Label-free quantification (LFQ) and isobaric labeling quantification (ILQ) are among the most popular protein quantification workflows in discovery proteomics. Here, we compared the TMT SPS/MS3 10-plex workflow to a label free single shot data-independent acquisition (DIA) workflow on a controlled sample set. The sample set consisted of ten samples derived from 10 biological replicates of mouse cerebelli spiked with the UPS2 protein standard in five different concentrations. For a fair comparison, we matched the instrument time for the two workflows. The LC–MS data were acquired at two facilities to assess interlaboratory reproducibility. Both methods resulted in a high proteome coverage (>5000 proteins) with low missing values on protein level (<2%). The TMT workflow led to 15–20% more identified proteins and a slightly better quantitative precision, whereas the quantitative accuracy was better for the DIA method. The quantitative performance was benchmarked by the number of true positives (UPS2 proteins) within the top 100 candidates. TMT and DIA showed a similar performance. The quantitative performance of the DIA data stayed in a similar range when searching the spectra against a fasta database directly, instead of using a project-specific library. Our experiments also demonstrated that both workflows are readily transferrable between facilities.

A progressive loss of protein homeostasis is characteristic of aging and a driver of neurodegeneration. To investigate this process quantitatively, we characterized proteome dynamics during brain aging by using the short-lived vertebrate Nothobranchius furzeri and combining transcriptomics, proteomics and thermal proteome profiling. We found that the 25 correlation between protein and mRNA levels is progressively reduced during aging, and that post-transcriptional mechanisms are responsible for over 40% of these alterations. These changes induce a progressive stoichiometry loss in protein complexes, including ribosomes, which have low thermal stability in brain lysates and whose component proteins are enriched in aggregates found in old brains. Mechanistically, we show that reduced proteasome activity occurs early 30 during brain aging, and is sufficient to induce loss of stoichiometry. Our work thus defines early events in the aging process that can be targeted to prevent loss of protein homeostasis and agerelated neurodegeneration.

Here, we report a comprehensive profiling of sulfur(VI) fluorides (S VI -Fs) as reactive groups for chemical biology applications. S VI -Fs are reactive functionalities that modify lysine, tyrosine, histidine, and serine sidechains. A panel of S VI -Fs were studied with respect to hydrolytic stability and reactivity with nucleophilic amino acid sidechains. The use of S VI -Fs to covalently modify carbonic anhydrase II (CAII) and a range of kinases was then investigated. Finally, the S VI -F panel was used in live cell chemoproteomic workflows, identifying novel protein targets based on the type of S VI -F used. This work highlights how S VI -F reactivity can be used as a tool to expand the liganded proteome.

Complete, reproducible extraction of protein material is essential for comprehensive and unbiased proteome analyses. A current gold standard is single-pot, solid-phase-enhanced sample preparation (SP3), in which organic solvent and magnetic beads are used to denature and capture protein aggregates, with subsequent washes removing contaminants. However, SP3 is dependent on effective protein immobilization onto beads, risks losses during wash steps, and exhibits losses and greater costs at higher protein inputs. Here, we propose solvent precipitation SP3 (SP4) as an alternative to SP3 protein cleanup, capturing acetonitrile-induced protein aggregates by brief centrifugation rather than magnetism—with optional low-cost inert glass beads to simplify handling. SP4 recovered equivalent or greater protein yields for 1–5000 μg preparations and improved reproducibility (median protein R 2 0.99 (SP4) vs 0.97 (SP3)). Deep proteome profiling revealed that SP4 yielded a greater recovery of low-solubility and transmembrane proteins than SP3, benefits to aggregating protein using 80 vs 50% organic solvent, and equivalent recovery by SP4 and S-Trap. SP4 was verified in three other labs across eight sample types and five lysis buffers—all confirming equivalent or improved proteome characterization vs SP3. With near-identical recovery, this work further illustrates protein precipitation as the primary mechanism of SP3 protein cleanup and identifies that magnetic capture risks losses, especially at higher protein concentrations and among more hydrophobic proteins. SP4 offers a minimalistic approach to protein cleanup that provides cost-effective input scalability, the option to omit beads entirely, and suggests important considerations for SP3 applications—all while retaining the speed and compatibility of SP3.

In an effort to identify novel drugs targeting fusion-oncogene induced acute myeloid leukemia (AML), we performed high-resolution proteomic analysis. In AML1-ETO (AE) driven AML we uncovered a de-regulation of phospholipase C (PLC) signaling. We identified PLCgamma 1 (PLCG1) as a specific target of the AE fusion protein which is induced after AE binding to intergenic regulatory DNA elements. Genetic inactivation of PLCG1 in murine and human AML inhibited AML1-ETO dependent self-renewal programs, leukemic proliferation, and leukemia maintenance in vivo. In contrast, PLCG1 was dispensable for normal hematopoietic stem- and progenitor cell function. These findings are extended to and confirmed by pharmacologic perturbation of Ca++-signaling in AML1-ETO AML cells, indicating that the PLCG1 pathway poses an important therapeutic target for AML1-ETO positive leukemic stem cells.