HATCHERY Feed & Management Vol 9 Issue 2 2021

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MICROBIAL MANAGEMENT

Managing microbiomes, one cell at a time Ruben Props, Frederiek-Maarten Kerckhof, Marc Indigne, Nico Boon, KYTOS

It’s no secret that microscopic life in aquaculture facilities is incredibly diverse, ranging from viruses to algae, to protozoa. Yet, current microbiome management practices in aquaculture typically center around a narrow set of opportunistic pathogens that may become virulent and cause diseases. In shrimp specifically, new microbial diseases have stagnated and even collapsed the growth of the industry on several occasions over the past few decades. As diseases prove difficult to fully eradicate once they are established, farmers try to safeguard crops via targeted diagnostics, and via strengthening resident microbiomes by the addition of prophylactic health products (e.g., pre-, pro-, and synbiotics). Such a management approach, however, poses several problems. First, it completely disregards the thousands of microbial organisms which are not pathogenic and occupy important niches in the aquaculture ecosystem. Secondly, most opportunistic pathogens are residents of both healthy and diseased aquaculture systems and only become virulent under specific environmental conditions. Lastly, prophylactic health agents are used according to rigid protocols. All of this results in a suboptimal management plan guided by sparse and infrequent microbiome information.

Breaking the status quo At KYTOS, a spin-off company of the Center for Microbial Ecology and Technology (CMET) and Ghent

Hatchery Feed & Management Vol 9 Issue 2 2021

University, we develop novel technologies to make routine microbiome health assessments an intrinsic part of day-to-day farming operations. Our core technology platform makes use of cytometry in which cells are propelled through a high-powered laser beam at rates of up to 5,000 microbes per second, while simultaneously recording their physiological properties. For each water sample, up to 1,000,000 data points that characterize the microbiome are collected. We then use machine-learning methods to translate these big data into so-called microbiome fingerprints. From these fingerprints, important microbiome health insights are extracted, that when compared to our curated reference database, can be used as a basis for formulating (pro-) active actionable management insights. Our holistic approach to microbiome health differs strongly from the current state-of-the-art diagnostic approaches as we make an assessment based on all microbial cells, and not a handful of opportunistic pathogens. Disease epidemics are caused by nearly all forms of microbial life (e.g., viruses, bacteria, algae, protozoa) and therefore we believe a holistic approach is key to getting a grip on the aquaculture microbiome.

Improving sampling efforts One of the major challenges facing microbiome analysis in the industry is gathering representative data. Ideally, samples are measured instantaneously, but in practice,


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