Genomic variation between bacterial strains from the same species can be so large that no two genomes may contain the same content. This has lead to a distinction between a species' core-genome (the pool of genes shared by all members of a species) and pan-genome (a species' global gene repertoire). Consequently, although strains belong to the same species, differences in the presence and absence of genomic content means that they may not function in the same manner, potentially affecting all sorts of phenotypes including bacterial virulence. A growing body of evidence suggests that the genetic background effect is actually a broad phenomenon that can be observed in different domains of life. However, due to difficulties associated with performing both genome-wide as well as species-wide experiments, comprehensive studies have so far been neglected. With the introduction of the genome- wide tool transposon sequencing (Tn-seq, a method we developed), it has now become feasible to untangle the influence of the genetic-background on a genome-wide scale and a species-wide level for a bacterial pathogen. Here we focus on the bacterium Streptococcus pneumoniae a common occupant of the nasopharynx, with a pan-genome 3-fold larger than the core-genome, and a major etiology of illness worldwide causing tens of millions of episodes of invasive pneumococcal disease and ~1.5 million deaths each year. We hypothesize that a diverse set of genes, pathways and small non-coding RNAs (ncRNAs), are involved in virulence and due to differences in genetic-background these components and the roles they play are only partially conserved across strains. We propose to determine in detail the virulence potential for 50 S. pneumoniae strains, covering 92% of the pan-genome, thereby unraveling the genomic-patterns that are most important for host-colonization and disease induction. This will enable us to predict: 1) the virulence-level of a genotype, and 2) a genotype's likelihood to evolve a higher virulence-level. Thereby this proposal fits into the major long-term goal of the lab, which is to understand how bacteria induce disease on a species-wide level in order to apply this knowledge to enable predictions on a strain's potential virulence, and design species-wide antimicrobial strategies.
The genomes of pathogenic bacteria from the same species may differ dramatically, which can affect their disease causing potential. Due to experimental limitations this variation is often ignored, which means we have a limited view of how a bacterium such as Streptococcus pneumoniae, which kills ~1.5 million people each year, causes disease. Due to the availability of new experimental tools we determine in detail for S. pneumoniae what a disease causing genome looks like enabling predictions on which strains cause disease and which strains are likely to increase their disease causing potential.
| McCoy, Katherine Maia; Antonio, Margaret L; van Opijnen, Tim (2017) MAGenTA: a Galaxy implemented tool for complete Tn-Seq analysis and data visualization. Bioinformatics 33:2781-2783 |
