In September 2015, I was in a position of many young investigators. I had just finished my Ph.D. focusing on a virulence factor of Staphylococcus aureus, but was unsure of what to focus on during my postdoc. Should I continue to work on S. aureus? Should I work on a new organism? What was I most interested in?
The Whiteley lab had extensive previous experience analyzing big datasets for transposon insertion sequencing (Tn-seq) and RNA-Seq. Therefore, I decided that I wanted to gain computational skills, and that instead of starting from scratch with a new organism, I would learn in a system that I was familiar with: S. aureus infections. Luckily, a previous member of the lab had collected Tn-Seq data for S. aureus mono- and co-infections using a murine chronic surgical wound model.
The main question I wanted to ask with this data was: Is the “essential genome” of bacterial pathogens static, or does it change with the environment? In our quest to combat microbes, historically we have looked for targets in “essential genes”, which we have typically considered to be genes that we are unable to make mutations in such as the ribosome and DNA replication machinery. However, as bacteria are shown to rapidly develop resistance to antibiotics by bypassing the requirement of these targets, new strategies are needed. We thought that it was possible that the growth environment impacted the essential genome during infection, as different nutrients were likely available in different types of infection.
From our initial analyses, it was clear that there were dramatic differences in the S. aureus genetic requirements during mono- and co- infection in the chronic wound. However, we thought that to truly explore the dynamics of the essential genome during infection we needed additional data. Luckily, two previous mono-infection Tn-seq studies had been performed using the same S. aureus transposon library as our data, but in two different infection models, a murine abscess model and a murine osteomyelitis model. Adding these datasets to our study revealed that while infection site does have an impact on the genes required for S. aureus to survive during infection, the presence of a co-infecting organism, P. aeruginosa, altered the requirement of 6% of the S. aureus genome (~200 genes). We dubbed these differentially required genes to be Community Dependent Essential Genes (CoDE genes). Our study indicated that co-infecting bacteria (“who you are with”) had a greater impact on the genes S. aureus required than infection site (“where you are”). Further, we found that CoDE genes weren’t limited to S. aureus and P. aeruginosa infections, but also occurred in an infection model with Aggregatibacter actinomycetemcomitans and Streptococcus gordonii.
One of the next questions we’re interested in is: What leads to CoDE genes? While we discovered CoDE genes in a chronic wound model, we predict that interactions with other microbes during polymicrobial infection may lead to more CoDE genes. Cystic fibrosis (CF) lung infections frequently harbor a complex polymicrobial community, and are a great model for studying polymicrobial interactions. We next plan at looking at if and how CoDE genes arise in CF lung infections with P. aeruginosa and other co-infecting CF pathogens. Time to get started!
The paper in Nature Microbiology is here: http://go.nature.com/2qf6YCp
Cover image: S. aureus (yellow) and P. aeruginosa (magenta) aggregates in a murine chronic surgical wound taken with confocal laser scanning microscopy and rendered with Imaris software. Photo credit: Jake Everett & Sophie Darch