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  Competition and cooperation relationships within human microbial communities.


   School of Life Sciences

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  Dr Fiona Whelan, Dr K Hardie  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

Typical studies of the human microbiome identify dysbiosis by sampling from healthy individuals, comparing them to individuals with a particular disease state, and reporting changes in the presence and/or abundance of bacterial species. Although this type of methodology has greatly enhanced our understanding of how overall changes to one’s microbiome can contribute to disease (e.g., ulcerative colitis, asthma, certain cancers), it does not provide us with a mechanistic understanding of how bacterial species, strains, and the intricate interactions between them are affected by and drive disease states within these complex communities. Without this fine-tuned level of understanding, it remains difficult to successfully treat microbiome-related disease states with directed interventions such as probiotics, antimicrobials, or targeted bacterial products. In order to mitigate disease and promote human health, we need a better understanding of how bacterial species and strains interact with each other within these complex communities.

Large-scale, comparative analyses of human microbiome samples is now feasible largely in part to improvements in sequencing technologies and advancements in bioinformatic software. In this project, the student will combine cutting-edge bioinformatic approaches and data analyses with traditional microbiology techniques to investigate species-species interactions within human microbial communities. Specifically, we will ask whether a certain species is more likely to persist in a microbial community if another species is also present (i.e., do pairs of species significantly co-occur across samples). The interactions between these species pairs will be assessed in vitro and their importance towards maintaining a healthy ecosystem interrogated. The precise focus of the project, and allocation between in silico and in vitro methods will be determined in consultation with the student but will be based upon the following aims:

1.      Data mining of public databases. We will identify statistically significant species-species co-occurrence patterns in human microbiome samples. Using previously published software, we will interrogate thousands of publicly available samples from various consortia (e.g., the Human Microbiome Project (HMP)) in order to ask whether certain bacteria are statistically more likely to be present in the presence of other species.

2.      Verification of results in vitro. We will choose a subset of the species-species co-occurrence pairs identified in Aim 1 to investigate in vitro. In the lab, we will assess whether each of these pairs act co-operatively to, for example, promote each other’s growth, metabolism, or virulence. This work will be followed up using an in vivo Drosophila infection model.

 This project will provide the student with a unique combination of bioinformatic and microbiology skills, which will be widely transferable to other areas of biological research. Further, the project can easily be shaped by the student’s interests to focus more heavily on either the computational or laboratory-based aspects of the research.

Biological Sciences (4)

References

Whelan FJ, Hall RJ, McInerney JO. Evidence for selection in the abundant accessory gene content of a prokaryote pangenome. Molecular Biology and Evolution. 2021. doi: 10.1093/molbev/msab139.
Whelan FJ, Waddell B, Syed SA†, Shekarriz S, Rabin HR, Parkins MD, Surette MG. Culture-enriched metagenomic sequencing enables in-depth profiling of the cystic fibrosis lung microbiota. Nature Microbiology. 2020. 5, 379-90. doi: 10.1038/s41564-019-0643-y.
Whelan FJ, Rusilowicz M, McInerney JO. Coinfinder: detecting significant associations and dissociations in pangenomes. Microbial Genomics. 2020 6(3) doi: 10.1099/mgen.0.000338.
Whelan FJ, Heirali AA, Rossi L, Rabin HR, Parkins MD, Surette MG. Longitudinal sampling of the lung microbiota in individuals with cystic fibrosis. 2017. PloS one. 12(3), e 0172811. doi: 10.1371/journal.pone.0172811.
Syed SA, Whelan FJ, Waddell B, Rabin HR, Parkins MD, Surette MG. Reemergence of Lower-Airway Microbiota in Lung Transplant Patients with Cystic Fibrosis. Annals of the American Thoracic Society. 2016. 13(12), 2132-42. doi: 10.1513/AnnalsATS.201606-431OC.

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