A computational framework to design robust and stable microbiome

   Department of Bioengineering

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  Dr R Tanaka, Dr Peter Graystock  No more applications being accepted  Funded PhD Project (UK Students Only)

About the Project

Agriculture and global food security rely on pollinators (e.g. bees) but pollinators are in decline worldwide. One of the main causes of their decline is their exposure to harmful chemicals such as pesticides and heavy metals. This project aims to tackle such a major global challenge of pollinator decline and food security by taking an interdisciplinary approach to understand holobionts, how they are impacted by anthropogenic environmental perturbations, and how we can manipulate organisms to rescue threatened species. Focusing on bumblebees as an example of a declining pollinator, we will investigate how their gut microbiome is disrupted by pesticides, which decreases their lifespan, and how we can make their gut microbiome more robust and stable against pesticides. The PhD student will develop a computational framework to address these questions systematically, building on our expertise in mathematical/computational modelling of microbiomes (Tanaka) and experimental studies of pollinators (Graystock). A healthy gut microbiome is considered to be crucial for the survival of bees, particularly when exposed to stressors. Bees come in contact with chemical stressors such as pesticides when foraging on treated crops and exposed flowers, and the pesticides can accumulate in the bee and their hive materials to much greater concentrations. Their gut microbiome harbours diverse microbial strains and some may help make the bee resilient to the pesticides, for instance by influencing the bees’ tolerance to toxicants via toxicant metabolism, immune system stimulation, and protecting against pathogens. The Graystock group has already collected preliminary data of gut microbiome from bumblebees which survived repeated exposure to pesticides. In this project, we will develop an in silico framework and use data on the composition of the gut microbiome to model and simulate microbiome dynamics and systematically investigate the following questions.

  • What makes the microbiome of bees that survived repeated pesticide treatment different from the microbiome of those that did not, in terms of microbiome diversity, richness, interactions, etc?
  • Is the evolved gut microbiome of the resilient bees stable? Is there one stable state or many?
  • Can we identify ‘weak spots’ that would ‘weaken’ the microbiome of resilient bees?
  • Can we find probiotic strategies that will modify and shape the gut microbiome of any bumblebee to make them more robust and stable against pesticides? For example, by transplant of single- or multi-species to change microbiome steady states, or pathogen competitive exclusion?
  • Is the chronological assembly of the bees’ gut microbiome important to reach a microbiome that makes the bees resilient to the pesticide? The computational frameworks developed in this project will help design a microbial tool kit to protect pollinators from exposure to pesticides.

The student would join the Leverhulme Centre for the Holobiont (www.imperial.ac.uk/holobiont/), a multi-institutional research centre devoted to understanding interactions between multicellular hosts and their microbial symbionts.

Informal enquiries are welcomed and should be sent to Prof Reiko Tanaka ([Email Address Removed])

How to apply:

Please email Prof Reiko Tanaka ([Email Address Removed]) and include in your application:

  • Statement of Purpose
  • Your CV
  • At least two references to be sent directly to Reiko Tanaka from the referees.

Full applications made before 15th January will be considered at any time.

Funding and eligibility:

A fully funded 4 years Leverhulme Studentship, including tuition fees and a standard research council stipend. The fees and stipend cover UK home applicants and standard research council eligibility criteria apply:


The successful applicant must hold, or be expected to complete, an Msc or MRes with merit/distinction in a relevant subject area (Applied Mathematics, Computational Systems Biology)

Biological Sciences (4) Computer Science (8) Mathematics (25)

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 About the Project