Protein Interaction Map Research Articles

Proteome- and Transcriptome-Wide Genetic Analysis Identifies Biological Pathways and Candidate Drug Targets for Preeclampsia.

Preeclampsia is a leading cause of maternal and perinatal morbidity and mortality. However, the current understanding of its underlying biological pathways remains limited. In this study, we performed a cross-platform proteome- and transcriptome-wide genetic analysis aimed at evaluating the causal relevance of >2000 circulating proteins with preeclampsia, supported by data on the expression of over 15 000 genes across 36 tissues leveraging large-scale preeclampsia genetic association data from women of European ancestry. We demonstrate genetic associations of 18 circulating proteins with preeclampsia (SULT1A1 [sulfotransferase 1A1], SH2B3 [SH2B adapter protein 3], SERPINE2 [serpin family E member 2], RGS18 [regulator of G-protein signaling 18], PZP [pregnancy zone protein], NOTUM [notum, palmitoleoyl-protein carboxylesterase], METAP1 [methionyl aminopeptidase 1], MANEA [mannosidase endo-alpha], jun-D [JunD proto-oncogene], GDF15 [growth differentiation factor 15], FGL1 [fibrinogen like 1], FGF5 [fibroblast growth factor 5], FES [FES proto-oncogene], APOBR [apolipoprotein B receptor], ANP [natriuretic peptide A], ALDH-E2 [aldehyde dehydrogenase 2 family member], ADAMTS13 [ADAM metallopeptidase with thrombospondin type 1 motif 13], and 3MG [N-methylpurine DNA glycosylase]), among which 11 were either directly or indirectly supported by gene expression data, 9 were supported by Bayesian colocalization analyses, and 5 (SERPINE2, PZP, FGF5, FES, and ANP) were supported by all lines of evidence examined. Protein interaction mapping identified potential shared biological pathways through natriuretic peptide signaling, blood pressure regulation, immune tolerance, and thrombin activity regulation. This investigation identified multiple targetable proteins linked to cardiovascular, inflammatory, and coagulation pathways, with SERPINE2, PZP, FGF5, FES, and ANP identified as pivotal proteins with likely causal roles in the development of preeclampsia. The identification of these potential targets may guide the development of targeted therapies for preeclampsia.

Collagen prolyl 4-hydroxylase subunit α member-induced head and neck squamous cell carcinoma aggressiveness is antagonized by LLGL2 via reduced expression of occludin.

There are three isoforms of human collagen prolyl 4-hydroxylases (C-P4Hs), each of which has been reported to play an important role in regulating the progression of a variety of human cancers. By analyzing TGCA datasets on human head and neck squamous cell carcinoma (HNSC), we find that a higher expression of all three C-P4HAs (the α subunit of C-P4Hs) is a superior prognostic indicator than a higher expression of two or a single C-P4HA. Unexpectedly, some patients with higher levels of three C-P4HAs survive longer than patients whose tumors have lower expression of C-P4HAs. Therefore, there may be molecule(s) that can negate the deleterious effects of overexpressing C-P4HAs during cancer progression. By constructing a functional protein interaction network of C-P4HAs and analyzing molecules whose expressions are correlated significantly with that of C-P4HAs, we identify scribble cell polarity complex component 2 (LLGL2) as a factor that antagonizes the effects of overexpressed C-P4HAs on HNSC. Silencing of LLGL2 in the human oral squamous cell line Cal-27 upregulates the expression of occludin and increases cancer cell invasion and migration. In contrast, knocking down C-P4HA alone inhibits cell migration and invasion. Furthermore, simultaneously downregulating three C-P4HAs has more pronounced effects on inhibiting cell migration and invasion. Accordingly, high LLGL2 expression is also a marker indicating improved prognosis in patients with HNSC. These results suggest that the interplay between LLGL2 and C-P4HAs may be targeted to mitigate HNSC tumorigenesis and progression.

PairK: Pairwise k-mer alignment for quantifying protein motif conservation in disordered regions.

Protein-protein interactions are often mediated by a modular peptide recognition domain binding to a short linear motif (SLiM) in the disordered region of another protein. The ability to predict domain-SLiM interactions would allow researchers to map protein interaction networks, predict the effects of perturbations to those networks, and develop biologically meaningful hypotheses. Unfortunately, sequence database searches for SLiMs generally yield mostly biologically irrelevant motif matches or false positives. To improve the prediction of novel SLiM interactions, researchers employ filters to discriminate between biologically relevant and improbable motif matches. One promising criterion for identifying biologically relevant SLiMs is the sequence conservation of the motif, exploiting the fact that functional motifs are more likely to be conserved than spurious motif matches. However, the difficulty of aligning disordered regions has significantly hampered the utility of this approach. We present PairK (pairwise k-mer alignment), an MSA-free method to quantify motif conservation in disordered regions. PairK outperforms both standard MSA-based conservation scores and a modern LLM-based conservation score predictor on the task of identifying biologically important motif instances. PairK can quantify conservation over wider phylogenetic distances than MSAs, indicating that SLiMs may be more conserved than is implied by MSA-based metrics. PairK is available as open-source code at https://github.com/jacksonh1/pairk.

Bidirectional linkage of DNA barcodes for the multiplexed mapping of higher-order protein interactions in cells.

Capturing the full complexity of the diverse hierarchical interactions in the protein interactome is challenging. Here we report a DNA-barcoding method for the multiplexed mapping of pairwise and higher-order protein interactions and their dynamics within cells. The method leverages antibodies conjugated with barcoded DNA strands that can bidirectionally hybridize and covalently link to linearize closely spaced interactions within individual 3D protein complexes, encoding and decoding the protein constituents and the interactions among them. By mapping protein interactions in cancer cells and normal cells, we found that tumour cells exhibit a larger diversity and abundance of protein complexes with higher-order interactions. In biopsies of human breast-cancer tissue, the method accurately identified the cancer subtype and revealed that higher-order protein interactions are associated with cancer aggressiveness.

Proteomic Blueprint of Atlantic Cod (Gadus morhua) Otoliths Revealing Environmental Stress Insights through Label-Free Quantitative Shotgun Proteomics

Otoliths of the fish’s inner ear serve as a natural chronological recorder because of their continuous formation marked by daily, monthly, and annual increments. Despite their importance, the comprehensive protein content of otoliths remains not fully identified. Using the label-free shotgun proteomics method with one-dimensional liquid chromatography coupled to electrospray ionization-orbitrap tandem mass spectrometry, we quantified a broad range of proteins, with individual otoliths containing between 1341 and 1839 proteins. The identified proteins could potentially serve as a blueprint for fish growth from embryo to adult. We quantified eleven heat-shock proteins (HSPs) in both sexes and several proteins impacted by endocrine disruptors, indicating the otolith’s capacity to reflect environmental stress, potentially linked to climate change effects and altering of hormonal and neuroendocrine functions. Our bioinformatic ontology analysis confirmed the presence of proteins critical for various biological processes, including structural and enzymatic proteins. Protein–protein interaction (PPI) mapping also identified key interactions between the identified proteins. These findings significantly advance our understanding of otolith proteomics, offering a solid foundation for future work. Most of the identified proteins deposited daily and influenced by the environment were not implicated in the biomineralization of otolith, raising the potential for the otolith proteome to recreate details of fish life history at previously unrealized levels.

Human milk proteins differentiate over the sex of newborns and across stages of lactation

Background & AimsHuman milk (HM) is a complete food that meets the nutritional and energy demands of the newborns. It contains numerous bioactive components, including functional proteins. Variations in HM energy and lipid content have already been reported related to the newborn's sex, but differences between protein profiles are still scarce. This work aimed to identify differences between HM proteins produced by mothers of female and male newborns, in the lactation stages of colostrum and mature milk, and the metabolic pathways involved. MethodsA total of 98 HM samples were collected from 39 lactating women and classified according to the newborn's sex, stages of lactation, and three mothers' age groups, and evaluated about protein concentration and one-dimensional electrophoretic profile. Next, to assess samples with the greatest differences, the HM proteins regarding the newborn's sex and the stages of lactation were compared using nano-LC-MS/MS, in 24 HM samples randomly rearranged into four groups: female and male infants, and colostrum and mature milk. Functional classification, metabolic pathways, and protein interaction networks were analyzed by Gene Ontology, KEGG, and STRING, respectively. ResultsThe soluble protein content of HM decreased throughout lactation, with differences regarding isolated factors, such as mothers' age group, child's sex and stages of lactation, and also in terms of their interactions. A total of 146 proteins were identified, 42 of which showed different abundances over the sexes of newborns and 53 between the stages of lactation. In general, proteins related to metabolic processes were up-regulated for mothers of male infants and in the mature stage of lactation, while proteins related to defense were up-regulated in mothers of female infants and in the colostrum phase. ConclusionThis study indicated that there are differentiated and specific nutritional and defense needs of newborns, by sex and by lactation phase, which is highly relevant for a more appropriate supply of food to infants receiving HM from donor mothers.

DNA methylation analysis in patients with neurodevelopmental disorders improves variant interpretation and reveals complexity

Analysis of genomic DNA methylation by generating epigenetic signature profiles (“episignatures”) is increasingly being implemented in genetic diagnosis. Here we report our experience using episignature analysis to resolve both uncomplicated and complex cases of neurodevelopmental disorder (NDD). We analysed 97 NDDs divided into: (i) a validation cohort of 59 patients with likely pathogenic/pathogenic variants characterized by a known episignature and (ii) a test cohort of 38 patients harbouring variants of unknown significance (VUS) or unidentified variants. The expected episignature was obtained in most cases with likely pathogenic/pathogenic variants (53/59; 90%), a revealing exception being the overlapping profile of two SMARCB1 pathogenic variants with ARID1A/B:c.6200, confirmed by the overlapping clinical features. In the test cohort, five cases showed the expected episignature, including: (i) novel pathogenic variants in ARID1B and BRWD3; (ii) a deletion in ATRX causing MRXFH1 X-linked mental retardation and (iii) confirmed the clinical diagnosis of Cornelia de Lange (CdL) syndrome in mutation negative CdL patients. Episignatures analysis of the in BAF complex components revealed novel functional protein interactions and common episignatures affecting homologous residues in highly conserved paralogous proteins (SMARCA2 M856V and SMARCA4 M866V). Finally, we also found sex-dependent episignatures in X-linked disorders. Implementation of episignature profiling is still in its early days but with increasing utilization come increasing awareness of the capacity of this methodology to help resolve the complex challenges of genetic diagnoses.

Expression analysis and mapping of Viral—Host Protein interactions of Poxviridae suggests a lead candidate molecule targeting Mpox

BackgroundMonkeypox (Mpox) is an important human pathogen without etiological treatment. A viral-host interactome study may advance our understanding of molecular pathogenesis and lead to the discovery of suitable therapeutic targets.MethodsGEO Expression datasets characterizing mRNA profile changes in different host responses to poxviruses were analyzed for shared pathway identification, and then, the Protein–protein interaction (PPI) maps were built. The viral gene expression datasets of Monkeypox virus (MPXV) and Vaccinia virus (VACV) were used to identify the significant viral genes and further investigated for their binding to the library of targeting molecules.ResultsInfection with MPXV interferes with various cellular pathways, including interleukin and MAPK signaling. While most host differentially expressed genes (DEGs) are predominantly downregulated upon infection, marked enrichments in histone modifiers and immune-related genes were observed. PPI analysis revealed a set of novel virus-specific protein interactions for the genes in the above functional clusters. The viral DEGs exhibited variable expression patterns in three studied cell types: primary human monocytes, primary human fibroblast, and HeLa, resulting in 118 commonly deregulated proteins. Poxvirus proteins C6R derived protein K7 and K7R of MPXV and VACV were prioritized as targets for potential therapeutic interventions based on their histone-regulating and immunosuppressive properties. In the computational docking and Molecular Dynamics (MD) experiments, these proteins were shown to bind the candidate small molecule S3I-201, which was further prioritized for lead development.ResultsMPXV circumvents cellular antiviral defenses by engaging histone modification and immune evasion strategies. C6R-derived protein K7 binding candidate molecule S3I-201 is a priority promising candidate for treating Mpox.

Extracellular vesicle dynamics in COPD: understanding the role of miR-422a, SPP1 and IL-17 A in smoking-related pathology

BackgroundChronic obstructive pulmonary disease (COPD) induced by smoking poses a significant global health challenge. Recent findings highlight the crucial role of extracellular vesicles (EVs) in mediating miRNA regulatory networks across various diseases. This study utilizes the GEO database to uncover distinct expression patterns of miRNAs and mRNAs, offering a comprehensive understanding of the pathogenesis of smoking-induced COPD. This study aims to investigate the mechanisms by which extracellular vesicles (EVs) mediate the molecular network of miR-422a-SPP1 to delay the onset of COPD caused by smoking.MethodsThe smoking-related miRNA chip GSE38974-GPL7723 was obtained from the GEO database, and candidate miRs were retrieved from the Vesiclepedia database. Downstream target genes of the candidate miRs were predicted using mRNA chip GSE38974-GPL4133, TargetScan, miRWalk, and RNA22 databases. This prediction was integrated with COPD-related genes from the GeneCards database, downstream target genes predicted by online databases, and key genes identified in the core module of WGCNA analysis to obtain candidate genes. The candidate genes were subjected to KEGG functional enrichment analysis using the “clusterProfiler” package in R language, and a protein interaction network was constructed. In vitro experiments involved overexpressing miRNA or extracting extracellular vesicles from bronchial epithelial cell-derived exosomes, co-culturing them with myofibroblasts to observe changes in the expression levels of the miR-422a-SPP1-IL-17 A regulatory network, and assessing protein levels of fibroblast differentiation-related factors α-SMA and collagen I using Western blot analysis.ResultsThe differential gene analysis of chip GSE38974-GPL7723 and the retrieval results from the Vesiclepedia database identified candidate miRs, specifically miR-422a. Subsequently, an intersection was taken among the prediction results from TargetScan, miRWalk, and RNA22 databases, the COPD-related gene retrieval results from GeneCards database, the WGCNA analysis results of chip GSE38974-GPL4133, and the differential gene analysis results. This intersection, combined with KEGG functional enrichment analysis, and protein-protein interaction analysis, led to the final screening of the target gene SPP1 and its upstream regulatory gene miR-422a. KEGG functional enrichment analysis of mRNAs correlated with SPP1 revealed the IL-17 signaling pathway involved. In vitro experiments demonstrated that miR-422a inhibition targets suppressed the expression of SPP1 in myofibroblasts, inhibiting differentiation phenotype. Bronchial epithelial cells, under cigarette smoke extract (CSE) stress, could compensate for myofibroblast differentiation phenotype by altering the content of miR-422a in their Extracellular Vesicles (EVs).ConclusionThe differential gene analysis of Chip GSE38974-GPL7723 and the retrieval results from the Vesiclepedia database identified candidate miRs, specifically miR-422a. Further analysis involved the intersection of predictions from TargetScan, miRWalk, and RNA22 databases, gene search on COPD-related genes from the GeneCards database, WGCNA analysis from Chip GSE38974-GPL4133, and differential gene analysis, combined with KEGG functional enrichment analysis and protein interaction analysis. Ultimately, the target gene SPP1 and its upstream regulatory gene miR-422a were selected. KEGG functional enrichment analysis on mRNAs correlated with SPP1 revealed the involvement of the IL-17 signaling pathway. In vitro experiments showed that miR-422a targeted inhibition suppressed the expression of SPP1 in myofibroblast cells, inhibiting differentiation phenotype. Furthermore, bronchial epithelial cells could compensate for myofibroblast differentiation phenotype under cigarette smoke extract (CSE) stress by altering the miR-422a content in their extracellular vesicles (EVs).

Protein Interaction Map of APOBEC3 Enzyme Family Reveals Deamination-Independent Role in Cellular Function

Human APOBEC3 enzymes are a family of single-stranded (ss)DNA and RNA cytidine deaminases that act as part of the intrinsic immunity against viruses and retroelements. These enzymes deaminate cytosine to form uracil which can functionally inactivate or cause degradation of viral or retroelement genomes. In addition, APOBEC3s have deamination-independent antiviral activity through protein and nucleic acid interactions. If expression levels are misregulated, some APOBEC3 enzymes can access the human genome leading to deamination and mutagenesis, contributing to cancer initiation and evolution. While APOBEC3 enzymes are known to interact with large ribonucleoprotein complexes, the function and RNA dependence are not entirely understood. To further understand their cellular roles, we determined by affinity purification mass spectrometry (AP-MS) the protein interaction network for the human APOBEC3 enzymes and mapped a diverse set of protein–protein and protein–RNA mediated interactions. Our analysis identified novel RNA-mediated interactions between APOBEC3C, APOBEC3H Haplotype I and II, and APOBEC3G with spliceosome proteins, and APOBEC3G and APOBEC3H Haplotype I with proteins involved in tRNA methylation and ncRNA export from the nucleus. In addition, we identified RNA-independent protein-protein interactions with APOBEC3B, APOBEC3D, and APOBEC3F and the prefoldin family of protein-folding chaperones. Interaction between prefoldin 5 (PFD5) and APOBEC3B disrupted the ability of PFD5 to induce degradation of the oncogene cMyc, implicating the APOBEC3B protein interaction network in cancer. Altogether, the results uncover novel functions and interactions of the APOBEC3 family and suggest they may have fundamental roles in cellular RNA biology, their protein–protein interactions are not redundant, and there are protein-protein interactions with tumor suppressors, suggesting a role in cancer biology. Data are available via ProteomeXchange with the identifier PXD044275.

Txtools: an R package facilitating analysis of RNA modifications, structures, and interactions.

We present txtools, an R package that enables the processing, analysis, and visualization of RNA-seq data at the nucleotide-level resolution, seamlessly integrating alignments to the genome with transcriptomic representation. txtools' main inputs are BAM files and a transcriptome annotation, and the main output is a table, capturing mismatches, deletions, and the number of reads beginning and ending at each nucleotide in the transcriptomic space. txtools further facilitates downstream visualization and analyses. We showcase, using examples from the epitranscriptomic field, how a few calls to txtools functions can yield insightful and ready-to-publish results. txtools is of broad utility also in the context of structural mapping and RNA:protein interaction mapping. By providing a simple and intuitive framework, we believe that txtools will be a useful and convenient tool and pave the path for future discovery. txtools is available for installation from its GitHub repository at https://github.com/AngelCampos/txtools.

FGF2 gene's antisense protein, NUDT6, plays a depressogenic role by promoting inflammation and suppressing neurogenesis without altering FGF2 signalling.

Fibroblast growth factor-2 (FGF2) is involved in the regulation of affective behaviour and shows antidepressant effects through the Akt and extracellular signal regulated kinase (ERK) 1/2 pathways. Nudix hydrolase 6 (NUDT6) protein is encoded from FGF2 gene's antisense strand and its role in the regulation of affective behaviour is unknown. Here, we overexpressed NUDT6 in the hippocampus and investigated its behavioural effects and the underlying molecular mechanisms affecting the behaviour. We showed that increasing hippocampal NUDT6 results in depression-like behaviour in rats without changing FGF2 levels or activating its downstream effectors, Akt and ERK1/2. Instead, NUDT6 acted by inducing inflammatory signalling, specifically by increasing S100 calcium binding protein A9 (S100A9) levels, activating nuclear factor-kappa B-p65 (NF-κB-p65), and elevating microglia numbers along with a reduction in neurogenesis. Our results suggest that NUDT6 could play a role in major depression by inducing a proinflammatory state. This is the first report of an antisense protein acting through a different mechanism of action than regulationof its sense protein. The opposite effects of NUDT6 and FGF2 on depression-like behaviour may serve as a mechanism to fine-tune affective behaviour. Our findings open up new venues for studying the differential regulation and functional interactions of sense and antisense proteins in neural function and behaviour, as well as in neuropsychiatric disorders. KEY POINTS: Hippocampal overexpression of nudix hydrolase 6 (NUDT6), the antisense protein of fibroblast growth factor-2 (FGF2), increases depression-like behaviour in rats. Hippocampal NUDT6 overexpression triggers a neuroinflammatory cascade by increasing S100 calcium binding proteinA9 (S100A9) expression and nuclear NF-κB-p65 translocation in neurons, in addition to microglial recruitment and activation. Hippocampal NUDT6 overexpression suppresses neurogenesis. NUDT6 exerts its actions without altering the levels or downstream signalling pathways of FGF2.

Host cell protein networks as a novel co-elution mechanism during protein A chromatography.

Host cell proteins (HCPs) are process-related impurities of therapeutic proteins produced in for example, Chinese hamster ovary (CHO) cells. Protein A affinity chromatography is the initial capture step to purify monoclonal antibodies or Fc-based proteins and is most effective for HCP removal. Previously proposed mechanisms that contribute to co-purification of HCPs with the therapeutic protein are either HCP-drug association or leaching from chromatin heteroaggregates. In this study, we analyzed protein A eluates of 23 Fc-based proteins by LC-MS/MS to determine their HCP content. The analysis revealed a high degree of heterogeneity in the number of HCPs identified in the different protein A eluates. Among all identified HCPs, the majority co-eluted with less than three Fc-based proteins indicating a drug-specific co-purification for most HCPs. Only ten HCPs co-purified with over 50% of the 23 Fc-based proteins. A correlation analysis of HCPs identified across multiple protein A eluates revealed their co-elution as HCP groups. Functional annotation and protein interaction analysis confirmed that some HCP groups are associated with protein-protein interaction networks. Here, we propose an additional mechanism for HCP co-elution involving protein-protein interactions within functional networks. Our findings may help to guide cell line development and to refine downstream purification strategies.

Mapping adipocyte interactome networks by HaloTag-enrichment-mass spectrometry.

Mapping protein interaction complexes in their natural state in vivo is arguably the Holy Grail of protein network analysis. Detection of protein interaction stoichiometry has been an important technical challenge, as few studies have focused on this. This may, however, be solved by artificial intelligence (AI) and proteomics. Here, we describe the development of HaloTag-based affinity purification mass spectrometry (HaloMS), a high-throughput HaloMS assay for protein interaction discovery. The approach enables the rapid capture of newly expressed proteins, eliminating tedious conventional one-by-one assays. As a proof-of-principle, we used HaloMS to evaluate the protein complex interactions of 17 regulatory proteins in human adipocytes. The adipocyte interactome network was validated using an in vitro pull-down assay and AI-based prediction tools. Applying HaloMS to probe adipocyte differentiation facilitated the identification of previously unknown transcription factor (TF)-protein complexes, revealing proteome-wide human adipocyte TF networks and shedding light on how different pathways are integrated.

Inhibition of anti-tumour reactivity of immune cells in the salivary gland cancer: A proteomic approach

BackgroundAdenoid cystic carcinoma (ACC), mucoepidermoid carcinoma (MEC), and oral squamous cell carcinoma (OSCC) respond differently to immunotherapy. Pembrolizumab, an immune checkpoint inhibitor, has been approved by the Food and Drug Administration for the treatment of squamous cell carcinomas of the head and neck region. While MEC has shown some response to pembrolizumab; however, ACC is the least responsive. At the molecular level, head and neck cancers produce immunosuppressive molecules, resulting in immune evasion. Therefore, we hypothesised that salivary gland cancer cells produce a higher number of immunosuppressive proteins that cause suppression of the immune system's anti-tumour reactivity. MethodTo determine differential protein expressions in OSCC, MEC, and ACC, we constructed cancer–immune cell co-culture models using different oral and salivary gland cancer cells. We performed SWATH, proteome profilers, gene ontology biological function, functional annotation clustering and protein interaction network analysis of all cancer samples in the co-culture models. ResultsAnalysis of the acquired data showed that the overexpressed proteins in the OSCC cells and participated more in metabolic process, while in the salivary gland cancer cells, overexpressed proteins participated more in immune processes, immune checkpoint pathway. Upon protein function analysis of salivary gland cells, the overexpressed proteins found negatively affecting immune process and checkpoint pathway proteins. ConclusionOverall, we conclude that salivary gland cancer is less responsive to immunotherapy, possibly because of the high presence of immunosuppressive proteins. However, further analysis is needed to verify the biological functions and interactive partners of each differentially expressed protein in ACC cells.

Epstein-Barr Virus: Human Interactome Reveals New Molecular Insights into Viral Pathogenesis for Potential Therapeutics and Antiviral Drug Discovery.

Host-virus Protein-Protein Interactions (PPIs) play pivotal roles in biological processes crucial for viral pathogenesis and by extension, inform antiviral drug discovery and therapeutics innovations. Despite efforts to develop the Epstein-Barr virus (EBV)-host PPI network, there remain significant knowledge gaps and a limited number of interacting human proteins deciphered. Furthermore, understanding the dynamics of the EBV-host PPI network in the distinct lytic and latent viral stages remains elusive. In this study, we report a comprehensive map of the EBV-human protein interactions, encompassing 1752 human and 61 EBV proteins by integrating data from the public repository HPIDB (v3.0) as well as curated high-throughput proteomic data from the literature. To address the stage-specific nature of EBV infection, we generated two detailed subset networks representing the latent and lytic stages, comprising 747 and 481 human proteins, respectively. Functional and pathway enrichment analysis of these subsets uncovered the profound impact of EBV proteins on cancer. The identification of highly connected proteins and the characterization of intrinsically disordered and cancer-related proteins provide valuable insights into potential therapeutic targets. Moreover, the exploration of drug-protein interactions revealed notable associations between hub proteins and anticancer drugs, offering novel perspectives for controlling EBV pathogenesis. This study represents, to the best of our knowledge, the first comprehensive investigation of the two distinct stages of EBV infection using high-throughput datasets. This makes a contribution to our understanding of EBV-host interactions and provides a foundation for future drug discovery and therapeutic interventions.

Functional interaction of Clock genes and bone morphogenetic proteins in the adrenal cortex.

The bone morphogenetic protein (BMP) system in the adrenal cortex plays modulatory roles in the control of adrenocortical steroidogenesis. BMP-6 enhances aldosterone production by modulating angiotensin (Ang) II-mitogen-activated protein kinase (MAPK) signaling, whereas activin regulates the adrenocorticotropin (ACTH)-cAMP cascade in adrenocortical cells. A peripheral clock system in the adrenal cortex was discovered and it has been shown to have functional roles in the adjustment of adrenocortical steroidogenesis by interacting with the BMP system. It was found that follistatin, a binding protein of activin, increased Clock mRNA levels, indicating an endogenous function of activin in the regulation of Clock mRNA expression. Elucidation of the interrelationships among the circadian clock system, the BMP system and adrenocortical steroidogenesis regulated by the hypothalamic-pituitary-adrenal (HPA) axis would lead to an understanding of the pathophysiology of adrenal disorders and metabolic disorders and the establishment of better medical treatment from the viewpoint of pharmacokinetics.

Repurposing Proximity-Dependent Protein Labeling (BioID2) for Protein Interaction Mapping in E. coli.

Methods that identify protein-protein interactions are essential for understanding molecular mechanisms controlling biological systems. Proximity-dependent labeling has proven to be a valuable method for revealing protein-protein interaction networks in living cells. A mutant form of the biotin protein ligase enzyme from Aquifex aeolicus (BioID2) underpins this methodology by producing biotin that is attached to proteins that enter proximity to it. This labels proteins for capture, extraction, and identification. In this chapter, we present a toolkit for BioID2 specifically adapted for use in E. coli, exemplified by the chemotaxis protein CheA. We have created plasmids containing BioID2 as expression cassettes for proteins (e.g., CheA) fused to BioID2 at either the N or C terminus, optimized with an 8×GGS linker. We provide a methodology for expression and verification of CheA-BioID2 fusion proteins in E. coli cells, the in vivo biotinylation of interactors by protein-BioID2 fusions, and extraction and analysis of interacting proteins that have been biotinylated.

Mapping protein states and interactions across the tree of life with co-fractionation mass spectrometry

We present CFdb, a harmonized resource of interaction proteomics data from 411 co-fractionation mass spectrometry (CF-MS) datasets spanning 21,703 fractions. Meta-analysis of this resource charts protein abundance, phosphorylation, and interactions throughout the tree of life, including a reference map of the human interactome. We show how large-scale CF-MS data can enhance analyses of individual CF-MS datasets, and exemplify this strategy by mapping the honey bee interactome.

Genes Such as IRS2 Differ from Ewing Sarcoma and Normal Tissue-specific Expression for Osteosarcoma

Objective: To screen and validate the expression of other key genes specific to osteosarcoma that distinguish normal tissue from Ewing sarcoma using a bioinformatics approach. Methods: GSE73166 for osteosarcoma associated with Ewing sarcoma and GSE42352 for osteosarcoma associated with normal tissue were obtained from the GEO database, and these two datasets were screened for differential genes (DEGs) and subjected to corresponding GO enrichment and KEGG enrichment with GSEA validation, and then correlation analysis, PCA and immuno-infiltration analysis were performed on the two datasets, and the These two datasets were intersected to derive 28 differential genes, and the corresponding heat map analysis and protein interaction network analysis were performed for these 28 genes, and then the expression statistics of these 28 genes in GSE21257 for different graded genes and survival analysis in R2 for osteosarcoma in TARGET. Results: TNFRSF11B, COL12A1, PLOD2, PTGES, MEF2C, IRS2 and MMP13 were found to have an effect on the staging of osteosarcoma, while CCND1 (P=0.021), IRS2 (P=0.015), OLFML2B (P=0.035), CPE (P=0.037), MAMDC2 (P=0.044) and MMP13 (P=0.013) had an impact on the survival prognosis of osteosarcoma. Conclusions: IRS2 and 11 other genes differ from Ewing sarcoma and normal tissues, producing a specific expression on the staging or survival prognosis of osteosarcoma.