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Wamsley, N.

Publications and source records attributed to Wamsley, N..

3 recordsLinked to original sources

JMod: Joint modeling of mass spectra for empowering multiplexed DIA proteomics

Parallelization of data acquisition substantially increases the throughput of mass spectrometry-based proteomics. However, parallelization also increases the density of mass spectra and consequently the overlap between ions, frustrating their analysis. To improve sequence identification and quantification from such spectra, we developed an open-source software for Joint Modeling of mass spectra (JMod). JMod models overlapping peaks as linear superpositions of their components in both MS1 and MS2 space, which permits multiplexed DIA with smaller mass offsets to increase the multiplexing capacity and thus proteomics throughput for a given plexDIA tag. This enables 9-plexDIA using 2 Da offset PSMtags, increasing throughput 9-fold while preserving quantitative accuracy and coverage depth. Furthermore, we use JMod to deconvolve simultaneous labeling by mass tags and heavy amino acids, thus increasing the throughput of metabolic pulse experiments measuring protein synthesis and degradation rates in single cells from mouse liver. By supporting enhanced decoding of highly multiplexed DIA spectra, JMod provides an open and flexible software that increases the throughput of sensitive proteomics.

bioinformatics↗

Increasing mass spectrometry throughput using time-encoded sample multiplexing

Liquid chromatography-mass spectrometry (LC-MS) can enable precise and accurate quantification of analytes at high-sensitivity, but the rate at which samples can be analyzed remains limiting. Throughput can be increased by multiplexing samples in the mass domain with plexDIA, yet multiplexing along one dimension will only linearly scale throughput with plex. To enable combinatorial-scaling of proteomics throughput, we developed a complementary multiplexing strategy in the time domain, termed timePlex. timePlex staggers and overlaps the separation periods of individual samples. This strategy is orthogonal to isotopic multiplexing, which enables combinatorial multiplexing in mass and time domains when paired together, and thus multiplicatively increased throughput. We demonstrate this with 3-timePlex and 3-plexDIA, enabling the multiplexing of 9 samples per LC-MS run, and 3-timePlex and 9-plexDIA exceeding 500 samples / day with a combinatorial 27-plex. Crucially, timePlex supports sensitive analyses, including of single cells. These results establish timePlex as a methodology for label-free multiplexing and combinatorial scaling of the throughput of LC-MS proteomics. We project this combined approach will eventually enable an increase in throughput exceeding 1,000 samples / day. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=97 SRC="FIGDIR/small/655515v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@1c1d799org.highwire.dtl.DTLVardef@1319339org.highwire.dtl.DTLVardef@1b8bf4borg.highwire.dtl.DTLVardef@16d9e9_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

Targeted proteomic quantitation of NRF2 signaling and predictive biomarkers in HNSCC

The NFE2L2/NRF2 oncogene and transcription factor drives a gene expression program that promotes cancer progression, metabolic reprogramming, immune evasion and chemoradiation resistance. Patient stratification by NRF2 activity may guide treatment decisions to improve outcome. Here, we developed a mass spectrometry (MS)-based targeted proteomics assay based on internal standard triggered parallel reaction monitoring (IS-PRM) to quantify 69 NRF2 pathway components and targets as well as 21 proteins of broad clinical significance in head and neck squamous cell carcinoma (HNSCC). We improved the existing IS-PRM acquisition algorithm, called SureQuant, to increase throughput, sensitivity, and precision. Testing the optimized platform on 27 lung and upper aerodigestive cancer cell models revealed 35 NRF2 responsive proteins. In formalin-fixed paraffin-embedded (FFPE) HNSCCs, NRF2 signaling intensity positively correlated with NRF2 activating mutations and with SOX2 protein expression. PD-L2/CD273 and protein markers of T-cell infiltration correlated positively with one another and with human papilloma virus (HPV) infection status. p16/CDKN2A protein expression positively correlated with the HPV oncogenic E7 protein, and confirmed the presence of translationally active virus. This work establishes a clinically actionable HNSCC protein biomarker assay capable of quantifying over 600 peptides from frozen or FFPE archived tissues in under 90 minutes.

cancer biology↗