Development of an efficient, effective, and economical technology for proteome analysis.

We present an efficient, effective, and economical approach, named E3technology, for proteomics sample preparation. By immobilizing silica microparticles into the polytetrafluoroethylene matrix, we develop a robust membrane medium, which could serve as a reliable platform to generate proteomics-friendly samples in a rapid and low-cost fashion. We benchmark its performance using different formats and demonstrate them with a variety of sample types of varied complexity, quantity, and volume. Our data suggest that E3technology provides proteome-wide identification and quantitation performance equivalent or superior to many existing methods. We further propose an enhanced single-vessel approach, named E4technology, which performs on-filter in-cell digestion with minimal sample loss and high sensitivity, enabling low-input and low-cell proteomics. Lastly, we utilized the above technologies to investigate RNA-binding proteins and profile the intact bacterial cell proteome.

Assessment of Kinome-Wide Activity Remodeling upon Picornavirus Infection.

Picornaviridae represent a large family of single-stranded positive RNA viruses of which different members can infect both humans and animals. These include the enteroviruses (e.g., poliovirus, coxsackievirus, and rhinoviruses) as well as the cardioviruses (e.g., encephalomyocarditis virus). Picornaviruses have evolved to interact with, use, and/or evade cellular host systems to create the optimal environment for replication and spreading. It is known that viruses modify kinase activity during infection, but a proteome-wide overview of the (de)regulation of cellular kinases during picornavirus infection is lacking. To study the kinase activity landscape during picornavirus infection, we here applied dedicated targeted mass spectrometry-based assays covering ∼40% of the human kinome. Our data show that upon infection, kinases of the MAPK pathways become activated (e.g., ERK1/2, RSK1/2, JNK1/2/3, and p38), while kinases involved in regulating the cell cycle (e.g., CDK1/2, GWL, and DYRK3) become inactivated. Additionally, we observed the activation of CHK2, an important kinase involved in the DNA damage response. Using pharmacological kinase inhibitors, we demonstrate that several of these activated kinases are essential for the replication of encephalomyocarditis virus. Altogether, the data provide a quantitative understanding of the regulation of kinome activity induced by picornavirus infection, providing a resource important for developing novel antiviral therapeutic interventions.

A Causal Model of Ion Interference Enables Assessment and Correction of Ratio Compression in Multiplex Proteomics.

Multiplex proteomics using isobaric labeling tags has emerged as a powerful tool for the simultaneous relative quantification of peptides and proteins across multiple experimental conditions. However, the quantitative accuracy of the approach is largely compromised by ion interference, a phenomenon that causes fold changes to appear compressed. The degree of compression is generally unknown, and the contributing factors are poorly understood. In this study, we thoroughly characterized ion interference at the MS2 level using a defined two-proteome experimental system with known ground-truth. We discovered remarkably poor agreement between the apparent precursor purity in the isolation window and the actual level of observed reporter ion interference in MS2 scans-a discrepancy that we found resolved by considering cofragmentation of peptide ions hidden within the spectral "noise" of the MS1 isolation window. To address this issue, we developed a regression modeling strategy to accurately predict reporter ion interference in any dataset. Finally, we demonstrate the utility of our procedure for improved fold change estimation and unbiased PTM site-to-protein normalization. All computational tools and code required to apply this method to any MS2 TMT dataset are documented and freely available.

Substances in the mandibular glands mediate queen effects on larval development and colony organization in an annual bumble bee.

Social organization is commonly dynamic, with extreme examples in annual social insects, but little is known about the underlying signals and mechanisms. Bumble bee larvae with close contact to a queen do not differentiate into gynes, pupate at an earlier age, and are commonly smaller than siblings that do not contact a queen. We combined detailed observations, proteomics, microRNA transcriptomics, and gland removal surgery to study the regulation of brood development and division of labor in the annual social bumble bee Bombus terrestris. We found that regurgitates fed to larvae by queens and workers differ in their protein and microRNA composition. The proteome of the regurgitate overlaps significantly with that of the mandibular (MG) and hypopharyngeal glands (HPG), suggesting that these exocrine glands are sources of regurgitate proteins. The proteome of the MG and HPG, but not the salivary glands, differs between queens and workers, with caste-specificity preserved for the MG and regurgitate proteomes. Queens subjected to surgical removal of the MG showed normal behavior, brood care, and weight gain, but failed to shorten larval development. These findings suggest that substances in the queen MG are fed to larvae and influence their developmental program. We suggest that when workers emerge and contribute to larval feeding, they dilute the effects of the queen substances, until she can no longer manipulate the development of all larvae. Longer developmental duration may allow female larvae to differentiate into gynes rather than to workers, mediating the colony transition from the ergonomic to the reproductive phase.

Liver mitochondrial cristae organizing protein MIC19 promotes energy expenditure and pedestrian locomotion by altering nucleotide metabolism.

Liver mitochondria undergo architectural remodeling that maintains energy homeostasis in response to feeding and fasting. However, the specific components and molecular mechanisms driving these changes and their impact on energy metabolism remain unclear. Through comparative mouse proteomics, we found that fasting induces strain-specific mitochondrial cristae formation in the liver by upregulating MIC19, a subunit of the MICOS complex. Enforced MIC19 expression in the liver promotes cristae formation, mitochondrial respiration, and fatty acid oxidation while suppressing gluconeogenesis. Mice overexpressing hepatic MIC19 show resistance to diet-induced obesity and improved glucose homeostasis. Interestingly, MIC19 overexpressing mice exhibit elevated energy expenditure and increased pedestrian locomotion. Metabolite profiling revealed that uracil accumulates in the livers of these mice due to increased uridine phosphorylase UPP2 activity. Furthermore, uracil-supplemented diet increases locomotion in wild-type mice. Thus, MIC19-induced mitochondrial cristae formation in the liver increases uracil as a signal to promote locomotion, with protective effects against diet-induced obesity.

SILAC-IodoTMT for Assessment of the Cellular Proteome and Its Redox Status.

Stable isotope labeling by amino acids in cell culture (SILAC) and iodoacetyl tandem mass tag (iodoTMT) are well-implemented mass spectrometry-based approaches for quantification of proteins and for site-mapping of cysteine modification. We describe here a combination of SILAC and iodoTMT to assess ongoing changes in the global proteome and cysteine modification levels using liquid chromatography separation coupled with high-resolution mass spectrometry (LC-MS/MS).

Quantitative Assessment of Arsenite-Induced Perturbation of Ubiquitinated Proteome.

Arsenic contamination in food and groundwater constitutes a public health concern for more than 200 million people worldwide. Individuals chronically exposed to arsenic through drinking and ingestion exhibit a higher risk of developing cancers and cardiovascular diseases. Nevertheless, the underlying mechanisms of arsenic toxicity are not fully understood. Arsenite is known to bind to and deactivate RING finger E3 ubiquitin ligases; thus, we reason that a systematic interrogation about how arsenite exposure modulates global protein ubiquitination may reveal novel molecular targets for arsenic toxicity. By employing liquid chromatography-tandem mass spectrometry, in combination with stable isotope labeling by amino acids in cell culture (SILAC) and immunoprecipitation of di-glycine-conjugated lysine-containing tryptic peptides, we assessed the alterations in protein ubiquitination in GM00637 human skin fibroblast cells upon arsenite exposure at the entire proteome level. We observed that arsenite exposure led to altered ubiquitination of many proteins, where the alterations in a large majority of ubiquitination events are negatively correlated with changes in expression of the corresponding proteins, suggesting their modulation by the ubiquitin-proteasomal pathway. Moreover, we observed that arsenite exposure confers diminished ubiquitination of a rate-limiting enzyme in cholesterol biosynthesis, HMGCR, at Lys248. We also revealed that TRC8 is the major E3 ubiquitin ligase for HMGCR ubiquitination in HEK293T cells, and the arsenite-induced diminution of HMGCR ubiquitination is abrogated upon genetic depletion of TRC8. In summary, we systematically characterized arsenite-induced perturbations in a ubiquitinated proteome in human cells and found that the arsenite-elicited attenuation of HMGCR ubiquitination in HEK293T cells involves TRC8.

A Computational Toolbox to Investigate the Metabolic Potential and Resource Allocation in Fission Yeast.

The fission yeast, Schizosaccharomyces pombe, is a popular eukaryal model organism for cell division and cell cycle studies. With this extensive knowledge of its cell and molecular biology, S. pombe also holds promise for use in metabolism research and industrial applications. However, unlike the baker's yeast, Saccharomyces cerevisiae, a major workhorse in these areas, cell physiology and metabolism of S. pombe remain less explored. One way to advance understanding of organism-specific metabolism is construction of computational models and their use for hypothesis testing. To this end, we leverage existing knowledge of S. cerevisiae to generate a manually curated high-quality reconstruction of S. pombe's metabolic network, including a proteome-constrained version of the model. Using these models, we gain insights into the energy demands for growth, as well as ribosome kinetics in S. pombe. Furthermore, we predict proteome composition and identify growth-limiting constraints that determine optimal metabolic strategies under different glucose availability regimes and reproduce experimentally determined metabolic profiles. Notably, we find similarities in metabolic and proteome predictions of S. pombe with S. cerevisiae, which indicate that similar cellular resource constraints operate to dictate metabolic organization. With these cases, we show, on the one hand, how these models provide an efficient means to transfer metabolic knowledge from a well-studied to a lesser-studied organism, and on the other, how they can successfully be used to explore the metabolic behavior and the role of resource allocation in driving different strategies in fission yeast. IMPORTANCE Our understanding of microbial metabolism relies mostly on the knowledge we have obtained from a limited number of model organisms, and the diversity of metabolism beyond the handful of model species thus remains largely unexplored in mechanistic terms. Computational modeling of metabolic networks offers an attractive platform to bridge the knowledge gap and gain new insights into physiology of lesser-studied organisms. Here we showcase an example of successful knowledge transfer from the budding yeast Saccharomyces cerevisiae to a popular model organism in molecular and cell biology, fission yeast Schizosaccharomyces pombe, using computational models.

A modification-centric assessment tool for the performance of chemoproteomic probes.

Chemoproteomics has emerged as a key technology to expand the functional space in complex proteomes for probing fundamental biology and for discovering new small-molecule-based therapies. Here we report a modification-centric computational tool termed pChem to provide a streamlined pipeline for unbiased performance assessment of chemoproteomic probes. The pipeline starts with an experimental setting for isotopically coding probe-derived modifications that can be automatically recognized by pChem, with masses accurately calculated and sites precisely localized. pChem exports on-demand reports by scoring the profiling efficiency, modification homogeneity and proteome-wide residue selectivity of a tested probe. The performance and robustness of pChem were benchmarked by applying it to eighteen bioorthogonal probes. These analyses reveal that the formation of unexpected probe-derived modifications can be driven by endogenous reactive metabolites (for example, bioactive aldehydes and glutathione). pChem is a powerful and user-friendly tool that aims to facilitate the development of probes for the ever-growing field of chemoproteomics.

Accurate Proteoform Identification and Quantitation Using pTop 2.0.

The remarkable advancement of top-down proteomics in the past decade is driven by the technological development in separation, mass spectrometry (MS) instrumentation, novel fragmentation, and bioinformatics. However, the accurate identification and quantification of proteoforms, all clearly-defined molecular forms of protein products from a single gene, remain a challenging computational task. This is in part due to the complicated mass spectra from intact proteoforms when compared to those from the digested peptides. Herein, pTop 2.0 is developed to fill in the gap between the large-scale complex top-down MS data and the shortage of high-accuracy bioinformatic tools. Compared with pTop 1.0, the first version, pTop 2.0 concentrates mainly on the identification of the proteoforms with unexpected modifications or a terminal truncation. The quantitation based on isotopic labeling is also a new function, which can be carried out by the convenient and user-friendly "one-key operation," integrated together with the qualitative identifications. The accuracy and running speed of pTop 2.0 is significantly improved on the test data sets. This chapter will introduce the main features, step-by-step running operations, and algorithmic developments of pTop 2.0 in order to push the identification and quantitation of intact proteoforms to a higher-accuracy level in top-down proteomics.

Yeast has evolved to minimize protein resource cost for synthesizing amino acids.

Proteins, as essential biomolecules, account for a large fraction of cell mass, and thus the synthesis of the complete set of proteins (i.e., the proteome) represents a substantial part of the cellular resource budget. Therefore, cells might be under selective pressures to optimize the resource costs for protein synthesis, particularly the biosynthesis of the 20 proteinogenic amino acids. Previous studies showed that less energetically costly amino acids are more abundant in the proteomes of bacteria that survive under energy-limited conditions, but the energy cost of synthesizing amino acids was reported to be weakly associated with the amino acid usage in Saccharomyces cerevisiae Here we present a modeling framework to estimate the protein cost of synthesizing each amino acid (i.e., the protein mass required for supporting one unit of amino acid biosynthetic flux) and the glucose cost (i.e., the glucose consumed per amino acid synthesized). We show that the logarithms of the relative abundances of amino acids in S. cerevisiae's proteome correlate well with the protein costs of synthesizing amino acids (Pearson's r = -0.89), which is better than that with the glucose costs (Pearson's r = -0.5). Therefore, we demonstrate that S. cerevisiae tends to minimize protein resource, rather than glucose or energy, for synthesizing amino acids.

Assessment of a complete and classified platelet proteome from genome-wide transcripts of human platelets and megakaryocytes covering platelet functions.

Novel platelet and megakaryocyte transcriptome analysis allows prediction of the full or theoretical proteome of a representative human platelet. Here, we integrated the established platelet proteomes from six cohorts of healthy subjects, encompassing 5.2 k proteins, with two novel genome-wide transcriptomes (57.8 k mRNAs). For 14.8 k protein-coding transcripts, we assigned the proteins to 21 UniProt-based classes, based on their preferential intracellular localization and presumed function. This classified transcriptome-proteome profile of platelets revealed: (i) Absence of 37.2 k genome-wide transcripts. (ii) High quantitative similarity of platelet and megakaryocyte transcriptomes (R = 0.75) for 14.8 k protein-coding genes, but not for 3.8 k RNA genes or 1.9 k pseudogenes (R = 0.43-0.54), suggesting redistribution of mRNAs upon platelet shedding from megakaryocytes. (iii) Copy numbers of 3.5 k proteins that were restricted in size by the corresponding transcript levels (iv) Near complete coverage of identified proteins in the relevant transcriptome (log2fpkm > 0.20) except for plasma-derived secretory proteins, pointing to adhesion and uptake of such proteins. (v) Underrepresentation in the identified proteome of nuclear-related, membrane and signaling proteins, as well proteins with low-level transcripts. We then constructed a prediction model, based on protein function, transcript level and (peri)nuclear localization, and calculated the achievable proteome at ~ 10 k proteins. Model validation identified 1.0 k additional proteins in the predicted classes. Network and database analysis revealed the presence of 2.4 k proteins with a possible role in thrombosis and hemostasis, and 138 proteins linked to platelet-related disorders. This genome-wide platelet transcriptome and (non)identified proteome database thus provides a scaffold for discovering the roles of unknown platelet proteins in health and disease.

Assessment of the Cytoprotective Effects of High-Dose Valproic Acid Compared to a Clinically Used Lower Dose.

OBJECTIVE: Valproic acid (VPA) treatment improves survival in animal models of injuries on doses higher than those allowed by Food and Drug Administration (FDA). We investigated the proteomic alterations induced by a single high-dose (140mg/kg) of VPA (VPA140) compared to the FDA-approved dose of 30mg/kg (VPA30) in healthy humans. We also describe the proteomic and transcriptomic changes induced by VPA140 in an injured patient. We hypothesized that VPA140 would induce cytoprotective changes in the study participants. METHODS: Serum samples were obtained from healthy subjects randomized to two groups; VPA140 and VPA30 at 3 timepoints: 0h(baseline), 2h, and 24h following infusion(n = 3/group). Samples were also obtained from an injured patient that received VPA140 at 0h, 6h and 24h following infusion. Proteomic analyses were performed using liquid chromatography-mass spectrometry (LC-MS/MS), and transcriptomic analysis was performed using RNA-sequencing. Differentially expressed (DE) proteins and genes were identified for functional annotation and pathway analysis using iPathwayGuide and gene set enrichment analysis (GSEA), respectively. RESULTS: For healthy individuals, a dose comparison was performed between VPA140 and VPA30 groups at 2 and 24 h. Functional annotation showed that top biological processes in VPA140 versus VPA30 analysis at 2 h included regulation of fatty acid (P = 0.002) and ATP biosynthesis (P = 0.007), response to hypoxia (P = 0.017), cell polarity regulation (P = 0.031), and sequestration of calcium ions (P = 0.031). Top processes at 24 h in VPA140 versus VPA30 analysis included amino acid metabolism (P = 0.023), collagen catabolism (P = 0.023), and regulation of protein breakdown (P = 0.023). In the injured patient, annotation of the DE proteins in the serum showed that top biological processes at 2 h included neutrophil chemotaxis (P = 0.002), regulation of cellular response to heat (P = 0.008), regulation of oxidative stress (P = 0.008) and regulation of apoptotic signaling pathway (P = 0.008). Top biological processes in the injured patient at 24 h included autophagy (P = 0.01), glycolysis (P = 0.01), regulation of apoptosis (P = 0.01) and neuron apoptotic processes (P = 0.02). CONCLUSIONS: VPA140 induces cytoprotective changes in human proteome not observed in VPA30. These changes may be responsible for its protective effects in response to injuries.

A Proteomics-Based Assessment of Inflammation Signatures in Endotoxemia.

We have previously shown that multimers of plasma pentraxin-3 (PTX3) were predictive of survival in patients with sepsis. To characterize the release kinetics and cellular source of plasma protein changes in sepsis, serial samples were obtained from healthy volunteers (n = 10; three time points) injected with low-dose endotoxin (lipopolysaccharide [LPS]) and analyzed using data-independent acquisition MS. The human plasma proteome response was compared with an LPS-induced endotoxemia model in mice. Proteomic analysis of human plasma revealed a rapid neutrophil degranulation signature, followed by a rise in acute phase proteins. Changes in circulating PTX3 correlated with increases in neutrophil-derived proteins following LPS injection. Time course analysis of the plasma proteome in mice showed a time-dependent increase in multimeric PTX3, alongside increases in neutrophil-derived myeloperoxidase (MPO) upon LPS treatment. The mechanisms of oxidation-induced multimerization of PTX3 were explored in two genetic mouse models: MPO global knock-out (KO) mice and LysM Cre Nox2 KO mice, in which NADPH oxidase 2 (Nox2) is only deficient in myeloid cells. Nox2 is the enzyme responsible for the oxidative burst in neutrophils. Increases in plasma multimeric PTX3 were not significantly different between wildtype and MPO or LysM Cre Nox2 KO mice. Thus, PTX3 may already be stored and released in a multimeric form. Through in vivo neutrophil depletion and multiplexed vascular proteomics, PTX3 multimer deposition within the aorta was confirmed to be neutrophil dependent. Proteomic analysis of aortas from LPS-injected mice returned PTX3 as the most upregulated protein, where multimeric PTX3 was deposited as early as 2 h post-LPS along with other neutrophil-derived proteins. In conclusion, the rise in multimeric PTX3 upon LPS injection correlates with neutrophil-related protein changes in plasma and aortas. MPO and myeloid Nox2 are not required for the multimerization of PTX3; instead, neutrophil extravasation is responsible for the LPS-induced deposition of multimeric PTX3 in the aorta.

ProteoCombiner: integrating bottom-up with top-down proteomics data for improved proteoform assessment.

MOTIVATION: We present a high-performance software integrating shotgun with top-down proteomic data. The tool can deal with multiple experiments and search engines. Enable rapid and easy visualization, manual validation and comparison of the identified proteoform sequences including the post-translational modification characterization. RESULTS: We demonstrate the effectiveness of our approach on a large-scale Escherichia coli dataset; ProteoCombiner unambiguously shortlisted proteoforms among those identified by the multiple search engines. AVAILABILITY AND IMPLEMENTATION: ProteoCombiner, a demonstration video and user tutorial are freely available at https://proteocombiner.pasteur.fr, for academic use; all data are thus available from the ProteomeXchange consortium (identifier PXD017618). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Assessment of Tractable Cysteines for Covalent Targeting by Screening Covalent Fragments.

Targeted covalent inhibition and the use of irreversible chemical probes are important strategies in chemical biology and drug discovery. To date, the availability and reactivity of cysteine residues amenable for covalent targeting have been evaluated by proteomic and computational tools. Herein, we present a toolbox of fragments containing a 3,5-bis(trifluoromethyl)phenyl core that was equipped with chemically diverse electrophilic warheads showing a range of reactivities. We characterized the library members for their reactivity, aqueous stability and specificity for nucleophilic amino acids. By screening this library against a set of enzymes amenable for covalent inhibition, we showed that this approach experimentally characterized the accessibility and reactivity of targeted cysteines. Interesting covalent fragment hits were obtained for all investigated cysteine-containing enzymes.

Identification of biomarkers for the accurate and sensitive diagnosis of three bacterial pneumonia pathogens using in silico approaches.

BACKGROUND: Pneumonia ranks as one of the main infectious sources of mortality among kids under 5 years of age, killing 2500 a day; late research has additionally demonstrated that mortality is higher in the elderly. A few biomarkers, which up to this point have been distinguished for its determination lack specificity, as these biomarkers fail to build up a differentiation between pneumonia and other related diseases, for example, pulmonary tuberculosis and Human Immunodeficiency Infection (HIV). There is an inclusive global consensus of an improved comprehension of the utilization of new biomarkers, which are delivered in light of pneumonia infection for precision identification to defeat these previously mentioned constraints. Antimicrobial peptides (AMPs) have been demonstrated to be promising remedial specialists against numerous illnesses. This research work sought to identify AMPs as biomarkers for three bacterial pneumonia pathogens such as Streptococcus pneumoniae, Klebsiella pneumoniae, Acinetobacter baumannii using in silico technology. Hidden Markov Models (HMMER) was used to identify putative anti-bacterial pneumonia AMPs against the identified receptor proteins of Streptococcus pneumoniae, Klebsiella pneumoniae, and Acinetobacter baumannii. The physicochemical parameters of these putative AMPs were computed and their 3-D structures were predicted using I-TASSER. These AMPs were subsequently subjected to docking interaction analysis against the identified bacterial pneumonia pathogen proteins using PATCHDOCK. RESULTS: The in silico results showed 18 antibacterial AMPs which were ranked based on their E values with significant physicochemical parameters in conformity with known experimentally validated AMPs. The AMPs also bound the pneumonia receptors of their respective pathogens sensitively at the extracellular regions. CONCLUSIONS: The propensity of these AMPs to bind pneumonia pathogens proteins justifies that they would be potential applicant biomarkers for the recognizable detection of these bacterial pathogens in a point-of-care POC pneumonia diagnostics. The high sensitivity, accuracy, and specificity of the AMPs likewise justify the utilization of HMMER in the design and discovery of AMPs for disease diagnostics and therapeutics.

Ecotoxicoproteomic assessment of microplastics and plastic additives in aquatic organisms: A review.

Advances in proteomics have greatly improved chemical toxicity assessment and predictions of adverse outcomes in organisms. Ecotoxicoproteomics has been employed to elucidate biological pathways affected by chemicals and provide data that can be incorporated into adverse outcome pathways (AOP) to better define the ecological risk of emerging pollutants. Microplastics (MPs) and plastic additives have raised global concern due to their widespread use in aquatic environments, bioaccumulation in tissues, and toxic effects in aquatic organisms. Despite showing sublethal toxicity in many cases, mechanisms underlying these emerging pollutants are underexplored. In this review, adverse effects and recent ecotoxicoproteomic studies of MPs and typical additives (i.e. plasticizers, flame retardants, antioxidants, and UV stabilizers) in aquatic organisms are summarized. Proteomics data show that MPs adversely affect ingestion and reproduction via disrupting pathways related to energy metabolism, stress-related defense, and cytoskeletal dynamics. Biological processes including lipid metabolism, energy homeostasis, skeletal development, neurotransmitter signaling, and immune response are modulated by additives and induce developmental malformations in fish embryos/larvae. Furthermore, plastic additives also exert reproductive toxicity, hepatotoxicity, and neurotoxicity in invertebrates (e.g. mussel, abalone, and oyster) and fish by disrupting detoxification/oxidative stress, hormonal modulation, signal transduction, and apoptosis. Additional studies are needed to complement the omic knowledge of chemical additives that are not well documented (e.g. UV stabilizers) for improving understanding into toxic mechanisms and for characterizing ecological risk linked to plastic contaminants.

Integrated Label-Free and 10-Plex DiLeu Isobaric Tag Quantitative Methods for Profiling Changes in the Mouse Hypothalamic Neuropeptidome and Proteome: Assessment of the Impact of the Gut Microbiome.

Gut microbiota can regulate host physiological and pathological status through gut-brain communications or pathways. However, the impact of the gut microbiome on neuropeptides and proteins involved in regulating brain functions and behaviors is still not clearly understood. To address the problem, integrated label-free and 10-plex DiLeu isobaric tag-based quantitative methods were implemented to compare the profiling of neuropeptides and proteins in the hypothalamus of germ-free (GF)- vs conventionally raised (ConvR)-mice. A total of 2943 endogenous peptides from 63 neuropeptide precursors and 3971 proteins in the mouse hypothalamus were identified. Among these 368 significantly changed peptides (fold changes over 1.5 and a p-value of <0.05), 73.6% of the peptides showed higher levels in GF-mice than in ConvR-mice, and 26.4% of the peptides had higher levels in ConvR-mice than in GF-mice. These peptides were mainly from secretogranin-2, phosphatidylethanolamine-binding protein-1, ProSAAS, and proenkephalin-A. A quantitative proteomic analysis employing DiLeu isobaric tags revealed that 282 proteins were significantly up- or down-regulated (fold changes over 1.2 and a p-value of <0.05) among the 3277 quantified proteins. These neuropeptides and proteins were mainly involved in regulating behaviors, transmitter release, signaling pathways, and synapses. Interestingly, pathways including long-term potentiation, long-term depression, and circadian entrainment were involved. In the present study, a combined label-free and 10-plex DiLeu-based quantitative method enabled a comprehensive profiling of gut microbiome-induced dynamic changes of neuropeptides and proteins in the hypothalamus, suggesting that the gut microbiome might mediate a range of behavioral changes, brain development, and learning and memory through these neuropeptides and proteins.

Harnessing the Secretome of Mesenchymal Stromal Cells for Traumatic Spinal Cord Injury: Multicell Comparison and Assessment of In Vivo Efficacy.

Cell therapy offers significant promise for traumatic spinal cord injury (SCI), which despite many medical advances, has limited treatment strategies. Able to address the multifactorial and dynamic pathophysiology of SCI, cells present various advantages over standard pharmacological approaches. However, the use of live cells is also severely hampered by logistical and practical considerations. These include specialized equipment and expertise, standardization of cell stocks, sustained cell viability post-thawing, and cryopreservation-induced delayed-onset cell death. For this reason, we suggest a novel and clinically translatable alternative to live-cell systemic infusion, which retains the efficacy of the latter while overcoming many of its limitations. This strategy involves the administration of concentrated cell secretome and exploits the trophic mechanism by which stromal cells function. In this study, we compare the efficacy of intravenously delivered concentrated conditioned media (CM) from human umbilical cord matrix cells (HUCMCs), bone marrow mesenchymal stromal cells, as well as newborn and adult fibroblasts in a rat model of moderately severe cervical clip compression/contusion injury (C7--T1, 35 g). This is further paired with a thorough profile of the CM cytokines, chemokines, and angiogenic factors. The HUCMC-derived CM was most effective at limiting acute (48 h post-SCI) vascular pathology, specifically lesion volume, and functional vascularity. Principle component analysis (PCA), hierarchical clustering, and interaction analysis of proteins highly expressed in the HUCMC secretome suggest involvement of the MAPK/ERK, JAK/STAT, and immune cell migratory pathways. This "secretotherapeutic" strategy represents a novel and minimally invasive method to target multiple organ systems and several pathologies shortly after traumatic SCI.