Bacterial Doubling Times in the Wild

How fast do bacteria grow outside the laboratory? This simple question is very difficult to address directly, because it is near-impossible to track a lineage of bacterial cells, ancestor-to-decendant, inside an infected patient or through a river. Now in new work published in Proceedings B, Beth Gibson, Ed Feil, Adam Eyre-Walker and I exploit genome sequencing to try to get a handle on the problem indirectly.

We have done it by comparing two known quantities and taking the ratio: the rate at which DNA mutates in bacteria per year, and the rate it mutates per replication. This tells us in theory how many replications there are per year.

The mutation rate per replication has long been studied in the laboratory, and is around once per billion letters. Meanwhile, the recent avalanche of genomic data has allowed microbiologists to quantify the rate at which bacteria evolve over short time scales such as a year, including during outbreaks and even within individual infected patients. Most bugs mutate about once per million letters per year, with ten-fold variation above and below this not uncommon among different species.

For five species both these quantities exist. The fastest bug we looked at causes cholera and we estimate it doubles once every hour on average (give or take 30 minutes). The slowest was Salmonella, which we estimate doubles once a day on average (give or take 8 hours). In between were Staph. aureus and Pseudomonas at about two hours each, and E. coli at 15 hours. These are average over the very diverse and often hostile conditions that a bacterial cell may find itself in during the course of its natural lifecycle. To find out more about the work, please check out the paper.

PhD Studentship: Genomic prediction of antimicrobial resistance spread

This position is now closed
An opportunity has arisen for a D.Phil. (Ph.D.) place on the BBSRC-funded Oxford Interdisciplinary Bioscience Doctoral Training Partnership in the area of Artificial Intelligence, specifically Predicting the spread of antimicrobial resistance from genomics using machine learning.

If successful in a competitive application process, the candidate will join a cohort of students enrolled in the DTP’s one-year interdisciplinary training programme, before commencing the research project and joining my research group at the Big Data Institute.

This project addresses the BBSRC priority area “Combatting antimicrobial resistance” by using ML to predict the spread of antimicrobial resistance in human, animal and environmental bacteria exemplified by Escherichia coli. Understanding how quickly antimicrobial resistance (AMR) will spread helps plan effective prevention, improved biosecurity, and strategic investment into new measures. We will develop ML tools for large genomic datasets to predict the future spread of AMR in humans, animals and the environment. The project will create new methods based on award-winning probabilistic ML tools pioneered in my group (BASTA, SCOTTI) by training models using genomic and epidemiological data informative about past spread of AMR. We will apply the tools collaboratively to genomic studies of E. coli in Kenya, the UK and across Europe from humans, animals and the environment, Enterobacteriaceae in North-West England, and Campylobacter in Wales. Genomics has proven effective for asking “what went wrong” in the context of outbreak investigation and AMR spread; here we will address the greater challenge of repurposing such information using ML for forward prediction of future spread of AMR. Scrutiny will be intense because future predictions can and will be tested, raising the bar for the biological realism required while producing computationally efficient tools.

Attributes of suitable applicants: Understanding of genomics. Interest in infectious disease. Some numeracy, e.g. mathematics A-level, desirable. Experience of coding would help.

Funding notes: BBSRC eligibility criteria for studentship funding applies (https://www.ukri.org/files/legacy/news/training-grants-january-2018-pdf/). Successful students will receive a stipend of no less than the standard RCUK stipend rate, currently set at £14,777 per year.

How to apply: send me a CV and brief covering letter/email (no more than 1 page) explaining why you are interested and suitable by the Wednesday 11 July initial deadline. I will invite the best applicant/s to submit with me a formal application in time for the Friday 13 July second-stage deadline.

Royal Society Summer Science Exhibition Stall July 2-8

Next week researchers from the Modernising Medical Microbiology consortium, collaborating groups and I will exhibit the Resistance is Futile stall at the Royal Society Summer Science Exhibition. The exhibition is a free event in central London open to all visitors. Our stall is an opportunity to tell visitors about our research, and how advances in genetics are influencing day-to-day life. On show at the Resistance is Futile stall:

Oxford Nanopore Technology Demos

DNA sequencing in the NHS is shortening the time to diagnose antibiotic resistance in serious infections

Evolution Dance Mat

Resistance mutants arise spontaneously through chance copying errors during DNA replication

Antibiotic Resistance Coconut Shy

Antibiotic use gives resistance mutants a strong advantage so they rapidly increase in frequency.

The exhibition runs from Monday 2 July - Sunday 8 July at Carlton House Terrace, London, SW1Y 5AG. For more information about our stall click here and for general visitor information about the exhibition click here. Please spread the word!

During the exhibition we will be tweeting from @ResistanceIF

Our stall is generously supported by Oxford Nanopore Technology, the Nuffield Department of Medicine, and through public engagement research funding awarded to our research groups by the Wellcome Trust, the Royal Society, the National Institute for Health Research, the Oxford Biomedical Research Centre, the Natural Environment Research Council, the Medical Research Council, the Newton Fund and the Bill & Melinda Gates Foundation.

Postdoc positions in Data Science and Molecular Microbiology

These positions are now closed
As part of the move to the Big Data Institute, two new postdoctoral positions funded by the Robertson Foundation are available in Data Science and Molecular Microbiology.

The BDI is a new interdisciplinary research centre aiming to develop, evaluate and deploy efficient methods for acquiring and analysing biomedical data at scale and for exploiting the opportunities arising from such studies. The BDI is a joint venture between the renowned Nuffield Department of Population Health (NDPH) and NDM.

The Data Scientist role, split between the BDI and London, will be part of a team developing systems for continuous record linkage between Public Health England and other population health records. The aims are to design record linkage algorithms, manage front ends for viewing the data source, and analyse and interpret results. We're looking for a graduate or equivalent experience in computer science, data science, statistics, or any other relevant subject with a strong quantitative component. Knowledge of databases like SQL and computer programming are needed.

The Molecular Microbiology role, based mainly at the John Radcliffe Hospital Microbiology Department, will be part of a team researching Staphylococcus aureus infection using RNA sequencing, genome wide association studies, and biochemical and immunological assays of bacterial behaviour. The aims include designing microbiological protocols, researching bacterial molecular genetics and data analysis. We're looking for a PhD or equivalent experience in a relevant subject such as microbiology, immunology, genetics or biochemistry. Experience designing protocols and basic microbiological and immunological skills are required.

The deadline for the posts is Noon on 6 June 2018. Both are one year positions. For more details or to apply click here for the Data Scientist role and here for the Molecular Microbiologist role.

The group has moved to the Big Data Institute, University of Oxford

From April we have moved to the Big Data Institute, Nuffield Department of Population Health at the University of Oxford. The group is maintaining its close links to the Modernising Medical Microbiology Consortium and the John Radcliffe Hospital, Oxford. I am grateful to the Robertson Foundation for funding. We're excited about joining new colleagues and benefiting from their expertise in epidemiology, health informatics, genetics and infection, while continuing to cultivate strong links with our existing collaborators in Oxford and around the world.