicillin/clavulanate and third generation cephalosporins in Salmonella enterica from three Spanish hospitals

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pp 121-182

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Marques AP, Duarte AJ, Chambel L, Teixeira MF, San Romão MV, Tenreiro R Genomic diversity of Oenococcus oeni from different winemaking regions of Portugal

2011

Mora A, Herrera A, López C, Dahbi G, Mamani R, Pita JM, Alonso MP, Llovo J, Bernárdez MI, Blanco JE, Blanco M, Blanco J Characteristics of the Shiga-toxin-producing enteroaggregative Escherichia coli O104:H4 German outbreak strain and of STEC strains isolated in Spain

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INTERNATIONAL MICROBIOLOGY 14(3) 2011

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