Urine metaproteomics for rapid clinical UTI diagnoses?

Traditionally, clinical microbiology diagnostics has been 1) labor intensive 2) Slow 3) Error prone 4) Slow and 5) Slow.

A lot of groups are working on it, and I think most people at ASMS 2016 saw Dr. Pandey's overview of the work Johns Hopkins is doing to overhaul the field with rapid LC-MS/MS microbial identifications that massively exceed the diagnostic powers of MALDI-TOF based ID.

Lots of techniques are going to be necessary to improve clinical micro -- because there are a LOT of clinically important pathogens -- and body fluids.

This brand new multi-lab study in my local area is a great, reasonably simple and obviously effective approach that could be applied in the clinic to rapid urine diagnoses.

The study is somewhat of a follow-up to a paper from some of these authors last year and since I'm reading them back to back, I'm probably going to kind of lump them together.

Despite the massive dynamic range problems (we seem to see in all body fluids) and the presence of the normal microbiota, these authors demonstrate a surprising level of diagnostic power from their workflow. 12 healthy humans vs 12 patients with UTIs...and they find both diagnostic markers to separate the 2 groups -- as well as the power to identify individual pathogenic species.

The workflow is as shown in the picture above, so I won't go into it. Something that stood out as interesting to me is the database they started out with.

They used a tool called CD-HIT to generate their FASTA database and this tool seems really interesting. You can direct link to it here and this is a somewhat recent paper detailing the tool.

I'll have to investigate this tool a bit later.

If you are interested in clinical proteomics for diagnostics, or just urine in general, I'd definitely look up these papers!

EDIT after a short dog walk: One of the cool findings in the newest study, which didn't really hit me until we were some ways from the office, is that the urine sediment pellet has a lot of diagnostic power -- and if you only look at the soluble proteins you might miss what you need for accurate diagnosis.