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Deubiquitinases (DUBs) antagonize protein ubiquitination by removing ubiquitin from substrates. Identifying the physiological substrates of each DUB is critical for understanding DUB function and the principles that govern the specificity of this class of enzymes. Since multiple DUBs can act on the same substrate, it can be challenging to identify substrates using inactivating a single enzyme. Here, we outline a method that enables the identification of proteins whose stability depends on DUB activity and an approach to profile DUB specificity in Xenopus egg extract. By coupling broad DUB inhibition with quantitative proteomics, we circumvent DUB redundancy to identify DUB substrates. By adding back recombinant DUBs individually to the extract, we pinpoint DUBs sufficient to counteract proteasomal degradation of these newly identified substrates. We apply this method to Xenopus egg extract but suggest that it can also be adapted to other cell lysates.

Photoreceptor cells are highly susceptible to oxidative-stress-induced damage due to their high metabolic rate. Oxidative stress plays a key role in driving pathological events in several different ocular diseases, which lead to retinal degeneration and ultimately blindness. A growing number of studies have been performed to understand downstream events caused by ROS induced oxidative stress in photoreceptor cells; however, the underlying mechanisms of ROS toxicity are not fully understood. To shed light on ROS induced downstream pathological events, we employed a tandem mass tag (TMT) labelling-based quantitative mass-spectrometric approach to determine proteome changes in 661W photoreceptor cells following oxidative stress induction via the application of different concentrations of H2O2 at different time points. Overall, 5920 proteins were identified and quantified, and 450 differentially expressed proteins (DEPs) were identified, which were altered in a dose and time dependent manner in all treatment groups compared to the control group. These proteins were involved in several biological pathways, including spliceosome and ribosome response, activated glutathione metabolism, decreased ECM-receptor interaction, oxidative phosphorylation, abnormally regulated lysosome, apoptosis, and ribosome biogenesis. Our results highlighted ECM receptor interaction, oxidative phosphorylation and spliceosome pathways as the major targets of oxidative stress that might mediate vascular dysfunction and cellular senescence.

INTRODUCTION. Protein phosphorylation is a primary mechanism of signal transduction in cellular systems. Isobaric tagging can be used to investigate alterations in phosphorylation events in sample multiplexing experiments where quantification extends across all conditions. As such, innovations in tandem mass tag methods can facilitate the expansion of the depth and breadth of phosphoproteomics analyses. AREAS COVERED. This review discusses the current state of tandem mass tag-centric phosphoproteomics and highlights advances in reagent chemistry, instrumentation, data acquisition, and data analysis. We stress that approaches for phosphoproteomic investigations require high-specificity enrichment, sensitive detection, and accurate phosphorylation site localization. EXPERT OPINION. Tandem mass tag-centric phosphoproteomics will continue to be an important conduit for our understanding of signal transduction in living organisms. We anticipate that progress in phosphopeptide enrichment methodologies, enhancements in instrumentation and data acquisition technologies, and further refinements in analytical strategies will be key to the discovery of biologically relevant data from phosphoproteomics studies.

Mass-spectrometry-based phosphoproteomics has become indispensable for understanding cellular signaling in complex biological systems. Despite the central role of protein phosphorylation, the field still lacks inexpensive, regenerable, and diverse phosphopeptides with ground-truth phosphorylation positions. Here, we present Iterative Synthetically Phosphorylated Isomers (iSPI), a proteome-scale library of human-derived phosphoserine-containing phosphopeptides that is inexpensive, regenerable, and diverse, with precisely known positions of phosphorylation. We demonstrate possible uses of iSPI, including use as a phosphopeptide standard, a tool to evaluate and optimize phosphorylation-site localization algorithms, and a benchmark to compare performance across data analysis pipelines. We also present AScorePro, an updated version of the AScore algorithm specifically optimized for phosphorylation-site localization in higher energy fragmentation spectra, and the FLR viewer, a web tool for phosphorylation-site localization, to enable community use of the iSPI resource. iSPI and its associated data constitute a useful, multi-purpose resource for the phosphoproteomics community.

Summary Genetically diverse mouse populations are powerful tools for characterizing the regulation of the proteome and its relationship to whole-organism phenotypes. We used mass spectrometry to profile and quantify the abundance of 6,798 proteins in liver tissue from mice of both sexes across 58 Collaborative Cross (CC) inbred strains. We previously collected liver proteomics data from the related Diversity Outbred (DO) mice and their founder strains. We show concordance across the proteomics datasets despite being generated from separate experiments, allowing comparative analysis. We map protein abundance quantitative trait loci (pQTLs), identifying 1,087 local and 285 distal in the CC mice and 1,706 local and 414 distal in the DO mice. We find that regulatory effects on individual proteins are conserved across the mouse populations, in particular for local genetic variation and sex differences. In comparison, proteins that form complexes are often co-regulated, displaying varying genetic architectures, and overall show lower heritability and map fewer pQTLs. We have made this resource publicly available to enable quantitative analyses of the regulation of the proteome.

Angiotensin II type 1 receptors (AT1Rs) are one of the most widely studied G-protein-coupled receptors. To fully appreciate the diversity in cellular signaling profiles activated by AT1R transducer-biased ligands, we utilized peroxidase-catalyzed proximity labeling to capture proteins in close proximity to AT1Rs in response to six different ligands: angiotensin II (full agonist), S1I8 (partial agonist), TRV055 and TRV056 (G-protein-biased agonists), and TRV026 and TRV027 (β-arrestin-biased agonists) at 90 s, 10 min, and 60 min after stimulation (ProteomeXchange Identifier PXD023814). We systematically analyzed the kinetics of AT1R trafficking and determined that distinct ligands lead AT1R to different cellular compartments for downstream signaling activation and receptor degradation/recycling. Distinct proximity labeling of proteins from a number of functional classes, including GTPases, adaptor proteins, and kinases, was activated by different ligands suggesting unique signaling and physiological roles of the AT1R. Ligands within the same class, that is, either G-protein-biased or β-arrestin-biased, shared high similarity in their labeling profiles. A comparison between ligand classes revealed distinct signaling activation such as greater labeling by G-protein-biased ligands on ESCRT-0 complex proteins that act as the sorting machinery for ubiquitinated proteins. Our study provides a comprehensive analysis of AT1R receptor-trafficking kinetics and signaling activation profiles induced by distinct classes of ligands.

The development of the TMTpro-16plex series expanded the breadth of commercial isobaric tagging reagents by nearly 50% over classic TMT-11plex. In addition to the described 16plex reagents, the proline-based TMTpro molecule can accommodate two additional combinations of heavy carbon and nitrogen isotopes. Here, we introduce the final two labeling reagents, TMTpro-134C and TMTpro-135N, which permit the simultaneous global protein profiling of 18 samples with essentially no missing values. For example, six conditions with three biological replicates can now be perfectly accommodated. We showcase the 18plex reagent set by profiling the proteome and phosphoproteome of a pair of isogenic mammary epithelial cell lines under three conditions in triplicate. We compare the depth and quantitative performance of this data set with a TMTpro-16plex experiment in which two samples were omitted. Our analysis revealed similar numbers of quantified peptides and proteins, with high quantitative correlation. We interrogated further the TMTpro-18plex data set by highlighting changes in protein abundance profiles under different conditions in the isogenic cell lines. We conclude that TMTpro-18plex further expands the sample multiplexing landscape, allowing for complex and innovative experimental designs.

Isobaric labeling has rapidly become a predominant strategy for proteome-wide abundance measurements. Coupled to mass spectrometry, sample multiplexing techniques using isobaric labeling are unparalleled for profiling proteins and posttranslational modifications across multiple samples in a single experiment. Here, I highlight aspects of isobaric labeling in the context of expanding the breadth of multiplexing, improving quantitative accuracy and proteome depth, and developing a wide range of diverse applications. I underscore two facets that enhance quantitative accuracy and reproducibility, specifically the availability of quality control standards for isobaric labeling experiments and the evolution of data acquisition methods. I also emphasize the necessity for standardized methodologies, particularly for emerging high-throughput workflows. Future developments in sample multiplexing will further strengthen the importance of isobaric labeling for comprehensive proteome profiling.

The SH-SY5Y cell line is often used as a surrogate for neurons in cell-based studies. This cell line is frequently differentiated with all-trans retinoic acid (ATRA) over a 7-day period, which confers neuron-like properties to the cells. However, no analysis of proteome remodeling has followed the progress of this transition. Here, we quantitatively profiled over 9400 proteins across a 7-day treatment with retinoic acid using state-of-the-art mass spectrometry-based proteomics technologies, including FAIMS, real-time database searching, and TMTpro16 sample multiplexing. Gene ontology analysis revealed that categories with the highest increases in protein abundance were related to the plasma membrane/extracellular space. To showcase our data set, we surveyed the protein abundance profiles linked to neurofilament bundle assembly, neuron projections, and neuronal cell body formation. These proteins exhibited increases in abundance level, yet we observed multiple patterns among the queried proteins. The data presented represent a rich resource for investigating temporal protein abundance changes in SH-SY5Y cells differentiated with retinoic acid. Moreover, the sample preparation and data acquisition strategies used here can be readily applied to any analogous cell line differentiation analysis.

Mammalian cells reorganize their proteomes in response to nutrient stress through translational suppression and degradative mechanisms using the proteasome and autophagy systems1,2. Ribosomes are central targets of this response, as they are responsible for translation and subject to lysosomal turnover during nutrient stress3–5. The abundance of ribosomal (r)-proteins (around 6% of the proteome; 107 copies per cell)6,7 and their high arginine and lysine content has led to the hypothesis that they are selectively used as a source of basic amino acids during nutrient stress through autophagy4,7. However, the relative contributions of translational and degradative mechanisms to the control of r-protein abundance during acute stress responses is poorly understood, as is the extent to which r-proteins are used to generate amino acids when specific building blocks are limited7. Here, we integrate quantitative global translatome and degradome proteomics8 with genetically encoded Ribo–Keima5 and Ribo–Halo reporters to interrogate r-protein homeostasis with and without active autophagy. In conditions of acute nutrient stress, cells strongly suppress the translation of r-proteins, but, notably, r-protein degradation occurs largely through non-autophagic pathways. Simultaneously, the decrease in r-protein abundance is compensated for by a reduced dilution of pre-existing ribosomes and a reduction in cell volume, thereby maintaining the density of ribosomes within single cells. Withdrawal of basic or hydrophobic amino acids induces translational repression without differential induction of ribophagy, indicating that ribophagy is not used to selectively produce basic amino acids during acute nutrient stress. We present a quantitative framework that describes the contributions of biosynthetic and degradative mechanisms to r-protein abundance and proteome remodelling in conditions of nutrient stress. During nutrient stress, ribosomal protein abundance is regulated primarily by translational and non-autophagic degradative mechanisms, but ribosome density per cell is largely maintained by reductions in cell volume and rates of cell division.

The rise of sample multiplexing in quantitative proteomics for the dissection of complex phenotypic comparisons has been advanced by the development of ever more sensitive and robust instrumentation. Here, we evaluated the utility of the Orbitrap Eclipse Tribrid mass spectrometer (advanced quadrupole filter, optimized FTMS scan overhead) and new instrument control software features (Precursor Fit filtering, TurboTMT and Real-time Peptide Search filtering). Multidimensional comparisons of these novel features increased total peptide identifications by 20% for SPS-MS(3) methods and 14% for HRMS(2) methods. Importantly Real-time Peptide Search filtering enabled a ∼2× throughput improvement for quantification. Across the board, these sensitivity increases were attained without sacrificing quantitative accuracy. New hardware and software features enable more efficient characterization in pursuit of comparative whole proteome insights.

Sample multiplexing using isobaric tagging is a powerful strategy for proteome-wide protein quantification. One major caveat of isobaric tagging is ratio compression that results from the isolation, fragmentation, and quantification of coeluting, near-isobaric peptides, a phenomenon typically referred to as “ion interference”. A robust platform to ensure quality control, optimize parameters, and enable comparisons across samples is essential as new instrumentation and analytical methods evolve. Here, we introduce TKO-iQC, an integrated platform consisting of the Triple Knockout (TKO) yeast digest standard and an automated web-based database search and protein profile visualization application. We highlight two new TKO standards based on the TMTpro reagent (TKOpro9 and TKOpro16) as well as an updated TKO Viewing Tool, TVT2.0. TKO-iQC greatly facilitates the comparison of instrument performance with a straightforward and streamlined workflow.

Isobaric labeling empowers proteome-wide expression measurements simultaneously across multiple samples. Here an expanded set of 16 isobaric reagents based on an isobutyl-proline immonium ion reporter structure (TMTpro) is presented. These reagents have similar characteristics to existing tandem mass tag reagents but with increased fragmentation efficiency and signal. In a proteome-scale example dataset, we compared eight common cell lines with and without Torin1 treatment with three replicates, quantifying more than 8,800 proteins (mean of 7.5 peptides per protein) per replicate with an analysis time of only 1.1 h per proteome. Finally, we modified the thermal stability assay to examine proteome-wide melting shifts after treatment with DMSO, 1 or 20 µM staurosporine with five replicates. This assay identified and dose-stratified staurosporine binding to 228 cellular kinases in just one, 18-h experiment. TMTpro reagents allow complex experimental designs—all with essentially no missing values across the 16 samples and no loss in quantitative integrity. A set of isobaric labeling reagents called TMTpro enables deep quantitative comparisons of proteome measurements across 16 samples.

Degradation and recycling of plasma membrane proteins occurs via the endolysosomal system, wherein endosomes bud into the cytosol from the plasma membrane and subsequently mature into degradative lysosomal compartments. While methods have been developed for rapid selective capture of lysosomes (Lyso-IP), analogous methods for isolation of early endosome intermediates are lacking. Here, we develop an approach for rapid isolation of early/sorting endosomes through affinity capture of the early endosome-associated protein EEA1 (Endo-IP) and provide proteomic and lipidomic snapshots of EEA1-positive endosomes in action. We identify recycling, regulatory and membrane fusion complexes, as well as candidate cargo, providing a proteomic landscape of early/sorting endosomes. To demonstrate the utility of the method, we combined Endo- and Lyso-IP with multiplexed targeted proteomics to provide a spatial digital snapshot of amyloid precursor protein (APP) processing by β and γ-Secretases, which produce amyloidogenic Aβ species, and quantify small molecule modulation of Secretase action on endosomes. We anticipate that the Endo-IP approach will facilitate systematic interrogation of processes that are coordinated on EEA1-positive endosomes.

Protein phosphorylation is a central mechanism of cellular signal transduction in living organisms. Phosphoproteomic studies systematically catalogue and characterize alterations in phosphorylation states across multiple cellular conditions and are often incorporated into global proteomics experiments. Previously, we found that spin column-based Fe(3+)-NTA enrichment integrated well with our workflow but remained a bottleneck for methods that require higher throughput or a scale that is beyond the capacity of these columns. Here, we compare our well-established spin column-based enrichment strategy with one encompassing magnetic beads. Our data show little difference when using either method in terms of the number of identified phosphopeptides as well as their physicochemical properties. In all, we illustrate how the potentially scalable and automation-friendly magnetic Fe(3+)-NTA beads can seamlessly substitute spin column-based Fe(3+)-NTA agarose beads for global phosphoproteome profiling.

Thioredoxin/glutathione reductase (TXNRD3) is a selenoprotein composed of thioredoxin reductase and glutaredoxin domains. This NADPH-dependent thiol oxidoreductase evolved through gene duplication within the Txnrd family, is expressed in the testes, and can reduce both thioredoxin and glutathione in vitro; however, the function of this enzyme remains unknown. To characterize the function of TXNRD3 in vivo, we generated a strain of mice bearing deletion of Txnrd3 gene. We show that these Txnrd3 knockout mice are viable and without discernable gross phenotypes, and also that TXNRD3 deficiency leads to fertility impairment in male mice. We found that Txnrd3 knockout animals exhibited a lower fertilization rate in vitro, a sperm movement phenotype, and an altered thiol redox status in sperm cells. Proteomic analyses further revealed a broad range of substrates reduced by TXNRD3 during sperm maturation, presumably as a part of sperm quality control. Taken together, these results show that TXNRD3 plays a critical role in male reproduction via the thiol redox control of spermatogenesis.

Cell state changes are associated with proteome remodeling to serve newly emergent cell functions. Here, we show that NGN2-driven conversion of human embryonic stem cells to induced neurons (iNeurons) is associated with increased PINK1-independent mitophagic flux that is temporally correlated with metabolic reprogramming to support oxidative phosphorylation. Global multiplex proteomics during neurogenesis revealed large-scale remodeling of functional modules linked with pluripotency, mitochondrial metabolism, and proteostasis. Differentiation-dependent mitophagic flux required BNIP3L and its LC3 interacting region (LIR) motif, and BNIP3L also promoted mitophagy in dopaminergic neurons. Proteomic analysis of ATG12(−/−) iNeurons revealed accumulation of endoplasmic reticulum, Golgi and mitochondria during differentiation, indicative of widespread organelle remodeling during neurogenesis. This work reveals broad organelle remodeling of membrane-bound organelles during NGN2-driven neurogenesis via autophagy, identifies BNIP3L’s central role in programmed mitophagic flux, and provides a proteomic resource for elucidating how organelle remodeling and autophagy alter the proteome during changes in cell state.

Summary Parkinson's disease (PD) is a complex and highly variable neurodegenerative disease. Familial PD is caused by mutations in several genes with diverse and mostly unknown functions. It is unclear how dysregulation of these genes results in the relatively selective death of nigral dopaminergic neurons (DNs). To address this question, we modeled PD by knocking out the PD genes PARKIN (PRKN), DJ-1 (PARK7), and ATP13A2 (PARK9) in independent isogenic human pluripotent stem cell (hPSC) lines. We found increased levels of oxidative stress in all PD lines. Increased death of DNs upon differentiation was found only in the PARKIN knockout line. Using quantitative proteomics, we observed dysregulation of mitochondrial and lysosomal function in all of the lines, as well as common and distinct molecular defects caused by the different PD genes. Our results suggest that precise delineation of PD subtypes will require evaluation of molecular and clinical data., Highlights • CRISPR knockin of reporter in TH locus allows live tracking and isolation of DNs • Large-scale 3D midbrain DN differentiation using spinner flask culture • Phenotypic comparison of isogenic DNs harboring knockouts of PARKIN, DJ-1, or ATP13A2 • Transcriptomics and quantitative proteomics studies determine common and distinct PD pathways, In this article, Ahfeldt, Rubin, and colleagues model Parkinson's disease (PD) in human pluripotent stem cells by knocking out PARKIN, DJ-1, or ATP13A2. They report increased levels of oxidative stress in all PD lines and death of dopaminergic neurons in the PARKIN-KO. Using transcriptomics and quantitative proteomics approaches they determine common and distinct molecular defects caused by different PD genes.

MCL-1 is an anti-apoptotic BCL-2 family protein essential for survival of diverse cell types and is a major driver of cancer and chemoresistance. The mechanistic basis for the oncogenic supremacy of MCL-1 among its anti-apoptotic homologs is unclear and implicates physiologic roles of MCL-1 beyond apoptotic suppression. Here we find that MCL-1-dependent hematologic cancer cells specifically rely on fatty acid oxidation (FAO) as a fuel source because of metabolic wiring enforced by MCL-1 itself. We demonstrate that FAO regulation by MCL-1 is independent of its anti-apoptotic activity, based on metabolomic, proteomic, and genomic profiling of MCL-1-dependent leukemia cells lacking an intact apoptotic pathway. Genetic deletion of Mcl-1 results in transcriptional downregulation of FAO pathway proteins such that glucose withdrawal triggers cell death despite apoptotic blockade. Our data reveal that MCL-1 is a master regulator of FAO, rendering MCL-1-driven cancer cells uniquely susceptible to treatment with FAO inhibitors.

Induced pluripotent stem cells generated from patients with geographic atrophy as well as healthy individuals were differentiated to retinal pigment epithelium (RPE) cells. By integrating transcriptional profiles of 127,659 RPE cells generated from 43 individuals with geographic atrophy and 36 controls with genotype data, we identified 439 expression Quantitative Trait (eQTL) loci in cis that were associated with disease status and specific to subpopulations of RPE cells. We identified loci linked to two genes with known associations with geographic atrophy - PILRB and PRPH2, in addition to 43 genes with significant genotype x disease interactions that are candidates for novel genetic associations for geographic atrophy. On a transcriptome-only level, we identified molecular pathways significantly upregulated in geographic atrophy-RPE including in extracellular cellular matrix reorganisation, neurodegeneration, and mitochondrial functions. We subsequently implemented a large-scale proteomics analysis, confirming modification in proteins associated with these pathways. We also identified six significant protein (p) QTL that regulate protein expression in the RPE cells and in geographic atrophy - two of which share variants with cis-eQTL. Transcriptome-wide association analysis identified genes at loci previously associated with age-related macular degeneration. Further analysis conditional on disease status, implicated statistically significant RPE-specific eQTL. This study uncovers important differences in RPE homeostasis associated with geographic atrophy.

Removal of damaged organelles via the process of selective autophagy constitutes a major form of cellular quality control. Damaged organelles are recognized by a dedicated surveillance machinery, leading to the assembly of an autophagosome around the damaged organelle, prior to fusion with the degradative lysosomal compartment. Lysosomes themselves are also prone to damage and are degraded through the process of lysophagy. While early steps involve recognition of ruptured lysosomal membranes by glycan-binding Galectins and ubiquitylation of transmembrane lysosomal proteins, many steps in the process, and their inter-relationships, remain poorly understood, including the role and identity of cargo receptors required for completion of lysophagy. Here, we employ quantitative organelle capture and proximity biotinylation proteomics of autophagy adaptors, cargo receptors, and Galectins in response to acute lysosomal damage, thereby revealing the landscape of lysosomal proteome remodeling during lysophagy. Among proteins dynamically recruited to damaged lysosomes were ubiquitin-binding autophagic cargo receptors. Using newly developed lysophagic flux reporters including Lyso-Keima, we demonstrate that TAX1BP1, together with its associated kinase TBK1, are both necessary and sufficient to promote lysophagic flux in both Hela cells and induced neurons (iNeurons). While the related receptor OPTN can drive damage-dependent lysophagy when overexpressed, cells lacking either OPTN or CALCOCO2 still maintain significant lysophagic flux in HeLa cells. Mechanistically, TAX1BP1-driven lysophagy requires its N-terminal SKICH domain, which binds both TBK1 and the autophagy regulatory factor RB1CC1, and requires upstream ubiquitylation events for efficient recruitment and lysophagic flux. These results identify TAX1BP1 as a central component in the lysophagy pathway and provide a proteomic resource for future studies of the lysophagy process.

Targeted mass spectrometry-based assays typically rely on previously acquired large data sets for peptide target selection. Such repositories are widely available for unlabeled peptides. However, they are less common for isobaric tagged peptides. Here we have assembled two series of six data sets originating from a mouse embryonic fibroblast cell line (NIH/3T3). One series is of peptides derived from a tryptic digest of a whole cell proteome and a second from enriched phosphopeptides. These data sets encompass three labeling approaches (unlabeled, TMT11-labeled, and TMTpro16-labeled) and two data acquisition strategies (ion trap MS2 with and without FAIMS-based gas phase separation). We identified a total of 1 509 526 peptide-spectrum matches which covered 11 482 proteins from the whole cell proteome tryptic digest, and 188 849 phosphopeptides from the phosphopeptide enrichment. The data sets were of similar depth, and while overlap across data sets was modest, protein overlap was high, thus reinforcing the comprehensiveness of these data sets. The data also supported FAIMS as a means to increase data set depth. These data sets provide a rich resource of peptides that may be used as starting points for targeted assays. Future data sets may be compiled for any genome-sequenced organism using the technologies and strategies highlighted herein. The data have been deposited in the ProteomeXchange Consortium with data set identifier PXD024298.

The development of streamlined and high-throughput sample processing workflows is important for capitalizing on emerging advances and innovations in mass spectrometry-based applications. While the adaptation of new technologies and improved methodologies is fast paced, automation of upstream sample processing often lags. Here we have developed and implemented a semiautomated paramagnetic bead-based platform for isobaric tag sample preparation. We benchmarked the robot-assisted platform by comparing the protein abundance profiles of six common parental laboratory yeast strains in triplicate TMTpro16-plex experiments against an identical set of experiments in which the samples were manually processed. Both sets of experiments quantified similar numbers of proteins and peptides with good reproducibility. Using these data, we constructed an interactive website to explore the proteome profiles of six yeast strains. We also provide the community with open-source templates for automating routine proteomics workflows on an opentrons OT-2 liquid handler. The robot-assisted platform offers a versatile and affordable option for reproducible sample processing for a wide range of protein profiling applications.

Nicotine is a prominent active compound in tobacco and many smoking cessation products. Some of the biological effects of nicotine are well documented in in vitro and in vivo systems; however, data are scarce concerning the time-dependent changes on protein and phosphorylation events in response to nicotine. Here, we profiled the proteomes of SH-SY5Y and A549 cell lines subjected to acute (15 min, 1 h and 4 h) or chronic (24 h, 48 h) nicotine exposures. We used sample multiplexing (TMTpro16) and quantified more than 9000 proteins and over 7000 phosphorylation events per cell line. Among our findings, we determined a decrease in mitochondrial protein abundance for SH-SY5Y, while we detected alterations in several immune pathways, such as the complement system, for A549 following nicotine treatment. We also explored the proposed association between smoking (specifically nicotine) and SARS-CoV2. Here, we found several host proteins known to interact with viral proteins that were affected by nicotine in a time dependent manner. This dataset can be mined further to investigate the potential role of nicotine in different biological contexts. SIGNIFICANCE: Smoking is a major public health issue that is associated with several serious chronic, yet preventable diseases, including stroke, heart disease, type 2 diabetes, cancer, and susceptibility to infection. Tobacco smoke is a complex mixture of thousands of different compounds, among which nicotine is the main addictive compound. The biological effects of nicotine have been reported in several models, however very little data are available concerning the temporal proteomic and phosphoproteomic changes in response to nicotine. Here, we provide a dataset exploring the potential role of nicotine on different biological processes over time, including implications in the study of SARS-CoV2.

Isobaric tag-based sample multiplexing strategies are extensively used for global protein abundance profiling. However, such analyses are often confounded by ratio compression resulting from the co-isolation, co-fragmentation, and co-quantification of co-eluting peptides, termed “interference.” Recent analytical strategies incorporating ion mobility and real-time database searching have helped to alleviate interference, yet further assessment is needed. Here, we present the strain-specific peptide (SSP) interference reference sample, a tandem mass tag (TMT)-pro-labeled quality control that leverages the genetic variation in the proteomes of eight phylogenetically divergent mouse strains. Typically, a peptide with a missense mutation has a different mass and retention time than the reference or native peptide. TMT reporter ion signal for the native peptide in strains that encode the mutant peptide suggests interference which can be quantified and assessed using the interference-free index (IFI). We introduce the SSP by investigating interference in three common data acquisition methods and by showcasing improvements in the IFI when using ion mobility-based gas-phase fractionation. In addition, we provide a user-friendly, online viewer to visualize the data and streamline the calculation of the IFI. The SSP will aid in developing and optimizing isobaric tag-based experiments.

Stable isotope labeling is a leading strategy for mass-spectrometry-based peptide quantification. Whereas TMTpro isobaric tagging can quantify up to 16 multiplexed samples in a single experiment, nonisobaric, yet chromatographically indistinguishable, variants of TMTpro reagents can be used in conjunction with the isobaric tag series for various peptide-targeting applications. Here we test the performance of two nonisobaric TMTpro variants, a stable-isotope-free TMTproZero tag and a nearly fully isotope-labeled "super-heavy" variant, shTMTpro, in a targeted assay for peptides of charge state 4+. We label each peptide with TMTproZero or Super Heavy TMTpro reagents and separately spike each peptide into a TMTpro16-labeled background (equal amount of peptide across all 16 channels). We observe that the expected 1:1 reporter ion ratio is distorted when a TMTproZero-labeled peptide is used; however, we note no such interference when shTMTpro substitutes the TMTproZero tag. Our data suggest that using the Super Heavy TMTpro reagent is an improvement over the TMTproZero reagent for the accurate quantification of high-charge-state peptides for trigger-based multiplexed assays.

The past decade revealed that cell identity changes, such as dedifferentiation or transdifferentiation, accompany the insulin-producing β-cell decay in most diabetes conditions. Mapping and controlling the mechanisms governing these processes is, thus, extremely valuable for managing the disease progression. Extracellular glucose is known to influence cell identity by impacting the redox balance. Here, we use global proteomics and pathway analysis to map the response of differentiating human pancreatic progenitors to chronically increased in vitro glucose levels. We show that exogenous high glucose levels impact different protein subsets in a concentration-dependent manner. In contrast, regardless of concentration, glucose elicits an antipodal effect on the proteome landscape, inducing both beneficial and detrimental changes in regard to achieving the desired islet cell fingerprint. Furthermore, we identified that only a subgroup of these effects and pathways are regulated by changes in redox balance. Our study highlights a complex effect of exogenous glucose on differentiating pancreas progenitors characterized by a distinct proteome signature. publishedVersion

Poison frogs sequester their chemical defenses from their diet of leaf litter arthropods for defense against predation. Little is known about poison frog physiological adaptations that confer this unusual ability to bioaccumulate dietary alkaloids from the intestines to skin glands for storage. We conducted an alkaloid-feeding experiment with the Diablito poison frog (Oophaga sylvatica) to determine how quickly toxins are accumulated and how toxins impact frog physiology using quantitative proteomics. Diablito frogs were able to rapidly accumulate the alkaloid decahydroquinoline to the skin storage glands within four days of dietary exposure, with decahydroquinoline also detected in the intestines and liver. Alkaloid exposure impacted tissue physiology, with protein abundance shifting in the intestines, liver, and skin. Many proteins that increased in abundance with toxin accumulation are plasma glycoproteins, including components of the complement system and the toxin-binding protein saxiphilin. Other protein classes that change in abundance with toxin accumulation are membrane proteins involved in small molecule transport and metabolism, including ABC transporters, solute carrier proteins, and cytochrome P450s. Overall, this work shows that poison frogs can rapidly accumulate alkaloid toxins, which alter carrier protein abundance, initiate an immune response, and alter small molecule transport and metabolism dynamics across tissues. More broadly, this study suggests that acute changes in diet may quickly change the chemical arsenal and physiology of poison frogs, which may have important consequences in their defense against predation.

Isobaric tagging is a powerful strategy for global proteome profiling. A caveat of isobaric-tag-based quantification is "interference", which may be caused by coeluting peptides that are coisolated, cofragmented, and coanalyzed, thereby confounding quantitative accuracy. Here, we present a two-proteome standard that challenges the mass spectrometer to measure a range of protein abundance ratios in a background of potential interference. The HYpro16 standard consists of tandem mass tag (TMT) pro16-labeled human peptides at a 1:1 ratio across all channels into which is spiked TMTpro16-labeled yeast peptides in triplicate at 20:1, 10:1, 4:1, and 2:1 ratios. We showcase the HYpro16 standard by (1) altering the MS2 isolation window width and (2) examining different data acquisition methods (hrMS2, SPS-MS3, RTS-MS3). Our data illustrate that wider isolation widths moderately increase the TMT signal, the benefits of which are offset by decreased ratio accuracy. We also show that using real-time database searching (RTS)-MS3 resulted in the most accurate ratios. Additionally, the number of quantified yeast proteins using RTS-MS3 approaches that of hrMS2 when using a yeast-specific database for real-time searching. In short, this quality control standard allows for the assessment of multiple quantitative measurements within a single run, which can be compared across instruments to benchmark and track performance.

The selection of growth media is a very important consideration of any cell-based proteomics experiment. Alterations thereof may result in differences in basal proteomes simply due to disparities in the metabolite composition of the media. We investigate the effect of growth media on the proteomes of three microorganisms, specifically E. coli, S. cerevisiae, and S. pombe, using tandem mass tag (TMT)-based quantitative proteomics. We compared the protein abundance profiles of these microorganisms propagated in two distinct growth media that are commonly used for the respective organism. Our sample preparation strategy included SP3 bead-assisted protein isolation and digestion. In addition, we assembled a replicate set of samples in which we altered the proteolytic digestion from sequential treatment with LysC and trypsin to only LysC. Despite differences in peptides identified and a drop in quantified proteins, the results were similar between the two datasets for all three microorganisms. Approximately 10% of the proteins of each respective microorganism were significantly altered in each dataset. As expected, gene ontology analysis revealed that the majority of differentially expressed proteins are implicated in metabolism. These data emphasize further the importance and the potential consequences of growth media selection. SIGNIFICANCE: Various microorganisms are used as model systems throughout in biological studies, including proteomics-based investigations. The growth conditions of these organisms are of utmost importance, of which one major consideration is the choice of growth media. We hypothesize that growth media selection has a considerable impact on the baseline proteome of a given microorganism. To test this hypothesis, we used tandem mass tag (TMT)-based quantitative multiplexed proteomics to profile the proteomes of E. coli, S. cerevisiae, and S. pombe each grown in two different, yet common, growth media for the respective species. Our data show that approximately 10% of the proteins of each respective microorganism were significantly altered and that many of the differentially expressed proteins are implicated in metabolism. We provide several datasets which are potentially valuable for growth media selection with respect to downstream biochemical analysis.

A vast number of human cell lines are available for cell culture model-based studies, and as such the potential exists for discrepancies in findings due to cell line selection. To investigate this concept, the authors determine the relative protein abundance profiles of a panel of eight diverse, but commonly studied human cell lines. This panel includes HAP1, HEK293T, HeLa, HepG2, Jurkat, Panc1, SH-SY5Y, and SVGp12. A mass spectrometry-based proteomics workflow designed to enhance quantitative accuracy while maintaining analytical depth is used. To this end, this strategy leverages TMTpro16-based sample multiplexing, high-field asymmetric ion mobility spectrometry, and real-time database searching. The data show that the differences in the relative protein abundance profiles reflect cell line diversity. The authors also determine several hundred proteins to be highly enriched for a given cell line, and perform gene ontology and pathway analysis on these cell line-enriched proteins. An R Shiny application is designed to query protein abundance profiles and retrieve proteins with similar patterns. The workflows used herein can be applied to additional cell lines to aid cell line selection for addressing a given scientific inquiry or for improving an experimental design.

Multiplexed, isobaric tagging methods are powerful techniques to increase throughput, precision, and accuracy in quantitative proteomics. The dynamic range and accuracy of quantitation, however, can be limited by coisolation of tag-containing peptides that release reporter ions and conflate quantitative measurements across precursors. Methods to alleviate these effects often lead to the loss of protein and peptide identifications through online or offline filtering of interference containing spectra. To alleviate this effect, high-Field Asymmetric-waveform Ion Mobility Spectroscopy (FAIMS) has been proposed as a method to reduce precursor coisolation and improve the accuracy and dynamic range of multiplex quantitation. Here we tested the use of FAIMS to improve quantitative accuracy using previously established TMT-based interference standards (triple-knockout [TKO] and Human-Yeast Proteomics Resource [HYPER]). We observed that FAIMS robustly improved the quantitative accuracy of both high-resolution MS(2) (HRMS(2)) and synchronous precursor selection MS(3) (SPS-MS(3))-based methods without sacrificing protein identifications. We further optimized and characterized the main factors that enable robust use of FAIMS for multiplexed quantitation. We highlight these factors and provide method recommendations to take advantage of FAIMS technology to improve isobaric-tag-quantification moving forward.

Quantitative proteomics employing isobaric reagents has been established as a powerful tool for biological discovery. Current workflows often utilize a dedicated quantitative spectrum to improve quantitative accuracy and precision. A consequence of this approach is a dramatic reduction in the spectral acquisition rate, which necessitates the use of additional instrument time to achieve comprehensive proteomic depth. This work assesses the performance and benefits of online and real-time spectral identification in quantitative multiplexed workflows. A Real-Time Search (RTS) algorithm was implemented to identify fragment spectra within milliseconds as they are acquired using a probabilistic score and to trigger quantitative spectra only upon confident peptide identification. The RTS-MS(3) was benchmarked against standard workflows using a complex two-proteome model of interference and a targeted 10-plex comparison of kinase abundance profiles. Applying the RTS-MS(3) method provided the comprehensive characterization of a 10-plex proteome in 50% less acquisition time. These data indicate that the RTS-MS(3) approach provides dramatic performance improvements for quantitative multiplexed experiments.

Multiplexing strategies are at the forefront of mass-spectrometry-based proteomics, with SPS-MS3 methods becoming increasingly commonplace. A known caveat of isobaric multiplexing is interference resulting from coisolated and cofragmented ions that do not originate from the selected precursor of interest. The triple knockout (TKO) standard was designed to benchmark data collection strategies to minimize interference. However, a limitation to its widespread use has been the lack of an automated analysis platform. We present a TKO Visualization Tool (TVT). The TVT viewer allows for automated, web-based, database searching of the TKO standard, returning traditional figures of merit, such as peptide and protein counts, scan-specific ion accumulation times, as well as the TKO-specific metric, the IFI (interference-free index). Moreover, the TVT viewer allows for plotting of two TKO standards to assess protocol optimizations, compare instruments, or measure degradation of instrument performance over time. We showcase the TVT viewer by probing the selection of (1) stationary phase resin, (2) MS2 isolation window width, and (3) number of synchronous precursor selection (SPS) ions for SPS-MS3 analysis. Using the TVT viewer will allow the proteomics community to search and compare TKO results to optimize user-specific data collection workflows.

Phosphorylation-mediated signaling pathways have major implications in cellular regulation and disease. However, proteins with roles in these pathways are frequently less abundant and phosphorylation is often sub-stoichiometric. As such, the efficient enrichment, and subsequent recovery of phosphorylated peptides, is vital. Mass spectrometry-based proteomics is a well-established approach for quantifying thousands of phosphorylation events in a single experiment. We designed a peptide internal standard-based assay directed toward sample preparation strategies for mass spectrometry analysis to understand better phosphopeptide recovery from enrichment strategies. We coupled mass-differential tandem mass tag (mTMT) reagents (specifically, TMTzero and TMTsuper-heavy), nine mass spectrometry-amenable phosphopeptides (phos9), and peak area measurements from extracted ion chromatograms to determine phosphopeptide recovery. We showcase this mTMT/phos9 recovery assay by evaluating three phosphopeptide enrichment workflows. Our assay provides data on the recovery of phosphopeptides, which complement other metrics, namely the number of identified phosphopeptides and enrichment specificity. Our mTMT/phos9 assay is applicable to any enrichment protocol in a typical experimental workflow irrespective of sample origin or labeling strategy. Graphical Abstract ᅟ.

Reporter ion interference remains a limitation of isobaric tag-based sample multiplexing. Advances in instrumentation and data acquisition modes, such as the recently developed real-time database search (RTS), can reduce interference. However, interference persists as does the need to benchmark upstream sample preparation and data acquisition strategies. Here, we present an updated Triple yeast KnockOut (TKO) standard as well as corresponding upgrades to the TKO viewing tool (TVT2.5, http://tko.hms.harvard.edu/). Specifically, we expand the TKO standard to incorporate the TMTpro18-plex reagents (TKO18). We also construct a variant thereof which has been digested only with LysC (TKO18L). We compare proteome coverage and interference levels of TKO18 and TKO18L data that are acquired under different data acquisition modes and analyzed using TVT2.5. Our data illustrate that RTS reduces interference while improving proteome coverage and suggest that digesting with LysC alone only modestly reduces interference, albeit at the expense of proteome depth. Collectively, the two new TKO standards coupled with the updated TVT represent a convenient and versatile platform for assessing and developing methods to reduce interference in isobaric tag-based experiments.

Rapid protein degradation enables cells to quickly modulate protein abundance. Dysregulation of short-lived proteins plays essential roles in disease pathogenesis. A focused map of short-lived proteins remains understudied. Cycloheximide, a translational inhibitor, is widely used in targeted studies to measure degradation kinetics for short-lived proteins. Here, we combined cycloheximide chase assays with advanced quantitative proteomics to map short-lived proteins under translational inhibition in four human cell lines. Among 11,747 quantified proteins, we identified 1,017 short-lived proteins (half-lives ≤ 8hr). These short-lived proteins are less abundant, evolutionarily younger, and less thermally stable than other proteins. We quantified 103 proteins with different stabilities among cell lines. We showed that U2OS and HCT116 cells express truncated forms of ATRX and GMDS, respectively, which have lower stability than their full-length counterparts. This study provides a large-scale resource of human short-lived proteins under translational arrest, leading to untapped avenues of protein regulation for therapeutic interventions.

Cannabis (Cannabis sativa), popularly known as marijuana, is the most commonly used psychoactive substance and is considered illicit in most countries worldwide. However, a growing body of research has provided evidence of the therapeutic properties of chemical components of cannabis known as cannabinoids against several diseases including Alzheimer’s disease (AD), multiple sclerosis (MS), Parkinson’s disease, schizophrenia and glaucoma; these have prompted changes in medicinal cannabis legislation. The relaxation of legal restrictions and increased socio-cultural acceptance has led to its increase in both medicinal and recreational usage. Several biochemically active components of cannabis have a range of effects on the biological system. There is an urgent need for more research to better understand the molecular and biochemical effects of cannabis at a cellular level, to understand fully its implications as a pharmaceutical drug. Proteomics technology is an efficient tool to rigorously elucidate the mechanistic effects of cannabis on the human body in a cell and tissue-specific manner, drawing conclusions associated with its toxicity as well as therapeutic benefits, safety and efficacy profiles. This review provides a comprehensive overview of both in vitro and in vivo proteomic studies involving the cellular and molecular effects of cannabis and cannabis-derived compounds.

Objectives Mass spectrometry-based proteomics enables near-comprehensive protein expression profiling. We aimed to compare quantitatively the relative expression levels of thousands of proteins across 5 pancreatic cell lines. Methods Using tandem mass tags (TMT10-plex), we profiled the global proteomes of 5 cell lines in duplicate in a single multiplexed experiment. We selected cell lines commonly used in pancreatic research: CAPAN-1, HPAC, HPNE, PANC1, and PaSCs. In addition, we examined the effects of different proteases (Lys-C and Lys-C plus trypsin) on the dataset depth. Results We quantified over 8000 proteins across the 5 cell lines. Analysis of variance testing of cell lines within each data set resulted in over 1400 statistically significant differences in protein expression levels. Comparing the data sets, 10% more proteins and 30% more peptides were identified in the Lys-C/trypsin data set than in the Lys-C-only data set. The correlation coefficient of quantified proteins common between the data sets was greater than 0.85. Conclusions We illustrate protein level differences across pancreatic cell lines. In addition, we highlight the advantages of Lys-C/trypsin over Lys-C-only digests for discovery proteomics. These data sets provide a valuable resource of cell line-dependent peptide and protein differences for future targeted analyses, including those investigating on- or off-target drug effects across cell lines.

Familial neurodegenerative diseases commonly involve mutations that result in either aberrant proteins or dysfunctional components of the proteolytic machinery that act on aberrant proteins. UBQLN2 is a ubiquitin receptor of the UBL/UBA family that binds the proteasome through its ubiquitin-like domain and is thought to deliver ubiquitinated proteins to proteasomes for degradation. UBQLN2 mutations result in familial amyotrophic lateral sclerosis (ALS)/frontotemporal dementia in humans through an unknown mechanism. Quantitative multiplexed proteomics was used to provide for the first time an unbiased and global analysis of the role of Ubqln2 in controlling the composition of the proteome. We studied several murine models of Ubqln2-linked ALS and also generated Ubqln2 null mutant mice. We identified impacts of Ubqln2 on diverse physiological pathways, most notably serotonergic signaling. Interestingly, we observed an upregulation of proteasome subunits, suggesting a compensatory response to diminished proteasome output. Among the specific proteins whose abundance is linked to UBQLN2 function, the strongest hits were the ubiquitin ligase TRIM32 and two retroelement-derived proteins, PEG10 and CXX1B. Cycloheximide chase studies using induced human neurons and HEK293 cells suggested that PEG10 and TRIM32 are direct clients. Although UBQLN2 directs the degradation of multiple proteins via the proteasome, it surprisingly conferred strong protection from degradation on the Gag-like protein CXX1B, which is expressed from the same family of retroelement genes as PEG10. In summary, this study charts the proteomic landscape of ALS-related Ubqln2 mutants and identifies candidate client proteins that are altered in vivo in disease models and whose degradation is promoted by UBQLN2.

Generating insulin-producing β-cells from human induced pluripotent stem cells is a promising cell replacement therapy for improving or curing insulin-dependent diabetes. The transplantation of end-stages differentiating cells into living hosts was demonstrated to improve β-cell maturation. Nevertheless, the cellular and molecular mechanisms outlining the transplanted cells’ response to the in vivo environment are still to be properly characterized. Here we use global proteomics and large-scale imaging techniques to demultiplex and filter the cellular processes and molecular signatures modulated by the immediate in vivo effect. We show that in vivo exposure swiftly confines in vitro generated human pancreatic progenitors to single hormone expression. The global proteome landscape of the transplanted cells was closer to native human islets, especially in regard to energy metabolism and redox balance. Moreover, our study indicates a possible link between these processes and certain epigenetic regulators involved in cell identity. Pathway analysis predicted HNF1A and HNF4A as key regulators controlling the in vivo islet-promoting response, with experimental evidence suggesting their involvement in confining islet cell fate following xeno-transplantation. publishedVersion

Cell replacement therapies hold great therapeutic potential. Nevertheless, our knowledge of the mechanisms governing the developmental processes is limited, impeding the quality of differentiation protocols. Generating insulin-expressing cells in vitro is no exception, with the guided series of differentiation events producing heterogeneous cell populations that display mixed pancreatic islet phenotypes and immaturity. The achievement of terminal differentiation ultimately requires the in vivo transplantation of, usually, encapsulated cells. Here we show the impact of cell confinement on the pancreatic islet signature during the guided differentiation of alginate encapsulated human induced pluripotent stem cells (hiPSCs). Our results show that encapsulation improves differentiation by significantly reshaping the proteome landscape of the cells towards an islet-like signature. Pathway analysis is suggestive of integrins transducing the encapsulation effect into intracellular signalling cascades promoting differentiation. These analyses provide a molecular framework for understanding the confinement effects on hiPSCs differentiation while confirming its importance for this process. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

Phosphorylation is a post-translational modification with a vital role in cellular signaling. Isobaric labeling-based strategies, such as tandem mass tags (TMT), can measure the relative phosphorylation states of peptides in a multiplexed format. However, the low stoichiometry of protein phosphorylation constrains the depth of phosphopeptide analysis by mass spectrometry. As such, robust and sensitive workflows are required. Here we evaluate and optimize high-Field Asymmetric waveform Ion Mobility Spectrometry (FAIMS) coupled to Orbitrap Tribrid mass spectrometers for the analysis of TMT-labeled phosphopeptides. We determined that using FAIMS-MS3 with three compensation voltages (CV) in a single method (e.g., CV = -40/-60/-80 V) maximizes phosphopeptide coverage while minimizing inter-CV overlap. Furthermore, consecutive analyses using MSA-CID (multistage activation collision-induced dissociation) and HCD (higher-energy collisional dissociation) fragmentation at the MS2 stage increases the depth of phosphorylation analysis. The methodology and results outlined herein provide a template for tailoring optimized FAIMS-based methods.

Deubiquitylating enzymes (DUBs) counteract ubiquitylation to control stability or activity of substrates. Identification of DUB substrates is challenging because multiple DUBs act on the same substrates, thwarting genetic approaches. Here, we circumvented redundancy by broadly inhibiting DUBs inXenopusegg extract. DUB inhibition increases ubiquitylation of hundreds of proteins, depleting free ubiquitin without inducing widespread degradation. Restoring available ubiquitin led to proteasomal degradation of over thirty proteins, indicating that deubiquitylation is essential to maintain their stability. We confirmed their DUB-dependent stability with recombinant human proteins, demonstrating evolutionary conservation. We profiled the ability of DUBs to rescue protein stability, and found that USP7 has a unique ability to broadly antagonize proteasomal degradation. Together, we provide a comprehensive characterization of ubiquitin dynamics in theXenopussystem, identify new DUB substrates, and present a new approach to characterize physiological DUB specificity that overcomes challenges posed by DUB redundancy

We explore the landscape of a mitochondrial-autophagosome synapse during mitophagy using proteomics and genetic screens., The PINK1 protein kinase activates the PARK2 ubiquitin ligase to promote mitochondrial ubiquitylation and recruitment of ubiquitin-binding mitophagy receptors typified by OPTN and TAX1BP1. Here, we combine proximity biotinylation of OPTN and TAX1BP1 with CRISPR-Cas9–based screens for mitophagic flux to develop a spatial proteogenetic map of PARK2-dependent mitophagy. Proximity labeling of OPTN allowed visualization of a “mitochondrial-autophagosome synapse” upon mitochondrial depolarization. Proximity proteomics of OPTN and TAX1BP1 revealed numerous proteins at the synapse, including both PARK2 substrates and autophagy components. Parallel mitophagic flux screens identified proteins with roles in autophagy, vesicle formation and fusion, as well as PARK2 targets, many of which were also identified via proximity proteomics. One protein identified in both approaches, HK2, promotes assembly of a high–molecular weight complex of PINK1 and phosphorylation of ubiquitin in response to mitochondrial damage. This work provides a resource for understanding the spatial and molecular landscape of PARK2-dependent mitophagy.

Stochasticity between independent LC–MS/MS runs is a challenging problem in the field of proteomics, resulting in significant missing values (i.e., abundance measurements) among observed peptides. To address this issue, several approaches have been developed including computational methods such as MaxQuant’s match-between-runs (MBR) algorithm. Often dozens of runs are all considered at once by MBR, transferring identifications from any one run to any of the others. To evaluate the error associated with these transfer events, we created a two-sample/two-proteome approach. In this way, samples containing no yeast lysate (n = 20) were assessed for false identification transfers from samples containing yeast (n = 20). While MBR increased the total number of spectral identifications by ~40%, we also found that 44% of all identified yeast proteins had identifications transferred to at least one sample without yeast. However, of these only 2.7% remained in the final data set after applying the MaxQuant LFQ algorithm. We conclude that false transfers by MBR are plentiful,0020but few are retained in the final data set.

Summary Mammalian tissues engage in specialized physiology that is regulated through reversible modification of protein cysteine residues by reactive oxygen species (ROS). ROS regulate a myriad of biological processes, but the protein targets of ROS modification that drive tissue-specific physiology in vivo are largely unknown. Here, we develop Oximouse, a comprehensive and quantitative mapping of the mouse cysteine redox proteome in vivo. We use Oximouse to establish several paradigms of physiological redox signaling. We define and validate cysteine redox networks within each tissue that are tissue selective and underlie tissue-specific biology. We describe a common mechanism for encoding cysteine redox sensitivity by electrostatic gating. Moreover, we comprehensively identify redox-modified disease networks that remodel in aged mice, establishing a systemic molecular basis for the long-standing proposed links between redox dysregulation and tissue aging. We provide the Oximouse compendium as a framework for understanding mechanisms of redox regulation in physiology and aging.

A comprehensive characterization of the molecular processes controlling cell fate decisions is essential to derive stable progenitors and terminally differentiated cells that are functional from human pluripotent stem cells (hPSCs). Here, we report the use of quantitative proteomics to describe early proteome adaptations during hPSC differentiation toward pancreatic progenitors. We report that the use of unbiased quantitative proteomics allows the simultaneous profiling of numerous proteins at multiple time points, and is a valuable tool to guide the discovery of signaling events and molecular signatures underlying cellular differentiation. We also monitored the activity level of pathways whose roles are pivotal in the early pancreas differentiation, including the Hippo signaling pathway. The quantitative proteomics data set provides insights into the dynamics of the global proteome during the transition of hPSCs from a pluripotent state toward pancreatic differentiation.

Saccharomyces cerevisiae and Schizosaccharomyces pombe are the most commonly studied yeast model systems, yet comparisons of global proteome remodeling between these yeast species are scarce. Here, we profile the proteomes of S. cerevisiae and S. pombe cultured with either glucose or pyruvate as the sole carbon source to define common and distinctive alterations in the protein landscape across species. In addition, we develop an updated streamlined-tandem mass tag (SL-TMT) strategy that substitutes chemical-based precipitation with more versatile bead-based protein aggregation method (SP3) prior to enzymatic digestion and TMT labeling. Our new workflow, SL-SP3-TMT, allow for near-complete proteome profiles in a single experiment for each species. The data reveal expected alterations in protein abundance and differences between species, highlighted complete canonical biochemical pathways, and provided insight into previously uncharacterized proteins. The techniques used herein, namely SL-SP3-TMT, can be applied to virtually any experiment aiming to study remodeling of the proteome using a high-throughput, comprehensive, yet streamlined mass spectrometry-based strategy. SIGNIFICANCE: Saccharomyces cerevisiae and Schizosaccharomyces pombe are single-celled eukaryotes that diverged from a common ancestor over a period of 100 million years, such that evolution has driven fundamental differences between the two species. Cellular metabolism and the regulation thereof are vital for living organisms. Here, we hypothesize that large scale proteomic alterations are prevalent upon the substitution of glucose with another carbon source, in this case pyruvate. To efficiently process our samples, we developed an updated streamlined-tandem mass tag (SL-TMT) strategy with more versatile bead-based protein aggregation. The data revealed expected alterations in protein abundance and illustrated differences between species. We highlighted complete canonical biochemical pathways and provided insight into previously uncharacterized proteins.