Quantitative analysis of discovery-based proteomic workflows now relies on high-throughput large-scale methods for identification and quantitation of proteins and post-translational modifications. Advancements in label-free quantitative techniques, using either data-dependent or data-independent mass spectrometric acquisitions, have coincided with improved instrumentation featuring greater precision, increased mass accuracy, and faster scan speeds. We recently reported on a new quantitative method called MS1 Filtering (Schilling et al. (2012) Mol. Cell. Proteomics 11, 202-214) for processing data-independent MS1 ion intensity chromatograms from peptide analytes using the Skyline software platform. In contrast, data-independent acquisitions from MS2 scans, or SWATH, can quantify all fragment ion intensities when reference spectra are available. As each SWATH acquisition cycle typically contains an MS1 scan, these two independent label-free quantitative approaches can be acquired in a single experiment. Here, we have expanded the capability of Skyline to extract both MS1 and MS2 ion intensity chromatograms from a single SWATH data-independent acquisition in an Integrated Dual Scan Analysis approach. The performance of both MS1 and MS2 data was examined in simple and complex samples using standard concentration curves. Cases of interferences in MS1 and MS2 ion intensity data were assessed, as were the differentiation and quantitation of phosphopeptide isomers in MS2 scan data. In addition, we demonstrated an approach for optimization of SWATH m/z window sizes to reduce interferences using MS1 scans as a guide. Finally, a correlation analysis was performed on both MS1 and MS2 ion intensity data obtained from SWATH acquisitions on a complex mixture using a linear model that automatically removes signals containing interferences. This work demonstrates the practical advantages of properly acquiring and processing MS1 precursor data in addition to MS2 fragment ion intensity data in a data-independent acquisition (SWATH), and provides an approach to simultaneously obtain independent measurements of relative peptide abundance from a single experiment.

There is an increasing need in biology and clinical medicine to robustly and reliably measure tens to hundreds of peptides and proteins in clinical and biological samples with high sensitivity, specificity, reproducibility, and repeatability. Previously, we demonstrated that LC-MRM-MS with isotope dilution has suitable performance for quantitative measurements of small numbers of relatively abundant proteins in human plasma and that the resulting assays can be transferred across laboratories while maintaining high reproducibility and quantitative precision. Here, we significantly extend that earlier work, demonstrating that 11 laboratories using 14 LC-MS systems can develop, determine analytical figures of merit, and apply highly multiplexed MRM-MS assays targeting 125 peptides derived from 27 cancer-relevant proteins and seven control proteins to precisely and reproducibly measure the analytes in human plasma. To ensure consistent generation of high quality data, we incorporated a system suitability protocol (SSP) into our experimental design. The SSP enabled real-time monitoring of LC-MRM-MS performance during assay development and implementation, facilitating early detection and correction of chromatographic and instrumental problems. Low to subnanogram/ml sensitivity for proteins in plasma was achieved by one-step immunoaffinity depletion of 14 abundant plasma proteins prior to analysis. Median intra- and interlaboratory reproducibility was <20%, sufficient for most biological studies and candidate protein biomarker verification. Digestion recovery of peptides was assessed and quantitative accuracy improved using heavy-isotope-labeled versions of the proteins as internal standards. Using the highly multiplexed assay, participating laboratories were able to precisely and reproducibly determine the levels of a series of analytes in blinded samples used to simulate an interlaboratory clinical study of patient samples. Our study further establishes that LC-MRM-MS using stable isotope dilution, with appropriate attention to analytical validation and appropriate quality control measures, enables sensitive, specific, reproducible, and quantitative measurements of proteins and peptides in complex biological matrices such as plasma.

The plant-specific protein GIGANTEA (GI) controls many developmental and physiological processes, mediating rhythmic post-translational regulation. GI physically binds several proteins implicated in the circadian clock, photoperiodic flowering, and abiotic stress responses. To understand GI's multifaceted function, we aimed to comprehensively and quantitatively identify potential interactors of GI in a time-specific manner, using proteomics on Arabidopsis plants expressing epitope-tagged GI. We detected previously identified (in)direct interactors of GI, as well as proteins implicated in protein folding, or degradation, and a previously uncharacterized transcription factor, CYCLING DOF FACTOR6 (CDF6). We verified CDF6's direct interaction with GI, and ZEITLUPE/FLAVIN-BINDING, KELCH REPEAT, F-BOX 1/LIGHT KELCH PROTEIN 2 proteins, and demonstrated its involvement in photoperiodic flowering. Extending interaction proteomics to time series provides a data resource of candidate protein targets for GI's post-translational control.

Mutations in the glucosylceramidase beta (GBA) gene are strongly associated with neurodegenerative diseases marked by protein aggregation. GBA encodes the lysosomal enzyme glucocerebrosidase, which breaks down glucosylceramide. A common explanation for the link between GBA mutations and protein aggregation is that lysosomal accumulation of glucosylceramide causes impaired autophagy. We tested this hypothesis directly by measuring protein turnover and abundance in Drosophila mutants with deletions in the GBA ortholog Gba1b. Proteomic analyses revealed that known autophagy substrates, which had severely impaired turnover in autophagy-deficient Atg7 mutants, showed little to no overall slowing of turnover or increase in abundance in Gba1b mutants. Likewise, Gba1b mutants did not have the marked impairment of mitochondrial protein turnover seen in mitophagy-deficient parkin mutants. Proteasome activity, microautophagy, and endocytic degradation also appeared unaffected in Gba1b mutants. However, we found striking changes in the turnover and abundance of proteins associated with extracellular vesicles (EVs), which have been proposed as vehicles for the spread of protein aggregates in neurodegenerative disease. These changes were specific to Gba1b mutants and did not represent an acceleration of normal aging. Western blotting of isolated EVs confirmed the increased abundance of EV proteins in Gba1b mutants, and nanoparticle tracking analysis revealed that Gba1b mutants had six times as many EVs as controls. Genetic perturbations of EV production in Gba1b mutants suppressed protein aggregation, demonstrating that the increase in EV abundance contributed to the accumulation of protein aggregates. Together, our findings indicate that glucocerebrosidase deficiency causes pathogenic changes in EV metabolism and may promote the spread of protein aggregates through extracellular vesicles.

Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) is the main method for high-throughput identification and quantification of peptides and inferred proteins. Within this field, data-independent acquisition (DIA) combined with peptide-centric scoring, as exemplified by the technique SWATH-MS, has emerged as a scalable method to achieve deep and consistent proteome coverage across large-scale data sets. We demonstrate that statistical concepts developed for discovery proteomics based on spectrum-centric scoring can be adapted to large-scale DIA experiments that have been analyzed with peptide-centric scoring strategies, and we provide guidance on their application. We show that optimal tradeoffs between sensitivity and specificity require careful considerations of the relationship between proteins in the samples and proteins represented in the spectral library. We propose the application of a global analyte constraint to prevent the accumulation of false positives across large-scale data sets. Furthermore, to increase the quality and reproducibility of published proteomic results, well-established confidence criteria should be reported for the detected peptide queries, peptides and inferred proteins.

Proper centromere function is critical to maintain genomic stability and to prevent aneuploidy, a hallmark of tumors and birth defects. A conserved feature of all eukaryotic centromeres is an essential histone H3 variant called CENP-A that requires a centromere targeting domain (CATD) for its localization. Although proteolysis prevents CENP-A from mislocalizing to euchromatin, regulatory factors have not been identified. Here, we identify an E3 ubiquitin ligase called Psh1 that leads to the degradation of Cse4, the budding yeast CENP-A homolog. Cse4 overexpression is toxic to psh1Δ cells and results in euchromatic localization. Strikingly, the Cse4 CATD is a key regulator of its stability and helps Psh1 discriminate Cse4 from histone H3. Taken together, we propose that the CATD has a previously unknown role in maintaining the exclusive localization of Cse4 by preventing its mislocalization to euchromatin via Psh1-mediated degradation.

Mass spectrometry with data-independent acquisition (DIA) is a promising method to improve the comprehensiveness and reproducibility of targeted and discovery proteomics, in theory by systematically measuring all peptide precursors in a biological sample. However, the analytical challenges involved in discriminating between peptides with similar sequences in convoluted spectra have limited its applicability in important cases, such as the detection of single-nucleotide polymorphisms (SNPs) and alternative site localizations in phosphoproteomics data. We report Specter (https://github.com/rpeckner-broad/Specter), an open-source software tool that uses linear algebra to deconvolute DIA mixture spectra directly through comparison to a spectral library, thus circumventing the problems associated with typical fragment-correlation-based approaches. We validate the sensitivity of Specter and its performance relative to that of other methods, and show that Specter is able to successfully analyze cases involving highly similar peptides that are typically challenging for DIA analysis methods.

Many cancers overexpress one or more of the six human pro-survival BCL2 family proteins to evade apoptosis. To determine which BCL2 protein or proteins block apoptosis in different cancers, we computationally designed three-helix bundle protein inhibitors specific for each BCL2 pro-survival protein. Following in vitro optimization, each inhibitor binds its target with high picomolar to low nanomolar affinity and at least 300-fold specificity. Expression of the designed inhibitors in human cancer cell lines revealed unique dependencies on BCL2 proteins for survival which could not be inferred from other BCL2 profiling methods. Our results show that designed inhibitors can be generated for each member of a closely-knit protein family to probe the importance of specific protein-protein interactions in complex biological processes.

While gene expression profiling has traditionally been the method of choice for large-scale perturbational profiling studies, proteomics has emerged as an effective tool in this context for directly monitoring cellular responses to perturbations. We previously reported a pilot library containing 3400 profiles of multiple perturbations across diverse cellular backgrounds in the reduced-representation phosphoproteome (P100) and chromatin space (Global Chromatin Profiling, GCP). Here, we expand our original dataset to include profiles from a new set of cardiotoxic compounds and from astrocytes, an additional neural cell model, totaling 5300 proteomic signatures. We describe filtering criteria and quality control metrics used to assess and validate the technical quality and reproducibility of our data. To demonstrate the power of the library, we present two case studies where data is queried using the concept of "connectivity" to obtain biological insight. All data presented in this study have been deposited to the ProteomeXchange Consortium with identifiers PXD017458 (P100) and PXD017459 (GCP) and can be queried at https://clue.io/proteomics .

Differentiation into environmentally resistant cysts is required for transmission of the ubiquitous intestinal parasite Giardia lamblia. Encystation in Giardia requires the production, processing and transport of Cyst Wall Proteins (CWPs) in developmentally induced, Golgi-like, Encystation Specific Vesicles (ESVs). Progress through this trafficking pathway can be followed by tracking CWP localization over time. However, there is no recognized system to distinguish the advancing stages of this process which can complete at variable rates depending on how encystation is induced. Here, we propose a staging system for encysting Giardia based on the morphology of CWP1-stained ESVs. We demonstrate the molecular distinctiveness of maturing ESVs at these stages by following GlRab GTPases through encystation. Previously, we established that Giardia's sole Rho family GTPase, GlRac, associates with ESVs and has a role in regulating their maturation and the secretion of their cargo. As a proof of principle, we delineate the relationship between GlRac and ESV stages. Through proteomic studies, we identify putative interactors of GlRac that could be used as additional ESV stage markers. This staging system provides a common descriptor of ESV maturation regardless of the source of encysting cells. Furthermore, the identified set of molecular markers for ESV stages will be a powerful tool for characterizing trafficking mutants that impair ESV maturation and morphology.

Resilience to Alzheimer's disease is an uncommon combination of high disease burden without dementia that offers valuable insights into limiting clinical impact. Here we assessed 43 research participants meeting stringent criteria, 11 healthy controls, 12 resilience to Alzheimer's disease and 20 Alzheimer's disease with dementia and analyzed matched isocortical regions, hippocampus, and caudate nucleus by mass spectrometry-based proteomics. Of 7115 differentially expressed soluble proteins, lower isocortical and hippocampal soluble Aβ levels is a significant feature of resilience when compared to healthy control and Alzheimer's disease dementia groups. Protein co-expression analysis reveals 181 densely-interacting proteins significantly associated with resilience that were enriched for actin filament-based processes, cellular detoxification, and wound healing in isocortex and hippocampus, further supported by four validation cohorts. Our results suggest that lowering soluble Aβ concentration may suppress severe cognitive impairment along the Alzheimer's disease continuum. The molecular basis of resilience likely holds important therapeutic insights.

Skeletal muscle has recently arisen as a regulator of central nervous system (CNS) function and aging, secreting bioactive molecules known as myokines with metabolism-modifying functions in targeted tissues, including the CNS. Here, we report the generation of a transgenic mouse with enhanced skeletal muscle lysosomal and mitochondrial function via targeted overexpression of transcription factor E-B (TFEB). We discovered that the resulting geroprotective effects in skeletal muscle reduce neuroinflammation and the accumulation of tau-associated pathological hallmarks in a mouse model of tauopathy. Muscle-specific TFEB overexpression significantly ameliorates proteotoxicity, reduces neuroinflammation, and promotes transcriptional remodeling of the aged CNS, preserving cognition and memory in aged mice. Our results implicate the maintenance of skeletal muscle function throughout aging in direct regulation of CNS health and disease and suggest that skeletal muscle originating factors may act as therapeutic targets against age-associated neurodegenerative disorders.

The number of publications in the field of chemical cross-linking combined with mass spectrometry (XL-MS) to derive constraints for protein three-dimensional structure modeling and to probe protein-protein interactions has increased during the last years. As the technique is now becoming routine for in vitro and in vivo applications in proteomics and structural biology there is a pressing need to define protocols as well as data analysis and reporting formats. Such consensus formats should become accepted in the field and be shown to lead to reproducible results. This first, community-based harmonization study on XL-MS is based on the results of 32 groups participating worldwide. The aim of this paper is to summarize the status quo of XL-MS and to compare and evaluate existing cross-linking strategies. Our study therefore builds the framework for establishing best practice guidelines to conduct cross-linking experiments, perform data analysis, and define reporting formats with the ultimate goal of assisting scientists to generate accurate and reproducible XL-MS results.

Changes in mitochondrial function with age vary between different muscle types, and mechanisms underlying this variation remain poorly defined. We examined whether the rate of mitochondrial protein turnover contributes to this variation. Using heavy label proteomics, we measured mitochondrial protein turnover and abundance in slow-twitch soleus (SOL) and fast-twitch extensor digitorum longus (EDL) from young and aged mice. We found that mitochondrial proteins were longer lived in EDL than SOL at both ages. Proteomic analyses revealed that age-induced changes in protein abundance differed between EDL and SOL with the largest change being increased mitochondrial respiratory protein content in EDL. To determine how altered mitochondrial proteomics affect function, we measured respiratory capacity in permeabilized SOL and EDL. The increased mitochondrial protein content in aged EDL resulted in reduced complex I respiratory efficiency in addition to increased complex I-derived H2 O2 production. In contrast, SOL maintained mitochondrial quality, but demonstrated reduced respiratory capacity with age. Thus, the decline in mitochondrial quality with age in EDL was associated with slower protein turnover throughout life that may contribute to the greater decline in mitochondrial dysfunction in this muscle. Furthermore, mitochondrial-targeted catalase protected respiratory function with age suggesting a causal role of oxidative stress. Our data clearly indicate divergent effects of age between different skeletal muscles on mitochondrial protein homeostasis and function with the greatest differences related to complex I. These results show the importance of tissue-specific changes in the interaction between dysregulation of respiratory protein expression, oxidative stress, and mitochondrial function with age.

Panorama is a web application for storing, sharing, analyzing, and reusing targeted assays created and refined with Skyline,1 an increasingly popular Windows client software tool for targeted proteomics experiments. Panorama allows laboratories to store and organize curated results contained in Skyline documents with fine-grained permissions, which facilitates distributed collaboration and secure sharing of published and unpublished data via a web-browser interface. It is fully integrated with the Skyline workflow and supports publishing a document directly to a Panorama server from the Skyline user interface. Panorama captures the complete Skyline document information content in a relational database schema. Curated results published to Panorama can be aggregated and exported as chromatogram libraries. These libraries can be used in Skyline to pick optimal targets in new experiments and to validate peak identification of target peptides. Panorama is open-source and freely available. It is distributed as part of LabKey Server,2 an open source biomedical research data management system. Laboratories and organizations can set up Panorama locally by downloading and installing the software on their own servers. They can also request freely hosted projects on https://panoramaweb.org , a Panorama server maintained by the Department of Genome Sciences at the University of Washington.

Phosphorylation regulates yeast spindle pole body (SPB) duplication and separation and likely regulates microtubule nucleation. We report a phosphoproteomic analysis using tandem mass spectrometry of enriched Saccharomyces cerevisiae SPBs for two cell cycle arrests, G1/S and the mitotic checkpoint, expanding on previously reported phosphoproteomic data sets. We present a novel phosphoproteomic state of SPBs arrested in G1/S by a cdc4-1 temperature-sensitive mutation, with particular focus on phosphorylation events on the γ-tubulin small complex (γ-TuSC). The cdc4-1 arrest is the earliest arrest at which microtubule nucleation has occurred at the newly duplicated SPB. Several novel phosphorylation sites were identified in G1/S and during mitosis on the microtubule nucleating γ-TuSC. These sites were analyzed in vivo by fluorescence microscopy and were shown to be required for proper regulation of spindle length. Additionally, in vivo analysis of two mitotic sites in Spc97 found that phosphorylation of at least one of these sites is required for progression through the cell cycle. This phosphoproteomic data set not only broadens the scope of the phosphoproteome of SPBs, it also identifies several γ-TuSC phosphorylation sites that influence microtubule formation.

Spectral counting methods provide an easy means of identifying proteins with differing abundances between complex mixtures using shotgun proteomics data. The crux spectral-counts command, implemented as part of the Crux software toolkit, implements four previously reported spectral counting methods, the spectral index (SI(N)), the exponentially modified protein abundance index (emPAI), the normalized spectral abundance factor (NSAF), and the distributed normalized spectral abundance factor (dNSAF).

Inorganic polyphosphate (polyP) is an ancient, ubiquitous, and well-conserved polymer which is present in all the studied organisms. It is formed by individual subunits of orthophosphate which are linked by structurally similar bonds and isoenergetic to those found in ATP. While the metabolism and the physiological roles of polyP have already been described in some organisms, including bacteria and yeast, the exact role of this polymer in mammalian physiology still remains poorly understood. In these organisms, polyP shows a co-localization with mitochondria, and its role as a key regulator of the stress responses, including the maintenance of appropriate bioenergetics, has already been demonstrated by our group and others. Here, using Wild-type (Wt) and MitoPPX (cells enzymatically depleted of mitochondrial polyP) SH-SY5Y cells, we have conducted a comprehensive study of the status of cellular physiology, using proteomics and metabolomics approaches. Our results suggest a clear dysregulation of mitochondrial physiology, especially of bioenergetics, in MitoPPX cells when compared with Wt cells. Moreover, the effects induced by the enzymatic depletion of polyP are similar to those present in the mitochondrial dysfunction that is observed in neurodegenerative disorders and in neuronal aging. Based on our findings, the metabolism of mitochondrial polyP could be a valid and innovative pharmacological target in these conditions.

Transcription factors and other chromatin-associated proteins are difficult to quantify comprehensively. Here, we combine facile nuclear sub-fractionation with data-independent acquisition mass spectrometry to achieve rapid, sensitive, and highly parallel quantification of the nuclear proteome in human cells. We apply this approach to quantify the response to acute degradation of BET bromodomains, revealing unexpected chromatin regulatory dynamics. The method is simple and enables system-level study of previously inaccessible chromatin and genome regulators.

Microproteins (MPs) are a potentially rich source of uncharacterized metabolic regulators. Here, we use ribosome profiling (Ribo-seq) to curate 3,877 unannotated MP-encoding small ORFs (smORFs) in primary brown, white, and beige mouse adipocytes. Of these, we validated 85 MPs by proteomics, including 33 circulating MPs in mouse plasma. Analyses of MP-encoding mRNAs under different physiological conditions (high-fat diet) revealed that numerous MPs are regulated in adipose tissue in vivo and are co-expressed with established metabolic genes. Furthermore, Ribo-seq provided evidence for the translation of Gm8773, which encodes a secreted MP that is homologous to human and chicken FAM237B. Gm8773 is highly expressed in the arcuate nucleus of the hypothalamus, and intracerebroventricular administration of recombinant mFAM237B showed orexigenic activity in obese mice. Together, these data highlight the value of this adipocyte MP database in identifying MPs with roles in fundamental metabolic and physiological processes such as feeding.