Selecting a sample preparation strategy for mass spectrometrybased proteomics is critical to the success of quantitative workflows. Here we present a universal, solid-phase protein preparation (USP 3 ) method which is rapid, robust, and scalable, facilitating high-throughput protein sample preparation for bottom-up and top-down mass spectrometry (MS) analysis. This technique builds upon the single-pot solid-phase-enhanced sample preparation (SP3) where we now demonstrate its scalability (low to high micrograms of protein) and the influence of variables such as bead and enzyme amounts on the efficiency of protein digestion. We also incorporate acid hydrolysis of DNA and RNA during complete proteome extraction resulting in a more reliable method that is simple and easy to implement for routine and high-throughput analysis of proteins. We benchmarked the performance of this technique against filter-aided sample preparation (FASP) using 30 μg of total HeLa protein lysate. We also show that the USP 3 method is compatible with top-down MS where we reproducibly detect over 1800 proteoforms from 50 μg of HeLa protein lysate. The USP 3 protocol allows for efficient and reproducible data to be generated in a cost-effective and robust manner with minimal down time between sample collection and analysis by MS.

Recent advances in mass spectrometry technology have seen remarkable increases in proteomic sequencing speed, while improvements to dynamic range have remained limited. An exemplar of this is the new timsTOF Pro instrument, which thanks to its trapped ion mobility, pushes effective fragmentation rates beyond 100Hz and provides accurate CCS values as well as impressive sensitivity. Established data dependent methodologies underutilize these advances by relying on long analytical columns and extended LC gradients to achieve comprehensive proteome coverage from biological samples. Here we describe the implementation of methods for short packed emitter columns that fully utilize instrument speed and CCS values by combining rapid generation of deep peptide libraries with enhanced matching of single shot data dependent sample analysis. Impressively, with only a 17 minute gradient separation (50 samples per day), the combination of high performance chromatography and CCS enhanced library based matching resulted in an average of 6,690 protein identifications within individual samples, and 7,797 proteins cumulatively across replicates from HeLa cell tryptic digests. Additionally, an ultra-high throughput setup utilizing 5 min gradients (180 samples per day) yielded an average of 2,800 protein identifications within individual samples and 4,254 proteins cumulatively across replicates. These workflows are simple to implement on available technology and do not require complex software solutions or custom made consumables to achieve high throughput and deep proteome analysis from biological samples.

Epithelial-mesenchymal transition (EMT) is a continuum that includes epithelial, partial EMT, and mesenchymal states, each of which is associated with cancer progression, invasive capabilities, and ultimately, metastasis. We used a lineage-traced sporadic model of pancreatic cancer to generate a murine organoid biobank from primary and secondary tumors, including sublines that underwent partial EMT and complete EMT. Using an unbiased proteomics approach, we found that organoid morphology predicts the EMT state, and the solid organoids are associated with a partial EMT signature. We also observed that exogenous TGFβ1 induces solid organoid morphology that is associated with changes in the S100 family, complete EMT, and the formation of high-grade tumors. S100A4 may be a useful biomarker for predicting EMT state, disease progression, and outcome in patients with pancreatic cancer.