Here are the highlights from the current issue of Development:

Small (molecule) steps to making bone

The repair of cartilage and bone following damage remains a clinical challenge. Current cell-based therapies rely mostly on adult mesenchymal stromal cells, but the expansion of these into correctly differentiated and functionally competent chondrocytes, which give rise to cartilage and then bone, remains problematic. Here, Naoki Nakayama and colleagues develop a small molecule-based approach that mimics the embryonic somitic chondrogenesis programme and can be used to differentiate mouse embryonic stem cells (ESCs) into chondrocytes in vitro (p. 3848). The authors first show that activation of Wnt signalling using a small molecule inhibitor of Gsk3 (CHR99021), together with inhibition of BMP signalling using a BMP type I receptor inhibitor (LDN193189), is sufficient to induce ESCs to form paraxial mesoderm-like progeny. This population, they report, expresses trunk paraxial mesoderm and somite markers but fails to express markers of sclerotome, which gives rise to cartilage. However, knowing that sonic hedgehog (Shh) and the BMP antagonist noggin are required for sclerotome induction in vivo, the researchers then demonstrate that short-term treatment of the mesodermal progeny with an Shh receptor agonist (SAG1) and the BMP inhibitor LDN193189 results in a sclerotome-like intermediate, leading to functional chondrocyte formation. When ectopically transplanted into immunocompromised mice, these chondrocytes were able to mineralise and form pieces of bone that contain marrow. This readily scalable and chemically defined method for directing chondrogenesis thus offers a promising approach for cartilage-mediated bone regeneration.

OTX2 gets a head start

The gene orthodenticle homologue 2 (Otx2) encodes a paired-type homeodomain transcription factor that is known to play a role in head morphogenesis. In the mouse, Otx2 is expressed in the anterior neurectoderm, where it is required for the differentiation of anterior neural tissues. Otx2 is also expressed in the anterior mesendoderm (AME) but its role here is unknown. On p. 3859, Patrick Tam and co-workers investigate the role of Otx2 in the AME. Using Otx2 AME conditional knockout embryos, the researchers show that Otx2 activity in the AME is essential for head formation. They further demonstrate that the expression of Dkk1 andLhx1, which are known regulators of head formation, is impaired in the AME of the Otx2conditional knockout embryos. Dkk1 is a direct target of Otx2, and the researchers further identify regulatory regions in the Lhx1 locus to which Otx2 can bind, suggesting that Lhx1 is also likely to be a direct target of Otx2. Finally, the analysis of AME-specific Otx2;Lhx1 andOtx2;Dkk1 compound mutant embryos reveals that Otx2 acts synergistically with Lhx1 andDkk1 in the AME during head formation. In summary, these findings uncover a crucial role for Otx2 during head and forebrain development.

A new TALE of PU.1 function

Numerous transcription factors (TFs), including PU.1 and Scl, are known to play important roles during haematopoiesis, but how these act within wider TF networks is unclear. Now, Berthold Göttgens and colleagues use transcription activator-like effectors (TALEs) to manipulate the expression of PU.1 and Scl and determine how these TFs function during developmental haematopoiesis (p. 4018). They first show that the modulation of PU.1 expression affects cell fate decisions during embryoid body haematopoiesis; PU.1 upregulation, for example, drives haematopoietic commitment but causes a loss of proliferative ability, whereas PU.1 repression inhibits the maturation and differentiation of early haematopoietic cells. They further report, using single-cell gene expression analyses, that TALE-induced PU.1 expression is associated with changes in the expression of several other haematopoietic genes, suggesting that early activation of PU.1 expression drives a haematopoietic programme at the expense of endothelial gene expression. Following on from this, the researchers show that the PU.1-14kb enhancer is active in the mid-gestation dorsal aorta in vivo, and that PU.1 is detectable in the early haemogenic endothelium. Together, these studies uncover a novel role for PU.1 during haematopoietic specification and highlight the use of TALEs in understanding developmental TF networks.

Modelling morphogen-controlled gene expression

Pattern formation during development often depends on the differential regulation of gene expression in response to a morphogen gradient, but how such gradients govern gene expression is unclear. A simplified view suggests that the morphogen activates a transcriptional activator, and that differential gene expression is dependent on the affinity or number of binding sites for this activator within target genes. However, this model does not account for bifunctional transcriptional effectors – those that function as activators and repressors – and has also been questioned by recent experimental results. Here, James Briscoe and colleagues describe a unifying mathematical model of morphogen-dependent gene expression that can explain recent counterintuitive findings (p. 3868). Using sonic hedgehog (Shh)-dependent patterning of the mouse neural tube as an example, the researchers develop mathematical models, based on statistical thermodynamic principles, that account for competitive binding of the active and repressive isoforms of Gli, the transcriptional effector of Shh, and that also represent other inputs that are known to regulate Shh target gene expression. Their modelling predicts that, for each Gli target gene, there is a neutral point in the Shh gradient, either side of which altering Gli binding affinity has the opposite effect on gene expression. They further report that inputs other than the morphogen determine the transcriptional response. Together, these analyses help reconcile conflicting results in the field and provide a theoretical framework that can be used to examine differential gene expression in other contexts.

PLUS…

 

The T-box gene family: emerging roles in development, stem cells and cancer

The T-box family of transcription factors exhibits widespread involvement throughout development in all metazoans. Here, Virginia Papaioannou provides an overview of the key features of T-box transcription factors and highlights their roles and mechanisms of action during various stages of development and in stem/progenitor cell populations. See the Primer on p. 3819

 

New insights into the maternal to zygotic transition

The initial phases of embryonic development occur in the absence of de novo transcription and are instead controlled by maternally inherited mRNAs and proteins.  Following this period of transcriptional silence, zygotic transcription begins, the maternal influence on development starts to decrease, and dramatic changes to the cell cycle take place. Here, Steven Harvey and colleagues discuss recent work that is shedding light on the maternal to zygotic transition. See the Review on p. 3834

 

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To form complex organs, somatic stem cells proliferate and then differentiate during development. In this process, intrinsic factors, i.e. the sequential expression of transcriptional genes, and extrinsic factors, i.e. extracellular microenvironment, are intimately involved. Recent in vitro studies have revealed that the physical properties of the extracellular niche, possibly tissue stiffness, may play an important role in cellular behavior, growth and differentiation. This is referred to as “mechanotransduction”. However, the procedure by which physical cues are sensed and translated into gene expression, and their physiological significance in vivo,are essentially unknown.

To understand the role of mechanotransduction in cellular behavior and fate specification during development, one of the critical points is to determine whether there are any spatiotemporal shifts in stiffness in a given developing tissue. Atomic force microscopy (AFM) is a strong tool for this purpose. Using this system, the stiffness in certain postnatal tissues including the brain has been previously examined. In our recent paper in Development, we combined this system with a structural support to measure stiffness in the embryonic mouse brain, one of the softest tissues in our body. We further combined this technique with immunostaining, to increase the spatiotemporal resolution of the measured tissue based on anatomical information (Figure 1A).

As a result, we obtained hitherto unknown results about the shift in stiffness in the developing brain tissue (Iwashita et al, 2014; Figure 1). First, stiffness in the proliferative zones including ventricular zone (VZ) and subventricular zone (SVZ) gradually increases during embryogenesis (Figure 1B). During brain development, gliogenesis starts around birth, after the neurogenic period takes place. Interestingly, previous studies showed in vitro that the lineage shift from neural to glial cells was influenced by a shift in stiffness. Our results provide an attractive scenario in which the extracellular environment, i.e. the stiffened tissue in the later stages of the embryonic brain, may be arranged for better production of glial cells in vivo.

Secondly, we found that there is a sharp peak in stiffness in the intermediate zone (IZ) and a gentle peak in the cortical plate (CP), at the middle stage of neurogenesis (Figure 1B, C). In addition, the stiffness in the IZ tends to be higher than other regions at the mid-stage of brain development. In the IZ, massive cell migration is observed during brain development. Although the physiological significance of the higher stiffness in the IZ is still unclear, it may contribute to directed migration of neural cells toward the CP.

To summarize, we described for the first time the spatiotemporal shift in stiffness that is observed in the developing brain. In this study, we measured the developing brain tissue and cellular stiffness as an experimental model. Our strategy, however, can be applied to profile various types of tissues and cells, and could help understanding the role of tissue stiffness as a physical cue for cell fate determination of somatic stem cells.

 Figure 1. Summary of spatiotemporal measurement using AFM (click image to see a bigger version)

(A) Immunohistological images of developing brains. Cortical layers consist of VZ, SVZ, IZ and CP. Preplate (PP) is a structure transiently appears in early phase of brain development. Red, Pax6; blue, Tbr2; green, Tuj1. This data is modified from Iwashita et al., 2014, Figure 2A.

(B) Schematics of the temporal shifts in stiffness in each layer. The vertical axis shows tissue stiffness. The horizontal axis shows the developmental time course.

(C) Schematics of the spatial shifts in stiffness of cortical layers in each developmental stage. The horizontal axis shows stiffness.

Misato Iwashita and Yoichi Kosodo

Iwashita, M., Kataoka, N., Toida, K., & Kosodo, Y. (2014). Systematic profiling of spatiotemporal tissue and cellular stiffness in the developing brain Development, 141 (19), 3793-3798 DOI: 10.1242/dev.109637

(5 votes)

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Last week, several of the Company of Biologists’ team de-camped to Surrey for our latest Workshop ‘From Stem Cells to Human Development’. Unlike previous events, this was a larger meeting, with 112 participants from all over the world. Organised by the editors of Development, the theme of the meeting (as implied by the title!) was how the use of stem cell technologies can inform our understanding of human development, and speakers covered a diverse array of topics – from the earliest stages of human development to generating different tissue types in vitro and using culture systems to understand organ morphogenesis as well as modelling disease. We also included presentations and a panel discussion on ethical aspects of human stem cell research – more on this in a later post!

Held in the beautiful surroundings of Wotton House, Surrey, the meeting proved a huge success – with a relaxed and collaborative atmosphere and plenty of time for discussion both during and between sessions. It also captured an exciting and growing field: now that we have the ability to generate many differentiated cell types (and tissues) from human stem cells in vitro, we can start to pick apart the mechanisms underlying our own development – and see the similarities and differences between humans and other mammalian systems.

Development will be publishing a formal meeting report in an upcoming issue; for now, here are a few photos of the event, as well as a Storify of tweets from the meeting – which we hope will give a flavour of this exciting workshop.

The poster sessions were hugely interactive – people had to be torn away from their posters to go back into the session!

The ethics session provided an important alternative view on stem cell research – what do we need to think about when planning our experiments and discussing our research with the public?

And outside the formal sessions, there was plenty of time for discussion – in the grounds of the venue, over meals and in the bar…

Look out for more on the Node on this workshop in the coming weeks!

(2 votes)

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This post was originally published in the Knoepfler Lab Stem Cell Blog. 

Sometimes in science there are unexpected threads tying seemingly very different things together.

Unraveling the knots in these threads can lead to new insights into important developmental processes and mechanisms of disease.

My lab studies epigenomic and transcription factors including a molecule called histone variant H3.3 (more here on H3.3).

H3.3 binds to the actual thread of DNA to create very different kinds of chromatin states than those made by the more traditional canonical histone H3 family members. Think of H3.3 as the unorthodox member of the histone H3 family.

Recent studies have indicated that H3.3 plays key roles in both stem cells and cancer.

What’s going on?

H3.3 has a powerful, unique impact on which genes are turned on or off in cells and in turn how cells decide how to structure their chromosomes including both stem cells and cancer cells.

The jobs of H3.3 of essentially being a gene thermostat and of regulating genomic architecture are fundamental to a variety of cellular and organismal process including as it turns out both sperm development and brain tumors. For better or worse, H3.3 is a key conductor of both of these processes.

My lab just came out with a new paper in the journal Development in which we knocked out one of two genes that make H3.3 protein and got some surprising results. Wait, you say, two genes make H3.3? Yes. Histones more generally are unusual proteins in a number of ways including the fact that more than one histone gene will make exactly the same histone protein. This is, of course, very different than most protein-coding genes that follow the one gene-one protein rule.

The two genes that make H3.3 protein, H3f3a and H3f3b, are expressed differentially so cells may make their total pool of H3.3 protein only from the “a” gene or only the “b” gene or from both. We knocked out the “b” gene.

For about half the mice lacking “b”, this meant that embryonic development failed. Interestingly, almost every surviving “b” knockout mouse was infertile including all males and just about every female. Why did this happen? The b-deficient germ cells, the cells that make sperm in males and eggs in females, essentially had a monkey wrench thrown into their chromatin machinery due to the fact that they had very little H3.3 protein.

As a result, some genes switched inappropriately into “on” mode, while others that were supposed to be active were  switched off. The germ cell DNA was also not packaged properly. The end result was dead or dysfunctional sperm. In addition, earlier on in the spermatogenesis process, specific more primitive germ cell populations in the “b” knockouts died as well.

One of the most prominent epigenetic factors involved in this germ cell phenotype in the “b” knockout mice was a histone mark called trimethylation of lysine 9 of histone H3 (H3K9me3). Histone marks constitute a code that helps regulate gene expression and chromatin architecture. H3K9me3 seem to help shut genes off.

With very little total H3.3 protein in the “b” knockout mouse germ cells, H3K9me3 accumulated abnormally (see image above of immunostained testes from Figure 3B: blue is DAPI and green is H3K9me3, with the bottom gray panels being H3K9me3 alone). We think this excess H3K9me3 played a central role in germ cell dysfunction and in infertility in the knockouts, but other histone marks were altered as well.

Turns out that the other H3.3-coding gene, H3f3a aka the “a” gene, is also required for normal murine sperm development too, but in addition in the humans the human version of the “a” gene (called H3F3A) is mutated in some of the most lethal of all childhood brain tumors called glioblastoma and diffuse intrinsic pontine glioma (DIPG), both called high-grade gliomas more broadly. H3F3B (the human form of the mouse “b” gene) is mutated in other human childhood tumors including bone and cartilage tumors. Therefore, mutated histone H3.3 is a new oncoprotein and H3F3A and H3F3B may normally act as tumor suppressor genes in a variety of tissues including brain, bone, and cartilage. We think that what H3.3 is doing normally in germ cells to maintain fertility and what goes wrong  there when we lower H3.3 levels both have some things in common with what H3.3 is doing so wrong when it is mutated to lead to brain tumors.

One of our lab’s big picture goals is to help to develop new treatments for pediatric gliomas because today sadly most of these children die within just a year or two of diagnosis even with today’s best treatments.How these H3.3 mutations lead to these lethal brain tumors in kids is not clear, but our lab and many others are working to figure this out. You can bet that chromatin and epigenetics have a lot to do with it and surprisingly insights from how H3.3 normally functions in germ cell development could help us figure out how H3.3 leads to cancers when it is mutated in people.

Yuen, B., Bush, K., Barrilleaux, B., Cotterman, R., & Knoepfler, P. (2014). Histone H3.3 regulates dynamic chromatin states during spermatogenesis Development, 141 (18), 3483-3494 DOI: 10.1242/dev.106450

(4 votes)

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Here are some of the highlights for September:

Research:

– Sylvain discussed his recent Development paper on the tristable regulatory network behind cell fate decisions in the early embryo.

– Aryeh wrote about his research on spontaneous patterning of human ES cells, recently published in Nature Methods (he is also hiring a postdoc!).

– and Christelle highlighted a recent paper on the role of Runx1 in the haematopoietic lineage.

Meeting reports:

– Denise went to the annual meeting of the Society for Developmental Biology.

– Gary shared his thoughts on the recent Xenopus meeting in sunny California.

– and Danielle and Gi Fay reported from the joint Autumn meeting of the British Societies for Developmental Biology and Matrix Biology.

Future of Research Symposium:

A group of postdocs in the Boston area are organising a symposium to discuss what should change to make science better. A series of posts examines some of the issues that will be discussed:

    – How should scientists be trained?

    – Workforce structure– are there too many postdocs?

    – Metrics and Incentives

    – Is the level of funding appropriate?

Also on the Node:

– Joana asked for advice on designing ChIP primers.

– What do you think makes a perfect conference venue?

– And we reposted a Development editorial, on the ethical issues frequently encountered by the journal.

Happy reading!

(2 votes)

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This is the last of four posts relating to the Future of Research symposium which was announced in a previous blog post. Each of these posts will discuss a topic that is the focus of a workshop at the Symposium. Even if you can’t attend, please tweet @FORsymp with suggestions, or follow us to respond to our questions about what YOU, trainee scientists, think is important. The hashtag for this post on the Funding workshop is: #FORfunding

Is the level of funding for research appropriate?

Industry research and development (R&D) spending has increased from approximately one third to two thirds of the total over the last decades, with Federal dollars making a complementary decrease (Historical Trends in Federal R&D). However, funding for basic research within this is primarily supplied by the Federal government. The Federal government accounts for 55% of total basic research funding (Science and Engineering Indicators 2014), whereas less than 4% of the money industry spent on R&D has gone to basic research (Research and Development 2008).

Figure 1: National R&D by funder. Source: NSF.

Part of the crisis in the scientific enterprise is due to the unpredictability of research funding over time. Federal biomedical research funding nearly tripled over the decade ending in 2002, but has shrunk ~25% since (Figure 2, Alberts, 2014). As early as 2003, the rapid increase in funds over the previous decade was generating questions as to where trainees would end up with no concomitant increase in academic positions (Russo, 2003). There was also a call for institutions to become more responsible for funding “hard-money” faculty positions, and to remove NIH incentives for doing so, rather than relying on external sources of funding for “soft-money” positions (Alberts, 2010). Now that there has been a contraction in funding, these problems, left unanswered, have become immediate. For institutions and individual researchers attempting to make long-term career or program decisions, uncertainty makes coming up with good plans very challenging.

Figure 2: NIH Budget. Source: AAAS.

Is funding well allocated?

Under the current system, funding primarily supports individual investigators for approximately five-year periods. Most of this funding is for project-based grants in response to proposals that designate a specific plan of work, usually relying on preliminary data.

A new Federal funding mechanism has recently been proposed, the Maximizing Investigators’ Research Award, which would support a lab’s overall research program rather than being specifically directed to a particular project.

Since funding for basic biomedical research comes heavily from tax dollars, it is important that taxpayers get value for their money. In particular, trainee support is a small fraction of the total (approximately 4% of the total NIH research grant budget).

What can be done?

Now that the system has reached an identified point of crisis (Alberts, 2014) there are unanswered questions as to what happens next and speculation is rife. For example, the spectre of “unpaid postdocs”, furthering the similarity of postdoctoral research to corporate internships, has been raised. But putting more money into the system has been suggested as only a temporary fix, that does not provide long-term solutions to the problems in academic structure (Martinson, 2007; Alberts, 2014).

The objective of the Funding workshop is to ask:

How do we structure funding to promote desired outcomes such as the discovery of basic knowledge, finding applications of knowledge for the betterment of society, and training the next generation of scientists?

Senator Elizabeth Warren has proposed both doubling the total investment in scientific and biomedical research and removing the NIH budget from the annual budgeting process (Warren 2013). The American Academy of Arts and Sciences (Augustine 2014) has offered a proposal along the same lines and further offer a number of detailed proposals for reducing overheads associated with securing and employing funding, focusing training funds on individuals rather than on programs, and improving communication with the public on the contributions and importance of the basic research enterprise.

We would like to hear your perspective on the merits of these proposals as well as suggestions of your own at the Symposium!

Questions relating to funding

Given that most funding comes from public sources, what is the moral obligation of scientists to serve the broader community? Is there a moral imperative to use the money as efficiently as possible (and therefore conduct science as efficiently as possible)?

Should funding for research and training be separated?

Should there be different funding mechanisms for post-docs that intend to pursue a career in industry versus academia?

Should there be a regional cost of living adjustment of grad student and post doc salaries?

This post has been written from input provided by the moderators of the workshop on “Funding in Research”.

References

Science and Engineering Indicators 2014. National Science Foundation.

Research and Development 2008: Essential Foundation for U.S. Competitiveness in a Global Economy. National Science Board.

Historical Trends in Federal R&D. AAAS (updated May 2014).

Alberts B (2010) Overbuilding Research Capacity. Science 329, 1257. DOI: 10.1126/science.1197077

Alberts B, Kirschner M W, Tilghman S, Varmus H (2014) Rescuing US biomedical research from its systemic flaws. PNAS 111 (16):5773-5777. DOI: 10.1073/pnas.1404402111

Augustine N R, Lane N, et al. (2014) Restoring the Foundation: The Vital Role of Research in Preserving the American Dream. American Academy of Arts and Sciences.

Diaz-Martinez, L (2014) Are Unpaid Postdocs the Next Trend in Biomedical Research? The ASCB post.

Martinson, B C (2007) Universities and the money fix. Nature 449, 141-142. DOI: 10.1038/449141a

Russo, E (2003) Victims of success. Nature 422, 354-355. DOI: 10.1038/nj6929-354a

Elizabeth Warren, Speech to Greater Boston Chamber of Commerce (2013).

(1 votes)

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Hosted in beautiful Seattle, the Society for Developmental Biology (SDB) held its 73^rd Annual Meeting on the University of Washington campus in (mostly) sunny July. Here researchers from around the world working on different developmental processes and models come together to share their results and learn about advances in the field. SDB is quite generous with their funds to support students and postdocs to attend the national meeting, and this year I benefited from this generosity. I won a presentation award at the regional SDB meeting held in my area which largely funded my trip to Seattle. Thank you, SDB!

Seattle Public Market

Kicking the meeting off was a Boot Camp for New Faculty, followed by a series of joint and concurrent sessions, workshops and symposia, and poster sessions. Early in the meeting was the Presidential Symposium featuring several invited researchers prominent in their fields, representing several developmental models. Here they discussed what genetic model organisms have taught us, using examples of research in their own fields. Paul Sternberg aptly summarized the main uses of model genetic organisms: “to identify the function of conserved genes, to assemble genes into functional pathways, and serve as a test bed for new approaches”. He also described his work using the worm as a model to study cell migration and how this model allowed him to test predictions. Ruth Lehmann added to our characterization of genetic model organisms that to study your developmental process of interest you need a good model/system and you need a good phenotype. She uses the fly to study the mechanism of mitochondrial inheritance and the role of Oskar in this process. Using Arabidopsis to study regulatory networks, Philip Benfey studies mutants with impaired root formation to understand cell specification. Next Terry Magnuson gave a fascinating history on laboratory use of mice leading into using mice to study genetics and human disease and the establishment of the collaborative cross, an effort to use genetically diverse founder strains to generate recombinant inbred strains [1]. Lastly, Wolfgang Driever talked about early development and the role of the Pou5f1/Oct4 transcriptional network using zebrafish. Such a broad overview of the advances achieved in development research made possible by using many model systems was a great way to kickoff the meeting.

Being a zebrafish neurobiologist, I mainly sought the sessions and talks pertinent to my work, and was not disappointed. David Raible chair the session on neural development, which consisted of seven different speakers covering sensory hair development in zebrafish and the programming involved in the cortex for neuronal diversity to mitochondrial transport in axons and the regulation of olfactory circuits. The symposium on Human Development and Disease, co-chaired by David Beier and Mark Majesky, had to be interesting to all, featuring talks from Alexandra Joyner, Andrew MacMahon, Ophir Klein, and Kiran Musunuru. Interspersed between these sessions were coffee breaks with delicious pastries. Scientists need their coffee, and Seattle is the place to get it.

Another session I found particularly interesting was the Awards Lectures. Here four awards, one FASEB and three SDB, were presented to five individuals followed by a short presentation from each. Kathryn Anderson was awarded the FASEB Excellence in Science Award and spoke about her work studying the importance of cilia in the mouse embryo. The Viktor Hamburger Outstanding Educator Prize was awarded to Larry Bock with the USA Science and Engineering Festival. He discussed how the festival started, the incredible amount of collaboration and participation that went with it, and the extraordinary impact it has on the young people who attended. It really makes me want to volunteer at the next event, as well as check out some of the speakers and exhibits myself! Richard Harland was awarded the Edwin G. Conklin Medal and discussed how often some of the most interesting experiments are deemed too risky for NIH funds, but are still worth doing. Finally, Janet Heasman and Christopher Wylie were awarded the Developmental Biology-SDB Lifetime Achievement Award. They described the evolution of the field of developmental biology over the years and the course their paths took along the way, intermingled with some funny stories, and the love they have for their family and work.

Each evening we meet for poster sessions and refreshments, and an opportunity to mix and mingle with fellow scientists and talk one-on-one about new data and ideas. Some of the best suggestions I’ve received have been from poster sessions. Throughout these poster sessions vendors were set up and ready to talk about their products or answer any questions. One such table was of great interest and benefit for me.  Sponsored by the FASEB Career Resources/MARC Program, Joe Tringali, Managing Director of Tringali & Associates, Inc., was on hand to provide individual resume critiques. He not only offered great advice on the organization and layout of my resume but also provided invaluable guidance on job hunting in alternative careers in science. I highly recommend that students and postdocs make use of opportunities such as these, receiving personal and professional advice is priceless. Additionally, I urge societies continue to provide opportunities for career/professional development and promote guidance and assistance of this kind. As “alternative careers” in science are fast becoming the majority, it behooves us all to provide grad students and postdocs with career development tools and guidance.

I would be remiss if I failed to mention the hilarious and fun ending to the meeting. We all gathered for a banquet and entertainment provided by Morris Maduro and Curtis Loer, two worm researchers with a knack for humor. They put together an hour show The Development Show, complete with jokes, adapted songs, video clips from the poster sessions, and short video segments. Anything that starts with a Star Wars theme, incorporates Nirvana and developmental biology (hence the “Smells like development” title), and adapts songs from Les Misérables to the lab setting has to be entertaining! See their full length show and a nice write-up from another Node blogger bere.

Though I have studied development the entirety of my graduate and postgraduate career, this is the first time I attended the national meeting, despite the fact that I am a regular attendee at the regional meetings.  I really enjoyed the superb quality of science discussed, the breadth of developmental processes presented, and the diversity of model systems used. I hope to attend more SDB meetings in the future.

1. The Collaborative Cross, a community resource for the genetic analysis of complex traits. Nat Genet, 2004. 36(11): p. 1133-1137.

(3 votes)

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This is the third of four posts relating to the Future of Research symposium which was announced in a previous blog post. Each of these posts will discuss a topic that is the focus of a workshop at the Symposium. Even if you can’t attend, please tweet @FORsymp with suggestions, or follow us to respond to our questions about what YOU, trainee scientists, think is important. The hashtag for this post on the Workforce workshop is: #FORmetrics

Rewards and incentives

What is “good science”? What is it that we want science to accomplish?

Does our current system reward “good science”, our shared goal, or are there perverse incentives that do the opposite? What are the problems and how could we reward scientists and institutions to produce the behaviors (such as collaboration, openness and honesty) that we believe support “good science”?

We all have ideas about what science is supposed to do/achieve, but these outcomes happen at a broad, communal, systems level. Meanwhile, rewards/incentives operate on individual scientists. Often, there is a disconnect between those two.

Many of the current incentives work on individuals or small groups of people (grants, jobs, fame, etc.), while many of the things we want science to do (cure disease, figure out how the world works, etc.) need to happen at a broader systems level. This may contribute to the disconnect between incentives and desired outcomes.

Intrinsic motivators may include curiosity, desire for freedom, etc.; the reasons people got into science in the first place. The extrinsic motivators are things like grant money, lab space, prestige, etc. How can we reinforce or encourage people’s own intrinsic motivations (at least the ones that lead to good science)?

The objective of the Metrics workshop is to ask: How can we fix the current system of incentives so that we reward scientists and institutions for the behaviors that we believe support “good science”?

Key areas where science “breaks”

Reproducibility and negative data
Part of the scientific endeavour is to provide checks and balances and reproduce results, or highlight when reproducibility fails. However, it is difficult to publish the results of replicating experiments or negative data and there is a worrying trend in the lack of reproducibility in some forms of analysis highlighted recently with regards to the widely-used technique of fluorescence-activated cell sorting (FACS, Hines et al., 2014). Some journals have made a call specifically looking for negative data and there are indications that the NIH may be looking to drive more studies reproducing data (Collins and Tabak, 2014) but more work on this area is key.

Publish or perish
Success in grant applications and career progression relies on publications (van Dijk et al., 2014). However this can lead to hyper-competition for “high-imapct” publications and in some recent, sad, cases, a lack of truth in publishing (Sovacoll, 2008; Nosek et al., 2012). Clearly the need to publish needs to be balanced with rigorous and honest scientific communication.

Other examples of broken systems

What can we learn from other folks who have tried to fix broken systems? For instance, the aviation industry has gone from a culture of “blame the dead pilot” to rigorous investigations of aviation accidents, which lead to improvements in the system for everyone. People like Atul Gawande in his book “Better” and Malcom Gladwell in “Outliers” have studied “positive deviants”, people who do their job much better than average in order to try to understand how we could all do better, and how we can change the system so that doing better becomes routine. Could we learn from hospitals that have used real patient involvement to improve safety and health outcomes, or from the aviation industry?

Hospitals using patient engagement to bring about real change have instituted a policy that every time a decision that will impact patients is made, a patient representative will be at the table (including who to hire, what equipment to buy, pricing issues, etc.). In science/universities, who are the stakeholders? Who should be at the table when decisions are made?

Where are the dark corners? Where do we hide our embarrassing failures? Examples could include things like replications failures or professional failures like honesty slip-ups. In the cockpit, everyone is responsible for the safety of the aircraft, and anyone who sees a problem is supposed to speak up; formerly, the all-powerful pilot was not supposed to be questioned. In medicine, whistle-blowing has improved patient outcomes by changing the culture so that everyone in the room is responsible for the outcome and it’s expected for those lower down the power curve to speak up if they see something. In science, how could we learn to talk openly about our mistakes without losing professional standing? How could we reward people for saying “I think (or know) that our paper was wrong/misleading/incomplete”?

Questions – please give us feedback!

How would we like scientists to behave, and what do we think science is supposed to achieve?

What are the current rewards and incentives, and what kind of behaviors and outcomes do they promote?

What else could we do to promote or reward the behaviors/outcomes we’d like to see?

What are the best parts of your job as a scientist? How could the system be changed so that you spend more of your time doing those things?

What prevents you from doing your science and doing it well?

How can we change the culture? How can we all agree on what the goal is?

This post has been written from input provided by the moderators of the workshop on “Metrics and Incentives in Science”.

References

Collins F. S. and Tabak L. A. Policy: NIH plans to enhance reproducibility. Nature, 2014; 505: 612-13.

Hines W. C., Su Y., Kuhn I., Polyak K. and Bissell M. J. Sorting Out the FACS: A Devil in the Details. Cell Reports, 2014; 6: 779-81.

Nosek B. A., Spies J. and Motyl M. Scientific Utopia: II – Restructuring Incentives and Practices to Promote Truth Over Publishability. Perspectives on Psychological Science, 2012.

Sovacool B. K. Exploring Scientific Misconduct: Isolated Individuals, Impure Institutions, or an Inevitable Idiom of Modern Science? Journal of Bioethical Inquiry, 2008; 5 (4): 271-82.

van Dijk D., Manor O. and Carey L. B. Publication metrics and success on the academic job market. Current Biology, 2014; 24 (11) R516–R517. PI Predictor

(2 votes)

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This is the second of four posts relating to the Future of Research symposium which was announced in a previous blog post. Each of these posts will discuss a topic that is the focus of a workshop at the Symposium. Even if you can’t attend, please tweet @FORsymp with suggestions, or follow us to respond to our questions about what YOU, trainee scientists, think is important. The hashtag for this post on the Workforce workshop is: #FORworkforce

Where do postdocs go?

There has been a tremendous shift in the job market for PhDs/post-docs over the past decades. The only job that PhDs/post-docs are trained for (academic PI positions) are precipitously dwindling. Under such conditions, how do we match the changing job market demand with the supply of rightly trained PhDs/post-docs?

There are high numbers of graduate trainees and postdoctoral researchers in the current academic research system (Alberts et al., 2014). There are now slowdowns, or even contractions, in the ability of academia, the government and industry to take on this excess number of postdocs. The goal of this workshop will be to figure out what the best ways of adapting the system to best reduce the postdoc pool (Bourne, 2013).

As discussed in a prior post, the assumption is that everyone who goes into academia wants to end up an academic. Expectations have been shown to change over time as a trainee progresses, in spite of strong encouragement from advisor, who actively discourage other career paths (Sauermann and Roach, 2012). And the jobs people are actually getting show that, actually, academia is one of the “alternative” careers, and not the default. So the workforce becomes filled with more trainees than are needed to replace current academics.

What is the cause of this mismatch?

The doubling of NIH budget in 1990s made provision for a huge influx of money – particularly soft money which the academic institutions used up for massive expansion (of a large number of PhDs, post-docs, etc.) without taking into consideration the long term effects of this one-time influx. The result is over the past decade, in conjunction with the economic crisis and sequestration, the NIH budget has contracted by 20 %, essentially leaving the trainees high and dry without good job prospects for the (academic) jobs that they were trained for.

What is the current demand on the workforce encompassing the grad students and post-docs?

Although almost all PhDs and post-docs are trained, or directed, to become PIs in academia, the current reality is that these academic jobs account for less than 15 % of the job market. Due to The Great Recession, jobs in industry are also in a downward flux. However, there are many new job opportunities that are opening up in fields that initially were considered alternative careers and looked down upon. These include: consulting for life sciences and pharmaceutical industries; sales; marketing and field specialists of high tech and technologically advanced products; science policy; communications; patent law and intellectual property; and many more.

There is a perception that there is actually a shortage of Science, Technology, Engineering and Math (STEM) graduates in the United States. However a recent report by the Center for Immigration Studies using US Census data (Camarota and Ziegler, 2014) is one of a chorus of recent publications suggesting that this is in fact not the case, and that STEM graduates are actually struggling to get jobs. Are we producing too many STEM graduate or too few? Bizarrely, the answer may be “both”, as recently discussed, and that we simply have too many graduates, who are trained for the wrong careers.

Questions – please give us feedback!

How did we get to this situation and what is perpetuating the problem?

What are possible ways of changing the structure of the workforce to relieve the pressure?

This post has been written from input provided by the moderators of the workshop on the “Structure of the Workforce”.

References

Alberts B, Kirschner M W, Tilghman S, Varmus H (2014) Rescuing US biomedical research from its systemic flaws. PNAS 111 (16):5773-5777. DOI: 10.1073/pnas.1404402111

Bourne H, (2013) Point of view: A fair deal for PhD students and postdocs. eLife 2:e01139. DOI: 10.7554/eLife.01139#sthash.rQShvUou.dpuf

Camarota S A, Ziegler K (2014) Is There a STEM Worker Shortage? A look at employment and wages in science, technology, engineering, and math. Center for Immigration Studies Report.

Sauermann H, Roach M (2012) Science PhD Career Preferences: Levels, Changes, and Advisor Encouragement. PLoS ONE 7(5): e36307. doi:10.1371/journal.pone.0036307

(3 votes)

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