Proteome Quantification Research Articles

Insights concerning advancing the agroecological sustainability of salinity tolerance through proteomics profiling of hexaploid wheat (Triticum aestivum L.)

Wheat plays a significant role in the provision of food and nutrition. However, rapid soil salinization poses a severe threat to its production worldwide. Salt stress stunts wheat growth and quality, resulting in low grain yields. The adaptation of wheat to salinity involves complex physio-biochemical and molecular mechanisms. This study aimed to identify the genetic approaches concerning salt stress-responsive proteins and protein pathways in wheat roots under controlled (0 mM) and NaCl stress (250 mM) solution using label-free proteomic quantification analysis. We found a significant accumulation of Na+ in the leaf and root compared with the controlled condition. Besides, we identified 2436 proteins enhanced under salt stress, with 198 differentially abundant proteins (DAPs), including 170 up-regulated and 28 down-regulated proteins. Many of these proteins were involved in salinity tolerance, including heat shock proteins, glutathione S-transferase, dehydrin, peroxidase, potassium channel beta subunit-type H+-ATPase, superoxide dismutase (Cu-Zn), 14-3-3 protein, peroxidase, malate dehydrogenase, and heat shock proteins. The abundance of a V-type H+ ATPase and 14-3-3 protein was also enhanced, facilitating Na+ compartmentalization in the vacuole through the salt overly sensitive (SOS) pathway. Additionally, many antioxidant enzymes, including peroxidase, glutathione-S-transferase, and thioredoxins, were up-regulated, playing a vital role in detoxifying reactive oxygen species (ROS) in salinity-stressed wheat roots. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses showed that salinity stress enhances the abundance of proteins in several metabolic pathways, such as the citrate cycle, ribosome, oxidative phosphorylation, glycolysis, carbon metabolism, and cytoplasm. We anticipate that the identified proteins under salinity conditions will provide us with a deeper understanding of their application in agriculture biotechnology.

Hypovirus infection induces proliferation and perturbs functions of mitochondria in the chestnut blight fungus.

The chestnut blight fungus, Cryphonectria parasitica, and hypovirus have been used as a model to probe the mechanism of virulence and regulation of traits important to the host fungus. Previous studies have indicated that mitochondria could be the primary target of the hypovirus. In this study, we report a comprehensive and comparative study comprising mitochondrion quantification, reactive oxygen species (ROS) and respiratory efficiency, and quantitative mitochondrial proteomics of the wild-type and virus-infected strains of the chestnut blight fungus. Our data show that hypovirus infection increases the total number of mitochondria, lowers the general ROS level, and increases mitochondrial respiratory efficiency. Quantification of mitochondrial proteomes revealed that a set of proteins functioning in energy metabolism and mitochondrial morphogenesis, as well as virulence, were regulated by the virus. In addition, two viral proteins, p29 and p48, were found to co-fractionate with the mitochondrial membrane and matrix. These results suggest that hypovirus perturbs the host mitochondrial functions to result in hypovirulence.

Interlaboratory Variability in the Madin-Darby Canine Kidney Cell Proteome.

Madin-Darby canine kidney (MDCK) cells are widely used to study epithelial cell functionality. Their low endogenous drug transporter protein levels make them an amenable system to investigate transepithelial permeation and drug transporter protein activity after their transfection. MDCK cells display diverse phenotypic traits, and as such, laboratory-to-laboratory variability in drug permeability assessments is observed. Consequently, in vitro-in vivo extrapolation (IVIVE) approaches using permeability and/or transporter activity data require calibration. A comprehensive proteomic quantification of 11 filter-grown parental or mock-transfected MDCK monolayers from 8 different pharmaceutical laboratories using the total protein approach (TPA) is provided. The TPA enables estimations of key morphometric parameters such as monolayer cellularity and volume. Overall, metabolic liability to xenobiotics is likely to be limited for MDCK cells due to the low expression of required enzymes. SLC16A1 (MCT1) was the highest abundant SLC transporter linked to xenobiotic activity, while ABCC4 (MRP4) was the highest abundant ABC transporter. Our data supports existing findings that claudin-2 levels may be linked to tight junction modulation, thus impacting trans-epithelial resistance. This unique database provides data on more than 8000 protein copy numbers and concentrations, thus allowing an in-depth appraisal of the control monolayers used in each laboratory.

Strategies for consistent and automated quantification of HDL proteome using data-independent acquisition

The introduction of mass spectrometry-based proteomics has revolutionized the high-density lipoprotein (HDL) field, with the description, characterization, and implication of HDL-associated proteins in an array of pathologies. However, acquiring robust, reproducible data is still a challenge in the quantitative assessment of HDL proteome. Data-independent acquisition (DIA) is a mass spectrometry methodology that allows the acquisition of reproducible data, but data analysis remains a challenge in the field. To date, there is no consensus on how to process DIA-derived data for HDL proteomics. Here, we developed a pipeline aiming to standardize HDL proteome quantification. We optimized instrument parameters and compared the performance of four freely available, user-friendly software tools (DIA-NN, EncyclopeDIA, MaxDIA, and Skyline) in processing DIA data. Importantly, pooled samples were used as quality controls throughout our experimental setup. A careful evaluation of precision, linearity, and detection limits, first using E. coli background for HDL proteomics and second using HDL proteome and synthetic peptides, was undertaken. Finally, as a proof of concept, we employed our optimized and automated pipeline to quantify the proteome of HDL and apolipoprotein B–containing lipoproteins. Our results show that determination of precision is key to confidently and consistently quantifying HDL proteins. Taking this precaution, any of the available software tested here would be appropriate for quantification of HDL proteome, although their performance varied considerably.

Proteomic quantification of HER-2 abundance and activation in pancreatic ductal adenocarcinoma tumor specimens using reverse phase protein array.

e16299 Background: Pancreatic adenocarcinoma (PDAC) is associated with poor survival and low response rates to available therapies, warranting a critical need for new treatment paradigms. Enrichment of tumor epithelium via laser microdissection (LMD) prior to reverse phase protein array (RPPA) analysis allows for the quantitative measurement and functional assessment of the activation state of protein drug targets. As part of an IRB-approved Molecular Tumor Board study at Inova Schar Cancer Institute, we harvested enriched tumor epithelium using LMD to support CLIA-based RPPA analysis of patients with pancreatic, breast, and other solid tumor malignancies to examine quantitative expression and activation (phosphorylation) of HER-2/3 and other known cancer-related pathways. Methods: Formalin fixed paraffin embedded (FFPE) primary and/or metastatic tumor biopsy specimens were obtained from 14 patients with PDAC, 14 patients with breast cancer, and 40 patients with other solid tumor malignancies. Tumor epithelium (5-10 µm2) was enriched via LMD prior to RPPA analysis for quantification of HER-2Total and phosphorylated (p)HER-2Y1248 and (p)HER-3Y1289 abundances as part of a 32-marker, CLIA-based RPPA panel examining the total and phosphoprotein abundances of targets with known relevance in solid tumors. Next generation sequencing (NGS; DNA-seq and RNA-seq) was performed on remaining tissue from each specimen. Fisher’s Exact test was used to compare activated HER2Total, pHER2Y1248 and pHER3Y1289. Results: RPPA analysis of LMD enriched tumor samples revealed significant HER-2Total expression in patients with PDAC vs other solid tumors (p=0.0112), with HER-2Total levels comparable to those measured in patients with breast cancer (p=0.0962). The mean HER-2Total abundances in PDAC, breast, and all other solid tumor malignancies were 1.6, 1.3, and 0.9, respectively. Activated pHER-2Y1248 and pHER-3Y1289 abundances did not differ between patients with PDAC vs all other solid tumors or between patients with PDAC vs breast cancer (p>0.05). RNA-seq analysis revealed ERBB2 overexpression in four of the 14 PDAC patients, while ERBB2 amplification by DNA-seq was not observed in any of the PDAC cases. Conclusions: HER-2 expression is not routinely evaluated in clinical practice in PDAC, but our results show higher median expression in PDAC than our solid tumor cohort, with nearly 50% of PDAC cases having total HER2 expression of 2+ or above. Our results may have clinical implications, especially as new classes of HER2 antibody drug conjugates are considered for patients with HER2 non amplified tumors across organ sites, and justify further investigation in a larger cohort. Clinical trial information: U20-11-4308 . [Table: see text]

ProtView: A Versatile Tool for In Silico Protease Evaluation and Selection in a Proteomic and Proteogenomic Context.

Many tools have been created to generate in silico proteome digests with different protease enzymes and provide useful information for selecting optimal digest schemes for specific needs. This can save on time and resources and generate insights on the observable proteome. However, there remains a need for a tool that evaluates digest schemes beyond protein and amino acid coverages in the proteomic domain. Here, we present ProtView, a versatile in silico protease combination digest evaluation workflow that maps in silico-digested peptides to both protein and genome references, so that the potential observable portions of the proteome, transcriptome, and genome can be identified. The proteomic identification and quantification of evidence for transcriptional, co-transcriptional, post-transcriptional, translational, and post-translational regulation can all be examined in silico with ProtView prior to an experiment. Benchmarking against biological data comparing multiple proteases shows that ProtView can correctly estimate performances among the digest schemes. ProtView provides this information in a way that is easy to interpret, allowing for digest schemes to be evaluated before carrying out an experiment, in context that can optimize both proteomic and proteogenomic experiments. ProtView is available at https://github.com/SSPuliasis/ProtView.

PepDESC: A Method for the Detection of Differentially Expressed Proteins for Mass Spectrometry-Based Single-Cell Proteomics Using Peptide-level Information

Single-cell proteomics as an emerging field has exhibited potential in revealing cellular heterogeneity at the functional level. However, accurate interpretation of single-cell proteomics data suffers from challenges such as measurement noise, internal heterogeneity, and the limited sample size of label-free quantitative mass spectrometry. Herein, the author describes peptide-level differential expression analysis for single-cell proteomic (pepDESC), a method for detecting differentially expressed proteins using peptide-level information designed for label-free quantitative mass spectrometry-based single-cell proteomics. While, in this study, the author focuses on the heterogeneity among the limited number of samples, pepDESC is also applicable to regular-size proteomics data. By balancing proteome coverage and quantification accuracy using peptide quantification, pepDESC is demonstrated to be effective in real-world single-cell and spike-in benchmark datasets. By applying pepDESC to published single-mouse macrophage data, the author found a large fraction of differentially expressed proteins among three types of cells, which remarkably revealed distinct dynamics of different cellular functions responding to lipopolysaccharide stimulation.

LFQ-Based Peptide and Protein Intensity Differential Expression Analysis.

Testing for significant differences in quantities at the protein level is a common goal of many LFQ-based mass spectrometry proteomics experiments. Starting from a table of protein and/or peptide quantities from a given proteomics quantification software, many tools and R packages exist to perform the final tasks of imputation, summarization, normalization, and statistical testing. To evaluate the effects of packages and settings in their substeps on the final list of significant proteins, we studied several packages on three public data sets with known expected protein fold changes. We found that the results between packages and even across different parameters of the same package can vary significantly. In addition to usability aspects and feature/compatibility lists of different packages, this paper highlights sensitivity and specificity trade-offs that come with specific packages and settings.

Repeat-Enhancing Featured Ion-Guided Stoichiometry for Identification and Quantification of Direct Infusion Proteome.

The direct infusion-shotgun proteome analysis (DI-SPA) alongside data-independent acquisition mass spectrometry achieved fast proteome identification and quantification without chromatographic separation. However, robust peptide identification and quantification (label and label-free) for the DI-SPA data is still insufficient. We find that in the absence of chromatography, the identification of DI-SPA can be boosted by extending acquisition cycles repeatedly and maximizing the utilization of the featured repetition characteristics, combined with the machine learning-based automatic peptide scoring strategy. Here, we present the repeat-enhancing featured ion-guided stoichiometry (RE-FIGS), a complete and compact solution to (repeated) DI-SPA data. Using our strategy, the peptide identification can be improved above 30% with high reproducibility (70.0%). Notably, the label-free quantification of repeated DI-SPA can be successfully obtained with high accuracy (mean median error, 0.108) and high reproducibility (median error, 0.001). We believe our RE-FIGS method could boost the broad application of the (repeated) DI-SPA method and offer a new choice for proteomic analysis.

Quantification of snake venom proteomes by mass spectrometry-considerations and perspectives.

The advent of soft ionization mass spectrometry-based proteomics in the 1990s led to the development of a new dimension in biology that conceptually allows for the integral analysis of whole proteomes. This transition from a reductionist to a global-integrative approach is conditioned to the capability of proteomic platforms to generate and analyze complete qualitative and quantitative proteomics data. Paradoxically, the underlying analytical technique, molecular mass spectrometry, is inherently nonquantitative. The turn of the century witnessed the development of analytical strategies to endow proteomics with the ability to quantify proteomes of model organisms in the sense of "an organism for which comprehensive molecular (genomic and/or transcriptomic) resources are available." This essay presents an overview of the strategies and the lights and shadows of the most popular quantification methods highlighting the common misuse of label-free approaches developed for model species' when applied to quantify the individual components of proteomes of nonmodel species (In this essay we use the term "non-model" organisms for species lacking comprehensive molecular (genomic and/or transcriptomic) resources, a circumstance that, as we detail in this review-essay, conditions the quantification of their proteomes.). We also point out the opportunity of combining elemental and molecular mass spectrometry systems into a hybrid instrumental configuration for the parallel identification and absolute quantification of venom proteomes. The successful application of this novel mass spectrometry configuration in snake venomics represents a proof-of-concept for a broader and more routine application of hybrid elemental/molecular mass spectrometry setups in other areas of the proteomics field, such as phosphoproteomics, metallomics, and in general in any biological process where a heteroatom (i.e., any atom other than C, H, O, N) forms integral part of its mechanism.

Proteomic Identification and Quantification of Secretory Proteins in Human Dermal Fibroblast-Conditioned Medium for Wound Repair and Hair Regeneration.

Human dermal fibroblasts secrete numerous growth factors and proteins that have been suggested to promote wound repair and hair regeneration. Human dermal fibroblast-conditioned medium (DFCM) was prepared, and proteomic analysis was performed. Secretory proteins in DFCM were identified using 1-dimensional sodium dodecyl sulphate-polyacrylamide gel electrophoresis, in-gel trypsin protein digestion, and quantitative liquid chromatography tandem mass spectrometry (LC-MS/MS). Identified proteins were analyzed using bioinformatic methods for the classification and evaluation of protein-protein interactions. Using LC-MS/MS, 337 proteins were identified in DFCM. Among them, 160 proteins were associated with wound repair, and 57 proteins were associated with hair regeneration. Protein-protein interaction network analysis of 160 DFCM proteins for wound repair at the highest confidence score (0.9) revealed that 110 proteins were grouped into seven distinctive interaction networks. Additionally, protein-protein interaction network analysis of 57 proteins for hair regeneration at the highest confidence score revealed that 29 proteins were grouped into five distinctive interaction networks. The identified DFCM proteins were associated with several pathways for wound repair and hair regeneration, including epidermal growth factor receptor, fibroblast growth factor, integrin, Wnt, cadherin, and transforming growth factor-β signaling pathways. DFCM contains numerous secretory proteins that comprise groups of protein-protein interaction networks that regulate wound repair and hair regeneration.

Abstract 1138: Novel SMARCA2 degrading bifunctional molecules as therapeutics in SMARCA4 mutant lung cancer

Abstract Lung cancer is the top cause of cancer mortality. Despite recent advances, the majority of patients with lung cancer still lack effective therapeutic options, underscoring the dire need for additional treatment approaches. Genomic studies have identified frequent mutations in subunits of the SWI/SNF chromatin remodeling complex including SMARCA4 and ARID1A in non-small cell lung cancer with a frequency of up to 33% in advanced stage disease, making it the most frequently mutated complex in lung cancer. Recent reports, and our own data, have identified the paralogue SMARCA2 to be synthetic lethal to SMARCA4 suggesting SMARCA2 is a valuable therapeutic target. However, the discovery of selective inhibitors of SMARCA2 has been challenging. To overcome this hurdle, we have utilized iterative structure-activity relationship (SAR) studies to develop novel, potent and selective SMARCA2 degrading small molecules based on proteolysis targeting chimera (PROTAC) technology. We demonstrated that YD23, our lead SMARCA2 PROTAC, potently and selectively induces degradation of SMARCA2. Using global proteomic analysis and quantification of more than 8000 proteins, we showed that our SMARCA2 PROTAC is highly selective for SMARCA2. Importantly, we showed that YD23 selectively inhibits growth of SMARCA4 mutant lung cancer cells in vitro. Mechanistically, we demonstrated that YD23 reduces chromatin accessibility only in SMARCA4 deficient cells. In particular, YD23 profoundly decreased chromatin accessibility at enhancers of a number of genes including cell cycle and cell growth regulatory genes. Gene expression profiling and pathway analysis indicated that various cell cycle genes were downregulated by YD23 consistent with the reduced chromatin accessibility at their regulatory regions. In conclusion, our study provides a potent chemical probe for studying the synthetic lethal interaction between SMARCA2 and SMARCA4, dissect the chromatin and epigenetic landscape alterations and lay the foundation for future preclinical and clinical development of SMARCA2 degraders as therapeutics. Citation Format: Sasi Kotagiri, Nicholas Blazanin, Yuanxin Xi, Jing Wang, Yonathan Lissanu. Novel SMARCA2 degrading bifunctional molecules as therapeutics in SMARCA4 mutant lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1138.

Abstract 5726: Pan-cancer proteogenomics expands the landscape of therapeutic targets

Abstract Background: Molecularly targeted therapies are critical for improving cancer treatment. Since proteins are the targets of these therapies and functional effectors of genomic aberrations, proteogenomics data from the Clinical Proteomics Tumor Analysis Consortium (CPTAC) provides an unprecedented opportunity to characterize existing and future therapeutic targets for cancer treatment. Approach: CPTAC proteogenomics data from >1000 cancer patients spanning 10 cancer types was used to evaluate current and potential therapeutic targets curated from four databases. Cell line data from DepMap was further integrated to distinguish causations from associations. Computational pipelines were deployed to identify synthetic lethality for targeting tumor suppressor loss and to prioritize tumor associated antigens as immunotherapy targets. Results: We systematically collected 3050 druggable proteins and classified them into 5 tiers to facilitate different applications such as companion diagnostics, drug repurposing, and new therapy development. Many druggable proteins showed poor mRNA-protein correlation, including secreted proteins and proteins whose abundance was correlated with their interaction partners instead of cognate mRNA, highlighting the necessity of direct proteomic quantification of drug targets. 618 druggable proteins showed both overexpression in tumors compared to normal and significant dependency in CRISPR-Cas9 screens of cell lines of the same lineage. Notably, PAK1, a kinase targeted by investigational drugs, demonstrated both overexpression and dependency in all cancer types. A similar analysis of phosphoproteomics data focusing on known activating sites of druggable proteins further revealed targetable dependencies driven by protein hyperactivation. The phosphosite pS50 on PTPN1, a phosphatase targeted by experimental drugs, was increased in 7 cancer types and PTPN1 demonstrated dependency in related cancer cell lines. Based on tumor proteogenomic data and cell line CRISPR-Cas9 screen data, we identified synthetic lethality for difficult to target tumor suppressor losses, revealing TP53 mutations as a candidate biomarker to select breast cancer patients for CHEK1 inhibition, and endometrial cancer patients for treatment with doxorubicin. We identified 140 proteins whose expression was restricted in normal tissues but abnormal in tumors. Experimental analysis of peptides predicted to have high binding affinity to the most common allotype HLA-A02 for 7 prioritized proteins identified 21 peptides from 5 proteins with both strong binding affinity and immunogenicity which could be further investigated as immunotherapy targets. Conclusion: We generate a comprehensive resource of protein and peptide targets that covers multiple therapeutic modalities. This unique resource will pave the way for repurposing of currently available drugs and developing new drugs for cancer treatment. Citation Format: Jonathan T. Lei, Sara R. Savage, Xinpei Yi, Bo Wen, Hongwei Zhao, Lauren K. Somes, Paul W. Shafer, Yongchao Dou, Qiang Gao, Valentina Hoyos, Bing Zhang. Pan-cancer proteogenomics expands the landscape of therapeutic targets. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5726.

PSMD2 contributes to the progression of esophageal squamous cell carcinoma by repressing autophagy

BackgroundThe ubiquitin–proteasome and autophagy-lysosomal systems collaborate in regulating the levels of intracellular proteins. Dysregulation of protein homeostasis is a central feature of malignancy. The gene encoding 26S proteasome non-ATPase regulatory subunit 2 (PSMD2) of the ubiquitin–proteasome system is an oncogene in various types of cancer. However, the detailed role of PSMD2 in autophagy and its relationship to tumorigenesis in esophageal squamous cell carcinoma (ESCC) remain unknown. In the present study, we have investigated the tumor-promoting roles of PSMD2 in the context of autophagy in ESCC.MethodsMolecular approaches including DAPgreen staining, 5-Ethynyl-2ʹ-deoxyuridine (EdU), cell counting kit 8 (CCK8), colony formation, transwell assays, and cell transfection, xenograft model, immunoblotting and Immunohistochemical analysis were used to investigate the roles of PSMD2 in ESCC cells. Data-independent acquisition (DIA) quantification proteomics analysis and rescue experiments were used to study the roles of PSMD2 in ESCC cells.ResultsWe demonstrate that the overexpression of PSMD2 promotes ESCC cell growth by inhibiting autophagy and is correlated with tumor progression and poor prognosis of ESCC patients. DIA quantification proteomics analysis shows a significant positive correlation between argininosuccinate synthase 1 (ASS1) and PSMD2 levels in ESCC tumors. Further studies indicate that PSMD2 activates the mTOR pathway by upregulating ASS1 to inhibit autophagy.ConclusionsPSMD2 plays an important role in repressing autophagy in ESCC, and represents a promising biomarker to predict prognosis and a therapeutic target of ESCC patients.

"Cell Surface Capture" Workflow for Label-Free Quantification of the Cell Surface Proteome.

Over the past decade, mass spectrometry-based proteomics has enabled an in-depth characterization of biological systems across a broad array of applications. The cell surface proteome ("surfaceome") in human disease is of significant interest, as plasma membrane proteins are the primary target of most clinically approved therapeutics, as well as a key feature by which to diagnostically distinguish diseased cells from healthy tissues. However, focused characterization of membrane and surface proteins of the cell has remained challenging, primarily due to the complexity of cellular lysates, which mask proteins of interest by other high-abundance proteins. To overcome this technical barrier and accurately define the cell surface proteome of various cell types using mass spectrometry proteomics, it is necessary to enrich the cell lysate for cell surface proteins prior to analysis on the mass spectrometer. This paper presents a detailed workflow for labeling cell surface proteins from cancer cells, enriching these proteins out of the cell lysate, and subsequent sample preparation for mass spectrometry analysis.

Discovery Proteomics and Absolute Protein Quantification Can Be Performed Simultaneously on an Orbitrap-Based Mass Spectrometer.

Mass spectrometry (MS) has steadily moved into the forefront of quantification-centered protein research. Protein cleavage isotope dilution MS is a proven way for quantifying proteins by using an isotope-labeled analogue of a peptide fragment of the parent protein as an internal standard. Parallel reaction monitoring (PRM) has become the go-to approach for such quantification on an Orbitrap-based instrument as it is assumed that the instrument sensitivity is enhanced. We performed a comparative study on data-dependent acquisition (DDA) and PRM-based workflows to quantify egg yolk protein precursors or vitellogenins (VTGs) Aa, Ab, and C in striped bass (Morone saxatilis). VTG proportions serve as a developmental measure of egg quality, possibly changing with the environment, and have been studied as an indicator of the health of North Carolina stocks. Based on single-factor analysis of variance comparisons of mean VTG amounts across fish from the same sample groupings, our results indicate that there is no statistical difference between MS1-based and MS2-based VTG quantification. We further conclude that DDA is able to deliver both discovery data and absolute quantification data in the same experiment.

Identification and Quantification of S-Sulfenylation Proteome of Mycobacterium tuberculosis under Oxidative Stress.

The ability to maintain redox homeostasis is critical for Mycobacterium tuberculosis (Mtb) to survive the redox stress of the host. There are many antioxidant systems in Mtb to ensure its normal replication and survival in the host, and cysteine thiols are one of them. S-sulfenylation is one of the reversible modifications of cysteine thiols to resist oxidative stress. In the study, we investigated the total cysteine thiols modification and S-sulfenylation modification of Mtb proteome under the oxidative stress provided by hydrogen peroxide. To determine and quantify the S-sulfenylation modified proteins, high specific IodoTMT6plex reagents and high resolution mass spectrometry were used to label and quantify the peptides and proteins modified. There are significant differences for the total cysteine modification levels of 279 proteins and S-sulfenylation modification levels of 297 proteins under hydrogen peroxide stress. Functional enrichment analysis indicated that these cysteine-modified proteins were involved in the oxidation-reduction process, fatty acid biosynthetic process, stress response, protein repair, cell wall, etc. In conclusion, our study provides a view of cysteine modifications of the Mtb proteome under oxidative stress, revealing a series of proteins that may play a role in maintaining redox homeostasis. IMPORTANCE With the continuous spread of drug-resistant tuberculosis, there is an urgent need for new antituberculosis drugs with new mechanisms. The ability of Mtb to resist oxidative stress is extremely important for maintaining redox homeostasis and survival in the host. The reversible modifications of cysteine residues have a dual role of protection from irreversible damage to protein functions and regulation, which plays an important role in the redox homeostasis system. Thus, to discover cysteine modification changes in the proteome level under oxidative stress is quintessential to elucidate its antioxidant mechanism. Our results provided a list of proteins involved in the antioxidant process that potentially could be considered targets for drug discovery and vaccine development. Furthermore, it is the first study to determine and quantify the S-sulfenylation-modified proteins in Mtb, which provided better insight into the Mtb response to the host oxidative defense and enable a deeper understanding of Mtb survival strategies.

Exogenous aralar/slc25a12 can replace citrin/slc25a13 as malate aspartate shuttle component in liver

The deficiency of CITRIN, the liver mitochondrial aspartate–glutamate carrier (AGC), is the cause of four human clinical phenotypes, neonatal intrahepatic cholestasis caused by CITRIN deficiency (NICCD), silent period, failure to thrive and dyslipidemia caused by CITRIN deficiency (FTTDCD), and citrullinemia type II (CTLN2). Clinical symptoms can be traced back to disruption of the malate-aspartate shuttle due to the lack of citrin. A potential therapy for this condition is the expression of aralar, the AGC present in brain, to replace citrin. To explore this possibility we have first verified that the NADH/NAD+ ratio increases in hepatocytes from citrin(−/−) mice, and then found that exogenous aralar expression reversed the increase in NADH/NAD+ observed in these cells. Liver mitochondria from citrin (−/−) mice expressing liver specific transgenic aralar had a small (~ 4–6 nmoles x mg prot−1 x min−1) but consistent increase in malate aspartate shuttle (MAS) activity over that of citrin(−/−) mice. These results support the functional replacement between AGCs in the liver. To explore the significance of AGC replacement in human therapy we studied the relative levels of citrin and aralar in mouse and human liver through absolute quantification proteomics. We report that mouse liver has relatively high aralar levels (citrin/aralar molar ratio of 7.8), whereas human liver is virtually devoid of aralar (CITRIN/ARALAR ratio of 397). This large difference in endogenous aralar levels partly explains the high residual MAS activity in liver of citrin(−/−) mice and why they fail to recapitulate the human disease, but supports the benefit of increasing aralar expression to improve the redox balance capacity of human liver, as an effective therapy for CITRIN deficiency.

Effects of Cysticercus cellulosae Excretory-Secretory Antigens on the TGF-β Signaling Pathway and Th17 Cell Differentiation in Piglets, a Proteomic Analysis.

Excretory-secretory antigens (ESAs) of Cysticercus cellulosae can directly regulate the proliferation and differentiation of host T regulatory (Treg) cells, thus inhibiting host immune responses. However, previous studies have only focused on this phenomenon, and the molecular mechanisms behind the ways in which C. cellulosae ESAs regulate the differentiation of host Treg/Th17 cells have not been reported. We collected CD3+ T cells stimulated by C. cellulosae ESAs through magnetic bead sorting and used label-free quantification (LFQ) proteomics techniques to analyze the signaling pathways of C. cellulosae ESAs regulating Treg/Th17 cell differentiation. Through gene set enrichment analysis (GSEA), we found that C. cellulosae ESAs could upregulate the TGF-β signaling pathway and downregulate Th17 cell differentiation in piglet T cells. Interestingly, we also found that the IL-2/STAT5 signaling pathway also affects the downregulation of Th17 cell differentiation. C. cellulosae ESAs activate the TGF-β signaling pathway and the IL-2/STAT5 signaling pathway in host T cells to further regulate the differentiation of Treg/Th17 cells in order to evade host immune attack. This study lays the foundation for the subsequent verification of these pathways, and further clarifies the molecular mechanism of C. cellulosae-mediated immune evasion.

Inter-Regional Proteomic Profiling of the Human Brain Using an Optimized Protein Extraction Method from Formalin-Fixed Tissue to Identify Signaling Pathways.

Proteomics offers vast potential for studying the molecular regulation of the human brain. Formalin fixation is a common method for preserving human tissue; however, it presents challenges for proteomic analysis. In this study, we compared the efficiency of two different protein-extraction buffers on three post-mortem, formalin-fixed human brains. Equal amounts of extracted proteins were subjected to in-gel tryptic digestion and LC-MS/MS. Protein, peptide sequence, and peptide group identifications; protein abundance; and gene ontology pathways were analyzed. Protein extraction was superior using lysis buffer containing tris(hydroxymethyl)aminomethane hydrochloride, sodium dodecyl sulfate, sodium deoxycholate, and Triton X-100 (TrisHCl, SDS, SDC, Triton X-100), which was then used for inter-regional analysis. Pre-frontal, motor, temporal, and occipital cortex tissues were analyzed by label free quantification (LFQ) proteomics, Ingenuity Pathway Analysis and PANTHERdb. Inter-regional analysis revealed differential enrichment of proteins. We found similarly activated cellular signaling pathways in different brain regions, suggesting commonalities in the molecular regulation of neuroanatomically-linked brain functions. Overall, we developed an optimized, robust, and efficient method for protein extraction from formalin-fixed human brain tissue for in-depth LFQ proteomics. We also demonstrate herein that this method is suitable for rapid and routine analysis to uncover molecular signaling pathways in the human brain.