CONCLUSIONS: Identification and quantification of phosphorylation sites are essential for biological interpretation of a phosphoproteomics experiment. For data independent acquisition mass spectrometry-based (DIA-MS) phosphoproteomics, extracting a site-level report from the output of current processing software is not straightforward as multiple peptides might contribute to a single site, multiple phosphorylation sites can occur on the same peptides, and protein isoforms complicate site specification. Currently only limited support is available from a commercial software package via a platform-specific solution with a rather simple site quantification method. Here we present sitereport, a software tool implemented in an extendable Python package called msproteomics to report phosphosites and phosphopeptides from a DIA-MS phosphoproteomics experiment with a proven quantification method called MaxLFQ. We demonstrate the use of sitereport for downstream data analysis at site level, allowing benchmarking different DIA-MS processing software tools.
METHODS: sitereport is available as a command line tool in the Python package msproteomics, released under the Apache License 2.0 and available from the Python Package Index (PyPI) at https://pypi.org/project/msproteomics and GitHub at https://github.com/tvpham/msproteomics.
BACKGROUND: Supplementary data are available at Bioinformatics online.

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.

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.

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-1β, 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.

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.

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.

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.

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.
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.
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.
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.

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.

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.