Metabolic regulation of protein N-alpha-acetylation by Bcl-xL promotes cell survival.

Previous experiments suggest a connection between the N-alpha-acetylation of proteins and sensitivity of cells to apoptotic signals. Here, we describe a biochemical assay to detect the acetylation status of proteins and demonstrate that protein N-alpha-acetylation is regulated by the availability of acetyl-CoA. Because the antiapoptotic protein Bcl-xL is known to influence mitochondrial metabolism, we reasoned that Bcl-xL may provide a link between protein N-alpha-acetylation and apoptosis. Indeed, Bcl-xL overexpression leads to a reduction in levels of acetyl-CoA and N-alpha-acetylated proteins in the cell. This effect is independent of Bax and Bak, the known binding partners of Bcl-xL. Increasing cellular levels of acetyl-CoA by addition of acetate or citrate restores protein N-alpha-acetylation in Bcl-xL-expressing cells and confers sensitivity to apoptotic stimuli. We propose that acetyl-CoA serves as a signaling molecule that couples apoptotic sensitivity to metabolism by regulating protein N-alpha-acetylation.

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.

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.

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.

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.

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.

Molecular mechanism of the dual activity of 4EGI-1: Dissociating eIF4G from eIF4E but stabilizing the binding of unphosphorylated 4E-BP1.

The eIF4E-binding protein (4E-BP) is a phosphorylation-dependent regulator of protein synthesis. The nonphosphorylated or minimally phosphorylated form binds translation initiation factor 4E (eIF4E), preventing binding of eIF4G and the recruitment of the small ribosomal subunit. Signaling events stimulate serial phosphorylation of 4E-BP, primarily by mammalian target of rapamycin complex 1 (mTORC1) at residues T37/T46, followed by T70 and S65. Hyperphosphorylated 4E-BP dissociates from eIF4E, allowing eIF4E to interact with eIF4G and translation initiation to resume. Because overexpression of eIF4E is linked to cellular transformation, 4E-BP is a tumor suppressor, and up-regulation of its activity is a goal of interest for cancer therapy. A recently discovered small molecule, eIF4E/eIF4G interaction inhibitor 1 (4EGI-1), disrupts the eIF4E/eIF4G interaction and promotes binding of 4E-BP1 to eIF4E. Structures of 14- to 16-residue 4E-BP fragments bound to eIF4E contain the eIF4E consensus binding motif, (54)YXXXXLΦ(60) (motif 1) but lack known phosphorylation sites. We report here a 2.1-Å crystal structure of mouse eIF4E in complex with m(7)GTP and with a fragment of human 4E-BP1, extended C-terminally from the consensus-binding motif (4E-BP150-84). The extension, which includes a proline-turn-helix segment (motif 2) followed by a loop of irregular structure, reveals the location of two phosphorylation sites (S65 and T70). Our major finding is that the C-terminal extension (motif 3) is critical to 4E-BP1-mediated cell cycle arrest and that it partially overlaps with the binding site of 4EGI-1. The binding of 4E-BP1 and 4EGI-1 to eIF4E is therefore not mutually exclusive, and both ligands contribute to shift the equilibrium toward the inhibition of translation initiation.

Phosphorylation of ubiquitin at Ser65 affects its polymerization, targets, and proteome-wide turnover.

Ubiquitylation is an essential post-translational modification that regulates numerous cellular processes, most notably protein degradation. Ubiquitin can itself be phosphorylated at nearly every serine, threonine, and tyrosine residue. However, the effect of this modification on ubiquitin function is largely unknown. Here, we characterized the effects of phosphorylation of yeast ubiquitin at serine 65 in vivo and in vitro. We find this post-translational modification to be regulated under oxidative stress, occurring concomitantly with the restructuring of the ubiquitin landscape into a highly polymeric state. Phosphomimetic mutation of S65 recapitulates the oxidative stress phenotype, causing a dramatic accumulation of ubiquitylated proteins and a proteome-wide reduction of protein turnover rates. Importantly, this mutation impacts ubiquitin chain disassembly, chain linkage distribution, ubiquitin interactions, and substrate targeting. These results demonstrate that phosphorylation is an additional mode of ubiquitin regulation with broad implications in cellular physiology.

Structure of the eukaryotic translation initiation factor eIF4E in complex with 4EGI-1 reveals an allosteric mechanism for dissociating eIF4G.

The interaction of the eukaryotic translation initiation factor eIF4E with the initiation factor eIF4G recruits the 40S ribosomal particle to the 5' end of mRNAs, facilitates scanning to the AUG start codon, and is crucial for eukaryotic translation of nearly all genes. Efficient recruitment of the 40S particle is particularly important for translation of mRNAs encoding oncoproteins and growth-promoting factors, which often harbor complex 5' UTRs and require efficient initiation. Thus, inhibiting the eIF4E/eIF4G interaction has emerged as a previously unpursued route for developing anticancer agents. Indeed, we discovered small-molecule inhibitors of this eIF4E/eIF4G interaction (4EGIs) that inhibit translation initiation both in vitro and in vivo and were used successfully in numerous cancer-biology and neurobiology studies. However, their detailed molecular mechanism of action has remained elusive. Here, we show that the eIF4E/eIF4G inhibitor 4EGI-1 acts allosterically by binding to a site on eIF4E distant from the eIF4G binding epitope. Data from NMR mapping and high-resolution crystal structures are congruent with this mechanism, where 4EGI-1 attaches to a hydrophobic pocket of eIF4E between ß-sheet2 (L60-T68) and α-helix1 (E69-N77), causing localized conformational changes mainly in the H78-L85 region. It acts by unfolding a short 310-helix (S82-L85) while extending α-helix1 by one turn (H78-S82). This unusual helix rearrangement has not been seen in any previous eIF4E structure and reveals elements of an allosteric inhibition mechanism leading to the dislocation of eIF4G from eIF4E.

A conserved function of corepressors is to nucleate assembly of the transcriptional preinitiation complex.

The plant corepressor TPL is recruited to diverse chromatin contexts, yet its mechanism of repression remains unclear. Previously, we have leveraged the fact that TPL retains its function in a synthetic transcriptional circuit in the yeast model Saccharomyces cerevisiae to localize repressive function to two distinct domains. Here, we employed two unbiased whole genome approaches to map the physical and genetic interactions of TPL at a repressed locus. We identified SPT4, SPT5 and SPT6 as necessary for repression with the SPT4 subunit acting as a bridge connecting TPL to SPT5 and SPT6. We also discovered the association of multiple additional constituents of the transcriptional preinitiation complex at TPL-repressed promoters, specifically those involved in early transcription initiation events. These findings were validated in yeast and plants through multiple assays, including a novel method to analyze conditional loss of function of essential genes in plants. Our findings support a model where TPL nucleates preassembly of the transcription activation machinery to facilitate rapid onset of transcription once repression is relieved.

Microdissected tumor cuboids: a microscale cancer model that retains a complex tumor microenvironment.

Present cancer disease models - typically based on cell cultures and animal models that lack the human tumor microenvironment (TME) - are extremely poor predictors of human disease outcomes. Microscale cancer models that combine the micromanipulation of tissues and fluids offer the exciting possibility of miniaturizing the drug testing workflow, enabling inexpensive, more efficient tests of high clinical biomimicry that maximize the use of scarce human tissue and minimize animal testing. Critically, these microscale models allow for precisely addressing the impact of the structural features of the heterogeneous TME to properly target and understand the contributions of these unique zones to therapeutic response. We have recently developed a precision slicing method that yields large numbers of cuboidal micro-tissues ("cuboids", ∼ (400 µm) 3 ) from a single tumor biopsy. Here we evaluate cuboids from syngeneic mouse tumor models and human tumors, which contain native immune cells, as models for drug and immunotherapy evaluation. We characterize relevant TME parameters, such as their cellular architecture (immune cells and vasculature), cytokine secretion, proteomics profiles, and their response to drug panels in multi-well arrays. Despite the cutting procedure and the time spent in culture (up to 7 days), the cuboids display strong functional responses such as cytokine and drug responses. Overall, our results suggest that cuboids make an excellent model for applications that require the TME, such as immunotherapy drug evaluations, including for clinical trials and personalized oncology approaches.

Efficient and economic protein labeling for NMR in mammalian expression systems: Application to a preT-cell and T-cell receptor protein.

Protein nuclear magnetic resonance (NMR) spectroscopy relies on the ability to isotopically label polypeptides, which is achieved through heterologous expression in various host organisms. Most commonly, Escherichia coli is employed by leveraging isotopically substituted ammonium and glucose to uniformly label proteins with 15N and 13C, respectively. Moreover, E. coli can grow and express proteins in uniformly deuterium-substituted water (D2O), a strategy useful for experiments targeting high molecular weight proteins. Unfortunately, many proteins, particularly those requiring specific posttranslational modifications like disulfide bonding or glycosylation for proper folding and/or function, cannot be readily expressed in their functional forms using E. coli-based expression systems. One such class of proteins includes T-cell receptors and their related preT-cell receptors. In this study, we present an expression system for isotopic labeling of proteins using a nonadherent human embryonic kidney cell line, Expi293F, and a specially designed media. We demonstrate the application of this platform to the ß subunit common to both receptors. In addition, we show that this expression system and media can be used to specifically label amino acids Phe, Ile, Val, and Leu in this system, utilizing an amino acid-specific labeling protocol that allows targeted incorporation at high efficiency without significant isotopic scrambling. We demonstrate that this system can also be used to express proteins with fluorinated amino acids. We were routinely able to obtain an NMR sample with a concentration of 200 µM from 30 mL of culture media, utilizing less than 20 mg of the labeled amino acids.

Automated Enrichment of Phosphotyrosine Peptides for High-Throughput Proteomics.

Phosphotyrosine (pY) enrichment is critical for expanding 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 handles 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.

Analysis of networks in the dorsolateral prefrontal cortex in chronic schizophrenia: Relevance of altered immune response.

The dorsolateral prefrontal cortex (DLPFC) has a crucial role in cognitive functioning and negative symptoms in schizophrenia. However, limited information of altered protein networks is available in this region in schizophrenia. We performed a proteomic analysis using single-shot liquid chromatography-tandem mass spectrometry of grey matter of postmortem DLPFC in chronic schizophrenia subjects (n = 20) and unaffected subjects (n = 20) followed by bioinformatic analysis to identify altered protein networks in schizophrenia (PXD024939 identifier in ProteomeXchange repository). Our results displayed a proteome profile in the DLPFC of 1989 proteins. 43 proteins were found significantly altered in schizophrenia. Analysis of this panel showed an enrichment of biological processes implicated in vesicle-mediated transport, processing and antigen presentation via MHC class II, intracellular transport and selenium metabolism. The enriched identified pathways were MHC class II antigen presentation, vesicle-mediated transport, Golgi ER retrograde transport, Nef mediated CD8 downregulation and the immune system. All these enriched categories were found to be downregulated. Furthermore, our network analyses showed crosstalk between proteins involved in MHC class II antigen presentation, membrane trafficking, Golgi-to-ER retrograde transport, Nef-mediated CD8 downregulation and the immune system with only one module built by 13 proteins. RAB7A showed eight interactions with proteins of all these pathways. Our results provide an altered molecular network involved in immune response in the DLPFC in schizophrenia with a central role of RAB7A. These results suggest that RAB7A or other proteins of this network could be potential targets for novel pharmacological strategies in schizophrenia for improving cognitive and negative symptoms.

The regulatory landscape of the yeast phosphoproteome.

The cellular ability to react to environmental fluctuations depends on signaling networks that are controlled by the dynamic activities of kinases and phosphatases. Here, to gain insight into these stress-responsive phosphorylation networks, we generated a quantitative mass spectrometry-based atlas of early phosphoproteomic responses in Saccharomyces cerevisiae exposed to 101 environmental and chemical perturbations. We report phosphosites on 59% of the yeast proteome, with 18% of the proteome harboring a phosphosite that is regulated within 5 min of stress exposure. We identify shared and perturbation-specific stress response programs, uncover loss of phosphorylation as an integral early event, and dissect the interconnected regulatory landscape of kinase-substrate networks, as we exemplify with target of rapamycin signaling. We further reveal functional organization principles of the stress-responsive phosphoproteome based on phosphorylation site motifs, kinase activities, subcellular localizations, shared functions and pathway intersections. This information-rich map of 25,000 regulated phosphosites advances our understanding of signaling networks.