Estimating the Reliability of Low-Abundant Signals and Limited Replicate Measurements through MS2 Peak Area in SWATH

Cov2MS: An Automated and Quantitative Matrix-Independent Assay for Mass Spectrometric Measurement of SARS-CoV-2 Nucleocapsid Protein

The pandemic readiness toolbox needs to be extended, targeting different biomolecules, using orthogonal experimental set-ups. Here, we build on our Cov-MS effort using LC-MS, adding SISCAPA technology to enrich proteotypic peptides of the SARS-CoV-2 nucleocapsid (N) protein from trypsin-digested patient samples. The Cov²MS assay is compatible with most matrices including nasopharyngeal swabs, saliva, and plasma and has increased sensitivity into the attomole range, a 1000-fold improvement compared to direct detection in a matrix. A strong positive correlation was observed with qPCR detection beyond a quantification cycle of 30-31, the level where no live virus can be cultured. The automatable sample preparation and reduced LC dependency allow analysis of up to 500 samples per day per instrument. Importantly, peptide enrichment allows detection of the N protein in pooled samples without sensitivity loss. Easily multiplexed, we detect variants and propose targets for Influenza A and B detection. Thus, the Cov²MS assay can be adapted to test for many different pathogens in pooled samples, providing longitudinal epidemiological monitoring of large numbers of pathogens within a population as an early warning system.

A large scale mass spectrometry-based histone screening for assessing epigenetic developmental toxicity

Toxicoepigenetics is an emerging field that studies the toxicological impact of compounds on protein expression through heritable, non-genetic mechanisms, such as histone post-translational modifications (hPTMs). Due to substantial progress in the large-scale study of hPTMs, integration into the field of toxicology is promising and offers the opportunity to gain novel insights into toxicological phenomena. Moreover, there is a growing demand for high-throughput human-based in vitro assays for toxicity testing, especially for developmental toxicity. Consequently, we developed a mass spectrometry-based proof-of-concept to assess a histone code screening assay capable of simultaneously detecting multiple hPTM-changes in human embryonic stem cells. We first validated the untargeted workflow with valproic acid (VPA), a histone deacetylase inhibitor. These results demonstrate the capability of mapping the hPTM-dynamics, with a general increase in acetylations as an internal control. To illustrate the scalability, a dose–response study was performed on a proof-of-concept library of ten compounds (1) with a known effect on the hPTMs (BIX-01294, 3-Deazaneplanocin A, Trichostatin A, and VPA), (2) classified as highly embryotoxic by the European Centre for the Validation of Alternative Methods (ECVAM) (Methotrexate, and All-trans retinoic acid), (3) classified as non-embryotoxic by ECVAM (Penicillin G), and (4) compounds of abuse with a presumed developmental toxicity (ethanol, caffeine, and nicotine).

Assessing technical and biological variation in SWATH-MS-based proteomic analysis of chronic lymphocytic leukaemia cells

Chronic lymphocytic leukaemia (CLL) exhibits variable clinical course and response to therapy, but the molecular basis of this variability remains incompletely understood. Data independent acquisition (DIA)-MS technologies, such as SWATH (Sequential Windowed Acquisition of all THeoretical fragments), provide an opportunity to study the pathophysiology of CLL at the proteome level. Here, a CLL-specific spectral library (7736 proteins) is described alongside an analysis of sample replication and data handling requirements for quantitative SWATH-MS analysis of clinical samples. The analysis was performed on 6 CLL samples, incorporating biological (IGHV mutational status), sample preparation and MS technical replicates. Quantitative information was obtained for 5169 proteins across 54 SWATH-MS acquisitions: the sources of variation and different computational approaches for batch correction were assessed. Functional enrichment analysis of proteins associated with IGHV mutational status showed significant overlap with previous studies based on gene expression profiling. Finally, an approach to perform statistical power analysis in proteomics studies was implemented. This study provides a valuable resource for researchers working on the proteomics of CLL. It also establishes a sound framework for the design of sufficiently powered clinical proteomics studies. Indeed, this study shows that it is possible to derive biologically plausible hypotheses from a relatively small dataset.