What is the problem?

Bloodstream infection results in sepsis, which kills more than 40,000 people in the UK every year. Quickly providing a working antibiotic is necessary to reduce morbidity and mortality. However, currently, it takes 24-48 hours to grow bacteria from patients’ blood, and then another 18 h to determine antibiotic susceptibility. This means that patients can be prescribed non-functional antibiotics, or extremely broad spectrum, “last resort” antibiotics – just in case of resistance – for some time.

What is the solution?

It is possible to sequence the genomes of bacteria in blood samples without significant culture. Since all antibiotic resistance (ABR) is encoded in the genome sequence, it is therefore theoretically possible to predict whether the bacterium causing an infection is resistant to antibiotics. However, our work understanding the molecular basis of ABR has contributed to our understanding that ABR is frequently complex and involves the amount that a gene is expressed, not just whether a gene is present or not. Ultimately, the amount of a protein, or number of proteins, being produced in the bacterium is what defines ABR. Proteomics is a methodology that allows quantification and identification of proteins. We aim to use proteomics to use proteomics to help better predict antibiotic resistance using whole genome sequencing, by uncovering the biology of resistance and bridging the gap between genotype and phenotype.

Outcome and next steps 

We have successfully identified and quantified bacterial proteins in blood samples from septic patients and used this to correctly predict resistance to beta-lactam antibiotics, the most commonly prescribed antibiotics used in humans (Takebayashi et al, 2022 BioRxiv 2022.02.27.482154). We have used proteomics to understand the complex interplay of factors that leads to fluoroquinolone resistance, and this has led to the establishment of 47 rules that predict fluoroquinolone resistance directly from whole genome sequencing (Wan nur Ismah et al, 2018 Antimicrobial Agents and Chemotherapy 62:e01814-17. We are currently turning our attention to the prediction of aminoglycoside resistance, and the complex interplay of factors that affect beta-lactam/beta-lactamase inhibitor resistance.