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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Recently, Tomer Stern and Itamar Harel posted on the Node about Graduate Peer Group, a discussion group where graduate students could interact with each other and address the challenges that arise specifically during graduate school. Many of these challenges go beyond research at the bench: how to communicate your research, how to manage relationships in the lab, how to establish collaborations, how to write manuscripts, etc.

Indeed, as a scientist advances in their career, they must become more than just researchers: they must also be writers, reviewers, mentors, managers and communicators. So, this month’s question is:

Which “away from the bench” skills are required to be a successful academic? How and when should those skills be developed?

Share your thoughts by leaving a comment below! You can comment anonymously if you prefer. We are also collating answers on social media via this Storify. And if you have any ideas for future questions please drop us an email!

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Pattern formation and regulation emerges from cellular activity determined by specific biophysical and genetic rules. A major challenge for developmental biology, biomedicine, and synthetic bioengineering is this highly indirect (Lobo et al., 2014b) relationship between the rules that govern processes at the lower scales, and the anatomical outcomes observed at the macroscopic scale. It is very hard to predict what a complex, iterative, distributed system such as an embryo or a regenerating animal will do, from knowledge of the low-level rules. It is even harder to infer what manipulation can be applied at the molecular level, to achieve a specific anatomical change in biomedical or synthetic morphology applications. This is known as an “inverse problem” in computer science; for example, it’s very easy to iterate a mathematical function like Z<=Z^2+c and create a beautiful fractal (http://mathworld.wolfram.com/MandelbrotSet.html ), but it’s an intractable task to take an arbitrary pattern and figure out what formula would produce it.

In this post, I describe our recent efforts to address the gulf between the molecular details that come out of bench experiments, and the complex patterns or regulatory behavior that we would like to understand and control. We view this as the beginning of a “bioinformatics of shape” – the creation of computational tools addressing shape, not only sequence or expression, and that assist human scientists in discovering models that explain pattern and complex, stochastic developmental phenotypes. An important component of this “robot scientist” (Sparkes et al., 2010) effort is enabling the inference of models that are generative (algorithmic): they specify every step, quantitatively, without ambiguity or magic, and show exactly what dynamics are sufficient to produce the pattern in question. The field is moving towards these kinds of models (Wittmann et al., 2009; Raspopovic et al., 2014; Uzkudun et al., 2015; Werner et al., 2015), and away from simple “arrow diagram” models, that capture valuable loss-of-function and interaction data, but only reveal the pieces necessary for the process to occur. That is generally insufficient to show why or how the complex patterning proceeds to a specific shape, or enable full control of its outcome toward a different goal state; thus, it is crucial to develop tools for generating and testing fully-specified generative models.

We first tackled the problem of planarian regeneration (Handberg-Thorsager et al., 2008; Lobo et al., 2012). A fragment of these complex bilaterian creatures regenerates all the missing components, no more and no less, in the correct orientation and at the correct locations (Reddien and Sanchez Alvarado, 2004; Gentile et al., 2011). People have been wondering about how this process works for at least 120 years, but despite remarkable molecular advances in stem cell regulation (Reddien et al., 2005; Wagner et al., 2011), there have been no quantitative models that algorithmically explain more than a few different patterning experiments in this very rich body of functional data. We began by creating a formal language (Lobo et al., 2013b) to describe possible experimental manipulations of worms (cuts, grafts, RNAi knockdown, etc.), and a graph representation scheme by which any shape of worm could be encoded (normal, 2-headed, etc.). We then encoded a large number of papers from the planarian literature into a database, which contains the sum total of current knowledge about this model species – a sort of expert system on planarian regeneration, which a human or algorithm can consult when needing to know what outcome results from a given experiment (Lobo et al., 2013a). Next, we created a virtual worm simulator – an in silico platform on which any genetic model of planaria could be run, and manipulated in virtual “experiments”, to see if the predicted outcomes matched the existing results from the database. Models could now be tested, but where to find a model detailed enough to be run on such a simulator? This problem is already so complex that human scientists have a very hard time to simply think of a model whose emergent behavior correctly predicts all the available results. With each new paper published, it becomes harder, not easier, to come up with a model that matches all the data. We thus implemented the final piece: a machine-learning module, that uses evolutionary computation to try to infer a model of gene regulation that behaves just like the real thing, under the published experimental perturbations. The system ran for several days on a supercomputer cluster, and indeed discovered a model that not only explained the existing data but made correct predictions for experiments it had never seen (Lobo and Levin, 2015).

This is the first model of regeneration discovered by an artificial (non-human) intelligence; we and others are testing the model’s predictions and its ability to suggest manipulations that result in never-before-seen phenotypes (as well as extending the platform to limb regeneration in multiple  species (Lobo et al., 2014a)). Remarkably, the model it found was not an incomprehensible hairball (akin to diagrams of “metabolism”) but a small, easy-to-understand network with only two unknowns (which have since been identified from their connections to neighbors in protein interactome databases). The power of this system is that any future papers’ data can be continuously be added to the database, and the inference process re-run, to discover ever better models.  Regardless of the fate of this particular model, we think this platform is a proof-of-concept, highly generalizable system for using artificial intelligence to assist scientists in the most creative aspect of our work: trying to come up with a testable model of what could be going on during complex pattern regulation.

References

Gentile, L., Cebria, F. and Bartscherer, K. (2011) ‘The planarian flatworm: an in vivo model for stem cell biology and nervous system regeneration’, Dis Model Mech 4(1): 12-9,

http://dmm.biologists.org/content/4/1/12.full.pdf

Handberg-Thorsager, M., Fernandez, E. and Salo, E. (2008) ‘Stem cells and regeneration in planarians’, Front Biosci 13: 6374-94, http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=18508666

Lobo, D., Beane, W. S. and Levin, M. (2012) ‘Modeling planarian regeneration: a primer for reverse-engineering the worm’, PLoS Comput Biol 8(4): e1002481, http://www.ncbi.nlm.nih.gov/pubmed/22570595

Lobo, D., Feldman, E. B., Shah, M., Malone, T. J. and Levin, M. (2014a) ‘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 11(6): e1004295, http://www.ncbi.nlm.nih.gov/pubmed/26042810

Lobo, D., Malone, T. J. and Levin, M. (2013a) ‘Planform: an application and database of graph-encoded planarian regenerative experiments’, Bioinformatics http://www.ncbi.nlm.nih.gov/pubmed/23426257

Lobo, D., Malone, T. J. and Levin, M. (2013b) ‘Towards a bioinformatics of patterning: a computational approach to understanding regulative morphogenesis’, Biology Open 2(2): 156-69, http://www.ncbi.nlm.nih.gov/pubmed/2342966

Lobo, D., Solano, M., Bubenik, G. A. and Levin, M. (2014b) ‘A linear-encoding model explains the variability of the target morphology in regeneration’, Journal of the Royal Society, Interface / the Royal Society 11(92): 20130918, http://www.ncbi.nlm.nih.gov/pubmed/24402915

Raspopovic, J., Marcon, L., Russo, L. and Sharpe, J. (2014) ‘Modeling digits. Digit patterning is controlled by a Bmp-Sox9-Wnt Turing network modulated by morphogen gradients’, Science 345(6196): 566-70, http://www.ncbi.nlm.nih.gov/pubmed/25082703

http://www.sciencemag.org/content/345/6196/566.full.pdf

Reddien, P. W., Oviedo, N. J., Jennings, J. R., Jenkin, J. C. and Sanchez Alvarado, A. (2005) ‘SMEDWI-2 is a PIWI-like protein that regulates planarian stem cells’, Science 310(5752): 1327-30,

Click to access 1327.pdf

Reddien, P. W. and Sanchez Alvarado, A. (2004) ‘Fundamentals of planarian regeneration’, Annu Rev Cell Dev Biol 20: 725-57, http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=15473858

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

Uzkudun, M., Marcon, L. and Sharpe, J. (2015) ‘Data-driven modelling of a gene regulatory network for cell fate decisions in the growing limb bud’, Molecular Systems Biology 11(7): 815, http://www.ncbi.nlm.nih.gov/pubmed/26174932

Wagner, D. E., Wang, I. E. and Reddien, P. W. (2011) ‘Clonogenic neoblasts are pluripotent adult stem cells that underlie planarian regeneration’, Science 332(6031): 811-6, http://www.sciencemag.org/content/332/6031/811.full.pdf

Werner, S., St√ºckemann, T., Beir√°n Amigo, M., Rink, J. C., J√ºlicher, F. and Friedrich, B. M. (2015) ‘Scaling and Regeneration of Self-Organized Patterns’, Physical Review Letters 114(13): 138101, http://link.aps.org/doi/10.1103/PhysRevLett.114.138101

Wittmann, D. M., Blochl, F., Trumbach, D., Wurst, W., Prakash, N. and Theis, F. J. (2009) ‘Spatial analysis of expression patterns predicts genetic interactions at the mid-hindbrain boundary’, PLoS Comput Biol 5(11): e1000569, http://www.ncbi.nlm.nih.gov/pubmed/19936059

(2 votes)

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Two PhD positions in the area of quantitative stem cell biology are available in the laboratory of Christian Schroeter, starting in spring 2016 at the Max Planck Institute for Molecular Physiology in Dortmund, Germany.

The aim of our research is to understand how pluripotent stem cells receive, process and integrate signals to take lineage decisions. Now that most of the important genes and proteins involved in differentiation decisions have been identified, we want to investigate the functions of the interaction networks formed by these molecules. In particular, we will ask questions such as: How do cells measure quantities of extracellular signals, and how do they encode this information in the dynamic activity of signal transduction networks? How are different signals integrated? How are fate decisions coordinated in cell populations to form tissues?

Successful candidates will address these questions using mainly mouse embryonic stem cells as a model system, and apply a combination of genetic engineering, molecular biology, immunohistochemistry and live cell microscopy to investigate the dynamics of decision-making processes in single cells. A strong focus of the projects will be on cutting edge live-cell imaging approaches. Together with collaborators we will use the resulting quantitative, dynamic data to develop predictive mathematical models for information processing and decision-making in pluripotent cells.

For further information about the lab and the Max Planck Institute for Molecular Physiology, please visit the lab’s website: http://www.mpi-dortmund.mpg.de/3257493/Dr_C_Schroeter

The full job ad is posted here: http://www.mpi-dortmund.mpg.de/3264913/job_full_offer_9714072?c=1879013

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In the frame of the 2016 “Juan de la Cierva” Call, a postdoctoral research post is available in Juan R. Martinez-Morales laboratory. (www.cabd.es).

CABD (UPO/CSIC). National Research Council. Seville. Spain.

The research project focuses on the morphogenesis of the optic cup as an epithelial model to identify key effector genes that determine cell and tissue architecture in zebrafish. By RNAseq analysis, we have identified some of these effector genes operating on basic cell properties such as: cell-adhesion, cell-contractility, and cytoskeletal organization. Investigating their role on epithelial cell geometry is now our objective. To this end we will use a combination of CRISPr/Cas9, live-imaging in zebrafish and gain and loss of function experiments in MDCK cysts.

• Gago-Rodrigues I, Fernández-Miñán A, Letelier J, Naranjo S, Tena JJ, Gómez-Skarmeta JL, Martinez-Morales JR (2015) Analysis of opo cis-regulatory landscape uncovers Vsx2 requirement in early eye morphogenesis. Nat Comm. 6:7054
• Tena JJ, González-Aguilera C, Fernández-Miñán A, Vázquez-Marín J, Parra-Acero H, Cross JW, Rigby PW, Carvajal JJ, Wittbrodt J, Gómez-Skarmeta JL, Martínez-Morales JR (2014) Comparative epigenomics in distantly related teleost species identifies conserved cis-regulatory nodes active during the vertebrate phylotypic period. Genome Research. 24(7): 1075-85
• Bogdanovic O, Delfino-Machín M, Nicolás-Pérez M, Gavilán MP, Gago-Rodrigues I, Fernández-Miñán A, Lillo C, Ríos RM, Wittbrodt J, Martínez-Morales JR (2012) Numb/Numbl-Opo antagonism controls retinal epithelium morphogenesis by regulating integrin endocytosis. Developmental Cell. 23 (4)

Candidate Requirements: We are seeking for highly motivated candidates with excellent publication record and a background either in Cell or Developmental Biology. Previous experience with zebrafish, MDCK cultures, or CRISPr technologies is not an essential requirement, but it will be considered positively.

Interested candidates should send a letter of interest, a CV and contact information for 2 referees before December 20, 2015 to: Juan R. Martinez-Morales: jrmarmor@upo.es

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