Isabel Gordo

In vivo long term evolution of a commensal in the gut microbiota

Isabel Gordo, Deputy Director of Science
Gulbenkian Science Institute, Portugal

Microbiota diversity is a key modulator of host health: a diverse gut microbiome is indicative of health and a microbiome exhibiting low diversity is typically associated with disease. How such microbiome diversity emerges and is maintained over the life of an individual host is one of the great mysteries that this project seeks to address.

Recent analysis of the Human Microbiome Project data suggests that within-host evolution of microbiota species can occur in the human gut over months or years. However, the limited sampling, difficulties with analyzing short read sequence data and lack of control of the initial conditions of strain colonization, makes it extraordinarily difficult to quantify rates of evolution. Furthermore, possible migration of strains from the environment raises uncertainty in establishing the relative contribution of mutation and horizontal gene transfer (HGT) to intra- and inter- species diversity in the gut.

Experimental evolution of bacteria model species colonizing the gut offers a powerful complementary approach to understand the emergence of strain diversity and its consequences for the function and structure of the gut microbiome. In this context the project team has developed a new in vivo long term experimental evolution (ivLTEE) mouse system, where the evolution of a commensal lineage within a rich ecosystem offers novel insights into the missing process of evolution within the microbiota. Using this unique experimental system together with dense time series sequencing, the researchers will characterize evolution in real time of a gut commensal throughout the adult life of laboratory mice.

Preliminary data identifies HGT as a key driver of evolutionary change in the initial stages of colonization under specific conditions. When direct competitors of a newly colonizing species reside in the gut, phage driven HGT generates new strains that acquire tens of genes from the resident microbiota. When these competitors are absent new mutations accumulate and new clones with an increased mutation rate (mutators) can emerge. Both HGT and mutation are identified as key evolutionary mechanism from comparative genomic studies. Yet, these have not only been hard to detect in real time but also their relative rates have been difficult to establish. This new ivLTEE offers exactly that possibility: quantification of the rate of long-term evolution via de novo mutation and HGT.

The spontaneous emergence and maintenance of hypermutators (rarely detected either in vitro or in vivo studies) in this complex ecosystem raises a conundrum: How can these be maintained? Will they be eliminated in the long term?; in other words: How does microbial genomic instability shape intra-species diversity in the gut ecosystem?  Both the short and the possible long term maintenance of clones with mutation rates 1000-fold higher than the typical rate can have strong effects in modulating the level of antibiotic resistance (AMR) in the gut microbiome. Not only will the level of spontaneous AMR be higher, but also it may increase to dominant levels, under antibiotic treatment. The project will also address the role of mutators in modulating AMR levels. The originality of the plan lies on its focus to characterise and quantify evolutionary change within a host lifetime, with great precision.

Dr Isabel Gordo is a principal investigator at the Gulbenkian Science Institute, Portugal. She graduated in Physics and received a PhD in Evolutionary Genetics from the University of Edinburgh in 2002. Her PostDoctoral research was carried out at the Gulbenkian Science Institute where she then became leader of the  Evolutionary Biology group in 2004. In 2010 she won an ERC Starting Grant and in 2015 a FCT Investigator Consolidator Grant.

She founded the Portuguese Society for Evolutionary Biology, has served as panel member of the European Research Council grants evaluation since 2014 and was elected an European Molecular Biology Organization member in 2017.

Her current research combines theoretical and empirical methods aiming at a better understanding of the major forces that shape diversity of bacteria and their resistance levels in the context of the gut microbiome. She uses Escherichia coli as a bacteria model and mice as a host model system.

Read more about Isabel Gordo's work here:

Niall Hyland

Drug-gut microbiota interactions: developing a pathway to personalized medicine in psychiatry

Niall Hyland, Senior Lecturer (Associate Professor)
University College Cork, Ireland

The microbiome plays a key role in health and disease and there has been considerable interest in therapeutic targeting of the microbiome as well as mining this rich resource in drug discovery efforts. However, a growing body of evidence now suggests that the gut microbiota can itself influence the actions of a range of drugs both by directly metabolising them and indirectly by affecting host drug metabolism, the consequences of which can be either beneficial or potentially harmful. Nevertheless, such studies have not extended to psychotropic medications nor addressed whether the dysbiosis associated with psychiatric illness may underpin the clinical response to psychotropic drugs.

The project's objectives are to determine the impact of clinically diagnosed depression on microbial drug metabolism; to identify whether depression-associated dysbiosis affects host drug metabolism and drug pharmacokinetics in a humanized rat model of depression; and to develop a Physiologically based Pharmacokinetic (PbPK) model incorporating a microbiome-mediated drug metabolism compartment for predicting drug pharmacokinetics in patients.

Researchers will measure the drug-metabolising activity of the gut microbiome from patients with depression by preparing a stable cell-free extract of human faeces, fecalase. Using high performance liquid chromatography we will then determine whether fecalase from depressed subjects differentially affects the metabolism of psychotropic drugs. To better understand the impact of disease-driven dysbiosis on host drug metabolism and pharmacokinetics, in a humanised rat model of depression they will examine the expression of genes involved in host drug metabolism and the pharmacokinetic profile of psychotropic medications. Finally, through the incorporation of different types of data, including -omics, enzymatic and pharmacokinetic data in an integrated way they will develop an in silico model which can be tailored to the individual patient characteristics and provide reliable predictions of drug levels in these patients.

Dr Niall Hyland is a tenured Senior Lecturer in the Department of Physiology and Faculty in APC Microbiome Ireland at University College Cork, Ireland.  He received a BSc (Hons) in Biomedical Sciences from the University of Ulster and PhD in Pharmacology from King’s College London.  Niall was a visiting fellow at the Department of Pharmacology and Experimental Therapeutics, Louisiana State University Medical Center (1998-1999) and completed an AstraZeneca/Canadian Association of Gastroenterology/Canadian Institutes of Health Research-funded postdoctoral fellowship at the University of Calgary in Canada. He returned to Ireland in 2007 to take up a GlaxoSmithKline-supported senior postdoctoral position at APC Microbiome Ireland and was subsequently appointed Lecturer in Pharmacology in the School of Medicine in 2008 and Senior Lecturer in Physiology in 2018.

Niall’s laboratory investigates the interactions between the gut microbiome and host in the context of intestinal physiology and the gut-brain axis. Current collaborative projects are investigating microbial drug metabolism; the bladder microbiome; and the temporal changes in the gut microbiome during colon carcinogenesis.  Dr Hyland has a H-Index of 22 and co-edited the book, The Gut-Brain Axis: Dietary, Probiotic, and Prebiotic Interventions on the Microbiota published by Elsevier/Academic Press.  

Read more about Niall Hyland's work here:


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