Proteomic Landscape Research Articles

Proteomic landscapes of inherited platelet disorders with different etiologies

BackgroundInherited platelet disorders (IPDs) are a heterogeneous group of rare diseases that are caused by the defects in early megakaryopoiesis, proplatelet formation, and/or mature platelet function. Although genomic sequencing is increasingly used to identify genetic variants underlying IPD, this technique does not disclose resulting molecular changes that impact platelet function. Proteins are the functional units that shape platelet function; however, insights into how variants that cause IPDs impact platelet proteomes are limited. ObjectivesThe objective of this study was to profile the platelet proteomics signatures of IPDs. MethodsWe performed unbiased label-free quantitative mass spectrometry (MS)–based proteome profiling on platelets of 34 patients with IPDs with variants in 13 ISTH TIER1 genes that affect different stages of platelet development. ResultsIn line with the phenotypical heterogeneity between IPDs, proteomes were diverse between IPDs. We observed extensive proteomic alterations in patients with a GFI1B variant and for genetic variants in genes encoding proteins that impact cytoskeletal processes (MYH9, TUBB1, and WAS). Using the diversity between IPDs, we clustered protein dynamics, revealing disrupted protein-protein complexes. This analysis furthermore grouped proteins with similar cellular function and location, classifying mitochondrial protein constituents and identifying both known and putative novel alpha granule associated proteins. ConclusionsWith this study, we demonstrate a MS–based proteomics perspective to IPDs. By integrating the effects of IPDs that impact different aspects of platelet function, we dissected the biological contexts of protein alterations to gain further insights into the biology of platelet (dys)function.

The proteomic landscape shows oncologic relevance in cystitis glandularis.

The relationship between cystitis glandularis (CG) and bladder malignancy remains unclear. We identified the oncologic significance of CG at the molecular level using liquid chromatography-tandem mass spectrometry-based proteomic analysis of 10 CG, 12 urothelial carcinoma (UC), and nine normal urothelium (NU) specimens. Differentially expressed proteins (DEPs) were identified based on an analysis of variance false discovery rate < 0.05, and their functional enrichment was analyzed using a network model, Gene Set Enrichment Analysis, and Gene Ontology annotation. We identified 9,890 proteins across all samples and 1,139 DEPs among the three entities. A substantial number of DEPs overlapped in CG/NU, distinct from UC. Interestingly, we found that a subset of DEP clusters (n = 53, 5%) was differentially expressed in NU but similarly between CG and UC. This "UC-like signature" was enriched for reactive oxygen species (ROS) and energy metabolism, growth and DNA repair, transport, motility, epithelial-mesenchymal transition, and cell survival. Using the top 10 shortlisted DEPs, including SOD2, PRKCD, CYCS, and HCLS1, we identified functional elements related to ROS metabolism, development, and transport using network analysis. The abundance of these four molecules in UC/CG than in NU was consistent with the oncologic functions in CG. Using a proteomic approach, we identified a predominantly non-neoplastic landscape of CG, which was closer to NU than to UC. We also confirmed a small subset of common DEPs in UC and CG, suggesting that altered ROS metabolism might imply potential cancerous risks in CG.

Proteomic analysis of brain metastatic lung adenocarcinoma reveals intertumoral heterogeneity and specific alterations associated with the timing of brain metastases

Brain metastases are associated with considerable negative effects on patients' outcome in lung adenocarcinoma (LADC). Here, we investigated the proteomic landscape of primary LADCs and their corresponding brain metastases. Proteomic profiling was conducted on 20 surgically resected primary and brain metastatic LADC samples via label-free shotgun proteomics. After sample processing, peptides were analyzed using an Ultimate 3000 pump coupled to a QExactive HF-X mass spectrometer. Raw data were searched using PD 2.4. Further data analyses were carried out using Perseus, RStudio and GraphPad Prism. Proteomic data were correlated with clinical and histopathological parameters and the timing of brain metastases. Mass spectrometry-based proteomic data are available via ProteomeXchange with identifier PXD027259. Out of the 6821 proteins identified and quantified, 1496 proteins were differentially expressed between primary LADCs and corresponding brain metastases. Pathways associated with the immune system, cell-cell/matrix interactions and migration were predominantly activated in the primary tumors, whereas pathways related to metabolism, translation or vesicle formation were overrepresented in the metastatic tumors. When comparing fast- versus slow-progressing patients, we found 454 and 298 differentially expressed proteins in the primary tumors and brain metastases, respectively. Metabolic reprogramming and ribosomal activity were prominently up-regulated in the fast-progressing patients (versus slow-progressing individuals), whereas expression of cell-cell interaction- and immune system-related pathways was reduced in these patients and in those with multiple brain metastases. This is the first comprehensive proteomic analysis of paired primary tumors and brain metastases of LADC patients. Our data suggest a malfunction of cellular attachment and an increase in ribosomal activity in LADC tissue, promoting brain metastasis. The current study provides insights into the biology of LADC brain metastases and, moreover, might contribute to the development of personalized follow-up strategies in LADC.

Proteomic Landscape of Human Spermatozoa: Optimized Extraction Method and Application

Human spermatozoa proteomics exposed to some physical, biological or chemical stressors is being explored. However, there is a lack of optimized sample preparation methods to achieve in-depth protein coverage for sperm cells. Meanwhile, it is not clear whether antibiotics can regulate proteins to affect sperm quality. Here, we systematically compared a total of six different protein extraction methods based the combination of three commonly used lysis buffers and physical lysis strategies. The urea buffer combined with ultrasonication (UA-ultrasonication) produced the highest protein extraction rate, leading to the deepest coverage of human sperm proteome (5685 protein groups) from healthy human sperm samples. Since the antibiotics, amoxicillin and clarithromycin, have been widely used against H. pylori infection, we conduct a longitudinal study of sperm proteome via data-independent acquisition tandem mass spectrometry (DIA-MS/MS) on an infected patient during on and off therapy with these two drugs. The semen examination and morphological analysis were performed combined with proteomics analysis. Our results indicated that antibiotics may cause an increase in the sperm concentration and the rate of malformed sperm and disrupt proteome expression in sperm. This work provides an optimized extraction method to characterize the in-depth human sperm proteome and to extend its clinical applications.

Proteomic Portrait of Human Lymphoma Reveals Protein Molecular Fingerprint of Disease Specific Subtypes and Progression.

The online version contains supplementary material available at 10.1007/s43657-022-00075-w.

Proteomic Profiling Reveals the Molecular Control of Oocyte Maturation

Meiotic maturation is an intricate and precisely regulated process orchestrated by various pathways and numerous proteins. However, little is known about the proteome landscape during oocytes maturation. Here, we obtained the temporal proteomic profiles of mouse oocytes during in vivo maturation. We successfully quantified 4694 proteins from 4500 oocytes in three key stages (germinal vesicle, germinal vesicle breakdown, and metaphase II). In particular, we discovered the novel proteomic features during oocyte maturation, such as the active Skp1–Cullin–Fbox pathway and an increase in mRNA decay–related proteins. Using functional approaches, we further identified the key factors controlling the histone acetylation state in oocytes and the vital proteins modulating meiotic cell cycle. Taken together, our data serve as a broad resource on the dynamics occurring in oocyte proteome and provide important knowledge to better understand the molecular mechanisms during germ cell development.

Physiological Characteristics and Proteome of Dalbergia odorifera in Loam and Gravel Substrates

Dalbergia odorifera, a crucial medicinal and commercial plant, shows great potential for ecological restoration in karst rocky desertification (KRD) areas. However, no studies have examined its adaptation mechanism to barren KRD environments. We focused on the physiological and protein variations of D. odorifera grown under loam substrate (LS), composite substrate (CS, 50% gravel), and gravel substrate (GS, 100% gravel). Results showed that volume, surface area, and dry weight of root in CS were the highest. Proteomic analysis revealed 516 and 443 differentially accumulated proteins (DAPs) in CS compared with LS and GS, respectively. Functional analysis showed that epidermal morphogenesis, organic substrate transport, lipid transport, and detection of abiotic stimulus were enriched in the overlapped DAPs. In addition, compared to LS, specific DAPs in CS were enriched to Gene Ontology (GO) terms such as root hair cell differentiation, ATP, carbohydrate metabolism, and also to pathways including carbohydrate digestion and absorption, starch and sucrose metabolism, HIF-1 signaling, mineral absorption, and lysosome. However, specific DAPs in CS relative to GS were clustered to hydrogen peroxide, fatty acid biosynthesis, and lipid metabolism. Furthermore, a series of transcripts encoding crucial DAPs were confirmed by RT-qPCR. In conclusion, the physiological characteristics and proteomic landscape showed that CS substrate was more favorable to the adaptation of D. odorifera to KRD than LS and GS substrates. The protein evaluation related to substrates in this study provides further evidence for ecological management of D. odorifera in KRD areas.

Prophage excision switches the primary ribosome rescue pathway and rescue-associated gene regulations in Escherichia coli.

Escherichia coli has multiple pathways to release nonproductive ribosome complexes stalled at the 3' end of nonstop mRNA: tmRNA (SsrA RNA)-mediated trans-translation and stop codon-independent termination by ArfA/RF2 or ArfB (YaeJ). The arfA mRNA lacks a stop codon and its expression is repressed by trans-translation. Therefore, ArfA is considered to complement the ribosome rescue activity of trans-translation, but the physiological situations in which ArfA is expressed have not been elucidated. Here, we found that the excision of CP4-57 prophage adjacent to E. coli ssrA leads to the inactivation of tmRNA and switches the primary rescue pathway from trans-translation to ArfA/RF2. This "rescue-switching" rearranges not only the proteome landscape in E. coli but also the phenotype such as motility. Furthermore, among the proteins with significantly increased abundance in the ArfA+ cells, we found ZntR, whose mRNA is transcribed together as the upstream part of nonstop arfA mRNA. Repression of ZntR and reconstituted model genes depends on the translation of the downstream nonstop ORFs that trigger the trans-translation-coupled exonucleolytic degradation by polynucleotide phosphorylase (PNPase). Namely, our studies provide a novel example of trans-translation-dependent regulation and re-define the physiological roles of prophage excision.

The First Pituitary Proteome Landscape From Matched Anterior and Posterior Lobes for a Better Understanding of the Pituitary Gland

To date, very few mass spectrometry (MS)–based proteomics studies are available on the anterior and posterior lobes of the pituitary. In the past, MS-based investigations have focused exclusively on the whole pituitary gland or anterior pituitary lobe. In this study, for the first time, we performed a deep MS-based analysis of five anterior and five posterior matched lobes to build the first lobe-specific pituitary proteome map, which documented 4090 proteins with isoforms, mostly mapped into chromosomes 1, 2, and 11. About 1446 differentially expressed significant proteins were identified, which were studied for lobe specificity, biological pathway enrichment, protein–protein interaction, regions specific to comparison of human brain and other neuroendocrine glands from Human Protein Atlas to identify pituitary-enriched proteins. Hormones specific to each lobe were also identified and validated with parallel reaction monitoring–based target verification. The study identified and validated hormones, growth hormone and thyroid-stimulating hormone subunit beta, exclusively to the anterior lobe whereas oxytocin–neurophysin 1 and arginine vasopressin to the posterior lobe. The study also identified proteins POU1F1 (pituitary-specific positive transcription factor 1), POMC (pro-opiomelanocortin), PCOLCE2 (procollagen C-endopeptidase enhancer 2), and NPTX2 (neuronal pentraxin-2) as pituitary-enriched proteins and was validated for their lobe specificity using parallel reaction monitoring. In addition, three uPE1 proteins, namely THEM6 (mesenchymal stem cell protein DSCD75), FSD1L (coiled-coil domain–containing protein 10), and METTL26 (methyltransferase-like 26), were identified using the NeXtProt database, and depicted tumor markers S100 proteins having high expression in the posterior lobe. In summary, the study documents the first matched anterior and posterior pituitary proteome map acting as a reference control for a better understanding of functional and nonfunctional pituitary adenomas and extrapolating the aim of the Human Proteome Project towards the investigation of the proteome of life.

Modular UBE2H-CTLH E2-E3 complexes regulate erythroid maturation.

The development of haematopoietic stem cells into mature erythrocytes - erythropoiesis - is a controlled process characterized by cellular reorganization and drastic reshaping of the proteome landscape. Failure of ordered erythropoiesis is associated with anaemias and haematological malignancies. Although the ubiquitin system is a known crucial post-translational regulator in erythropoiesis, how the erythrocyte is reshaped by the ubiquitin system is poorly understood. By measuring the proteomic landscape of in vitro human erythropoiesis models, we found dynamic differential expression of subunits of the CTLH E3 ubiquitin ligase complex that formed maturation stage-dependent assemblies of topologically homologous RANBP9- and RANBP10-CTLH complexes. Moreover, protein abundance of CTLH's cognate E2 ubiquitin conjugating enzyme UBE2H increased during terminal differentiation, and UBE2H expression depended on catalytically active CTLH E3 complexes. CRISPR-Cas9-mediated inactivation of CTLH E3 assemblies or UBE2H in erythroid progenitors revealed defects, including spontaneous and accelerated erythroid maturation as well as inefficient enucleation. Thus, we propose that dynamic maturation stage-specific changes of UBE2H-CTLH E2-E3 modules control the orderly progression of human erythropoiesis.

Intercellular cardiomyocyte to cardiac fibroblast signaling regulates global proteome and phosphoproteome landscape to promote oxidative stress via CK2

Intercellular cardiomyocyte to cardiac fibroblast signaling regulates global proteome and phosphoproteome landscape to promote oxidative stress via CK2

Integrated proteomic and transcriptomic landscape of macrophages in mouse tissues

Macrophages are involved in tissue homeostasis and are critical for innate immune responses, yet distinct macrophage populations in different tissues exhibit diverse gene expression patterns and biological processes. While tissue-specific macrophage epigenomic and transcriptomic profiles have been reported, proteomes of different macrophage populations remain poorly characterized. Here we use mass spectrometry and bulk RNA sequencing to assess the proteomic and transcriptomic patterns, respectively, of 10 primary macrophage populations from seven mouse tissues, bone marrow-derived macrophages and the cell line RAW264.7. The results show distinct proteomic landscape and protein copy numbers between tissue-resident and recruited macrophages. Construction of a hierarchical regulatory network finds cell-type-specific transcription factors of macrophages serving as hubs for denoting tissue and functional identity of individual macrophage subsets. Finally, Il18 is validated to be essential in distinguishing molecular signatures and cellular function features between tissue-resident and recruited macrophages in the lung and liver. In summary, these deposited datasets and our open proteome server (http://macrophage.mouseprotein.cn) integrating all information will provide a valuable resource for future functional and mechanistic studies of mouse macrophages.

Dynamic Interactomics by Cross-Linking Mass Spectrometry: Mapping the Daily Cell Life in Postgenomic Era.

The majority of processes that occur in daily cell life are modulated by hundreds to thousands of dynamic protein-protein interactions (PPI). The resulting protein complexes constitute a tangled network that, with its continuous remodeling, builds up highly organized functional units. Thus, defining the dynamic interactome of one or more proteins allows determining the full range of biological activities these proteins are capable of. This conceptual approach is poised to gain further traction and significance in the current postgenomic era wherein the treatment of severe diseases needs to be tackled at both genomic and PPI levels. This also holds true for COVID-19, a multisystemic disease affecting biological networks across the biological hierarchy from genome to proteome to metabolome. In this overarching context and the current historical moment of the COVID-19 pandemic where systems biology increasingly comes to the fore, cross-linking mass spectrometry (XL-MS) has become highly relevant, emerging as a powerful tool for PPI discovery and characterization. This expert review highlights the advanced XL-MS approaches that provide in vivo insights into the three-dimensional protein complexes, overcoming the static nature of common interactomics data and embracing the dynamics of the cell proteome landscape. Many XL-MS applications based on the use of diverse cross-linkers, MS detection methods, and predictive bioinformatic tools for single proteins or proteome-wide interactions were shown. We conclude with a future outlook on XL-MS applications in the field of structural proteomics and ways to sustain the remarkable flexibility of XL-MS for dynamic interactomics and structural studies in systems biology and planetary health.

Single-Cell Proteomic Interrogation of FLT3-ITD Leukemia Compartment Revealsdistinct Leukemia Cell Populations Resistant to Quizartinib, Decitabine and Venetoclax

Triplet therapy (TT) combining Quizartinib(Quiz), Decitabine(Dec) and Venetoclax(Ven) is highly effective against FLT3-ITD acute myeloid leukemia (AML) with high response rates (Yilmaz M, ASCO 2022).Signaling mutations, particularly those involving RAS/MAPK pathway, have emerged as key contributors to primary and secondary resistance to TT. Lack or loss of response to TT is not limited to presence or emergence of clones with signaling mutations and disease relapse occurs in FLT3-ITD AML patients with a variety of other mutations. We hypothesize that resistant leukemia clones have unique proteomic profiles that facilitate survival under therapy pressure and deciphering proteomic profiles at the single-cell level will delineate resistance mechanisms and adaptive responses driven by therapy pressure, and aid in identifying proteomic correlates of response and therapeutic vulnerabilities. To this end, we performed comprehensive single-cell proteomic analysis of serially collected samples (n:162) from patients treated with TT (n:14) and doublet (n:10, DEC+Quiz) therapy, using CyTOF and interrogated leukemia phenotypic profiles, apoptotic networks, signaling pathways, differentiation states and trajectories. First, we performed unsupervised analyses to identify leukemia cells and non-malignant cellular elements of the leukemia compartment in an unbiased manner, interrogated the leukemia proteomic landscape to identify leukemia associated proteomic features that may correlate with clinical response and assessed whether distinct mutation profiles are associated with specific proteomic profiles that may confer resistance to therapy. Since Ven targets BCL2 and FLT3i modulates the expression of anti-apoptotic molecules we assessed the expression of apoptosis regulators across leukemia landscapes and found that leukemia cells with immature phenotype, including those with leukemia stem cell(LSC) phenotype, almost always expressed moderate-high levels of BCL2. Monocytic cells(MC), generally situated in close proximity to leukemia cells in UMAPs, lacked BCL2 expression and had the highest levels of MCL1. Despite expressing moderate levels of MCL1 and BCL-XL, TT was effective in substantially eliminating CD34+ immature leukemia cells (Figure 1). Due to their contrasting apoptosis regulatory networks, we observed a relative enrichment of MCs, either benign or malignant, after TT. Since cells with MC phenotype were inherently resistant to TT we hypothesized that leukemia cell subsets having similar proteomic profiles to MCs will persist after TT. Of note, leukemia cell compartments harbor distinct differentiation hierarchies, the frequencies of which varied across patients. Phenotypic interrogation of leukemia cells (UMAP) revealed that LSCs generally clustered on the opposite pole distant from MCs and leukemia cells on poles facing MCs were more differentiated. Remarkably, FLT3-ITD mutation partners differentially altered and reshaped the proteomic landscape. NPM1 mutant FLT3-ITD AML cells displayed a less diverse leukemia architectural organization with differentiation block. Contrarily, signaling mutation diversified the leukemia landscape into a diverse continuum of differentiation states. Remarkably, we observed that RAS/MAPK mutations in FLT3-ITD AML overcame differentiation block and gave rise to a differentiation continuum encompassing less-differentiated, transitional and differentiated leukemia cells(Figure1). Importantly, we observed that transitional and CD34+ leukemia cells, mapped in close vicinity to MCs, and differentiated MCs preferentially persisted at D28, had active signaling pathways and expressed CD36, which indicates distinct metabolic programs could ensure survival under therapy pressure and also had lower levels of BCL2.The presence of CD34+ leukemia cells at D28, adapted under therapy pressure with persistent signaling at D28, both in CD34+ leukemia or MCs, was indicative of poor clinical outcomes. Conclusion: Single-cell proteomic assessment of FLT3-ITD AML treated with Quiz/Dec/Ven (TT) identifies a unique mode of resistance and proteomic features of surviving cells at D28, and elucidates how RAS/MAPK mutations diversify the leukemia proteomic landscape and modulate the architectural organization which eventually gives rise to emerging clones resistant to therapy. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Proteomic Characterization of Acute Myeloid Leukemia

Introduction: Acute myeloid leukemia (AML) is a disease characterized by the expansion of myeloid blasts in the bone marrow. Recently, we published the results of the first proteogenomic characterization of bone marrow blasts from 177 adult patients with AML (10.1016/j.ccell.2022.02.006) that were uniformly treated with intensive induction chemotherapy. Using mass spectrometry (MS) and next-generation sequencing we curated a multi-omics data set with global protein and gene expression, DNA mutations and chromosomal aberrations. We identified a proteomic subtype characterized by enhanced expression of mitochondrial proteins, significantly poorer overall survival and high sensitivity to inhibitors targeting mitochondrial respiration (Mito-AML). We have now expanded the proteomic data set with bone marrow biopsies from 90 additional adult patients with AML in order to facilitate the proteomic characterization of individual genetic subtypes of AML including nucleophosmin 1 (NPM1)-mutated AML. Methods: We used a label-free (LF), data-independent (DIA) MS-based proteomic workflow to profile protein expression in bone marrow-derived leukemic blasts from 90 additional patients with AML. The patient cohort was similar to our initial cohort with regard to demographic-, disease- and clinical characteristics. We applied stringent filtering, missing value imputation and batch correction to merge the two cohorts. We were able to validate the proteomic Mito-AML subtype in this merged cohort by our previously published machine-learning model. Next, we investigated proteomic differences between NPM1mut (n=89) and NPM1wt (n= 172) patients using linear models; we identified differentially regulated biological processes from the gene ontology (GO) and REACTOME gene sets as well as gene expression signatures of healthy and malignant cellular subtypes (van Galen et al.) using a gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA). Clustering of the NPM1mut proteome was done using a consensus approach on the Euclidean distances and kmeans with k = 2 was chosen based on a set of metrices, including silhouette and concordance score. Results: The global protein expression structure, represented by inter-sample Euclidean distance, was largely independent of blast maturity, genetic risk groups and mutations. In our combined cohort of 267 patients, we identified 33 Mito-AML patients, confirming a frequency of 12 % of this proteomic AML subtype. As published by us previously, Mito-AML showed poor overall survival and independent, significant risk of death in the combined cohort as well as in the 90 patient sub-cohort. Mutations in NPM1 are frequently found in de novo AML and are characterized by a more chemo-sensitive disease. In addition to proteins previously described as being differentially expressed we identified a number of previously unreported proteins including surface proteins (e.g. DmX-like protein 2 (DMXL2)), to be significantly higher expressed in NPM1mut AML. Together with our proteomic data for CD34+ progenitor cells from healthy donors our resource data set might reveal potential target structures for cellular therapies. Among the gene sets differentially enriched between NPM1mut and NPM1wt were terms associated to mitochondrial respiration and metabolism. Interestingly, Mito-AML was enriched among NPM1mut AML (48.5% in NPM1mut vs. 32% in NPM1wt), indicating that Mito-AML is a high-risk subset within NPM1mut AML. Furthermore, we identified regulation of chromosomal and nucleosome architecture amongst the top down-regulated processes in NPM1mut which is in accordance with the role of wild-type NPM1 to chaperone these structural processes. Interestingly, we observed among NPM1mut AML two sub-clusters that were either enriched for blasts with myelo-monocytic differentiation or for progenitor- and stem cell-like blasts indicating a cell-of-origin phenotype. Conclusion: We report the expansion of our previously published proteomic characterization of AML with bone marrow-derived AML blasts from 90 additional patients. We confirm the proteomic Mito-AML subtype and its poor outcome under intensive chemotherapy. We furthermore elucidate the proteomic landscape of NPM1mut AML and identifie two subgroups of NPM1mut AML that are characterized by either myelo-monocytic differentiation or a progenitor and stem cell-like blast state. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Abstract 15399: Proteomic Landscape of Plasma Lipoprotein Responses to Regular Exercise

Introduction: Lipoproteins are among the strongest predictors of CVD and are altered through regular exercise. However, the molecular changes underlying the potential benefits of exercise on plasma lipoproteins are unclear. Methods: Proteins (n=4979) were quantified from the plasma of 647 Black and White adults (56% women, mean age = 34.9 yrs) before and after 20-weeks of endurance exercise training using SomaScan. All subjects had complete data for 7 lipoprotein traits that improved with training: HDL-C, TG, large TG rich lipoprotein particles (LTRLP), small LDL particles (SLDLP), large HDL particles (LHDLP), TRLP size, and LDLP size. Fully adjusted linear mixed models were used to test the association of 1) baseline proteins with baseline lipoproteins and 2) delta proteins with delta lipoproteins (delta = post training - baseline value). Significance was determined as FDR&lt;0.05. Results: We identified numerous proteins associated with baseline levels of at least one of the seven lipoprotein traits (range: 48-1099) and whose changes in response to regular exercise were associated with concomitant changes in lipoproteins (range: 4-95) ( Table 1 ). Substantial overlap was found between proteins associated with lipoproteins across timepoints, with 16 proteins associated with 4 or more lipoprotein traits at both timepoints. Plasma abundance of 12/16 proteins significantly changed with training (FDR &lt;0.05). Additionally, for these proteins plasma abundance changed in concordance with the beneficial direction of the associated lipoprotein trait (e.g., proteins associated with atheroprotective lipoprotein traits increased with training and proteins associated with atherogenic traits decreased). Conclusions: Beneficial alterations to plasma lipoproteins with regular exercise are reflected in changes to the plasma proteome. Proteins identified here may represent novel markers of the benefits of regular exercise and of systemic lipoprotein metabolism.

Proteomic Landscape and Deduced Functions of the Cardiac 14-3-3 Protein Interactome.

Rationale: The 14-3-3 protein family is known to interact with many proteins in non-cardiac cell types to regulate multiple signaling pathways, particularly those relating to energy and protein homeostasis; and the 14-3-3 network is a therapeutic target of critical metabolic and proteostatic signaling in cancer and neurological diseases. Although the heart is critically sensitive to nutrient and energy alterations, and multiple signaling pathways coordinate to maintain the cardiac cell homeostasis, neither the structure of cardiac 14-3-3 protein interactome, nor potential functional roles of 14-3-3 protein-protein interactions (PPIs) in heart has been explored. Objective: To establish the comprehensive landscape and characterize the functional role of cardiac 14-3-3 PPIs. Methods and Results: We evaluated both RNA expression and protein abundance of 14-3-3 isoforms in mouse heart, followed by co-immunoprecipitation of 14-3-3 proteins and mass spectrometry in left ventricle. We identified 52 proteins comprising the cardiac 14-3-3 interactome. Multiple bioinformatic analyses indicated that more than half of the proteins bound to 14-3-3 are related to mitochondria; and the deduced functions of the mitochondrial 14-3-3 network are to regulate cardiac ATP production via interactions with mitochondrial inner membrane proteins, especially those in mitochondrial complex I. Binding to ribosomal proteins, 14-3-3 proteins likely coordinate protein synthesis and protein quality control. Localizations of 14-3-3 proteins to mitochondria and ribosome were validated via immunofluorescence assays. The deduced function of cardiac 14-3-3 PPIs is to regulate cardiac metabolic homeostasis and proteostasis. Conclusions: Thus, the cardiac 14-3-3 interactome may be a potential therapeutic target in cardiovascular metabolic and proteostatic disease states, as it already is in cancer therapy.

Hsa-let-7f-1-3p targeting the circadian gene Bmal1 mediates intervertebral disc degeneration by regulating autophagy

The intervertebral disc has an intrinsic circadian rhythm, elimination of which leads to stress in nucleus pulposus cells (NPCs), contributing to intervertebral disc degeneration (IDD). Disruption or deletion of Bmal1 (a core transcription factor) results in complete loss of circadian rhythms, make mice susceptibility to IDD. However, the underlying mechanism by which Bmal1 mediates IDD is remains enigmatic, and whether there are other upstream factors regulating Bmal1 in NPCs. In our study, we first found that the decrease of Bmal1 was significantly correlated with the grades of IDD. With gain- and loss-of-function, Bmal1 shown a protective effect on NPC viability and functions. Transcriptomic and proteomic landscape reveals the functional contributions of Bmal1, and phosphoproteomic analysis links to autophagy. Bioinformatics analysis identified that a novel miRNA hsa-let-7f-1-3p was directly target Bmal1 3’UTR and negatively correlated with NPC function. Finally, our animal model confirmed the protective role of Bmal1 in rat IDD and this effect could be attenuated by hsa-let-7f-1-3p. The hsa-let-7f-1-3p/Bmal1/autophagy axis provides a potential therapeutic strategy for the clinical treatment of IDD.

Chemoproteomic profiling to identify activity changes and functional inhibitors of DNA-binding proteins

DNA-binding proteins are promising therapeutic targets but are notoriously difficult to drug. Here, we evaluate a chemoproteomic DNA interaction platform as a complementary strategy for parallelized compound profiling. To enable this approach, we determined the proteomic binding landscape of 92 immobilized DNA sequences. Perturbation-induced activity changes of captured transcription factors in disease-relevant settings demonstrated functional relevance of the enriched subproteome. Chemoproteomic profiling of >300 cysteine-directed compounds against a coverage optimized bead mixture, which specifically captures >150 DNA binders, revealed competition of several DNA-binding proteins, including the transcription factors ELF1 and ELF2. We also discovered the first compound that displaces the DNA-repair complex MSH2-MSH3 from DNA. Compound binding to cysteine 252 on MSH3 was confirmed using chemoproteomic reactive cysteine profiling. Overall, these results suggested that chemoproteomic DNA bead pull-downs enable the specific readout of transcription factor activity and can identify functional "hotspots" on DNA binders toward expanding the druggable proteome.

Multiomic analysis reveals conservation of cancer-associated fibroblast phenotypes across species and tissue of origin.

Cancer-associated fibroblasts (CAFs) are integral to the solid tumor microenvironment. CAFs were once thought to be a relatively uniform population of matrix-producing cells, but single-cell RNA sequencing has revealed diverse CAF phenotypes. Here, we further probed CAF heterogeneity with a comprehensive multiomics approach. Using paired, same-cell chromatin accessibility and transcriptome analysis, we provided an integrated analysis of CAF subpopulations over a complex spatial transcriptomic and proteomic landscape to identify three superclusters: steady state-like (SSL), mechanoresponsive (MR), and immunomodulatory (IM) CAFs. These superclusters are recapitulated across multiple tissue types and species. Selective disruption of underlying mechanical force or immune checkpoint inhibition therapy results in shifts in CAF subpopulation distributions and affected tumor growth. As such, the balance among CAF superclusters may have considerable translational implications. Collectively, this research expands our understanding of CAF biology, identifying regulatory pathways in CAF differentiation and elucidating therapeutic targets in a species- and tumor-agnostic manner.