The fitness cost of spurious phosphorylation.

The fidelity of signal transduction requires the binding of regulatory molecules to their cognate targets. However, the crowded cell interior risks off-target interactions between proteins that are functionally unrelated. How such off-target interactions impact fitness is not generally known. Here, we use Saccharomyces cerevisiae to inducibly express tyrosine kinases. Because yeast lacks bona fide tyrosine kinases, the resulting tyrosine phosphorylation is biologically spurious. We engineered 44 yeast strains each expressing a tyrosine kinase, and quantitatively analysed their phosphoproteomes. This analysis resulted in ~30,000 phosphosites mapping to ~3500 proteins. The number of spurious pY sites generated correlates strongly with decreased growth, and we predict over 1000 pY events to be deleterious. However, we also find that many of the spurious pY sites have a negligible effect on fitness, possibly because of their low stoichiometry. This result is consistent with our evolutionary analyses demonstrating a lack of phosphotyrosine counter-selection in species with tyrosine kinases. Our results suggest that, alongside the risk for toxicity, the cell can tolerate a large degree of non-functional crosstalk as interaction networks evolve.

Systematic functional prioritization of protein posttranslational modifications.

Protein function is often regulated by posttranslational modifications (PTMs), and recent advances in mass spectrometry have resulted in an exponential increase in PTM identification. However, the functional significance of the vast majority of these modifications remains unknown. To address this problem, we compiled nearly 200,000 phosphorylation, acetylation, and ubiquitination sites from 11 eukaryotic species, including 2,500 newly identified ubiquitylation sites for Saccharomyces cerevisiae. We developed methods to prioritize the functional relevance of these PTMs by predicting those that likely participate in cross-regulatory events, regulate domain activity, or mediate protein-protein interactions. PTM conservation within domain families identifies regulatory "hot spots" that overlap with functionally important regions, a concept that we experimentally validated on the HSP70 domain family. Finally, our analysis of the evolution of PTM regulation highlights potential routes for neutral drift in regulatory interactions and suggests that only a fraction of modification sites are likely to have a significant biological role.

A tissue-specific atlas of mouse protein phosphorylation and expression.

Although most tissues in an organism are genetically identical, the biochemistry of each is optimized to fulfill its unique physiological roles, with important consequences for human health and disease. Each tissue's unique physiology requires tightly regulated gene and protein expression coordinated by specialized, phosphorylation-dependent intracellular signaling. To better understand the role of phosphorylation in maintenance of physiological differences among tissues, we performed proteomic and phosphoproteomic characterizations of nine mouse tissues. We identified 12,039 proteins, including 6296 phosphoproteins harboring nearly 36,000 phosphorylation sites. Comparing protein abundances and phosphorylation levels revealed specialized, interconnected phosphorylation networks within each tissue while suggesting that many proteins are regulated by phosphorylation independently of their expression. Our data suggest that the "typical" phosphoprotein is widely expressed yet displays variable, often tissue-specific phosphorylation that tunes protein activity to the specific needs of each tissue. We offer this dataset as an online resource for the biological research community.

A Python Package for the Localization of Protein Modifications in Mass Spectrometry Data.

Determining the correct localization of post-translational modifications (PTMs) on peptides aids in interpreting their effect on protein function. While most algorithms for this task are available as standalone applications or incorporated into software suites, improving their versatility through access from popular scripting languages facilitates experimentation and incorporation into novel workflows. Here we describe pyAscore, an efficient and versatile implementation of the Ascore algorithm in Python for scoring the localization of user defined PTMs in data dependent mass spectrometry. pyAscore can be used from the command line or imported into Python scripts and accepts standard file formats from popular software tools used in bottom-up proteomics. Access to internal objects for scoring and working with modified peptides adds to the toolbox for working with PTMs in Python. pyAscore is available as an open source package for Python 3.6+ on all major operating systems and can be found at pyascore.readthedocs.io.

Automated Enrichment of Phosphotyrosine Peptides for High-Throughput Proteomics.

Phosphotyrosine (pY) enrichment is critical for expanding the fundamental and clinical understanding of cellular signaling by mass spectrometry-based proteomics. However, current pY enrichment methods exhibit a high cost per sample and limited reproducibility due to expensive affinity reagents and manual processing. We present rapid-robotic phosphotyrosine proteomics (R2-pY), which uses a magnetic particle processor and pY superbinders or antibodies. R2-pY can handle up to 96 samples in parallel, requires 2 days to go from cell lysate to mass spectrometry injections, and results in global proteomic, phosphoproteomic, and tyrosine-specific phosphoproteomic samples. We benchmark the method on HeLa cells stimulated with pervanadate and serum and report over 4000 unique pY sites from 1 mg of peptide input, strong reproducibility between replicates, and phosphopeptide enrichment efficiencies above 99%. R2-pY extends our previously reported R2-P2 proteomic and global phosphoproteomic sample preparation framework, opening the door to large-scale studies of pY signaling in concert with global proteome and phosphoproteome profiling.

Anticodon sequence determines the impact of mistranslating tRNAAla variants.

Transfer RNAs (tRNAs) maintain translation fidelity through accurate charging by their cognate aminoacyl-tRNA synthetase and codon:anticodon base pairing with the mRNA at the ribosome. Mistranslation occurs when an amino acid not specified by the genetic message is incorporated into proteins and has applications in biotechnology, therapeutics and is relevant to disease. Since the alanyl-tRNA synthetase uniquely recognizes a G3:U70 base pair in tRNAAla and the anticodon plays no role in charging, tRNAAla variants with anticodon mutations have the potential to mis-incorporate alanine. Here, we characterize the impact of the 60 non-alanine tRNAAla anticodon variants on the growth of Saccharomyces cerevisiae. Overall, 36 tRNAAla anticodon variants decreased growth in single- or multi-copy. Mass spectrometry analysis of the cellular proteome revealed that 52 of 57 anticodon variants, not decoding alanine or stop codons, induced mistranslation when on single-copy plasmids. Variants with G/C-rich anticodons resulted in larger growth deficits than A/U-rich variants. In most instances, synonymous anticodon variants impact growth differently, with anticodons containing U at base 34 being the least impactful. For anticodons generating the same amino acid substitution, reduced growth generally correlated with the abundance of detected mistranslation events. Differences in decoding specificity, even between synonymous anticodons, resulted in each tRNAAla variant mistranslating unique sets of peptides and proteins. We suggest that these differences in decoding specificity are also important in determining the impact of tRNAAla anticodon variants.

Decoding Post-Translational Modification Crosstalk With Proteomics.

Post-translational modification (PTM) of proteins allows cells to regulate protein functions, transduce signals and respond to perturbations. PTMs expand protein functionality and diversity, which leads to increased proteome complexity. PTM crosstalk describes the combinatorial action of multiple PTMs on the same or on different proteins for higher order regulation. Here we review how recent advances in proteomic technologies, mass spectrometry instrumentation, and bioinformatics spurred the proteome-wide identification of PTM crosstalk through measurements of PTM sites. We provide an overview of the basic modes of PTM crosstalk, the proteomic methods to elucidate PTM crosstalk, and approaches that can inform about the functional consequences of PTM crosstalk.

IsobaricQuant enables cross-platform quantification, visualization, and filtering of isobarically-labeled peptides.

In mass spectrometry (MS)-based quantitative proteomics, labeling with isobaric mass tags such as iTRAQ and TMT can substantially improve sample throughput and reduce peptide missing values. Nonetheless, the quantification of labeled peptides tends to suffer from reduced accuracy due to the co-isolation of co-eluting precursors of similar mass-to-charge. Acquisition approaches such as multistage MS3 or ion mobility separation address this problem, yet are difficult to audit and limited to expensive instrumentation. Here we introduce IsobaricQuant, an open-source software tool for quantification, visualization, and filtering of peptides labeled with isobaric mass tags, with specific focus on precursor interference. IsobaricQuant is compatible with MS2 and MS3 acquisition strategies, has a viewer that allows assessing interference, and provides several scores to aid the filtering of scans with compression. We demonstrate that IsobaricQuant quantifications are accurate by comparing it with commonly used software. We further show that its QC scores can successfully filter out scans with reduced quantitative accuracy at MS2 and MS3 levels, removing inaccurate peptide quantifications and decreasing protein CVs. Finally, we apply IsobaricQuant to a PISA dataset and show that QC scores improve the sensitivity of the identification of protein targets of a kinase inhibitor. IsobaricQuant is available at https://github.com/Villen-Lab/isobaricquant.

Coisolation of Peptide Pairs for Peptide Identification and MS/MS-Based Quantification.

Stable-isotope labeling with amino acids in cell culture (SILAC)-based metabolic labeling is a widely adopted proteomics approach that enables quantitative comparisons among a variety of experimental conditions. Despite its quantitative capacity, SILAC experiments analyzed with data-dependent acquisition (DDA) do not fully leverage peptide pair information for identification and suffer from undersampling compared to label-free proteomic experiments. Herein, we developed a DDA strategy that coisolates and fragments SILAC peptide pairs and uses y-ions for their relative quantification. To facilitate the analysis of this type of data, we adapted the Comet sequence database search engine to make use of SILAC peptide paired fragments and developed a tool to annotate and quantify MS/MS spectra of coisolated SILAC pairs. This peptide pair coisolation approach generally improved expectation scores compared to the traditional DDA approach. Fragment ion quantification performed similarly well to precursor quantification in the MS1 and achieved more quantifications. Lastly, our method enables reliable MS/MS quantification of SILAC proteome mixtures with overlapping isotopic distributions. This study shows the feasibility of the coisolation approach. Coupling this approach with intelligent acquisition strategies has the potential to improve SILAC peptide sampling and quantification.

Thesaurus: quantifying phosphopeptide positional isomers.

Proteins can be phosphorylated at neighboring sites resulting in different functional states, and studying the regulation of these sites has been challenging. Here we present Thesaurus, a search engine that detects and quantifies phosphopeptide positional isomers from parallel reaction monitoring and data-independent acquisition mass spectrometry experiments. We apply Thesaurus to analyze phosphorylation events in the PI3K/AKT signaling pathway and show neighboring sites with distinct regulation.

DIAmeter: matching peptides to data-independent acquisition mass spectrometry data.

MOTIVATION: Tandem mass spectrometry data acquired using data independent acquisition (DIA) is challenging to interpret because the data exhibits complex structure along both the mass-to-charge (m/z) and time axes. The most common approach to analyzing this type of data makes use of a library of previously observed DIA data patterns (a 'spectral library'), but this approach is expensive because the libraries do not typically generalize well across laboratories. RESULTS: Here, we propose DIAmeter, a search engine that detects peptides in DIA data using only a peptide sequence database. Although some existing library-free DIA analysis methods (i) support data generated using both wide and narrow isolation windows, (ii) detect peptides containing post-translational modifications, (iii) analyze data from a variety of instrument platforms and (iv) are capable of detecting peptides even in the absence of detectable signal in the survey (MS1) scan, DIAmeter is the only method that offers all four capabilities in a single tool. AVAILABILITY AND IMPLEMENTATION: The open source, Apache licensed source code is available as part of the Crux mass spectrometry analysis toolkit (http://crux.ms). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

mRNA destabilization is the dominant effect of mammalian microRNAs by the time substantial repression ensues.

MicroRNAs (miRNAs) regulate target mRNAs through a combination of translational repression and mRNA destabilization, with mRNA destabilization dominating at steady state in the few contexts examined globally. Here, we extend the global steady-state measurements to additional mammalian contexts and find that regardless of the miRNA, cell type, growth condition, or translational state, mRNA destabilization explains most (66%->90%) miRNA-mediated repression. We also determine the relative dynamics of translational repression and mRNA destabilization for endogenous mRNAs as a miRNA is induced. Although translational repression occurs rapidly, its effect is relatively weak, such that by the time consequential repression ensues, the effect of mRNA destabilization dominates. These results imply that consequential miRNA-mediated repression is largely irreversible and provide other insights into the nature of miRNA-mediated regulation. They also simplify future studies, dramatically extending the known contexts and time points for which monitoring mRNA changes captures most of the direct miRNA effects.

Proteome and Phosphoproteome Analysis of Brown Adipocytes Reveals That RICTOR Loss Dampens Global Insulin/AKT Signaling.

Stimulating brown adipose tissue (BAT) activity represents a promising therapy for overcoming metabolic diseases. mTORC2 is important for regulating BAT metabolism, but its downstream targets have not been fully characterized. In this study, we apply proteomics and phosphoproteomics to investigate the downstream effectors of mTORC2 in brown adipocytes. We compare wild-type controls to isogenic cells with an induced knockout of the mTORC2 subunit RICTOR (Rictor-iKO) by stimulating each with insulin for a 30-min time course. In Rictor-iKO cells, we identify decreases to the abundance of glycolytic and de novo lipogenesis enzymes, and increases to mitochondrial proteins as well as a set of proteins known to increase upon interferon stimulation. We also observe significant differences to basal phosphorylation because of chronic RICTOR loss including decreased phosphorylation of the lipid droplet protein perilipin-1 in Rictor-iKO cells, suggesting that RICTOR could be involved with regulating basal lipolysis or droplet dynamics. Finally, we observe mild dampening of acute insulin signaling response in Rictor-iKO cells, and a subset of AKT substrates exhibiting statistically significant dependence on RICTOR.

Analysis of Molecular Networks in the Cerebellum in Chronic Schizophrenia: Modulation by Early Postnatal Life Stressors in Murine Models.

Despite the growing importance of the cerebellum as a region highly vulnerable to accumulating molecular errors in schizophrenia, limited information is available regarding altered molecular networks with potential therapeutic targets. To identify altered networks, we conducted one-shot liquid chromatography-tandem mass spectrometry in postmortem cerebellar cortex in schizophrenia and healthy individuals followed by bioinformatic analysis (PXD024937 identifier in ProteomeXchange repository). A total of 108 up-regulated proteins were enriched in stress-related proteins, half of which were also enriched in axonal cytoskeletal organization and vesicle-mediated transport. A total of 142 down-regulated proteins showed an enrichment in proteins involved in mitochondrial disease, most of which were also enriched in energy-related biological functions. Network analysis identified a mixed module of mainly axonal-related pathways for up-regulated proteins with a high number of interactions for stress-related proteins. Energy metabolism and neutrophil degranulation modules were found for down-regulated proteins. Further, two double-hit postnatal stress murine models based on maternal deprivation combined with social isolation or chronic restraint stress were used to investigate the most robust candidates of generated networks. CLASP1 from the axonal module in the model of maternal deprivation was combined with social isolation, while YWHAZ was not altered in either model. METTL7A from the degranulation pathway was reduced in both models and was identified as altered also in previous gene expression studies, while NDUFB9 from the energy network was reduced only in the model of maternal deprivation combined with social isolation. This work provides altered stress- and mitochondrial disease-related proteins involved in energy, immune and axonal networks in the cerebellum in schizophrenia as possible novel targets for therapeutic interventions and suggests that METTL7A is a possible relevant altered stress-related protein in this context.

R2-P2 rapid-robotic phosphoproteomics enables multidimensional cell signaling studies.

Recent developments in proteomics have enabled signaling studies where > 10,000 phosphosites can be routinely identified and quantified. Yet, current analyses are limited in throughput, reproducibility, and robustness, hampering experiments that involve multiple perturbations, such as those needed to map kinase-substrate relationships, capture pathway crosstalks, and network inference analysis. To address these challenges, we introduce rapid-robotic phosphoproteomics (R2-P2), an end-to-end automated method that uses magnetic particles to process protein extracts to deliver mass spectrometry-ready phosphopeptides. R2-P2 is rapid, robust, versatile, and high-throughput. To showcase the method, we applied it, in combination with data-independent acquisition mass spectrometry, to study signaling dynamics in the mitogen-activated protein kinase (MAPK) pathway in yeast. Our results reveal broad and specific signaling events along the mating, the high-osmolarity glycerol, and the invasive growth branches of the MAPK pathway, with robust phosphorylation of downstream regulatory proteins and transcription factors. Our method facilitates large-scale signaling studies involving hundreds of perturbations opening the door to systems-level studies aiming to capture signaling complexity.

The histone H3 Lys 27 demethylase JMJD3 regulates gene expression by impacting transcriptional elongation.

The histone H3 Lys 27 (H3K27) demethylase JMJD3 has been shown to play important roles in transcriptional regulation and cell differentiation. However, the mechanism underlying JMJD3-mediated transcriptional regulation remains incompletely understood. Here we show that JMJD3 is associated with KIAA1718, whose substrates include dimethylated H3K27 (H3K27me2), and proteins involved in transcriptional elongation. JMJD3 and KIAA1718 directly bind to and regulate the expression of a plethora of common target genes in both a demethylase activity-dependent and -independent manner in the human promyelocytic leukemia cell line HL-60. We found that JMJD3 and KIAA1718 collaborate to demethylate trimethylated H3K27 (H3K27me3) on a subset of their target genes, some of which are bivalently marked by H3K4me3 and H3K27me3 and associated with promoter-proximal, paused RNA polymerase II (Pol II) before activation. Reduction of either JMJD3 or KIAA1718 diminishes Pol II traveling along the gene bodies of the affected genes while having no effect on the promoter-proximal Pol II. Furthermore, JMJD3 and KIAA1718 also play a role in localizing elongation factors SPT6 and SPT16 to the target genes. Our results support the model whereby JMJD3 activates bivalent gene transcription by demethylating H3K27me3 and promoting transcriptional elongation. Taken together, these findings provide new insight into the mechanisms by which JMJD3 regulates gene expression.

Plug-and-play analysis of the human phosphoproteome by targeted high-resolution mass spectrometry.

Systematic approaches to studying cellular signaling require phosphoproteomic techniques that reproducibly measure the same phosphopeptides across multiple replicates, conditions, and time points. Here we present a method to mine information from large-scale, heterogeneous phosphoproteomics data sets to rapidly generate robust targeted mass spectrometry (MS) assays. We demonstrate the performance of our method by interrogating the IGF-1/AKT signaling pathway, showing that even rarely observed phosphorylation events can be consistently detected and precisely quantified.

TORC1 and TORC2 converge to regulate the SAGA co-activator in response to nutrient availability.

Gene expression regulation is essential for cells to adapt to changes in their environment. Co-activator complexes have well-established roles in transcriptional regulation, but less is known about how they sense and respond to signaling cues. We have previously shown that, in fission yeast, one such co-activator, the SAGA complex, controls gene expression and the switch from proliferation to differentiation in response to nutrient availability. Here, using a combination of genetic, biochemical, and proteomic approaches, we show that SAGA responds to nutrients through the differential phosphorylation of its Taf12 component, downstream of both the TORC1 and TORC2 pathways. Taf12 phosphorylation increases early upon starvation and is controlled by the opposing activities of the PP2A phosphatase, which is activated by TORC1, and the TORC2-activated Gad8AKT kinase. Mutational analyses suggest that Taf12 phosphorylation prevents cells from committing to differentiation until starvation reaches a critical level. Overall, our work reveals that SAGA is a direct target of nutrient-sensing pathways and has uncovered a mechanism by which TORC1 and TORC2 converge to control gene expression and cell fate decisions.

Angiogenin-induced tRNA fragments inhibit translation initiation.

Angiogenin is a stress-activated ribonuclease that cleaves tRNA within anticodon loops to produce tRNA-derived stress-induced fragments (tiRNAs). Transfection of natural or synthetic tiRNAs inhibits protein synthesis and triggers the phospho-eIF2α-independent assembly of stress granules (SGs), essential components of the stress response program. We show that selected tiRNAs inhibit protein synthesis by displacing eIF4G/eIF4A from uncapped > capped RNAs. tiRNAs also displace eIF4F, but not eIF4E:4EBP1, from isolated m(7)G cap. We identify a terminal oligoguanine motif that is required to displace the eIF4F complex, inhibit translation, and induce SG assembly. We show that the tiRNA-associated translational silencer YB-1 contributes to angiogenin-, tiRNA-, and oxidative stress-induced translational repression. Our data reveal some of the mechanisms by which stress-induced tRNA cleavage inhibits protein synthesis and activates a cytoprotective stress response program.