Proteomic Data Research Articles

MARLOWE: An Untargeted Proteomics, Statistical Approach to Taxonomic Classification for Forensics.

General proteomics research for fundamental science typically addresses laboratory- or patient-derived samples of known origin and composition. However, in a few research areas, such as environmental proteomics, clinical identification of infectious organisms, archeology, art/cultural history, and forensics, attributing the origin of a protein-containing sample to the organisms that produced it is a central focus. A small number of groups have approached this problem and developed software tools for taxonomic characterization and/or identification using bottom-up proteomics. Most such tools identify peptides via database search, and many rely on organism-specific peptides as markers. Our group recently introduced MARLOWE, a software tool for taxonomic characterization of unknown samples based on de novo peptide identification and signal-erosion-resistant strong peptides, which are shared peptides distributed in a taxonomy-dependent manner. In the current work, we further characterize the utility of MARLOWE using publicly available proteomics data from forensically-relevant samples. MARLOWE characterizes samples based on their protein profile, and returns ranked organism lists of potential contributors and taxonomic scores based on shared strong peptides between organisms. Overall, the correct characterization rate ranges between 44 and 100%, depending on the sample type and data acquisition parameters (with lower numbers associated with lower-quality data sets). MARLOWE demonstrates successful characterization of true contributors and close relatives, and provides sufficient specificity to distinguish certain microbial species. MARLOWE demonstrates its ability to provide insight into potential taxonomic sources for a wide range of sample types without prior assumptions about sample contents. This approach can find utility in forensic science and also broadly in bioanalytical applications that utilize proteomics approaches for taxonomic characterization.

Peripheral Transcriptomics in Acute and Long-Term Kidney Dysfunction in SARS-CoV2 Infection.

Acute kidney injury (AKI) is common in SARS-CoV-2 infection and COVID-19, often leading to long-term kidney dysfunction. However, the transcriptomic features of AKI severity and its long-term effects are underexplored. We performed bulk RNA sequencing on peripheral blood mononuclear cells (PBMCs) from hospitalized SARS-CoV-2 patients and complemented these findings with proteomic data from the same cohort. We compared the functional enrichment findings with historical sepsis-AKI data and subsequently examined the association between molecular signatures and long-term kidney function changes. In 283 patients, 57 had mild AKI (stage 1) and 49 had severe AKI (stage 2 or 3). Following adjustments for age, sex, severity of infection, and pre-existing chronic kidney disease (CKD), we identified 6,432 differentially expressed genes (DEGs) in the severe AKI vs. control comparison, 840 in the mild AKI vs. control, and 1,213 in the severe vs. mild AKI comparison (FDR<0.05). Common pathways included unfolded protein response, cellular response to stress via eIF2, and IFN-g-mediated inflammatory response. Severe AKI was linked to pathways involved in mitochondrial dysfunction and endoplasmic reticulum stress. Proteomic analysis confirmed 40 established AKI and inflammation biomarkers, while gene-set enrichment of transcription regulators revealed additional biomarkers for severe AKI. Comparison with PBMC transcriptomics from sepsis-related AKI showed significant functional overlap (30%). Analysis of post-discharge eGFR data in 115 patients identified 177 DEGs for severe vs. control, 106 for mild vs. control, and 46 for severe vs. mild AKI. Key associations included kidney function decline related to carbohydrate and mitochondrial metabolism, inflammatory-response, and cardiovascular regulation. We demonstrate that severe AKI in SARS-CoV-2 infection is linked to mitochondrial dysfunction and ER stress. The functional overlap with sepsis-AKI suggests potential broader therapeutic applicability. Long-term kidney dysfunction is influenced by disruptions in cellular energy metabolism and immune response.

Proteome-Wide Mendelian Randomization Identifies Therapeutic Targets for Abdominal Aortic Aneurysm.

The proteome is a key source of therapeutic targets. We conducted a comprehensive Mendelian randomization analysis across the proteome to identify potential protein markers and therapeutic targets for abdominal aortic aneurysm (AAA). Our study used plasma proteomics data from the UK Biobank, comprising 2923 proteins from 54 219 individuals, and from deCODE Genetics, which measured 4907 proteins across 35 559 individuals. Significant proteomic quantitative trait loci were used as instruments for Mendelian randomization. Genetic associations with AAA were sourced from the AAAgen consortium, a large-scale genome-wide association study meta-analysis involving 37 214 cases and 1 086 107 controls, and the FinnGen study, which included 3869 cases and 381 977 controls. Sequential analyses of colocalization and summary-data-based Mendelian randomization were performed to verify the causal roles of candidate proteins. Additionally, single-cell expression analysis, protein-protein interaction network analysis, pathway enrichment analysis, and druggability assessments were conducted to identify cell types with enriched expression and prioritize potential therapeutic targets. The proteome-wide Mendelian randomization analysis identified 34 proteins associated with AAA risk. Among them, 2 proteins, COL6A3 and PRKD2, were highlighted by colocalization analysis, summary-data-based Mendelian randomization, and the heterogeneity in an independent instrument test, providing the most convincing evidence. These protein-coding genes are primarily expressed in macrophages, smooth muscle cells, and mast cells within abdominal aortic aneurysm tissue. Several causal proteins are involved in pathways regulating lipid metabolism, immune responses, and extracellular matrix organization. Nine proteins have already been targeted for drug development in diabetes and other cardiovascular diseases, presenting opportunities for repurposing as AAA therapeutic targets. This study identifies causal proteins for AAA, enhancing our understanding of its molecular cause and advancing the development of therapeutics.

Microbial reaction rate estimation using proteins and proteomes.

Microbes transform their environments using diverse enzymatic reactions. However, it remains challenging to measure microbial reaction rates in natural environments. Despite advances in global quantification of enzyme abundances, the individual relationships between enzyme abundances and their reaction rates have not been systematically examined. Using matched proteomic and reaction rate data from microbial cultures, we show that enzyme abundance is often insufficient to predict its corresponding reaction rate. However, we discovered that global proteomic measurements can be used to make accurate rate predictions of individual reaction rates (median R2 = 0.78). Accurate rate predictions required only a small number of proteins and they did not need explicit prior mechanistic knowledge or environmental context. These results indicate that proteomes are encoders of cellular reaction rates, potentially enabling proteomic measurements in situ to estimate the rates of microbially mediated reactions in natural systems.

Abstract 15: Integrated Genomic and Proteomic Drug Target Discovery for Ischemic Stroke

Background: Ischemic stroke (IS) is a multifactorial disease with a significant genetic component contributing about 40% of the risk. Current prevention strategies focus on risk factor control, but integrating genomic and proteomic data could uncover key molecular targets for more effective treatments based on genetic insights. Objective: To utilize a comprehensive multi-omic approach to identify novel drug targets that mediate the genetic risk of IS. Methods: We analyzed genomic and proteomic data from 53,014 UK Biobank participants. Using a polygenic risk score (PRS) for IS from 43 independent risk variants, we deployed four analytical steps (Fig. 1, all steps corrected for multiple testing): (1) linear regression between PRS and 2,923 standardized protein levels measured at baseline, adjusted for age, sex, and genetic principal components; (2) association between selected proteins and IS; (3) Mendelian Randomization to assess causality for the proteins from (1+2), and (4) mediation to quantify the intermediary role of causal proteins in the PRS-stroke relationship. To provide clinical context, we conducted a proof-of-concept analysis using Alzheimer's disease (AD) given APOE's established role in AD risk. Results: We found 15 proteins that causally mediate the association between polygenic risk and IS (Fig. 2). The identified proteins are involved in cell adhesion (e.g. CD34, CD48, PODXL), inflammatory pathways (e.g. CD28, CD300A, NCR1), angiogenesis (FGF5, MET), and protein glycosylation (GALNT10, GCNT1), influencing vascular integrity, immune response, and blood vessel formation. Mediated effects range from 1-5% per protein and two proteins served as targets for existing or developing drugs (Tab. 1). As proof-of-concept, we discovered five proteins with significant mediation in AD, the strongest effect seen in APOE (10% mediated effect) and MENT (5%), confirming their known roles in neurodegenerative processes. Conclusion: This multi-omic strategy successfully identified 15 proteins mediating polygenic risk of IS, highlighting crucial pathways such as cell adhesion, inflammation, angiogenesis, and glycosylation. These findings can advance targeted therapies for stroke risk in primary prevention. Our proof-of-concept study illustrates the clinical meaning of the proteins in comparison with the known impact of APOE on AD. Future work should focus on validating these targets in clinical settings and exploring drug repurposing opportunities.

Expression pattern and prognostic significance of aldehyde dehydrogenase 2 in lung adenocarcinoma as a potential predictor of immunotherapy efficacy.

The incidence of alcohol-associated cancers is higher within Asian populations having an increased prevalence of an inactivating mutation in aldehyde dehydrogenase 2 (ALDH2), a mitochondrial enzyme required for the clearance of acetaldehyde, a cytotoxic metabolite of ethanol. The role of alcohol consumption in promoting lung cancer is controversial, and little attention has been paid to the association between alcohol drinking and pulmonary ALDH2 expression. We performed a comprehensive bioinformatic analysis of multi-omics data available in public databases to elucidate the role of ALDH2 in lung adenocarcinoma (LUAD). Transcriptional and proteomic data indicate a substantial pulmonary expression of ALDH2, which is functional for the metabolism of alcohol diffused from the bronchial circulation. ALDH2 expression is higher in healthy lung tissue than in LUAD and inhibits cell cycle, apoptosis, and epithelial-mesenchymal transition pathways. Moreover, low ALDH2 mRNA levels predict poor prognosis and low overall survival in LUAD patients. Interestingly, ALDH2 expression correlates with immune infiltration in LUAD. A better understanding of the role of ALDH2 in lung tumor progression and immune infiltration might support its potential use as a prognostic marker and therapeutic target for improving immunotherapeutic response.

Implication of the novel microtubule targeting agent, AUS_001, in pancreatic cancer cellular signaling.

748 Background: Pancreatic cancer (PanCa) is considered a major therapeutic challenge due to its poor prognosis, high mortality rate and resistance to most therapies, underlining the need for new treatment approaches. Our previous investigations revealed that the prenylated hydroxy-stilbene, AUS_001, inhibits β-tubulin polymerization via its unique binding to the colchicine site of tubulin. A cell-based profiling platform identified sensitivity of 12 out of 13 PanCa lines to AUS_001 with a median concentration causing 50% growth inhibition of 0.227µM. The goal of the current study was to elucidate the signaling activity and cellular responses following treatment with AUS_001 and explore the prospect of the latter in PanCa treatment. Methods: A series of functional and biochemical assays were performed to delineate the effect of AUS_001 on the growth, colony formation ability, invasive capacity and oxidative status of PanCa cells. Tumor growth was evaluated in PANC-1 implanted CB.17 SCID mice and MIA PaCa-2 implanted nude mice upon intraperitoneal administration of AUS_001 once weekly. Metabolic profiling was carried out using the Seahorse XF Analyzer. RNA silencing and adenovirus-mediated overexpression of the Dominant-Negative Mutant of c-Jun were employed to explore the link of c-Jun activation and AUS_001-induced cytotoxicity. Results: The potential of AUS_001 to disrupt PanCa cell functions was established in vitro and in vivo . Viability and compromised membrane integrity were multiplexed and resulted in half maximal effective concentration agreement indicating drug-induced cytotoxicity. AUS_001-treated cells underwent apoptosis followed by secondary necrosis, exerted diminished anchorage-independent growth and metastatic potential in vitro . Importantly, tumor growth was significantly reduced in PanCa murine xenograft models by AUS_001 as a monotherapy. Pretreatment with N-acetyl-l-cysteine did not alter cellular sensitivity to AUS_001, suggesting that the time-dependent induction of reactive oxygen species upon AUS_001 exposure is not the primary cause of cytotoxicity. Notably, the oxygen consumption rate, extracellular acidification rate and function of all mitochondrial complexes (I-IV) of live MIA PaCa_2 cells were significantly impaired in both glucose- and galactose-containing media 48h after AUS_001 administration. Integration of transcriptomic and proteomic data originating from AUS_001-challenged cells uncovered the dramatic induction of c-Jun and FosB stress responders. Further studies demonstrated that c-Jun transcriptional activation acts as a partial mediator of AUS_001-induced cytotoxicity. Conclusions: Collectively, our findings provide critical insights into the molecular events triggered by AUS_001 in PanCa cells and serve as supporting data for future exploration of AUS_001 as a novel PanCa therapeutic agent.

Demyelination of the amygdala mediates psychological stress-induced emotional disorders partially contributed by activation of P2X7R/NLRP3 cascade.

Psychological stress can lead to emotional disorders, such as anxiety and depression; however, the underlying mechanisms are complicated and remain unclear. In this study, we established a mouse psychological stress model using an improved communication box, in which the psychologically stressed mice received visual, auditory, and olfactory emotional stimuli from the mice receiving electric foot shock, thus avoiding physical stress interference. After the 14-day psychological stress paradigm, our mice exhibited a significant increase in depressive and anxious behaviors. We then performed proteomic liquid chromatography-tandem mass spectrometry for proteomic data analysis of the amygdala, and the results demonstrated that differentially expressed proteins were more enriched in myelin-related biological processes, cellular components, and molecular functions, indicating a correlation between psychological stress-induced emotional disorders and amygdala myelin damage. Molecular and morphological evidence further confirmed that psychological stress damages myelin ultrastructure, downregulated myelin basic protein and proteolipid protein expression, and reduced oligodendrocyte proliferation in the amygdala. Moreover, clemastine, an antimuscarinic and antihistaminic compound that has been shown to enhance oligodendrocyte differentiation and myelination, rescued depressive behaviors accompanied by increased oligodendrogenesis. In the amygdala, psychological stress was also noted to activate microglia and increase the levels of NOD-like receptor protein 3 (NLRP3) and the proinflammatory cytokines interleukin 1β and tumor necrosis factor α, as indicated by ELISA and Western blot analyses. Moreover, in stressed mice, the administration of Brilliant Blue G, a purinergic ligand-gated ion channel 7 receptor (P2X7R) antagonist, completely reversed the increases in NLRP3 and cleaved caspase-1 levels and partially prevented amygdala myelin damage. In conclusion, amygdala demyelination may mediate psychological stress-induced emotional disorders, and P2X7R/NLRP3 cascade activation partially contributes to amygdala myelin damage after psychological stress.

Abstract WP93: Cross-Platform Proteomics and Machine Learning Algorithms Nominate Biomarkers of Atrial Fibrillation in Stroke Patients: An Exploratory Study

Introduction: Atrial fibrillation (AFib) is a major risk factor for ischemic stroke (IS). AFib diagnosis is critical to optimize secondary prevention and reduce the recurrent stroke risk. Objectives: We undertook an exploratory cross-platform proteomics study to discover plasma biomarkers of AFib diagnosis in patients with IS or transient ischemic attack (TIA). Methods: We used clinical and proteomics data of stroke patients aged ≥18 years lodged within a prospective plasma repository from 2010 to 2014. We collected blood from each patient at hospital admission before administering any therapeutic intervention. Our outcome was differentially expressed levels of proteins in stroke patients with AFib compared to patients without AFib. We performed aptamer-based proteomics using the plasma 7K SomaScan assay. We identified the differentially expressed proteins using (i) ±1.5-fold change and unadjusted p-value &lt;0.05 cut-offs, (ii) Boruta random forest-based machine learning algorithm, and (iii) 30% or more variation explained by AFib in variance partitioning analysis (VPA). We selected the top proteins that were identified using two of the three selection approaches and conducted multivariable adjusted analyses. We conducted internal validation on the same samples using the PeptiQuant Plus biomarker assessment kits (BAK-270) for targeted protein quantitation. Results: We included 60 patients with IS/TIA (mean age 62.9 years, 50% males) classified into 11 AFib and 49 no AFib (Figure 1). SomaScan quantified 7307 protein targets including 6373 unique proteins. We identified 171 differentially expressed proteins in stroke patients with AFib compared to no AFib. After adjusting for age, sex, diabetes, and coronary artery disease in the multivariable analysis, we identified 53 top proteins independently associated with AFib in stroke patients (adjusted p&lt;0.05) (Figure 2). In the validation phase, we quantified 216 proteins using the BAK-270 platform, of which 185 proteins were overlapping with SomaScan. Using BAK-270, we validated increased levels of IGFBP2, B2M, and COL18A1 and decreased levels of CNDP1, AHSG, and SERPINA4 in stroke patients with AFib compared to no AFib (Figure 3). Conclusions: Our exploratory study highlights the potential of plasma proteomics as a valuable tool for discovering protein biomarkers to discriminate IS/TIA patients with AFib compared to no AFib. Further longitudinal studies with adequate sample sizes are needed to support these findings.

Crosstalk Between nNOS/NO and COX-2 Enhances Interferon-Gamma-Stimulated Melanoma Progression

Background/Objectives: Interferon gamma (IFN-γ) in the melanoma tumor microenvironment plays opposing roles, orchestrating both pro-tumorigenic activity and anticancer immune responses. Our previous studies demonstrated the role of neuronal nitric oxide synthase (nNOS) in IFN-γ-stimulated melanoma progression. However, the underlying mechanism has not been well defined. This study determined whether the nNOS/NO and COX-2/PGE2 signaling pathways crosstalk and augment the pro-tumorigenic effects of IFN-γ in melanoma. Methods: Bioinformatic analysis of patient and cellular proteomic data was conducted to identify proteins of interest associated with IFN-γ treatment in melanoma. Changes in protein expression were determined using various analytical techniques including western blot, flow cytometry, and confocal microscopy. The levels of PGE2 and nitric oxide (NO) were analyzed by HPLC chromatography and flow cytometry. In vivo antitumor efficacy was determined utilizing a human melanoma xenograft mouse model. Results: Our omics analyses revealed that the induction of COX-2 was significantly predictive of IFN-γ treatment in melanoma cells. In the presence of IFN-γ, PGE2 further enhanced PD-L1 expression and amplified the induction of nNOS, which increased intracellular NO levels. Cotreatment with celecoxib effectively diminished these changes induced by PGE2. In addition, nNOS blockade using a selective small molecule inhibitor (HH044), efficiently inhibited IFN-γ-induced PGE2 and COX-2 expression levels in melanoma cells. STAT3 inhibitor napabucasin also inhibited COX-2 expression both in the presence and absence of IFN-γ. Furthermore, celecoxib was shown to enhance HH044 cytotoxicity in vitro and effectively inhibit human melanoma tumor growth in vivo. HH044 treatment also significantly reduced tumor PGE2 levels in vivo. Conclusions: Our study demonstrates the positive feedback loop linking nNOS-mediated NO signaling to the COX-2/PGE2 signaling axis in melanoma, which further potentiates the pro-tumorigenic activity of IFN-γ.

Exploring the role of circulating proteins in multiple myeloma risk: a Mendelian randomization study

Multiple myeloma (MM) is an incurable blood cancer with unclear aetiology. Proteomics is a valuable tool in exploring mechanisms of disease. We investigated the causal relationship between circulating proteins and MM risk, using two of the largest cohorts with proteomics data to-date. We performed bidirectional two-sample Mendelian randomization (MR; forward MR = causal effect estimation of proteins and MM risk; reverse MR = causal effect estimation of MM risk and proteins). Summary statistics for plasma proteins were obtained from genome-wide association studies performed using SomaLogic (N = 35,559; deCODE) and Olink (N = 34,557; UK Biobank; UKB) proteomic platforms and for MM risk from a meta-analysis of UKB and FinnGen (case = 1649; control = 727,247) or FinnGen only (case = 1085; control = 271,463). Cis-SNPs associated with protein levels were used to instrument circulating proteins. We evaluated proteins for the consistency of directions of effect across MR analyses (with 95% confidence intervals not overlapping the null) and corroborating evidence from genetic colocalization. In the forward MR, 994 (SomaLogic) and 1570 (Olink) proteins were instrumentable. 440 proteins were analysed in both deCODE and UKB; 302 (69%) of these showed consistent directions of effect in the forward MR. Seven proteins had 95% confidence intervals (CIs) that did not overlap the null in both forward MR analyses and did not have evidence for an effect in the reverse direction: higher levels of dermatopontin (DPT), beta-crystallin B1 (CRYBB1), interleukin-18-binding protein (IL18BP) and vascular endothelial growth factor receptor 2 (KDR) and lower levels of odorant-binding protein 2b (OBP2B), glutamate-cysteine ligase regulatory subunit (GCLM) and gamma-crystallin D (CRYGD) were implicated in increasing MM risk. Evidence from genetic colocalization did not meet our threshold for a shared causal signal between any of these proteins and MM risk (h4 < 0.8). Our results highlight seven circulating proteins which may be involved in MM risk. Although evidence from genetic colocalization suggests these associations may not be robust to the effects of horizontal pleiotropy, these proteins may be useful markers of MM risk. Future work should explore the utility of these proteins in disease prediction or prevention using proteomic data from patients with MM or precursor conditions.

Comparative phenotyping of C57BL/6J substrains reveals distinctive patterns of cardiac aging.

Research in aging often refers to animal models, particularly C57BL/6J (B6J) mice, considered gold standard. However, B6J mice are distributed by different suppliers, which results in divers substrains exhibiting notable phenotypic differences. To ensure a suitable phenotype of cardiac aging, we performed heart analyses of young (5 months) and old B6J mice (24 months) from two substrains: B6JRj (Janvier) and B6JCrl mice (Charles River). In hearts of both substrains, myocardial fibrosis increased with age; however, only in old B6JRj mice cardiac hypertrophy associated with a decreased ejection fraction was observed. Gene set enrichment analysis in heart tissue using proteomic data revealed different age-associated pathway changes between the substrains, especially in oxidative phosphorylation. Functional assessment of isolated cardiomyocytes verified cardiac impairment during aging in B6JRj mice. Overall, results demonstrate that cardiac aging manifests as a moderate systolic dysfunction in B6JRj mice, while B6JCrl mice display no functional changes with age.

Mitochondrial dysfunction-driven AMPK-p53 axis activation underpins the anti-hepatocellular carcinoma effects of sulfane sulfur

Hepatocellular carcinoma (HCC) is the most prevalent form of primary liver cancer, notoriously refractory to conventional chemotherapy. Historically, sulfane sulfur-based compounds have been explored for the treatment of HCC, but their efficacy has been underwhelming. We recently reported a novel sulfane sulfur donor, PSCP, which exhibited improved chemical stability and structural malleability. This study aimed to investigate the effects of PSCP on HCC and elucidate the underlying mechanisms. We utilized bioinformatics algorithms for clustering, function enrichment, feature screening and survival analysis on proteomic data from the Cancer Proteome Atlas (CPTAC) and transcriptomic data from the Cancer Genome Atlas (TCGA). The impact of PSCP on HCC was assessed in vitro and in vivo, focusing on the expression and activity of p53 and AMP-activated protein kinase (AMPK), as well as mitochondrial function. The molecular target of PSCP was identified using Autodock, and binding interactions were visually analyzed. Sulfur metabolism was found to be reprogrammed in HCC, with downregulation of sulfur-related pathways correlating with poor patient prognosis. PSCP treatment significantly inhibited HCC tumor growth in an allograft model, reduced cell viability and proliferation, and induced apoptosis. PSCP potently increased p53 expression and induced AMPK phosphorylation in SNU398 HCC cells. AMPK suppression diminished PSCP-induced p53 upregulation. PSCP also impaired mitochondrial function by inhibiting mitochondrial respiratory complex I, with Ndus3 likely being the target of PSCP’s action. Supplementation with ATP significantly countered PSCP-induced SNU398 cell injury. Our findings suggest that the reprogramming of sulfur-related metabolic pathways is pivotal in HCC. PSCP presents as a promising therapeutic strategy by activating the AMPK-p53 signaling axis.

A Cross-Sectional Study on the Knowledge, Awareness, and Attitudes Toward Precision Orthodontics Among Orthodontists in India

Background Precision Orthodontics (PO) is a revolutionary concept that incorporates genetics into orthodontic practice. While many medical fields have adopted new genomic technologies, dentistry, particularly orthodontics, has been slower to adapt. PO involves the utilization of customized equipment and precise force delivery, coupled with the integration of genetic and proteomic data, to enhance the individualization of orthodontic therapies. With the emergence of precision medicine in healthcare, understanding the adoption and perception of PO is crucial in shaping the future of orthodontic practice. Objective This cross-sectional study aimed to assess the current state of knowledge, awareness, and attitudes toward PO among orthodontists in India. Methods A questionnaire-based survey was developed which was distributed online to orthodontists across India. The survey comprised three sections focusing on knowledge, awareness, and attitudes related to PO. The survey received 391 responses, representing 41.2% of the orthodontists surveyed. Results While 72.3% of surveyed orthodontists demonstrated awareness of PO, only 32% correctly defined it, revealing a notable knowledge gap. Furthermore, 66% of the respondents admitted a lack of knowledge regarding genomic concepts. Despite these gaps, a remarkably positive attitude was observed among orthodontists, with 98% expressing openness to adopting precision approaches. Conclusion This study underscores the need for targeted education in genomics for orthodontists to bridge knowledge gaps. To facilitate the integration of PO into routine practice, specific education and training may be required. The positive attitudes and willingness to embrace PO indicate a promising trajectory for its adoption, potentially enhancing patient care and treatment outcomes.

Development of an in vitro model to study muscle maladaptation to overtraining

Introduction Physical training stimulates skeletal muscle mitochondrial biogenesis and protein synthesis, inducing beneficial adaptations and promoting performance. However, in some cases when the training load is higher than required, the outcome may lead to non-functional overreaching – a state in which performance may be transiently reduced. This condition is relatively common especially among endurance athletes, and if protracted would result in the development of the overtraining syndrome (OTS), whose impact on skeletal muscle metabolism and function is still unknown. Muscle soreness, increased inflammation and reduced muscle mass are often reported. It has been reported that regeneration of skeletal muscle fibres is impaired, probably through a change in energy metabolism (Grobler et al., 2004). For instance, altered mitochondrial structure and function have been suggested (Grobler et al., 2004). The aim of the present project is to determine the molecular mechanisms underlying skeletal muscle maladaptation’s in response to simulated exercise in vitro. Methods Using a model developed in our laboratory (Zanou et al., 2021), we electrically stimulated C2C12 myotubes (a mouse skeletal muscle cell line) to simulate endurance exercise (Zanou et al., 2021). For simulated training (s-T) the stimulation was applied once daily, for three consecutive days. For simulated overtraining (s-OT), the stimulation was applied three times per day for three consecutive days. Mitochondrial biogenesis biomarkers have been measured, alongside proteomics analysis and mitochondrial respiration. Results In the in vitro s-T model, we observed the expected beneficial adaptations to training, which include myotube hypertrophy, increased fast and slow-twitch myosin heavy chain protein content, and increased mitochondrial respiration. Our proteomics data highlighted many positive adaptations, including upregulation of the muscle contractile and mitochondrial proteins. Immunofluorescence staining of F-actin and of the mitochondrial outer membrane protein Tom20, clearly showed robust F-actin structure and regular mitochondrial distribution in response to s-T. Interestingly, s-OT model presented myotube atrophy, and a decrease in fast and slow-twitch myosin heavy chain protein content. Mitochondrial respiration was increased in s-T and showed a clear trend versus reduction in s-OT. Our proteomics data revealed many downregulated proteins pathways in s-OT including muscle contractile and mitochondrial pathways. Immunofluorescence staining also revealed disrupted F-actin structure and aberrant mitochondrial aggregation in response to s-OT. Conclusions s-T recapitulates training positive adaptations, whereas s-OT recapitulates many of the muscle maladaptation observed in overtraining. Our next studies in human OTS muscle will validate key findings from our in vitro s-OT model and guide our mechanistic investigations into the molecular mechanisms of OTS.

Metabolomic and proteomic changes in leaves of rubber seedlings infected by Phytophthora palmivora.

Phytophthora palmivora, an oomycete pathogen, induces leaf fall disease in rubber trees (Hevea brasiliensis), causing significant economic losses. Effective disease management requires an understanding metabolic dynamics during infection. This study employed untargeted metabolomic and proteomic analyses to investigate the response of rubber seedling leaves to P. palmivora infection. Metabolomic profiling revealed 1702 and 979 metabolite peaks in positive and negative ionization modes, respectively, with 212 metabolites identified after duplicate removal. Principal component analysis (PCA) demonstrated distinct metabolic profiles between infected and non-infected leaves. Volcano plots indicated significant changes in 90 metabolites (P<0.05, fold-change ≥2), with 20 showing increased levels and 70 showing decreased levels in infected leaves. Pathway analysis highlighted nine metabolic pathways, with alanine, aspartate, and glutamate metabolism being the most impacted. Proteomic analysis identified 391 proteins, with 283 in infected leaves and 253 in control leaves. Among these, 145 were common to both conditions, suggesting their roles in maintaining homeostasis and responding to stress. Unique proteins in infected leaves were linked to oxidative phosphorylation, ATP synthesis, and metabolic adjustments, reflecting the increased energy demands. Control samples showed proteins related to growth and photosynthesis. Integrating metabolomic and proteomic data revealed significant alterations in energy metabolism pathways in response to infection. These findings enhance our understanding of rubber seedlings' defense strategies against P. palmivora, with implications for improving plant resistance and disease management strategies.

Proteomic and serologic assessments of responses to mRNA-1273 and BNT162b2 vaccines in human recipient sera

IntroductionThe first vaccines approved against SARS-CoV-2, mRNA-1273 and BNT162b2, utilized mRNA platforms. However, little is known about the proteomic markers and pathways associated with host immune responses to mRNA vaccination. In this proof-of-concept study, sera from male and female vaccine recipients were evaluated for proteomic and immunologic responses 1-month and 6-months following homologous third vaccination.MethodsAn aptamer-based (7,289 marker) proteomic assay coupled with traditional serology was leveraged to generate a comprehensive evaluation of systemic responsiveness in 64 and 68 healthy recipients of mRNA-1273 and BNT162b2 vaccines, respectively.ResultsSera from female recipients of mRNA-1273 showed upregulated indicators of inflammatory and immunological responses at 1-month post-third vaccination, and sera from female recipients of BNT162b2 demonstrated upregulated negative regulators of RNA sensors at 1-month. Sera from male recipients of mRNA-1273 showed no significant upregulation of pathways at 1-month post-third vaccination, though there were multiple significantly upregulated proteomic markers. Sera from male recipients of BNT162b2 demonstrated upregulated markers of immune response to doublestranded RNA and cell-cycle G(2)/M transition at 1-month. Random Forest analysis of proteomic data from pre-third-dose sera identified 85 markers used to develop a model predictive of robust or weaker IgG responses and antibody levels to SARS-CoV-2 spike protein at 6-months following boost; no specific markers were individually predictive of 6-month IgG response. Thirty markers that contributed most to the model were associated with complement cascade and activation; IL-17, TNFR pro-apoptotic, and PI3K signaling; and cell cycle progression.DiscussionThese results demonstrate the utility of proteomics to evaluate correlates or predictors of serological responses to SARS-CoV-2 vaccination.

Standard operating procedure combined with comprehensive quality control system for multiple LC-MS platforms urinary proteomics

Urinary proteomics is emerging as a potent tool for detecting sensitive and non-invasive biomarkers. At present, the comparability of urinary proteomics data across diverse liquid chromatography−mass spectrometry (LC-MS) platforms remains an area that requires investigation. In this study, we conduct a comprehensive evaluation of urinary proteome across multiple LC-MS platforms. To systematically analyze and assess the quality of large-scale urinary proteomics data, we develop a comprehensive quality control (QC) system named MSCohort, which extracted 81 metrics for individual experiment and the whole cohort quality evaluation. Additionally, we present a standard operating procedure (SOP) for high-throughput urinary proteome analysis based on MSCohort QC system. Our study involves 20 LC-MS platforms and reveals that, when combined with a comprehensive QC system and a unified SOP, the data generated by data-independent acquisition (DIA) workflow in urine QC samples exhibit high robustness, sensitivity, and reproducibility across multiple LC-MS platforms. Furthermore, we apply this SOP to hybrid benchmarking samples and clinical colorectal cancer (CRC) urinary proteome including 527 experiments. Across three different LC-MS platforms, the analyses report high quantitative reproducibility and consistent disease patterns. This work lays the groundwork for large-scale clinical urinary proteomics studies spanning multiple platforms, paving the way for precision medicine research.

Uncovering dark mass in population proteomics: Pan-analysis of single amino acid polymorphism relevant to cognition and aging.

Human proteome data across populations have been analyzed extensively to reveal protein quantitative associations with physiological or pathological states, while the single amino acid polymorphism (SAP) has been rarely investigated. In this work, we introduce a pan-SAP workflow that relies on pan-database searching independent of individual genome sequencing. Using ten cohorts comprising 2,004 individuals related to cognition disorder and aging, we quantify the SAP sites in key proteins, such as apolipoprotein E (APOE) in plasma and cerebrospinal fluid at the proteome level. Specifically, the quantification of heterozygous APOE-C112R, including its abundance and ratio, provides insights into the dosage effect and relationship with cognition disorder, which cannot be interpreted at the genomic level. Furthermore, our approach could precisely track age-related changes in APOE-C112R levels. Taken together, this pan-SAP workflow uncovered existing but hidden SAPs in multi-populations, connecting SAP quantification to disease progression and paving the way for broader proteomic investigations in complex diseases.

Overexpression of PLCG2 and TMEM38A inhibit tumor progression in clear cell renal cell carcinoma

Clear cell renal cell carcinoma is a prevalent urological malignancy, imposing substantial burdens on both patients and society. In our study, we used bioinformatics methods to select four putative target genes associated with EMT and prognosis and developed a nomogram model which could accurately predicting 5-year patient survival rates. We further analyzed proteome and single-cell data and selected PLCG2 and TMEM38A for the following experiments. Overexpression models of PLCG2 and TMEM38A were generated in Caki-1 and 786-O cell lines using plasmids. The in vitro experiments demonstrated that both of them exerted pro-apoptotic effects on Caki-1 and 786-O cells, inducing G2/M phase arrest, inhibiting proliferation, and suppressing EMT. In summary, we identified potential tumor suppressor factors and stratified ccRCC patients into high-risk and low-risk groups based on these factors. Furthermore, we elucidated the impact of PLCG2 and TMEM38A in Caki-1 and 786-O cell lines, offering novel avenues for therapeutic target exploration.