NUAK1 is a member of the AMP-activated protein kinase-related kinase family. Recent studies have shown that NUAK1 is involved in cellular senescence and motility in epithelial cells and fibroblasts. However, the physiological roles of NUAK1 are poorly understood because of embryonic lethality in NUAK1 null mice. The purpose of this study was to elucidate the roles of NUAK1 in adult tissues. We determined the tissue distribution of NUAK1 and generated muscle-specific NUAK1 knock-out (MNUAK1KO) mice. For phenotypic analysis, whole body glucose homeostasis and muscle glucose metabolism were examined. Quantitative phosphoproteome analysis of soleus muscle was performed to understand the molecular mechanisms underlying the knock-out phenotype. Nuak1 mRNA was preferentially expressed in highly oxidative tissues such as brain, heart, and soleus muscle. On a high fat diet, MNUAK1KO mice had a lower fasting blood glucose level, greater glucose tolerance, higher insulin sensitivity, and higher concentration of muscle glycogen than control mice. Phosphoproteome analysis revealed that phosphorylation of IRS1 Ser-1097 was markedly decreased in NUAK1-deficient muscle. Consistent with this, insulin signaling was enhanced in the soleus muscle of MNUAK1KO mice, as evidenced by increased phosphorylation of IRS1 Tyr-608, AKT Thr-308, and TBC1D4 Thr-649. These observations suggest that a physiological role of NUAK1 is to suppress glucose uptake through negative regulation of insulin signaling in oxidative muscle.

We undertook a comprehensive proteogenomic characterization of 95 prospectively collected endometrial carcinomas, comprising 83 endometrioid and 12 serous tumors. This analysis revealed possible new consequences of perturbations to the p53 and Wnt/β-catenin pathways, identified a potential role for circRNAs in the epithelial-mesenchymal transition, and provided new information about proteomic markers of clinical and genomic tumor subgroups, including relationships to known druggable pathways. An extensive genome-wide acetylation survey yielded insights into regulatory mechanisms linking Wnt signaling and histone acetylation. We also characterized aspects of the tumor immune landscape, including immunogenic alterations, neoantigens, common cancer/testis antigens, and the immune microenvironment, all of which can inform immunotherapy decisions. Collectively, our multi-omic analyses provide a valuable resource for researchers and clinicians, identify new molecular associations of potential mechanistic significance in the development of endometrial cancers, and suggest novel approaches for identifying potential therapeutic targets.

In the absence of a dominant driving mutation other than uniformly present TP53 mutations, deeper understanding of the biology driving ovarian high-grade serous cancer (HGSC) requires analysis at a functional level, including post-translational modifications. Comprehensive proteogenomic and phosphoproteomic characterization of 83 prospectively collected ovarian HGSC and appropriate normal precursor tissue samples (fallopian tube) under strict control of ischemia time reveals pathways that significantly differentiate between HGSC and relevant normal tissues in the context of homologous repair deficiency (HRD) status. In addition to confirming key features of HGSC from previous studies, including a potential survival-associated signature and histone acetylation as a marker of HRD, deep phosphoproteomics provides insights regarding the potential role of proliferation-induced replication stress in promoting the characteristic chromosomal instability of HGSC and suggests potential therapeutic targets for use in precision medicine trials.

Small extracellular vesicles (sEVs) are important mediators of intercellular communication with respect to diverse pathophysiological processes. Here, we determined novel phosphatidylserine (PS)-deficient sEV subpopulations as a major somatic cell-derived sEV subpopulation in blood because of long blood circulation half-life through escape from macrophage uptake. PS(-)-sEVs were identified in various cultured cells as a minor population. However, as a result of rapid uptake of PS(+)-sEVs by macrophages, circulating somatic cell-derived sEVs in the blood were found to be mainly PS(-)-sEVs. These results suggest that endogenous PS(-)-sEVs could indeed be the key player in sEV-mediated intercellular communication, a good target for sEV-based diagnosis, and a potent candidate for sEV-based drug delivery. Our findings bring a paradigm shift in the understanding of the biology and translational applications of sEVs.

Brown rot fungi release massive amounts of carbon from forest deadwood, particularly at high latitudes. These fungi degrade wood by generating small reactive oxygen species (ROS) to loosen lignocellulose, to then selectively remove carbohydrates. The ROS mechanism has long been considered the key adaptation defining brown rot wood decomposition, but recently, we found preliminary evidence that fungal glycoside hydrolases (GHs) implicated in early cell wall loosening might have been adapted to tolerate ROS stress and to synergize with ROS to loosen woody lignocellulose. In the current study, we found more specifically that side chain hemicellulases that help in the early deconstruction of the lignocellulosic complex are significantly more tolerant of ROS in the brown rot fungus Rhodonia placenta than in a white rot fungus (Trametes versicolor) and a soft rot fungus (Trichoderma reesei). Using proteomics to understand the extent of tolerance, we found that significant oxidation of secreted R. placenta proteins exposed to ROS was less than half of the oxidation observed for T. versicolor or T. reesei. The principal oxidative modifications observed in all cases were monooxidation and dioxidation/trioxidation (mainly in methionine and tryptophan residues), some of which were critical for enzyme activity. At the peptide level, we found that GHs in R. placenta were the least ROS affected among our tested fungi. These results confirm and describe underlying mechanisms of tolerance in early-secreted brown rot fungal hemicellulases. These enzymatic adaptations may have been as important as nonenzymatic ROS pathway adaptations in brown rot fungal evolution. IMPORTANCE Brown rot fungi play a critical role in carbon recycling and are of industrial interest. These fungi typically use reactive oxygen species (ROS) to indiscriminately "loosen" wood cell walls at the outset of decay. Brown rot fungi avoid oxidative stress associated with this ROS step by delaying the expression/secretion of many carbohydrate-active enzymes, but there are exceptions, notably some side chain hemicellulases, implicated in loosening lignocellulose. In this study, we provide enzyme activity and secretomic evidence that these enzymes in the brown rot model Rhodonia placenta are more ROS tolerant than the white and soft rot isolates tested. For R. placenta, and perhaps all brown rot lineages, these ROS tolerance adaptions may have played a long-overshadowed role in enabling brown rot.

Multiple myeloma (MM) is a highly refractory hematologic cancer. Targeted immunotherapy has shown promise in MM but remains hindered by the challenge of identifying specific yet broadly representative tumor markers. We analyzed 53 bone marrow (BM) aspirates from 41 MM patients using an unbiased, high-throughput pipeline for therapeutic target discovery via single-cell transcriptomic profiling, yielding 38 MM marker genes encoding cell-surface proteins and 15 encoding intracellular proteins. Of these, 20 candidate genes were highlighted that are not yet under clinical study, 11 of which were previously uncharacterized as therapeutic targets. The findings were cross-validated using bulk RNA sequencing, flow cytometry, and proteomic mass spectrometry of MM cell lines and patient BM, demonstrating high overall concordance across data types. Independent discovery using bulk RNA sequencing reiterated top candidates, further affirming the ability of single-cell transcriptomics to accurately capture marker expression despite limitations in sample size or sequencing depth. Target dynamics and heterogeneity were further examined using both transcriptomic and immuno-imaging methods. In summary, this study presents a robust and broadly applicable strategy for identifying tumor markers to better inform the development of targeted cancer therapy.

The mitochondrial kinase PTEN-induced kinase 1 (PINK1) and cytosolic ubiquitin ligase (E3) Parkin/PRKN are involved in mitochondrial quality control responses. PINK1 phosphorylates ubiquitin and the Parkin ubiquitin-like (Ubl) domain at serine 65 and promotes Parkin activation and translocation to damaged mitochondria. Upon Parkin activation, the Ubl domain is ubiquitinated at lysine (K) 27 and K48 residues. However, the contribution of K27/K48 ubiquitination toward Parkin activity remains unclear. In this study, ubiquitination of K56 (corresponding to K27 in the human), K77 (K48 in the human) or both was blocked by generating Drosophila Parkin (dParkin) mutants to examine the effects of Parkin Ubl domain ubiquitination on Parkin activation in Drosophila. The dParkin, in which K56 was replaced with arginine (dParkin K56R), rescued pupal lethality in flies by co-expression with PINK1, whereas dParkin K77R could not. The dParkin K56R exhibited reduced abilities of mitochondrial fragmentation and motility arrest, which are mediated by degrading Parkin E3 substrates Mitofusin and Miro, respectively. Pathogenic dParkin K56N, unlike dParkin K56R, destabilized the protein, suggesting that not only was dParkin K56N non-ubiquitin-modified at K56, but also the structure of the Ubl domain for activation was largely affected. Ubiquitin attached to K27 of the Ubl domain during PINK1-mediated Parkin activation was likely to be phosphorylated because human Parkin K27R weakened Parkin self-binding and activation in trans. Therefore, our findings suggest a new mechanism of Parkin activation, where an activation complex is formed through phospho-ubiquitin attachment on the K27 residue of the Parkin Ubl domain.

Despite advances in proteomic technologies, clinical translation of plasma biomarkers remains low, partly due to a major bottleneck between the discovery of candidate biomarkers and costly clinical validation studies. Due to a dearth of multiplexable assays, generally only a few candidate biomarkers are tested, and the validation success rate is accordingly low. Previously, mass spectrometry-based approaches have been used to fill this gap but feature poor quantitative performance and were generally limited to hundreds of proteins. Here, we demonstrate the capability of an internal standard triggered-parallel reaction monitoring (IS-PRM) assay to greatly expand the numbers of candidates that can be tested with improved quantitative performance. The assay couples immunodepletion and fractionation with IS-PRM and was developed and implemented in human plasma to quantify 5176 peptides representing 1314 breast cancer biomarker candidates. Characterization of the IS-PRM assay demonstrated the precision (median % CV of 7.7%), linearity (median R2 > 0.999 over 4 orders of magnitude), and sensitivity (median LLOQ < 1 fmol, approximately) to enable rank-ordering of candidate biomarkers for validation studies. Using three plasma pools from breast cancer patients and three control pools, 893 proteins were quantified, of which 162 candidate biomarkers were verified in at least one of the cancer pools and 22 were verified in all three cancer pools. The assay greatly expands capabilities for quantification of large numbers of proteins and is well suited for prioritization of viable candidate biomarkers.

Tumor-initiating cells with reprogramming plasticity or stem-progenitor cell properties (stemness) are thought to be essential for cancer development and metastatic regeneration in many cancers; however, elucidation of the underlying molecular network and pathways remains demanding. Combining machine learning and experimental investigation, here we report CD81, a tetraspanin transmembrane protein known to be enriched in extracellular vesicles (EVs), as a newly identified driver of breast cancer stemness and metastasis. Using protein structure modeling and interface prediction-guided mutagenesis, we demonstrate that membrane CD81 interacts with CD44 through their extracellular regions in promoting tumor cell cluster formation and lung metastasis of triple negative breast cancer (TNBC) in human and mouse models. In-depth global and phosphoproteomic analyses of tumor cells deficient with CD81 or CD44 unveils endocytosis-related pathway alterations, leading to further identification of a quality-keeping role of CD44 and CD81 in EV secretion as well as in EV-associated stemness-promoting function. CD81 is coexpressed along with CD44 in human circulating tumor cells (CTCs) and enriched in clustered CTCs that promote cancer stemness and metastasis, supporting the clinical significance of CD81 in association with patient outcomes. Our study highlights machine learning as a powerful tool in facilitating the molecular understanding of new molecular targets in regulating stemness and metastasis of TNBC.

G protein-coupled receptor (GPCR) biased agonism, the activation of some signaling pathways over others, is thought to largely be due to differential receptor phosphorylation, or "phosphorylation barcodes." At chemokine receptors, ligands act as "biased agonists" with complex signaling profiles, which contributes to the limited success in pharmacologically targeting these receptors. Here, mass spectrometry-based global phosphoproteomics revealed that CXCR3 chemokines generate different phosphorylation barcodes associated with differential transducer activation. Chemokine stimulation resulted in distinct changes throughout the kinome in global phosphoproteomic studies. Mutation of CXCR3 phosphosites altered β-arrestin conformation in cellular assays and was confirmed by molecular dynamics simulations. T cells expressing phosphorylation-deficient CXCR3 mutants resulted in agonist- and receptor-specific chemotactic profiles. Our results demonstrate that CXCR3 chemokines are non-redundant and act as biased agonists through differential encoding of phosphorylation barcodes and lead to distinct physiological processes.

Microglia, the innate immune cells of the central nervous system, have been genetically implicated in multiple neurodegenerative diseases. We previously mapped the genetic regulation of gene expression and mRNA splicing in human microglia, identifying several loci where common genetic variants in microglia-specific regulatory elements explain disease risk loci identified by GWAS. However, identifying genetic effects on splicing has been challenging due to the use of short sequencing reads to identify causal isoforms. Here we present the isoform-centric microglia genomic atlas (isoMiGA) which leverages the power of long-read RNA-seq to identify 35,879 novel microglia isoforms. We show that the novel microglia isoforms are involved in stimulation response and brain region specificity. We then quantified the expression of both known and novel isoforms in a multi-ethnic meta-analysis of 555 human microglia short-read RNA-seq samples from 391 donors, the largest to date, and found associations with genetic risk loci in Alzheimer's disease and Parkinson's disease. We nominate several loci that may act through complex changes in isoform and splice site usage.

We developed a multiplexed label-free quantification strategy, which integrates an efficient gel-assisted digestion protocol, high-performance liquid chromatography tandem MS analysis, and a bioinformatics alignment method to determine personalized proteomic profiles for membrane proteins in human tissues. This strategy provided accurate (6% error) and reproducible (34% relative S.D.) quantification of three independently purified membrane fractions from the same human colorectal cancer (CRC) tissue. Using CRC as a model, we constructed the personalized membrane protein atlas of paired tumor and adjacent normal tissues from 28 patients with different stages of CRC. Without fractionation, this strategy confidently quantified 856 proteins (≥2 unique peptides) across different patients, including the first and robust detection (Mascot score: 22,074) of the well-documented CRC marker, carcinoembryonic antigen 5 by a discovery-type proteomics approach. Further validation of a panel of proteins, annexin A4, neutrophils defensin A1, and claudin 3, confirmed differential expression levels and high occurrences (48-70%) in 60 CRC patients. The most significant discovery is the overexpression of stomatin-like 2 (STOML2) for early diagnostic and prognostic potential. Increased expression of STOML2 was associated with decreased CRC-related survival; the mean survival period was 34.77 ± 2.03 months in patients with high STOML2 expression, whereas 53.67 ± 3.46 months was obtained for patients with low STOML2 expression. Further analysis by ELISA verified that plasma concentrations of STOML2 in early-stage CRC patients were elevated as compared with those of healthy individuals (p < 0.001), suggesting that STOML2 may be a noninvasive serological biomarker for early CRC diagnosis. The overall sensitivity of STOML2 for CRC detection was 71%, which increased to 87% when combined with CEA measurements. This study demonstrated a sensitive, label-free strategy for differential analysis of tissue membrane proteome, which may provide a roadmap for the subsequent identification of molecular target candidates of multiple cancer types.

Following recent advances in high-throughput mass spectrometry (MS)-based proteomics, the numbers of identified phosphoproteins and their phosphosites have greatly increased in a wide variety of organisms. Although a critical role of phosphorylation is control of protein signaling, our understanding of the phosphoproteome remains limited. Here, we report unexpected, large-scale connections revealed between the phosphoproteome and protein interactome by integrative data-mining of yeast multi-omics data. First, new phosphoproteome data on yeast cells were obtained by MS-based proteomics and unified with publicly available yeast phosphoproteome data. This revealed that nearly 60% of ∼6,000 yeast genes encode phosphoproteins. We mapped these unified phosphoproteome data on a yeast protein-protein interaction (PPI) network with other yeast multi-omics datasets containing information about proteome abundance, proteome disorders, literature-derived signaling reactomes, and in vitro substratomes of kinases. In the phospho-PPI, phosphoproteins had more interacting partners than nonphosphoproteins, implying that a large fraction of intracellular protein interaction patterns (including those of protein complex formation) is affected by reversible and alternative phosphorylation reactions. Although highly abundant or unstructured proteins have a high chance of both interacting with other proteins and being phosphorylated within cells, the difference between the number counts of interacting partners of phosphoproteins and nonphosphoproteins was significant independently of protein abundance and disorder level. Moreover, analysis of the phospho-PPI and yeast signaling reactome data suggested that co-phosphorylation of interacting proteins by single kinases is common within cells. These multi-omics analyses illuminate how wide-ranging intracellular phosphorylation events and the diversity of physical protein interactions are largely affected by each other.

Kinase networks are important for cellular signal transduction. Despite tremendous efforts to uncover these signaling pathways, huge numbers of uncharacterized phosphosites still remain in the human proteome. Because of the transient nature of kinase-substrate interactions in vivo, it is almost impossible to identify direct substrates. Here, we present a strategy for the rapid, accurate and high-throughput discovery of in vitro kinase substrates using quantitative proteomics. Using 385 purified kinases (354 wild-type protein kinases, 21 mutants and 10 lipid kinases), we identified a total of 175,574 potential direct kinase substrates. In addition, we identified novel kinase groups, such as one group containing 30 threonine-directed kinases and another containing 15 serine/threonine/tyrosine kinases. Surprisingly, we observed that the diversity of substrates for tyrosine kinases was much higher than that for serine-threonine kinases.

The insertion of ion mobility spectrometry (IMS) between LC and MS can improve peptide identification in both proteomics and phosphoproteomics by providing structural information that is complementary to LC and MS, because IMS separates ions on the basis of differences in their shapes and charge states. However, it is necessary to know how phosphate groups affect the peptide collision cross sections (CCS) in order to accurately predict phosphopeptide CCS values and to maximize the usefulness of IMS. In this work, we systematically characterized the CCS values of 4,433 pairs of mono-phosphopeptide and corresponding unphosphorylated peptide ions using trapped ion mobility spectrometry (TIMS). Nearly one-third of the mono-phosphopeptide ions evaluated here showed smaller CCS values than their unphosphorylated counterparts, even though phosphorylation results in a mass increase of 80 Da. Significant changes of CCS upon phosphorylation occurred mainly in structurally extended peptides with large numbers of basic groups, possibly reflecting intramolecular interactions between phosphate and basic groups.

We present a motif-targeting phosphoproteome analysis workflow utilizing in vitro kinase reaction to enrich a subset of peptides with specific primary sequence motifs. Phosphopeptides are enriched and dephosphorylated with alkaline phosphatase, followed by in vitro kinase reaction to phosphorylate substrate peptides with specific primary-sequence motifs. These phosphopeptides are enriched again, TMT-labeled, dephosphorylated to enhance MS-detectability, and analyzed by LC/MS/MS. We applied this approach to inhibitor-treated cancer cells, and successfully profiled the inhibitory spectra of multiple kinase inhibitors. We anticipate this approach will be applicable to target specific subsets of the phosphoproteome using the wide variety of available recombinant protein kinases.

Regnase-1 is an endoribonuclease crucial for controlling inflammation by degrading mRNAs encoding cytokines and inflammatory mediators in mammals. However, it is unclear how Regnase-1-mediated mRNA decay is controlled in interleukin (IL)-1β- or Toll-like receptor (TLR) ligand-stimulated cells. Here, by analyzing the Regnase-1 interactome, we found that IL-1β or TLR stimulus dynamically induced the formation of Regnase-1-β-transducin repeat-containing protein (βTRCP) complex. Importantly, we also uncovered a novel interaction between Regnase-1 and 14-3-3 in both mouse and human cells. In IL-1R/TLR-stimulated cells, the Regnase-1-14-3-3 interaction is mediated by IRAK1 through a previously uncharacterized C-terminal structural domain. Phosphorylation of Regnase-1 at S494 and S513 is critical for Regnase-1-14-3-3 interaction, while a different set of phosphorylation sites of Regnase-1 is known to be required for the recognition by βTRCP and proteasome-mediated degradation. We found that Regnase-1-14-3-3 and Regnase-1-βTRCP interactions are not sequential events. Rather, 14-3-3 protects Regnase-1 from βTRCP-mediated degradation. On the other hand, 14-3-3 abolishes Regnase-1-mediated mRNA decay by inhibiting Regnase-1-mRNA association. In addition, nuclear-cytoplasmic shuttling of Regnase-1 is abrogated by 14-3-3 interaction. Taken together, the results suggest that a novel inflammation-induced interaction of 14-3-3 with Regnase-1 stabilizes inflammatory mRNAs by sequestering Regnase-1 in the cytoplasm to prevent mRNA recognition.

Mass-spectrometry-based phosphoproteomics can identify more than 10,000 phosphorylated sites in a single experiment. But, despite the fact that enormous phosphosite information has been accumulated in public repositories, protein kinase-substrate relationships remain largely unknown. Here, we describe a method to identify endogenous substrates of kinases by using a combination of a proximity-dependent biotin identification method, called BioID, with two other independent methods, kinase-perturbed phosphoproteomics and phosphorylation motif matching. For proof of concept, this approach was applied to casein kinase 2 (CK2) and protein kinase A (PKA), and we identified 24 and 35 putative substrates, respectively. We also show that known cancer-associated missense mutations near phosphosites of substrates affect phosphorylation by CK2 or PKA and thus might alter downstream signaling in cancer cells bearing these mutations. This approach extends our ability to probe physiological kinase-substrate networks by providing new methodology for large-scale identification of endogenous substrates of kinases.

Our ability to model the dynamics of signal transduction networks will depend on accurate methods to quantify levels of protein phosphorylation on a global scale. Here we describe a motif-targeting quantitation method for phosphorylation stoichiometry typing. Proteome-wide phosphorylation stoichiometry can be obtained by a simple phosphoproteomic workflow integrating dephosphorylation and isotope tagging with enzymatic kinase reaction. Proof-of-concept experiments using CK2-, MAPK- and EGFR-targeting assays in lung cancer cells demonstrate the advantage of kinase-targeted complexity reduction, resulting in deeper phosphoproteome quantification. We measure the phosphorylation stoichiometry of >1,000 phosphorylation sites including 366 low-abundance tyrosine phosphorylation sites, with high reproducibility and using small sample sizes. Comparing drug-resistant and sensitive lung cancer cells, we reveal that post-translational phosphorylation changes are significantly more dramatic than those at the protein and messenger RNA levels, and suggest potential drug targets within the kinase-substrate network associated with acquired drug resistance.

Protein phosphorylation regulates a wide range of cellular processes. Here, we report the proteome-wide mapping of in vivo phosphorylation sites in Arabidopsis by using complementary phosphopeptide enrichment techniques coupled with high-accuracy mass spectrometry. Using unfractionated whole cell lysates of Arabidopsis, we identified 2597 phosphopeptides with 2172 high-confidence, unique phosphorylation sites from 1346 proteins. The distribution of phosphoserine, phosphothreonine, and phosphotyrosine sites was 85.0, 10.7, and 4.3%. Although typical tyrosine-specific protein kinases are absent in Arabidopsis, the proportion of phosphotyrosines among the phospho-residues in Arabidopsis is similar to that in humans, where over 90 tyrosine-specific protein kinases have been identified. In addition, the tyrosine phosphoproteome shows features distinct from those of the serine and threonine phosphoproteomes. Taken together, we highlight the extent and contribution of tyrosine phosphorylation in plants.