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

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

Identification of State-Specific Proteomic and Transcriptomic Signatures of Microglia-Derived Extracellular Vesicles.

Microglia are resident immune cells of the brain that play important roles in mediating inflammatory responses in several neurological diseases via direct and indirect mechanisms. One indirect mechanism may involve extracellular vesicle (EV) release, so that the molecular cargo transported by microglia-derived EVs can have functional effects by facilitating intercellular communication. The molecular composition of microglia-derived EVs, and how microglial activation states impact EV composition and EV-mediated effects in neuroinflammation, remain poorly understood. We hypothesize that microglia-derived EVs have unique molecular profiles that are determined by microglial activation state. Using size-exclusion chromatography to purify EVs from BV2 microglia, combined with proteomic (label-free quantitative mass spectrometry or LFQ-MS) and transcriptomic (mRNA and noncoding RNA seq) methods, we obtained comprehensive molecular profiles of microglia-derived EVs. LFQ-MS identified several classic EV proteins (tetraspanins, ESCRT machinery, and heat shock proteins), in addition to over 200 proteins not previously reported in the literature. Unique mRNA and microRNA signatures of microglia-derived EVs were also identified. After treating BV2 microglia with lipopolysaccharide (LPS), interleukin-10, or transforming growth factor beta, to mimic pro-inflammatory, anti-inflammatory, or homeostatic states, respectively, LFQ-MS and RNA seq revealed novel state-specific proteomic and transcriptomic signatures of microglia-derived EVs. Particularly, LPS treatment had the most profound impact on proteomic and transcriptomic compositions of microglia-derived EVs. Furthermore, we found that EVs derived from LPS-activated microglia were able to induce pro-inflammatory transcriptomic changes in resting responder microglia, confirming the ability of microglia-derived EVs to relay functionally relevant inflammatory signals. These comprehensive microglia-EV molecular datasets represent important resources for the neuroscience and omics communities and provide novel insights into the role of microglia-derived EVs in neuroinflammation.

On the excessive use of coefficient of variation as a metric of quantitation quality in proteomics.

The coefficient of variation (CV) is often used in proteomics as a proxy to characterize the performance of a quantitation method and/or the related software. In this note, we question the excessive reliance on this metric in quantitative proteomics that may result in erroneous conclusions. We support this note using a ground-truth Human-Yeast-E. coli dataset demonstrating in a number of cases that erroneous data processing methods may lead to a low CV which has nothing to do with these methods' performances in quantitation.

Proteomic Profiling of Dilated Cardiomyopathy Plasma Samples ─ Searching for Biomarkers with Potential to Predict the Outcome of Therapy.

Determination of the prognosis and treatment outcomes of dilated cardiomyopathy is a serious problem due to the lack of valid specific protein markers. Using in-depth proteome discovery analysis, we compared 49 plasma samples from patients suffering from dilated cardiomyopathy with plasma samples from their healthy counterparts. In total, we identified 97 proteins exhibiting statistically significant dysregulation in diseased plasma samples. The functional enrichment analysis of differentially expressed proteins uncovered dysregulation in biological processes like inflammatory response, wound healing, complement cascade, blood coagulation, and lipid metabolism in dilated cardiomyopathy patients. The same proteome approach was employed in order to find protein markers whose expression differs between the patients well-responding to therapy and nonresponders. In this case, 45 plasma proteins revealed statistically significant different expression between these two groups. Of them, fructose-1,6-bisphosphate aldolase seems to be a promising biomarker candidate because it accumulates in plasma samples obtained from patients with insufficient treatment response and with worse or fatal outcome. Data are available via ProteomeXchange with the identifier PXD046288.

Multispecies Benchmark Analysis for LC-MS/MS Validation and Performance Evaluation in Bottom-Up Proteomics.

We present an instrument-independent benchmark procedure and software (LFQ_bout) for the validation and comparative evaluation of the performance of LC-MS/MS and data processing workflows in bottom-up proteomics. The procedure enables a back-to-back comparison of common and emerging workflows, e.g., diaPASEF or ScanningSWATH, and evaluates the impact of arbitrary and inadequately documented settings or black-box data processing algorithms. It enhances the overall performance and quantification accuracy by recognizing and reporting common quantification errors.

Comprehensive Proteomics Analysis of the Hemolymph Composition of Sugar-Fed Aedes aegypti Female and Male Mosquitoes.

In arthropods, hemolymph carries immune cells and solubilizes and transports nutrients, hormones, and other molecules that are involved in diverse physiological processes including immunity, metabolism, and reproduction. However, despite such physiological importance, little is known about its composition. We applied mass spectrometry-based label-free quantification approaches to study the proteome of hemolymph perfused from sugar-fed female and male Aedes aegypti mosquitoes. A total of 1403 proteins were identified, out of which 447 of them were predicted to be extracellular. In both sexes, almost half of these extracellular proteins were predicted to be involved in defense/immune response, and their relative abundances (based on their intensity-based absolute quantification, iBAQ) were 37.9 and 33.2%, respectively. Interestingly, among them, 102 serine proteases/serine protease-homologues were identified, with almost half of them containing CLIP regulatory domains. Moreover, proteins belonging to families classically described as chemoreceptors, such as odorant-binding proteins (OBPs) and chemosensory proteins (CSPs), were also highly abundant in the hemolymph of both sexes. Our data provide a comprehensive catalogue of A. aegypti hemolymph basal protein content, revealing numerous unexplored targets for future research on mosquito physiology and disease transmission. It also provides a reference for future studies on the effect of blood meal and infection on hemolymph composition.

Quantitative proteomics analysis reveals the protective role of S14G-humanin in septic acute kidney injury using 4D-label-free and PRM Approaches.

Mitochondrial dysfunction contributes to septic acute kidney injury (S-AKI), making mitochondrial protection a potential therapeutic strategy. This study investigates the effects of S14G-humanin (HNG) in S-AKI, utilizing 4D-label-free and parallel reaction monitoring (PRM) techniques for proteomic analysis. An S-AKI model was created in male C57BL/6 mice using lipopolysaccharide (LPS) injection, followed by HNG administration. After 24 h, kidney tissues were analyzed for histology, biochemistry, mitochondrial function, and proteomics. HNG treatment improved renal function, reduced tubular injury, and decreased pro-inflammatory cytokines and oxidative stress markers. Proteomic analysis identified 5900 proteins, with 5111 quantifiable. HNG altered the expression of 132 proteins, with 18 selected for PRM validation. Ten of these proteins were linked to key pathways, including fatty acid degradation and PPAR signaling. This study is the first to show HNG's protective effects in S-AKI, providing insights into its mechanisms through advanced proteomic techniques.

Quantitative proteomics reveals cellular responses to individual mAb expression and tunicamycin in CHO cells.

Chinese hamster ovary (CHO) cells are popular in the pharmaceutical industry for their ability to produce high concentrations of antibodies and their resemblance to human cells in terms of protein glycosylation patterns. Current data indicate the relevance of CHO cells in the biopharmaceutical industry, with a high number of product commendations and a significant market share for monoclonal antibodies. To enhance the production capabilities of CHO cells, a deep understanding of their cellular and molecular composition is crucial. Genome sequencing and proteomic analysis have provided valuable insights into the impact of the bioprocessing conditions, productivity, and product quality. In our investigation, we conducted a comparative analysis of proteomic profiles in high and low monoclonal antibody-producing cell lines and studied the impact of tunicamycin (TM)-induced endoplasmic reticulum (ER) stress. We examined the expression levels of different proteins including unfolded protein response (UPR) target genes by using label-free quantification techniques for protein abundance. Our results show the upregulation of proteins associated with protein folding mechanisms in low producer vs. high producer cell line suggesting a form of ER stress related to specific protein production. Further, Hspa9 and Dnaja3 are notable candidates activated by the mitochondria UPR and play important roles in protein folding processes in mitochondria. We identified significant upregulation of Nedd8 and Lgmn proteins in similar levels which may contribute to UPR stress. Interestingly, the downregulation of Hspa5/Bip and Pdia4 in response to tunicamycin treatment suggests a low-level UPR activation. KEY POINTS: • Proteome profiling of recombinant CHO cells under mild TM treatment. • Identified protein clusters are associated with the unfolded protein response (UPR). • The compared cell lines revealed noticeable disparities in protein expression levels.

Changes in the liver proteome of zebrafish (Danio rerio) exposed to glyphosate and aminomethylphosphonic acid in the presence of a humic substance.

Herbicide exposure can pose a considerable threat to non-target aquatic animals. We aimed to study changes in the liver proteome of a model cyprinid fish species, zebrafish Danio rerio, to provide a molecular basis for the adverse effects of environmentally relevant concentrations of glyphosate (100 µg/L), its breakdown product aminomethylphosphonic acid (AMPA; 100 µg/L), and a mixture of both (50 + 50 µg/L) in the presence of humic acid (20 mg/L), which simulated a component of natural organic matter in the aquatic environment. Proteomic analysis was performed by means of high-performance liquid chromatography-tandem mass spectrometry employing a label-free quantification approach. The results present molecular evidence of the stress responses and disturbance of primary metabolic processes such as immune response, dysregulation in DNA repair, necroptosis and apoptosis signaling pathways, oxidative phosphorylation, cholesterol, lipoprotein, and carbohydrate metabolism. We registered the synergistic effect of the glyphosate and AMPA co-exposure, which was expressed in a substantial increase in the number of dysregulated proteins compared to the solo treatments. Humic acid alleviated the effects of glyphosate and its mixture with AMPA and aggravated the impact of AMPA exposure. RuvB-like 2, a protein taking part in DNA repair, and EIF2S1, involved in the regulation of stress-induced gene expression, were downregulated in the liver of zebrafish from all treatments.

Tissue-based absolute quantification using large-scale TMT and LFQ experiments.

Relative and absolute intensity-based protein quantification across cell lines, tissue atlases and tumour datasets is increasingly available in public datasets. These atlases enable researchers to explore fundamental biological questions, such as protein existence, expression location, quantity and correlation with RNA expression. Most studies provide MS1 feature-based label-free quantitative (LFQ) datasets; however, growing numbers of isobaric tandem mass tags (TMT) datasets remain unexplored. Here, we compare traditional intensity-based absolute quantification (iBAQ) proteome abundance ranking to an analogous method using reporter ion proteome abundance ranking with data from an experiment where LFQ and TMT were measured on the same samples. This new TMT method substitutes reporter ion intensities for MS1 feature intensities in the iBAQ framework. Additionally, we compared LFQ-iBAQ values to TMT-iBAQ values from two independent large-scale tissue atlas datasets (one LFQ and one TMT) using robust bottom-up proteomic identification, normalisation and quantitation workflows.