Lionel Guy research group

Evolution of host adaptation

Our research explores how microorganisms, particularly bacteria, adapt to hosts, and how their relationships evolve over time. The overall goal of our research is to better understand the long- and short-term evolution of host adaptation, and to identify strategies and critical genetic innovations that allow free-living bacteria to adapt to, and then profit from, or live in symbiosis with, eukaryotic hosts.

For their wide variety in host-adaptation strategies and their ecological success, we currently focus on the bacterial order Legionellales, which includes two human pathogens, Legionella and Coxiella and their related intracellular groups, like Francisella. So far, all described species of Legionellales can replicate intracellularly, although their degree of reliance on their host and their host spectrum varies, which makes them especially interesting to study.

Projects are currently explored:

1. Emergence and evolution of host-adaptation in Legionellales

• Is the current diversity of Legionellales resulting from a single event of host-adaptation? Was the ancestor of Legionella and Coxiella living inside amoebae?
• What systems, crucial for host-adaptation, were invented or recruited that paved the way to its current ecological success?
• What can we learn about the early eukaryotic hosts of Legionellales by investigating their first bacterial pathogens?

To answer these questions, we are using a comparative genomics approach, tapping into the unexplored diversity of Legionellales. We are also using state-of-the art metagenomics and single-cell genomics to harvest organisms that are uncultivable. We aim at reconstructing the ancestors of Legionellales and establish the flow of host-adaptation systems.

2. WoodenLeg: Legionella in wastewater treatment plants used at paper and pulp mills

Paper and pulp mills (PPM) use large quantities of water to produce paper from wood. Biological treatment plants (BTP) are commonly used to remove organic compounds from process water of such mills, thereby lowering the risk of pollution and eutrophication of downstream recipients. Despite a crucial role for the functioning of such BTP plants, its microbiomes have barely been studied, which is noteworthy, not least since they can host pathogenic Legionella, representing a severe risk of infection for workers and neighbors.

Here, we want to understand the biotic interactions taking place in the BTP, with a particular emphasis on their impact on Legionella growth, using metagenomics.

This study should (i) identify factors and microorganisms enhancing or preventing Legionella growth in BTPs, (ii) contribute a simple, inexpensive routine method to monitor the microbiome; (iii) contribute to a better understanding of the BTP process to improve its design and operation.

3. Bioinformatics tools

Over the years, the lab and its members have developed and contributed to a variety of bioinformatic tools.

TADA: taxonomy-aware dataset aggregator

TADA generates datasets for evolutionary and comparative genomic studies of bacterial and archaeal genomes. Given a few user-defined options and rules, it downloads taxonomic and phylogenomic information from publicly available sources and then performs a sampling procedure.

TADA was conceptualized written by Emil Hägglund, PhD student with Siv GE Andersson, under the supervision of Lionel Guy.

• Publication
• Code

miComplete

miComplete is a compact software aimed at rapidly and accurately determining of the quality of assembled genomes, often metagenome assembled bins.

miComplete was first written and conceptualized by Lionel Guy, then re-written and extended by Eric Hugoson.

• Publication
• Code 1 and code 2

phyloSkeleton

A predecessor to TADA, phyloSkeleton offers tools to easily select the most representative organisms, following a set of simple rules based on taxonomy and assembly quality.

phyloSkeleton was conceptualized and written by Lionel Guy. Users should nowadays use TADA (see above).

• Publication
• Code

genoPlotR

genoPlotR automatically creates publication-grade linear maps of gene and genomes, in a highly automatic, flexible and reproducible way.

genoPlotR was conceptualized and written by Lionel Guy, with contributions from Jens Roat Kultima, under the supervision of Siv GE Andersson.

• Publication
• Website
• Code