Amsterdam Science Magazine issue 11 by Amsterdam Science

Issue

#11 September 2020

Amsterdam ScienceÂ

Diaphragm and COVID-19

Interview Gravitation grants

Insect recovery

Preface

Index

Dear reader, In COVID-19 times, everything is different; For the first time in five years, we were unable to release an issue in spring. A little later than planned, we managed to collect enough interesting science stories for issue #11 of our magazine. With regards to COVID-19, we present very relevant research from the Amsterdam UMC on how ventilator support can weaken the respiratory system of COVID-19 patients (see page 14. In relation to that, we want to bring the Amsterdam UMC Corona Research Fund to your attention. It aims to gather financial support to kick-start urgent research on novel treatments and on patient recovery (see page 21). In addition to these coronavirus-related articles, this issue also has contributions on other exciting research “made in Amsterdam”. We complete our interview series on NWO Gravitation Grant consortia headed by Amsterdam researchers with two interviews: one with Danielle Posthuma (professor in Human Genetics at the VU University), who heads the consortium “BRAINSCAPES: A Roadmap from Neurogenetics to Neurobiology” and one with Frank van Harmelen (professor in Artificial Intelligence at the VU University), who heads the consortium “Hybrid Intelligence”. In the same area, we also introduce the company FINDEST in our Valorisation section. FINDEST is an award-winning start-up from the VU University that exploits artificial intelligence for technology scouting. If you wondered what high-tech structure has been captured on the front cover, I’ve got a surprise for you. It is a close-up of a piece of sponge that is part of an experimental technique for protein analysis called “immuno-blotting”! Ordinary household material, but very attractive when photographed up close. Similarly, the backcover illustrates tedious work on the analysis of protein networks in the brain: a collection of petri dishes with yeast spots that map interactions between proteins. What else is in this issue? Brain evolution and the connection between brain rhythms and muscle movement are presented in two VU contributions. Three astronomy contributions in this issue are about the origin of the cosmos and the first galaxies. The centrefold image shows an artist’s impression of the cosmic web of gasses. The web that regulates insect abundance and diversity is presented in an infographic designed by VU ecology researchers. They describe a roadmap towards global insect recovery. UvA ecologists explain how the pace of life can influence the response of different organisms towards climate change. We aim to present this eleventh issue of Amsterdam Science in a session of Amsterdam Science Now. Due to corona measures we will have to rethink the format; check our website www.amsterdamscience.org to see the up-to-date planning and programme. Our editorial board has again undergone changes: Renée van Amerongen (UvA), Maria Constantin (UvA), Federica Burla (AMOLF), Adriaan Schiphorst (UvA), Mohit Dubey (NIN) and Ritu Bhandari (NIN) have left the editorial board. We thank them for their valuable contributions to the magazine and we welcome Thomas Aalders (UvA) en Harshal Agrawal (AMOLF). Positions are open in the editorial board, so please contact us if you are interested in participating, especially staff members are encouraged to join us! Write an e-mail to amsterdamscience@gmail.com. Enjoy the eleventh issue and don’t forget to visit our website to submit your own Amsterdam Science contribution! On behalf of the editors in chief, Michel Haring

ABOUT THE COVER IMAGE: These troublesome times challenge us all to change our perspective. On our front cover you see an item that is commonly used in biology laboratories, but from a different perspective. Do you recognize it like this? It is a sponge pad used for Western Blot transfers, a regularly used method for protein detection. Photo by Andrea Ganz, PhD candidate 100-plus Study, Molecular & Cellular Neurobiology, CNCR VU.

14 A vital pump

04 Pace of life

20 Cosmic flashlights

07 Mapping the universe 05 Our vulnerable brain

18 Insect recovery

08 Interview Gravitation grants

21 Corona fund UMC

& more

colophon Editors in Chief: Michel Haring; Sabine Spijker Members of editorial board: Nadine Böke; Esther Visser; Céline Koster; Francesco Mutti; Jans Henke; Annike Bekius; Magdalena Solà; Iraklis Vretzakis; Peter Hordijk; Athira Menon; Shuo Chen; Sarah Brand; Harshal Agrawal; Thomas Aalders; Jop Briët;

Magazine manager: Heleen Verlinde E-mail: amsterdamscience@gmail.com Website: www.amsterdamscience.org Design: Van Lennep, Amsterdam Copy Editor: DBAR Science Editor Printer: GTV Drukwerk

11 Valorisation 12 Centerfold 17 Spotlight 17 Alumnus 21 Spotlight 22 Puzzle 22 Cartoon 23 About 24 Perspective

Ecology

A slow pace of life makes animals more sensitive to unpredictable climate variations → Climate variability is increasing. How will this affect different plant and animal species? The answer to this question is important to inform conservation strategies. Our research shows that we should not rely solely on big-data research to find the answer. Instead we should consider the mechanistic underpinnings of biological variation as a starting point when we want to extrapolate species responses to future environmental changes. ISABEL M. SMALLEGANGE is Associate Professor at the Institute for Biodiversity and Ecosystem Dynamics, UvA. MATTY P. BERG is Full Professor at the Department of Ecological Science, VU, and Affiliate Professor at the Groningen Institute of Evolutionary Life Sciences, University of Groningen.

↓ Figure 1 Changes in climate variability can affect the predictability of environmental conditions such as the availability of food. Different species respond differently to such changes in predictability.

In our analysis, we focus on the socalled life-history speed or ‘pace of life’. The life-history speed of animals and plants ranges from slow to fast. Slow life-history species are typically characterised by late maturation, long life span and not many offspring. Fast life-history species have the opposite characteristics. The pace of life of species plays a crucial role in how they respond to variations in their environment. Environments can change in a myriad of ways, but one that is receiving increasing interest is the way in which the autocorrelation of environmental conditions changes over time. In highly autocorrelated environments, the state of the environment in the near future is strongly related to the current environmental

“The pace of life directs species’ responses to their environment” state (Fig. 1, right graph). Hence, it is predictable for the organism. In uncorrelated environments, there is no correlation between environmental states at different moments in time, leading to unpredictability (Fig. 1, left graph). Analyses of life-history data from hundreds of plant and animal populations using big-data approaches have revealed that species on the fast end of the life-history speed continuum are more sensitive to shifts in temporal autocorrelation than slow life-history species [1]. These analyses rely on big biodiversity databases comprising data on species diversity, abundance and traits in order to identify general patterns of how the life-history speed

Ecology

of species determines their response to environmental changes. Typical of big-data approaches, however, the species’ life histories in these analyses are phenomenological descriptions that lack a mechanistic representation of the biological processes that give rise to observed life-history variation. This means that, without a mechanistic underpinning to data patterns, we do not understand why and how species react to novel environmental conditions. Therefore, extrapolating beyond the range of existing data is problematic. We set out to explore in simulations how a fast life-history species, the beach hopper Orchestia gammarellus (Fig. 2, left), and a slow life-history species, the reef manta ray Mobula alfredi (previously Manta alfredi) (Fig. 2, right), respond to changes in food conditions [2]. We found that the beach hopper responds strongly to how often food conditions are favourable, whereas the manta ray responds strongly to how predictable food conditions are. These results are opposite to those found in big-data analyses based on phenomenological descriptions of life histories [1]. Our simulations have a mechanistic underpinning based on individual energy budgets; hence, we can explain why the two species react differently. The population growth rate of the beach hopper is very sensitive to perturbations to individual reproduction. As rich food conditions directly affect individual reproduction, any shift in how often food conditions are favour-

able will have direct consequences for population growth. In contrast, the population growth rate of the reef manta ray is very sensitive to perturbation of individual growth, which impacts the population growth rate only indirectly. A shift in how often conditions are favourable has much less of an effect on the population growth of the slow life-history species than a shift in the predictability of food conditions.

← Figure 2 A fast life-history species, the beach hopper Orchestia gammarellus (up; photo by Roy Kleukers) and a slow life-history species, the reef manta ray Manta alfredi (bottom; CC BY license).

Our findings highlight the importance of focusing on the mechanistic underpinnings of biological variation as a starting point for extrapolation of species responses to novel (climate) change. While big-data research methods are increasingly used to tackle complex eco-societal problems, we should not discard conventional scientific methods of inquiry. The empirical cycle starts with collecting data, but the purpose of such data is to inform theories, not to be a method in itself. Ω

→ Reference [1] M. Paniw, A. Ozgul and R. SalgueroGómez. Ecology Letters 21, 275–286 (2018). doi: 10.1111/ele.12892 [2] I.M. Smallegange and M. Berg. Ecology and Evolution 9, 9350-9361 (2019). doi: 10.1002/ece3.5485

Our smart but vulnerable brain

YONGBIN WEI is a PhD student at the Center for Neurogenomics and Cognitive Research, VU.

→ During the long history of evolution, humans (Homo Sapiens) have captured more complex cognitive abilities as compared to other highly developed, intelligent great apes. For example, human language is unique among all forms of animal communications. Using language, we can easily share our emotions and attitude with our friends and family - an ability not possessed by any other primate species. Our complex language system, together with sophisticated sociability, helps us to build various ways of collaborations that form perhaps the most intricate social structure on the earth. The question then arises, “Why do humans have more complex cognitive abilities?” It has been argued that the size of the brain is the reason for the differentiated complexity of cognitions and behaviours. The human brain is known to be three times larger than the brain of the chimpanzee, our closest living evolutionary relative. This bigger brain brings humans around 86

billion neurons, which is a strikingly large number when compared to other primate species, who have around 30 billion neurons. These 86 billion neurons, in particular the 16 billion in the neocortex, form the basis of computational capacities that support humans’ complex cognitive abilities. Neurons are wired into neural circuits, which are further interconnected with one another to form a large-scale network within the whole brain, called the connectome. Neuroimaging studies revealing the connectome organisation have shown that the connectome is composed of spatially distributed functional networks. These distributed networks match the functional specifications of the human brain. This means that a functional network is responsible for brain functions related to a specific cognitive or behavioural domain. Among all functional networks, the frontoparietal network, salience network and default-mode network are known as higher-order cognitive

networks. They play an essential role in higher-order brain functions involved in social cognition and language processing. During human brain evolution, brain regions within these higher-order cognitive networks expanded remarkably more than the other functional networks. This in-

J “The yin and yang of the human brain: smarter but more vulnerable”

teresting phenomenon triggered us to investigate what drives such a rapid expansion of human cognitive networks. The evolutionary cortical expansion of the human brain may be inherently determined by the information encoded in the human genome. Although humans share the majority of their genes with other non-human primates, some human-specific genes, for instance the NOTCH2NL gene as discussed in Dr. Frank Jacobs’ (UvA) article in the previous issue of Amsterdam Science Magazine (issue 8, page 13), may regulate the growth of cortex in the human brain. Recent research from the lab of Dr. Martijn van den Heuvel (VU) has further suggested a set of “human-accelerated” (HAR) genes to be important for the evolutionary expansion of human higher-order cognitive networks. HAR genes are defined as genes associated with the segments of the human genome that are conserved throughout vertebrate evolution, but are strikingly different in humans (see Figure). By integrating gene expression data and comparative neuroimaging data

Astronomy

Neurosciences

of humans and chimpanzees, we found that the rapid evolutionary cortical expansion of cognitive networks in the human brain runs parallel with high expressions of HAR genes. Examining gene expression across primate species has also shown that HAR genes are differentially more expressed in higher-order cognitive networks in humans in contrast to the chimpanzee and macaque. Our findings thus suggest that the increased expression of HAR genes may regulate the formation and expansion of cognitive networks in the human brain. As HAR genes are involved in the formation of synapses and dendrites (contact points and extensions of brain cells, respectively), such an up-regulated HAR gene expression also implies more complex neural circuits in the cognitive networks in humans compared to non-human primates. HAR genes may also influence brain functions in our daily life. Genome-wide association studies have identified genetic variants that are associated with the activity of brain functional networks. HAR

genes were found to be specifically associated with genetic variants related to the functional activity of the default-mode network, a network particularly important for social cognition and involved in multiple brain disorders. Interestingly, HAR genes were also found to be associated with genetic variants related to intelligence and sociability, and brain disorders such as schizophrenia and autism. These results imply a trade-off in human evolution: HAR genes brought us more complex cognitive abilities; however, they can also made our brain more vulnerable to brain disorders. Ω

→ Reference Y. Wei et al., Nature Communications 10, 4839 (2019). doi: 10.1038/s41467019-12764-8

Mapping the universe with the largest optical telescope on Earth

↓ Figure The human accelerated regions (HARs) of the genome are associated with the larger expansion of cognitive networks during evolution of the human brain as compared to the brain of the chimpanzee.

JURE JAPELJ is postdoc at the Anton Pannekoek Institute of Astronomy, UvA.

→ Reference J. Japelj et al., Astronomy & Astrophysics 632, A94 (2019). doi: 10.1051/0004-6361/201936048

→ On the largest scales, all clusters of matter in the universe today are linked together by web-like filaments of cosmic gas, forming an inconceivably vast, intricate structure called the cosmic web. The structure of this web contains important information about how the universe evolved, but it is so large, and its filaments so faint, that observing it directly has been extremely difficult so far. With the Extremely Large Telescope, the largest telescope ever to be built, we will soon see the cosmic web more clearly than ever before. Cosmology is the science that attempts to understand the origin and evolution of the universe. Thankfully, imprints of the history of the universe are left on the cosmic web. By mapping out the large-scale structure of the universe, we don’t just learn how matter is spread throughout space today, but also what it looked like billions of years ago. This is because the light that we see today from the furthest corners of the universe has taken many billions of years to reach us, allowing us to glimpse what the ancient universe looked like. More locally, the evolution of the cosmic web can also teach us about galaxy development: galaxies are born in the web and their growth is intimately linked with how matter is distributed around them. Unfortunately for us, mapping the web is difficult because the filaments

connecting galaxies and galaxy clusters are extremely faint. However, we can use a trick. The clouds of hydrogen making up the filaments leave an imprint on the light coming from galaxies behind them. Depending on the distance between us and a galaxy, these clouds absorb different parts of its spectrum. The spectrum of a distant galaxy therefore teaches us about the locations and sizes of the clouds in the direction of that galaxy. Rather than looking at a single galaxy, we can observe a large number of galaxies that lie close to each other in the sky (see centrefold image pag. 12). By using advanced interpolation techniques to reconstruct the gas in all directions, we obtain a three-dimensional map of the web in front of the observed background galaxies. A similar tomography technique is used in medical applications to map the networks of the human brain. We use it on a vastly different scale: that of the cosmic web. Measuring the spectra of thousands of faint galaxies with a high precision requires big telescopes. The European Southern Observatory has recently started the construction of what

will be the largest optical telescope on Earth—the 39-metre Extremely Large Telescope (ELT). Located on the top of Cerro Armazones in Chile, this telescope will stand in a dome the size of a football field and will be the world’s biggest eye on the sky. One of the instruments on the telescope, currently being developed by a large international consortium, will be the multi-object spectrograph MOSAIC. It will enable us to measure the light spectra of hundreds of faint galaxies in a single measurement and to make a detailed map of the cosmic web at unprecedented distances. The tomography of the cosmic web is a relatively new technique, which means that we do not yet fully grasp the practical requirements necessary to carry it out successfully. We need to run simulations to optimise the way galaxy observations will be carried out and improve our analytical tools. We performed a series of simulations, combining cosmological simulations of the universe and models of MOSAIC’s performance, and demonstrated that the ELT and MOSAIC can map the cosmic web at distances that no other telescopes and instruments can. With a resolu-

↑ Figure Artist’s impression of the Extremely Large Telescope, which is being constructed in Chile. Credit: ESO/L. Calçada

tion of about eight million light years, we can study in detail how properties of galaxies, such as their mass, depend on their position relative to the filaments of the web, and thus understand how galaxy evolution depends on the gas in the web. The mapping of the cosmic web will be one of the most ambitious projects of the ELT, and our study lays the foundations for the preparations that will follow in the years before the ELT and MOSAIC become operational. Ω

“We will see the cosmic web more clearly than ever before"

Interview

Every year, the Netherlands Organisation for Scientific Research (NWO) selects six research consortia for large-scale (20 M€) research on important topics. This grant scheme is called NWO Gravitation. In this issue of Amsterdam Science, we interview two researchers each coordinating a Gravitation project. Danielle Posthuma leads the Gravitation programme BRAINSCAPES and Frank van Harmelen coordinates the programme Hybrid Intelligence: Augmenting Human Intellect.

Hybrid Intelligence: augmenting Human Intellect Authors: Peter Hordijk and Shuo Chen, Amsterdam Science editors

AI research in the Netherlands. So, there is no better place to initiate the Gravitation programme.”

→ Last year, Frank, together with research teams from the University of Amsterdam, TU Delft and the universities of Groningen, Leiden and Utrecht, won a prestigious NWO-Gravitation programme grant for research on artificial intelligence (AI), titled "Hybrid Intelligence: Augmenting Human Intellect". The consortium will receive 19 million euro to conduct a ten-year research programme.

What is the punchline of the programme? “The punchline “Augmenting Human Intellect” pretty much sums it up. We want our AI systems to support us instead of replace us. A mixed team of a human and an artificial teacher are better than each of them separately: the AI teacher can spend time on explaining new material while the AI teacher takes care of more routine tasks (the AI system never gets bored of practicing the same multiplication tables). Also, as humans we suffer from many cognitive biases: confirmation bias, in-group and out-group bias, recency bias, and many others. In a collaborative team of AI systems and humans, the AI systems can make us aware of such biases, and help us to correct them. Summarising: we should make combined teams that perform better than humans or machines on their own, and operate together, in a shared context.”

Foto: Frank van Harmelen bij de Open Innovation 2.0 Conference 2016 door Sebastiaan ter Burg, Creative Commons BY 2.0 Generic

We talked to Frank via Zoom to pick his brain, to talk about the Gravitation programme and to find out what ‘hybrid intelligence’ really is.

Gravitation: from human brains to hybrid intelligence

Can you tell us about your background and how you came to work in Amsterdam? “I started as a mathematics student at the University of Amsterdam in the 70s/80s. But during my Master’s studies, I realised that the optimal group size in mathematics is one, which results in an interesting but rather lonely existence. At the time, computer science and its education were in their early days and I followed several courses about the new topic. Here, I quickly realised that in computer science, you work in teams. And that suited me much better. So, I graduated in computer science and mathematics. Next, I got the opportunity to go to Edinburgh for a PhD in Artificial Intelligence. After returning to Amsterdam in the early 90s with a PhD degree and a girlfriend, I started my 5 years postdoc training at the UvA, followed by a switch to the VU for a staff position which I still hold, currently as full professor. And now, because of all developments in this field and the combined size of all the AI research groups at at the UvA and VU, Amsterdam has become the centre of

How do you explain the context to a computer? “When humans work together, they have a goal. For example:I am trying to teach you something, or I am trying to convince you of something, or we are negotiating a compromise, etc. Computers can only truly collaborate with us if the are aware of those goals of the collaboration, and of the roles of each of the participants. Current computers have no such ‘contextual awareness’.” What will this hybrid computer/ human collaboration look like? “In certain settings, it may be very useful to give the hybrid a physical appearance – like a small robot in a children's cancer ward. But in other situations it can be just a desktop

computer – just a voice and a camera would be sufficient.” Where would we see the first hybrid appearing? “This is a gradual development, not a sudden event – unlike Frankenstein. My colleague Catholijn Jonker at TU Delft built the pocket negotiator, which runs on your phone and can help to negotiate the price of a house, etc. For us, our moonshot goal is to build an AI system that collaborates with us as scientists, and that does it so well that we can make the AI system a real, full co-author on a scientific paper, because it contributed to making a hypothesis, doing the experiments and co-writing the publication.” How is collaboration organised in the Gravitation programme? “This grant is a real collaboration between 6 Dutch universities – each with their specific expertise as required for the programme. The worst that could happen is that we all keep on doing our own thing in parallel. To make sure that doesn’t happen, we organised different solutions. We dedicated office space for our researchers and PhD students in a brand new building at the VU

campus to facilitate collaboration. We are now recruiting 27 PhD students – a massive number. We agreed that each of these PhD students will have two supervisors, each from a different university. This is another way to integrate. And we work on application domains such as healthcare and education, in which groups from different universities collaborate on a common subtopic. Another great thing of the grant is the freedom we are given by NWO: we can set our own goals and we only have to report the first outcomes after 5 years.” Do you need massive computers or data centres for this work? “Of course, we need hardware and we use robots to build demonstrations. But it's all off-the-shelf AI equipment. We have our own servers in the department. The innovation will come from the algorithms and the software we write, not from the hardware.” Ω For more information, please visit www.hybrid-intelligence-centre.nl

Valorisation

Interview

Can you describe the different research strategies for BRAINSCAPES? “The research programme is divided into different research projects. First, we aim to conduct and use large-scale genetic studies to map the involvement of specific cell types for multiple brain disorders: brain maps. The disorders we are interested in are are a burden to our society, and often co-occur. Think of depression, schizophrenia, and addiction. Then, we will assess the involvement of predicted cell types in animal models of brain disorders. Next, we aim to

BRAINSCAPES: from genetic findings to understanding disease

“We are moving towards a new kind of Neuroscience”

→ What is the idea behind BRAINSCAPES? “BRAINSCAPES is a collaborative effort between 7 Dutch institutes that share the common goal of integrating genetics and neurosciences to gain insight into brain disorders. The past decade has seen a true revolution in genetics, with so-called genome-wide association studies (GWASs) linking traits to genetic variants across a population, for example patient versus control. These GWAS studies have reached the point where they can reliably point towards the involvement of genetic variants in brain-related disorders. We are now ready for the next step, which is to use this information to gain mechanistic and neurobiological insight into the traits we have studied, and provide well-grounded suggestions for therapeutic targets. The translation from GWAS results to real biology is not straightforward and, so far, has actually been rather poor. In our BRAINSCAPES consortium, however, we have designed a plan of action to improve this. We have clear ideas of how to optimally benefit from GWAS results by rooting them into neurobiology. One of our main assets is that we will invest heavily in integrating biological information from multiple levels of the biological system: the genetic results for several brain disorders will be interpreted with the aid of many existing and novel resources, where we project genetic variation of genes not only to the genes themselves -- the classical genetics approach -- but also to cells that specifically express these genes. From a neuroscience perspective, cells function in brain circuits to regulate behaviour. Hence, this translation from genes to single cells to circuits and onwards would allow us to generate specific and testable hypotheses of how genetic variation may lead to brain disorders. In short, this team effort aims to generate a roadmap that guides how genetic findings can be leveraged to understand disease mechanisms.”

How did the consortium come about? “I believe it all started with a phone call, some e-mails and some further calls between 3-4 principal investigators from the UMC Utrecht and VU Amsterdam. The initial focus was mostly on neurobiology, with hardly any genetics included. When they decided genetics was essential, I was added to the team and asked to lead the process. Which I enthusiastically did, as it had been my dream for the last 10 years to set up a large collaborative project, or even an institute, where we work in a multidisciplinary team, aimed at systematically dissecting brain disorders. The opportunity to go to the limits of your own expertise and then hand over to other members of your team who fully realise the potential of your findings, and vice versa, is how science should be done, in my opinion. We selected collaborators whom we knew would be open to transdisciplinary influences and I am very excited to work with this team, learn from each other and see how the integration of our expertise can forward our understanding of brain disorders.” Which institutes are involved? “Our consortium is a close collaboration between geneticists, computational experts and (neuro)biologists. It is led by the VU University Amster-

dam. The other institutes are Amsterdam UMC, locations VUmc and AMC, the University Medical Centre Utrecht, the Hubrecht Institute Utrecht, Leiden University Medical Center and the Delft University of Technology.”

“The past decade has seen a true revolution in genetics”

What part of the research programme is taking place in Amsterdam? “BRAINSCAPES’ scientists from the different institutes are working in close collaboration, there are no isolated teams. Researchers from Amsterdam are thus involved in the projects running at the other institutes and vice versa. We do have some focal points of expertise, for example, in Amsterdam, our expertise lies in running genetic analyses, pinpointing parts of the genome that are important for a specific trait that we are interested in using an array of computational tools. Because we want to translate the genes found in such a trait to specific cell types, we need the expertise from Leiden, where they perform the computational analysis to identify cell-type specific transcriptomic profiles. Obviously, we also need wet-lab experiments, where we acquire single cell gene expression data after a stimulus that is important for the trait we investigate. These types of experiments are performed in Utrecht.”

The full research programme therefore requires not only close collaborations within the work packages, but also between them. We further strongly advocate an open-science strategy, which means we aim to publicly share our code, tools and results for use in the wider scientific community and aim to publish open-access. We further strive for statistical rigour and have initiated a structural registration of all subprojects that are conducted in BRAINSCAPES. The latter means that all hypotheses, experimental set-ups and methods are registered before any experiment can take place, to avoid practices like hypothesising after results are known.”

What is the ultimate goal of BRAINSCAPES? “After 10 years, we hope to have achieved 3 major aims. The first is to set-up a roadmap for how to integrate genetic findings with biological resources, and conduct genetically-informed functional experiments. Second, we aim to educate a new generation of scientists that are trained in an integrated field of genetics and neuroscience. Lastly, we aim to have gained novel mechanistic insight into several brain disorders. As such, we hope that we can be accountable for the start of several drug-treatment trials by then.” What makes BRAINSCAPES unique? “In my opinion, our uniqueness is the combination of die-hard ‘dry’ scientists (statistical genetics, computation biology) with ‘wet-lab’ scientists, who all – and this is extremely important – have a passionate dedication to make this endeavour –to under-

stand how structural changes in DNA affect biological circuitry, and the functioning of the organism– work. In the past year that I have worked with this team, not once did I feel our discussions were about ‘I’ or ‘me’ for anyone. Instead, we have a unique common dedication, putting our scientific goals before any individual fame, transferring our knowledge, inspiring each other’s passions and, importantly, allowing the new generation of early-career researchers to blossom. With this, we are moving towards a new kind of science, where borders between disciplines are blurred, science is more integrated, focussed, rigorous and reliable, and our goals are completed collaboratively.” Ω

Follow Brainscapes on Twitter! @Brainscapes1

Smartly connecting R&D developers with new technologies → FINDEST is the company using IGOR^AI, an innovative search engine that connects R&D professionals with scientific knowledge and new technologies. Founded at the VU, the company was one of the winners of the 2019 Academic Startup Competition.

illustration: Tom van Dun InfoComics

Authors: Sabine Spijker and Esther Visser, Amsterdam Science editors.

identify the neural circuity in which identified cell types are involved and determine the role of identified cell types in brain disorder-relevant circuitry. Finally, we will generate and work-out new ideas and devise spinoff projects aimed to develop novel treatment regimes.

new technologies, because IGOR^AI “understands” what job a technology should do in the context of a technical problem. It can find both existing solutions as well as radically new, cross-industry solutions that humans never thought of before.

Our world faces many challenges, such as climate change, depleting resources and increasing populations. To beat these global challenges, companies need to change course, innovate and develop new technological ideas. But how to find the information you need among hundreds of millions of scientific papers and patents, and over a whopping billion webpages?

Since the official launch in March 2017, the company has grown to 26 people and is now working with over a hundred customers worldwide, including GE Healthcare, Heineken and Shell. So far, eight innovations have been successfully implemented after being found by IGOR^AI and 50 other successfully scouted technologies resulted in development projects at customers.

A start-up team based at the VU in Amsterdam began to bridge this gap between available scientific knowledge and businesses in need of information by developing an intelligent search approach. This resulted in the search engine IGOR^AI. It radically simplifies the exploration of

Fuelled by being listed as one of the hundred most innovative companies in the Netherlands in 2018 and by winning the academic start-up competition in 2019, Findest has accelerated the development of IGOR^AI. Visit the website www.findest.eu for a taste. Especially if you’re looking

for COVID-19-related solutions, test the free-to-use IGOR^COV-19 search engine, specifically designed to find solutions in virology/healthcare science. Ω

The cosmic web

For billions of years, gravity has been pulling matter in the universe together. Small variations in the distribution of matter right after the Big Bang have led to the formation of the planets, stars, galaxies and galaxy clusters we see today, as well as large â&#x20AC;&#x2DC;voidsâ&#x20AC;&#x2122; where there is no matter at all. Matter in the universe thus forms a majestic structure called the cosmic web - shown in blue in this image - in which clusters of matter, millions of light-years apart, are connected to one another by strings of cosmic gas. Up until very recently, the only way to study the cosmic web over long

distances was by simulating it. However, the European Organisation for Astronomical Research in the Southern Hemisphere (ESO) is currently building the largest optical telescope on Earth, with which we will be able to directly measure and map out the structure of the cosmic web by studying the light spectra of distant galaxies. Curious about how this works, and how researchers of the University of Amsterdam are involved? See page 7.

Image credit: K.G. Lee/MPIA/Haus der Astronomie

Human physiology

The diaphragm, a vital pump

COEN OTTENHEIJM is University Research Chair Professor at the Dept. of Physiology. LEO HEUNKS is Full Professor at the Dept. of Intensive Care; both at Amsterdam UMC, location VUmc.

→ Usually, we hardly think about our lungs as they tend to work fine all by themselves. But even a relatively simple virus can wreak havoc in our lungs, threatening life as we know it at all levels. The ‘respiratory failure’ that goes with viral infection also occurs during ‘normal’ pneumonia, sepsis or after a serious car accident, for example. To treat respiratory failure, mechanical ventilation in the Intensive Care Unit (ICU) is the only lifesaving intervention. Mechanical ventilation supports the diaphragm, the large muscle in our torso that is key to our ability to breathe. However, there is a catch: long-term mechanical ventilation is not good at all for your diaphragm. This is because the diaphragm is used much less when a patient is ventilated, which eventually leads to its partial degeneration (‘disuse atrophy’). Our research at Amsterdam UMC focusses on ventilation-induced diaphragm atrophy in patients with respiratory failure. In addition, we study novel drugs to restore respiratory muscles in ICU patients. How respiration works Our bodies simply cannot function without oxygen. We have therefore no choice but to inhale air and extract the oxygen from it, followed by its distribution by red blood cells to our tissues and organs. Obviously, the lungs are the key organ that controls the inhalation of air. To do this, the lungs need to breathe: they are constantly in

“Damage to the diaphragm during mechanical ventilation”

motion inhaling fresh, oxygen-rich air and exhaling oxygen-poor air, which is supplemented with waste, such as CO2. This motion of the lungs is permanent, occurs about 12–20 times per minute (in rest) and is driven by the so-called “respiratory muscle pump”. The respiratory muscle pump is composed of a large number of muscles in the neck and chest, that act together to drive air into the alveoli. Alveoli are the little ‘sacs’ at the end of the respiratory tree where oxygen and carbon dioxide exchange takes place. The diaphragm is the most important muscle for inhalation. It is situated underneath the lungs and above the liver. The diaphragm is arched upward when relaxed and flattens when it contracts, pulling the lungs down to induce a ‘vacuum’ which allows inhalation. Normally, the diaphragm can handle inhalation well by itself. However, when breathing becomes more difficult, for example due to stiffening of the lungs, other muscles are used to help out. These include the scalene muscles in the neck, the sternocleidomastoid muscles which link the head to the sternum or chest bone, and eventually the abdominal wall muscles for active expiration. When the respiratory muscle pump is unable to maintain adequate CO2 elimination or oxygen uptake, a life-threatening condition occurs, which is when mechanical ventilation becomes necessary.

Human physiology

Control subject

ICU patient

The impact of mechanical ventilation We now know that in patients on mechanical ventilation, respiratory muscle weakness may develop rapidly. One of the main reasons is the sudden inactivity of the diaphragm, imposed by the ventilator. This rapidly induces disuse atrophy in the diaphragm. Our pre-clinical and clinical teams at Amsterdam UMC study the mechanisms underlying the development of respiratory muscle weakness in mechanically ventilated patients. The unique collaboration between our preclinical and clinical groups allows us to approach this important clinical problem from different perspectives. Animal models for long-term mechanical ventilation are used to understand the impact of mechanical ventilation on respiratory muscle structure and function. We ventilate mice and rats for up to 18 hours, using tiny mechanical ventilators. In these studies, we focus on the gigantic protein titin. Titin is the largest protein that is known, comprising ~35,000 amino acids. It spans the entire length of the basic building block of muscle, the sarcomere. Since titin is an elastic protein, it senses the shortening of these sarcomeres during contraction of muscles such as the diaphragm. We found that the elasticity of titin determines the extent of the atrophy in the disused diaphragm during mechanical ventilation in ICU patients. Using biopsies from the diaphragm of ventilated patients, we measure the contractility of the muscle fibres. In addition, we study the structural and biochemical changes that reduce contractility, such as cellular stress induced by reactive oxygen species (known as ‘oxidative stress’). The findings obtained provide important insights in the pathophysiology of respiratory muscle weakness in these patients.

↑ Figure 1 The ultrastructure of diaphragm muscle fibres. Electron microscopy of a diaphragm biopsy of a control subject (left) illustrates the highly organised striation pattern in the muscle cells. The striation reflects the serially linked sarcomeres in a muscle fibre. In the mechanically ventilated ICU patient (right), the sarcomere structure is extremely damaged, as indicated by the complete loss of striation.

Among the things we find are a reduced force response of the sarcomeres in the diaphragm of patients, ultrastructural damage in the muscle fibres and unusually rapid fibrosis, which resembles scarring and impairs tissue structure and function. We also follow diaphragm changes in critically ill patients during their ICU stay. For this, we use a series of pressure transducers, positioned in the stomach and oesophagus of ventilated patients, to assess contractile performance of the respiratory muscle pump. This provides an opportunity to investigate the contractile performance of the respiratory muscles at different time points during admission

in the ICU. Sophisticated analysis of the pressure signals allows early detection of dysfunction and fatigue of the diaphragm (this dysfunction can occur already within the first 24 hours after ICU admission!). In addition, it allows us to evaluate the effects of novel drugs that improve contractile efficiency of the respiratory muscles. For example, we are interested in the ability of calcium sensitisers to improve to force response of sarcomeres to calcium. This is because calcium influx in muscle cells is absolutely required to generate contractile force. → Figure 2 Diaphragm MRI. The MRI image shows the sagittal plane of the thorax, with in black the lungs, in grey the liver and in between them the diaphragm. The image is acquired at the end of inspiration, which is the moment the diaphragm has the greatest thickness (~1 cm).

Furthermore, our groups investigate the feasibility and validity of novel radiological techniques to measure respiratory muscle function. Currently, we focus on tissue Doppler imaging (a bed-side technique to determine diaphragm atrophy), speckle tracking ultrasound (also a bed-side technique that allows to measure diaphragm contractility) and dynamic Magnetic Resonance Imaging (MRI; a more elaborate technique that allows to determine the effect of mechanical ventilation on diaphragm geometry). This is done in

lung diaphragm

liver

collaboration with the Department of Radiology at Amsterdam UMC. The effects of PEEP An example of the multidisciplinary approach is our recent work on the effects of positive end-expiratory pressure (PEEP) applied during mechanical ventilation on diaphragm function. PEEP is routinely applied in ventilated patients to prevent airway and alveolar collapse and, as such, improve oxygen uptake. PEEP increases end-expiratory lung volume. As the increased long volume might flatten the diaphragm, we anticipated that diaphragm structure and function might become affected. To study this, we used a rat model for mechanical ventilation, diaphragm biopsies of critically ill patients and ultrasound (on both rats and patients). Indeed, we found that PEEP shortens the muscle fibres in the diaphragm (Fig. 3). In response, the diaphragm develops atrophy along its long axis. This

Human physiology

Navigatie Spotlight

Alumnus “Keeping pressure on the diaphragm prevents problems with respiration after ICU”

means that ~15% of the serially linked sarcomeres in the diaphragm muscle fibres is absorbed and disappears. We think that this contributes to weaning failure in the ICU, which is the inability to stop mechanical ventilation. We will study this phenomenon, funded by our recently obtained TOP grant from ZonMw-OPEN and R01 grant from the National Institutes of Health (USA). We will use advanced MRI and mathematical modelling to elucidate how mechanical ventilation with PEEP affects the geometry and the contractile function of the diaphragm. This work will reveal not only the magnitude of the PEEP-induced diaphragm shortening, but also whether the shortening is uniform across the whole diaphragm, and if the shortening is sufficient to impair diaphragm contractility. Importantly, we will also study if and how, in critically ill patients, the diaphragm adapts to longterm length changes. In preclinical research, we will study which structures sense the diaphragm muscle fibre shortening that is induced by PEEP, and that drive the molecular changes leading to longitudinal atrophy. Such structures are likely to be mechanosensory proteins such as titin; however, this is an unexplored concept.

↑ Figure 3 Graphic summery of the proposed mechanism by which ventilation with PEEP results in diaphragm weakness and ultimately ventilator weaning failure. The schematic changes in sarcomeres (the contractile units of muscle fibres) from start of mechanical ventilation (T0) to ventilator weaning(T3). PEEP flattens the diaphragm and may reduce muscle fibre length and contractile efficiency (T0→T1). Longitudinal fibre atrophy (T1→T2) causes the absorption of muscle fibers (only one sarcomere is depicted). When PEEP is acutely withdrawn, the end-expiratory lung volume suddenly decreases (T2→T3). This stretches the adapted, longitudinally atrophied fibres to excessive sarcomere lengths. Overlap between myosin (in blue) and actin (purple) filaments within sarcomeres is minimal. This reduces the contractile efficiency of the diaphragm.

The layout of titin within the muscle’s sarcomere makes it ideally suited to sense changes in mechanical loading caused by ventilation with PEEP. To identify the role of titin-based mechanosensing in the development of longitudinal atrophy, we plan to use two genetically engineered titin mouse models, one of which will have a longer, more compliant titin isoform,

and one a stiffer isoform. This work will be performed in collaboration with Prof. Henk Granzier (University of Arizona), a leading scientist in titin biology. If our hypotheses are proven to be right, this will directly impact current clinical practice regarding mechanical ventilation in critically ill patients. For instance, a gradual (rather than acute) withdrawal of PEEP during weaning trials might be advised while closely monitoring diaphragm function. There is much to be gained by improved weaning from mechanical ventilation. Ventilator weaning failure is a major clinical problem; it is encountered in >30% of critically ill patients, its predicted costs in the US are 64 billion USD/year in 2020 (>10% of the total hospital costs!) and, most importantly, patients experiencing weaning failure are at much higher risk of death. Ω

Mechanical ventilation and the COVID-19 pandemic Recently, the issue of mechanical ventilation has gained widespread attention due to the COVID-19 pandemic. Many patients infected by Covid-19 develop a severe pneumonia, leading to respiratory failure. As a result, they require mechanical ventilation for up to several weeks. The consequences of COVID-19 and the long-term mechanical ventilation on diaphragm structure and function are yet unknown, but they might be of major clinical importance for several reasons. First, severe diaphragm weakness developed during the ICU stay might contribute to ventilator weaning failure, thus further prolonging the period in the ICU. Second, if weaning from the ventilator is successful and patients are released from hospital, persisting diaphragm weakness might compromise their quality of life for years, for example by causing shortness of breath during mild exercise. Together with other university medical centres, we are now investigating the diaphragm of COVID-19 patients. To this end, we study diaphragm tissue from patients who did not survive and donated their organs for scientific research.

TOM BANNINK did his PhD at CWI and QuSoft and is now a deep-learning scientist at Plumerai, studying binarised neural networks.

→ In 2013, I received my Bachelor’s degrees in mathematics and physics at Utrecht University. In this period, as well as during the Master’s, I enjoyed competing in team-based algorithmic programming competitions. Programming in general has always been a huge hobby. I started my PhD project at CWI and QuSoft in the field of quantum computing. The topic of this project was rather different than what I had done in my Master’s, and even within my PhD thesis, I covered a rather wide variety of topics, ranging from quantum random walks to quasi-random properties of linear maps to power series in stochastic processes. They all, however, had a rather large programming component.

In the last year of my PhD, a friend pointed me to his friend who had just launched the start-up Plumerai, a company that focuses on Binarised Neural Networks (BNNs). These are relatively new types of neural networks where all weights are constrained to be +1 or -1. Plumerai makes chips that specialise in running BNNs with extremely low power consumption. The company also has a research side which aims to understand and improve the quality of these neural networks. Although constraining a network to have binary weights greatly improves its power consumption, it will also degrade the accuracy. Therefore, a lot of research is required to understand how to train these net-

works in ways that allow them to maintain their usefulness. This research position felt like quite a switch coming from quantum computing, but it was the perfect fit for me as it allowed me to combine the things I like most, programming and mathematics. I have now worked almost half a year at Plumerai and it gets more exciting every day. Ω Insider’s advice: “Having a network was very useful in finding a job, make sure to let your friends know you're looking for a job."

Muscle groups sync to the brain’s rhythm These coordinated neural patterns are also known as muscle synergies.

COEN S. ZANDVOORT is a PhD student at the Institute for Brain and Behavior Amsterdam & Amsterdam Movement Sciences, VU.

→ To voluntarily move like a human, the nervous system has to coordinate the activation of many muscles simultaneously. One could argue that the generation of movement is a computationally heavy task for the nervous system. To reduce the demands, the nervous system may simplify the control by activating a group of muscles by one central command. Such a command involves the timed orchestration of neural patterns to the muscles that are required in a movement.

The current approaches to study muscle synergies, however, cannot quantify which neural structures (e.g., the spinal cord, the brainstem and/or the brain) contribute. Based on locomotion studies in animal models, it was previously thought that these synergies were predominantly controlled in the spinal cord. However, muscle synergies may also manifest in brain(stem) activity. Knowing which and how neural structures are involved in controlling muscle synergies would be helpful for developing interventions. In particular, this would benefit patients with neurological disorders affecting the motor system. We examined whether muscle synergies are represented in the cortical areas – the outer portions – of the brain that control movement, and how these areas are interacting with muscle synergies. The brain and muscular activities of healthy adults were recorded while they were balancing on one leg. We then looked for the neural activity that is coupled in the brain to muscle synergies during the

task to examine how they are linked. The results showed that muscle synergies are represented in the sensorimotor areas of the brain, in particular when the muscle groups involved in the synergy are associated with balance control. These cortical sensorimotor areas and muscle synergies are tightly coupled at neural rhythms that are known for their involvement in sensory and motor processes, namely at 40 Hz. This long-range synchronization between motor cortex and multiple muscles jointly is of interest, as several examples thus far suggested neural synchronization to selectively control individual muscles, such as those in your hand.

Our study is the first to show that muscle synergies are manifested in the brain, where neural oscillations synchronize motor cortex and spinal motor neuron pools, leading to successful and efficient movement execution. This work also offers a methodological approach to explore the feasibility of altering brainsynergy interactions in patient populations. Ω

← Figure Example of muscle synergy representation in the human brain. The coloured areas indicate a rhythmic coupling between the sensorimotor cortex and muscle synergy. This synergy includes muscles of the right leg; hence, the brain representation is most pronounced at the left hemisphere.

Infographic

A roadmap to insect recovery → Despite being generally small and often seen as pests, insects are a vital part of the world's ecosystems. Their roles vary from simply being food for other animals to pollinating and protecting our crops. Unfortunately, insects are globally on the decline, both in numbers and in diversity. A study pub-

lished last year estimated that over 40% of insect species worldwide are threatened with extinction, driven primarily by habitat loss to intensive agriculture, as well as agrochemical pollutants, invasive species and climate change [1]. The good news? Since the main driver of insect decline is hu-

Replace synthetic pesticides and herbicides with ecological agents These include natural pest-controlling agents like insect predators, parasitoids and pathogens. Synthetic agrochemicals tend to accumulate in ecosystems. This can instantly kill insects or have more insidious long-term effects.

Increase (agricultural) landscape heterogeneity Our recent shift toward industrial-scale intensive agriculture has severely affected insect populations. We should practice multi- or inter-cropping, maintain hedgerows and encourage wildflowers to grow between fields.

Increase awareness and use citizen science for data collection Inform the general public of the value of insects to society, and engage them in citizen science projects to collect data on a much larger scale.

Design by Jans Henke Images from pxfuel.com Silhouettes by Robin Heinen

man activity, we also have the power to help their populations recover. With this in mind, Jeff Harvey (VU, NIOO-KNAW) banded together with scientists from 21 countries to produce a 'roadmap' to insect conservation and recovery, from shortterm 'no-regret' solutions to long-term global measures [2].

→ Reference [1] F. Sánchez-Bayo, K.A.G. Wyckhuys doi: 10.1016/j.biocon.2019.01.020. [2] J.A. Harvey, et al. (2020). doi: 10.1038/s41559-019-1079-8 [3] A.C.S. Owens, S.M. Lewis. (2018). doi: 10.1002/ece3.4557

Reduce light, water and noise pollution While water and noise pollution are self-explanatory, artificial lighting also strong effects insects, causing disorientation, attraction (commonly leading to death), desensitisation and impaired communication [3]. Warm-coloured LED lights are generally the most insect-friendly.

Reduce trade of ecologically harmful products and non-native species The economic value of environmentally harmful products can be reduced by trade agreements. Measures should also be taken to limit the introduction of alien species, which can become invasive and destabilise entire ecosystems.

Prioritise key problems To tackle the problem of global insect decline, we must identify priority species, areas and issues. The IUCN Red List assessments of insects should be updated.

Research the effect of stress factors on insect populations The contribution of different stressors that drive insect declines has to be investigated in field studies at the intersects of agricultural and natural habitats.

Analyse overlooked data on insect diversity Much data in private, museum and academic insect collections remain unused. With these data one can form new censuses of past insect diversity, especially in areas where scientific data are lacking.

Enhance conservation and restoration programmes Alongside preserving nature parks, insects would benefit from bottom-up restoration efforts. Reduce management of marginal habitats like roadside verges and encourage people to make their garden insect friendly.

Explore public-private partnerships While part of these measures can be funded by governments, alternative financing initiatives must be explored to achieve sustainable and large-scale change.

Implement global monitoring programmes Standardised monitoring protocols under the auspices of for example the UN or IUCN, should be implemented globally. Establish standardised monitoring sites for long term research.

The impact of these measures should be monitored by research. Such a ‘learning-by-doing’ approach ensures that the conservation strategies are robust to newly emerging pressures and threats. Most importantly, we should not wait to act until we have addressed every knowledge gap. We must act now.

Astronomy

Spotlight

A ménage-a-trois at the inhibitory synapse

Cosmic flashlights in the early galaxies → The universe is transparent. Yet, outer space is not empty, but filled with gas. This gas is transparent because it consists of charged atoms and electrons; it is ionised. The electrons that would absorb high-energy ultraviolet radiation have already been freed from their atoms. But why?

SAM GEEN is postdoctoral researcher at the Anton Pannekoek Institute for Astronomy, UvA.

→ Reference C.-C. He, M. Ricotti and S. Geen, Monthly Notices of the Royal Astronomical Society 492 (4), 4858–4873 (2020) doi: 10.1093/mnras/ staa165

The gas in the universe was not always like this. Before it was ionised, it used to be opaque. It is thought that light from the first galaxies, 13 billion years ago, was responsible for the ionisation. However, it is a mystery how this light was able to reach the gas outside those galaxies: if we look at non-ionised clouds in our own Milky Way, we see that most light is trapped inside the clouds. If this would also be the

case for the clouds in the first galaxies, this would mean that the universe should have stayed opaque.

we see in the Milky Way, which is due to the relatively simple chemical composition of these birth clouds.

In our recent paper, we unlock a piece of the puzzle using large-scale simulations. We compare clouds in the Milky way to clouds similar to those in the first galaxies, and model the light of stars that are tens to hundreds of times as massive as our Sun (depicted by circles in the image). This light ionises the stellar surroundings, thereby destroying the clouds the stars were born in (purple to yellow structures in the image).

The simulations help us understand how light could have escaped galaxies in the young universe, creating the transparent, ionised gas that makes up most of our universe's volume today. Ω

Paradoxically, the denser clouds in the first galaxies allowed more light to escape than the more tenuous clouds

“Stars destroyed the very clouds that gave birth to them” ← Figure The birth clouds in the first galaxies come in different shapes and sizes. Three examples of similar mass but different sizes are shown (left to right), each evolving with time (the left column is 27 million years from top to bottom, the middle is 9 million years, and the right is 2.7 million years. Each column shows six “free-fall” times, or the length of time it would take the cloud to collapse under gravity with no other physics). The colours indicate gas densities from low (black) to high (yellow). As the initially cold and dense clouds form stars (shown as circles), the more massive stars begin to emit high-energy light that heats up and evaporates the clouds (the most energetic light sources are shown in blue and green). As the stars get old, they expand, cool down and stop producing high-energy light (shown as red circles).

SABINE SPIJKER is Amsterdam Science editor and professor at the CNCR, Vrije universiteit Amsterdam

→ For every output of our brain, communication between neurons is essential. Some of this communication ‘excites’ the other neuron, some of it inhibits the other neuron. This inhibitory communication is carried out by neurotransmitters such as GABA and glycine, and their corresponding receptors. These receptors normally have a wealth of other proteins interacting with them, assuring proper function. In this paper, Sophie van der Spek and colleagues set out to find the interactors of the glycine receptor. They isolated several glycine receptor complexes in which multiple proteins from the mouse brain resided. To know which of these proteins is able to interact with what other proteins they used a named ‘YeastTwo-Hybrid’. You express the protein you are interested in in yeast cells in a way that it is fused to a portion of a transcription factor. These yeast

cells already express a complement of proteins that are normally expressed in the mouse brain, where these fragments are fused to the second half of the same transcription factor. Only when the yeast cell expresses both parts, namely a protein that can interact with the protein of interest, the two parts of the transcription factor become fully functional due to their hybrid the two interacting proteins make, and will then activate a reporter gene. This reporter gene can make yeast cells have a blue appearance, as visible in this figure, to ease finding those cells that express the protein of interest. Sophie and colleagues established that the glycine receptor complex harboured Gephyrin and Iseq3, both proteins known from their interaction with the GABA receptor, the other type of inhibitory receptor. Specifically, Iseq3 was pulled into the comples because it interacts with Gephyrin basically forming a ménage-a-trois. In addition, it was rather surprising that a family member of Iqsec3, namely Iqsec2, which is normally found at excitatory rather than

inhibitory synapses was able to form a distinct glycine receptor complex. As such, this paper is the first step in revealing the (functional) make-up of inhibitory synapses in our brain. Ω Reference van der Spek SJF, Koopmans F, Paliukhovich I, Ramsden SL, Harvey K, Harvey RJ et al. Glycine Receptor Complex Analysis Using Immunoprecipitation-Blue Native Gel Electrophoresis-Mass Spectrometry. Proteomics 2020; 20: e1900403.

Figure A yeast two-hybrid assay confirms the interaction between Iqsec3 and Gephyrin. Yeast colonies turn blue when the proteins they overexpress interact with each other. Paper replicates of the blue yeast colonies are shown for those that express the N-terminal region of Iqsec3 (amino acids 1-649) or full-length Iqsec3 in combination with the G-domain of Gephyrin (amino acids 1-173) or fulllength Gephyrin (1-736). Iqsec3 does not interact with the C and E domain of Gephyrin. Interaction between the Gdomain of Gephyrin and the E domain of the GlyR ß subunit was used as positive control.

Support the research into corona at Amsterdam UMC → The corona crisis isn’t over. The urgency for research was and still is very high during the worldwide outbreak of the COVID-19 virus. We still need to battle the virus and find a treatment for the infected patients. Researchers around the world have taken action to deal with this crisis by starting new scientific research, also at the Amsterdam University Medical Center (Amsterdam UMC). In these extraordinary circumstances, the fundraising foundations of the academic institutions in Amsterdam joined forces and founded the ‘Corona Research Funds Amsterdam UMC’. The result is a unique collaboration between the AMC founda-

tion, the VUmc Fund, the University of Amsterdam, the Amsterdam University Fund (Amsterdam Universiteitsfonds), the VU Amsterdam and the VU Association (VUvereniging). The purpose: providing researchers of Amsterdam UMC the opportunity to start new and promising research projects as soon as possible to battle the virus and treat patients. The fund has funded seven new projects in the last months. For example, a research project about the recovery of COVID-19 patients after a long stay at the ICU. Ω You can help us too! For more information, visit www.coronaresearchfonds.nl

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About

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Editorial Board

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ANNIKE BEKIUS PhD researcher Human Movement Sciences, VU

win NADINE BÖKE Communications advisor Faculty of Science, UvA

the first ten correct answers will win an Amsterdam Science canvas bag.

answer puzzle issue 8

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JANS HENKE PhD researcher Physics, UvA

#08 November 2018

Amsterdam Science Issue

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Amsterdam Science

The correct answer to the puzzle from issue 9: the root of a plant, infected with a filamentous fungi.

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#10 December 2019

Amsterdam Science

Conformal motions

Interview Erwin Peterman

Empathy for pain

Detecting ghosts

→ Amsterdam Science gives Master’s students, PhD and postdoc researchers as well as staff a platform for communicating their latest and most interesting findings to a broad audience. This is an opportunity to show each other and the rest of the world the enormous creativity, quality, diversity and enthusiasm that characterises the Amsterdam science community. Amsterdam Science covers all research areas being pursued in Amsterdam: mathematics, chemistry, astronomy, physics, biological and biomedical sciences, health and neuroscience, ecology, earth and environmental sciences, forensic science, computer science, logic and cognitive sciences.

cartoon

FRANCESCO MUTTI Assistant professor Biocatalysis, Faculty of Science, UvA

Supercapacitors

Interview Caroline Nevejan

CÉLINE KOSTER PhD researcher Clinical Genetics, Amsterdam UMC/AMC

Relativistic jets

Interview MiCRop

Memory traces

HELEEN VERLINDE Amsterdam Science Magazine manager

SHUO CHEN PhD researcher, Informatics Institute, UvA HARSHAL AGRAWAL PhD researcher Nanoscale Solar Cells, AMOLF THOMAS AALDERS PhD researcher Molecular Plant Pathology, UvA JOP BRIËT Senior researcher, Algorithms and Complexity group, CWI MAGDA SOLA GARCIA PhD researcher Photonic Materials, AMOLF SARAH BRANDS PhD researcher Massive Stars API, UvA

The current editorial board of Amsterdam Science consists of Master’s students, PhD researchers and other members of the science faculties of UvA and VU, the Academic Medical Centre (UMC/AMC) and various research institutes (ARCNL, AMOLF, CWI and NIN) in Amsterdam. We aim towards full representation and active participation in our editorial board of every research institute located in Amsterdam.

ESTHER VISSER PhD researcher, Center for Neurogenomics and Cognitive Research (CNCR), VU

Editors in chief

IRAKLIS VRETZAKIS Master’s student Neurosciences, VU

SABINE SPIJKER, Professor of Molecular mechanisms of cognition, VU

Have a look at: www.amsterdamscience.org for the remit of the magazine and upload your contribution for consideration for a future issue of Amsterdam Science.

One of the editors will contact you, primed to hear about your exciting story or striking image, and to discuss with you how it could reach a broad audience via publication in the magazine.

MICHEL HARING, Professor of Plant Physiology, UvA

PETER HORDIJK Professor Vascular Biology, UMC ATHIRA MENON Postdoc researcher API, UvA

Insects also have to take measures

Are you eager to share the exciting research you published with your colleagues? Are there developments in your field that we all should know about? And are you conducting your research at one of the Amsterdam universities or research institutes? © Bart Groeneveld

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Guess Perspective what?

To investigate interactions between proteins scientist can use a yeast two-hybrid assay. Yeast colonies on paper replicates turn blue ONLY when the proteins they produce interact with each other. The image shows a panel of different proteins that have been tested; only a few are positive for interaction and stain blue (for details see page 21).