One of the most important problems in experimental biology has to do with variability / heterogeneity (Rubin, 1990): why do different organisms react differently to the same perturbation or reagent? This is observed even among clonal populations (e.g., cohorts of planarian flatworms descended from the fission of 1 animal and living in the same environment), and has huge implications for both efficacy and side-effects of biomedical interventions. Understanding and being able to predict such outcomes requires quantitative, fully-specified models and an analysis of the attractors in the state space describing their dynamics (Davies et al., 2011; Huang et al., 2009). Unfortunately, uncovering such models is very difficult – far more challenging than just describing the epistasis between proteins necessary for a process to occur. We recently addressed this problem by creating a machine learning platform to help infer mechanistic models of complex processes with stochastic outcomes (Lobikin et al., 2015a).

Our lab studies developmental bioelectricity – the mechanisms by which cells (not just neurons) coordinate their activity using voltage gradients (Levin, 2014; Tseng and Levin, 2013). About 10 years ago, we began using the frog embryo to ask what would happen if a small number of widely-distributed somatic cells during embryogenesis was selectively depolarized (resting potential brought closer to 0) (Morokuma et al., 2008). We took advantage of the glycine gated chloride channel, which turned out to be expressed in a ubiquitous but sparse cell population (Blackiston et al., 2011). We used ivermectin, a drug that specifically locks this channel in an open state, to allow negative chloride ions to leave cells down their concentration gradient and thus depolarize that cell population – akin to clonal analysis. To our surprise, the first effect we noticed was not in those cells themselves, but in melanocytes (pigment cells derived from the neural crest). In depolarized embryos, the melanocytes converted to a metastatic-like phenotype: they over-proliferated, changed shape to a drastically-arborized morphology, and invaded inappropriate areas of the body (brain, blood vessels, soft internal organs) in an MMP-dependent manner.

We called the GlyR-expressing cells “instructor” cells, since they were able to change the behavior of a remote cell population, and used a variety of targeting and rescue strategies to show that the effect did occur at long range (was not cell-autonomous). The phenotype recapitulated the metastatic phase of melanoma, but without DNA damage, mutations in oncogenes, or carcinogen exposure (Chernet and Levin, 2013; Lobikin et al., 2012). The bioelectric disregulation of instructor cell state was sufficient to kickstart this process; the phenotype was very clean – the tadpoles developed normally, although later we also found subtle effects on muscle development and vasculature (Lobikin et al., 2015b). The affected tadpoles were not hard to identify: they turned pitch black because of the excess and spread-out shape of the melanocytes which took over their bodies.

Investigating the mechanism of this effect was relatively straightforward. We dissected the signaling pathway and showed that it relied on a number of components related to serotonergic signaling, via the serotonin transporter (which was under voltage control) and cAMP. We implicated a number of signaling proteins in this cascade, tested their functional relationships with each other, and made the usual “arrow model” of the process (Blackiston et al., 2011). But one aspect remained unsatisfying. The phenotype was all-or-none: we never observed a partially-converted animal. Depending on the penetrance of any given functional treatment, some percentage of the tadpoles would convert (entirely), and some would remain unaffected. It’s as if they were flipping a (biased) coin to decide, but all of the cells in the animal were flipping the same coin. And our arrow diagram model could not predict or explain the precise percentage of melanoma-converted animals that would result from any given experiment. Indeed, the more experiments we did, the harder the problem got, because the dataset that had to be matched by any candidate model was getting more and more complex. This is a pervasive problem in many areas of biology, because the ever-growing mountain of data that is being published makes it ever more difficult for scientists to come up with models that fit the data.

To address this, we turned to a platform we recently designed, using artificial intelligence techniques to help human scientists infer predictive models from published functional data on planarian regeneration (Lobo and Levin, 2015). The system (Lobikin et al., 2015a) used evolutionary computation to search the space of all possible networks comprised of the elements we knew were involved in melanocyte regulation by instructor cells’ voltage. Each network was evaluated against a set of our data, to see if it correctly predicted what percentage of animals would become converted if a specific reagent was used to perturb the pathway. What makes this system powerful is that it does not exhaustively test all possible networks, but uses mutation and a survival of the fittest strategy to home in on the correct answer. The system literally evolved a network specifying the functional connections among the pieces and the strength of each connection, which could correctly recapitulate the complex probabilistic dataset.

Remarkably, not only did it identify a network that correctly explained the data against which we searched, but that same network correctly predicted new experiments it had never seen (which were not present in the training phase). One of the surprises revealed by the discovered model was that there are actually 2 different molecular states that lead to hyperpigmentation. Their resultant phenotype is the same, and would not have been recognized as different based on cell- or tissue-level characterization, but the network model showed that there are two distinct attractors corresponding to the converted state, and thus two molecularly-different ways to reach the same outcome.

This model can now be interrogated for testable mechanistic predictions, and can be used to generate suggested interventions for getting the desired outcome in specific situations. We think this is a proof of principle for using this strategy to derive predictive models matching a complex dataset (with multiple stochastic outcomes for the same input), which could be used by many labs to infer mechanisms from functional data (in basic research), or to identify models matching individual physiological and genetic circuits (for personalized biomedicine approaches). We believe that this is an early step in the creation of the next generation of bioinformatics tools (Lobo et al., 2014; Lobo et al., 2013) – a part of the nascent “robot scientist” field (King et al., 2009; Sparkes et al., 2010), which must augment the efforts of human researchers if we are to glean insights and actionable intelligence from the ever-growing deluge of data.

We welcome collaborations with researchers interested in applying these techniques to their own functional data.

References

Blackiston, D., Adams, D. S., Lemire, J. M., Lobikin, M. and Levin, M. (2011). Transmembrane potential of GlyCl-expressing instructor cells induces a neoplastic-like conversion of melanocytes via a serotonergic pathway. Dis Model Mech 4, 67-85, http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=20959630

Chernet, B. and Levin, M. (2013). Endogenous Voltage Potentials and the Microenvironment: Bioelectric Signals that Reveal, Induce and Normalize Cancer. J Clin Exp Oncol Suppl 1, http://www.ncbi.nlm.nih.gov/pubmed/25525610

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4267524/pdf/nihms621827.pdf

Davies, P. C., Demetrius, L. and Tuszynski, J. A. (2011). Cancer as a dynamical phase transition. Theor Biol Med Model 8, 30, http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=21867509

Huang, S., Ernberg, I. and Kauffman, S. (2009). Cancer attractors: a systems view of tumors from a gene network dynamics and developmental perspective. Seminars in cell & developmental biology 20, 869-876, http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=19595782

King, R. D., Rowland, J., Oliver, S. G., Young, M., Aubrey, W., Byrne, E., Liakata, M., Markham, M., Pir, P., Soldatova, L. N., et al. (2009). The automation of science. Science 324, 85-89, http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=19342587

Levin, M. (2014). Molecular bioelectricity: how endogenous voltage potentials control cell behavior and instruct pattern regulation in vivo. Mol. Biol. Cell 25, 3835-3850, http://www.ncbi.nlm.nih.gov/pubmed/25425556

Lobikin, M., Chernet, B., Lobo, D. and Levin, M. (2012). Resting potential, oncogene-induced tumorigenesis, and metastasis: the bioelectric basis of cancer in vivo. Phys Biol 9, 065002, http://www.ncbi.nlm.nih.gov/pubmed/23196890

Lobikin, M., Lobo, D., Blackiston, D. J., Martyniuk, C. J., Tkachenko, E. and Levin, M. (2015a). Serotonergic regulation of melanocyte conversion: A bioelectrically regulated network for stochastic all-or-none hyperpigmentation. Sci Signal 8, ra99, http://www.ncbi.nlm.nih.gov/pubmed/26443706

Lobikin, M., Pare, J. F., Kaplan, D. L. and Levin, M. (2015b). Selective depolarization of transmembrane potential alters muscle patterning and muscle cell localization in Xenopus laevis embryos. Int J Dev Biol, http://www.ncbi.nlm.nih.gov/pubmed/26198143

Lobo, D., Feldman, E. B., Shah, M., Malone, T. J. and Levin, M. (2014). A bioinformatics expert system linking functional data to anatomical outcomes in limb regeneration. Regeneration, n/a-n/a, http://dx.doi.org/10.1002/reg2.13

Lobo, D. and Levin, M. (2015). Inferring Regulatory Networks from Experimental Morphological Phenotypes: A Computational Method Reverse-Engineers Planarian Regeneration. PLoS Comput Biol in press,

Lobo, D., Malone, T. J. and Levin, M. (2013). Towards a bioinformatics of patterning: a computational approach to understanding regulative morphogenesis. Biol Open 2, 156-169, http://www.ncbi.nlm.nih.gov/pubmed/23429669

Morokuma, J., Blackiston, D., Adams, D. S., Seebohm, G., Trimmer, B. and Levin, M. (2008). Modulation of potassium channel function confers a hyperproliferative invasive phenotype on embryonic stem cells. Proc Natl Acad Sci U S A 105, 16608-16613, http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18931301

Rubin, H. (1990). The significance of biological heterogeneity. Cancer Metastasis Rev 9, 1-20, http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=2208565

Sparkes, A., Aubrey, W., Byrne, E., Clare, A., Khan, M. N., Liakata, M., Markham, M., Rowland, J., Soldatova, L. N., Whelan, K. E., et al. (2010). Towards Robot Scientists for autonomous scientific discovery. Autom Exp 2, 1, http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=20119518

Tseng, A. and Levin, M. (2013). Cracking the bioelectric code: Probing endogenous ionic controls of pattern formation. Communicative & Integrative Biology 6, 1-8, http://www.landesbioscience.com/journals/cib/article/22595/

(5 votes)

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This Sticky Wicket article first featured in Journal of Cell Science. Read other articles and cartoons of Mole & Friends here.

“Watch out, you might get what you’re after! Dee-dee dee-dee-dee-dee. I’m an or-din-ar-y guy.” Hey, there. Just chilling to some old tunes and enjoying a cloudy day, curled up with some journals and a cup of ‘tea.’ “There. Has. Got. To. Be. A. Way.”

Speaking of reading, have you ever noticed that there are some ideas, although discredited (at least inmy mind), that will just not go away? In my own fields (there are a few fields I work in) there are a lot of examples of these. I’m sure you can identify some too. Examples? ‘Nature is logical.’ ‘Evolution seeks the simplest solution to a problem.’ ‘Biological processes are elegant (in the formal sense).’ ‘We evolved from organisms that are alive today.’ ‘There is a ladder of evolutionary progress.’ And then there are many that go in the form, ‘Things work like this: X causes Y.’ Or even worse, ‘X explains Y.’ Many of these are specific to an area of course, but you know what I mean. I hope you know what I mean.

Someone publishes something shaky, or explained as an artifact, and it gets cited and cited and cited. Why? I bet there are a bunch of reasons, and before we wax on about how we might do something about this, it might be good to consider the reasons. Maybe we don’t want to do something about it. Or maybe we do. I’m in a ‘list’ sort of mood, so here is a list. Reasons why questionable (or outright wrong) stuff sticks around. Or, if you prefer: how bad ideas survive.

1. The idea is attractive on the surface. This is one reason why some ideas just won’t curl up and go away. As humans, we want explanations that we can wrap into neat little packages. If we have only a superficial understanding of a process, or sadly, even if we have a very good understanding, we may jump to untested conclusions and assume that they are correct. And if someone informs us that they are not, we can forget this information in favor of the ‘neat package.’ We may say that science is in the details, but we tend to remember the things that fit nicely together, even if they are wrong. Some philosophers of science insist that our mission is to disprove hypotheses, but while this sometimes is indeed the case, most of us have an idea and find evidence to support it. The more we like an idea, the more readily we enlist ‘facts’ into its support, and discount those that don’t fit. Of course we should resist this temptation, but as I say, it’s human nature.

2. The people who promote the idea don’t go away. This is something I realized a long time ago: when I was a feisty young Mole, I might hear a talk, or read a paper, that I dismissed as nonsense (okay, I still do that). But then I’d make the mistake of thinking that that was the end of it. Since then I’ve noticed that when a popular idea is disproven, the folks who have invested time and effort in the idea can continue to promote it, choosing to ignore the inconsistencies. Small groups continue to have meetings where they all agree to the discredited idea, and they publish (perhaps by having each other review the work). The ‘impact’ is often minimal, but it doesn’t go away. One field I work in has a lot of such ‘splinter groups’ and if a member of such a group happens to be chairing a more major meeting (it happens!) we find whole sessions devoted to ideas that we thought had died years ago. And sometimes, if a proponent of a discredited idea has influence (by position, or perhaps by other, more valid contributions) some of us in the mainstream prefer to cite the ideas rather than ‘rocking the boat.’ It’s easier.

3. We’re lazy. There, I’ve said it. We really are. And by this, I mean, intellectually lazy. We are passionate about the work we are doing, and want people to take it seriously, but when we put it into the context of the literature we often rely on information we have gotten from reviews rather than educating ourselves with a critical reading of the primary literature. And here’s where this gets really bad: when we write a review, we rely on earlier reviews for our information. “But Mole,” you counter, “when I write a review I do literature searches, I don’t rely only on older reviews!” Good for you. But how often to you only depend on what the abstract of a paper says when you need a few bits of information to make a point? How often do you examine the data in support of a statement you wish to make in your review article, or the introduction of your paper? I don’t mean you, of course, I mean ‘other people.’ Lazy people.

4. Even wrong ideas are useful. This is insidious, and it happens all the time. Say we have submitted a body of work that we feel makes an important contribution, but our reviewers want to know ‘the mechanism’ responsible for one of the observations. Finding the actual mechanism could take us years, and it isn’t really the point of the paper. But there is an idea out there, however discredited, that we can invoke to satisfy the reviewer. So we identify the correlates predicted by the idea, show them in our system, cite the questionable literature, and hope we can slide it past the reviewer (who is busy working on his or her own work, so lets it go). Presto, another bad idea gets a new life.

5. Even bad ideas are based on stuff that works. Not always, but sometimes. I’ll give you an example. Years ago, when the world (and siRNA) was young, there was a construct that apparently silenced an interesting gene and gave a useful phenotype. It turned out that it was off target, and the authors made sure to let the readership know (and kudos to them for their prompt transparency). But that didn’t stop dozens of papers that used the same construct to produce the phenotype in their own systems, publishing that it was consistent with their own idea of what was going on (and based on the wrong target). Ugh! But this sort of thing goes on all the time. Only great diligence on the part of reviewers (and authors!) can prevent this, but, sigh, see number 3.

6. Publications in ‘top’ journals trump publications in ‘lesser’ journals. Maybe you knew this was coming. Someone publishes something interesting, really interesting, in a glossy journal, or one with nice soft pages. But, as it turns out, it’s just wrong. The ‘top’ journal isn’t particularly interested in publishing results that discredit their publication (which is getting lots of citations, see number 3). So researchers who can show that the work was misinterpreted, not reproducible, or just plain wrong submit to journals without the same impact factor, and sadly, without the same impact (these should not be the same thing). So while those working closely in the field know that the original paper was wrong, many who are in other fields (for whom the bad idea is nevertheless ‘useful,’ see number 5) and others who write reviews (see number 3) go with the work in the ‘top’ journal. I’m not saying that this is how it should be, but it is what it is.

7. There are other reasons people want the idea to stick around.  Sadly, this is something we have to live with – not everyone is interested in what careful research has to tell us. Some of this relates to emotional investment, and some to alternative agendas. Examples of the first can be found in assertions that vaccines cause autism, or cell phones cause cancer – in the absence of a satisfactory explanation, people who are emotionally involved with a question will cling to any answer, regardless of its validity. For the second sort, economic consequences of findings are often offset by stringent adherence to discredited ideas. We know this, but it is sometimes startling how pervasive it is, and not only among non-scientists. Even scientists can have conflicts of interest (although in my case, they never add up to much moola – I’d love to have some real conflicts of interest. But I digress.) And perhaps the worst conflict of interest? If my ideas are proven wrong, I might have trouble getting my next grant, and thus difficulty maintaining my lifestyle, so I have a very vested interest in keeping my bad idea alive. I don’t me an ‘I’ of course, I mean ‘someone else,’ but I put this into the first person to be polite. Perhaps I should have said, “the vicious piranha, who doesn’t care about anyone but himself, has a vested interest.”

Okay, so that’s a few of the reasons why not all bad ideas don’t go away. What can we do about it? Hey, this is Mole here – you know I’m going to make some suggestions. But they may not be exactly what you expect. Are we going to burn down the house of bad ideas? Stay tuned.

(4 votes)

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I am a third year PhD student and I work on limb regeneration in a non-model organism: Bolitoglossa ramosi, a salamander belonging to the family Plethodontidae. These salamanders show some important biological differences when compared to the most studied models in this field (axolotls and newts), such as the absence of lungs and postaxial development of the digits. They also undergo direct development, i.e. they hatch from their eggs as a little version of the adult, without intermediate larval stages.

Our lab focuses mainly on the gene expression profile of limb regeneration in this organism, using RNA-Seq. To the best of our knowledge, the full details of limb regeneration in terrestrial salamanders, as well as the genes that are involved in this process, have been not yet been described Therefore, it is important to evaluate the difference in the genetic profiles of different species of salamanders during the limb regeneration process.

In the spring of 2015 I enjoyed one of the most fascinating experiences of my life , both academically and personally. I am doing my PhD in Colombia, in a field almost unknown in my country and where the facilities and grants are limited. When I heard that I would have the opportunity to visit the lab of Jeremy Brockes at UCL (London) for one month, thanks for a Development Travelling Fellowship and my lab, I felt very excited. I was going to visit a country which is know for a lot of good things, to learn from people that have been working for many years in this wonderful biological process that is regeneration, a process that interested great scientist, such as T.H Morgan.

The main reason for this visit was to share the result of my thesis with the researchers of Jeremy’s lab and hear their comments and suggestions to help me complete my research in my country. I also wanted to learn general techniques that may be helpful for my project in the future, as well as experience one of the main models in this field, the newt (Notophthalmus viridescens), the main organism of choice in the Brockes lab.

During this short visit a learnt useful tips on the best way to perform certain techniques such as qPCR, immunohistochemistry, injection into fertilized newt eggs, electroporation in adult salamanders, and transfection in salamander cell cultures. The results that I got during my visit allowed me to analyze different situations, both when you see the result that you expect and when you get a completely unexpected outcome.The discussions around the reasons for unexpected results were for me the most important, because I believe that you learn more from mistakes or strange results.

In general the aims of the visit were successful. Due to time limitations I was obviously not able to achieve all of them, but the members of the lab tried to support me and taught me what they could in this short period. Additionally, during this visit I had the opportunity to visit the lab of Aziz Aboobaker (University of Oxford) for a couple of days. With him I had the opportunity to discuss some points of my project, and both him and his lab gave me many suggestions, particularly on the bioinformatics approaches used in my research.

This visit was a wonderful life experience. I had the opportunity to meet many researchers in this field, including some student that will be my coworkers in the future. It was also very important for me personally to visit this beautiful city.

I am very grateful to Jeremy Brockes and his lab for allowing me to visit an learn from them, and to Aziz lab’s for their suggestions, The Company of Biologist and my lab for the economic support to fulfill this visit.

(7 votes)

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This interview first featured in the Journal of Cell Science and is part of their interview series Cell Scientists to Watch.

What motivated you to become a scientist?

My motivation was being curious. My family is religious and everything was kind of explained by religion but I have this need of knowing more about life. There was a news piece on TV – the presentation of the Nobel Prize; I don’t even remember who it was but that inspired me. I think I was 14 years old and, so, I made up my mind that I wanted to follow biology and be a scientist.

You work on nuclear reprogramming and induced pluripotent stem cells. What are the specific questions that your group is currently trying to answer?

We know what the reprogramming players are but we don’t really understand how it all works. The questions we are addressing are related to trying to understand what the molecular mechanisms are, by which the key reprogramming factors work. We know there are transcription factors that mediate reprogramming; but how do they do it? These transcription factors are encoded by genes that are expressed in our target cells – pluripotent cells; specifically, they are Oct4, Nanog and Sox2. Some are Yamanaka factors, others are encoded by genes that I have identified as having nuclear reprogramming capacity. Nanog was, actually, the first identified gene with nuclear reprogramming ability in the conversion of somatic cells back into pluripotent cells. I published this work just a few months before the Yamanaka discovery. Since then, I continued studying how Nanog mediates reprogramming.

What are the experimental roadblocks that you faced and how did you address them?

Well, you’re always facing experimental roadblocks. To me, whenever they appear I see a great opportunity to make a relevant finding. The induced pluripotent stem (iPS) cell system had clear advantages over the cell fusion system I was using, because you could define your factors and at the end generate diploid pluripotent cells. But when I adopted Shinya Yamanaka’s system, the only cell products I was making were these highly proliferative cells that wouldn’t undergo the conversion into iPS cells. I found inspiration in the work that my colleagues in the lab were doing. They were defining new culture conditions to maintain pluripotent cells’ self renewing, and when I used their conditions in the reprogramming system they turned out to be instructive in terms of inducing these cells to undergo reprogramming into iPS cells. So out of an experimental roadblock, I ended up making what was a very interesting finding at the time, which highlighted the importance of the culturing environment for the reprogramming process. When you face difficulty, it can actually be quite exciting.

How did you establish your collaborations and what advice on collaborating would you give to someone who is planning to start their own lab?

Many of the collaborations I established came naturally. It was easy to collaborate with people I knew from my time as a postdoc, and it was also very straightforward to collaborate with scientists at the same career stage as me. Sometimes, with collaborations, there are periods when there is some miscommunication and delays, and that can be quite frustrating. I think that, once you have a collaboration, if you are a new PI, it’s really important that you have continuous communication because misunderstandings can lead to conflict. It can happen that there is a misunderstanding about who is the corresponding author in a collaborative work, so it’s good if there is communication and a clear understanding from the beginning.

Many early-career scientists find that the advice given by senior scientists on how to establish a successful academic career can be outdated in the current funding climate. As someone who has established his lab relatively recently, what advice would you give?

What you just said is correct, I think they’re a bit detached from the reality of a new PI. If you thought your PhD was hard and your postdoc was difficult, being a PI is even harder. Don’t take anything for granted, because everything is going to be difficult; getting funding is going to be difficult, and publishing work is going to be more difficult than when you were a postdoc. Having that big name at the end was actually a great help to get your work under review, and you don’t have that when you start your own lab. Talk to editors at meetings, so they know who you are. If you find that obtaining funding is difficult, keep trying, be persistent. So the advice I give is: it’s hard, so be prepared. Don’t think it’s just a continuation of your postdoc – it’s a lot harder and it’s a learning process.

When you started your own lab, were there any challenges you faced that you didn’t expect?

The greatest challenge was that I thought it would be easy to obtain grant funding. At the start – because I’d done OK and I had a few offers to go to different institutes to start my own lab – I had the impression that it was going to be easy to obtain funding. I was quite fortunate that I got the first grant that I applied for, but there were some issues. It was my first application and I was not well advised as to how much the costs would be, and so this grant was a bit short on funding. Essentially, I had the budget for one post and limited research consumables in a field which is highly competitive and where experiments can be quite expensive. I needed to do certain adjustments, and it was hard to go through that 5-year period with what was quite limited funding.

Do you think taking time for science outreach activities should be more of a priority for scientists?

I think it’s important for the general public to hear from the scientists directly, to be educated about what we really do in the lab, and not to just have this view of science from what they read in tabloids and newspapers. At the same time, it’s actually quite a rewarding experience for the PI. I’ve been surprised with the questions I’ve had from the lay audience. They tend to be quite interesting!

I asked you earlier about why you became a scientist. What motivates you now?

Science is a bit like an addiction. I’d say I’m continuously excited with the next thing: the next question, the next result, the next experiment. It’s a passion, it’s an obsession. It’s finding out the answer to the question and getting that burst from that finding. And I need that to be happy; so, yes, I’m addicted to science.

Could you share with us an interesting fact about yourself that people wouldn’t know by just looking at your CV?

I have a passion for football. I support Benfica, my local team back in Portugal. I follow the results and I watch the games on the computer whenever I can. I also, kind of passionately, follow the Portuguese national football team. I’d say that that is probably my second obsession.

Also, watch this additional short clip:

(3 votes)

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The Helmholtz Zentrum München (HMGU; https://www.helmholtz-muenchen.de) – a research institution within the Helmholtz Association of German Research Centers, is a leading center in health research with a focus on Environmental Health. The Comprehensive Pneumology Center (CPC, www.cpc-munich.org) at HMGU is a translational research center dedicated to respiratory medicine, which is also a partner site of the German Center for Lung Research (DZL; www.dzl.de), an association of the leading university and non-university institutions dedicated to lung research in Germany. Using translational research methods, the CPC seeks to develop new approaches for the prevention, diagnosis and therapy of chronic lung diseases, most importantly chronic obstructive pulmonary disease (COPD), diffuse parenchymal lung disease (DPLD), endstage lung disease, or lung cancer.

The Research Group Herbert Schiller, established within the HMGU as part of CPC and DZL from October 2015, focuses on mechanisms of tissue regeneration and the role of cell-matrix adhesions in stem cell differentiation (see references below^1-4).

In particular, the group aims at characterizing the extracellular niche of the distal airways and its function in regulation of airway epithelial homeostasis, regeneration upon injury, and metastatic colonization. Using systems biology tools, such as mass spectrometry driven proteomics and single cell expression analysis, in combination with mouse models of lung disease we wish to identify fundamental molecular principles of tissue/organ regeneration and homeostasis.

1. Schiller, H.B. et al. Time- and compartment-resolved proteome profiling of the extracellular niche in lung injury and repair. Molecular systems biology 11, 819 (2015).
2. Schiller, H.B. et al. beta1- and alphav-class integrins cooperate to regulate myosin II during rigidity sensing of fibronectin-based microenvironments. Nature cell biology 15, 625-636 (2013).
3. Schiller, H.B. & Fassler, R. Mechanosensitivity and compositional dynamics of cell-matrix adhesions. EMBO reports 14, 509-519 (2013).
4. Schiller, H.B., Friedel, C.C., Boulegue, C. & Fassler, R. Quantitative proteomics of the integrin adhesome show a myosin II-dependent recruitment of LIM domain proteins. EMBO reports 12, 259-266 (2011).

For this purpose HMGU offers a position at the earliest possible date for a

Postdoctoral Scientist – Keywords: Basement membrane composition and architecture, stem cell niche, lung development, injury and regeneration, proteomics

Job description: The postdoc should aim at establishing a functional understanding of the spatiotemporal variation of the composition of basement membrane niches along the distal airway tree. In particular, the impact of basement membrane biology on stem cell dynamics upon lung injury and repair shall be addressed. The project will encompass a variety of state of the art methods including immunofluorescence imaging, mass spectrometry driven proteomics and single cell expression analysis, in vivo injury mouse models, as well as in vitro organoid models.

Your qualifications: You should hold a PhD in biology, biochemistry, or an equivalent field and have gained profound expertise in the analysis of mouse models, mouse (Cre/lox) genetics, mouse dissection, histology and immunofluorescence imaging during your PhD. You also should have excellent skills in state of the art molecular biology methods (e.g. CRISPR and molecular cloning) as well as statistical data analysis.

Our Offer: We offer you working in a young creative team in an innovative, well- equipped and scientifically stimulating surrounding with a variety of training opportunities (including mass spectrometry based systems biology). The full-time position (TV-L E13) is sponsored by the HMGU for a duration of three years with the possibility of extension. The Helmholtz Center Munich as holder of the Bavarian Advancement of Women Prize and of the Total E-Quality Certificate is striving to increase the overall proportion of women on its staff and thus expressly urges qualified women to apply.

We look forward to receiving your application containing a CV, list of publications, a letter of motivation, as well as names and phone number to two referees via e-mail.

Please send your application to:

Kathleen Junge

E-Mail: cpc-jobs@helmholtz-muenchen.de

Telefon: 089 3187-4698

Helmholtz Center Munich

Comprehensive Pneumology Center (CPC)

Institute of Lung biology and Disease (iLBD)

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This cartoon was first published in the Journal of Cell Science. Read other articles and cartoons of Mole & Friends here.

Part I- ‘The imposter’

Part II- ‘The teaching monster’

Part III- ‘The Pact’

Part IV- ‘The fit’

Part V- ‘The plan’

(4 votes)

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Here are the highlights from the current issue of Development:

Spatial mapping in the brain

Many sensory systems show topographic mapping: the spatial organisation of peripheral receptors is preserved in the brain regions where the sensory information is relayed. One example of such mapping is found in the mouse somatosensory system, where there is clear spatial organisation of the trigeminal ganglion (TG) neurons innervating the whiskers and of their central axons, which in turn project somatotopically to the brainstem. Whisker pattern provides a template for somatotopic map formation, but is it sufficient? Filippo Rijli and colleagues (p. 3704) have devised an elegant neuronal tracing experiment to investigate this, using an Edn1 mutant mouse line that has ectopic whisker rows in the lower jaw. They find that TG neurons innervating these ectopic whiskers acquire molecular characteristics of neurons that normally innervate the whiskers of the upper jaw, suggesting that peripheral input influences the molecular signature of these neurons. However, spatial segregation of these neurons and their axons is poor and topographic mapping fails. Thus, while peripheral signalling influences neuronal identity – and, the authors show, can at later stages cause some repatterning of neuronal targeting – it is not sufficient to instruct topographic mapping in the brain; neuron-intrinsic systems are also essential.

Mnx1: making and maintaining β-cells

Endocrine cell differentiation in the pancreas must be tightly controlled to produce appropriate numbers of each endocrine cell type in the islets. Dysregulation of this process can cause severe physiological problems – diabetes, associated with loss of β-cell generation or function, being the most obvious example. One transcription factor known to be involved in β-cell differentiation is Mnx1, mutation of which is associated with neonatal diabetes. By inactivating Mnx1 in either endocrine progenitors or β-cells, Fong Cheng Pan and co-workers have provided insights into the roles of this key regulator in mouse (p. 3637). They find that Mnx1 acts as a lineage specification factor: upon its depletion, β-cells fail to differentiate but δ-cell number is increased. Mnx1 is also needed for β-cell maintenance: mutants show extensive β- to δ-cell transdifferentiation. Intriguingly, the authors identify a small population of escaper β-cells in which Mnx1 has not been depleted, allowing expansion and differentiation; these cells then show enhanced proliferation and are able to restore (and in fact surpass) the normal β-cell number and function in the adult. Together, these data demonstrate that Mnx1 plays multiple important roles in endocrine pancreas development and function, and highlight potential mechanisms of compensation for β-cell loss.

Cells on the move: keeping polarised with Pak

In culture, cells typically lose their apicobasal polarity and their cell-cell interactions when they migrate. However, in vivo, collective cell migration is a common phenomenon, and apicobasal polarity is often at least partially maintained. How and why migrating cell clusters retain their apicobasal polarity is still poorly understood. The border cell cluster in the Drosophila oocyte provides an accessible model to address these questions, which Mohit Prasad and colleagues (p. 3692) have exploited to analyse the role of the Pak3 kinase. The authors find that Pak3 depletion in migrating border cells impairs migration – likely due to defects in the direction, length and stability of the protrusions extended by the border cells. These data suggest that forward-rear polarisation of the cluster is impaired. However, there are also severe defects in apicobasal polarity, and the authors define a signalling cascade involving Rac1, Pak3 and the JNK pathway, which regulates the apicobasal localisation of polarity proteins. As well as identifying another important player regulating collective cell migration, these data suggest an intriguing link between forward-rear and apicobasal polarity, which has yet to be investigated further.

PLUS:

Strigolactone biosynthesis and signaling in plant development

Strigolactones (SLs), first identified for their role in parasitic and symbiotic interactions in the rhizosphere, constitute the most recently discovered group of plant hormones.  In their poster article, Catherine Rameau and colleagues summarize current understanding of the SL pathway and discuss how this pathway regulates plant development. See the Development at a Glance article on p. 3615

Progress and renewal in gustation: new insights into taste bud development

The sense of taste, or gustation, is mediated by taste buds, which are housed in specialized taste papillae found in a stereotyped pattern on the surface of the tongue. Here, Linda Barlow reviews how the pattern of taste buds is established in embryos and discusses the cellular and molecular mechanisms governing taste cell turnover. See the Review article on p. 3620

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At the beginning of October 2015, the workshop “Transgenerational Epigenetic Inheritance” organized by Edith Heard, Ruth Lehmann and the Company of Biologists took place in Wiston House, West Sussex, United Kingdom. 20 invited speakers, all leading experts in the field, presented their thoughts about transgenerational epigenetic inheritance and their research towards describing and understanding these effects. In addition, 10 early career scientists (young PIs, postdocs and PhD students) selected from applications got the possibility to take part in the meeting and also to present their work in a talk. Luckily, I had the opportunity to join the workshop as one of only four participating PhD students.

The presentations covered various aspects of transgenerational epigenetic inheritance: Not only discussions of possible biological mechanisms, but also philosophical perspectives and conceptual thoughts about the topic. It was especially interesting to listen to such a broad variety of talks covering different aspects of transgenerational epigenetic inheritance in various model organisms.

For me, working on chromatin-based epigenetic memory in Drosophila melanogaster, it was very interesting to learn about the latest studies focusing on other potential mechanisms including small RNAs or even prions in various organisms ranging from yeast to Caenorhabditis elegans, plants and mammals.

I have really enjoyed the workshop. It was great to have had the opportunity to join such a small conference as a PhD student and also to get the chance to present the ideas and first results of my PhD work to leading experts in the field. The discussions about my project and beyond were very fruitful. I now have a different, much broader view on transgenerational epigenetic inheritance.

In my opinion, this workshop format provides a unique opportunity, especially for early career scientists, to interact with experienced experts in a certain field. I would definitively apply for a similar workshop again, if it covers a topic related to my work.

Check www.biologists.com/workshops/

Maybe there is also a workshop planned about your research interests. I think it will be worth applying.

(3 votes)

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Research:

– Can we make embryos in silico? Miquel posted about his recent paper in Bioinformatics, and the modeling framework he implemented in the new tool EmbryoMaker.

– What does YAP do? Muriel explained the role of this Hippo effector in the Xenopus retina.

– Histones, regeneration and crickets were all present in Hideyo Ohuchi’s post.

– How are positions between protrusions in bones maintained? Tomer Stern told us about bones and scaling on his post.

– Artificial intellegence in the lab. Mike Levin posted about using machine learning to generate models for planarian regeneration.

Techniques:

– Viewing less to see more. Hiroki Ueda wrote about tissue clearing and better visualisation.

– Techniques for the live-cell analysis of plant embryogenesis were summarised by Daisuke Kurihara.

Discussion:

– Making the most of graduate school. Tomer and Itamer told us about how they organised a Graduate Peer Group and what they learnt from it.

– Don Gibson posted about his push to have Barbara McClintock as the woman on the $10 bill.

Meeting reports: 

– “Ich hab mein Herz in Heidelber verloren”. Jerome Korzelius posted about the European Drosophila Research Conference.

– Ana Ribeiro attended the joint meeting of the Spanish, Portuguese and British Societies for Developmental Biology and posted about her experience.

Also on the Node:

– An interview with Mike Levine featured on the Node this month.

– A new intern joined the Node! Say hi to Helena.

– A unique opportunity for early career scientists interested in cardiovascular regeneration is available.

Happy reading!

(2 votes)

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Chris Puhl and Rebecca McIntosh

As a part of a team of students from the MRC Centre for Developmental Neurobiology, Kings College London we commissioned and edited an issue of The Biochemical Society’s magazine, The Biochemist. The issue is entitled ‘What makes us human’ and is a discussion of the evolutionary steps that lead to modern humans. The articles in the issue were written by a fantastic set of authors. The potential role of connectivity in the evolution of humans was one of many topics we were interested in but didn’t include in the end. Here we share some of our ideas on the topic.

Is a large or highly connected brain more important for human intelligence?

Whenever anyone talks about what makes humans special compared to other animals on earth, our intelligence and self-consciousness is often the first thing mentioned. The cognitive abilities held by humans are usually attributed to the size of our cortex, which is the most rostral, outermost and highly folded region part of the brain. The mammalian cortex is generated by a varied progenitor pool that has expanded and diversified through evolution^1,2.

A large number of studies have tried to elucidate the human specific genes and regulatory elements that are involved in generating and regulating mammalian neuronal progenitors in order to make a larger brain during development^3,4. Together these studies suggest that as brains evolve to be larger, the stem and progenitor cells that make the brain show increased heterogeneity in both cell biology and gene transcription^1-4. This results in blurred lines between stem/progenitor cells and differentiating/committed cells in the developing human brain^3,4. It is still unknown whether a larger brain containing more neurons alone can have a subsequent effect on intelligence or cognitive ability. In fact, even authors of these studies have suggested that the evolution of human-like cognitive abilities would have required more than a big brain full of a large number of neurons. Is it possible (even likely) that something else has to change in the brain inorder to evolve consciousness and levels of learning and memory that are considered human traits.

So if not the size of the brain, what other candidate do we have for explaining our unique cognitive abilities? One possibility is that the critical factor lies in how the neurons connect to each other. Greater amounts of cortical connectivity allow for a greater number of neural circuits to exist and thus potentially allow for a more plastic, adaptable brain. This line of thinking can be summarized by: ‘it’s not the size of your brain but what you do with it that matters’.

Increased connectivity

One human-specific genetic change that has been shown to boost synaptic connectivity is the duplication of SRGAP2. Around the transition from Australopithecus to Homo (approximately 3.4 million years ago) an initial duplication event generated SRGAP2B⁵. This initial duplication was followed by secondary duplication events which generated SRGAP2C ~2.4mya and SRGAP2D ~1mya. Interestingly, these gene duplication events (summarised in figure 1) occur around the time that the neocortex expands, use of stone tools begins, and more complex culture and behaviour emerges⁶. All of these duplication events were incomplete and were found to generate truncated proteins that assume a dominant negative function and antagonise the ancestral SRGAP2 protein⁵. Additional quantification of the paralogues found that of the three duplicated genes, only SRGAP2C is expressed in any significant amount in the human brain.

Charrier et al. 2012 examined the functional consequences of the SRGAP2 gene duplication and the inhibitory interaction with its paralog SRGAP2C⁷. Inhibition of SRGAP2 led to much faster radial migration of neurons in the cortex with less leading process branching. They also found that expression of SRGAP2C in mouse pyramidal neurons in vitro led to drastically altered morphology of dendritic spines. Dendritic spines receive most of the excitatory inputs for a neuron, and thus any changes to their morphology can have drastic effects on neuronal output. They are also thought to allow neurons to sample inputs over a greater area of nearby space and thus allow for additional connectivity without a corresponding increase in brain size⁸.

In mice, SRGAP2 promotes spine maturation and limits density. On the other hand, coexpression with SRGAP2C led to increased spine density, lengthened dendritic necks and ultimately led to marginally larger spine heads (figure 2). These ‘mutant’ spines also required more time to fully mature. These results are intriguing as human spines are known to be more dense in the cortex, have longer necks and larger heads, and also to develop more slowly (termed neoteny)^{9 -11}. This experiment then provides an anatomical readout of what may have been occurred in the human brain after the gene duplication event⁵.

While these studies have shown that a human-specific gene can alter neuronal anatomy, the physicological and functional outcome of the expression of this gene is still not clear. Do the cells expressing both SRGAP2 and SRGAP2C have different electrical properties from those that do not? Do they integrate their inputs differently? Are the rules governing plasticity different or altered for cells with different dendritic spine sizes?

These experiments suggest a plethora of future directions for research. There are a number of human-specific duplicate genes that are incomplete or missing segments^12,13. If these genes are important in neurodevelopment or neuronal structure and behavior, then they could assume roles analogous to that played by SRGAP2C to its parent gene. And of course, linking these genetic changes to anatomical and ultimately behavioral changes in neurons would be the ultimate goal in explaining what it is that makes us human.

References

1. http://www.biochemist.org/bio/03705/0016/037050016.pdf.
2. Gotz M, Huttner WB (2005) The cell biology of neurogenesis. Nat Rev Mol Cell Biol. 2005 Oct;6(10):777-88.
3. Florio M, Albert M, Taverna E, Namba T, Brandl H, Lewitus E, Haffner C, Sykes A, Wong FK, Peters J, Guhr E, Klemroth S, Prufer K, Kelso J, Naumann R, Nusslein I, Dahl A, Lachmann R, Paabo S, Huttner WB (2015) Human-specific gene ARHGAP11B promotes basal progenitor amplification and neocortex expansion. Science 347(6229):1465-70.
4. Johnson MB, Wang PP, Atabay KD, Murphy EA, Doan RN, Hecht JL, Walsh CA. (2015) Single-cell analysis reveals transcriptional heterogeneity of neural progenitors in human cortex. Nat Neurosci. 18(5):637-46.
5. Dennis MY, Nuttle X, Sudmant PH, Antonacci F, Graves TA, Nefedov M, Rosenfield JA, Sajjadian S, Malig M, Kotkiewicz H, Curry CJ, Shafer S, Shaffer LG, de Jong PJ, Wilson RK, Eichler EE (2012) Evolution of Human-Specific Neural SRGAP2 Genes by Incomplete Segmental Duplication. Cell, 149:912-922.
6. Jobling M, Hurles M, Tyler-Smith C (2004) Human Evolutionary Genomics. New York: Garland Science.
7. Charrier C, Joshi K, Coutinho-Budd J, Kim J-E, Lambert N, de Marchena J, Jin W-L, Vanderhaeghen P, Ghosh A, Sassa T, Polleux F (2012) Inhibition of SRGAP2 Function by Its Human-Specific Paralogs Induces Neoteny during Spine Maturation. Cell 149: 923-935.
8. Yuste, R (2011) Dendritic Spines and Distributed Circuits. Neuron, 71:772-781.
9. Elston GN, Benavides-Piccione R, DeFelipe J (2001) The pyramidal cell in cognition: a comparative study in human and monkey. Neurosci. 21: RC163.
10. Benavides-Piccione R, Ballesteros-Yanez I, DeFelipe J, Yuste R (2002) Cortical area and species differences in dendritic spine morphology. Neurocytology 31:337-346.
11. Petanjek Z, Judas M, Simic G, Rasin MR, Uylings HB, Rakic P, Kostovic I (2011) Extraordinary neoteny of synaptic spines in the human prefrontal cortex. Natl. Acad. Sci. USA, 108:13281-132886.
12. Sudmant PH, Kitzman JO, Antonacci F, Alkan C, Malig M, Tsalenko A, Sampas N, Bruhn L, Shendure J, Eichler EE ; 1000 Genoms Project (2010) Diversity of human copy number variation and multicopy genes. Science, 330:641-646.
13. Fortna A, Kim Y, MacLaren E, Marshall K, Hahn G, Meltesen L, Brenton M, Hink R, Burgers S, Hernandez-Boussard T, Karimpour-Fard A, Glueck D, McGavran L, Berry R, Pollack J, Sikela JM (2004) Lineage-specific gene duplication and loss in human and great ape evolution. PLoS Biol. 2(7):E207.

(1 votes)

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