Understanding biological processes on a global proteome-wide scale is crucial in scientific research. Achieving statistically significant quantitative data often involves studying large cohorts comprising hundreds of biological samples and replicates. An effective workflow must be capable of processing, measuring, and analyzing a high volume of samples while ensuring data reproducibility and consistent performance throughout the study. The primary aim of this study was to introduce a robust workflow for high-throughput label-free quantification using a Vanquish Neo LC system equipped with a 5.5 cm uPAC Neo High Throughput column and an Orbitrap Exploris 480 mass spectrometer.

We evaluated three gradient lengths, namely 3.5, 5.5, and 10 minutes. The mass spectrometric method, predominantly the isolation window widths, have been optimized for two different objectives: one method for giving maximum proteome coverage of the sample, another for gaining high-quality quantitative information on the protein abundances. To further showcase the quantitative capabilities of these methods, we employed a three-species proteome mix, achieving accurate quantification results across all three gradient lengths using the MS method for quantitative analysis. Furthermore, we demonstrated the workflow's robustness through an analysis of several 100 consecutive injections, proving this workflow to be suitable for the reliable analysis of large cohort studies. Data processing was carried out using different software tools with library-free analysis approaches.

The main objective of this study was to evaluate the suitability of µPAC columns with 5.5cm flow path for maximizing the throughput of MS analysis gaining reliable and robust quantitative information. Each gradient length was analyzed for the number of identified proteins and peptides from different amounts of HeLa digests. Despite the short gradients, the data clearly illustrate that a median of 5-6 points per peak could be measured for isolated HeLa peptide XICs, achieved by meticulous duty cycle adjustments in each of the three DIA methods tested.

In experiments focused on label-free quantification (LFQ), precision and accuracy in measuring relative protein and peptide abundances are crucial. To assess the quantitative performance of the described methods, the study analyzed a mix of three species proteomes, i.e. tryptic digests of human, yeast, and E.coli proteins mixed in specific ratios. The quantification precision, evaluated through coefficients of variation (CV) across different technical replicates at both the protein and peptide levels, consistently demonstrated CVs well below 10% and minimal missing values, indicating high technical reproducibility.