Proteome profiling of Campylobacter jejuni 81-176 at 37 °C and 42 °C by label-free mass spectrometry.

BACKGROUND: The main natural reservoir for Campylobacter jejuni is the avian intestinal tract. There, C. jejuni multiplies optimally at 42 °C - the avian body temperature. After infecting humans through oral intake, the bacterium encounters the lower temperature of 37 °C in the human intestinal tract. Proteome profiling by label-free mass spectrometry (DIA-MS) was performed to examine the processes which enable C. jejuni 81-176 to thrive at 37 °C in comparison to 42 °C. In total, four states were compared with each other: incubation for 12 h at 37 °C, for 24 h at 37 °C, for 12 h at 42 °C and 24 h at 42 °C. RESULTS: It was shown that the proteomic changes not only according to the different incubation temperature but also to the length of the incubation period were evident when comparing 37 °C and 42 °C as well as 12 h and 24 h of incubation. Altogether, the expression of 957 proteins was quantifiable. 37.1 - 47.3% of the proteins analyzed showed significant differential regulation, with at least a 1.5-fold change in either direction (i.e. log2 FC ≥ 0.585 or log2 FC ≤ -0.585) and an FDR-adjusted p-value of less than 0.05. The significantly differentially expressed proteins could be arranged in 4 different clusters and 16 functional categories. CONCLUSIONS: The C. jejuni proteome at 42 °C is better adapted to high replication rates than that at 37 °C, which was in particular indicated by the up-regulation of proteins belonging to the functional categories "replication" (e.g. Obg, ParABS, and NapL), "DNA synthesis and repair factors" (e.g. DNA-polymerase III, DnaB, and DnaE), "lipid and carbohydrate biosynthesis" (e.g. capsular biosynthesis sugar kinase, PrsA, AccA, and AccP) and "vitamin synthesis, metabolism, cofactor biosynthesis" (e.g. MobB, BioA, and ThiE). The relative up-regulation of proteins with chaperone function (GroL, DnaK, ClpB, HslU, GroS, DnaJ, DnaJ-1, and NapD) at 37 °C in comparison to 42 °C after 12 h incubation indicates a temporary lower-temperature proteomic response. Additionally the up-regulation of factors for DNA uptake (ComEA and RecA) at 37 °C compared to 42 °C indicate a higher competence for the acquisition of extraneous DNA at human body temperature.

A novel selenium nanocomposite modified by AANL inhibits tumor growth by upregulating CLK2 in lung cancer.

Lung cancer is a malignant tumor with high mortality and drug resistance. Therefore, it is urgent to explore natural and nontoxic drugs to treat lung cancer. In this study, the natural active ingredient AANL extracted from Agrocybe aegirita was used to modify nanoselenium by an oxidation-reduction method. Transmission electron microscope detection and infrared spectroscopy showed that a novel selenium nanocomposite named AANL-SeNPs was successfully prepared. The results of nanoscale characterization showed that AANL-SeNPs had good stability and uniform dispersion in aqueous solution by zeta potential and spectrum analysis. At the cellular level, we found that AANL-SeNPs significantly inhibited the cell viability of lung cancer cells, and the cell inhibition rate of 60 nM AANL-SeNPs was 39 % in H157 cells, 67 % in H147 cells, and 62 % in A549 cells. The IC50 value of AANL-SeNPs was 51.85 nM in A549 cells and 81.57 nM in H157 cells. Moreover, AANL-SeNPs could inhibit the cell proliferation and migration, and enhance the sensitivity of lung cancer cells to osimertinib and has no toxic to normal cells. In vivo, AANL-SeNPs significantly slowed tumor growth in tumor-bearing mice by establishing a subcutaneous transplantation tumor model for lung cancer, and the tumor size was smaller and was reduced about 79 % in 2 mg/kg AANL-SeNPs group compared with PBS group. Mechanistically, a total of 38 differentially expressed proteins were identified by data-independent acquisition mass spectrometry. A significantly upregulated protein, CDC-like kinase 2 (CLK2), was screened and validated for further analysis, which showed that the expression levels of CLK2 were increased in H157 and H1437 cells after AANL-SeNPs treatment. The results obtained in this study suggest that a novel selenium nanocomposite AANL-SeNPs, which inhibits lung cancer by upregulating the expression of CLK2.

Mass Spectrometry-Based Proteomics Analysis Unveils PTPRS Inhibits Proliferation and Inflammatory Response of Keratinocytes in Psoriasis.

In this study, we used data-independent acquisition-mass spectrometry (DIA-MS) to analyze the serum proteome in psoriasis vulgaris (PsO). The serum proteomes of seven healthy controls and eight patients with PsO were analyzed using DIA-MS. Weighted gene co-expression network analysis was used to identify differentially expressed proteins (DEPs) that were closely related to PsO. Hub proteins of PsO were also identified. The Proteomics Drug Atlas 2023 was used to predict candidate hub protein drugs. To confirm the expression of the candidate factor, protein tyrosine phosphatase receptor S (PTPRS), in psoriatic lesions and the psoriatic keratinocyte model, immunohistochemical staining, quantitative real-time polymerase chain reaction, and western blotting were performed. A total of 129 DEPs were found to be closely related to PsO. The hub proteins for PsO were PVRL1, FGFR1, PTPRS, CDH2, CDH1, MCAM, and THY1. Five candidate hub protein drugs were identified: encorafenib, leupeptin, fedratinib, UNC 0631, and SCH 530348. PTPRS was identified as a common pharmacological target for these five drugs. PTPRS knockdown in keratinocytes promoted the proliferation and expression of IL-1α, IL-1ß, IL-23A, TNF-α, MMP9, CXCL8, and S100A9. PTPRS expression was decreased in PsO, and PTPRS negatively regulated PsO. PTPRS may be involved in PsO pathogenesis through the inhibition of keratinocyte proliferation and inflammatory responses and is a potential treatment target for PsO.

Quantitative proteomic analysis reveals unique Hsp90 cycle-dependent client interactions.

Hsp90 is an abundant and essential molecular chaperone that mediates the folding and activation of client proteins in a nucleotide-dependent cycle. Hsp90 inhibition directly or indirectly impacts the function of 10-15% of all proteins due to degradation of client proteins or indirect downstream effects. Due to its role in chaperoning oncogenic proteins, Hsp90 is an important drug target. However, compounds that occupy the ATP-binding pocket and broadly inhibit function have not achieved widespread use due to negative effects. More selective inhibitors are needed; however, it is unclear how to achieve selective inhibition. We conducted a quantitative proteomic analysis of soluble proteins in yeast strains expressing wild-type Hsp90 or mutants that disrupt different steps in the client folding pathway. Out of 2,482 proteins in our sample set (approximately 38% of yeast proteins), we observed statistically significant changes in abundance of 350 (14%) of those proteins (log2 fold change ≥ 1.5). Of these, 257/350 (∼73%) with the strongest differences in abundance were previously connected to Hsp90 function. Principal component analysis of the entire dataset revealed that the effects of the mutants could be separated into 3 primary clusters. As evidence that Hsp90 mutants affect different pools of clients, simultaneous co-expression of 2 mutants in different clusters restored wild-type growth. Our data suggest that the ability of Hsp90 to sample a wide range of conformations allows the chaperone to mediate folding of a broad array of clients and that disruption of conformational flexibility results in client defects dependent on those states.

Use of data-independent acquisition mass spectrometry to identify an objective serum indicator of the need for osteoporotic therapeutic intervention.

Osteoporosis is characterized by weakened bone microstructure and loss of bone mass. Current diagnostic criteria for osteoporosis are based on the T-score, which is a measure of bone mineral density. However, osteoporotic fragility fractures can occur regardless of the T-score, underscoring the need for additional criteria for the early detection of patients at fracture risk. To identify indicators of reduced bone strength, we performed serum proteomic analysis using data-independent acquisition mass spectrometry with serum samples from two patient groups, one with osteoporosis but no fractures and the other with osteopenia and fragility fractures. Collective evaluation of the results identified six serum proteins that changed to a similar extent in both patient groups compared with controls. Of these, extracellular matrix protein 1 (ECM1), which contributes to bone formation, showed the most significant increase in serum levels in both patient groups. An ELISA-based assay suggested that ECM1 could serve as a serum indicator of the need for therapeutic intervention; however, further prospective studies with a larger sample size are necessary to confirm these results. The present findings may contribute to the provision of early and appropriate therapeutic strategies for patients at risk of osteoporotic fractures. SIGNIFICANCE: This study aimed to identify objective serum indicators of the need for therapeutic intervention in individuals at risk of osteoporotic fracture. Comprehensive proteome analyses of serum collected from patients with osteoporosis but no fractures, patients with osteopenia and fragility fractures, and controls were performed by data-independent acquisition mass spectrometry. Collective evaluation of the proteome analysis data and ELISA-based assays identified serum ECM1 as a potential objective marker of the risk of fragility fractures in patients with osteoporosis or osteopenia. The findings are an important step toward the development of appropriate bone health management methods to improve well-being and maintain quality of life.

Comparative analysis of proteomic adaptations in Enterococcus faecalis and Enterococcus faecium after long term bile acid exposure.

BACKGROUND: All gastrointestinal pathogens, including Enterococcus faecalis and Enterococcus faecium, undergo adaptation processes during colonization and infection. In this study, we investigated by data-independent acquisition mass spectrometry (DIA-MS) two crucial adaptations of these two Enterococcus species at the proteome level. Firstly, we examined the adjustments to cope with bile acid concentrations at 0.05% that the pathogens encounter during a potential gallbladder infection. Therefore, we chose the primary bile acids cholic acid (CA) and chenodeoxycholic acid (CDCA) as well as the secondary bile acid deoxycholic acid (DCA), as these are the most prominent bile acids. Secondly, we investigated the adaptations from an aerobic to a microaerophilic environment, as encountered after oral-fecal infection, in the absence and presence of deoxycholic acid (DCA). RESULTS: Our findings showed similarities, but also species-specific variations in the response to the different bile acids. Both Enterococcus species showed an IC50 in the range of 0.01- 0.023% for DCA and CDCA in growth experiments and both species were resistant towards 0.05% CA. DCA and CDCA had a strong effect on down-expression of proteins involved in translation, transcription and replication in E. faecalis (424 down-expressed proteins with DCA, 376 down-expressed proteins with CDCA) and in E. faecium (362 down-expressed proteins with DCA, 391 down-expressed proteins with CDCA). Proteins commonly significantly altered in their expression in all bile acid treated samples were identified for both species and represent a "general bile acid response". Among these, various subunits of a V-type ATPase, different ABC-transporters, multi-drug transporters and proteins related to cell wall biogenesis were up-expressed in both species and thus seem to play an essential role in bile acid resistance. Most of the differentially expressed proteins were also identified when E. faecalis was incubated with low levels of DCA at microaerophilic conditions instead of aerobic conditions, indicating that adaptations to bile acids and to a microaerophilic atmosphere can occur simultaneously. CONCLUSIONS: Overall, these findings provide a detailed insight into the proteomic stress response of two Enterococcus species and help to understand the resistance potential and the stress-coping mechanisms of these important gastrointestinal bacteria.

An Updated Guide to the Identification, Quantitation, and Imaging of the Crustacean Neuropeptidome.

Crustaceans serve as a useful, simplified model for studying peptides and neuromodulation, as they contain numerous neuropeptide homologs to mammals and enable electrophysiological studies at the single-cell and neural circuit levels. Crustaceans contain well-defined neural networks, including the stomatogastric ganglion, oesophageal ganglion, commissural ganglia, and several neuropeptide-rich organs such as the brain, pericardial organs, and sinus glands. As existing mass spectrometry (MS) methods are not readily amenable to neuropeptide studies, there is a great need for optimized sample preparation, data acquisition, and data analysis methods. Herein, we present a general workflow and detailed methods for MS-based neuropeptidomic analysis of crustacean tissue samples and circulating fluids. In conjunction with profiling, quantitation can also be performed with isotopic or isobaric labeling. Information regarding the localization patterns and changes of peptides can be studied via mass spectrometry imaging. Combining these sample preparation strategies and MS analytical techniques allows for a multi-faceted approach to obtaining deep knowledge of crustacean peptidergic signaling pathways.

Comprehensive profiling of the human fecal proteome from IBD patients with DIA-MS enables evaluation of disease-relevant proteins.

PURPOSE: Inflammatory bowel disease (IBD), which includes ulcerative colitis (UC) and Crohn's disease (CD), is characterized by chronic gastrointestinal inflammation. A high unmet need exists for noninvasive biomarkers in IBD to monitor changes in disease activity and guide treatment decisions. Stool is an easily accessed, disease proximal matrix in IBD, however the composition of the IBD fecal proteome remains poorly characterized. EXPERIMENTAL DESIGN: A data-independent acquisition LC-MS/MS approach was used to profile the human fecal proteome in two independent cohorts (Cohort 1: healthy n = 5, UC n = 5, CD n = 5, Cohort 2: healthy n = 20, UC n = 10, and CD n = 10) to identify noninvasive biomarkers reflective of disease activity. RESULTS: 688 human proteins were quantified, with 523 measured in both cohorts. In UC stool 96 proteins were differentially abundant and in CD stool 126 proteins were differentially abundant compared to healthy stool (absolute log2 fold change > 1, p-value < 0.05). Many of these fecal proteins are associated with infiltrating immune cells and ulceration/rectal bleeding, which are hallmarks of IBD pathobiology. Mapping the identified fecal proteins to a whole blood single-cell RNA sequencing data set revealed the involvement of various immune cell subsets to the IBD fecal proteome. CONCLUSIONS AND CLINICAL RELEVANCE: Findings from this study not only confirmed the presence of established fecal biomarkers for IBD, such as calprotectin and lactoferrin, but also revealed new fecal proteins from multiple pathways known to be dysregulated in IBD. These novel proteins could serve as potential noninvasive biomarkers to monitor specific aspects of IBD disease activity which could expedite clinical development of novel therapeutic targets.

Longitudinal plasma proteomic profiling of EML4-ALK positive lung cancer receiving ALK-TKIs therapy.

BACKGROUND: Anaplastic lymphoma kinase-tyrosine kinase inhibitors (ALK-TKIs) has demonstrated remarkable therapeutic effects in ALK-positive non-small cell lung cancer (NSCLC) patients. Identifying prognostic biomarkers can enhance the clinical efficacy of relapsed or refractory patients. METHODS: We profiled 737 plasma proteins from 159 pre-treatment and on-treatment plasma samples of 63 ALK-positive NSCLC patients using data-independent acquisition-mass spectrometry (DIA-MS). The consensus clustering algorithm was used to identify subtypes with distinct biological features. A plasma-based prognostic model was constructed using the LASSO-Cox method. We performed the Mfuzz analysis to classify the patterns of longitudinal changes in plasma proteins during treatment. 52 baseline plasma samples from another independent ALK-TKI treatment cohort were collected to validate the potential prognostic markers using ELISA. RESULTS: We identified three subtypes of ALK-positive NSCLC with distinct biological features and clinical efficacy. Patients in subgroup 1 exhibited activated humoral immunity and inflammatory responses, increased expression of positive acute-phase response proteins, and the worst prognosis. Then we constructed and verified a prognostic model that predicts the efficacy of ALK-TKI therapy using the expression levels of five plasma proteins (SERPINA4, ATRN, APOA4, TF, and MYOC) at baseline. Next, we explored the longitudinal changes in plasma protein expression during treatment and identified four distinct change patterns (Clusters 1-4). The longitudinal changes of acute-phase proteins during treatment can reflect the treatment status and tumor progression of patients. Finally, we validated the prognostic efficacy of baseline plasma CRP, SAA1, AHSG, SERPINA4, and TF in another independent NSCLC cohort undergoing ALK-TKI treatment. CONCLUSIONS: This study contributes to the search for prognostic and drug-resistance biomarkers in plasma samples for ALK-TKI therapy and provides new insights into the mechanism of drug resistance and the selection of follow-up treatment.

Screening of novel biomarkers for acute kidney transplant rejection using DIA-MS based proteomics.

BACKGROUND: Kidney transplantation is the preferred treatment for patients with end-stage renal disease. However, acute rejection poses a threat to the graft long-term survival. The aim of this study was to identify novel biomarkers to detect acute kidney transplant rejection. METHODS: The serum proteomic profiling of kidney transplant patients with T cell-mediated acute rejection (TCMR) and stable allograft function (STA) was analyzed using data-independent acquisition mass spectrometry (DIA-MS). The differentially expressed proteins (DEPs) of interest were further verified by enzyme-linked immunosorbent assay (ELISA). RESULTS: A total of 131 DEPs were identified between STA and TCMR patients, 114 DEPs were identified between mild and severe TCMR patients. The verification results showed that remarkable higher concentrations of serum amyloid A protein 1 (SAA1) and insulin like growth factor binding protein 2 (IGFBP2), and lower fetuin-A (AHSG) concentration were found in TCMR patients when compared with STA patients. We also found higher SAA1 concentration in severe TCMR group when compared with mild TCMR group. The receiver operating characteristics (ROC) analysis further confirmed that combination of SAA1, AHSG, and IGFBP2 had excellent performance in the acute rejection diagnosis. CONCLUSIONS: Our data demonstrated that serum SAA1, AHSG, and IGFBP2 could be effective biomarkers for diagnosing acute rejection after kidney transplantation. DIA-MS has great potential in biomarker screening of kidney transplantation.

Proteomic mapping reveals dysregulated angiogenesis in the cerebral arteries of rats with early-onset hypertension.

Hypertension is associated with the presence of vascular abnormalities, including remodeling and rarefaction. These processes play an important role in cerebrovascular disease development; however, the mechanistic changes leading to these diseases are not well characterized. Using data-independent acquisition-based mass spectrometry analysis, here we determined the protein changes in cerebral arteries in pre- and early-onset hypertension from the spontaneously hypertensive rat (SHR), a model that resembles essential hypertension in humans. Our analysis identified 125 proteins with expression levels that were significantly upregulated or downregulated in 12-week-old spontaneously hypertensive rats compared to normotensive Wistar Kyoto rats. Using an angiogenesis enrichment analysis, we further identified a critical imbalance in angiogenic proteins that promoted an anti-angiogenic profile in cerebral arteries at early onset of hypertension. In a comparison to previously published data, we demonstrate that this angiogenic imbalance is not present in mesenteric and renal arteries from age-matched SHRs. Finally, we identified two proteins (Fbln5 and Cdh13), whose expression levels were critically altered in cerebral arteries compared to the other arterial beds. The observation of an angiogenic imbalance in cerebral arteries from the SHR reveals critical protein changes in the cerebrovasculature at the early onset of hypertension and provides novel insights into the early pathology of cerebrovascular disease.

Potential biomarkers for psoriasis topical treatment by in-depth serum proteomics.

BACKGROUND: Psoriasis is a chronic skin disease, and topical sequential therapy with a combination of calcipotriol and calcipotriol betamethasone is currently approved topical treatment. However, the exact mechanism by which this treatment regimen relieves psoriasis is unknown. METHOD: We assembled a cohort of 65 psoriasis patients and divided post-treatment cohort into responder group and non-responder group according to the Psoriasis Area Severity Index (PASI) score after 12-week treatment. We measured the expression levels of proteins in collected 130 serum samples using our in-depth proteomics platform with a data-independent acquisition mass spectrometer and antibody microarray. We performed bioinformatics analyses of the biologic processes and signaling pathways that were changed in the responder group and constructed a proteomics landscape of psoriasis pathogenesis response to treatment. We then validated the biomarkers of disease severity in an independent cohort of 88 samples using an enzyme-linked immunosorbent assay. RESULTS: We first identified 174 differentially expressed proteins (DEPs) for comparative analysis of proteins between responders and non-responders at baseline (p < 0.05). Then pathway analysis showed that the responders focused more on signaling molecules and interaction, complement and coagulation cascades, whereas the non-responders more on signal transduction and IL-17 signaling pathways. We further identified four candidate biomarkers (COLEC11, C1QA, BNC2, ITIH4) response to treatment. We also found 125 DEPs (p < 0.05) after treatment compared with before treatment in responder group. Pathway analysis showed an enrichment in pathways related to complement and coagulation cascades, phagosome, ECM-receptor interaction, cholesterol metabolism, vitamin digestion and absorption. CD14 was validated as potential biomarkers for the disease severity of psoriasis and treatment targets. CONCLUSION: In this work, we analyzed the response to topical sequential therapy and finally identified four biomarkers. Additionally, we found that topical sequential therapy may alleviate psoriasis by regulating lipid metabolism and modulating the immune response by affecting the complement activation process.

Population serum proteomics uncovers a prognostic protein classifier for metabolic syndrome.

Metabolic syndrome (MetS) is a complex metabolic disorder with a global prevalence of 20%-25%. Early identification and intervention would help minimize the global burden on healthcare systems. Here, we measured over 400 proteins from ∼20,000 proteomes using data-independent acquisition mass spectrometry for 7,890 serum samples from a longitudinal cohort of 3,840 participants with two follow-up time points over 10 years. We then built a machine-learning model for predicting the risk of developing MetS within 10 years. Our model, composed of 11 proteins and the age of the individuals, achieved an area under the curve of 0.774 in the validation cohort (n = 242). Using linear mixed models, we found that apolipoproteins, immune-related proteins, and coagulation-related proteins best correlated with MetS development. This population-scale proteomics study broadens our understanding of MetS and may guide the development of prevention and targeted therapies for MetS.

Identification of gravity-responsive proteins in the femur of spaceflight mice using a quantitative proteomic approach.

Although the microgravity (µ-g) environment that astronauts encounter during spaceflight can cause severe acute bone loss, the molecular mechanism of this bone loss remains unclear. To investigate the gravity-response proteins involved in bone metabolism, it is important to comprehensively determine which proteins exhibit differential abundance associated with mechanical stimuli. However, comprehensive proteomic analysis using small bone samples is difficult because protein extraction in mineralized bone tissue is inefficient. Here, we established a high-sensitivity analysis system for mouse bone proteins using data-independent acquisition mass spectrometry. This system successfully detected 40 proteins in the femoral diaphysis showing differential abundance between mice raised in a µ-g environment, where the bone mass was reduced by gravity unloading, and mice raised in an artificial 1-gravity environment on the International Space Station. Additionally, 22 proteins, including noncollagenous bone matrix proteins, showed similar abundance between the two groups in the mandible, where bone mass was unaltered due to mastication stimuli, suggesting that these proteins are responsive to mechanical stimuli. One of these proteins, SPARCL1, is suggested to promote osteoclastogenesis induced by receptor activator of nuclear factor-κB ligand. We expect these findings to lead to new insights into the mechanisms of bone metabolism induced by mechanical stimuli. SIGNIFICANCE: We aimed to investigate the gravity-response proteins involved in bone metabolism. To this end, we established a comprehensive analysis system for mouse bone proteins using data-independent acquisition mass spectrometry, which is particularly useful in comprehensively analyzing the bone proteome using small sample volumes. In addition, a comprehensive proteomic analysis of the femoral diaphysis and mandible, which exhibit different degrees of bone loss in mice raised on the International Space Station, identified proteins that respond to mechanical stimuli. SPARCL1, a mechanical stimulus-responsive protein, was consequently suggested to be involved in osteoclast differentiation associated with bone remodeling. Our findings represent an important step toward elucidating the molecular mechanism of bone metabolism induced by mechanical stimuli.

Overexpression of SERPINA3 suppresses tumor progression by modulating SPOP/NF­κB in lung cancer.

The pathogenesis mechanism of lung cancer is very complex, with high incidence and mortality. Serpin family A member 3 (SERPINA3) expression levels were reduced in the sera of patients with lung cancer and may be a candidate diagnostic and prognostic survival biomarker in lung cancer, as previously reported. However, the detailed biological functions of SERPINA3 in the pathogenesis of lung cancer remain unknown. In the present study, it was aimed to explore the effects of SERPINA3 on the occurrence of lung cancer. SERPINA3 expression was assessed using bioinformatics database analysis and experimental detection. Then, the biological effects of SERPINA3 were investigated in a cell culture system and a xenograft model of human lung cancer. The potential regulatory mechanism of SERPINA3 in lung cancer was explored by data­independent acquisition mass spectrometry (DIA­MS) detection and further validated by western blotting (WB). The results indicated that SERPINA3 expression levels were significantly downregulated in lung cancer tissues and cell lines. At the cellular level, it was revealed that overexpressed SERPINA3 inhibited cell growth, proliferation, migration and invasion and promoted the apoptosis of lung cancer cells. Moreover, overexpressed SERPINA3 enhanced the sensitivity of lung cancer cells to osimertinib. In vivo, a xenograft model of human lung cancer was established with BALB/c nude mice. After the injection of A549 cells, the tumor growth of the tumor­bearing mice in the SERPINA3­overexpressing group increased more slowly, and the tumor volume was smaller than that in the empty­vector group. Mechanistically, a total of 65 differentially expressed proteins were identified. It was found that the speckle­type POZ protein (SPOP) was significantly upregulated in SERPINA3­overexpressing H157 cells using DIA­MS detection and analysis. WB validation showed that SPOP expression increased, and NF­kappaB (NF­κB) p65 was inhibited in cell lines and tumor tissues of mice when SERPINA3 was overexpressed. The present findings suggest that SERPINA3 is involved in the development of lung cancer and has an antineoplastic role in lung cancer.

Data-independent acquisition-based mass spectrometry(DIA-MS) for quantitative analysis of patients with chronic hepatitis B.

Chronic hepatitis B is a significant public health problem and complex pathologic process, and unraveling the underlying mechanisms and pathophysiology is of great significance. Data independent acquisition mass spectrometry (DIA-MS) is a label-free quantitative proteomics method that has been successfully applied to the study of a wide range of diseases. The aim of this study was to apply DIA-MS for proteomic analysis of patients with chronic hepatitis B. We performed comprehensive proteomics analysis of protein expression in serum samples from HBV patients and healthy controls by using DIA-MS. Gene Ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and protein network analysis were performed on differentially expressed proteins and were further combined with literature analysis. We successfully identified a total of 3786 serum proteins with a high quantitative performance from serum samples in this study. We identified 310 differentially expressed proteins (DEPs) (fold change > 1.5 and P value < 0.05 as the criteria for a significant difference) between HBV and healthy samples. A total of 242 upregulated proteins and 68 downregulated proteins were among the DEPs. Some protein expression levels were significantly elevated or decreased in patients with chronic hepatitis B, indicating a relation to chronic liver disease, which should be further investigated.

Proteome Landscapes of Human Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma.

Liver cancer is among the top leading causes of cancer mortality worldwide. Particularly, hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (CCA) have been extensively investigated from the aspect of tumor biology. However, a comprehensive and systematic understanding of the molecular characteristics of HCC and CCA remains absent. Here, we characterized the proteome landscapes of HCC and CCA using the data-independent acquisition (DIA) mass spectrometry (MS) method. By comparing the quantitative proteomes of HCC and CCA, we found several differences between the two cancer types. In particular, we found an abnormal lipid metabolism in HCC and activated extracellular matrix-related pathways in CCA. We next developed a three-protein classifier to distinguish CCA from HCC, achieving an area under the curve (AUC) of 0.92, and an accuracy of 90% in an independent validation cohort of 51 patients. The distinct molecular characteristics of HCC and CCA presented in this study provide new insights into the tumor biology of these two major important primary liver cancers. Our findings may help develop more efficient diagnostic approaches and new targeted drug treatments.

Advanced mass spectrometry workflows for accurate quantification of trace-level host cell proteins in drug products: Benefits of FAIMS separation and gas-phase fractionation DIA.

Therapeutic monoclonal antibodies (mAb) production relies on multiple purification steps before release as a drug product (DP). A few host cell proteins (HCPs) may co-purify with the mAb. Their monitoring is crucial due to the considerable risk they represent for mAb stability, integrity, and efficacy and their potential immunogenicity. Enzyme-linked immunosorbent assays (ELISA) commonly used for global HCP monitoring present limitations in terms of identification and quantification of individual HCPs. Therefore, liquid chromatography tandem mass spectrometry (LC-MS/MS) has emerged as a promising alternative. Challenging DP samples show an extreme dynamic range requiring high performing methods to detect and reliably quantify trace-level HCPs. Here, we investigated the benefits of adding high-field asymmetric ion mobility spectrometry (FAIMS) separation and gas phase fractionation (GPF) prior to data independent acquisition (DIA). FAIMS LC-MS/MS analysis allowed the identification of 221 HCPs among which 158 were reliably quantified for a global amount of 880 ng/mg of NIST mAb Reference Material. Our methods have also been successfully applied to two FDA/EMA approved DPs and allowed digging deeper into the HCP landscape with the identification and quantification of a few tens of HCPs with sensitivity down to the sub-ng/mg of mAb level.

High-Field Asymmetric Waveform Ion Mobility Spectrometry: Practical Alternative for Cardiac Proteome Sample Processing.

Heart tissue sample preparation for mass spectrometry (MS) analysis that includes prefractionation reduces the cellular protein dynamic range and increases the relative abundance of nonsarcomeric proteins. We previously described "IN-Sequence" (IN-Seq) where heart tissue lysate is sequentially partitioned into three subcellular fractions to increase the proteome coverage more than a single direct tissue analysis by mass spectrometry. Here, we report an adaptation of the high-field asymmetric ion mobility spectrometry (FAIMS) coupled to mass spectrometry, and the establishment of a simple one step sample preparation coupled with gas-phase fractionation. The FAIMS approach substantially reduces manual sample handling, significantly shortens the MS instrument processing time, and produces unique protein identification and quantification approximating the commonly used IN-Seq method in less time.

A transformer architecture for retention time prediction in liquid chromatography mass spectrometry-based proteomics.

Accurate retention time (RT) prediction is important for spectral library-based analysis in data-independent acquisition mass spectrometry-based proteomics. The deep learning approach has demonstrated superior performance over traditional machine learning methods for this purpose. The transformer architecture is a recent development in deep learning that delivers state-of-the-art performance in many fields such as natural language processing, computer vision, and biology. We assess the performance of the transformer architecture for RT prediction using datasets from five deep learning models Prosit, DeepDIA, AutoRT, DeepPhospho, and AlphaPeptDeep. The experimental results on holdout datasets and independent datasets exhibit state-of-the-art performance of the transformer architecture. The software and evaluation datasets are publicly available for future development in the field.