Urinary Tract Infections (UTIs), are one of the most common infections globally. To improve treatment, there is a need to understand the physiological state of bacteria involved in the infection. Escherichia coli accounts for a large proportion of UTIs, and in this context we aim to profile the proteomes of Escherichia coli (E. coli), isolated from the urine of patients with UTIs and compare and correlate those proteomes with proteomes from E. coli cultured in various conditions, to better understand the physiology of E. coli in vivo.

By comparing and correlating in vitro and in vivo E. coli proteomes, we aim to understand critical features that describe in vitro and in vivo growth of E. coli in Urine. These include nutrient availability and host-immune properties.

Here we present a workflow that allows the comparison and correlation of in vitro generated proteomes, with the aim of understanding in vivo E coli physiology, and benchmarking in vitro models.

Our data suggests that the major processes that drive the differences between our current in vitro models and in vivo sample; are involved in amino-acid metabolism and carbon metabolism - including fatty acid metabolism, glucose metabolism and the glyoxylate cycle, environmental conditions such as low oxygen tension are also implicated. Furthermore, we also identify clusters of patient derived samples, that may be driven by the host state, such as the availability of glycolytic substrates, or host immune response.

The workflow presented here shows a data-driven approach to generate hypotheses aimed at improving in vitro models to better mimic in vivo conditions.And shows particular value in iterative approaches in model design. It also allows the functional investigation of diverse clinical proteomes.