Welcome to Michelle Baker and Henry Todman

We are delighted to welcome two new lab members this month, Michelle Baker and Henry Todman. Both Michelle and Henry are joint appointments with the School of Mathematics, co-supervised with Theo Kypraios.

Michelle has rejoined our lab, following a post-doc with Jamie Twycross and Liz Sockett. Michelle’s previous stint with us was very productive, leading to our first AMR slurry modelling paper, which I am sure contributed to our grant success. Michelle will be with us for two years. Michelle writes:

I am a post-doctoral researcher in the field of mathematical biology, and am particularly interested in the study of bacteria and antibiotic resistance. I work in the EVAL-FARMS project using mathematical modelling to investigate the risk of emergence of antibiotic resistance from agricultural slurries. This interdisciplinary project allows me to work alongside experts from a wide range of disciplines to tackle the problem in an integrated way and to produce high quality research.

I completed my PhD in Mathematics here at the University of Nottingham, focussed on cytokine dynamics in arthritic disease. After completing my PhD I took up a research position supervised by Prof Liz Sockett and Dr Jamie Twycross, investigating the potential of predatory bacteria to be used as ‘living antibiotics’.

Henry Todman has joined us as a four year PhD student associated with the EVAL-FARMS project. Henry writes:

I am a mathematical modelling PhD student working with Dov, Theo Kypraios and Michelle Baker. My PhD research will primarily look at developing new mathematical models to assess the risks of bacterial population carrying antimicrobial resistance genes and fitting these models to experimental data produced from the EVAL-FARMS project. 

Prior to beginning my PhD, I studied Mathematics at the University of Warwick for my undergraduate degree, and also completed an MSc in Mathematical Medicine and Biology at the University of Nottingham. Over the course of my MSc I was exposed to a wide range of current research topics in mathematical biology, however, it was antimicrobial resistance that immediately captured my interest. This led me to complete my dissertation on the phage-mediated spread of AMR, and I am now eager to pursue this topic even further in my PhD.

Outside of work, I am a keen climber and you will often find me hanging off some rock in the Peak District, or taking part in bouldering competitions around the country.

 

New Publication: Reconstructing promoter activity from Lux bioluminescent reporters

Absolutely delighted to report that our paper has been published:

Iqbal M, Doherty N, Page AML, Qazi SNA, Ajmera I,  Lund PA, Kyraios T, Scott DJ, Hill PJ and Stekel DJ (2017) Reconstructing promoter activity from Lux bioluminescent reporters. PLOS Computational Biology 13(9): e1005731. https://doi.org/10.1371/journal.pcbi.1005731.

Abstract

The bacterial Lux system is used as a gene expression reporter. It is fast, sensitive and non-destructive, enabling high frequency measurements. Originally developed for bacterial cells, it has also been adapted for eukaryotic cells, and can be used for whole cell biosensors, or in real time with live animals without the need for euthanasia. However, correct interpretation of bioluminescent data is limited: the bioluminescence is different from gene expression because of nonlinear molecular and enzyme dynamics of the Lux system. We have developed a computational approach that, for the first time, allows users of Lux assays to infer gene transcription levels from the light output. This approach is based upon a new mathematical model for Lux activity, that includes the actions of LuxAB, LuxEC and Fre, with improved mechanisms for all reactions, as well as synthesis and turn-over of Lux proteins. The model is calibrated with new experimental data for the LuxAB and Fre reactions from Photorhabdus luminescens—the source of modern Lux reporters—while literature data has been used for LuxEC. Importantly, the data show clear evidence for previously unreported product inhibition for the LuxAB reaction. Model simulations show that predicted bioluminescent profiles can be very different from changes in gene expression, with transient peaks of light output, very similar to light output seen in some experimental data sets. By incorporating the calibrated model into a Bayesian inference scheme, we can reverse engineer promoter activity from the bioluminescence. We show examples where a decrease in bioluminescence would be better interpreted as a switching off of the promoter, or where an increase in bioluminescence would be better interpreted as a longer period of gene expression. This approach could benefit all users of Lux technology.

Author summary

Bioluminescent reporters are used in many areas of biology as fast, sensitive and non-destructive measures of gene expression. They have been developed for bacteria, adapted now for other kinds of organisms, and recently been used for whole cell biosensors, and for real-time live animal models for infection without the need for euthanasia. However, users of Lux technologies rely on the light output being similar to the gene expression they wish to measure. We show that this is not the case. Rather, there is a nonlinear relationship between the two: light output can be misleading and so limits the way that such data can be interpreted. We have developed a new computational method that, for the first time, allows users of Lux reporters to infer accurate gene transcription levels from bioluminescent data. We show examples where a small decrease in light would be better interpreted as promoter being switched off, or where an increase in light would be better interpreted as promoter activity for a longer time.

 

Thanks to all my brilliant collaborators and coauthors. Thanks also to the lovely referees (one of whom signed their review) who said of the article: “an extremely important contribution to the field” (Reviewer 1) and “a significant advance” (Reviewer 2) and  provided helpful and constructive feedback.

 

 

New publication: microbial mass movements

Delighted that our perspective in Science has been published.

Zhu Y-G, Gillings M, Simonet P, Stekel DJ, Banwart S and Penuelas J. Microbial mass movements. Science 357: 1099-1100.

My involvement is relatively minor: we have written a much longer piece (which we are looking to publish also) to which I have contributed a fairly substantial section on modelling – and then when Michael Gillings put together this short perspective for Science, he compressed everything I wrote into a single sentence! Maybe it is an improvement 🙂 Anyway, it is a real privelege to have coauthored which such amazing international scientists, and a delight that we have had it published in such a great journal.

Summary

For several billion years, microorganisms and the genes they carry have mainly been moved by physical forces such as air and water currents. These forces generated biogeographic patterns for microorganisms that are similar to those of animals and plants (1). In the past 100 years, humans have changed these dynamics by transporting large numbers of cells to new locations through waste disposal, tourism, and global transport and by modifying selection pressures at those locations. As a consequence, we are in the midst of a substantial alteration to microbial biogeography. This has the potential to change ecosystem services and biogeochemistry in unpredictable ways.

Medical Research Foundation funds £2.8M PhD programme in antimicrobial resistance

The Medical Research Foundation has announced a £2.8M PhD programme in antimicrobial resistance. Led by Matthew Avison at Bristol, this will bring 18 fully funded PhD students to support ongoing AMR projects. One of the students will be at Nottingham in association with the EVAL-FARMS project. We will be advertising three projects as part of the programme; these will be led by team members who don’t have any direct resource from the existing EVAL-FARMS funding – and are likely to be in the areas of phage-mediated spread of resistance, use of anaerobic digestion to mitigate resistance, and farm systems economic models to identify factors to best mitigate the impact of agri-AMR on human health.

Nottingham has also posted a Blog on the funding and I reproduce the text below:

New funding for Antimicrobial Resistance research

Research into new ways to tackle antimicrobial resistance has been given a boost as the University of Nottingham is one of the universities set to benefit from a £2.85m investment from the Medical Research Foundation.

New scientists will explore ways to tackle antimicrobial resistance through a new PhD training programme by the Medical Research Foundation, the charitable foundation of the Medical Research Council (MRC).

Fully funded

The first intake of the Antimicrobial Resistance PhD Training Programme will fully fund 18 students for four years, and the University of Nottingham is one of the 16 participating universities across the UK.

Dr Dov Stekel is leading the University of Nottingham programme and will be looking to recruit students later this year ready to start in 2018. Dr Stekel says: “This funding allows us to broaden our research with a PhD student working with team members who have not yet had access to resources from our other antimicrobial resistance research grants. Antimicrobial Resistance is a major global challenge and it will be very exciting to see the type of projects that are put forward and how they will help us progress our understanding of this problem.”

Antibiotics transformed healthcare in the 20th Century and are considered one of the greatest medical achievements of the era. Today, we still rely on antibiotics to treat everything from minor cuts to life-threatening bacterial infections, and to prevent infection after surgery. These drugs have drastically improved our quality of life and increased our lifespan.

Global threat

In the 21st Century, antibiotic overuse and misuse has led to antibiotics rapidly becoming ineffective. Antimicrobial resistance, specifically antibiotic resistance, now poses a global threat to human life. We need urgent action to halt resistance and to speed up new treatments for bacterial infection. The Medical Research Foundations PhD Training Programme in AMR has been designed in response.

Working with the MRC, the Medical Research Foundation spotted a gap in funding for PhD studentships in this field of research – currently there are few emerging researchers trained in the multidisciplinary approach required to tackle the antimicrobial resistance problem. The programme is designed to help build a strong, active network of new researchers to approach this global challenge in innovative ways.

The Medical Research Foundation’s Chair, Professor Nicholas Lemoine, said: “The Medical Research Foundation is delighted to be funding the UK’s only national PhD Training Programme in antimicrobial resistance research.  We believe this will help to strengthen the UK’s research capacity to respond to the global health challenge of antimicrobial resistance, including antibiotic resistance and drug-resistant infections.”

The Medical Research Foundation is continuing to seek funds from its supporters and other sources to fund two further cohorts of PhD students in antimicrobial resistance in the future.

 

Sankalp Arya will be speaking at EDAR 4

Sankalp is on a roll! More good news. His Abstract to the 4th International Symposium on the Environmental Dimension of Antibiotic Resistance has been accepted as an oral presentation. He’ll be giving a talk with title “Comparison of Different Modelling Approaches for Plasmid Transfer Dynamics” during Session 7 on Thursday 17th August. We have some interesting phage model results too so it is possible he may talk about both plasmid and phage mediated transfer.

When we submitted the abstract there was a “modelling” stream to submit to (which we dutifully did) – interestingly there is no modelling stream at the conference. There appear to be some bioinformatics talks, but it looks like Sankalp’s will be the only modelling talk. I am a bit surprised by this – there is a very clear need for models to be able to quantify spread of AMR, and make predictions about interventions. Perhaps on the other hand this is an opportunity for collaborations – we do modelling!