Plasma proteomics altered between blood culture positive and negative patients:
Compared with blood cultures of patients without bloodstream infections, blood culture positive samples appear to have altered plasma proteomics, a new pilot study reveals.
The study involved 10 plasma samples from adult patients who presented with fever. The participants were between the ages of 53 and 91 years (median age 76 years). Samples were collected based on suspicion of serious bacterial bloodstream infections. An age- and sex-matched cohort provided 10 blood samples as controls.
Plasma samples were then extracted and treated to digest albumin. Ultra performance liquid chromatography followed by mass spectrometry was performed to separate, identify and quantify the proteins.
After removing albumin and considering only those with at least two unique peptides, analysis found 172 proteins of interest. On the basis of these proteins, principal component analysis showed separation of the culture positive and negative patients on the biplot space.
Orthogonal Projections to Latent Structures Discriminant Analysis identified proteins that had predictive variance for the controls and cases. Among these proteins were putative protein N-methyltransferase (p=0.02), ceramide synthase 3 (p=0.03), cathespin D (p=-0.06) and ubiquitin carboxyl-terminal hydrolase 1 (p=0.02).
Pathway analysis revealed that scavenging heme from plasma and binding and uptake of ligands by scavenger receptors were the two overrepresented pathways in controls, as measured by their proteomic profiles.
On the other hand, cases showed an enrichment of changes in lipid metabolism, phagocytosis, and coagulation pathways and complement activation. All of these have previously been associated with infections in the bloodstream.
Initial findings thus show that there is a clear change in the plasma proteomics between culture positive and negative patients. These should be explored further and applied in larger-scale studies to potentially find universally-altered proteins or profiles for easier and clinically applicable tests.
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