Data-independent acquisition mass spectrometry in severe rheumatic heart disease (RHD) identifies a proteomic signature showing ongoing inflammation and effectively classifying RHD cases.

BACKGROUND: Rheumatic heart disease (RHD) remains a major source of morbidity and mortality in developing countries. A deeper insight into the pathogenetic mechanisms underlying RHD could provide opportunities for drug repurposing, guide recommendations for secondary penicillin prophylaxis, and/or inform development of near-patient diagnostics. METHODS: We performed quantitative proteomics using Sequential Windowed Acquisition of All Theoretical Fragment Ion Mass Spectrometry (SWATH-MS) to screen protein expression in 215 African patients with severe RHD, and 230 controls. We applied a machine learning (ML) approach to feature selection among the 366 proteins quantifiable in at least 40% of samples, using the Boruta wrapper algorithm. The case-control differences and contribution to Area Under the Receiver Operating Curve (AUC) for each of the 56 proteins identified by the Boruta algorithm were calculated by Logistic Regression adjusted for age, sex and BMI. Biological pathways and functions enriched for proteins were identified using ClueGo pathway analyses. RESULTS: Adiponectin, complement component C7 and fibulin-1, a component of heart valve matrix, were significantly higher in cases when compared with controls. Ficolin-3, a protein with calcium-independent lectin activity that activates the complement pathway, was lower in cases than controls. The top six biomarkers from the Boruta analyses conferred an AUC of 0.90 indicating excellent discriminatory capacity between RHD cases and controls. CONCLUSIONS: These results support the presence of an ongoing inflammatory response in RHD, at a time when severe valve disease has developed, and distant from previous episodes of acute rheumatic fever. This biomarker signature could have potential utility in recognizing different degrees of ongoing inflammation in RHD patients, which may, in turn, be related to prognostic severity.

Application of SWATH mass spectrometry in the identification of circulating proteins does not predict future weight gain in early psychosis.

Weight gain is a common consequence of treatment with antipsychotic drugs in early psychosis, leading to further morbidity and poor treatment adherence. Identifying tools that can predict weight change in early psychosis may contribute to better-individualised treatment and adherence. Recently we showed that proteomic profiling with sequential window acquisition of all theoretical fragment ion spectra (SWATH) mass spectrometry (MS) can identify individuals with pre-diabetes more likely to experience weight change in relation to lifestyle change. We investigated whether baseline proteomic profiles predicted weight change over time using data from the BeneMin clinical trial of the anti-inflammatory antibiotic, minocycline, versus placebo. Expression levels for 844 proteins were determined by SWATH proteomics in 83 people (60 men and 23 women). Hierarchical clustering analysis and principal component analysis of baseline proteomics data did not reveal distinct separation between the proteome profiles of participants in different weight change categories. However, individuals with the highest weight loss had higher Positive and Negative Syndrome Scale (PANSS) scores. Our findings imply that mode of treatment i.e. the pharmacological intervention for psychosis may be the determining factor in weight change after diagnosis, rather than predisposing proteomic dynamics.

Unblocking the sink: improved CID-based analysis of phosphorylated peptides by enzymatic removal of the basic C-terminal residue.

A one-step enzymatic reaction for improving the collision-induced dissociation (CID)-based tandem mass spectrometry (MS/MS) analysis of phosphorylated peptides in an ion trap is presented. Carboxypeptidase-B (CBP-B) was used to selectively remove C-terminal arginine or lysine residues from phosphorylated tryptic/Lys-C peptides prior to their MS/MS analysis by CID with a Paul-type ion trap. Removal of this basic C-terminal residue served to limit the extent of gas-phase neutral loss of phosphoric acid (H3PO4), favoring the formation of diagnostic b and y ions as determined by an increase in both the number and relative intensities of the sequence-specific product ions. Such differential fragmentation is particularly valuable when the H3PO4 elimination is so predominant that localizing the phosphorylation site on the peptide sequence is hindered. Improvement in the quality of tandem mass spectral data generated by CID upon CBP-B treatment resulted in greater confidence both in assignment of the phosphopeptide primary sequence and for pinpointing the site of phosphorylation. Higher Mascot ion scores were also generated, combined with lower expectation values and higher delta scores for improved confidence in site assignment; Ascore values also improved. These results are rationalized in accordance with the accepted mechanisms for the elimination of H3PO4 upon low energy CID and insights into the factors dictating the observed dissociation pathways are presented. We anticipate this approach will be of utility in the MS analysis of phosphorylated peptides, especially when alternative electron-driven fragmentation techniques are not available.