Pain after surgery is of major perioperative concern because it is associated with substantial complications, including chronic post-surgical pain (CPSP) development. The CPSP incidence is high, and its accurate prediction or prevention has been so far unsuccessful. Based on experimental studies in healthy volunteers, we hypothesised that pre-surgical plasma proteome data and multi-feature discriminant modelling can improve the accuracy of predicting susceptibility versus resilience to CPSP. To test this, we conducted a proof-of-concept case-control study: thirty-two female surgical patients undergoing either open hysterectomy or thoracotomy were stratified by CPSP presence three months post-surgery. Preoperative blood samples were analysed by unbiased deep proteomics to identify plasma proteins associated with phenotypes of CPSP susceptibility vs resilience. These were then integrated with pre-surgical psychosocial factors to develop discriminative models. Among 684 identified plasma proteins, 106 turned out to be discriminatory for the CPSP-susceptible and 104 for the CPSP-resilient phenotype. At postoperative month 3, physical dysfunction, anxiety, and depression were significantly higher in CPSP-susceptible patients. The addition of proteomic data to the model improved the accuracy of phenotype discrimination in internal cross-validation when compared to psychosocial and neurocognitive factors alone. Protein network analysis was consistent with the hypothesis that pre-surgical immune and complement activation may be associated with CPSP risk. Furthermore, computational drug repositioning suggested candidate molecular targets potentially relevant to modulating the CPSP risk profile. Overall, our results illustrate the feasibility and potential utility of multimodal datasets to discriminate between CPSP phenotypes. When combined with network based analysis and drug repositioning this approach may open new avenues for identifying drug targets and personalized mitigation of CPSP in the future.

Background Early-life development of the gut microbiome plays a critical role in shaping host physiology. However, a comprehensive understanding of how diet, microbial community assembly, functional capacity, and host intestinal maturation axes evolve and coordinate over time remains lacking. Most studies focus on a single axis, rely on cross-sectional sampling, or have limited functional resolution, restricting insight into developmental dynamics. Here, we characterized early-life maturation of the gut ecosystem using longitudinal, metaproteome-level analysis in a murine model. Results Using ultra-sensitive metaproteomics, we profiled fecal samples collected at seven postnatal time points from day 10 through weaning and into early adulthood (day 48) in pups from two contemporaneously raised C57BL/6 cohorts differing only in maternal origin (a long-established local colony and newly purchased pregnant females from the same vendor). Analyses accounted for time, cohort, and sex effects. Microbial communities underwent pronounced taxonomic turnover, shifting from early dominance by facultative anaerobes to obligate anaerobes after weaning, accompanied by increasing species richness and functional complexity across cohorts and sexes. Taxonomic changes supported increasing functional redundancy that converged by postnatal day 34 and remained stable into early adulthood. KEGG clustering showed this redundancy to be driven by coordinated upregulation of distinct metabolic pathways alongside maintenance of core functions. Direct detection of low-abundant dietary proteins provided evidence for dietary transitions coinciding with microbial maturation: milk proteins were detected only before weaning, while solid food components predominated afterward. Maternal origin significantly influenced microbial engraftment trajectories, leading to cohort-specific taxonomic and functional differences despite identical housing and diet. In parallel, host intestinal proteome maturation mirrored microbial succession, with coordinated shifts in metabolic, absorptive, regulatory, and effector pathways, including antimicrobial peptides and carbohydrate-modifying enzymes. Conclusions By directly integrating microbial, dietary, functional, and host axes within a longitudinal framework, this study provides a comprehensive view of murine gut ecosystem maturation during early life and offers a reference for interpreting developmental microbiome dynamics and improving experimental design and reproducibility in mouse studies.

Diabetic painful neuropathy (DPN) is characterized by neuropathic pain accompanied by loss of sensory function. We hypothesized that neurodegeneration in the dorsal root ganglion (DRG) could underlie DPN progression. To address this question, we performed multi-omic evaluation on DRGs from otherwise healthy organ donors, donors with diabetes but no neuropathy, and donors with clinically diagnosed DPN. We discovered that the first stages of neurodegeneration begin early in diabetes before the onset of DPN, with Nageotte nodule formation accompanied by apoptotic gene expression and decreased proportion of specific populations of A-fibers in DPN with remodeling of non-neuronal cells. Our findings define DPN as a neurodegenerative disorder of the DRG, identify molecular markers of disease stage, and highlight the need for early intervention to prevent irreversible neurodegeneration.

Abstract Metaproteomics measures functional expression in complex microbial communities, but extreme sample complexity and dynamic range challenge acquisition strategies. Trapped ion mobility spectrometry with parallel accumulation–serial fragmentation (PASEF) has expanded into multiple acquisition modes, yet systematic evaluations in high-complexity metaproteomes remain limited. Here, we benchmark five PASEF modes—DDA-, DIA-, Slice-, Synchro-, and midia-PASEF—using a complex fecal peptide background spiked with defined bacterial references. Across three gradients and input levels, 540 LC–MS acquisitions are analyzed under matched conditions. Based on data-derived performance scores, DIA-based strategies outperform DDA-PASEF in peptide and protein coverage, particularly for low-abundance microbial features. DIA- and Slice-PASEF show strong quantitative reproducibility, reduced ratio compression, and consistent species-abundance scaling, while functional profiling reveals expanded annotation depth. When tested in a murine colonic injury model, the two highest-scoring methods, DIA- and Slice-PASEF, capture concordant host and microbial responses.

Introduction Understanding the molecular architecture of peripheral sensory neurons is critical as we pursue novel drug targets against pain and neuropathy. Sensory neurons in the dorsal root ganglion (DRG) show extensive compartmentalization; thus, understanding each compartment-from the peripheral to central terminals-is key to this effort.Methods To systematically profile this spatial complexity, we generated a TurboIDfl/fl transgenic mouse line (ROSA26em1(TurboID)Bros), enabling targeted proximity labelling and deep proteomic profiling of DRG neuron compartments via Tg(Advillin-Cre)+.Results Our data reveal distinct proteomic signatures across neuronal compartments that reflect specialized neuronal functions. We provide proteomic insights into previously inaccessible nerve terminals both in the periphery (innervating the skin) and in the spinal cord. Further, using a DRG explant model of chemotherapy-induced peripheral neuropathy, we uncover novel and discrete proteome changes, highlighting neuronal vulnerability.Conclusion Together, our findings provide a unique proteome atlas of the sensory neuron proteome across anatomical domains and demonstrate the utility of proximity labelling proteomics for detecting compartment-specific molecular alterations in a disease model.Significance This study highlights the potential of TurboID-based proteomics to uncover cell type-specific differences in the peripheral nervous system, serving as a valuable resource for mechanistic studies of sensory neuron function and pathology.

Evodiamine (EVO) is a natural product found in Tetradium ruticarpum. It inhibits vascular smooth muscle cell (VSMC) proliferation, a key mechanism in the pathogenesis of atherosclerosis and restenosis. This study characterizes the mechanism of action behind the antiproliferative activity of evodiamine in platelet derived growth factor (PDGF)-activated VSMC. We confirmed the antiproliferative activity of EVO (0.3 and 1 µmol/L) in cultured primary VSMC by resazurin conversion and bromo-deoxyuridine (BrdU) incorporation assays, respectively, and its ability to arrest VSMC in G2/M by flow cytometric cell cycle analysis. Annexin V- Fluorescein Isothiocyanate (FITC)/propidium iodide (PI) staining and western blot analysis of caspase-3 cleavage detected low levels of apoptosis in response to 3 µmol/L EVO. We demonstrate that EVO (3 µmol/L) induces mitotic catastrophe (MC), as evidenced by characteristic nuclear morphology observed by confocal microscopy and polyploidy detected by flow cytometric DNA content analysis. Mechanistically, we rule out DNA damage as a cause of MC by western blot analysis of phospho-Ser139 histone H2A.X (γH2A.X). Instead, EVO induces centrosome amplification involving polo-like kinase 4 (PLK4) signaling. This is evident in cells co-treated with EVO (3 µmol/L) and the PLK4 inhibitor centrinone B (CENB) at 125 nmol/L by blunted centrosome amplification and cell cycle arrest. The study concludes with a proteomic analysis of purified centrosomes, which identifies candidates involved in this mechanism. In conclusion, evodiamine induces mitotic catastrophe via centrosome amplification in VSMC, positioning it as an antiproliferative agent with a distinct mechanism.

Our understanding of how sex and age influence chronic pain at the molecular level is still limited with wide-reaching consequences for adolescent patients. Here, we leveraged deep proteome profiling of mouse dorsal root ganglia (DRG) from adolescent (4-week-old) and adult (12-week-old) male and female mice to investigate the establishment of neuropathic pain in the spared nerve injury (SNI)-model in parallel. We quantified over 12,000 proteins, including notable ion channels involved in pain, highlighting the sensitivity of our approach. Differential expression revealed sex- and age-dependent proteome changes upon nerve injury. In contrast to most previous studies, our comprehensive dataset enabled us to determine differentially expressed proteins (DEPs), which were shared between male and female mice of both age groups. Among these, the vast majority (94%) were also expressed and, in part, altered in human DRG of neuropathic pain patients, indicating evolutionary conservation. Proteome signatures represented numerous targets of FDA-approved drugs comprising both (i) known pain therapeutics (e.g. Pregabalin and opioids) and, importantly, (ii) compounds with high potential for future re-purposing, e.g. Ptprc-modulators and Epoetins. Protein network and multidimensional analysis uncovered distinct hubs of sex- and age-shared biological pathways impacted by neuropathic pain, such as neuronal activity and synaptic function, DNA-damage, and neuroimmune interactions. Taken together, our results capture the complexity of nerve injury-associated DRG alterations in mice at the network level, moving beyond single-candidate studies. Consequently, we provide an innovative resource of the molecular landscape of neuropathic pain, enabling novel opportunities for translational pain research and network-based drug discovery.

Post-operative pain management is crucial, yet remains a global healthcare challenge with many patients suffering from unexpectedly severe acute pain, leading to impaired recovery and chronic pain. Post-operative pain models are useful for research and intervention development. However, there is substantial variability in design, reporting, and translational relevance. To provide an integrated map that links preclinical model choice, outcome domains, and methodological safeguards to clinical relevance, we conducted a systematic review and quantitative trend-analysis. We evaluated models, outcomes, methodologies, study details, quality, reporting, and patterns in relation to perioperative domains. Screening of 7519 records identified 674 studies, which were analyzed for methodological quality, risk of bias, and reporting trends. Incision models dominated, while procedure-specific models accounted for 14 %. Sex bias was evident, with 83 % of studies using only males and limited justification for single-sex studies. Most pain-related behavior assessments were mechanical (87 %), with non-evoked (24 %) and movement-evoked (5 %) less utilized. The majority used fewer assessments, but 17 % used three or more outcomes. Methodological rigor remains limited, with randomization and blinding reported in just over half of studies, and sample size calculations in only 18 %. Critical details such as housing enrichment or experimenter sex were rarely reported. Together, these patterns motivate a minimum translational set for further studies: combine different behavioural outcomes aligned to perioperative domains, include both sexes or justify single-sex designs, and predefine and transparently report perioperative regimens alongside randomization, blinding, and sample-size planning. We advocate for these changes to improve translational research in this field.

The peripheral nervous system (PNS) plays a critical role in pathological conditions, including chronic pain disorders, that manifest differently in men and women. To investigate this sexual dimorphism at the molecular level, we integrated quantitative proteomic profiling of human dorsal root ganglia (hDRG) and peripheral nerve tissue into the expanding omics framework of the PNS. Using data-independent acquisition (DIA) mass spectrometry, we characterized a comprehensive proteomic profile, validating tissue-specific differences between the hDRG and peripheral nerve. Through multi-omic analyses and in vitro functional assays, we identified sex-specific molecular differences, with TNFα signalling emerging as a key sexually dimorphic pathway with higher prominence in men. Genetic evidence from genome-wide association studies further supports the functional relevance of TNFα signalling in the periphery, while clinical trial data and meta-analyses indicate a sex-dependent response to TNFα inhibitors. Collectively, these findings underscore a functionally sexual dimorphism in the PNS, with direct implications for sensory and pain-related clinical translation.

The functional characterization of host-gut microbiome interactions remains limited by the sensitivity of current metaproteomic approaches. Here, we present uMetaP, an ultra-sensitive workflow combining advanced LC-MS technologies with an FDR-validated de novo sequencing strategy, novoMP. uMetaP markedly expands functional coverage and improves the taxonomic detection limit of the gut dark metaproteome by 5000-fold, enabling precise detection and quantification of low-abundance microbial and host proteins. Applied to a mouse model of intestinal injury, uMetaP revealed host-microbiome functional networks underlying tissue damage, beyond genomic findings. Orthogonal validation using transcriptomic data from Crohn's disease patients confirmed key host protein alterations. Furthermore, we introduce the concept of a druggable metaproteome, mapping functional targets within the host and microbiota. By redefining the sensitivity limits of metaproteomics, uMetaP provides a highly valuable framework for advancing microbiome research and developing therapeutic strategies for microbiome-related diseases.

Progressive neurological decline in multiple sclerosis is associated with axonal loss and synaptic dysfunction in the non-demyelinated normal appearing gray matter (NAGM) and prominently in the cerebellum. In contrast to early disease stages, where synaptic and neuro-axonal pathology correlates with the extent of T cell infiltration, a prominent role of the innate immune system has been proposed for progressive MS. However, the specific contribution of microglia and astrocytes to synaptic cerebellar pathology in the NAGM- independent of an adaptive T cell response - remains largely unexplored. In the present study, we quantified synaptic changes in the cerebellar NAGM distant from demyelinated lesions in a mouse model of toxic demyelination. Proteomic analysis of the cerebellar cortex revealed differential regulation of synaptic and glutamate transport proteins in the absence of evident structural synaptic pathology or local gray matter demyelination. At the functional level, synaptic changes manifested as a reduction in frequency-dependent facilitation at the parallel fiber- Purkinje cell synapse. Further, deficiency of MyD88, an adaptor protein of the innate immune response, associated with a functional recovery in facilitation, reduced changes in the differential expression of synaptic and glutamate transport proteins, and reduced transcription levels of inflammatory cytokines. Nevertheless, the characteristics of demyelinating lesions and their associated cellular response were similar to wild type animals. Our work brings forward an experimental paradigm mimicking the diffuse synaptic pathology independent of demyelination in late stage MS and highlights the complex regulation of synaptic pathology in the cerebellar NAGM. Moreover, our findings suggest a role of astrocytes, in particular Bergmann glia, as key cellular determinants of cerebellar synaptic dysfunction.

Peripheral nerves drive movement and sensation but are highly vulnerable to injury, making them critical sites in the development of neuropathic pain. Nerve trauma initiates profound plasticity, yet the molecular programs driving both early and persistent axonal remodeling remain poorly understood. Here, we present a uniquely longitudinal proteomic perspective on injured sciatic nerve fibers, spanning acute (7-14 days) to chronic (98 days) stages in the mouse spared nerve injury (SNI)-model of neuropathic pain. Given the importance of demographic diversity in pain research, we compared male and female mice at adolescent and adult stages. Using MEFISTO (MEssage FInding for Spatio-Temporal Ordering), a time-aware latent factor model, we resolved complex proteome trajectories and identified temporal patterns of injury-induced axonal reorganization. Notably, we observed sex- and age-biased differences in immune and neuronal pathways. Despite comparable pain behaviors, these molecular distinctions suggest heterogeneity of nerve injury-induced molecular changes. In parallel, a robust sex-shared injury response emerged, characterized by early neuronal injury/repair, sustained metabolic and immune reprogramming and late structural and transcriptional remodeling. Many dozens of identified proteome alterations match transcriptome changes in nerves from human patients with neuropathy highlighting the translational relevance of our data. In summary, we provide a demographically inclusive, temporally resolved resource that advances our understanding of long-term peripheral nerve remodeling. By bridging early and late injury phases our findings provide a framework for mechanistic translational research and identifying therapeutic targets relevant to nerve injury and associated neuropathic pain.

A significant number of patients develop chronic pain after surgery, but prediction of those who are at risk is currently not possible. Thus, prognostic prediction models that include bio-psycho-social and physiological factors in line with the complex nature of chronic pain would be urgently required. Here, we performed a translational study in male volunteers before and after an experimental incision injury. We determined multi-modal features ranging from pain characteristics and psychological questionnaires to blood plasma proteomics. Outcome measures included pain intensity ratings and the extent of the area of hyperalgesia to mechanical stimuli surrounding the incision, as a proxy of central sensitization. A multi-step logistic regression analysis was performed to predict outcome measures based on feature combinations using data-driven cross-validation and prognostic model development. Phenotype-based stratification resulted in the identification of low and high responders for both outcome measures. Regression analysis revealed prognostic proteomic, specific psychophysical, and psychological features. A combinatorial set of distinct features enabled us to predict outcome measures with increased accuracy compared to using single features. Remarkably, in high responders, protein network analysis suggested a protein signature characteristic of low-grade inflammation. Alongside, in silico drug repurposing highlighted potential treatment options employing antidiabetic and anti-inflammatory drugs. Taken together, we present here an integrated pipeline that harnesses bio-psycho-physiological data for prognostic prediction in a translational approach. This pipeline opens new avenues for clinical application with the goal of stratifying patients and identifying potential new targets, as well as mechanistic correlates, for postsurgical pain.

In this protocol, we describe how to perform bulk proteomics on frozen human dorsal root ganglia (hDRG) tissue from donors from tissue preparation to data-independent acquisition mass spectrometry (DIA-MS).

Metaproteomics uniquely characterizes host-microbiome interactions. However, most species detected by metagenomics remain hidden to metaproteomics due to sensitivity limits. We present a novel ultra-sensitive metaproteomic solution (uMetaP) that, for the first time, reaches full-length 16S rRNA taxonomic depth and can simultaneously decipher functional features. Querying the mouse gut microbiome, uMetaP achieved unprecedented performance in key metrics like protein groups (47925) alongside taxonomic (220 species) and functional annotations (223 KEGG pathways)-all within 30-min analysis time and with high reproducibility, sensitivity, and quantitative precision. uMetaP revealed previously unidentified proteins of unknown functions, small proteins, and potentially new natural antibiotics. Leveraging the extreme sensitivity of uMetaP and SILAC-labelled bacteria, we revealed the true limit of detection and quantification for the “dark” metaproteome of the mouse gut. Moreover, using a two-bacteria proteome mix, we demonstrated single-bacterium resolution (500 fg) with exceptional quantification precision and accuracy. From deciphering the interplay of billions of microorganisms with the host to exploring microbial heterogeneity, uMetaP represents a quantum leap in metaproteomics. Taken together, uMetaP will open new avenues for our understanding of the microbial world and its connection to health and disease.### Competing Interest StatementD.G.V, F.X., M.B, R. K., and M.S. declare no competing financial interest. C.K is an employee of Bruker Daltonics GmbH & Co. KG.

Personalized strategies in pain management and prevention should be based on individual risk factors as early as possible, but the factors most relevant are not yet known. An innovative approach would be to integrate multi-modal risk factors, including blood proteomics, in predicting high pain responders and using them as targets for personalized treatment options. Here, we determined and mapped multi-modal factors to prognosticate a phenotype with high risk of developing pain and hyperalgesia after an experimental incision in humans. We profiled unbiased blood plasma proteome signature of 26 male volunteers, assessed psychophysical and psychological aspects before incision injury. Outcome measures were pain intensity ratings and the extent of the area of hyperalgesia to mechanical stimuli surrounding the incision as a proxy for central sensitization. Phenotype-based stratification resulted in the identification of low- and high-responders for the two different outcome measures. Logistic regression analysis revealed prognostic potential for blood plasma proteins and for psychophysical and psychological parameters. The combination of certain parameters increased the prognostic accuracy for both outcome measures, exceeding 97%. In high-responders, term-term-interaction network analysis showed a proteome signature of a low-grade inflammation reaction. Intriguingly, in silico drug repurposing indicates a high potential for specific antidiabetic and anti-inflammatory drugs already available. In conclusion, we show an integrated pipeline that provides a valuable resource for patient stratification and the identification of (i) multi-feature prognostic models, (ii) treatment targets, and (iii) mechanistic correlates that may be relevant for individualized management of pain and its long-term consequences. ### Competing Interest Statement MS received research awards and travel support by the German Pain Society (DGSS) both of which were sponsored by Astellas Pharma GmbH (Germany). MS received one-time consulting honoraria by Grunenthal GmbH (Germany). None of these funding sources influenced the content of this study, and MS declares no conflict of interest. During the past 5 yr, EPZ received financial support from Grunenthal for research activities and from Grunenthal, Novartis (Switzerland), Medtronic for advisory board activities, lecture fees, or both. None of this research support/funds was used for or influenced this manuscript, and EPZ declares no conflict of interest. The remaining authors declare that they have no conflicts of interest. ### Clinical Trial DRKS00016641 ### Funding Statement Funding: Deutsche Forschungsgemeinschaft (DFG) (SCHM 2533/6e1 and SCHM 2533/4e1 to MS, PO1319/3e1 to EPZ). Federal Ministry of Education and Research (BMBF), Germany, to EPZ (01KC1903). University of Vienna to MS. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: University Hospital Muenster of the local Ethics Committee of the Medical Faculty (registration no 2018-081-b-S) I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors

Mitochondrial dysfunction is associated with inflammatory bowel diseases (IBDs). To understand how microbial-metabolic circuits contribute to intestinal injury, we disrupt mitochondrial function in the epithelium by deleting the mitochondrial chaperone, heat shock protein 60 (Hsp60Δ/ΔIEC). This metabolic perturbation causes self-resolving tissue injury. Regeneration is disrupted in the absence of the aryl hydrocarbon receptor (Hsp60Δ/ΔIEC;AhR-/-) involved in intestinal homeostasis or inflammatory regulator interleukin (IL)-10 (Hsp60Δ/ΔIEC;Il10-/-), causing IBD-like pathology. Injury is absent in the distal colon of germ-free (GF) Hsp60Δ/ΔIEC mice, highlighting bacterial control of metabolic injury. Colonizing GF Hsp60Δ/ΔIEC mice with the synthetic community OMM12 reveals expansion of metabolically flexible Bacteroides, and B. caecimuris mono-colonization recapitulates the injury. Transcriptional profiling of the metabolically impaired epithelium reveals gene signatures involved in oxidative stress (Ido1, Nos2, Duox2). These signatures are observed in samples from Crohn's disease patients, distinguishing active from inactive inflammation. Thus, mitochondrial perturbation of the epithelium causes microbiota-dependent injury with discriminative inflammatory gene profiles relevant for IBD.

IntroductionMetaproteomics is a rapidly advancing field that offers unique insights into the taxonomic composition and the functional activity of microbial communities, and their effects on host physiology. Classically, data-dependent acquisition (DDA) mass spectrometry (MS) has been applied for peptide identification and quantification in metaproteomics. However, DDA-MS exhibits well-known limitations in terms of depth, sensitivity, and reproducibility. Consequently, methodological improvements are required to better characterize the protein landscape of microbiomes and their interactions with the host.MethodsWe present an optimized proteomic workflow that utilizes the information captured by Parallel Accumulation-Serial Fragmentation (PASEF) MS for comprehensive metaproteomic studies in complex fecal samples of mice.Results and discussionWe show that implementing PASEF using a DDA acquisition scheme (DDA-PASEF) increased peptide quantification up to 5 times and reached higher accuracy and reproducibility compared to previously published classical DDA and data-independent acquisition (DIA) methods. Furthermore, we demonstrate that the combination of DIA, PASEF, and neuronal-network-based data analysis, was superior to DDA-PASEF in all mentioned parameters. Importantly, DIA-PASEF expanded the dynamic range towards low-abundant proteins and it doubled the quantification of proteins with unknown or uncharacterized functions. Compared to previous classical DDA metaproteomic studies, DIA-PASEF resulted in the quantification of up to 4 times more taxonomic units using 16 times less injected peptides and 4 times shorter chromatography gradients. Moreover, 131 additional functional pathways distributed across more and even uniquely identified taxa were profiled as revealed by a peptide-centric taxonomic-functional analysis. We tested our workflow on a validated preclinical mouse model of neuropathic pain to assess longitudinal changes in host-gut microbiome interactions associated with pain - an unexplored topic for metaproteomics. We uncovered the significant enrichment of two bacterial classes upon pain, and, in addition, the upregulation of metabolic activities previously linked to chronic pain as well as various hitherto unknown ones. Furthermore, our data revealed pain-associated dynamics of proteome complexes implicated in the crosstalk between the host immune system and the gut microbiome. In conclusion, the DIA-PASEF metaproteomic workflow presented here provides a stepping stone towards a deeper understanding of microbial ecosystems across the breadth of biomedical and biotechnological fields.

BACKGROUND:Acute pain after surgery is common and often leads to chronic post-surgical pain, but neither treatment nor prevention is currently sufficient. We hypothesised that specific protein networks (protein-protein interactions) are relevant for pain after surgery in humans and mice.METHODS:Standardised surgical incisions were performed in male human volunteers and male mice. Quantitative and qualitative sensory phenotyping were combined with unbiased quantitative mass spectrometry-based proteomics and protein network theory. The primary outcomes were skin protein signature changes in humans and phenotype-specific protein-protein interaction analysis 24 h after incision. Secondary outcomes were interspecies comparison of protein regulation as well as protein-protein interactions after incision and validation of selected proteins in human skin by immunofluorescence.RESULTS:Skin biopsies in 21 human volunteers revealed 119/1569 regulated proteins 24 h after incision. Protein-protein interaction analysis delineated remarkable differences between subjects with small (low responders, n=12) and large incision-related hyperalgesic areas (high responders, n=7), a phenotype most predictive of developing chronic post-surgical pain. Whereas low responders predominantly showed an anti-inflammatory protein signature, high responders exhibited signatures associated with a distinct proteolytic environment and persistent inflammation. Compared to humans, skin biopsies in mice habored even more regulated proteins (435/1871) 24 h after incision with limited overlap between species as assessed by proteome dynamics and PPI. Immunohistochemistry confirmed the expression of high priority candidates in human skin biopsies.CONCLUSIONS:Proteome profiling of human skin after incision revealed protein-protein interactions correlated with pain and hyperalgesia, which may be of potential significance for preventing chronic post-surgical pain. Importantly, protein-protein interactions were differentially modulated in mice compared to humans opening new avenues for successful translational research.

Metaproteomics is gaining momentum in microbiome research due to the multi-dimensional information it provides. However, current approaches have reached their detection limits. We present a highly-sensitive metaproteomic workflow using the extra information captured by Parallel Accumulation-Serial Fragmentation (PASEF) technology. The comparison of different acquisition modes and data analysis software packages showed that DIA-PASEF and DIA-NN doubled protein identifications of mouse gut microbiota and, importantly, also of the host proteome. DIA-PASEF significantly improved peptide detection reproducibility and quantification accuracy, which resulted in more than twofold identified taxa, reaching depths comparable to metagenomic studies. Consequently, DIA-PASEF exhibited improved coverage of functional networks revealing 131 additional pathways compared to DDA-PASEF. We applied our optimized workflow to a pre-clinical mouse model of chronic pain, in which we deciphered novel host-microbiome interactions. In summary, we present here a metaproteomic approach that paves the way for increasing the functional characterization of microbiome ecosystems and is applicable to diverse fields of biological research.