First use of bioRxiv: Reconstructing Promoter Activity From Lux Bioluminescent Reporters

Today I have made a new publication foray and submitted a manuscript to bioRxiv. This is the main paper to have come out of work on our BBSRC Lux grant. We are yet to find a peer-review home – but one of our co-authors has already had a conversation with someone who wants to use the method – so it was time to put the manuscript out there while we continue with the peer-review process. R code and Biomodels submission will follow. The manuscript details are:

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Authorship networks as an alternative to authorship lists

I am starting to think about different barriers to multidisciplinary research. One of the barriers is the traditional list of authors on journal research articles. The problem is that one has a linear list – and as a consequence the position on that list becomes hierarchical. Typically in our field, that means that being the first or final author on the list is over-valued, while other authorship locations are less valued. This then has an impact on jobs, promotions, etc.

Where research is genuinely multidisciplinary, this then becomes very problematic. Journals have tried to respond to this in various ways, including having joint first (or last) authorships and lists of author contributions (usually an afterthought at the end of the paper).

I propose here a radical alternative to an author list: an authorship network. This would replace the list of authors with a network (or graph) showing how the people have contributed to the work. Nodes on the graph could represent people, activities or grant codes. Edges could connect people to activities, people to grants (either as authors of the grant, or employed by the grant), people to each other (e.g. supervision relationships).

I have had a go at representing my most complex paper in this way. Here it is. Rectangular nodes are the authors. Rounded rectangles are the grants. Ovals are activities. Arrows between people link who is supervised by whom. Edges between people and grants represent grant authorship (blue) or employment (arrows). Edges from people to activities show who has done what, with thicker edges for the main contributors (i.e. Hiroki doing most of the modelling and Taku doing most of the experiments).

takahashi_et_alCompare the graph with the list of authors:

Hiroki Takahashi, Taku Oshima, Jon L. Hobman, Neil Doherty, Selina R. Clayton, Mudassar Iqbal, Philip J. Hill, Toru Tobe, Naotake Ogasawara, Shigehiko Kanaya, Dov J. Stekel.
I think the graph is far more informative. It is immediately clear that there are two main activities in experiments and modelling. It is clear that the BBSRC/JST is the central grant, while there is a contribution from the other BBSRC grant. Jon Hobman’s centrality to the research is also much clearer from the graphical view than appears from his position as third author on the list.
I’d appreciate some feedback and ideas.

 

New publication: The dynamic balance of import and export of zinc in Escherichia coli suggests a heterogeneous population response to stress

I am absolutely delighted to see the (online) publication today of our paper:

Takahashi H, Oshima T, Hobman JL, Doherty N, Clayton SR, Iqbal M, Hill PJ, Tobe T, Ogasawara N, Kanaya S and Stekel DJ 2015. The dynamic balance of import and export of zinc in Escherichia coli suggests a heterogeneous population response to stress. Journal of the Royal Society Interface DOI: .

The abstract is at the bottom of the post. First I want to say why I am so happy about this particular paper.

1. This is the first piece of work I have published in which I have made a successful funding application (I say “I” loosely, as Taku Oshima wrote the Japanese part of the bid along with Naotake Ogasawara, Shigehiko Kanaya and Toru Tobe, and Jon Hobman wrote much of the UK part of the bid; however, I was PI as this was a Systems Biology call); led the research (most of the hard work was done by Hiroki Takahashi and Taku Oshima); wrote the paper (different parts were written by different people – almost all authors made an important contribution); and have seen the paper published. A complete cycle of more than 5 years from grant application to publication.

2. This is the first paper on which I am corresponding author that contains new experimental results. More than that, I played an important role in devising many of the experiments (time courses and viable cell count assays) – not in terms of technical details (in which I have little expertise) but in terms of what experiments we need and why we need to do them.

3. This is the first time I have come a complete “Systems Biology” cycle: from experiments, to models, to predictions, to experimental confirmation, to a new model and then new predictions.

4. Some of the most important ideas in this paper came as a result of one of the most enjoyable weeks in my scientific career. Hiroki, Jon, Selina and I were all attending the Biometals Conference in Brussels in July 2012. While Hiroki and I attended a few sessions of the conference, most of the time we spent in our hotel lobby trying to get the model to fit the data. The first data we had were the LB data, which the model could fit without too much trouble. When Taku asked me what other data we needed, I said: “time series, with different concentrations of zinc”, and by the conference we had those data too. Only one problem: the model no longer fitted the data.

Hiroki and I spent that week trying to work out how to get the model to work. Each morning, we sat in the hotel lobby, and over endless cups of tea, we devised new versions of the model; each afternoon Hiroki would code them up, and then run them overnight on the supercomputer in Japan. And the next morning, the model would still not fit the data. By the last day we were tearing our hair out: nothing we could think of would work. We had one last (desperate) idea: ditch the 100uM zinc data. Boom! The model fitted the 12.5uM zinc data just fine! And this led to the heterogeneity hypothesis, the viable cell count assay, the stochastic model, and all the results that make this paper exciting. It is that kind of week that we go into careers in science for: the frustration and delight of grappling with and overcoming a difficult problem.

5. As alluded to in the previous points, it has been an absolute delight working with my coauthors on this paper, and I have many happy memories in the UK, Japan and Brussels.

6. Finally, on a more personal note: we received this funding on 17th March 2010. In between receiving the funding and having the paper published (5 years later) I have got married (July 2010), had a baby (July 2011), had another baby (November 2013) and am now more tired yet more happy than at any other point in my life 🙂

Now for the abstract!

Abstract

Zinc is essential for life, but toxic in excess. Thus all cells must control their internal zinc concentration. We used a systems approach, alternating rounds of experiments and models, to further elucidate the zinc control systems in Escherichia coli. We measured the response to zinc of the main specific zinc import and export systems in the wild-type, and a series of deletion mutant strains. We interpreted these data with a detailed mathematical model and Bayesian model fitting routines. There are three key findings: first, that alternate, non-inducible importers and exporters are important. Second, that an internal zinc reservoir is essential for maintaining the internal zinc concentration. Third, our data fitting led us to propose that the cells mount a heterogeneous response to zinc: some respond effectively, while others die or stop growing. In a further round of experiments, we demonstrated lower viable cell counts in the mutant strain tested exposed to excess zinc, consistent with this hypothesis. A stochastic model simulation demonstrated considerable fluctuations in the cellular levels of the ZntA exporter protein, reinforcing this proposal. We hypothesize that maintaining population heterogeneity could be a bet-hedging response allowing a population of cells to survive in varied and fluctuating environments.

New publication: AtMYB93 is a novel negative regulator of lateral root development in Arabidopsis

Thanks to Juliet Coates, we have a new publication:

Gibbs, D. J., Voß, U., Harding, S. A., Fannon, J., Moody, L. A., Yamada, E., Swarup, K., Nibau, C., Bassel, G. W., Choudhary, A., Lavenus, J., Bradshaw, S. J., Stekel, D. J., Bennett, M. J. and Coates, J. C. 2014. AtMYB93 is a novel negative regulator of lateral root development in Arabidopsis. New Phytologist. doi: 10.1111/nph.12879.

Summary

  • Plant root system plasticity is critical for survival in changing environmental conditions. One important aspect of root architecture is lateral root development, a complex process regulated by hormone, environmental and protein signalling pathways.
  • Here we show, using molecular genetic approaches, that the MYB transcription factor AtMYB93 is a novel negative regulator of lateral root development in Arabidopsis.
  • We identify AtMYB93 as an interaction partner of the lateral-root-promoting ARABIDILLO proteins. Atmyb93 mutants have faster lateral root developmental progression and enhanced lateral root densities, while AtMYB93-overexpressing lines display the opposite phenotype. AtMYB93 is expressed strongly, specifically and transiently in the endodermal cells overlying early lateral root primordia and is additionally induced by auxin in the basal meristem of the primary root. Furthermore, Atmyb93 mutant lateral root development is insensitive to auxin, indicating that AtMYB93 is required for normal auxin responses during lateral root development.
  • We propose that AtMYB93 is part of a novel auxin-induced negative feedback loop stimulated in a select few endodermal cells early during lateral root development, ensuring that lateral roots only develop when absolutely required. Putative AtMYB93 homologues are detected throughout flowering plants and represent promising targets for manipulating root systems in diverse crop species.

And it has even made BBSRC headlines.

To be fair, most credit goes to Juliet and to Dan Gibbs, who have been working on this project for many years. My contribution is fairly minor: I am responsible for the p-values in the manuscript! One of the referees was unhappy that some of the claims lacked statistical backing (which is fair enough – I would have made the same point as a referee) so I ran some likelihood ratio tests with simulated data in order to ensure that all claims had statistical backing. I’m really pleased for Juliet and Dan, because I know how much they have put into this paper.

 

New Publication: Adaptation for Protein Synthesis Efficiency in a Naturally Occurring Self-Regulating Operon

Dorota’s second paper has just been published in PLoS ONE as:

Herman, D., Thomas, C.M. and Stekel, D.J. 2012. Adaptation for Protein Synthesis Efficiency in a Naturally Occurring Self-Regulating Operon. PLoS ONE 7(11): e49678.

We are particularly pleased with this work, and had some very nice comments from the reviewers. The quotes (from two different reviewers) here are reproduced with permission from PLoS ONE:

“the kinds of questions the authors address appear to be the most rewarding uses of computational/mathematical uses in biology”

“I found this paper important because it investigates a system with biological plausible parameters, thus, revealing whether the results of previous purely theoretical studies are biologically plausible.”

We are hoping for that sort of reception more generally in the community!

The abstract of the paper is:

The korAB operon in RK2 plasmids is a beautiful natural example of a negatively and cooperatively self-regulating operon. It has been particularly well characterized both experimentally and with mathematical models. We have carried out a detailed investigation of the role of the regulatory mechanism using a biologically grounded mechanistic multi-scale stochastic model that includes plasmid gene regulation and replication in the context of host growth and cell division. We use the model to compare four hypotheses for the action of the regulatory mechanism: increased robustness to extrinsic factors, decreased protein fluctuations, faster response-time of the operon and reduced host burden through improved efficiency of protein production. We find that the strongest impact of all elements of the regulatory architecture is on improving the efficiency of protein synthesis by reduction in the number of mRNA molecules needed to be produced, leading to a greater than ten-fold reduction in host energy required to express these plasmid proteins. A smaller but still significant role is seen for speeding response times, but this is not materially improved by the cooperativity. The self-regulating mechanisms have the least impact on protein fluctuations and robustness. While reduction of host burden is evident in a plasmid context, negative self-regulation is a widely seen motif for chromosomal genes. We propose that an important evolutionary driver for negatively self-regulated genes is to improve the efficiency of protein synthesis.

New publication – Springer book chapter

I received today from John Herbert the pdf of our newly published book chapter:

Herbert, J.M.J., Stekel, D.J., Mura, M., Sychev, M. and Bicknell, R. 2011. Bioinformatic methods for finding differentially expressed genes in cDNA libraries, applied to the identification of tumour vascular targets. In Lu, C. et al., cDNA libraries: Methods and Applications, Methods in Molecular Biology 729. Springer.

The abstract of the chapter is:

The aim of this method is to guide a bench scientist to maximise cDNA library analyses to predict biologically relevant genes to pursue in the laboratory. Many groups have successfully utilised cDNA libraries to discover novel and/or differentially expressed genes in pathologies of interest. This is despite the high cost of cDNA library production using the Sanger method of sequencing, which produces modest numbers of expressed sequences compared to the total transcriptome. Both public and propriety cDNA libraries can be utilised in this way, and combining biologically relevant data can reveal biologically interesting genes. Pivotal to the quality of target identification are the selection of biologically relevant libraries, the accuracy of Expressed Sequence Tag to gene assignment, and the statistics used. The key steps, methods, and tools used to this end will be described using vascular targeting as an example. With the advent of next-generation sequencing, these or similar methods can be applied to find novel genes with this new source of data.