The clinical proteomics field has seen enormous growth in the past 20 years, with over 40000 scientific manuscripts published. At the same time, actual clinical application of the reported findings is obviously scarce. In this manuscript we discuss the key issues that may be responsible for this apparent lack of success, which cannot be measured by the numbers of publications, but by the impact on patient management and treatment. We proceed with suggestions for potential solutions, which include keeping a strict focus on potential patient benefit. We hope this manuscript can help shaping the field, so it can in fact deliver on its realistic promise, to bring significant improvement in management and care to patients.

Fluctuating salinity is symptomatic of climate change challenging aquatic species. The melting of polar ice, rising sea levels, coastal surface and groundwater salinization, and increased evaporation in arid habitats alter salinity world-wide. Moreover, the frequency and intensity of extreme weather events such as rainstorms and floods increase, causing rapid shifts in brackish and coastal habitat salinity. Such salinity alterations disrupt homeostasis, and ultimately diminish fitness, of aquatic organisms by interfering with metabolism, reproduction, immunity, and other critical aspects of physiology. Proteins are central for these physiological mechanisms. They represent the molecular building blocks of phenotypes that govern organismal responses to environmental challenges. Environmental cues regulate proteins in concerted fashion, necessitating holistic analyses of proteomes for comprehending salinity stress responses. Proteomics approaches reveal molecular causes of population declines and enable holistic bioindication geared towards timely interventions to prevent local extinctions. Proteomics analyses of salinity effects on aquatic organisms have been performed since the mid-1990s, propelled by the invention of two-dimensional protein gels, soft ionization techniques for mass spectrometry, and nano-liquid chromatography in the 1970s and 1980s. This review summarizes the current knowledge on salinity regulation of proteomes from aquatic organisms, including key methodological advances over the past decades.

Ocean metaproteomics provides valuable insights into the structure and function of marine microbial communities. Yet, ocean samples are challenging due to their extensive biological diversity that results in a very large number of peptides with a large dynamic range. This study characterized the capabilities of data independent acquisition (DIA) mode for use in ocean metaproteomic samples. Spectral libraries were constructed from discovered peptides and proteins using machine learning algorithms to remove incorporation of false positives in the libraries. When compared with 1-dimensional and 2-dimensional data dependent acquisition analyses (DDA), DIA outperformed DDA both with and without gas phase fractionation. We found that larger discovered protein spectral libraries performed better, regardless of the geographic distance between where samples were collected for library generation and where the test samples were collected. Moreover, the spectral library containing all unique proteins present in the Ocean Protein Portal outperformed smaller libraries generated from individual sampling campaigns. However, a spectral library constructed from all open reading frames in a metagenome was found to be too large to be workable, resulting in low peptide identifications due to challenges maintaining a low false discovery rate with such a large database size. Given sufficient sequencing depth and validation studies, spectral libraries generated from previously discovered proteins can serve as a community resource, saving resequencing efforts. The spectral libraries generated in this study are available at the Ocean Protein Portal for this purpose.

Sepsis is characterized by life-threatening organ dysfunction caused by dysregulated host response to infection. An underlying cause of sepsis is dysregulation of neutrophil-endothelial interactions. To date, therapeutic approaches are supportive, and there are no effective drugs that target immune dysregulation and alter neutrophil-endothelium function. In our prior investigation, three distinct neutrophil functional phenotypes (i.e., Hyperimmune, Hypoimmune and Hybrid) were identified in sepsis patients through a comprehensive analysis encompassing clinical, organ-on-chip and proteomic assessments. In this study, we utilized bioinformatics to elucidate cellular processes impacting each neutrophil phenotype. These findings were leveraged to identify potential FDA-approved therapeutics that could be repurposed to target proteins within each phenotype highlighting the impact in normalizing altered neutrophil-related responses such as adhesion and migration. A protein-protein interaction network was employed to prioritize these target proteins. Finally, we identify several FDA approved therapeutics for treating sepsis including a (pre)clinical trial therapeutic targeting VTN in the Hybrid phenotype, a therapeutic targeting TRPV2 in the Hypoimmune phenotype and a (pre)clinical trial therapeutic targeting H2AC21 in the Hyperimmune phenotype. Thus, we not only identified critical cellular processes impacting each neutrophil phenotype but also reveal those protein targets that could be prioritized for future validation in the treatment of sepsis.

The nuclear steroid hormone receptor Progesterone Receptor (PGR) is expressed in granulosa cells in the ovarian follicle in a tightly regulated pattern in response to the surge of Luteinizing Hormone (LH) that stimulates ovulation. PGR plays a critical role in mediating ovulation in response to LH, however the mechanism for this is still unknown. We performed immunoprecipitation-mass spectrometry using the KGN human granulosa cell line expressing the primary PGR isoforms PGR-A or PGR-B, to identify novel interacting proteins that regulate PGR function in these ovary-specific target cells. Proteomic analysis revealed protein interactions with both PGR isoforms that were gained (e.g. transcriptional coactivators) or lost (e.g. chaperone proteins) in response to the PGR agonist R5020. Additionally, isoform-specific interactions, including different families of transcriptional regulators, were identified. Comparison with published datasets of PGR interacting proteins in human breast cancer cell lines and decidualised endometrial stromal cells demonstrated a remarkable number of tissue-specific interactions, shedding light on how PGR can maintain diverse functions in different tissues. In conclusion, we provide a comprehensive novel dataset of the PGR interactome in previously unstudied ovarian cells and offer new insights into ovary-specific PGR transcriptional mechanisms.

High-altitude hypoxic environments significantly affect the cardiovascular system and blood pressure regulation. However, the underlying pathological mechanisms remain unclear, necessitating further studies on the effect of high-altitude hypoxic exposure on blood pressure. We established a long-term high-altitude hypoxia exposure model, exposing spontaneously hypertensive rats (SHRs) to high-altitude hypoxia for 10 weeks, and performed quantitative proteomics and metabolomics of the abdominal aorta of SHRs using tandem mass tag-based quantitative proteomics and metabolomics. Analysis using bioinformatics and enrichment strategies indicated that the altered proteins and metabolites participate in various biological processes. The differentially expressed proteins primarily participate in oxidative phosphorylation pathways, thermogenesis, the tricarboxylic acid cycle, and carbon metabolism. We speculated that oxidative phosphorylation and thermogenesis were related to the reduced blood pressure in SHRs under high-altitude hypoxic conditions. Combined proteome and metabolome analyses revealed that altered metabolites, including thiamine, S-adenosylhomocysteine, pantothenic acid, fumaric acid, and homoserine, participated alongside differentially expressed proteins in the process of blood pressure reduction in high-altitude hypoxic environments in SHRs. This study elucidated the potential molecular mechanisms underlying blood pressure reduction in SHRs under high-altitude hypoxic conditions by integrating proteomics and metabolomics, providing insights into exploring how high-altitude hypoxia affects blood pressure at the molecular level.

The development of the gut microbiome in infancy is a vulnerable process that may be perturbed by antibiotics or supported by probiotics. While effects of these “biotics” have been well-studied through DNA sequencing, it remains unclear how the resulting compositional changes affect the microbiome’s metabolic functions. Additionally, limits in method standardization require careful quality assessment of studies reporting fecal metabolome. We conducted a systematic search in Embase and MEDLINE for studies describing fecal metabolites from term and near-term infants, together with anti-, pre-, or probiotic intervention. The search identified 680 articles, of which 60 were assessed for eligibility and 21 included. We first developed operational checklists for transparent and reproducible reporting and evaluated the quality of metabolomic methodologies. This analysis supported our aim to summarise changes in the fecal metabolome induced by biotic interventions. Despite a varying quality of metabolomic methodology, we identified similarities in the fecal metabolome profiles in response to specific biotic interventions. Among the most frequently observed metabolites, which seemed to be consistently altered after biotic interventions, were bile acids, aromatic amino acids, and short-chain fatty acids. We conclude with a discussion on appropriate experimental design, controls, and metabolomics reporting to guide future research permitting meta-analyses.

Proximity-dependent biotinylation (PDB) is a powerful means of exploring the cellular environments in which proteins reside. Expressing a protein of interest (bait) fused to a biotin ligase and adding biotin induces the covalent biotinylation of proximal partners, which are recovered on streptavidin beads and identified by MS. However, a major technical limitation of PDB is peptide carryover into subsequent MS runs. This is mitigated via lengthy inter-sample washing, considerably lowering throughput. This study aims to optimize PDB sample acquisition using an EvoSep LC system coupled to a timsTOF mass spectrometer, which has higher throughput and sensitivity than our current system, with less carryover. Our efforts resulted in an ~15-fold increase in throughput using the 60 samples-per-day (SPD) gradient with better sensitivity, identifying nearly double the proteins found by our previously standardized workflow. Significance scoring also revealed more sensitive detection of high-confidence proximal interactions (~1.5-fold) for five well-characterized baits, validating the new experimental workflow. Importantly, carryover was extremely limited, even without inter-sample washing, and limited to easily filterable abundant proteins. Without washing, this method can process 60 samples per day, using 1/16th of the sample amount previously required.

The human gut microbiome exhibits characteristics of complex ecosystems, including the ability to resist and compete with exogenous species or communities. Understanding microbiome responses to such competition is crucial, especially for fecal microbiota transplantation (FMT), where success depends on microbial interactions. During these processes, microbial communities undergo coalescence, combining and interacting in ways that lead to complex ecological outcomes. In this study, we investigated the coalescent dynamics of ten pairs of human gut microbiota through in vitro co-culturing. Metaproteomic analysis revealed that post-coalescence changes were not simply an average of the initial microbiotas but instead, both coalescent microbiotas behaved as cohesive structures, influencing the competitive outcome towards one of them. While taxonomic similarities were observed between co-cultured communities and their parental samples, 23% of proteins showed differential expression. Interestingly, the competitive outcomes followed a “rock-paper-scissors” dynamic, with different species contributing to competition outcomes across different pairs. This highlights the complexity of microbial competition, suggesting that no single factor consistently determines dominance. Pre-co-culturing may thus be a promising method for predicting outcomes in FMT and other ecological therapies.

This article explores the issues involved in developing personalized medicine as part of the KidneySign project, which aim is to mobilize translational Big Data to validate a proteomic biomarker of renal fibrosis. This research offers hope for the management of chronic kidney disease in terms of early diagnosis and treatment. This article looks at how the human and social sciences can be mobilized within the project to study the adjoining ethical, legal and social issues. By highlighting these aspects, this point of view defends a multidisciplinary approach to personalized medicine and artificial intelligence in medicine. The presentation of theoretical and methodological contributions of social sciences in the case of KidneySign offers an opportunity to better understand the integration of these disciplines into biomedical research. It allows to question the study protocol itself and to frame it through legal contributions (considering the legal aspects, consequences and challenges). Moreover, by carrying out a sociological study, one may identify key points and highlight the limits of the technophile fantasy in the representations of patients and healthcare professionals. The introduction of new technologies into medical research and practice requires particular attention to ethics.

The integration of big data into nephrology research has opened new avenues for analyzing and understanding complex biological datasets, driving advancements in personalized management of cardiovascular and kidney diseases. This paper explores the multifaceted challenges and opportunities presented by big data in nephrology, emphasizing the importance of data standardization, sophisticated storage solutions, and advanced analytical methods. We discuss the role of data science workflows, including data collection, preprocessing, integration, and analysis, in facilitating comprehensive insights into disease mechanisms and patient outcomes. Furthermore, we highlight the potential of predictive and prescriptive analytics, as well as the application of large language models (LLMs), in improving clinical decision-making and enhancing the accuracy of disease predictions. The use of high-performance computing (HPC) is also examined, showcasing its critical role in processing large-scale datasets and accelerating machine learning algorithms. Through this exploration, we aim to provide a comprehensive overview of the current state and future directions of big data analytics in nephrology, with a focus on enhancing patient care and advancing medical research.

Post-translational modifications (PTMs) are of significant interest in molecular biomedicine due to their crucial role in signal transduction across various cellular and organismal processes. Characterizing PTMs, distinguishing between functional and inert modifications, quantifying their occupancies, and understanding PTM crosstalk are challenging tasks in any biosystem. Studying each PTM often requires a specific, labor-intensive experimental design. Here, we present a PTM-centric proteome informatic pipeline for predicting relevant PTMs in mass spectrometry-based proteomics data without prior information. Once predicted, these in silico identified PTMs can be incorporated into a refined database search and compared to measured data. As a practical application, we demonstrate how this pipeline can be used to study glycoproteomics in oral squamous cell carcinoma based on the proteome profile of primary tumors. Subsequently, we experimentally identified cellular proteins that are differentially expressed in cells treated with multikinase inhibitors dasatinib and staurosporine using mass spectrometry-based proteomics. Computational enrichment analysis was then employed to determine the potential PTMs of differentially expressed proteins induced by both drugs. Finally, we conducted an additional round of database search with the predicted PTMs. Our pipeline successfully analyzed the enriched PTMs and detected proteins not identified in the initial search. Our findings support the effectiveness of PTM-centric searching of MS data in proteomics based on computational enrichment analysis, and we propose integrating this approach into future proteomics search engines.

Human males and females show differences in the incidence of neutrophil-associated diseases and differences in neutrophil responses such as a faster response to the chemorepellent SLIGKV in males. Little is known about the basis of sex-based differences in human neutrophils. We used mass spectrometry to identify proteins and phosphoproteins in unstimulated human neutrophils and in neutrophils incubated with the SLIGKV, a protease activated receptor 2 agonist. There were 132 proteins with higher levels in unstimulated male neutrophils; these proteins tended to be associated with RNA regulation, ribosome, and phosphoinositide signaling pathways, whereas 30 proteins with higher levels in unstimulated female neutrophils were associated with metabolic processes, proteosomes, and phosphatase regulatory proteins. Unstimulated male neutrophils had increased phosphorylation of 32 proteins compared to females. After exposure to SLIGKV, male neutrophils showed a faster response in terms of protein phosphorylation compared to female neutrophils. Male neutrophils have higher levels of proteins and higher phosphorylation of proteins associated with RNA processing and signaling pathways. Female neutrophils have higher levels of proteins associated with metabolism and proteolytic pathways. This suggests that male neutrophils might be more ready to adapt to a new environment, and female neutrophils might be more effective at responding to pathogens.

Glycosylation, a significant form of post-translational modification (PTM) in organisms, is aberrantly expressed in cancer due to altered glycosyltransferase activity. Studies have shown specific changes in glycan structures associated with epithelial-mesenchymal transition (EMT) of cancer cells. This study analyzed glycans in bronchoalveolar lavage fluid (BALF) from lung adenocarcinoma (LUAD) patients and found a significant reduction in glycans containing the bisecting-GlcNAc structure. Further investigation revealed that reduced expression of β-1,4-mannosyl-glycoprotein 4-β-N-acetylglucosaminyltransferase (MGAT3) downregulates epithelial markers, promoting EMT. Additionally, we observed a notable downregulation of both mRNA and protein expression of Forkhead box protein A2 (FOXA2) in early-stage LUAD, with FOXA2 loss emerging as an adverse prognostic indicator. Cellular models demonstrated that FOXA2 deficiency decreased MGAT3 expression during TGF-β1-driven EMT, leading to reduced levels of bisecting-GlcNAc N-glycans in LUAD cells. Our findings unveil a novel mechanism underlying the downregulation of MGAT3 and bisecting GlcNAc N-glycan expression during EMT, a process crucial for tumor metastasis.

Gracilaria is a genus of red-algae found mainly in Asia. The population of Gracilaria spread throughout Indonesia’s marine waters, especially in coastal areas. To date, the unique protein expressions using proteomic approach moreover in Central Java area, Indonesia is sporadic. Nonetheless, there has been no report mentioned about Gracilaria spp. amino acid sequences nor its characteristics. Based on the background mentioned, we aimed to conduct protein characterization by using peptide sequence analysis LC-HRMS. Liquid chromatography coupled with high-resolution mass spectrometry (LC–HRMS) use has growing across biomedical and environmental sciences, hence provides high accuracy for the detection. We followed the LC-HRMS standard protocol, with optimized precipitation standard. TCA/Aceton precipitation of protein were used as protein purification, then the precipitate subjected for Trypsin digestion. Result of protein analysis were described as protein concentrations, molecular model, and peptide sequences. This experiment showed four identified sequences derived from Rhodophyta database, there are TKKILDK (845.5455 Da), TVKSLLTK (889.5717 Da), ILVKTLK (814.5761 Da), TGcGRSKR (921.4683 Da). This study uncovers peptide sequences for Gracilaria spp. and its similarity with other red algae species along with the function of whole peptide sequences. Furthermore, amino acid models of secondary structure Hidden Markov Model(HMM) were provided to support our findings.

This study aimed to identify the total proteome of Hydra vulgaris, a freshwater polyp representative of the phylum Cnidaria. This organism, known for its organized nerve net, has been a favoured model due to its unique regeneration capabilities, simple bilayer architecture separated by a mesoglea, and limited cell types. While vertebrate models offer insights into molecular signaling, invertebrate like Hydra have been instrumental in uncovering the evolutionary roles of various molecules. Despite advances in genomic analyses of Hydra, a comprehensive proteomic analysis has been lacking. Here, we explored the proteome of Hydra vulgaris using a combination of gel electrophoresis and nanoflow liquid chromatography-mass spectrometry, identifying over 5,200 proteins across all cellular components. This proteomic analysis helps gain insight into the evolutionary origins and ancestral functions of proteins involved in contemporary diseases such as Alzheimer's disease or inherited retinal dystrophies. This analysis led to the identification of proteins corresponding to transporter proteins, or to endoplasmic reticulum. Such are ATPase, calcium-binding or retinal proteins with 4 linked to photoreceptors and 6 implicated in Alzheimer disease. The data set provided in this article describes the proteins identified in the body of Hydra and the processes and functions associated with a selection of them.

Peptides play an indispensable role in various biological functions and show therapeutic potential. The forest musk deer, an important source of musk, is a focal species in traditional medicine. While cell culture techniques offer a sustainable alternative for musk production, the complexity of peptide components produced by these methods remains poorly understood. To bridge this knowledge gap, we compared the peptidomic profiles of secretions from cultured musk gland cells with those of natural musk cells using the EASY-nLC 1000 UHPLC (Ultra-High Performance Liquid Chromatography) system. Our analysis revealed similarities and notable differences between the peptide profiles of cultured cell secretions and those of natural musk, with significant implications for the biosynthesis and chemical composition of musk. This study provides critical insights into the peptidomic differences between cultured cell secretions and natural musk, highlighting the challenges and potential of using cell culture techniques for the sustainable production of musk components. Future research should focus on refining conditions to more closely emulate the natural biosynthetic pathways of musk peptides.

The mammalian ejaculate is very well suited for proteomics studies. As such, investigations on the sperm proteomics are offering a huge amount of new information on the biology of the spermatozoa. Among domestic animals, horses represent a special interest species, in which reproductive technologies and an important market of genetic material has growth exponentially in the last decade. Investigations using proteomic approaches have been conducted in recent years, showing that proteomics is a potent tool to dig into the biology of the stallion spermatozoa. The aim of this review is to present an overview of the research conducted, and how these studies have improved our knowledge of the stallion sperm biology. The main outcomes of the research conducted so far have been an improved knowledge of the metabolism, and its importance of sperm functions, the impact of different technologies in the sperm proteome, and the identification of potential biomarkers. Moreover, proteomics of the seminal plasma and phosphoproteomics are identified as areas of major interest.