This Spotlight article was written by Dianne Gerrelli, Steven Lisgo, Andrew J. Copp and Susan Lindsay, and was first published in Development.

Congenital anomalies are a significant burden on human health. Understanding the developmental origins of such anomalies is key to developing potential therapies. The Human Developmental Biology Resource (HDBR), based in London and Newcastle, UK, was established to provide embryonic and fetal material for a variety of human studies ranging from single gene expression analysis to large-scale genomic/transcriptomic studies. Increasingly, HDBR material is enabling the derivation of stem cell lines and contributing towards developments in tissue engineering. Use of the HDBR and other fetal tissue resources discussed here will contribute to the long-term aims of understanding the causation and pathogenesis of congenital anomalies, and developing new methods for their treatment and prevention.

Introduction

An important goal of developmental biology is to understand human embryonic/fetal development and the causes of congenital anomalies. A better understanding of the gene pathways that lead to developmental anomalies will aid new medical approaches for disease treatment and prevention. The causes of congenital anomalies include a variety of genetic and environmental factors, with the majority probably involving multifactorial aetiology. In Europe the recorded prevalence of major congenital anomalies is 23.9 per 1000 pregnancies, of which 80% were live births and 20% resulted in termination, fetal death or stillbirth (Dolk et al., 2010). Children who survive with congenital anomalies frequently experience long-term disability. For example, patients with congenital heart defects (the commonest group of anomalies) may develop severe disability in the first few days after birth (e.g. transposition of the great vessels), often requiring early surgery. In economic terms, the lifetime cost of caring for someone with a severe birth defect, like spina bifida, is estimated at over $0.5 million (Yi et al., 2011). This represents a challenge not only for individuals and families, but also for healthcare systems. In recent decades it has become possible to prevent some congenital anomalies. Two notable examples are vaccination of women against rubella to reduce the number of newborn babies with congenital rubella syndrome (Tookey and Peckham, 1999), and supplementation with folic acid in early pregnancy to decrease the prevalence of neural tube defects (Eichholzer et al., 2006).

Animal models are widely used to test hypotheses about the development of the embryo and fetus. Over the last 10 years there have been huge advances in the understanding of model organisms, in terms of whole-genome sequencing, identifying gene regulatory networks and determining developmental mechanisms. A striking finding is that the majority of protein-coding genes are shared between mouse and human (Yue et al., 2014). Therefore, the differences between the species are unlikely to be due to gene diversity but mainly to modifications in regulatory programmes controlling where and when genes are expressed. The spatial and temporal control of gene expression is therefore extremely important and might help to explain what makes us human.

As well as similarities, there are many established differences between the development of humans and model organisms such as the mouse. Most notably, during evolution the brain has changed in size and shape. Differences are particularly evident in the development of the human cerebral cortex (Bae et al., 2015), with huge increases in the number of cells and in the complexity of cell types. The cortex of the human brain also undergoes a process of folding known as gyrification, which increases the number of cortical neurons. This gyrification is thought to correlate with increased cognitive abilities (Gautam et al., 2015). The mouse brain does not undergo gyrification.

As another example, the eyes of humans are also more complex: they contain three types of cone cells as opposed to only two in mice; while the macula – a highly pigmented area at the back of the human retina – is absent in mice. A number of genes whose mutation is associated with human congenital syndromes, such as KAL1 (ANOS1) (Cadman et al., 2007) and SHOX (Blaschke and Rappold, 2006), are not found in the mouse genome. Thus, although model organisms have proved hugely valuable in understanding developmental processes, there is also a need to study human tissue directly.

Here, we present an overview of the resources available to the research community for analysing human development, with a particular focus on the Human Developmental Biology Resource (HDBR). Resources such as tissue banks, bioinformatics portals and archive collections provide researchers with crucial information and material for the analysis of human development and associated congenital abnormalities.

Research tissue banks

Several research tissue banks have been created in the UK and elsewhere to enable researchers to gain access to human embryonic and fetal samples. These banks collect tissue in a systematic fashion and conform to the highest ethical standards and research governance.

The Human Developmental Biology Resource (HDBR)

The HDBR (www.hdbr.org; with whom the authors are associated) was established in 1999 and is funded by the Medical Research Council and Wellcome Trust. It has National Research Ethics Service approval and is licensed by the UK Human Tissue Authority (https://www.hta.gov.uk/). The collection of material from elective terminations of pregnancy currently comprises over 4000 specimens aged between 3 and 20 post-conception weeks (pcw). The resource continues to collect material, with 400 new specimens added each year. All specimens are karyotyped, with 4% having chromosomal abnormalities (most commonly trisomy 21 and monosomy X) and 9% displaying some form of phenotypic abnormality.

Various types of sample are available from the HDBR (Fig. 1). The majority of tissue provided by the resource is from chromosomally normal samples but material can also be provided from specimens with chromosomal abnormalities. Fresh tissue from specific organs and developmental ages can be used in a range of scientific procedures, such as fluorescence-activated cell sorting of live cells to purify specific human fetal cell populations in order to derive primary cell lines or stem cells. Frozen tissue can be used for the production of mRNA, genomic DNA or protein. These samples are being used in large-scale transcriptome analyses to compare human and animal models and across specific tissues, sexes and between normal and karyotypically abnormal samples.

Fig. 1 Examples of resources available from the HDBR. (A) Images of embryos at (from left to right) CS12 [∼26 days post conception (dpc)], CS16 (∼37 dpc) and CS19 (∼47 dpc). (B) A CS17 (∼41 dpc) embryo with trisomy 21. (C) CS12-CS21 series of 3D models, generated using optical projection tomography (OPT) from embryos in the HDBR collection, displayed at their relative sizes. Movies and images of the models can be viewed or the full models requested via the HuDSeN website (www.hudsen.org). (D) The HDBR provides access to curated gene expression data. The upper image shows a section through a CS17 embryo stained with anti-GAP43 antibody (brown); the lower image is of the corresponding section in the CS17 OPT model onto which the GAP43 expression data have been mapped (red, strong expression; yellow, moderate expression). Expression data were mapped from experimental sections to digital sections using MAPaint software (http://www.emouseatlas.org/emap/home.html). (E) 3D expression domain of GAP43 expression in the head and part of the body built up by mapping data from sections as shown in D. Experimental and mapped data are uploaded to a spatial database (www.hudsen.org). (F) Word cloud representation of the expression data available in the HuDSeN human gene expression spatial database (www.hudsen.org). The word cloud represents the number of entries for each gene and there are currently data from 128 genes. Scale bars: 1 mm.
 

The HDBR also provides a gene expression service using RNA in situ hybridisation or protein immunohistochemistry. Sectioned embryonic or fetal tissue is used to identify the temporal and spatial expression of specific genes or proteins. Gene expression data from this service, as well as data generated by external projects, are digitally imaged and made accessible via an open access database (www.hudsen.org). Some stained sections are also available at high resolution (http://nbb-slidepath.ncl.ac.uk/dih; username and password available on request).

Material can be provided to researchers in the UK without the need for project ethics review, as well as to international groups with relevant ethical review body approvals. Over 10,000 slides and tissue samples have been distributed to registered users in the last 5 years, and ∼100 projects are registered per year. The majority of projects are based in the UK, but a growing number of users are in the USA (17%), mainland Europe (11%) and other locations worldwide. Distribution of human embryonic and fetal tissue is prioritised to projects that investigate congenital disorders. Of particular interest are studies that aim to understand the function of genes important for early development, genes linked to human-specific functions (e.g. cognitive function and language) and genes associated with significant anatomical or functional differences between mice and humans.

A wide variety of studies have been carried out using HDBR materials (Fig. 2). These range from investigation of single genes underlying genetic disorders (Tischfield et al., 2010;Thomas et al., 2014) to high-throughput studies of transcriptomes (Kang et al., 2011) and regulatory sequences (Necsulea et al., 2014). Advances in high-throughput sequencing technologies have opened the door to large-scale cross-species comparisons that are highlighting differences in transcript sequence, alternative splicing, expression level and regulation between humans and model organisms (Cotney et al., 2013; Bae et al., 2014). Some studies, such as the investigation of tail bud development in chick and human (Olivera-Martinez et al., 2012), dissect key processes of early development. Organ-specific tissues have been used for the derivation of primary cell lines and stem cells (U et al., 2014).

Fig 2. HDBR material has been used in many different types of studies.Examples are shown of the types of study carried out using HDBR material. (A,B) Examples from the gene expression service. HDBR staff perform gene expression analysis on sectioned tissue by in situ hybridisation (A) or immunohistochemistry (B) on behalf of researchers. (C-E) The types of studies that researchers carry out in their own laboratories with material provided by HDBR: to produce cell lines or perform functional analysis (C); gene expression studies in paraffin fixed sections (D); and transcriptomics studies in cells or tissues (E).

Other tissue banks

A number of other groups, in the UK and USA, have set up collections of human fetal material. These are normally organised around defined scientific projects and the samples are not usually available to the wider scientific community. However, there are exceptions where banks have been established to provide material for use in research. For example, the South Wales Initiative for Fetal Tissue (http://www.biobankswales.org.uk/swift-research-tissue-bank/) provides clinical grade fetal tissue (5 and 12 pcw) primarily for human therapeutics, and the University of Maryland Brain and Tissue Bank in the USA (http://medschool.umaryland.edu/btbank/catalog.asp) can provide access to both adult and fetal tissue.

Bioinformatics portals

A number of sites provide valuable information on human development for researchers. For example, the BrainSpan project (www.brainspan.org) has generated transcriptome data and gene expression data from multiple regions of the embryonic, fetal and adult brain. The UNSW Embryology portal is an education and research website that has links to many collections of human embryonic and fetal specimens (https://embryology.med.unsw.edu.au/embryology/index.php/).

In the UK a consortium of UKCRC funders has established The National Tissue Directory and Coordination Centre (www.biobankinguk.org). This directory will enable researchers to find human biobanks within the UK and gain access to their collections through one system. These and other bioinformatics databases are essential resources for researchers, particularly those whose access to primary tissue is limited.

Archive resources

The Carnegie collection (www.ehd.org/virtual-human-embryo/)

Seven thousand human embryos are stored in the Carnegie collection at the National Museum of Health and Medicine, Washington, D.C. This material was used to develop the comprehensive Carnegie staging system based on internal as well as external features. Carnegie staging (CS1-23) is now employed universally in human embryo research. Individual embryos throughout the embryonic period have been sectioned and, in an attempt to make the collection more accessible for research and teaching, digital images from a subset of these have been acquired. The images are labelled with standard anatomy terms to help with interpretation, or used to generate 3D models and 252 movies.

The Kyoto collection (http://bird.cac.med.kyoto-u.ac.jp/index_e.html)

This is the largest human embryo collection in the world, with over 44,000 specimens between CS7 and CS23. Maternal epidemiological data and detailed clinical information on the pregnancies were collected for each specimen. Five hundred normal and 500 abnormal embryos have been serially sectioned, and a further 1300 staged human embryos have been digitally imaged by magnetic resonance (MR) microscopy and 3D reconstructions produced.

Conclusions

The landscape for developmental biology and clinical research has changed within the last few years, with more emphasis being placed on large-scale sequencing projects such as the Genotype-Tissue Expression Project (GTEx Consortium, 2013), Geuvadis (Lappalainen et al., 2013) and the UK 100,000 Genomes Project (Siva, 2015). These projects and numerous others aim to map variations in gene expression in thousands of individual patients and correlate this with disease phenotypes and bioinformatics information on sites such as the Encyclopedia of DNA Elements (ENCODE; https://www.encodeproject.org/;Kellis et al., 2014). Other studies are using novel algorithms to interrogate the sequencing data to investigate gene networks (Liu et al., 2014). These projects are now identifying candidate genes that could play a role in a range of human diseases and syndromes.

The next step in this gene discovery pipeline will be to test candidate genes in model organisms and human tissue. This analysis needs to be performed at the cellular level to determine whether the genes are expressed in tissues and cell types relevant to the disease under study. The HDBR is ideally placed to assist researchers wishing to investigate genes thought to be responsible for congenital abnormalities. In addition, some groups are using material provided by the HDBR to study epigenetic regulation and in functional studies. Other projects include the derivation of stem cells and scaffolds for tissue engineering projects. It is likely in the coming years that the HDBR will not only support projects wishing to understand key developmental processes but will also increasingly provide resources to underpin translational research.

References

Bae, B.-I., Tietjen, I., Atabay, K. D., Evrony, G. D., Johnson, M. B., Asare, E., Wang, P. P., Murayama, A. Y., Im, K., Lisgo, S. N. et al. (2014). Evolutionarily dynamic alternative splicing of GPR56 regulates regional cerebral cortical patterning. Science 343, 764-768. doi:10.1126/science.1244392

Bae, B.-I., Jayaraman, D. and Walsh, C. A. (2015). Genetic changes shaping the human brain. Dev. Cell 32, 423-434. doi:10.1016/j.devcel.2015.01.035

Blaschke, R. J. and Rappold, G. (2006). The pseudoautosomal regions, SHOX and disease. Curr. Opin. Genet. Dev. 16, 233-239. doi:10.1016/j.gde.2006.04.004

Cadman, S. M., Kim, S.-H., Hu, Y., González-Martínez, D. and Bouloux, P.-M. (2007). Molecular pathogenesis of Kallmann’s syndrome. Horm. Res. 67, 231-242. doi:10.1159/000098156

Cotney, J., Leng, J., Yin, J., Reilly, S. K., DeMare, L. E., Emera, D., Ayoub, A. E., Rakic, P. and Noonan, J. P. (2013). The evolution of lineage-specific regulatory activities in the human embryonic limb. Cell 154, 185-196. doi:10.1016/j.cell.2013.05.056

Dolk, H., Loane, M. and Garne, E. (2010). The prevalence of congenital anomalies in Europe. Adv. Exp. Med. Biol. 686, 349-364. doi:10.1007/978-90-481-9485-8_20

Eichholzer, M., Tönz, O. and Zimmermann, R. (2006). Folic acid: a public-health challenge. Lancet 367, 1352-1361.doi:10.1016/S0140-6736(06)68582-6

Gautam, P., Anstey, K. J., Wen, W., Sachdev, P. S. and Cherbuin, N. (2015). Cortical gyrification and its relationships with cortical volume, cortical thickness, and cognitive performance in healthy mid-life adults. Behav. Brain Res. 287, 331-339. doi:10.1016/j.bbr.2015.03.018

GTEx Consortium (2013). The Genotype-Tissue Expression (GTEx) project. Nat. Genet. 45, 580-585. doi:10.1038/ng.2653

Kang, H. J., Kawasawa, Y. I., Cheng, F., Zhu, Y., Xu, X., Li, M., Sousa, A. M. M., Pletikos, M., Meyer, K. A., Sedmak, G. et al. (2011). Spatio-temporal transcriptome of the human brain. Nature 478, 483-489. doi:10.1038/nature10523

Kellis, M., Wold, B., Snyder, M. P., Bernstein, B. E., Kundaje, A., Marinov, G. K., Ward, L. D., Birney, E., Crawford, G. E., Dekker, J. et al. (2014). Defining functional DNA elements in the human genome. Proc. Natl. Acad. Sci. USA 111, 6131-6138. doi:10.1073/pnas.1318948111

Lappalainen, T., Sammeth, M., Friedländer, M. R., t Hoen, P. A. C., Monlong, J., Rivas, M. A., Gonzàlez-Porta, M., Kurbatova, N., Griebel, T., Ferreira, P. G. et al. (2013). Transcriptome and genome sequencing uncovers functional variation in humans. Nature 501, 506-511. doi:10.1038/nature12531

Liu, L., Lei, J., Sanders, S. J., Willsey, A. J., Kou, Y., Cicek, A. E., Klei, L., Lu, C., He, X., Li, M. et al. (2014). DAWN: a framework to identify autism genes and subnetworks using gene expression and genetics. Mol. Autism 5, 22. doi:10.1186/2040-2392-5-22

Necsulea, A., Soumillon, M., Warnefors, M., Liechti, A., Daish, T., Zeller, U., Baker, J. C., Grützner, F. and Kaessmann, H. (2014). The evolution of lncRNA repertoires and expression patterns in tetrapods. Nature 505, 635-640. doi:10.1038/nature12943

Olivera-Martinez, I., Harada, H., Halley, P. A. and Storey, K. G. (2012). Loss of FGF-dependent mesoderm identity and rise of endogenous retinoid signalling determine cessation of body axis elongation. PLoS Biol. 10, e1001415.doi:10.1371/journal.pbio.1001415

Siva, N. (2015). UK gears up to decode 100,000 genomes from NHS patients. Lancet 385, 103-104. doi:10.1016/S0140-6736(14)62453-3

Thomas, M. G., Crosier, M., Lindsay, S., Kumar, A., Araki, M., Leroy, B. P., McLean, R. J., Sheth, V., Maconachie, G., Thomas, S. et al. (2014). Abnormal retinal development associated with FRMD7 mutations. Hum. Mol. Genet. 23, 4086-4093. doi:10.1093/hmg/ddu122

Tischfield, M. A., Baris, H. N., Wu, C., Rudolph, G., Van Maldergem, L., He, W., Chan, W.-M., Andrews, C., Demer, J. L., Robertson, R. L. et al. (2010). Human TUBB3 mutations perturb microtubule dynamics, kinesin interactions, and axon guidance. Cell 140, 74-87. doi:10.1016/j.cell.2009.12.011

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D. Bullara* and Y. De Decker
*domenico.bullara@mail.com

When Catarina Vicente (Community Manager of “The Node”) proposed us to write a post about our recent paper on pattern formation in zebrafish [Bullara2015] we were very glad for the opportunity she was giving us to tell the background story about our work in this blog. We are not biologists (we are two theoretical chemists working in the field of nonlinear chemistry and self-organization) and we took Dr. Vicente’s invitation as an opportunity to present our outsiders’ point of view on a quite debated question related to morphogenesis. We therefore very much hope to gain inspiring feedbacks from your comments.

Following this spirit, we initially wrote our post including a number of theoretical details and comments, in the hope to bridge the gap between the typical jargon and assumed basic knowledge of theoretical nonlinear chemistry and experimental developmental biology. We however realized that the final manuscript was too long to fit the scopes of this blog. So – following Dr. Vicente’s advice – we decided to leave the full version in a separate file (which can be downloaded here) for the interested reader, and summarize what we think may be the more interesting paragraphs in the following post.

— Alan Turing and the reaction-diffusion mechanism

Morphogenesis and nonlinear chemistry share a special bond since the British mathematician Alan Turing published his seminal paper “On the chemical basis of morphogenesis” [Turing1952], which set the basis for a theoretical development of both disciplines. The basic question that Turing wanted to answer was: How can a system with such a high degree of symmetry as an egg cell (essentially a sphere) develop organisms with a much lower degree of symmetry (i. e. living beings)?

The pivotal idea of Turing is that “a system of chemical substances, called morphogens, reacting together and diffusing through a tissue, is adequate to account for the main phenomena of morphogenesis. Such a system, although it may originally be quite homogeneous, may later develop a pattern or structure due to an instability of the homogeneous equilibrium [NOTE1], which is triggered off by random disturbances” [Turing1952]. This mechanism has since then being referred to as the “reaction-diffusion (RD) mechanism”, and the corresponding stationary patterns as “Turing patterns”.

From a molecular point of view, a chemical reaction is essentially an exchange of atoms between molecules, or between molecular segments of a single molecule. But theoretical approaches to reactive systems are often based on a much coarser level of description: one usually divides the whole space into a collection of infinitesimal volumes (or points), within which chemical reactions are considered as local processes. In this framework, diffusion is a physical mechanism which allows molecules to migrate from one point in space to another in a Brownian motion. Both concepts can straightforwardly be extended to non-chemical systems, as long as one can define local events taking place between the units composing a system whose outcome is to change the number of units (reactions) and Brownian motions of these units (diffusion). From this point of view a wolf killing a rabbit or a cell undergoing mitosis may be both considered as “reactions”, although not chemical ones.

Precise mathematical requirements involving the parameters of the system must be fulfilled in order for a RD system to undergo the kind of dynamical instability described by Turing. When this happens, one says that a “Turing instability” or “Turing bifurcation” occurs, and stationary patterns with an intrinsic wavelength can be generated. The original model proposed by Alan Turing as well as several other pattern-generating models undergo precisely this type of instability, which led in practice to an identification of the terms “Turing instability”, “Turing patterns” and “reaction-diffusion mechanism”. It is important however to understand that these terms express separate concepts, and therefore a Turing instability (as well as a Turing pattern) is not limited to reaction-diffusion mechanisms.

— Turing patterns without diffusion? The riddle of the zebrafish stripes

Our interest in zebrafish patterning began in 2012, when we discovered the experimental work of Shigeru Kondo and coworkers [Yamaguchi2007, Nakamasu2009, Inaba2012, Hamada2014]. In their experiments the zebrafish skin patterns exhibit a dynamics which closely resemble what can be observed in typical RD equations schemes forming Turing patterns. Moreover, the experiments clearly shows that the stripes of the zebrafish possess an intrinsic wavelength, which is recovered even after total ablation of the pattern. Both these results would strongly suggest that a RD mechanism could be behind the observed pattern formation. We believe however that this idea should be ruled out for several reasons, among which the following two stand as the most important.

The first reason is that the cell-to-cell interactions, which are at the core of the pattern formation mechanism, cannot be considered as local events like reactions in RD systems. They involve instead two specific distances. When two skin pigment cells of different colors (the yellow xantophore and the black melanophore) are in close contact, they mutually inhibit each other’s growth. However, xantophores can also increase the rate at which melanophores appear (and their survivability) at long distance. The nonlocal character of the cellular interactions makes it impossible to cast them into chemical-like reactive terms, which (as said before) are supposed to act locally at each point in space.

The second – and perhaps even more important – evidence is that the pigment cells do not diffuse across the skin of zebrafish. They do exhibit some degree of mobility, but their movement – which has been characterized in vitro as a “run-and-catch” motion [Yamanaka2014] – cannot be represented as a Brownian motion. Even more importantly, this motion is very limited and is not enough to induce by itself a migration of pigment cells into separate domains [Mahalwar2014] [NOTE2]. In other words, cells are in a first approximation almost immobile.

The patterns on the skin of zebrafish thus look like RD patterns, but cannot be explained by reaction and diffusion. In order to solve the riddle posed by these patterns, we took inspiration from nonlinear nanochemistry. When chemical reactions are described at the nanoscale they cannot be interpreted as local processes, but as “propagating” in space. In mathematical terms, this effect translates into virtual diffusion terms [DeDecker2004] even if the molecules are immobile, because the reaction itself can induce a redistribution of the molecular populations in space. We thus thought that a similar effect could also exist for pigment cells on the skin of zebrafish.

— A new mechanism: differential growth

The question we wanted to answer was essentially the following: Is the the nonlocal character of the short-range and long-range interactions able to create a “virtual movement” of cells across the zebrafish skin, and to generate in such a way a pattern with an intrinsic wavelength?

To test our hypothesis, we needed a simple mathematical model which is also biologically relevant. In order to test whether the observed pattern formation can be explained only in terms of non-local interactions between xantophores and melanophores, we decided to completely remove any form of cellular motion from our model. For the same reason, we did not explicitly include a third type of pigment cell (iridophores), which was shown to be of some importance in the pattern formation on the body of the fish [Singh2014], but not in the fins [Patterson2013]. We then introduced the short-range and long-range interactions as stochastic processes occurring with different probabilities, opting again for the simplest possible implementation: pairwise cell-to-cell interactions. For the sake of completeness we also included the spontaneous differentiation and death of both pigment cells on the skin of the fish [NOTE3]. Finally we further simplified our model by finding a mathematically simple yet biologically representative set of parameters which would trigger pattern formation.

Numerical simulations showed that patterns with an intrinsic wavelength could be formed with our model. We moreover observed that the morphology and the periodicity of the patterns resemble those of the experiments. An analytical study of the evolution equations also showed that the patterns emerge from a Turing bifurcation, despite the absence of cellular motion, thanks to the non-local cellular interactions. This mechanism is intrinsically different from the reaction-diffusion mechanism proposed by Turing although, in our opinion, the patterns thus generated may still be called Turing patterns, because they result from a Turing bifurcation generated by nonequilibrium processes. The key ingredient to form the patterns is that cells can “be born” and die with different rates – or in more mathematical words can have different growth rates – depending on their surrounding. In order to give a unambiguous connotation to this mechanism and distinguish it from others, we proposed to call it “differential growth”. Differential growth promotes a non-trivial redistribution of cells across space by combining short-range and long-range cellular interactions in an appropriate way. In such situations cellular migration becomes accessory to pattern formation, so one cannot rule out the possibility of having Turing patterns solely because of lack of extensive cellular movement.

As a final note, we would like to mention a related, very interesting article which has recently been published in Development [Hiscock2015]. The authors propose a way to rationalize the different patterns-generating mechanism under a common mathematical framework, and try to derive simple rules for the control parameters which can be used as a guide to design experiments. It is interesting to note that the only mechanism for which the authors could not calculate a simple parametric constraint is precisely the type of mechanism we consider here. For reaction-diffusion systems, classical toy models can be used to derive the general rule that “the inhibitor must diffuse faster than the activator”. For the class of systems which fall under the differential growth mechanism, our model suggests that “the inhibitor must grow faster than the activator”, provided that the growth of the former is controlled by a long-range positioning of the latter.

— Notes

[NOTE1] Intended as the mathematical equilibrium of the set of equations describing the dynamics of the system, or in other words any reference homogeneous steady state solution of the latter.

[NOTE2] One of our initial guesses was that the short-range movement shown by the pigment cells could have been important in shaping the fine details of the stripes, more particular the small gap observed between two adjacent stripes. Because of the nature of our model, we could not test this hypothesis ourselves, but we recently discovered a preprint paper by A. Volkening and B. Sandstede titled “Modeling stripe formation in zebrafish: an agent-based approach” which independently proves this hypothesis true with a different modelling approach.

[NOTE3] To this regard, we feel like we should somehow apologize to the biology community for the choice of jargon we made in our paper: we there call “birth” what should more correctly be called “differentiation”. The reason of this choice is that the name commonly used in the stochastic mechanics literature for the class of processes we used is “birth/death” processes, so we felt that the model could be more easily understood by a broader audience of also non-biological scientists if we stuck to these names.

— References

[Bullara2015] Bullara, D., & De Decker, Y. (2015). Pigment cell movement is not required for generation of Turing patterns in zebrafish skin Nature Communications, 6 DOI: 10.1038/ncomms7971

[DeDecker2004] De Decker Y, Tsekouras GA, Provata A, Erneux T, & Nicolis G (2004). Propagating waves in one-dimensional discrete networks of coupled units. Physical review. E, Statistical, nonlinear, and soft matter physics, 69 (3 Pt 2) PMID: 15089388

[Hamada2014] Hamada, H., Watanabe, M., Lau, H., Nishida, T., Hasegawa, T., Parichy, D., & Kondo, S. (2013). Involvement of Delta/Notch signaling in zebrafish adult pigment stripe patterning Development, 141 (2), 318-324 DOI: 10.1242/dev.099804

[Hiscock2015] Hiscock, T., & Megason, S. (2015). Mathematically guided approaches to distinguish models of periodic patterning Development, 142 (3), 409-419 DOI: 10.1242/dev.107441

[Inaba2012] Inaba M, Yamanaka H, & Kondo S (2012). Pigment pattern formation by contact-dependent depolarization. Science, 335 (6069) PMID: 22323812
[Mahalwar2014] P. Mahalwar, B. Walderich, A.P. Singh and C. Nüsslein-Volhard, Local reorganization of xantophores fine-tunes and colors the striped pattern of zebrafish, Science 345:1362-1364 (2014).

[Nakamasu2009] Nakamasu, A., Takahashi, G., Kanbe, A., & Kondo, S. (2009). Interactions between zebrafish pigment cells responsible for the generation of Turing patterns Proceedings of the National Academy of Sciences, 106 (21), 8429-8434 DOI: 10.1073/pnas.0808622106

[Patterson2013] Patterson, L., & Parichy, D. (2013). Interactions with Iridophores and the Tissue Environment Required for Patterning Melanophores and Xanthophores during Zebrafish Adult Pigment Stripe Formation PLoS Genetics, 9 (5) DOI: 10.1371/journal.pgen.1003561

[Singh2014] Singh, A., Schach, U., & Nüsslein-Volhard, C. (2014). Proliferation, dispersal and patterned aggregation of iridophores in the skin prefigure striped colouration of zebrafish Nature Cell Biology, 16 (6), 604-611 DOI: 10.1038/ncb2955

[Turing1952] Turing, A. (1952). The Chemical Basis of Morphogenesis Philosophical Transactions of the Royal Society B: Biological Sciences, 237 (641), 37-72 DOI: 10.1098/rstb.1952.0012

[Yamaguchi2007] Yamaguchi, M., Yoshimoto, E., & Kondo, S. (2007). Pattern regulation in the stripe of zebrafish suggests an underlying dynamic and autonomous mechanism Proceedings of the National Academy of Sciences, 104 (12), 4790-4793 DOI: 10.1073/pnas.0607790104

[Yamanaka2014] Yamanaka, H., & Kondo, S. (2014). In vitro analysis suggests that difference in cell movement during direct interaction can generate various pigment patterns in vivo Proceedings of the National Academy of Sciences, 111 (5), 1867-1872 DOI: 10.1073/pnas.1315416111

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A 4-year PhD position is available in the group ‘ Evolution of nutrient and growth homeostasis in animals’ at the Sars Centre in Bergen/Norway. The successful candidate will study the molecular and cellular links between feeding, nutrient availability and reproduction using the sea anemone Nematostella vectensis as a main model organism.

Further details on the position, group and application procedure are available here:
http://www.sars.no/jobs/2015-10092_phd_steinmetz.php

Contact details:

Dr Patrick Steinmetz

e-mail:patrick.steinmetz@uib.no

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This week the Node is in Boston, MA! This Friday (25th of September) our community manager Cat will be giving two talks:

2.30 p.m.- Inside a Career in Scientific Publishing and Science Communication

Tufts Boston Campus, Sackler Building (145 Harrison Avenue), Room 316

6 p.m.- YEN Boston discussion: Building a Developmental Biology Community

Harvard Medical School, Warren Alpert Building: Room 563 (register here)

If you are in the Boston area, join us for one (or both!) of these talks! Cat would love to chat to you before or after the talks about the Node, social media or alternative careers. We look forward to meeting you!

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This editorial first appeared in Development.

In September 2014, Development organised a four-day workshop titled ‘From Stem Cells to Human Development’. In planning this meeting, we sought to fill what we saw as a gap in the meeting calendar – a way of bringing together a diverse cross-section of researchers with a common interest in using the rapidly developing tools of stem cell biology, genetic engineering and genomic analysis to understand human development (for a review of the meeting, see Medvinsky and Livesey, 2015). The enthusiasm with which this workshop was met, from invited speakers and registered participants alike, confirmed our view that we are now in a period in which significant inroads into understanding human development will be made. With our ever-improving ability to model tissue development in vitro and to manipulate the human genome (and epigenome), we are now in a position to analyse human organogenesis and to understand how it differs from that in other model organisms – and hence to start to probe the developmental biology underlying the evolution of our species.

As we wrote in an editorial in January, “The human development field represents an essential growth area for the developmental biology community, and Development is keen to play an active role in supporting and inspiring it” (Pourquié et al., 2015). This Special Issue celebrates that aim – bringing together a collection of Reviews and Research Articles that directly address a broad range of topics in human developmental biology: from the earliest stages of human development to cellular ageing and degeneration, and from basic questions of how an organ is formed to ways in which we might translate this knowledge in the clinic. We are also supporting this initiative with a second ‘From Stem Cells to Human Development’ meeting, to be held in September 2016. More details on what should be a fantastic follow-up event can be found at http://workshops.biologists.com/from-stem-cells-to-human-development-2/.

Studying human development is obviously a challenging endeavour, given the practical and ethical difficulties in working with human material. However, as discussed by Dianne Gerrelli and colleagues (2015), there is a growing set of resources for researchers, including the Human Developmental Biology Resource (with which the authors are affiliated), which provides embryonic and foetal material and a range of valuable services. Maintaining and developing such resources will be essential as research on human development progresses.

Complementing work using human tissue, much of the research into human development relies on the generation and manipulation of human pluripotent stem cells (hPSCs) – either embryonic (hESCs) or induced (hiPSCs). There has, however, been much debate surrounding the pluripotent status of such hPSCs, particularly when compared with their mouse equivalents, as well as their in vivo counterparts. In their Review, Martin Pera and colleagues (Davidson et al., 2015) discuss these controversies in the light of recent attempts to generate truly naïve hESCs. Kathy Niakan and co-workers are also interested in pluripotent states and human-mouse comparisons. In their Research Article (Blakeley et al., 2015), they report single-cell RNA sequencing analyses of human and mouse preimplantation epiblasts, identifying important differences in the transcriptomes – and presumably therefore the development – of the early human and mouse embryo. One challenge in the field has been that functional assays for pluripotency of human cells are limited. To address this, Hiromitsu Nakauchi and colleagues (Masaki et al., 2015) investigate whether generating inter-specific chimeras (using mouse epiblasts and PSCs from various species) might provide an alternative assay system. Also using mouse embryology to probe human development are Felipe Vilella and colleagues, who describe a microRNA secreted in human endometrial fluid that can promote mouse embryo adhesion during implantation (Vilella et al., 2015), potentially identifying a novel route by which the efficiency of implantation can be modulated.

In another research paper investigating the role of microRNAs in human development (Jönsson et al., 2015), Malin Parmar and co-workers analyse the microRNAs expressed in the human foetal brain and in PSC-derived neural progenitor cells, identifying region-specific microRNAs that probably influence neural cell fate. Generating a functional nervous system requires not only that cell fate is correctly defined, but also that appropriate connectivity is established and that neurons are properly supported by glia. Frederick Livesey and colleagues address the former problem in cortical neuron cultures (Kirwan et al., 2015), while Motoharu Sakaue and Maya Sieber-Blum describe a protocol for generating supporting Schwann-like cells from human epidermal neural crest stem cells (Sakaue and Sieber-Blum, 2015). Meanwhile, Ikuo Suzuki and Pierre Vanderhaeghen (2015) review various aspects of studying neural development using hPSCs and discuss how these approaches should allow us to gain insights into the evolution of the human brain.

Katie Pollard and Lucia Franchini’s interests also lie in understanding human evolution, but from a genomic perspective. Their Review (Franchini and Pollard, 2015) discusses how we can combine sequencing information with functional genomics and stem cell biology to identify and characterise changes in the human genome that might have led to human-specific developmental traits. They highlight the importance of appropriate experimental systems – not only model organisms but also through human stem cells and organoids – in which to test the function of human-specific genomic features. The ability to model not only cellular differentiation but also tissue formation in a dish constitutes a major breakthrough in the field over the past decade. Meritxell Huch and Bon-Kyoung Koo review the latest advances in generating endodermal organoids from both embryonic and adult stem cells (Huch and Koo, 2015) and provide a perspective on where this field is heading. The Review by Neil Hanley and colleagues (Jennings et al., 2015), while also focussing on endoderm development – in this case, pancreas – provides a complementary viewpoint, discussing what is known about human pancreas development in vivo and how these insights translate into our ability to generate β-cells in vitro.

Turning to other organs, Christine Mummery and Charles Murry and their colleagues both focus on heart development. Mummery’s work (van den Berg et al., 2015) characterises the transcriptome of the human foetal heart and compares it with the RNA profile of PSC-derived cardiomyocytes. Meanwhile, Murry’s study (Palpant et al., 2015) provides insights into how cardiomyocytes are specified in a hESC system. The final Research Article of this issue returns to the topic of organoid formation, this time the mammary gland. Christina Scheel and co-workers (Linnemann et al., 2015) present an organoid system that allows the regenerative potential and morphogenetic dynamics of mammary epithelial cells to be studied.

Although understanding human development is an important goal in itself, the translational potential of this field is clear: if we can grow human tissues in vitro, we can use these to model disease, to test potential drugs and to develop cell therapies. Two Spotlights in this issue discuss these aspects of the field. Scott Thies and Charles Murry (2015) present some of the most promising preclinical data and clinical trials of stem cell therapies, while Elsa Vera and Lorenz Studer (2015) highlight a potential problem with using stem cell-derived models in disease research: both hESCs and hiPSCs are ‘young’ cells, whereas many diseases – particularly neurodegenerative disorders – afflict the old. Although these articles stray from the classic scope of a developmental biology journal, we hope that they illustrate the continuum of both the field, from basic understanding of developmental processes to their applications in regenerative therapy, and of development itself – from embryogenesis through post-embryonic maturation to ageing and decline.

We have a limited number of print copies of this Special Issue to give away to interested readers. If you would like one, please send an email to dev@biologists.com with your mailing address. Whether in print or online, we hope you enjoy this Special Issue on Human Development. We see an exciting future for this field, and we want Development to be at the heart of it. We therefore encourage those of you working in this area to consider Development as a potential venue for the publication of your best work and we look forward to many more exciting human development papers finding their way into the pages of our journal.

(3 votes)

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Here are the highlights from the current issue of Development – our Special Issue on “Human Development”. This Special Issue brings together a collection of Reviews and Research Articles that directly address a broad range of topics in human developmental biology: from the earliest stages of human development to cellular ageing and degeneration, and from basic questions of how an organ is formed to ways in which we might translate this knowledge in the clinic. Happy reading!

Enabling research with human embryonic and fetal tissue resources

Gerrelli and colleagues summarise the remit and efforts of the Human Developmental Biology Resource – and other similar projects – that provides researchers with access to human tissue and related services. See the Spotlight article on p. 3073

The advancement of human pluripotent stem cell-derived therapies into the clinic

In their opinion piece, Thies and Murry consider progress in the use of human PSCs in regenerative medicine – fuelled by advances in developmental biology – in five areas that offer great promise for clinical applications. See the Spotlight article on p. 3077

When rejuvenation is a problem: challenges of modeling late-onset neurodegenerative disease

Vera and Studer discuss the difficulties involved in using stem cells to study diseases of the elderly and review how these might be overcome. See the Spotlight article on p. 3085

The pluripotent state in mouse and human

Pera and colleagues examine recent efforts in defining and capturing the human naïve pluripotent state in vivo and in vitro, in light of the different states of pluripotency found in the mouse. See the Review article on p. 3090

Genomic approaches to studying human-specific developmental traits

Franchini and Pollard discuss how genome sequencing and functional genomic approaches are enabling analyses of the evolutionary and developmental origin of traits unique to our species. See the Review article on p. 3100

Modelling mouse and human development using organoid cultures

Huch and Koo review recent advances in the generation of ESC- and adult stem cell-derived organoids in order to understand the development of endoderm-derived organs in human and to develop therapeutic strategies for repair. See the Review article on p. 3113

Human pancreas development

Jennings, Hanley and colleagues present a human-centric view of the latest advances in our understanding of pancreas development and the relevance of these insights from a clinical perspective. See the Review article on p. 3126

Is this a brain which I see before me? Modeling human neural development with pluripotent stem cells

Suzuki and Vanderhaeghen examine stem cell-based approaches to analysing human brain development, from specification of particular cell types to building neuronal networks. See the Review article on p. 3138

PLUS:

Research Articles/Techniques and Resources:

• Defining the three cell lineages of the human blastocyst by single-cell RNA-seq

• Comprehensive analysis of microRNA expression in regionalized human neural progenitor cells reveals microRNA-10 as a caudalizing factor

• Development and function of human cerebral cortex neural networks from pluripotent stem cells in vitro

• Human epidermal neural crest stem cells as a source of Schwann cells

• Inhibition of β-catenin signaling respecifies anterior-like endothelium into beating human cardiomyocytes

• Hsa-miR-30d, secreted by the human endometrium, is taken up by the pre-implantation embryo and might modify its transcriptome

• Interspecific in vitro assay for the chimera-forming ability of human pluripotent stem cells

• Transcriptome of human foetal heart compared with cardiomyocytes from pluripotent stem cells

• Quantification of regenerative potential in primary human mammary epithelial cells

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The National University of Singapore (NUS) invites applications for faculty appointment as Head of the Department of Anatomy.

The Department’s mission is to enhance the international stature of the School and of NUS through excellence in teaching and research. It is committed to teaching undergraduate medical, dental, pharmacy, and life science students. In addition, the Department provides research training to both undergraduate and postgraduate research students. Currently, research in the Department focuses on neurobiology, cancer biology and venoms & toxins in a vibrant academic environment. Researchers in the Department use a variety of techniques in cellular and molecular biology and the Department and the School are well equipped with state-of-the-art facilities.

The Department has over the past 5 years attracted SGD 10 million in competitive grant funding. The Department has 21 faculty members and a total of around 100 staff and postgraduate students. The Department publishes on average 57 scientific papers annually in high impact journals such as Cell, Nature Cell Biology, Nature Medicine, Journal of Clinical Investigations, Cancer Research, Hepatology, Advanced Materials, PNAS and Journal of Neuroscience. The Department enjoys strong collaborative links with research institutes within NUS, government agencies as well as overseas research institutes and leading universities.

The candidate should be an outstanding scholar who will be able to provide strong leadership in research and teaching with an excellent track record and international recognition for research in any of the main areas of research in the Department, or in developmental biology. Administrative experience in leading an academic department would be an added advantage. A generous start up package and first class laboratory facilities are available. The Head is expected to generate strong research programmes, secure external funding and provide intellectual leadership characteristic of a world-class university.

Remuneration will commensurate with the candidate’s qualifications and experience. Informal enquiries can be made to Ms Lee Sing Ee: medlse@nus.edu.sg Tel +65 6772 3729.

Interested parties should submit their applications, supported by a detailed resume and names of at least six referees to:

Ms LEE Sing Ee

Assistant Director, Academic Affairs

Dean’s Office

Yong Loo Lin School of Medicine

National University of Singapore

1E Kent Ridge Road, NUHS Tower Block

Level 11, Singapore 119228

Fax: +65-6778-5743   Email: medlse@nus.edu.sg

Closing Date: 31 October 2015

(Only shortlisted candidates will be notified)

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Genetically engineered mouse models have been used extensively to study a wide variety of biological processes in vivo, and innovations in genetic engineering have made it possible to dissect more intricate biological questions. For example, the first mice that showed successful germline transmission of foreign DNA were created in the 1980s, and this allowed the generation of various transgenic “oncomice” such as the first mouse model of breast cancer using the MMTV-Myc transgene ¹, and the first mouse model of osteosarcoma using the MT-FosLTR transgene ². Subsequently in the early 1990s, mice were developed to have whole-body deletions of various genes such as the p53 tumor suppressor gene ³. The combination of the ability to introduce oncogenes and delete tumor suppressor genes through these initial transgenic mouse technologies contributed greatly to our current understanding of cancer development, progression, and treatment.

Nonetheless, transgenic mice and whole-body knock out mice sometimes do not survive development ⁴. To overcome this limitation, investigators harnessed site-specific recombinase systems from bacteriophages and yeasts such as the Cre-loxP and the Flp-FRT systems, which were first adapted to the mouse genome for germline transmission in the 1990s to enable temporally-regulated and tissue-specific genetic manipulations ^{5, 6}. Since then, many conditional mouse alleles utilizing transgenic or endogenous promoter-driven Cre and loxP-regulated genes have been generated to increase tissue-specificity of gene expression and decrease pre-mature lethality and other unwanted phenotypes. Additionally, replication-defective viruses (adenoviruses, lentiviruses) containing Cre recombinase (Adeno-Cre, Lenti-Cre) have also been used to further improve upon the temporal regulation of gene expression ⁷. Further modifications enabled the viruses to carry specific promoter-driven Cre recombinases to add tissue specificity after viral delivery ⁸. Finally, similar temporal regulation can be achieved by using fusion proteins combining Cre and mutated hormone receptors such as the estrogen receptor (Cre-ER^T2) ⁹. By utilizing this approach, metabolites of tamoxifen can be used to translocate Cre-ER^T2 to the nucleus and thus activate subsequent Cre-mediated gene modification.

Recently, there has been increasing interest in combining more than one recombinase system in the same mouse model using dual recombinase technology to allow for sequential mutagenesis and to better model sporadic cancers in the adult mouse ^{10, 11}. In our lab, we have generated two complimentary new mouse alleles that facilitates the regulation of Cre-ER^T2 by the Flp-FRT recombinase system. Both alleles are knocked into the endogenous Col1a1 locus for ubiquitous expression, and also at the same time reserve the two Rosa26 alleles for other transgenes of interest. In the first mouse allele, Col1a1^{FRT-Cre-ER-T2-FRT}, Cre-ER^T2 is flanked by FRT sites. The rationale to generate Col1a1^{FRT-Cre-ER-T2-FRT} mice is to enable whole animal ubiquitous expression of Cre-ER^T2 until exposure to Flp recombinase (Figure 1A). After Flp-mediated recombination of the FRT sites, cells are no longer able to express Cre-ER^T2 and therefore lose the ability to delete DNA flanked by loxP sites following exposure to tamoxifen. In this way, different mutations can be introduced in adjacent cells in vivo so that the consequences for intercellular interactions, such as cancer cells and stromal cells, can be studied.   In the second mouse allele, Col1a1^{FRT-STOP-FRT-Cre-ER-T2}, Cre-ER^T2 sits downstream of a FRT-flanked STOP cassette, which inhibits transcription of Cre-ER^T2. The rationale to generate Col1a1^{FRT-STOP-FRT-Cre-ER-T2} is that initially no cell expresses Cre-ER^T2 because transcription of Cre-ER^T2 is terminated by an upstream FRT site-flanked transcription STOP cassette (Figure 1B). However, after Flp-mediated recombination, the STOP cassette is excised. Therefore, these cells can initiate transcription of the Cre-ER^T2 fusion protein, which in response to subsequent exposure to tamoxifen translocates into the nucleus to recombine DNA flanked by loxP sites. Cells without exposure to Flp will not be able to undergo Cre-mediated DNA recombination. In this way, the Col1a1^{FRT-STOP-FRT-Cre-ER-T2} allele enables sequential mutations within the same cell over time. First, one mutation occurs in the cell from Flp recombinase, and then tamoxifen activates Cre recombinase in the same cell to mutate a second gene to study how the order of gene mutations may affect cellular outcome. In addition, multiple genes may be mutated by Flp recombinase to initiate tumor development. Then, the role of a loxP-flanked gene in tumor maintenance can be studied because only the tumor cell will express Cre-ER^T2. This allele can therefore be used to identify potential therapeutic targets.

Through characterization of the Col1a1^{FRT-Cre-ER-T2-FRT} mice using the reporter allele Rosa26^{mTmG 12}, we found that a single intraperitoneal injection of tamoxifen at 75mg/kg into Col1a1^{FRT-Cre-ER-T2-FRT}; Rosa26^mTmG/+ mice is sufficient to translocate the Cre-ER^T2 fusion protein into the nucleus and mediate recombination of the loxP-sites flanking tdTomato. This resulted in the deletion of the tdTomato red fluorescent protein, and the subsequent expression of eGFP green fluorescent protein from cells of all tissues examined. The limitation of this model is that there is an age- and tissue-dependent Cre-ER^T2 activation independent of tamoxifen administration, most notably in the pancreas and the liver. Therefore, in experiments involving these organs using the Col1a1^{FRT-Cre-ER-T2-FRT} mice, age of the mice at the onset of Flp and tamoxifen administration is crucial for the interpretation of the results.

We also characterized the Col1a1^{FRT-STOP-FRT-Cre-ER-T2} mice using the reporter allele Rosa26^mTmG. When Col1a1^{FRT-STOP-FRT-Cre-ER-T2}; Rosa26^mTmG/+ mice were given a single intraperitoneal injection of tamoxifen at 75mg/kg, there was no Cre-ER^T2-mediated deletion of the tdTomato red fluorescent protein or expression of the eGFP green fluorescent protein. Next, we generated a mouse model of soft tissue sarcoma using the new allele to verify the ability of the STOP cassette to be removed by Flp, and the subsequent ability of Cre-ER^T2 to manipulate loxP-flanked alleles. In this model, Col1a1^{FRT-STOP-FRT-Cre-ER-T2}; Kras^{FRT-STOP-FRT/+}; p53^FRT/FRT; Rosa26^mTmG/+ mice were first administered intramuscular injection of adenovirus carrying Flp recombinase in the hindlimb to form soft tissue sarcomas at the site of injection via the expression of the oncogenic KRAS protein and elimination of the p53 tumor suppressor protein ^{11, 13, 14}. Following the formation of soft tissue sarcomas, either single intratumoral injection of 4-hydroxytamoxifen or several doses of systemic 4-hydroxytamoxifen were administered. The resulting tumor showed tumor parenchymal cells with deletion of tdTomato red fluorescent protein and expression of eGFP green fluorescent protein, while the tumor stromal cells such as the vasculature continued to express tdTomato. One potential challenge in this model is that while the Col1a1^{FRT-STOP-FRT-Cre-ER-T2} is functional, single intraperitoneal injection of tamoxifen failed to activate Cre-ER^T2 in primary sarcomas. Therefore, the delivery of an adequate level of tamoxifen and/or its metabolites into the tumor is critical to activate Cre-ER^T2 expression with this allele.

We anticipate that these two new alleles will allow for increased control of gene manipulation in genetically engineered mouse models. These alleles, in conjunction with other new technologies in the field such as the CRISPR/Cas9 system ¹⁵, have the potential to bring together the speed and efficiency of the CRISPR/Cas9 system with the spatial and temporal control of dual recombinase technology, manipulate the genome in vivo to study development, cancer and other diseases in the mouse.

Minsi Zhang and David Kirsch, Department of Radiation Oncology, Duke University Medical Center

Main reference

Zhang, M., & Kirsch, D. The generation and characterization of novel Col1a1FRT-Cre-ER-T2-FRT and Col1a1FRT-STOP-FRT-Cre-ER-T2 mice for sequential mutagenesis. Disease Models & Mechanisms. 2015. 8(9), 1155-1166 DOI: 10.1242/dmm.021204

Other references:

1. Stewart TA, Pattengale PK, Leder P. Spontaneous mammary adenocarcinomas in transgenic mice that carry and express MTV/myc fusion genes. Cell. 1984;38(3):627-37. PubMed PMID: 6488314.
2. Ruther U, Komitowski D, Schubert FR, Wagner EF. c-fos expression induces bone tumors in transgenic mice. Oncogene. 1989;4(7):861-5. PubMed PMID: 2547184.
3. Donehower LA, Harvey M, Slagle BL, McArthur MJ, Montgomery CA, Jr., Butel JS, Bradley A. Mice deficient for p53 are developmentally normal but susceptible to spontaneous tumours. Nature. 1992;356(6366):215-21. doi: 10.1038/356215a0. PubMed PMID: 1552940.
4. Jacks T, Fazeli A, Schmitt EM, Bronson RT, Goodell MA, Weinberg RA. Effects of an Rb mutation in the mouse. Nature. 1992;359(6393):295-300. doi: 10.1038/359295a0. PubMed PMID: 1406933.
5. Orban PC, Chui D, Marth JD. Tissue- and site-specific DNA recombination in transgenic mice. Proc Natl Acad Sci U S A. 1992;89(15):6861-5. PubMed PMID: 1495975; PubMed Central PMCID: PMC49604.
6. Dymecki SM. Flp recombinase promotes site-specific DNA recombination in embryonic stem cells and transgenic mice. Proc Natl Acad Sci U S A. 1996;93(12):6191-6. PubMed PMID: 8650242; PubMed Central PMCID: PMC39212.
7. Wang Y, Krushel LA, Edelman GM. Targeted DNA recombination in vivo using an adenovirus carrying the cre recombinase gene. Proc Natl Acad Sci U S A. 1996;93(9):3932-6. PubMed PMID: 8632992; PubMed Central PMCID: PMC39462.
8. Sutherland KD, Proost N, Brouns I, Adriaensen D, Song JY, Berns A. Cell of origin of small cell lung cancer: inactivation of Trp53 and Rb1 in distinct cell types of adult mouse lung. Cancer Cell. 2011;19(6):754-64. doi: 10.1016/j.ccr.2011.04.019. PubMed PMID: 21665149.
9. Indra AK, Warot X, Brocard J, Bornert JM, Xiao JH, Chambon P, Metzger D. Temporally-controlled site-specific mutagenesis in the basal layer of the epidermis: comparison of the recombinase activity of the tamoxifen-inducible Cre-ER(T) and Cre-ER(T2) recombinases. Nucleic Acids Res. 1999;27(22):4324-7. PubMed PMID: 10536138; PubMed Central PMCID: PMCPMC148712.
10. Shai A, Dankort D, Juan J, Green S, McMahon M. TP53 Silencing Bypasses Growth Arrest of BRAFV600E-Induced Lung Tumor Cells In a Two-Switch Model of Lung Tumorigenesis. Cancer research. 2015. doi: 10.1158/0008-5472.CAN-14-3701. PubMed PMID: 26001956.
11. Schonhuber N, Seidler B, Schuck K, Veltkamp C, Schachtler C, Zukowska M, Eser S, Feyerabend TB, Paul MC, Eser P, Klein S, Lowy AM, Banerjee R, Yang F, Lee CL, Moding EJ, Kirsch DG, Scheideler A, Alessi DR, Varela I, Bradley A, Kind A, Schnieke AE, Rodewald HR, Rad R, Schmid RM, Schneider G, Saur D. A next-generation dual-recombinase system for time- and host-specific targeting of pancreatic cancer. Nat Med. 2014;20(11):1340-7. doi: 10.1038/nm.3646. PubMed PMID: 25326799; PubMed Central PMCID: PMC4270133.
12. Muzumdar MD, Tasic B, Miyamichi K, Li L, Luo L. A global double-fluorescent Cre reporter mouse. Genesis. 2007;45(9):593-605. doi: 10.1002/dvg.20335. PubMed PMID: 17868096.
13. Moding EJ, Lee CL, Castle KD, Oh P, Mao L, Zha S, Min HD, Ma Y, Das S, Kirsch DG. Atm deletion with dual recombinase technology preferentially radiosensitizes tumor endothelium. J Clin Invest. 2014;124(8):3325-38. doi: 10.1172/JCI73932. PubMed PMID: 25036710; PubMed Central PMCID: PMC4109553.
14. Moding EJ, Castle KD, Perez BA, Oh P, Min HD, Norris H, Ma Y, Cardona DM, Lee CL, Kirsch DG. Tumor cells, but not endothelial cells, mediate eradication of primary sarcomas by stereotactic body radiation therapy. Sci Transl Med. 2015;7(278):278ra34. doi: 10.1126/scitranslmed.aaa4214. PubMed PMID: 25761890; PubMed Central PMCID: PMC4360135.
15. Platt RJ, Chen S, Zhou Y, Yim MJ, Swiech L, Kempton HR, Dahlman JE, Parnas O, Eisenhaure TM, Jovanovic M, Graham DB, Jhunjhunwala S, Heidenreich M, Xavier RJ, Langer R, Anderson DG, Hacohen N, Regev A, Feng G, Sharp PA, Zhang F. CRISPR-Cas9 knockin mice for genome editing and cancer modeling. Cell. 2014;159(2):440-55. doi: 10.1016/j.cell.2014.09.014. PubMed PMID: 25263330; PubMed Central PMCID: PMC4265475.

(1 votes)

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PhD POSITION

THE ROLE OF JNK SIGNALLING IN BRAIN REGENERATION

A PhD position is currently available (starting January 2016) to develop a project involving the analysis of the role(s) of the JNK signalling in brain regeneration using Drosophila (mainly) and zebrafish as model systems.

Most of the project will be developed at the “Cell Signalling and Morphogenesis” laboratory of the Institute of Molecular Biology of Barcelona but will also include short periods at the “Center for Regenerative Therapies TU Dresden”

REQUIREMENTS

Graduates in Biology, Physics or related areas with a strong track record and deep interest in Developmental Genetics, Neurosciences or Regenerative Biomedicine are encouraged to apply. Laboratory experience would be a definitive advantage.

The successful candidate will hold a research stipend in Dresden for up to 3 years and develop his/her research project(s) using a wide array of techniques and in vivo models.

CONTACT:

Dr. Enrique Martin‐Blanco, IBMB‐CSIC, SPAIN

(+34934034668 – embbmc [at] ibmb.csic.es)

Prof. Michael Brand, CRTD, GERMANY

(+4935145882301 – michael.brand [at] biotec.tu-dresden.de)

Job offer EMB-MB

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

Text translated from the Italian. I think. With profound apologies to Dante Alighieri (D.A.)

Midway (or more? I hope not) on the journey of my independent career

I found myself in a dark forest…okay, it was my dark office;

My grant had been rejected, and the revision was soon due.¹

I wasn’t writing normally; everything was coming out in triplets.

Sort of like a poem, except it didn’t rhyme. Or maybe it did,

If it were in another language. Except I don’t speak any other languages.²

Why did my grant crash and burn?³ How did I fail so badly?

Okay, it wasn’t an awful score, but miles away from being funded.

It’s just so unfair, this whole rejection thing. I mean, why can’t I get agood review?

Oh, but drat⁴, I hate revising grants. They eat my time like lions, or maybe

Gerbils. Or knockout mouse lines I have to list. Make a note, I have to remember

To list all the bloody mouse lines. I got dinged⁵ on that. I shouldn’t have to do this.

Yeh, lions and gerbils and knockout mice, oh my. And maybe bears.

But then there was a figure before me, to lead me on a tour, he said, of Grant Hell.

“It’s going to be a long night,” he told me, “maybe have a snack first.⁶”

“Who are you?” I asked, because he looked like Dumbledore.

And I didn’t want to go all Harry Potter on him. “I was Francis Bacon in life⁷”, said he.

Great. But hey, it could have been worse, I guess. “Can I call you Frank?”

“This is all my fault, you know,” he said, “I devised the scientific method,

which I still think is a good thing. I didn’t even think about grants.

My bad. Do you still say ‘My bad?’ Anyway, my bad.”

“But grants are a reality of how we do science. Okay, in my day we didn’t have

Grants; we had to find a benefactor.⁸ But you, at least, have a better chance.

And still, many of you would rather complain than revise your approach.”

And into Grant Hell⁹ we went. “We’re going to start at the bottom,”

He whispered, “because that’s really how it goes. Are you up for this,

or are you going to punk out?” I really wanted a drink. Not tea.

We were bathed in flames, but as shades we didn’t burn. Good, that.

“This is the Ninth Circle,” Frank said. “We won’t stay here because it’s really bad,

This is Treachery, saved for those who steal other’s projects.¹⁰” It really stank.

We passed by this one, and up to the Eighth, the circle of Fraud. It also stank.

“Some desperate sociopaths¹¹ who fake results to write a grant,” he whispered.

I was glad they had their heads firmly inserted where heads don’t properly go.

We stopped to watch Violence in the Seventh Circle. Saved for those who

Blamed their trainees for their failures. Here, the wretched watched

As their papers were shredded and labs were trashed. Serves them right.

Here in the Seventh, the trainees taunted the damned mentors.

“You could have paid attention to what I was doing!” “You jerk,

You could have mentored me, instead of dissing everything.”¹²

We climbed our way to the Sixth Circle, and here we found Heresy.

“WTF?” I asked Frank. He shrugged. “Hey, I didn’t make this place.

Here is where we go when our ideas are completely out of line with the field.”

“But that’s just good science,” I argued. “Are you telling me that these

Poor souls are here because they disagree with the common wisdom?

We have to just toe the party line and not have our own ideas?”

“No,” said Frank. “You’re missing the point. They are here because

They can’t convince anyone that their alternative viewpoint has any value.

So they huddle together and agree with themselves, and no one else.”

I approached one of the denizens. He looked at me with red-rimmed eyes.

“‘AIDS isn’t a virus’,” he quoted, “‘it is a condition of immoral lifestyle. So is cancer.’”

“I get it,” I told Frank, “alternative is fine, but stupid is stupid.”

Up to the Fifth Circle, we roamed. Here was Anger. The wretched moaned,

And complained about their fate to each other, which was pretty awful.

Since they were all working on pretty much the same things.

“It’s all your fault!” said one to the group. “If I were the only one in this field,

I’d have my grants funded. Everything I proposed was perfectly fine.”

“That’s what I said,” complained another. “Except it’s your fault.”¹³

to be continued…

↵1- Mole is a huge baby about writing grants. He calls it ‘bleeding on paper.’ The process involves putting together a plan, with supporting data, for work that is meant to have not yet been attempted, but generally must be well underway, without supporting funds. These are reviewed by ‘peers,’ other scientists who may have a passing familiarity with the research area, who meet to figure out how not to support the application. Following the almost inevitable rejection, the application is revised with more supporting data (generated without support, somehow), which results in a ‘revision,’ submitted for evisceration by another set of peers. As a consequence, a great deal of work is done without support. Once approved and funded (if that happens), the now funded scientist forgets all of the bloodshed, and generally works on something else altogether.

↵2- This is true. Including English.

↵3- (cadere a pezzi). Grants are either funded or not. If they are not funded (the most common scenario), we tend to feel that they utterly failed, and in a sense this is true. Unlike hand grenades, horseshoes and the predictions of pundits, ‘close’ does not matter with grants. This is not conventional wisdom: most will assume that ‘nearly funded’ means ‘it will get funded next time.’ Unfortunately, this does not follow. Each grant or its revision should be written as though it is the first time anyone will see it. Most often, that is the case (see Footnote 1).

↵4- merde

↵5- Ho un ragno nei pantaloni (lit. I have a spider in my pants). One never knows what a reviewer will home in on, and when we are working on a revision, we often refocus on such criticisms. However, do not be deceived: while it is important to pay attention to all criticisms, these are not ‘why’ a grant does not get funded. Do not fall into the trap of thinking that by ‘fixing’ such problems, the grant will not pay off.

↵6- Mangia un panino al burro di arachidi.

↵7- 22 January 1561–9 April 1626. English. ‘Frank’ was not only a scientist but also a philosopher, statesman, jurist, orator, and author. In addition, he worked as Attorney General and Lord Chancellor of England. He makes Mole feel exceptionally lazy.

↵8- The benefactor system was one way science was done until well into the 19th century. The only alternative was to finance the work oneself (a ghastly thought). Unlike the grant system, which relies on peer review (at least on the surface), one needed to convince a benefactor to provide the funding, and often the place in which the work was done, and funds could be withdrawn at any time. While it may seem outdated, a form of this is practiced today in the form of contracts from industry, who often seem even more pernicious than the benefactors were.

↵9- Every applicant for a research grant has experienced Grant Hell in some form. Here, though, Mole is being escorted through the nine circles of Grant Hell to learn why grants are not successful. He begins at the lowest level (unlike D.A.’s tour of real Hell) because it gets better as he goes up. But it’s all pretty awful.

↵10- It is not the case that grants fail to be funded because they were stolen from someone else. Mole simply hopes this is the case. Actually, he hopes that these people will be bitten by monkeys.

↵11- Colui che morde la scimmia (lit. he who bites the monkey)

↵12- Some investigators fail to realize that the critical interactions among laboratory workers and themselves goes two ways. Criticism is an important part of the enterprise, but if this is only negative, the morale of the laboratory declines. We are not only our laboratories’ critique, but also the cheerleaders. When we support the work of our trainees, and devote ourselves to their development, they can help us find our way out of this circle of Grant Hell. Mole is forever grateful to his own trainees, who pull together to generate supporting data for ideas he writes in his grants, and once the grant is submitted (whether or not it is supported) he works with them to develop the findings further.

↵13- It is often the case that grants are not supported because too many other people are working on the same questions, which raises issues as tohow important the questions are. This is something many applicants never take into consideration, making the error of believing that given that so many others are working on something, it must be important. But those who evaluate the proposal vary in their interests, and are often unconvinced by this argument. The answer is not to try to force others out of our area of interest, but instead, to frame our research plans in such a way that we highlight how our own work is unique. Where would the field be if you had never worked in it? Where would it be if you were not supported in what you plan to do? Channel that anger into something creative, or indeed, this circle of Grant Hell will be home.

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