Protein Interaction Map Research Articles

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.

Functional Interactions of BAF and LEM Proteins in the Formation of Germ Cells

Functional Interactions of BAF and LEM Proteins in the Formation of Germ Cells

Disclosing the molecular profile of the human amniotic mesenchymal stromal cell secretome by filter-aided sample preparation proteomic characterization

BackgroundThe secretome of mesenchymal stromal cells isolated from the amniotic membrane (hAMSCs) has been extensively studied for its in vitro immunomodulatory activity as well as for the treatment of several preclinical models of immune-related disorders. The bioactive molecules within the hAMSCs secretome are capable of modulating the immune response and thus contribute to stimulating regenerative processes. At present, only a few studies have attempted to define the composition of the secretome, and several approaches, including multi-omics, are underway in an attempt to precisely define its composition and possibly identify key factors responsible for the therapeutic effect.MethodsIn this study, we characterized the protein composition of the hAMSCs secretome by a filter-aided sample preparation (FASP) digestion and liquid chromatography-high resolution mass spectrometry (LC–MS) approach. Data were processed for gene ontology classification and functional protein interaction analysis by bioinformatics tools.ResultsProteomic analysis of the hAMSCs secretome resulted in the identification of 1521 total proteins, including 662 unique elements. A number of 157 elements, corresponding to 23.7%, were found as repeatedly characterizing the hAMSCs secretome, and those that resulted as significantly over-represented were involved in immunomodulation, hemostasis, development and remodeling of the extracellular matrix molecular pathways.ConclusionsOverall, our characterization enriches the landscape of hAMSCs with new information that could enable a better understanding of the mechanisms of action underlying the therapeutic efficacy of the hAMSCs secretome while also providing a basis for its therapeutic translation.

Protein interaction mapping reveals widespread targeting of development-related host transcription factors by phytoplasma effectors.

Phytoplasmas are pathogenic bacteria that reprogram plant host development for their own benefit. Previous studies have characterized a few different phytoplasma effector proteins that destabilize specific plant transcription factors. However, these are only a small fraction of the potential effectors used by phytoplasmas; therefore, the molecular mechanisms through which phytoplasmas modulate their hosts require further investigation. To obtain further insights into the phytoplasma infection mechanisms, we generated a protein-protein interaction network between a broad set of phytoplasma effectors and a large, unbiased collection of Arabidopsis thaliana transcription factors and transcriptional regulators. We found widespread, but specific, interactions between phytoplasma effectors and host transcription factors, especially those related to host developmental processes. In particular, many unrelated effectors target specific sets of TCP transcription factors, which regulate plant development and immunity. Comparison with other host-pathogen protein interaction networks shows that phytoplasma effectors have unusual targets, indicating that phytoplasmas have evolved a unique and unusual infection strategy. This study contributes a rich and solid data source that guides further investigations of the functions of individual effectors, as demonstrated for some herein. Moreover, the dataset provides insights into the underlying molecular mechanisms of phytoplasma infection.

High-Efficiency Enrichment by Saturating Nanoliters of Protein Affinity Media.

Affinity-purification mass spectrometry (AP-MS) is an established technique for identifying protein-protein interactions (PPIs). The basic technology involves immobilizing a high-specificity ligand to a solid-phase support (e.g., an agarose or magnetic bead) to pull down protein(s) of interest from cell lysates. Although these supports are engineered to minimize interactions with background protein, the conventional method recovers mostly nonspecific binders. The law of mass action for dilute solutions has taught us to use an excess of beads to capture all target proteins, especially weakly interacting ones. However, modern microbead technology presents a binding environment that is much different from a dilute solution. We describe a fluidic platform that captures and processes ultralow nanoliter quantities of magnetic particles, simultaneously increasing the efficiency of PPI detection and strongly suppressing nonspecific binding. We demonstrate the concept with synthetic mixtures of tagged protein and illustrate performance with a variety of AP-MS experiment types. These include a BioID experiment targeting lamin-A interactors from HeLa cells and pulldowns using GFP-tagged proteins associated with a double-strand DNA repair mechanism. We show that efficient extraction requires saturation of the solid-phase support and that <10 nL of beads is sufficient to generate comprehensive protein interaction maps.

Rapid Biomolecular Trifluoromethylation Using Cationic Aromatic Sulfonate Esters as Visible-Light-Triggered Radical Photocages.

Described here is a photodecaging approach to radical trifluoromethylation of biomolecules. This was accomplished by designing a quinolinium sulfonate ester that, upon absorption of visible light, achieves decaging via photolysis of the sulfonate ester to ultimately liberate free trifluoromethyl radicals that are trapped by π-nucleophiles in biomolecules. This photodecaging process enables protein and protein-interaction mapping experiments using trifluoromethyl radicals that require only 1 s reaction times and low photocage concentrations. In these experiments, aromatic side chains are labeled in an environmentally dependent fashion, with selectivity observed for tryptophan (Trp), followed by histidine (His) and tyrosine (Tyr). Scalable peptide trifluoromethylation through photodecaging is also demonstrated, where bespoke peptides harboring trifluoromethyl groups at tryptophan residues can be synthesized with 5-7 min reaction times and good yields.

Whole-Exome Sequencing in a Family with an Unexplained Tendency for Venous Thromboembolism: Multicomponent Prediction of Low-Frequency Variant Deleteriousness and of Individual Protein Interaction.

Whole-exome sequencing (WES) in families with an unexplained tendency for venous thromboembolism (VTE) may favor detection of low-frequency variants in genes with known contribution to hemostasis or associated with VTE-related phenotypes. WES analysis in six family members, three of whom affected by documented VTE, filtered for MAF < 0.04 in 192 candidate genes, revealed 22 heterozygous (16 missense and six synonymous) variants in patients. Functional prediction by multi-component bioinformatics tools, implemented by a database/literature search, including ClinVar annotation and QTL analysis, prioritized 12 missense variants, three of which (CRP Leu61Pro, F2 Asn514Lys and NQO1 Arg139Trp) were present in all patients, and the frequent functional variants FGB Arg478Lys and IL1A Ala114Ser. Combinations of prioritized variants in each patient were used to infer functional protein interactions. Different interaction patterns, supported by high-quality evidence, included eight proteins intertwined in the "acute phase" (CRP, F2, SERPINA1 and IL1A) and/or in the "fibrinogen complex" (CRP, F2, PLAT, THBS1, VWF and FGB) significantly enriched terms. In a wide group of candidate genes, this approach highlighted six low-frequency variants (CRP Leu61Pro, F2 Asn514Lys, SERPINA1 Arg63Cys, THBS1 Asp901Glu, VWF Arg1399His and PLAT Arg164Trp), five of which were top ranked for predicted deleteriousness, which in different combinations may contribute to disease susceptibility in members of this family.

Functional Interactions of BAF and LEM Proteins in the Formation of Germ Cells

Recovery of the nuclear structure after cell division requires special interactions between the integral proteins of the inner nuclear membrane having a special LEM domain (LEMD), nuclear lamina proteins (lamins) and the conserved BAF protein that serves as a central link in these interactions, providing topological relationships between chromatin and nuclear envelope. The dynamic transformations of these protein ensembles in the mitotic cycle are characterized in detail at the molecular level, however, less attention is paid to the developing germ cells undergoing meiotic divisions, despite of their nuclei, especially in diplotene oocytes, differ significantly in structure from the somatic nucleus. This review summarizes the still relatively scarce experimental data proving the significance of functional interactions between BAF and LEMD proteins for gamete formation, from the selection of germline cells to the transformation of haploid spermatids into morphologically mature spermatozoa.

Genome-Wide Identification and Expression Analysis of the RADIALIS-like Gene Family in Camellia sinensis.

The RADIALIS-like (RL) proteins are v-myb avian myeloblastosis viral oncogene homolog (MYB)-related transcription factors (TFs), and are involved in many biological processes, including metabolism, development, and response to biotic and abiotic stresses. However, the studies on the RL genes of Camellia sinensis are not comprehensive enough. Therefore, we undertook this study and identified eight CsaRLs based on the typical conserved domain SANT Associated domain (SANT) of RL. These genes have low molecular weights and theoretical pI values ranging from 5.67 to 9.76. Gene structure analysis revealed that six CsaRL genes comprise two exons and one intron, while the other two contain a single exon encompassing motifs 1 and 2, and part of motif 3. The phylogenetic analysis divided one hundred and fifty-eight RL proteins into five primary classes, in which CsaRLs clustered in Group V and were homologous with CssRLs of the Shuchazao variety. In addition, we selected different tissue parts to analyze the expression profile of CsaRLs, and the results show that almost all genes displayed variable expression levels across tissues, with CsaRL1a relatively abundant in all tissues. qRT-PCR (real-time fluorescence quantitative PCR) was used to detect the relative expression levels of the CsaRL genes under various abiotic stimuli, and it was found that CsaRL1a expression levels were substantially higher than other genes, with abscisic acid (ABA) causing the highest expression. The self-activation assay with yeast two-hybrid system showed that CsaRL1a has no transcriptional activity. According to protein functional interaction networks, CsaRL1a was well connected with WIN1-like, lysine histidine transporter-1-like, β-amylase 3 chloroplastic-like, carbonic anhydrase-2-like (CA2), and carbonic anhydrase dnaJC76 (DJC76). This study adds to our understanding of the RL family and lays the groundwork for further research into the function and regulatory mechanisms of the CsaRLs gene family in Camellia sinensis.

IFI27 Integrates Succinate and Fatty Acid Oxidation to Promote Adipocyte Thermogenic Adaption.

Mitochondria are the pivot organelles to control metabolism and energy homeostasis. The capacity of mitochondrial metabolic adaptions to cold stress is essential for adipocyte thermogenesis. How brown adipocytes keep mitochondrial fitness upon a challenge of cold-induced oxidative stress has not been well characterized. This manuscript shows that IFI27 plays an important role in cristae morphogenesis, keeping intact succinate dehydrogenase (SDH) function and active fatty acid oxidation to sustain thermogenesis in brown adipocytes. IFI27 protein interaction map identifies SDHB and HADHA as its binding partners. IFI27 physically links SDHB to chaperone TNF receptor associated protein 1 (TRAP1), which shields SDHB from oxidative damage-triggered degradation. Moreover, IFI27 increases hydroxyacyl-CoA dehydrogenase trifunctional multienzyme complex subunit alpha (HADHA) catalytic activity in β-oxidation pathway. The reduced SDH level and fatty acid oxidation in Ifi27-knockout brown fat results in impaired oxygen consumption and defective thermogenesis. Thus, IFI27 is a novel regulator of mitochondrial metabolism and thermogenesis.

A comprehensive protein interaction map and druggability investigation prioritized dengue virus NS1 protein as promising therapeutic candidate.

Dengue Virus (DENV) is a serious threat to human life worldwide and is one of the most dangerous vector-borne diseases, causing thousands of deaths annually. We constructed a comprehensive PPI map of DENV with its host Homo sapiens and performed various bioinformatics analyses. We found 1195 interactions between 858 human and 10 DENV proteins. Pathway enrichment analysis was performed on the two sets of gene products, and the top 5 human proteins with the maximum number of interactions with dengue viral proteins revealed noticeable results. The non-structural protein NS1 in DENV had the maximum number of interactions with the host protein, followed by NS5 and NS3. Among the human proteins, HBA1 and UBE2I were associated with 7 viral proteins, and 3 human proteins (CSNK2A1, RRP12, and HSP90AB1) were found to interact with 6 viral proteins. Pharmacophore-based virtual screening of millions of compounds in the public databases was performed to identify potential DENV-NS1 inhibitors. The lead compounds were selected based on RMSD values, docking scores, and strong binding affinities. The top ten hit compounds were subjected to ADME profiling which identified compounds C2 (MolPort-044-180-163) and C6 (MolPort-001-742-737) as lead inhibitors against DENV-NS1. Molecular dynamics trajectory analysis and intermolecular interactions between NS1 and the ligands displayed the molecular stability of the complexes in the cellular environment. The in-silico approaches used in this study could pave the way for the development of potential specie-specific drugs and help in eliminating deadly viral infections. Therefore, experimental and clinical assays are required to validate the results of this study.

Extracellular Vesicle-Serpine-1 Affects Neural Progenitor Cell Mitochondrial Networks and Synaptic Density: Modulation by Amyloid Beta and HIV-1

Brain endothelial extracellular vesicles carrying amyloid beta (EV-Aβ) can be transferred to neural progenitor cells (NPCs) leading to NPC dysfunction. However, the events involved in this EV-mediated Aβ pathology are unclear. EV-proteomics studies identified Serpine-1 (plasminogen activator inhibitor 1, PAI-1) as a major connecting “hub” on several protein–protein interaction maps. Serpine-1 was described as a key player in Aβ pathology and was linked to HIV-1 infection as well. Therefore, the aim of this work was to address the hypothesis that Serpine-1 can be transferred via EVs from brain endothelial cells (HBMEC) to NPCs and contribute to NPC dysfunction. HBMEC concentrated and released Serpine-1 via EVs, the effect that was potentiated by HIV-1 and Aβ. EVs loaded with Serpine-1 were readily taken up by NPCs, and HIV-1 enhanced this event. Interestingly, a highly specific Serpine-1 inhibitor PAI039 increased EV-Aβ transfer to NPCs in the presence of HIV-1. PAI039 also partially blocked mitochondrial network morphology alterations in the recipient NPCs, which developed mainly after HIV + Aβ-EV transfer. PAI039 partly attenuated HIV-EV-mediated decreased synaptic protein levels in NPCs, while increased synaptic protein levels in NPC projections. These findings contribute to a better understanding of the complex mechanisms underlying EV-Serpine-1 related Aβ pathology in the context of HIV infection. They are relevant to HIV-1 associated neurocognitive disorders (HAND) in an effort to elucidate the mechanisms of neuropathology in HIV infection.

Targeted cross-linker delivery for the in situ mapping of protein conformations and interactions in mitochondria

Current methods for intracellular protein analysis mostly require the separation of specific organelles or changes to the intracellular environment. However, the functions of proteins are determined by their native microenvironment as they usually form complexes with ions, nucleic acids, and other proteins. Here, we show a method for in situ cross-linking and analysis of mitochondrial proteins in living cells. By using the poly(lactic-co-glycolic acid) (PLGA) nanoparticles functionalized with dimethyldioctadecylammonium bromide (DDAB) to deliver protein cross-linkers into mitochondria, we subsequently analyze the cross-linked proteins using mass spectrometry. With this method, we identify a total of 74 pairs of protein-protein interactions that do not exist in the STRING database. Interestingly, our data on mitochondrial respiratory chain proteins ( ~ 94%) are also consistent with the experimental or predicted structural analysis of these proteins. Thus, we provide a promising technology platform for in situ defining protein analysis in cellular organelles under their native microenvironment.

MicroRNA-Based Markers of Oral Tongue Squamous Cell Carcinoma and Buccal Squamous Cell Carcinoma: A Systems Biology Approach.

Oral tongue squamous cell carcinoma (OTSCC) and buccal squamous cell carcinoma (BSCC) are the first and second leading causes of oral cancer, respectively. OTSCC and BSCC are associated with poor prognosis in patients with oral cancer. Thus, we aimed to indicate signaling pathways, Gene Ontology terms, and prognostic markers mediating the malignant transformation of the normal oral tissue to OTSCC and BSCC. The dataset GSE168227 was downloaded and reanalyzed from the GEO database. Orthogonal partial least square (OPLS) analysis identified common differentially expressed miRNAs (DEMs) in OTSCC and BSCC compared to their adjacent normal mucosa. Next, validated targets of DEMs were identified using the TarBase web server. With the use of the STRING database, a protein interaction map (PIM) was created. Using the Cytoscape program, hub genes and clusters within the PIM were shown. Next, gene-set enrichment analysis was carried out using the g:Profiler tool. Using the GEPIA2 web tool, analyses of gene expression and survival analysis were also performed. Two DEMs, including has-miR-136 and has-miR-377, were common in OTSCC and BSCC (p value <0.01; |Log2 FC| > 1). A total of 976 targets were indicated for common DEMs. PIM included 96 hubs, and the upregulation of EIF2S1, CAV1, RAN, ANXA5, CYCS, CFL1, MYC, HSP90AA1, PKM, and HSPA5 was significantly associated with a poor prognosis in the head and neck squamous cell carcinoma (HNSCC), while NTRK2, HNRNPH1, DDX17, and WDR82 overexpression was significantly linked to favorable prognosis in the patients with HNSCC. "Clathrin-mediated endocytosis" was considerably dysregulated in OTSCC and BSCC. The present study suggests that has-miR-136 and has-miR-377 are underexpressed in OTSCC and BSCC than in normal oral mucosa. Moreover, EIF2S1, CAV1, RAN, ANXA5, CYCS, CFL1, MYC, HSP90AA1, PKM, HSPA5, NTRK2, HNRNPH1, DDX17, and WDR82 demonstrated prognostic markers in HNSCC. These findings may benefit the prognosis and management of individuals with OTSCC/BSCC. However, additional experimental verification is required.

Mass spectrometric exploration of phytohormone profiles and signaling networks.

Phytohormones have crucial roles in plant growth, development, and acclimation to environmental stress; however, measuring phytohormone levels and unraveling their complex signaling networks and interactions remains challenging. Mass spectrometry (MS) has revolutionized the study of complex biological systems, enabling the comprehensive identification and quantification of phytohormones and their related targets. Here, we review recent advances in MS technologies and highlight studies that have used MS to discover and analyze phytohormone-mediated molecular events. In particular, we focus on the application of MS for profiling phytohormones, elucidating phosphorylation signaling, and mapping protein interactions in plants.

Prognostic biomarkers and molecular pathways mediating Helicobacter pylori-induced gastric cancer: a network-biology approach.

Cancer of the stomach is the second most frequent cancer-related death worldwide. The survival rate of patients with gastric cancer (GC) remains fragile. There is a requirement to discover biomarkers for prognosis approaches. Helicobacter pylori in the stomach is closely associated with the progression of GC. We identified the genes associated with poor/favorable prognosis in H. pylori-induced GC. Multivariate statistical analysis was applied on the Gene Expression Omnibus (GEO) dataset GSE54397 to identify differentially expressed miRNAs (DEMs) in gastric tissues with H. pylori-induced cancer compared with the H. pylori-positive with non-cancerous tissue. A protein interaction map (PIM) was built and subjected to DEMs targets. The enriched pathways and biological processes within the PIM were identified based on substantial clusters. Thereafter, the most critical genes in the PIM were illustrated, and their prognostic impact in GC was investigated. Considering p-value less than 0.01 and |Log2 fold change| as >1, five microRNAs demonstrated significant changes among the two groups. Gene functional analysis revealed that the ubiquitination system, neddylation pathway, and ciliary process are primarily involved in H. pylori-induced GC. Survival analysis illustrated that the overexpression of DOCK4, GNAS, CTGF, TGF-b1, ESR1, SELE, TIMP3, SMARCE1, and TXNIP was associated with poor prognosis, while increased MRPS5 expression was related to a favorable prognosis in GC patients. DOCK4, GNAS, CTGF, TGF-b1, ESR1, SELE, TIMP3, SMARCE1, TXNIP, and MRPS5 may be considered prognostic biomarkers for H. pylori-induced GC. However, experimental validation is necessary in the future.

Meet the First Authors.

Meet the First Authors.

Transcriptomic Analysis of Acetaminophen Biodegradation by Penicillium chrysogenum var. halophenolicum and Insights into Energy and Stress Response Pathways.

(1) Background: Acetaminophen (APAP), an active component of many analgesic and antipyretic drugs, is one of the most concerning trace contaminants in the environment and is considered as an emergent pollutant of marine and aquatic ecosystems. Despite its biodegradability, APAP has become a recalcitrant compound due to the growth of the global population, the ease of availability, and the inefficient wastewater treatment applied. (2) Methods: In this study, we used a transcriptomic approach to obtain functional and metabolic insights about the metabolization of APAP by a phenol-degrading fungal strain, Penicillium chrysogenum var. halophenolicum. (3) Results: We determined that the transcriptomic profile exhibited by the fungal strain during APAP degradation was very dynamic, being characterized by an abundance of dysregulated transcripts which were proportional to the drug metabolization. Using a systems biology approach, we also inferred the protein functional interaction networks that could be related to APAP degradation. We proposed the involvement of intracellular and extracellular enzymes, such as amidases, cytochrome P450, laccases, and extradiol-dioxygenases, among others. (4) Conclusions: Our data suggested that the fungus could metabolize APAP via a complex metabolic pathway, generating nontoxic metabolites, which demonstrated its potential in the bioremediation of this drug.