Differential Protein Expression Analysis Research Articles

Inhibition of FBP1 expression by KMT5A through TWIST1 methylation is one of the mechanisms leading to chemoresistance in breast cancer.

Lysine methyltransferase 5A (KMT5A) is the sole mammalian enzyme known to catalyse the mono‑methylation of histone H4 lysine 20 and non‑histone proteins such as p53, which are involved in the occurrence and progression of numerous cancers. The present study aimed to determine the function of KMT5A in inducing docetaxel (DTX) resistance in patients with breast carcinoma by evaluating glucose metabolism and the underlying mechanism involved. The upregulation or downregulation of KMT5A‑related proteins was examined after KMT5A knockdown in breast cancer (BRCA) cells by Tandem Mass Tag proteomics. Through differential protein expression and pathway enrichment analysis, the upregulated key gluconeogenic enzyme fructose‑1,6‑bisphosphatase 1 (FBP1) was discovered. Loss of FBP1 expression is closely related to the development and prognosis of cancers. A dual‑luciferase reporter gene assay confirmed that KMT5A inhibited the expression of FBP1 and that overexpression of FBP1 could enhance the chemotherapeutic sensitivity to DTX through the suppression of KMT5A expression. The KMT5A inhibitor UNC0379 was used to verify that DTX resistance induced by KMT5A through the inhibition of FBP1 depended on the methylase activity of KMT5A. According to previous literature and interaction network structure, it was revealed that KMT5A acts on the transcription factor twist family BHLH transcription factor 1 (TWIST1). Then, it was verified that TWSIT1 promoted the expression of FBP1 by using a dual‑luciferase reporter gene experiment. KMT5A induces chemotherapy resistance in BRCA cells by promoting cell proliferation and glycolysis. After the knockdown of the KMT5A gene, the FBP1 related to glucose metabolism in BRCA was upregulated. KMT5A knockdown expression and FBP1 overexpression synergistically inhibit cell proliferation and block cells in the G2/M phase. KMT5A inhibits the expression of FBP1 by methylating TWIST1 and weakening its promotion of FBP1 transcription. In conclusion, KMT5A was shown to affect chemotherapy resistance by regulating the cell cycle and positively regulate glycolysis‑mediated chemotherapy resistance by inhibiting the transcription of FBP1 in collaboration with TWIST1. KMT5A may be a potential therapeutic target for chemotherapy resistance in BRCA.

Multi-omics analysis reveals that Cas13d contributes to PI3K-AKT signaling and facilitates cell proliferation via PFKFB4 upregulation

The CRISPR-Cas system is a powerful gene editing technology, the clinical application of which is currently constrained due to safety concerns. A substantial body of safety research concerning Cas9 exists; however, scant attention has been directed toward investigating the safety profile of the emergent Cas13 system, which confers RNA editing capabilities. In particular, uncertainties persist regarding the potential cellular impacts of Cas13d in the absence of reliance on a cleavage effect. In this study, we conducted an initial exploration of the effects of Cas13d on HeLa cells. Total RNA and protein samples were extracted after transfection with a Cas13d-expressing plasmid construct, followed by transcriptomic and proteomic sequencing. Differential gene expression analysis identified 94 upregulated and 847 downregulated genes, while differential protein expression analysis identified 185 upregulated and 231 downregulated proteins. Subsequently, enrichment analysis was conducted on the transcriptome and proteome sequencing data, revealing that the PI3K-Akt signaling pathway is a common term. After intersecting the differentially expressed genes enriched in the PI3K-Akt signaling pathway with all the differentially expressed proteins, it was found that the expression of the related regulatory gene PFKFB4 was upregulated. Moreover, western blot analysis demonstrated that Cas13d can mediate PI3K-Akt signaling upregulation through overexpression of PFKFB4. CCK-8 assay, colony formation, and EdU experiments showed that Cas13d can promote cell proliferation. Our data demonstrate, for the first time, that Cas13d significantly impacts the transcriptomic and proteomic profiles, and proliferation phenotype, of HeLa cells, thus offering novel insights into safety considerations regarding gene editing systems.

Proteome-wide Characterization and Pathophysiology Correlation in Non-ischemic Cardiomyopathies.

Although the clinical consequences of advanced heart failure (HF) may be similar across different etiologies of cardiomyopathies, their proteomic expression may show substantial differences in relation to underlying pathophysiology. We aimed to identify myocardial tissue-based proteomic characteristics and the underlying molecular pathophysiology in non-ischemic cardiomyopathy with different etiologies. Comparative extensive proteomic analysis of the myocardium was performed in nine patients with biopsy-proven non-ischemic cardiomyopathies (3 dilated cardiomyopathy [DCM], 2 hypertrophic cardiomyopathy [HCM], and 4 myocarditis) as well as five controls using tandem mass tags combined with liquid chromatography-mass spectrometry. Differential protein expression analysis, Gene Ontology (GO) analysis, and Ingenuity Pathway Analysis (IPA) were performed to identify proteomic differences and molecular mechanisms in each cardiomyopathy type compared to the control. Proteomic characteristics were further evaluated in accordance with clinical and pathological findings. The principal component analysis score plot showed that the controls, DCM, and HCM clustered well. However, myocarditis samples exhibited scattered distribution. IPA revealed the downregulation of oxidative phosphorylation and upregulation of the sirtuin signaling pathway in both DCM and HCM. Various inflammatory pathways were upregulated in myocarditis with the downregulation of Rho GDP dissociation inhibitors. The molecular pathophysiology identified by extensive proteomic analysis represented the clinical and pathological properties of each cardiomyopathy with abundant proteomes. Different etiologies of non-ischemic cardiomyopathies in advanced HF exhibit distinct proteomic expression despite shared pathologic findings. The benefit of tailored management strategies considering the different proteomic expressions in non-ischemic advanced HF requires further investigation.

Combined transcriptome and proteome analysis reveals MSN and ARFIP2 as biomarkers for trastuzumab resistance of breast cancer.

HER2-positive breast cancer (BC) accounts for 20-30% of all BC subtypes and is linked to poor prognosis. Trastuzumab (Tz), a humanized anti-HER2 monoclonal antibody, is a first-line treatment for HER2-positive breast cancer which faces resistance challenges. This study aimed to identify the biomarkers driving trastuzumab resistance. Differential expression analysis of genes and proteins between trastuzumab-sensitive (TS) and trastuzumab-resistant (TR) cells was conducted using RNA-seq and iTRAQ. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) were used to study their functions. The prognostic significance and protein levels of ARFIP2 and MSN were evaluated using online tools and immunohistochemistry. Sensitivity of MSN and ARFIP2 to other therapies was assessed using public pharmacogenomics databases and the R language. Five genes were up-regulated, and nine genes were down-regulated in TR cells at both transcriptional and protein levels. Low ARFIP2 and high MSN expression linked to poor BC prognosis. MSN increased and ARFIP2 decreased in TR patients, correlating with shorter OS. MSN negatively impacted fulvestrant and immunotherapy sensitivity, while ARFIP2 had a positive impact. Our findings suggest that MSN and ARFIP2 could serve as promising biomarkers for predicting response to Tz, offering valuable insights for future research in the identification of diagnostic and therapeutic targets for BC patients with Tz resistance.

334 Identification of novel plasma protein biomarkers for diagnosis and prediction of Alzheimer’s disease in African Americans

OBJECTIVES/GOALS: To identify novel panel of plasma protein biomarkers to improve prediction and diagnosis of Alzheimer’s disease (AD) for African Americans (AA), who are at greater risk of developing AD compared to non-Hispanic White individuals but are underrepresented in AD research. METHODS/STUDY POPULATION: Pre-existing plasma samples from 460 AA individuals with clinical diagnoses of AD, cognitively unimpaired (CU), mild cognitive impairment (MCI), or dementia with Lewy bodies (DLB) will undergo untargeted proteomics using the SomaScan assay, where modified single stranded DNA aptamers bind to protein targets which are quantified by DNA microarray. Protein expression levels will be compared between diagnostic groups to identify differentially expressed proteins. Additional clinical, genetic, and lifestyle factors will be compared with protein expression when available. Proteins of interest, identified by differential protein expression analysis results, will be included in receiver operating characteristic analyses to identify the optimal set of proteins for diagnostic classification. RESULTS/ANTICIPATED RESULTS: A pilot experiment utilizing plasma from 40 individuals identified multiple differentially expressed proteins (DEPs) between AD and non-AD groups. Eight proteins were nominated from the differential protein analysis into a receiver operating characteristic (ROC) analysis based on pvalue and previous implication in AD genome wide association studies. Proteins involved in microglial activation, neuronal adhesion, cell proliferation, and innate immunity were nominated. The ROC model achieved 100% classification accuracy of AD and CU groups using age, sex, and the eight nominated proteins. It is expected that there will be more significant associations when utilizing the full cohort of 460 AA and that DEPs between AD, CU, MCI, and DLB will be identified. DISCUSSION/SIGNIFICANCE: The nomination of a novel panel of plasma biomarkers developed from an AA cohort will directly serve the AA community by improving access to an early and accurate diagnosis of AD. Access to improved prediction and diagnosis will likely improve disease management, thus improving patient outcomes and decreasing burden on families and caregivers.

Cardiac mitochondrial metabolism during pregnancy and the postpartum period.

The goal of the present study was to characterize changes in mitochondrial respiration in the maternal heart during pregnancy and after birth. Timed pregnancy studies were performed in 12-wk-old female FVB/NJ mice, and cardiac mitochondria were isolated from the following groups of mice: nonpregnant (NP), midpregnancy (MP), late pregnancy (LP), and 1-wk postbirth (PB). Similar to our previous studies, we observed increased heart size during all stages of pregnancy (e.g., MP and LP) and postbirth (e.g., PB) compared with NP mice. Differential cardiac gene and protein expression analyses revealed changes in several mitochondrial transcripts at LP and PB, including several mitochondrial complex subunits and members of the Slc family, important for mitochondrial substrate transport. Respirometry revealed that pyruvate- and glutamate-supported state 3 respiration was significantly higher in PB vs. LP mitochondria, with respiratory control ratio (RCR) values higher in PB mitochondria. In addition, we found that PB mitochondria respired more avidly when given 3-hydroxybutyrate (3-OHB) than mitochondria from NP, MP, and LP hearts, with no differences in RCR. These increases in respiration in PB hearts occurred independent of changes in mitochondrial yield but were associated with higher abundance of 3-hydroxybutyrate dehydrogenase 1. Collectively, these findings suggest that, after birth, maternal cardiac mitochondria have an increased capacity to use 3-OHB, pyruvate, and glutamate as energy sources; however, increases in mitochondrial efficiency in the postpartum heart appear limited to carbohydrate and amino acid metabolism.NEW & NOTEWORTHY Few studies have detailed the physiological adaptations that occur in the maternal heart. We and others have shown that pregnancy-induced cardiac growth is associated with significant changes in cardiac metabolism. Here, we examined mitochondrial respiration and substrate preference in isolated mitochondria from the maternal heart. We show that following birth, cardiac mitochondria are "primed" to respire on carbohydrate, amino acid, and ketone bodies. However, heightened respiratory efficiency is observed only with carbohydrate and amino acid sources. These results suggest that significant changes in mitochondrial respiration occur in the maternal heart in the postpartum period.

Analysis of physiological response and differential protein expression of Paramichelia baillonii saplings under phosphorus deficiency.

Paramichelia baillonii is a rare and fast-growing tree species in subtropical China. The acidic red soil in southern China severely limits its growth as it lacks sufficient available phosphorus (P), resulting in declining soil fertility and nutrient availability. The effect of P deficiency on P. Baillonii growth, root attributes, and physiological response has not yet been reported. Understanding the adaptability of P. baillonii to low-P conditions can improve afforestation and soil management in southern China. Therefore, we conducted a pot experiment on 2-year-old saplings and treated them with different P levels. Results showed that P deficiency (0-5 mg L-1 ) decreased growth attributes, root morphological traits, and nutrient uptake of P. baillonii saplings compared to control (CK). Similarly, reduction in chlorophyll a, b, total chlorophyll, net photosynthetic rate (Pn), transpiration rate (Tr), and Gs were seen in low P treatment saplings compared to CK. Whereas superoxide dismutase, peroxidase, malondialdehyde, acid phosphatase activity, and soluble protein content increased with increasing P-deficiency up to 5 mg L-1 , and soluble sugar showed oppsite trend. Moreover, the proteomics analysis identified 2721 proteins, 196 showing differential expression, with 90 up- and 106 down-regulated. Importantly, the metabolic activities increased in the pentose phosphate pathway, starch and sucrose metabolism, amino sugar and nucleotide sugar metabolism, and phenylpropanoid biosynthesis pathways to sustain regular plant growth under P deficiency. This study delves into the dynamic morpho-physiological and proteomic changes in response to P deficiency. Overall, growth and nutrient uptake were reduced, countered by adaptive biochemical and proteomic shifts, including heightened antioxidant activities and modifications in metabolic pathways, highlighting the resilient strategies of P. baillonii saplings under P deficiency.

Abstract B007: Vandetanib abrogates antiestrogen resistance in MAPK-driven ER+ breast cancer by halting key intracellular signaling pathways and multiple druggable kinases

Abstract Introduction: Vandetanib has been shown to abrogate ER+ breast cancer growth via inhibition of MAPK; we sought to elucidate the effects of Vandetanib on MAPK-driven endocrine-resistant breast cancer. Methods: Chronically treated MCF7-TAM (Tamoxifen), MCF7-EXE (Exemestane), and wild-type MCF7 ER+ breast cancer cell lines were treated with Vandetanib and/or Tamoxifen. Cell viability assays were conducted with CellTiter-Glo. Cells were treated with Vandetanib (10 uM) and vehicle for 24 hours, and mRNA sequencing was performed. To elicit TKI-specific proteomic changes, cells were treated with control or IC90 Vandetanib for 48 hours, and the signatures of kinase activity were determined using a multiplex inhibitor bead library coupled with mass spectrometry. Differential gene (DGE) and protein (DPE) expression analyses were performed to determine enriched and depleted transcripts and kinase activity with Vandetanib treatment. Gene set enrichment analysis was performed to determine the shared and unique pathways regulated by Vandetanib for each model. A Vandetanib response signature was compiled using the top 20 downregulated genes and analyzed with METABRIC and SCAN-B datasets to assess effects on survival in ER+ breast cancer patients. Results: MCF7-TAM and MCF7-EXE demonstrated lower Tamoxifen IC50 when treated with Vandetanib compared to Tamoxifen alone, which showed synergistic effects. Data analysis of mRNA libraries showed reduced tumor progression and signaling of MAPK, PI3K/AKT, RAS, CCND1, MYC, and EGFR across all three lines, as well as increased ERBB2 signaling, which may denote a potential adaptive bypass mechanism to Vandetanib treatment. Gene sets showed increased estrogen response, ESR1 activity, and sensitivity to tamoxifen across all three lines. Notable key players in PI3K/AKT and MAPK signaling such as TYRO3 were significantly downregulated at both the gene and protein levels. Additionally, JAK2 demonstrated dual upregulation and has been implicated with favorable prognosis due to associations with immune infiltration. The downregulated Vandetanib gene set conferred significantly improved OS (HR=0.75, p<0.0001, METABRIC; HR=0.87, p=0.034, SCAN-B) and RFS (HR=0.60, p<0.0001, METABRIC) in ER+ breast cancer patients from both datasets. Multiple druggable kinases such as RET, EGFR, FGFR2/3, CDK6, and SRC were depleted by Vandetanib treatment. Upregulated druggable kinases identified with Vandetanib treatment include MTOR, FGFR4, ERBB2, and JAK1. Conclusions: Vandetanib overcomes antiestrogen resistance in MAPK-driven models of ER+ breast cancer by halting key signaling pathways such as MAPK, PI3K/AKT, MYC, and ERBB2, among others. Upregulated druggable kinases may serve as targets to overcome resistance to Vandetanib. Downregulated targets with Vandetanib could serve as biomarkers to select patients most likely to benefit from Vandetanib treatment. Citation Format: Rasha T Kakati, Austin Whitman, Hyunsoo Kim, Philip M Spanheimer. Vandetanib abrogates antiestrogen resistance in MAPK-driven ER+ breast cancer by halting key intracellular signaling pathways and multiple druggable kinases [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr B007.

Effect of Semaglutide on High-Fat-Diet-Induced Liver Cancer in Obese Mice.

This study aims to investigate the impact of semaglutide on the expression of liver cancer proteins in obese mice induced by a high-fat diet. Sixteen obese mice were randomly divided into two groups: the high-fat diet group and the semaglutide group, each consisting of eight mice. Additionally, eight normal male mice were included as the control group. Serum samples were collected, and a differential expression analysis of total proteins in adipose tissue was performed using quantitative tandem mass spectrometry (TMT) in combination with liquid chromatography-tandem mass spectrometry (LC-MS/MS). Significant differential proteins were identified and subjected to a bioinformatics analysis. The findings revealed that these differential proteins, namely, integrin αV (ITGAV), laminin γ1 (LAMC1), fatty acid-binding protein 5 (FABP5), and lipoprotein lipase (LPL), regulate the occurrence and development of liver cancer by participating in the extracellular matrix (ECM) signaling pathway and the peroxisome proliferator-activated receptor (PPAR) signaling pathway. Notably, semaglutide can decelerate the progression of liver cancer by inducing the expression of ITGAV, LAMC1, FABP5, and LPL in the adipose tissue of obese mice.

Idiopathic pulmonary fibrosis-specific Bayesian network integrating extracellular vesicle proteome and clinical information

Idiopathic pulmonary fibrosis (IPF) is a progressive disease characterized by severe lung fibrosis and a poor prognosis. Although the biomolecules related to IPF have been extensively studied, molecular mechanisms of the pathogenesis and their association with serum biomarkers and clinical findings have not been fully elucidated. We constructed a Bayesian network using multimodal data consisting of a proteome dataset from serum extracellular vesicles, laboratory examinations, and clinical findings from 206 patients with IPF and 36 controls. Differential protein expression analysis was also performed by edgeR and incorporated into the constructed network. We have successfully visualized the relationship between biomolecules and clinical findings with this approach. The IPF-specific network included modules associated with TGF-β signaling (TGFB1 and LRC32), fibrosis-related (A2MG and PZP), myofibroblast and inflammation (LRP1 and ITIH4), complement-related (SAA1 and SAA2), as well as serum markers, and clinical symptoms (KL-6, SP-D and fine crackles). Notably, it identified SAA2 associated with lymphocyte counts and PSPB connected with the serum markers KL-6 and SP-D, along with fine crackles as clinical manifestations. These results contribute to the elucidation of the pathogenesis of IPF and potential therapeutic targets.

Decoding the host-pathogen interspecies molecular crosstalk during oral candidiasis in humans: an in silico analysis.

Introduction: The objective of this study is to investigate the interaction between Candida albicans and human proteins during oral candidiasis, with the aim of identifying pathways through which the pathogen subverts host cells. Methods: A comprehensive list of interactions between human proteins and C. albicans was obtained from the Human Protein Interaction Database using specific screening criteria. Then, the genes that exhibit differential expression during oral candidiasis in C. albicans were mapped with the list of human-Candida interactions to identify the corresponding host proteins. The identified host proteins were further compared with proteins specific to the tongue, resulting in a final list of 99 host proteins implicated in oral candidiasis. The interactions between host proteins and C. albicans proteins were analyzed using the STRING database, enabling the construction of protein-protein interaction networks. Similarly, the gene regulatory network of Candida proteins was reconstructed using data from the PathoYeastract and STRING databases. Core module proteins within the targeted host protein-protein interaction network were identified using ModuLand, a Cytoscape plugin. The expression levels of the core module proteins under diseased conditions were assessed using data from the GSE169278 dataset. To gain insights into the functional characteristics of both host and pathogen proteins, ontology analysis was conducted using Enrichr and YeastEnrichr, respectively. Result: The analysis revealed that three Candida proteins, HHT21, CYP5, and KAR2, interact with three core host proteins, namely, ING4 (in the DNMT1 module), SGTA, and TOR1A. These interactions potentially impair the immediate immune response of the host against the pathogen. Additionally, differential expression analysis of fungal proteins and their transcription factors in Candida-infected oral cell lines indicated that Rob1p, Tye7p, and Ume6p could be considered candidate transcription factors involved in instigating the pathogenesis of oral candidiasis during host infection. Conclusion: Our study provides a molecular map of the host-pathogen interaction during oral candidiasis, along with potential targets for designing regimens to overcome oral candidiasis, particularly in immunocompromised individuals.

Label-Free Quantitative Thermal Proteome Profiling Reveals Target Transcription Factors with Activities Modulated by MC3R Signaling.

Thermal proteome profiling with label-free quantitation using ion-mobility-enhanced LC-MS offers versatile data sets, providing information on protein differential expression, thermal stability, and the activities of transcription factors. We developed a multidimensional data analysis workflow for label-free quantitative thermal proteome profiling (TPP) experiments that incorporates the aspects of gene set enrichment analysis, differential protein expression analysis, and inference of transcription factor activities from LC-MS data. We applied it to study the signaling processes downstream of melanocortin 3 receptor (MC3R) activation by endogenous agonists derived from the proopiomelanocortin prohormone: ACTH, α-MSH, and γ-MSH. The obtained information was used to map signaling pathways downstream of MC3R and to deduce transcription factors responsible for cellular response to ligand treatment. Using our workflow, we identified differentially expressed proteins and investigated their thermal stability. We found in total 298 proteins with altered thermal stability, resulting from MC3R activation. Out of these, several proteins were transcription factors, indicating them as being downstream target regulators that take part in the MC3R signaling cascade. We found transcription factors CCAR2, DDX21, HMGB2, SRSF7, and TET2 to have altered thermal stability. These apparent target transcription factors within the MC3R signaling cascade play important roles in immune responses. Additionally, we inferred the activities of the transcription factors identified in our data set. This was done with Bayesian statistics using the differential expression data we obtained with label-free quantitative LC-MS. The inferred transcription factor activities were validated in our bioinformatic pipeline by the phosphorylated peptide abundances that we observed, highlighting the importance of post-translational modifications in transcription factor regulation. Our multidimensional data analysis workflow allows for a comprehensive characterization of the signaling processes downstream of MC3R activation. It provides insights into protein differential expression, thermal stability, and activities of key transcription factors. All proteomic data generated in this study are publicly available at DOI: 10.6019/PXD039945.

Quantitative proteomics analysis of permethrin and temephos-resistant Ae. aegypti revealed diverse differentially expressed proteins associated with insecticide resistance from Penang Island, Malaysia.

Synthetic insecticides are the primary vector control method used globally. However, the widespread use of insecticides is a major cause of insecticide-resistance in mosquitoes. Hence, this study aimed at elucidating permethrin and temephos-resistant protein expression profiles in Ae. aegypti using quantitative proteomics. In this study, we evaluated the susceptibility of Ae. aegypti from Penang Island dengue hotspot and non-hotspot against 0.75% permethrin and 31.25 mg/l temephos using WHO bioassay method. Protein extracts from the mosquitoes were then analysed using LC-ESI-MS/MS for protein identification and quantification via label-free quantitative proteomics (LFQ). Next, Perseus 1.6.14.0 statistical software was used to perform differential protein expression analysis using ANOVA and Student's t-test. The t-test selected proteins with≥2.0-fold change (FC) and ≥2 unique peptides for gene expression validation via qPCR. Finally, STRING software was used for functional ontology enrichment and protein-protein interactions (PPI). The WHO bioassay showed resistance with 28% and 53% mortalities in adult mosquitoes exposed to permethrin from the hotspot and non-hotspot areas. Meanwhile, the susceptibility of Ae. aegypti larvae revealed high resistance to temephos in hotspot and non-hotspot regions with 80% and 91% mortalities. The LFQ analyses revealed 501 and 557 (q-value <0.05) differentially expressed proteins in adults and larvae Ae. aegypti. The t-test showed 114 upregulated and 74 downregulated proteins in adult resistant versus laboratory strains exposed to permethrin. Meanwhile, 13 upregulated and 105 downregulated proteins were observed in larvae resistant versus laboratory strains exposed to temephos. The t-test revealed the upregulation of sodium/potassium-dependent ATPase β2 in adult permethrin resistant strain, H15 domain-containing protein, 60S ribosomal protein, and PB protein in larvae temephos resistant strain. The downregulation of troponin I, enolase phosphatase E1, glucosidase 2β was observed in adult permethrin resistant strain and tubulin β chain in larvae temephos resistant strain. Furthermore, the gene expression by qPCR revealed similar gene expression patterns in the above eight differentially expressed proteins. The PPI of differentially expressed proteins showed a p-value at <1.0 x 10-16 in permethrin and temephos resistant Ae. aegypti. Significantly enriched pathways in differentially expressed proteins revealed metabolic pathways, oxidative phosphorylation, carbon metabolism, biosynthesis of amino acids, glycolysis, and citrate cycle. In conclusion, this study has shown differentially expressed proteins and highlighted upregulated and downregulated proteins associated with insecticide resistance in Ae. aegypti. The validated differentially expressed proteins merit further investigation as a potential protein marker to monitor and predict insecticide resistance in field Ae. aegypti. The LC-MS/MS data were submitted into the MASSIVE database with identifier no: MSV000089259.

Substrate topographies modulate the secretory activity of human bone marrow mesenchymal stem cells

BackgroundMesenchymal stem cells (MSCs) secrete a diversity of factors with broad therapeutic potential, yet current culture methods limit potency outcomes. In this study, we used topographical cues on polystyrene films to investigate their impact on the secretory profile and potency of bone marrow-derived MSCs (hBM-MSCs). hBM-MSCs from four donors were cultured on topographic substrates depicting defined roughness, curvature, grooves and various levels of wettability.MethodsThe topographical PS-based array was developed using razor printing, polishing and plasma treatment methods. hBM-MSCs from four donors were purchased from RoosterBio and used in co-culture with peripheral blood mononuclear cells (PBMCs) from Cell Applications Inc. in an immunopotency assay to measure immunosuppressive capacity. Cells were cultured on low serum (2%) for 24–48 h prior to analysis. Image-based analysis was used for cell quantification and morphology assessment. Metabolic activity of BM-hMSCs was measured as the mitochondrial oxygen consumption rate using an extracellular flux analyzer. Conditioned media samples of BM-hMSCs were used to quantify secreted factors, and the data were analyzed using R statistics. Enriched bioprocesses were identify using the Gene Ontology tool enrichGO from the clusterprofiler. One-way and two-way ANOVAs were carried out to identify significant changes between the conditions. Results were deemed statistically significant for combined P < 0.05 for at least three independent experiments.ResultsCell viability was not significantly affected in the topographical substrates, and cell elongation was enhanced at least twofold in microgrooves and surfaces with a low contact angle. Increased cell elongation correlated with a metabolic shift from oxidative phosphorylation to a glycolytic state which is indicative of a high-energy state. Differential protein expression and gene ontology analyses identified bioprocesses enriched across donors associated with immune modulation and tissue regeneration. The growth of peripheral blood mononuclear cells (PBMCs) was suppressed in hBM-MSCs co-cultures, confirming enhanced immunosuppressive potency. YAP/TAZ levels were found to be reduced on these topographies confirming a mechanosensing effect on cells and suggesting a potential role in the immunomodulatory function of hMSCs.ConclusionsThis work demonstrates the potential of topographical cues as a culture strategy to improve the secretory capacity and enrich for an immunomodulatory phenotype in hBM-MSCs.

Proteomic characterisation of polyethylene terephthalate and monomer degradation by Ideonella sakaiensis

Synthetic plastics, like polyethylene terephthalate (PET), have become an essential part of modern life. Many of these products are remarkably persistent in the environment, and the accumulation in the environment is recognised as a major threat. Therefore, an increasing interest has been focusing on the screening for organisms able to degrade and assimilate the plastic. Ideonella sakaiensis originally isolated from a plastisphere has been reported as a bacterium that was solely thriving on the degradation on PET films. The processes affected by the presence of PET and its monomeric substances terephthalic acid, ethylene glycol, ethyl glycolate, and sodium glyoxylate monohydrate were elucidated by analysis of differential protein expression. The exposure of PET and its monomers induced the MHETase and affect two major pathways: the TCA cycle and the β-oxidation pathway. The increased expression of proteins directly or indirectly involved in these pathways suggests their underlying importance in the degradation of PET by I. sakaiensis since these proteins are mechanistically supporting the enzymes involved in the degradation of PET and its monomers.

Prolfqua: A Comprehensive R-Package for Proteomics Differential Expression Analysis

Mass spectrometry is widely used for quantitative proteomics studies, relative protein quantification, and differential expression analysis of proteins. There is a large variety of quantification software and analysis tools. Nevertheless, there is a need for a modular, easy-to-use application programming interface in R that transparently supports a variety of well principled statistical procedures to make applying them to proteomics data, comparing and understanding their differences easy. The prolfqua package integrates essential steps of the mass spectrometry-based differential expression analysis workflow: quality control, data normalization, protein aggregation, statistical modeling, hypothesis testing, and sample size estimation. The package makes integrating new data formats easy. It can be used to model simple experimental designs with a single explanatory variable and complex experiments with multiple factors and hypothesis testing. The implemented methods allow sensitive and specific differential expression analysis. Furthermore, the package implements benchmark functionality that can help to compare data acquisition, data preprocessing, or data modeling methods using a gold standard data set. The application programmer interface of prolfqua strives to be clear, predictable, discoverable, and consistent to make proteomics data analysis application development easy and exciting. Finally, the prolfqua R-package is available on GitHub https://github.com/fgcz/prolfqua, distributed under the MIT license. It runs on all platforms supported by the R free software environment for statistical computing and graphics.

Urine supernatant reveals a signature that predicts survival in clear-cell renal cell carcinoma.

To profile the cell-free urine supernatant and plasma of a small cohort of clear-cell renal cell carcinoma (ccRCC) patients by measuring the relative concentrations of 92 proteins related to inflammation. Using The Cancer Genome Atlas (TCGA), we then performed a targeted mRNA analysis of genes encoding the above proteins and defined their effects on overall survival (OS). Samples were collected prospectively from ccRCC patients. A multiplex proximity extension assay was used to measure the concentrations of 92 inflammation-related proteins in cell-free urine supernatants and plasma. Transcriptomic and clinical information from ccRCC patients was obtained from TCGA. Unsupervised clustering and differential protein expression analyses were performed on protein concentration data. Targeted mRNA analysis on genes encoding significant differentially expressed proteins was performed using TCGA. Backward stepwise regression analyses were used to build a nomogram. The performance of the nomogram and clinical benefit was assessed by discrimination and calibration, and a decision curve analysis, respectively. Unsupervised clustering analysis revealed inflammatory signatures in the cell-free urine supernatant of ccRCC patients. Backward stepwise regressions using TCGA data identified transcriptomic risk factors and risk groups associated with OS. A nomogram to predict 2-year and 5-year OS was developed using these risk factors. The decision curve analysis showed that our model was associated with a net benefit improvement compared to the treat-all/none strategies. We defined four novel biomarkers using proteomic and transcriptomic data that distinguish severity of prognosis in ccRCC. We showed that these biomarkers can be used in a model to predict 2-year and 5-year OS in ccRCC across different tumour stages. This type of analysis, if validated in the future, provides non-invasive prognostic information that could inform either management or surveillance strategies for patients.

Data-independent acquisition mass spectrometry identification of extracellular vesicle biomarkers for gastric adenocarcinoma.

Early diagnosis of gastric adenocarcinoma (GAC) can effectively prevent the progression of the disease and significantly improve patient survival. Currently, protein markers in clinical practice barely meet patient needs; it is therefore imperative to develop new diagnostic biomarkers with high sensitivity and specificity. In this study, we extracted extracellular vesicles (EV) from the sera of 33 patients with GAC and 19 healthy controls, then applied data-independent acquisition (DIA) mass spectrometry to measure protein expression profiles. Differential protein expression analysis identified 23 proteins showing expression patterns across different cancer stages, from which 15 proteins were selected as candidate biomarkers for GAC diagnosis. From this subset of 15 proteins, up to 6 proteins were iteratively selected as features and logistic regression was used to distinguish patients from healthy controls. Furthermore, serum-derived EV from a new cohort of 12 patients with gastric cancer and 18 healthy controls were quantified using the same method. A classification panel consisting of GSN, HP, ORM1, PIGR, and TFRC showed the best performance, with a sensitivity and negative predictive value (NPV) of 0.83 and 0.82. The area under curve (AUC) of the receiver operating characteristic (ROC) is 0.80. Finally, to facilitate the diagnosis of advanced stage GAC, we identified a 3-protein panel consisting of LYZ, SAA1, and F12 that showed reasonably good performance with an AUC of 0.83 in the validation dataset. In conclusion, we identified new protein biomarker panels from serum EVs for early diagnosis of gastric cancer that worth further validation.

Identification of hub proteins in cerebrospinal fluid as potential biomarkers of Alzheimer's disease by integrated bioinformatics.

Alzheimer's disease (AD) is a heterogeneous neurodegenerative disease with complex pathophysiology. Therefore, the identification of novel effective fluid biomarkers is essential for Alzheimer's disease diagnosis and drug development. This study aimed to identify potential candidate hub proteins in cerebrospinal fluid for precise Alzheimer's disease diagnosis using bioinformatics methods. A total of 29 co-significant differentially expressed proteins were identified by differential protein expression analysis in four different cohorts. Functional enrichment analysis revealed that most of these proteins were enriched in pathways related to glycometabolism. Using the Least Absolute Shrinkage and Selection Operator (LASSO) and random forest feature selection methods, six hub proteins [14-3-3 protein zeta/delta (YWHAZ), SPARC-related modular calcium-binding protein 1 (SMOC1), aldolase A (ALDOA), pyruvate kinase isoenzyme type M2 (PKM), chitinase-3-like protein 1 (CHI3L1), and secreted phosphoprotein 1 (SPP1)] were identified. These six hub proteins were upregulated in the cerebrospinal fluid of patients with Alzheimer's disease compared with cognitively unimpaired control individuals. Meanwhile, SMOC1, ALDOA, and PKM were specifically upregulated in the cerebrospinal fluid of patients with Alzheimer's disease but not in other neurodegenerative diseases. Build AD diagnostic models showed that a single hub protein or six hub proteins combination had an excellent ability to discriminate Alzheimer's disease. In conclusion, our study suggests that these identified hub proteins, which are related to glycometabolism, may be potential biomarkers for further basic and clinical research in Alzheimer's disease.

Uncovering the Key Targets and Therapeutic Mechanisms of Qizhen Capsule in Gastric Cancer through Network Pharmacology and Bioinformatic Analyses.

Objective. This study is aimed at screening out effective active compounds of Qizhen capsule (QZC) and exploring the underlying mechanisms against gastric cancer (GACA) by combining both bioinformatic analysis and experimental approaches. Weighted gene coexpression network analysis (WGCNA), network pharmacology, molecular docking simulation, survival analysis, and data-based differential gene and protein expression analysis were employed to predict QZC's potential targets and explore the underlying mechanisms. Subsequently, multiple experiments, including cell viability, apoptosis, and protein expression analyses, were conducted to validate the bioinformatics-predicted therapeutic targets. The results indicated that luteolin, rutin, quercetin, and kaempferol were vital active compounds, and TP53, MAPK1, and AKT1 were key targets. Molecular docking simulation showed that the four abovementioned active compounds had high binding affinities to the three main targets. Enrichment analysis showed that vital active compounds exerted therapeutic effects on GACA through regulating the TP53 pathway, MAPK pathway, and PI3K/AKT pathway. Furthermore, data-based gene expression analysis revealed that TP53 and JUN genes were not only differentially expressed between normal and GACA tissues but also correlated with clinical stages. In parallel, in vitro experimental results suggested that QZC exerted therapeutic effects on GACA by decreasing IC50 values, downregulating AKT expression, upregulating TP53 and MAPK expression, and increasing apoptosis of SGC-7901 cells. This study highlights the potential candidate biomarkers, therapeutic targets, and basic mechanisms of QZC in treating GACA, providing a foundation for new drug development, target mining, and related animal studies in GACA.