Mass Spectrometry-Driven Discovery of Neuropeptides Mediating Nictation Behavior of Nematodes.

Neuropeptides regulate animal physiology and behavior, making them widely studied targets of functional genetics research. While the field often relies on differential -omics approaches to build hypotheses, no such method exists for neuropeptidomics. It would nonetheless be valuable for studying behaviors suspected to be regulated by neuropeptides, especially when little information is otherwise available. This includes nictation, a phoretic strategy of Caenorhabditis elegans dauers that parallels host-finding strategies of infective juveniles of many pathogenic nematodes. We here developed a targeted peptidomics method for the model organism C. elegans and show that 161 quantified neuropeptides are more abundant in its dauer stage compared with L3 juveniles. Many of these have orthologs in the commercially relevant pathogenic nematode Steinernema carpocapsae, in whose infective juveniles, we identified 126 neuropeptides in total. Through further behavioral genetics experiments, we identify flp-7 and flp-11 as novel regulators of nictation. Our work advances knowledge on the genetics of nictation behavior and adds comparative neuropeptidomics as a tool to functional genetics workflows.

Proteomic Analysis Identifies GSN as a Noninvasive Circulating Serum Biomarker for Predicting Early Recurrence of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is susceptible to early recurrence, but it lacks effective predictive biomarkers. In this study, we retrospectively selected 179 individuals as a discovery cohort (126 HCC patients and 53 liver cirrhosis (LC) patients) for screening candidate serum biomarkers of early recurrence based on data independent acquisition-mass spectrometry strategy. And then, the candidate biomarkers were validated in an additional independent cohort with 192 individuals (142 HCC patients and 50 LC patients) using parallel reaction monitoring targeted quantitative techniques (PXD047852). Eventually, we validated that gelsolin (GSN) concentrations were significantly lower in HCC than in LC (p < 0.0001), patients with low GSN concentrations had a poor prognosis (p < 0.0001), and GSN concentrations were significantly lower in early recurrence HCC than in late recurrence HCC (p < 0.0001). These trends were also observed in alpha-fetoprotein (AFP)-negative HCC patients. The area under the curve of machine-learning-based predictive model (GSN and microvascular invasion) for predicting early recurrence risk reached 0.803 (95% confidence interval (CI): 0.786-0.820) and maintained the same efficacy in AFP-negative patients. In conclusion, GSN is a novel serum biomarker for early recurrence of HCC. The model could provide timely warning to HCC patients at high risk of recurrence.

Targeted Mass Spectrometry Analyses of Somatic Mutations in Colorectal Cancer Specimens Using Differential Ion Mobility.

Identification of K-Ras and B-Raf mutations in colorectal cancer (CRC) is essential to predict patients' response to anti-EGFR therapy and formulate appropriate therapeutic strategies to improve prognosis and survival. Here, we combined parallel reaction monitoring (PRM) with high-field asymmetric waveform ion mobility (FAIMS) to enhance mass spectrometry sensitivity and improve the identification of low-abundance K-Ras and B-Raf mutations in biological samples without immunoaffinity enrichment. In targeted LC-MS/MS analyses, FAIMS reduced the occurrence of interfering ions and enhanced precursor ion purity, resulting in a 3-fold improvement in the detection limit for K-Ras and B-Raf mutated peptides. In addition, the ion mobility separation of isomeric peptides using FAIMS facilitated the unambiguous identification of K-Ras G12D and G13D peptides. The application of targeted LC-MS/MS analyses using FAIMS is demonstrated for the detection and quantitation of B-Raf V600E, K-Ras G12D, G13D, and G12V in CRC cell lines and primary specimens.

Differential Contributions of Interferon Classes to Host Inflammatory Responses and Restricting Virus Progeny Production.

Fundamental to mammalian intrinsic and innate immune defenses against pathogens is the production of Type I and Type II interferons, such as IFN-ß and IFN-γ, respectively. The comparative effects of IFN classes on the cellular proteome, protein interactions, and virus restriction within cell types that differentially contribute to immune defenses are needed for understanding immune signaling. Here, a multilayered proteomic analysis, paired with biochemical and molecular virology assays, allows distinguishing host responses to IFN-ß and IFN-γ and associated antiviral impacts during infection with several ubiquitous human viruses. In differentiated macrophage-like monocytic cells, we classified proteins upregulated by IFN-ß, IFN-γ, or pro-inflammatory LPS. Using parallel reaction monitoring, we developed a proteotypic peptide library for shared and unique ISG signatures of each IFN class, enabling orthogonal confirmation of protein alterations. Thermal proximity coaggregation analysis identified the assembly and maintenance of IFN-induced protein interactions. Comparative proteomics and cytokine responses in macrophage-like monocytic cells and primary keratinocytes provided contextualization of their relative capacities to restrict virus production during infection with herpes simplex virus type-1, adenovirus, and human cytomegalovirus. Our findings demonstrate how IFN classes induce distinct ISG abundance and interaction profiles that drive antiviral defenses within cell types that differentially coordinate mammalian immune responses.

Single Isotopologue for In-Sample Calibration and Absolute Quantitation by LC-MS/MS.

Targeted mass spectrometry (MS)-based absolute quantitative analysis has been increasingly used in biomarker discovery. The ability to accurately measure the masses by MS enabled the use of isotope-incorporated surrogates having virtually identical physiochemical properties with the target analytes as calibrators. Such a unique capacity allowed for accurate in-sample calibration. Current in-sample calibration uses multiple isotopologues or structural analogues for both the surrogate and the internal standard. Here, we simplified this common practice by using endogenous light peptides as the internal standards and used a mathematical deduction of "heavy matching light, HML" to directly quantify an endogenous analyte. This method provides all necessary assay performance parameters in the authentic matrix, including the lower limit of quantitation (LLOQ) and intercept of the calibration curve, by using only a single isotopologue of the analyte. This method can be applied to the quantitation of proteins, peptides, and small molecules. Using this method, we quantified the efficiency of heart tissue digestion and recovery using sodium deoxycholate as a detergent and two spiked exogenous proteins as mimics of heart proteins. The results demonstrated the robustness of the assay.

Simultaneous targeted and discovery-driven clinical proteotyping using hybrid-PRM/DIA.

BACKGROUND: Clinical samples are irreplaceable, and their transformation into searchable and reusable digital biobanks is critical for conducting statistically empowered retrospective and integrative research studies. Currently, mainly data-independent acquisition strategies are employed to digitize clinical sample cohorts comprehensively. However, the sensitivity of DIA is limited, which is why selected marker candidates are often additionally measured targeted by parallel reaction monitoring. METHODS: Here, we applied the recently co-developed hybrid-PRM/DIA technology as a new intelligent data acquisition strategy that allows for the comprehensive digitization of rare clinical samples at the proteotype level. Hybrid-PRM/DIA enables enhanced measurement sensitivity for a specific set of analytes of current clinical interest by the intelligent triggering of multiplexed parallel reaction monitoring (MSxPRM) in combination with the discovery-driven digitization of the clinical biospecimen using DIA. Heavy-labeled reference peptides were utilized as triggers for MSxPRM and monitoring of endogenous peptides. RESULTS: We first evaluated hybrid-PRM/DIA in a clinical context on a pool of 185 selected proteotypic peptides for tumor-associated antigens derived from 64 annotated human protein groups. We demonstrated improved reproducibility and sensitivity for the detection of endogenous peptides, even at lower concentrations near the detection limit. Up to 179 MSxPRM scans were shown not to affect the overall DIA performance. Next, we applied hybrid-PRM/DIA for the integrated digitization of biobanked melanoma samples using a set of 30 AQUA peptides against 28 biomarker candidates with relevance in molecular tumor board evaluations of melanoma patients. Within the DIA-detected approximately 6500 protein groups, the selected marker candidates such as UFO, CDK4, NF1, and PMEL could be monitored consistently and quantitatively using MSxPRM scans, providing additional confidence for supporting future clinical decision-making. CONCLUSIONS: Combining PRM and DIA measurements provides a new strategy for the sensitive and reproducible detection of protein markers from patients currently being discussed in molecular tumor boards in combination with the opportunity to discover new biomarker candidates.

Quantification of putative ovarian cancer serum protein biomarkers using a multiplexed targeted mass spectrometry assay.

BACKGROUND: Ovarian cancer is the most lethal gynecologic malignancy in women, and high-grade serous ovarian cancer (HGSOC) is the most common subtype. Currently, no clinical test has been approved by the FDA to screen the general population for ovarian cancer. This underscores the critical need for the development of a robust methodology combined with novel technology to detect diagnostic biomarkers for HGSOC in the sera of women. Targeted mass spectrometry (MS) can be used to identify and quantify specific peptides/proteins in complex biological samples with high accuracy, sensitivity, and reproducibility. In this study, we sought to develop and conduct analytical validation of a multiplexed Tier 2 targeted MS parallel reaction monitoring (PRM) assay for the relative quantification of 23 putative ovarian cancer protein biomarkers in sera. METHODS: To develop a PRM method for our target peptides in sera, we followed nationally recognized consensus guidelines for validating fit-for-purpose Tier 2 targeted MS assays. The endogenous target peptide concentrations were calculated using the calibration curves in serum for each target peptide. Receiver operating characteristic (ROC) curves were analyzed to evaluate the diagnostic performance of the biomarker candidates. RESULTS: We describe an effort to develop and analytically validate a multiplexed Tier 2 targeted PRM MS assay to quantify candidate ovarian cancer protein biomarkers in sera. Among the 64 peptides corresponding to 23 proteins in our PRM assay, 24 peptides corresponding to 16 proteins passed the assay validation acceptability criteria. A total of 6 of these peptides from insulin-like growth factor-binding protein 2 (IBP2), sex hormone-binding globulin (SHBG), and TIMP metalloproteinase inhibitor 1 (TIMP1) were quantified in sera from a cohort of 69 patients with early-stage HGSOC, late-stage HGSOC, benign ovarian conditions, and healthy (non-cancer) controls. Confirming the results from previously published studies using orthogonal analytical approaches, IBP2 was identified as a diagnostic biomarker candidate based on its significantly increased abundance in the late-stage HGSOC patient sera compared to the healthy controls and patients with benign ovarian conditions. CONCLUSIONS: A multiplexed targeted PRM MS assay was applied to detect candidate diagnostic biomarkers in HGSOC sera. To evaluate the clinical utility of the IBP2 PRM assay for HGSOC detection, further studies need to be performed using a larger patient cohort.

Exoproteome analysis of Pseudomonas aeruginosa response to high alkane stress.

Microbial biodegradation serves as an effective approach to treat oil pollution. However, the application of such methods for the degrading long-chain alkanes still encounters significant challenges. Comparative proteomics has extensively studied the intracellular proteins of bacteria that degrade short- and medium-chain alkanes, but the role and mechanism of extracellular proteins in many microorganism remain unclear. To enhance our understanding of the roles of extracellular proteins in the adaptation to long-chain alkanes, a label-free LC-MS/MS strategy was applied for the relative quantification of extracellular proteins of Pseudomonas aeruginosa SJTD-1-M (ProteomeXchange identifier PXD014638). 444 alkane-sentitive proteins were acquired and their cell localization analysis was performed using the Pseudomonas Genome Database. Among them, 111 proteins were found to be located in extracellular or Outer Membrane Vesicles (OMVs). The alkane-induced abundance of 11 extracellular or OMV target proteins was confirmed by parallel reaction monitoring (PRM). Furthermore, we observed that the expression levels of three proteins (Pra, PA2815, and FliC) were associated with the carbon chain length of the added alkane in the culture medium. The roles of these proteins in cell mobility, alkane emulsification, assimilation, and degradation were further discussed. OMVs were found to contain a number of enzymes involved in alkane metabolism, fatty acid beta-oxidation, and the TCA cycle, suggesting their potential as sites for facilitated alkane degradation. In this sense, this exoproteome analysis contributes to a better understanding of the role of extracellular proteins in the hydrocarbon treatment process.

Combinatory data-independent acquisition and parallel reaction monitoring method for revealing the lipid metabolism biomarkers of coronary heart disease and its comorbidities.

Disorders of lipid metabolism are a common cause of coronary heart disease (CHD) and its comorbidities. In this study, ultra-performance liquid chromatography-high-resolution mass spectrometry in data-independent acquisition (DIA) mode was applied to collect abundant tandem mass spectrometry data, which provided valuable information for lipid annotation. For the lipid isomers that could not be completely separated by chromatography, parallel reaction monitoring (PRM) mode was used for quantification. A total of 223 plasma lipid metabolites were annotated, and 116 of them were identified for their fatty acyl chain composition and location. In addition, 152 plasma lipids in patients with CHD and its comorbidities were quantitatively analyzed. Multivariate statistical analysis and metabolic pathway analysis demonstrated that glycerophospholipid and sphingolipid metabolism deserved more attention for CHD. This study proposed a method combining DIA and PRM for high-throughput characterization of plasma lipids. The results also improved our understanding of metabolic disorders of CHD and its comorbidities, which can provide valuable suggestions for medical intervention.

Global Phosphoproteomics Unveils Kinase-Regulated Networks in Systemic Lupus Erythematosus.

Systemic lupus erythematosus (SLE) is an autoimmune disorder characterized by immune complex deposition in multiple organs. Despite the severe symptoms caused by it, the underlying mechanisms of SLE, especially phosphorylation-dependent regulatory networks remain elusive. Herein, by combining high-throughput phosphoproteomics with bioinformatics approaches, we established the global phosphoproteome landscape of the peripheral blood mononuclear cells from a large number of SLE patients, including the remission stage (SLE_S), active stage (SLE_A), rheumatoid arthritis, and healthy controls, and thus a deep mechanistic insight into SLE signaling mechanism was yielded. Phosphorylation upregulation was preferentially in patients with SLE (SLE_S and SLE_A) compared with healthy controls and rheumatoid arthritis populations, resulting in an atypical enrichment in cell adhesion and migration signatures. Several specifically upregulated phosphosites were identified, and the leukocyte transendothelial migration pathway was enriched in the SLE_A group by expression pattern clustering analysis. Phosphosites identified by 4D-label-free quantification unveiled key kinases and kinase-regulated networks in SLE, then further validated by parallel reaction monitoring. Some of these validated phosphosites including vinculin S275, vinculin S579 and transforming growth factor beta-1-induced transcript 1 S68, primarily were phosphorylation of Actin Cytoskeleton -related proteins. Some predicted kinases including MAP3K7, TBK1, IKKß, and GSK3ß, were validated by Western blot using kinases phosphorylation sites-specific antibodies. Taken together, the study has yielded fundamental insights into the phosphosites, kinases, and kinase-regulated networks in SLE. The map of the global phosphoproteomics enables further understanding of this disease and will provide great help for seeking more potential therapeutic targets for SLE.

Proteomics revealed an association between ribosome-associated proteins and amyloid beta deposition in Alzheimer's disease.

Most scholars believe that amyloid-beta (Aß) has the potential to induce apoptosis, stimulate an inflammatory cascade, promote oxidative stress and exacerbate the pathological progression of Alzheimer's disease (AD). Therefore, it is crucial to investigate the deposition of Aß in AD. At approximately 6 months of age, APP/PS1 double transgenic mice gradually exhibit the development of plaques, as well as spatial and learning impairment. Notably, the hippocampus is specifically affected in the course of AD. Herein, 6-month-old APP/PS1 double transgenic mice were utilized, and the differentially expressed (DE) proteins in the hippocampus were identified and analyzed using 4D label-free quantitative proteomics technology and parallel reaction monitoring (PRM). Compared to wild-type mice, 29 proteins were upregulated and 25 proteins were downregulated in the AD group. Gene Ontology (GO) enrichment analysis of biological processes (BP) indicated that the DE proteins were mainly involved in 'ribosomal large subunit biogenesis'. Molecular function (MF) analysis results were primarily associated with '5.8S rRNA binding' and 'structural constituent of ribosome'. In terms of cellular components (CC), the DE proteins were mainly found in 'polysomal ribosome', 'cytosolic large ribosomal subunit', 'cytosolic ribosome', and 'large ribosomal subunit', among others. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis demonstrated that the results were mainly enriched in the 'Ribosome signaling pathway'. The key target proteins identified were ribosomal protein (Rp)l18, Rpl17, Rpl19, Rpl24, Rpl35, and Rpl6. The PRM verification results were consistent with the findings of the 4D label-free quantitative proteomics analysis. Overall, these findings suggest that Rpl18, Rpl17, Rpl19, Rpl24, Rpl35, and Rpl6 may have potential therapeutic value for the treatment of AD by targeting Aß.

Parallel-reaction monitoring revealed altered expression of a number of epitranscriptomic reader, writer, and eraser proteins accompanied with colorectal cancer metastasis.

RNA contains more than 170 types of chemical modifications, and these modified nucleosides are recognized, installed and removed by their reader, writer, and eraser (RWE) proteins, respectively. Here, we employed a parallel-reaction monitoring (PRM)-based targeted proteomic method, in conjunction with stable isotope labeling by amino acids in cell culture (SILAC), to examine comprehensively the differential expression of epitranscriptomic RWE proteins in a matched pair of primary/metastatic colorectal cancer (CRC) cells, namely SW480/SW620. We were able to quantify 113 nonredundant epitranscriptomic RWE proteins; among them, 48 and 5 were up- and down-regulated by >1.5-fold in SW620 over SW480 cells, respectively. Some of those proteins with marked up-regulation in metastatic CRC cells, including NAT10, hnRNPC, and DKC1, were documented to assume important roles in the metastasis of CRC and other types of cancer. Interrogation of the Clinical Proteomic Tumor Analysis Consortium data revealed the involvement of DUS1L in the initiation and metastatic transformation of CRC. It can be envisaged that the PRM method can be utilized, in the future, to identify epitranscriptomic RWE proteins involved in the metastatic transformations of other types of cancer.

Developing quantitative assays for six urinary glycoproteins using parallel reaction monitoring, data-independent acquisition, and TMT-based data-dependent acquisition.

Quantitative approaches encompassing parallel reaction monitoring (PRM), data-independent acquisition (DIA), and data-dependent acquisition (DDA) are commonly used to investigate protein expression profiles. However, analytical performances of assays developed using PRM, DIA, and Tandem Mass Tag (TMT)-based DDA for quantitative proteomics have yet not been investigated. Here, we developed assays for glycopeptides identified from six glycoproteins, including Leucine-rich alpha-2-glycoprotein (LRG1), Prostaglandin-H2 D-isomerase (PTGDS), Aminopeptidase N (ANPEP), CD63 antigen (CD63), Clusterin (CLU), and Prostatic acid phosphatase (ACPP), using PRM, DDA, and DIA and evaluated the analytical performances of each assay using the different acquisition modes. We also compared assays in each acquisition mode on three different orbitrap instruments: Thermo Fisher Q Exactive, Exploris 480, and Lumos. We found that DIA showed the largest linear range, highest sensitivity, and most reproducibility. We then applied our developed DIA assays to urine samples from non-aggressive (n = 48) and aggressive (n = 35) prostate cancer patients. In conclusion, we developed assays for the six glycoproteins, evaluated the analytical performances of each assay in DIA, PRM, and PRM acquisition modes on three types of mass spectrometry instruments, and chose the DIA assays for the quantitative analysis of urine samples from patients with aggressive and non-aggressive prostate cancer.

Temporal Profiling of Epitranscriptomic Modulators during Osteogenic Differentiation of Human Embryonic Stem Cells.

Osteogenesis is modulated by multiple regulatory networks. Recent studies showed that RNA modifications and their reader, writer, and eraser (RWE) proteins are involved in regulating various biological processes. Few studies, however, were conducted to investigate the functions of RNA modifications and their RWE proteins in osteogenesis. By using LC-MS/MS in parallel-reaction monitoring (PRM) mode, we performed a comprehensive quantitative assessment of 154 epitranscriptomic RWE proteins throughout the entire time course of osteogenic differentiation in H9 human embryonic stem cells (ESCs). We found that approximately half of the 127 detected RWE proteins were down-regulated during osteogenic differentiation, and they included mainly proteins involved in RNA methylation and pseudouridylation. Protein-protein interaction (PPI) network analysis unveiled significant associations between the down-regulated epitranscriptomic RWE proteins and osteogenesis-related proteins. Gene set enrichment analysis (GSEA) of publicly available RNA-seq data obtained from osteogenesis imperfecta patients suggested a potential role of METTL1 in osteogenesis through the cytokine network. Together, this is the first targeted profiling of epitranscriptomic RWE proteins during osteogenic differentiation of human ESCs, and our work unveiled potential regulatory roles of these proteins in osteogenesis. LC-MS/MS data were deposited on ProteomeXchange (PXD039249).

Metaproteomic Analysis of Nasopharyngeal Swab Samples to Identify Microbial Peptides in COVID-19 Patients.

During the COVID-19 pandemic, impaired immunity and medical interventions resulted in cases of secondary infections. The clinical difficulties and dangers associated with secondary infections in patients necessitate the exploration of their microbiome. Metaproteomics is a powerful approach to study the taxonomic composition and functional status of the microbiome under study. In this study, the mass spectrometry (MS)-based data of nasopharyngeal swab samples from COVID-19 patients was used to investigate the metaproteome. We have established a robust bioinformatics workflow within the Galaxy platform, which includes (a) generation of a tailored database of the common respiratory tract pathogens, (b) database search using multiple search algorithms, and (c) verification of the detected microbial peptides. The microbial peptides detected in this study, belong to several opportunistic pathogens such as Streptococcus pneumoniae, Klebsiella pneumoniae, Rhizopus microsporus, and Syncephalastrum racemosum. Microbial proteins with a role in stress response, gene expression, and DNA repair were found to be upregulated in severe patients compared to negative patients. Using parallel reaction monitoring (PRM), we confirmed some of the microbial peptides in fresh clinical samples. MS-based clinical metaproteomics can serve as a powerful tool for detection and characterization of potential pathogens, which can significantly impact the diagnosis and treatment of patients.

Integrative Proteomic and Pharmacological Analysis of Colon Cancer Reveals the Classical Lipogenic Pathway with Prognostic and Therapeutic Opportunities.

Despite recent advancements, the high mortality rate remains a concern in colon cancer (CAC). Identification of therapeutic markers could prove to be a great asset in CAC management. Multiple studies have reported hyperactivation of de novo lipogenesis (DNL), but its association with the pathology is unclear. This study aims to establish the importance as well as the prognostic and therapeutic potential of DNL in CAC. The key lipogenic enzymes fatty acid synthase along with ATP citrate lyase were quantified using an LC-MS/MS-based targeted proteomics approach in the samples along with the matched controls. The potential capacity of the proteins to distinguish between the tumor and controls was demonstrated using random forest-based class prediction analysis using the peptide intensities. Furthermore, in-depth proteomics of DNL inhibition in the CAC cell line revealed the significance of the pathway in proliferation and metastasis. DNL inhibition affected the major signaling pathways, including DNA repair, PI3K-AKT-mTOR pathway, membrane trafficking, proteasome, etc. The study revealed the upregulation of 26S proteasome machinery as a result of the treatment with subsequent induction of apoptosis. Again, in silico molecular docking-based drug repurposing was performed to find potential drug candidates. Furthermore, we have demonstrated that blocking DNL could be explored as a therapeutic option in CAC treatment.

Phosphoproteomics Profiling Defines a Target Landscape of the Basophilic Protein Kinases AKT, S6K, and RSK in Skeletal Myotubes.

Phosphorylation-dependent signal transduction plays an important role in regulating the functions and fate of skeletal muscle cells. Central players in the phospho-signaling network are the protein kinases AKT, S6K, and RSK as part of the PI3K-AKT-mTOR-S6K and RAF-MEK-ERK-RSK pathways. However, despite their functional importance, knowledge about their specific targets is incomplete because these kinases share the same basophilic substrate motif RxRxxp[ST]. To address this, we performed a multifaceted quantitative phosphoproteomics study of skeletal myotubes following kinase inhibition. Our data corroborate a cross talk between AKT and RAF, a negative feedback loop of RSK on ERK, and a putative connection between RSK and PI3K signaling. Altogether, we report a kinase target landscape containing 49 so far unknown target sites. AKT, S6K, and RSK phosphorylate numerous proteins involved in muscle development, integrity, and functions, and signaling converges on factors that are central for the skeletal muscle cytoskeleton. Whereas AKT controls insulin signaling and impinges on GTPase signaling, nuclear signaling is characteristic for RSK. Our data further support a role of RSK in glucose metabolism. Shared targets have functions in RNA maturation, stability, and translation, which suggests that these basophilic kinases establish an intricate signaling network to orchestrate and regulate processes involved in translation.

Tandem mass tag (TMT) quantitative protein analysis-based proteomics and parallel reaction monitoring (PRM) validation revealed that MST4 accelerates osteosarcoma proliferation by increasing MRC2 activity.

Osteosarcoma is one of the most common orthopedic malignancies and is characterized by rapid disease progression and a poor prognosis. Currently, research on methods to inhibit osteosarcoma proliferation is still limited. In this study, we found that MST4 levels were significantly increased in osteosarcoma cell lines and tumor tissues compared to normal controls and demonstrated that MST4 is an influential factor in promoting osteosarcoma proliferation both in vivo and in vitro. Proteomic analysis was performed on osteosarcoma cells in the MST4 overexpression and vector expression groups, and 545 significantly differentially expressed proteins were identified and quantified. The candidate differentially expressed protein MRC2 was then identified using parallel reaction monitoring validation. Subsequently, MRC2 expression was silenced with small interfering RNA (siRNA), and we were surprised to find that this alteration affected the cell cycle of MST4-overexpressing osteosarcoma cells, promoted apoptosis and impaired the positive regulation of osteosarcoma growth by MST4. In conclusion, this study identified a novel approach for suppressing osteosarcoma proliferation. Reduction of MRC2 activity inhibits osteosarcoma proliferation in patients with high MST4 expression by altering the cell cycle, which may be valuable for treating osteosarcoma and improving patient prognosis.

Orthogonal proteomics methods warrant the development of Duchenne muscular dystrophy biomarkers.

BACKGROUND: Molecular components in blood, such as proteins, are used as biomarkers to detect or predict disease states, guide clinical interventions and aid in the development of therapies. While multiplexing proteomics methods promote discovery of such biomarkers, their translation to clinical use is difficult due to the lack of substantial evidence regarding their reliability as quantifiable indicators of disease state or outcome. To overcome this challenge, a novel orthogonal strategy was developed and used to assess the reliability of biomarkers and analytically corroborate already identified serum biomarkers for Duchenne muscular dystrophy (DMD). DMD is a monogenic incurable disease characterized by progressive muscle damage that currently lacks reliable and specific disease monitoring tools. METHODS: Two technological platforms are used to detect and quantify the biomarkers in 72 longitudinally collected serum samples from DMD patients at 3 to 5 timepoints. Quantification of the biomarkers is achieved by detection of the same biomarker fragment either through interaction with validated antibodies in immuno-assays or through quantification of peptides by Parallel Reaction Monitoring Mass Spectrometry assay (PRM-MS). RESULTS: Five, out of ten biomarkers previously identified by affinity-based proteomics methods, were confirmed to be associated with DMD using the mass spectrometry-based method. Two biomarkers, carbonic anhydrase III and lactate dehydrogenase B, were quantified with two independent methods, sandwich immunoassays and PRM-MS, with Pearson correlations of 0.92 and 0.946 respectively. The median concentrations of CA3 and LDHB in DMD patients was elevated in comparison to those in healthy individuals by 35- and 3-fold, respectively. Levels of CA3 vary between 10.26 and 0.36 ng/ml in DMD patients whereas those of LDHB vary between 15.1 and 0.8 ng/ml. CONCLUSIONS: These results demonstrate that orthogonal assays can be used to assess the analytical reliability of biomarker quantification assays, providing a means to facilitate the translation of biomarkers to clinical practice. This strategy also warrants the development of the most relevant biomarkers, markers that can be reliably quantified with different proteomics methods.

Identification evidence unraveled by strict proteomics rules toward forensic samples.

Snake venom is a complex mixture of proteins and peptides secreted by venomous snakes from their poison glands. Although proteomics for snake venom composition, interspecific differences, and developmental evolution has been developed for a decade, current diagnosis or identification techniques of snake venom in clinical intoxication and forensic science applications are mainly dependent on morphological and immunoassay. It could be expected that the proteomics techniques directly offer great help. This work applied a bottom-up proteomics method to identify proteins' types and species attribution in suspected snake venom samples using ultrahigh-performance liquid chromatography-quadrupole-electrostatic field Orbitrap tandem mass spectrometric technique, and cytotoxicity assay was amended to provide a direct evidence of toxicity. Toward the suspicious samples seized in the security control, sample pretreatment (in-sol and in-gel digestion) and data acquisition (nontargeted and targeted screening) modes complemented and validated each other. We have implemented two consequent approaches in identifying the species source of proteins in the samples via the points of venom proteomics and strict forensic identification. First, we completed a workflow consisting of a proteomics database match toward an entire SWISS-PROT (date 2018-11-22) database and a result-directed specific taxonomy database. The latter was a helpful hint to compare master protein kinds and reveal the insufficiency of specific venom proteomics characterization rules. Second, we suggested strict rules for protein identification to meet the requirements of forensic science on improved identification correctness, that is, (1) peptide spectrum matches confidence, peptide confidence, and protein confidence were both high (with the false-discovery ratio less than 1%); (2) the number of unique peptides was more than or equal to two in one protein, and (3) within unique peptides, which at least 75% of the ∆m/z of the matched y and b ions were less than 5 ppm. We identified these samples as cobra venom containing 10 highly abundant proteins (P00597, P82463, P60770, Q9YGI4, P62375, P49123, P80245, P60302, P01442, and P60304) from two snake venom protein families (acid phospholipase A2 and three-finger toxins), and the most abundant proteins were cytotoxins.