Contrasting genes conferring short- and long-term biofilm adaptation in Listeria

Author:

Monteith William12,Pascoe Ben32,Mourkas Evangelos2,Clark Jack4,Hakim Maliha5,Hitchings Matthew D.6,McCarthy Noel7,Yahara Koji8,Asakura Hiroshi9,Sheppard Samuel K.2ORCID

Affiliation:

1. Department of Biology, University of Bath, Claverton Down, Bath, UK

2. Department of Biology, University of Oxford, Oxford, UK

3. Big Data Institute, University of Oxford, Oxford, UK

4. Department of Genetics, University of Leicester, University Road, Leicester, UK

5. Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, UK

6. Swasnsea University Medical School, Swansea University, Singleton Campus, Swansea, UK

7. School of Medicine, Trinity College Dublin, Dublin, Ireland

8. Antimicrobial Resistance Research Center, National Institute of Infectious Diseases, Tokyo, Japan

9. Division of Biomedical Food Research, National Institute of Health Sciences, Tonomachi 3-25-26, Kawasaki-ku, Kawasaki, Kanagawa 210-9501, Japan

Abstract

Listeria monocytogenes is an opportunistic food-borne bacterium that is capable of infecting humans with high rates of hospitalization and mortality. Natural populations are genotypically and phenotypically variable, with some lineages being responsible for most human infections. The success of L. monocytogenes is linked to its capacity to persist on food and in the environment. Biofilms are an important feature that allow these bacteria to persist and infect humans, so understanding the genetic basis of biofilm formation is key to understanding transmission. We sought to investigate the biofilm-forming ability of L. monocytogenes by identifying genetic variation that underlies biofilm formation in natural populations using genome-wide association studies (GWAS). Changes in gene expression of specific strains during biofilm formation were then investigated using RNA sequencing (RNA-seq). Genetic variation associated with enhanced biofilm formation was identified in 273 genes by GWAS and differential expression in 220 genes by RNA-seq. Statistical analyses show that the number of overlapping genes flagged by either type of experiment is less than expected by random sampling. This novel finding is consistent with an evolutionary scenario where rapid adaptation is driven by variation in gene expression of pioneer genes, and this is followed by slower adaptation driven by nucleotide changes within the core genome.

Funder

Medical Research Council

Publisher

Microbiology Society

Subject

General Medicine

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