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coonlab.bsky.social
@coonlab.bsky.social
· Jul 30
coonlab.bsky.social
@coonlab.bsky.social
· Jul 30
SynchroSep-MS: Parallel LC Separations for Multiplexed Proteomics
Achieving high throughput remains a challenge in MS-based proteomics for large-scale applications. We introduce SynchroSep-MS, a novel method for parallelized, label-free proteome analysis that leverages the rapid acquisition speed of modern mass spectrometers. This approach employs multiple liquid chromatography columns, each with an independent sample, simultaneously introduced into a single mass spectrometer inlet. A precisely controlled retention time offset between sample injections creates distinct elution profiles, facilitating unambiguous analyte assignment. We modified the DIA-NN workflow to effectively process these unique parallelized data, accounting for retention time offsets. Using a dual-column setup with mouse brain peptides, SynchroSep-MS detected approximately 16,700 unique protein groups, nearly doubling the peptide information obtained from a conventional single proteome analysis. The method demonstrated excellent precision and reproducibility (median protein %RSDs less than 4%) and high quantitative linearity (median R2 greater than 0.96) with minimal matrix interference. SynchroSep-MS represents a new paradigm for data collection and the first example of label-free multiplexed proteome analysis via parallel LC separations, offering a direct strategy to accelerate throughput for demanding applications such as large-scale clinical cohorts and single-cell analyses without compromising peak capacity or causing ionization suppression.
pubs.acs.org
coonlab.bsky.social
@coonlab.bsky.social
· Jun 18
coonlab.bsky.social
@coonlab.bsky.social
· Jun 18
coonlab.bsky.social
@coonlab.bsky.social
· Jun 17
coonlab.bsky.social
@coonlab.bsky.social
· Jun 17
coonlab.bsky.social
@coonlab.bsky.social
· Jun 17
coonlab.bsky.social
@coonlab.bsky.social
· Jun 17
coonlab.bsky.social
@coonlab.bsky.social
· Jun 17
coonlab.bsky.social
@coonlab.bsky.social
· Jun 17