Towards the in vivo identification of protein-protein interactions.

Protein-protein interactions (PPIs) play crucial roles in biological processes. The conventional methods based on affinity purification of a protein of interest (POI) have been widely used to identify unknown PPIs. Recently, proximity-dependent biotin identification (BioID) has been used increasingly to investigate PPIs. BioID utilizes the proximity-dependent biotinylation, in the presence of biotin, of endogenous proteins that are located within a certain distance of POI-fused biotin ligase, which enables us to reveal the more physiologically relevant PPIs in vivo compared to the conventional methods. However, there is little information on an appropriate way to administer biotin in vivo. Recent studies reported some biotin supplementations for in vivo BioID. In this commentary, we review the BioID technique as a tool to examine PPIs, and we introduce a potential method to achieve efficient proximity labelling for in vivo BioID.

How Far Are We from the Completion of the Human Protein Interactome Reconstruction?

After more than fifteen years from the first high-throughput experiments for human protein-protein interaction (PPI) detection, we are still wondering how close the completion of the genome-scale human PPI network reconstruction is, what needs to be further explored and whether the biological insights gained from the holistic investigation of the current network are valid and useful. The unique structure of PICKLE, a meta-database of the human experimentally determined direct PPI network developed by our group, presently covering ~80% of the UniProtKB/Swiss-Prot reviewed human complete proteome, enables the evaluation of the interactome expansion by comparing the successive PICKLE releases since 2013. We observe a gradual overall increase of 39%, 182%, and 67% in protein nodes, PPIs, and supporting references, respectively. Our results indicate that, in recent years, (a) the PPI addition rate has decreased, (b) the new PPIs are largely determined by high-throughput experiments and mainly concern existing protein nodes and (c), as we had predicted earlier, most of the newly added protein nodes have a low degree. These observations, combined with a largely overlapping k-core between PICKLE releases and a network density increase, imply that an almost complete picture of a structurally defined network has been reached. The comparative unsupervised application of two clustering algorithms indicated that exploring the full interactome topology can reveal the protein neighborhoods involved in closely related biological processes as transcriptional regulation, cell signaling and multiprotein complexes such as the connexon complex associated with cancers. A well-reconstructed human protein interactome is a powerful tool in network biology and medicine research forming the basis for multi-omic and dynamic analyses.

Genome-wide promoter analysis, homology modeling and protein interaction network of Dehydration Responsive Element Binding (DREB) gene family in Solanum tuberosum.

Dehydration Responsive Element Binding (DREB) regulates the expression of numerous stress-responsive genes, and hence plays a pivotal role in abiotic stress responses and tolerance in plants. The study aimed to develop a complete overview of the cis-acting regulatory elements (CAREs) present in S. tuberosum DREB gene promoters. A total of one hundred and four (104) cis-regulatory elements (CREs) were identified from 2.5kbp upstream of the start codon (ATG). The in-silico promoter analysis revealed variable sets of cis-elements and functional diversity with the predominance of light-responsive (30%), development-related (20%), abiotic stress-responsive (14%), and hormone-responsive (12%) elements in StDREBs. Among them, two light-responsive elements (Box-4 and G-box) were predicted in 64 and 61 StDREB genes, respectively. Two development-related motifs (AAGAA-motif and as-1) were abundant in StDREB gene promoters. Most of the DREB genes contained one or more Myeloblastosis (MYB) and Myelocytometosis (MYC) elements associated with abiotic stress responses. Hormone-responsive element i.e. ABRE was found in 59 out of 66 StDREB genes, which implied their role in dehydration and salinity stress. Moreover, six proteins were chosen corresponding to A1-A6 StDREB subgroups for secondary structure analysis and three-dimensional protein modeling followed by model validation through PROCHECK server by Ramachandran Plot. The predicted models demonstrated >90% of the residues in the favorable region, which further ensured their reliability. The present study also anticipated pocket binding sites and disordered regions (DRs) to gain insights into the structural flexibility and functional annotation of StDREB proteins. The protein association network determined the interaction of six selected StDREB proteins with potato proteins encoded by other gene families such as MYB and NAC, suggesting their similar functional roles in biological and molecular pathways. Overall, our results provide fundamental information for future functional analysis to understand the precise molecular mechanisms of the DREB gene family in S. tuberosum.

Uncovering the Mechanisms and Molecular Targets of Weibing Formula 1 against Gastritis: Coupling Network Pharmacology with GEO Database.

Weibing Formula 1, a classic traditional formula, has been widely used clinically to treat gastritis in recent years. However, the potential pharmacological mechanism of Weibing Formula 1 is still unclear to date. A network pharmacology-based strategy was performed to uncover the underlying mechanisms of Weibing Formula 1 against gastritis. Furthermore, we structured the drug-active ingredients-genes-disease network and PPI network of shared targets, and function enrichment analysis of these targets was carried out. Ultimately, Gene Expression Omnibus (GEO) datasets and real-time quantitative PCR were used to verify the related genes. We found 251 potential targets corresponding to 135 bioactive components of Weibing Formula 1. Then, 327 gastritis-related targets were known gastritis-related targets. Among which, 60 common targets were shared between potential targets of Weibing Formula 1 and known gastritis-related targets. The results of pathway enrichment analysis displayed that 60 common targets mostly participated in various pathways related to Toll-like receptor signaling pathway, MAPK signaling pathway, cytokine-cytokine receptor interaction pathway, chemokine signaling pathway, and apoptosis. Based on the GSE60427 dataset, 15 common genes were shared between differentially expressed genes and 60 candidate targets. The verification results of the GSE5081 dataset showed that except for DUOX2 and VCAM1, the other 13 genes were significantly upregulated in gastritis, which was consistent with the results in the GSE60427 dataset. More importantly, real-time quantitative PCR results showed that the expressions of PTGS2, MMP9, CXCL2, and CXCL8 were significantly upregulated and NOS2, EGFR, and IL-10 were downregulated in gastritis patients, while the expressions of PTGS2, MMP9, CXCL2, and CXCL8 were significantly downregulated and NOS2, EGFR, and IL-10 were upregulated after the treatment of Weibing Formula 1. PTGS2, NOS2, EGFR, MMP9, CXCL2, CXCL8, and IL-10 may be the important direct targets of Weibing Formula 1 in gastritis treatment. Our study revealed the mechanism of Weibing Formula 1 in gastritis from an overall and systematic perspective, providing a theoretical basis for further knowing and application of this formula in the future.

Network pharmacology study on the mechanism of the Chinese medicine Radix Isatidis (Banlangen) for COVID-19.

ABSTRACT: Radix Isatidis (Banlangen) is a well-known traditional Chinese medicine for the treatment of different diseases and prevention of many body disorders. Besides, it also plays a pivotal role in novel coronavirus pneumonia, coronavirus disease 2019 (COVID-19). However, few researchers know its active ingredients and mechanism of action for COVID-19. To find whether Banlangen has a pharmacological effect on COVID-19. In this research, we systematically analyze Banlangen and COVID-19 through network pharmacology technology. A total of 33 active ingredients in Banlangen, 92 targets of the active ingredients, and 259 appropriate targets of COVID-19 were obtained, with 11 common targets. The analysis of the biological process of gene ontology and the enrichment of Kyoto Encyclopedia of Genes and Genomes signaling pathway suggests that Banlangen participated in the biological processes of protein phosphatase binding, tetrapyrrole binding, the apoptotic process involving cysteine-type endopeptidase activity, etc. The COVID-19 may be treated by regulating advanced glycation end products/a receptor for advanced glycation end products signaling pathway, interleukin-17 signaling pathway, tumor necrosis factor signaling pathway, sphingolipid signaling pathway, and p53 signaling pathway. Banlangen has a potential pharmacological effect on COVID-19, which has the value of further exploration in the following experiment and clinical application.

Efficient induction of proximity-dependent labelling by biotin feeding in BMAL1-BioID knock-in mice.

Proximity-dependent biotin identification (BioID) is a useful method to identify unknown protein-protein interactions. Few reports have described genetically engineered knock-in mouse models for in vivo BioID. Thus, little is known about the proper method for biotin administration and which tissues are applicable. Here, we established a BioID knock-in mouse model of Brain and Muscle ARNT-Like 1 (BMAL1) and the BirA biotin ligase with R118G mutation (BirA*). The BMAL1-BioID mouse model was used to investigate the effect of biotin diet feeding on protein biotinylation in several tissues. The BMAL1-BirA* fusion protein-retained proper intracellular localization of BMAL1 and binding to CLOCK protein in HEK293T cells. A biotin labelling assay in mouse embryonic fibroblasts revealed the protein biotinylation activity of BMAL1-BirA* expressed in knock-in mouse cells depending on biotin supplementation. Lastly, feeding a 0.5% biotin diet for 7 days induced protein biotinylation in the brain, heart, testis and liver of BMAL1-BioID mice without adverse effects on spermatogenesis. In the kidney, the biotin diet increased biotinylated protein levels in BMAL1-BioID and control mice, suggesting the existence of endogenous biotinylation activity. These results provide valuable information to optimize the in vivo BioID procedure.

The TRIM9/TRIM67 neuronal interactome reveals novel activators of morphogenesis.

TRIM9 and TRIM67 are neuronally enriched E3 ubiquitin ligases essential for appropriate morphogenesis of cortical and hippocampal neurons and fidelitous responses to the axon guidance cue netrin-1. Deletion of murine Trim9 or Trim67 results in neuroanatomical defects and striking behavioral deficits, particularly in spatial learning and memory. TRIM9 and TRIM67 interact with cytoskeletal and exocytic proteins, but the full interactome is not known. Here we performed the unbiased proximity-dependent biotin identification (BioID) approach to define TRIM9 and TRIM67 protein-protein proximity network in developing cortical neurons and identified putative neuronal TRIM interaction partners. Candidates included cytoskeletal regulators, cytosolic protein transporters, exocytosis and endocytosis regulators, and proteins necessary for synaptic regulation. A subset of high-priority candidates was validated, including Myo16, Coro1A, MAP1B, ExoC1, GRIP1, PRG-1, and KIF1A. For a subset of validated candidates, we utilized total internal reflection fluorescence microscopy to demonstrate dynamic colocalization with TRIM proteins at the axonal periphery, including at the tips of filopodia. Further analysis demonstrated that the RNA interference-based knockdown of the unconventional myosin Myo16 in cortical neurons altered growth cone filopodia density and axonal branching patterns in a TRIM9- and netrin-1-dependent manner. Future analysis of other validated candidates will likely identify novel proteins and mechanisms by which TRIM9 and TRIM67 regulate neuronal form and function. [Media: see text].

Traditional Chinese medicine network pharmacology study on exploring the mechanism of Xuebijing Injection in the treatment of coronavirus disease 2019.

As a representative drug for the treatment of severe community-acquired pneumonia and sepsis, Xuebijing (XBJ) injection is also one of the recommended drugs for the prevention and treatment of coronavirus disease 2019 (COVID-19), but its treatment mechanism for COVID-19 is still unclear. Therefore, this study aims to explore the potential mechanism of XBJ injection in the treatment of COVID-19 employing network pharmacology and molecular docking methods. The corresponding target genes of 45 main active ingredients in XBJ injection and COVID-19 were obtained by using multiple database retrieval and literature mining. 102 overlapping targets of them were screened as the core targets for analysis. Then built the PPI network, TCM-compound-target-disease, and disease-target-pathway networks with the help of Cytoscape 3.6.1 software. After that, utilized DAVID to perform gene ontology (GO) function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis to predict the action mechanism of overlapping targets. Finally, by applying molecular docking technology, all compounds were docked with COVID-19 3 CL protease(3CLpro), spike protein (S protein), and angiotensin-converting enzyme II (ACE2). The results indicated that quercetin, luteolin, apigenin and other compounds in XBJ injection could affect TNF, MAPK1, IL6 and other overlapping targets. Meanwhile, anhydrosafflor yellow B (AHSYB), salvianolic acid B (SAB), and rutin could combine with COVID-19 crucial proteins, and then played the role of anti-inflammatory, antiviral and immune response to treat COVID-19. This study revealed the multiple active components, multiple targets, and multiple pathways of XBJ injection in the treatment of COVID-19, which provided a new perspective for the study of the mechanism of traditional Chinese medicine (TCM) in the treatment of COVID-19.

Use of split-dihydrofolate reductase for the detection of protein-protein interactions and simultaneous selection of multiple plasmids in Plasmodium falciparum.

Defining protein-protein interactions is fundamental to the understanding of gene function. Protein-fragment complementation assays have been used for the analysis of protein-protein interactions in various organisms. The split-dihydrofolate reductase (DHFR) protein-fragment complementation assay utilises two complementary fragments of the enzyme fused to a pair of potentially interacting proteins. If these proteins interact, the DHFR fragments associate, fold into their native structure, reconstitute their function and confer resistance to antifolate drugs. We show that murine DHFR fragments fused to interacting proteins reconstitute a functional enzyme and confer resistance to the antifolate drug WR99210 in Plasmodium falciparum. These data demonstrate that the split-DHFR method can be used to detect in vivo protein-protein interactions in the parasite. Additionally, we show that split-DHFR fragments can be used as selection markers, permitting simultaneous selection of two plasmids in the presence of a single antifolate drug. Taken together, these experiments show that split-DHFR represents a valuable tool for the characterisation of Plasmodium protein function and genetic manipulation of the parasite.

Phase-separated condensate-aided enrichment of biomolecular interactions for high-throughput drug screening in test tubes.

Modification-dependent and -independent biomolecular interactions, including protein-protein, protein-DNA/RNA, protein-sugar, and protein-lipid interactions, play crucial roles in all cellular processes. Dysregulation of these biomolecular interactions or malfunction of the associated enzymes results in various diseases; therefore, these interactions and enzymes are attractive targets for therapies. High-throughput screening can greatly facilitate the discovery of drugs for these targets. Here, we describe a biomolecular interaction detection method, called phase-separated condensate-aided enrichment of biomolecular interactions in test tubes (CEBIT). The readout of CEBIT is the selective recruitment of biomolecules into phase-separated condensates harboring their cognate binding partners. We tailored CEBIT to detect various biomolecular interactions and activities of biomolecule-modifying enzymes. Using CEBIT-based high-throughput screening assays, we identified known inhibitors of the p53/MDM2 (MDM2) interaction and of the histone methyltransferase, suppressor of variegation 3-9 homolog 1 (SUV39H1), from a compound library. CEBIT is simple and versatile, and is likely to become a powerful tool for drug discovery and basic biomedical research.

A network pharmacology-based strategy for predicting anti-inflammatory targets of ephedra in treating asthma.

Asthma, the most common chronic respiratory disease in the world, is involved in a sustained inflammatory response caused by a variety of immune cells. Ephedra with multi-target, multi-pathway functions is an effective treatment for asthma. However, the ingredients and anti-inflammatory targets of ephedra in treating asthma are unclear. Therefore, there is a need for further research. Ephedra-related and anti-inflammatory targets were found and then combined to get intersection, which represented potential anti-inflammatory targets of ephedra. Moreover, compound-anti-inflammatory target and asthma-target protein-protein interaction network were merged to get the protein-protein interaction network intersection and core genes in asthma-target protein-protein interaction network. For the anti-inflammatory targets of ephedra in treating asthma, Gene Ontology and pathway analysis were executed to confirm gene functions of ephedra in antagonizing inflammation of asthma. Finally, molecular docking, qRT-PCR, WB and ELISA were performed to assess the binding activities between the compounds and anti-inflammatory targets of ephedra in treating asthma. Critical compounds and anti-inflammatory targets of ephedra in treating asthma were identified, including quercetin, luteolin, kempferol, naringenin, beta-sitosterol, SELE, IL-2 and CXCL10. The biological processes of anti-inflammatory targets of ephedra in treating asthma were involved in immune response, inflammatory response, cell-cell signaling and response to lipopolysaccharide. Moreover, 22 pathways were obtained and we proved that critical compounds inhabited the expression of SELE, IL-2 and CXCL10 at mRNA and protein levels.

Network Pharmacology-Based Study on the Molecular Biological Mechanism of Action for Compound Kushen Injection in Anti-Cancer Effect.

BACKGROUND Compound Kushen injection (CKI) is a traditional Chinese medicine preparation for clinical treatment of cancer pain or treatment of various types of solid tumors. The purpose of this study was to identify the main active compounds from CKI and to investigate its anti-cancer mechanisms via drug target biological network pharmacology construction and prediction. MATERIAL AND METHODS Constituents of CKI were retrieved from Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. Disease targets were collected in the Human Gene (Gene Cards) and Human Mendelian Inheritance (OMIM) databases. "Ingredients-protein targets-pathway" networks were constructed using Cytoscape. STRING database platform to construct enrichment of protein-protein interactions (PPI), related diseases and pathways network. Gene Ontology (GO) biological functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway of were performed to investigate by using Bioconductor tool for analysis. RESULTS The results indicated that 60 constituents of absorption, distribution, metabolism, and excretion (ADME) filtration resulted in 33 constituents exhibiting significant correlations with anti-cancer and CKI may target 113 proteins, including IL6, EGFR, CASP3, VEGFA, MYC, and ESR1. GO and KEGG enrichment analysis results show that 129 biological processes and 93 signal pathways associated with cancer. It mainly involves cancers such as prostate cancer, bladder cancer, hepatocellular carcinoma, colorectal cancer, breast cancer, etc. Active ingredients might also induce apoptosis in cancer cells via the p53 and PI3K-Akt signaling pathway mechanism. CONCLUSIONS This study was based on pharmacological networks results for the prediction of the multi-constituent, multi-target, and multi-pathway mechanisms of CKI, which might be a promising potential therapeutic and prevention candidate for anti-cancer. However, based on computer data mining and analysis, this study still needs to be further verified by in vivo/in vitro experiments, and the safety of CKI needs to be evaluated.

Depicting the genetic architecture of pediatric cancers through an integrative gene network approach.

The genetic etiology of childhood cancers still remains largely unknown. It is therefore essential to develop novel strategies to unravel the spectrum of pediatric cancer genes. Statistical network modeling techniques have emerged as powerful methodologies for enabling the inference of gene-disease relationship and have been performed on adult but not pediatric cancers. We performed a deep multi-layer understanding of pan-cancer transcriptome data selected from the Treehouse Childhood Cancer Initiative through a co-expression network analysis. We identified six modules strongly associated with pediatric tumor histotypes that were functionally linked to developmental processes. Topological analyses highlighted that pediatric cancer predisposition genes and potential therapeutic targets were central regulators of cancer-histotype specific modules. A module was related to multiple pediatric malignancies with functions involved in DNA repair and cell cycle regulation. This canonical oncogenic module gathered most of the childhood cancer predisposition genes and clinically actionable genes. In pediatric acute leukemias, the driver genes were co-expressed in a module related to epigenetic and post-transcriptional processes, suggesting a critical role of these pathways in the progression of hematologic malignancies. This integrative pan-cancer study provides a thorough characterization of pediatric tumor-associated modules and paves the way for investigating novel candidate genes involved in childhood tumorigenesis.

Systems pharmacology-based study of Tanreqing injection in airway mucus hypersecretion.

ETHNOPHARMACOLOGICAL RELEVANCE: Mucus hypersecretion (MH) is recognized as a key pathophysiological and clinical feature of many airway inflammatory diseases. MUC5AC is a major component of airway mucus. Tanreqing injection (TRQ) is a widely used herbal formula for the treatment of respiratory inflammations for years in China. However, a holistic network pharmacology approach to understanding its therapeutic mechanisms against MH has not been pursued. AIM OF THE STUDY: This study aimed to explore the systems-level potential active compounds and therapeutic mechanisms of TRQ in the treatment of MH. MATERIALS AND METHODS: We established systems pharmacology-based strategies comprising compound screenings, target predictions, and pathway identifications to speculate the potential active compounds and therapeutic targets of TRQ. We also applied compound-target and target-disease network analyses to evaluate the possible action mechanisms of TRQ. Then, lipopolysaccharide (LPS)-induced Sprague-Dawley (SD) rat model was constructed to assess the effect of TRQ in the treatment of MH and to validate the possible molecular mechanisms as predicted in systems pharmacology approach. RESULTS: The comprehensive compound collection successfully generated 55 compound candidates from TRQ. Among them, 11 compounds with high relevance to the potential targets were defined as representative and potential active ingredients in TRQ formula. Target identification revealed 172 potential targets, including pro-inflammatory cytokines of tumor necrosis factor α (TNF-α), interleukin (IL)-6, and IL-8. Pathway analyses uncovered the possible action of TRQ in the regulation of IL-17 signaling pathway and its downstream protein MUC5AC. Then in vivo experiment indicated that TRQ could significantly inhibit LPS stimulated MUC5AC over-production as well as the expression of TNF-α, IL-6, IL-8, and IL-17A, in both protein and mRNA levels. CONCLUSIONS: Based on the systems pharmacology method and in vivo experiment, our work provided a general knowledge on the potential active compounds and possible therapeutic targets of TRQ formula in its anti-MH process. This work might suggest directions for further research on TRQ and provide more insight into better understanding the chemical and pharmacological mechanisms of complex herbal prescriptions in a network perspective.

A Fluorescence Anisotropy-Based Comprehensive Method for the In Vitro Screening of COI1-JAZs Agonists and Antagonists.

The phytohormone (+)-7-iso-jasmonoyl-L-isoleucine (JA-Ile) causes protein-protein interactions (PPI) between F-box Protein CORONATINE INSENSITIVE 1 (COI1) and JASMONATE ZIM DOMAIN (JAZ) transcriptional repressor. A total of 13 JAZ subtypes are encoded in the genome of Arabidopsis thaliana; however, their genetic redundancy obfuscates the individual function of each JAZ. One approach to decipher this redundant signaling network is chemical genetics, using small molecules specific to individual JAZ subtype, for which a reliable and high-throughput screening system of the ligands for all combinations of COI1-JAZs would be indispensable. In this chapter, we describe a fluorescence anisotropy-based quantitative screening system for the ligands of COI1-JAZ co-receptors. Our method is applicable to agonists and antagonists of the COI1-JAZs.

Traditional Chinese medicine network pharmacology study on exploring the mechanism of Xuebijing Injection in the treatment of coronavirus disease 2019 / 中国天然药物

As a representative drug for the treatment of severe community-acquired pneumonia and sepsis, Xuebijing (XBJ) injection is also one of the recommended drugs for the prevention and treatment of coronavirus disease 2019 (COVID-19), but its treatment mechanism for COVID-19 is still unclear. Therefore, this study aims to explore the potential mechanism of XBJ injection in the treatment of COVID-19 employing network pharmacology and molecular docking methods. The corresponding target genes of 45 main active ingredients in XBJ injection and COVID-19 were obtained by using multiple database retrieval and literature mining. 102 overlapping targets of them were screened as the core targets for analysis. Then built the PPI network, TCM-compound-target-disease, and disease-target-pathway networks with the help of Cytoscape 3.6.1 software. After that, utilized DAVID to perform gene ontology (GO) function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis to predict the action mechanism of overlapping targets. Finally, by applying molecular docking technology, all compounds were docked with COVID-19 3 CL protease(3CLpro), spike protein (S protein), and angiotensin-converting enzyme II (ACE2). The results indicated that quercetin, luteolin, apigenin and other compounds in XBJ injection could affect TNF, MAPK1, IL6 and other overlapping targets. Meanwhile, anhydrosafflor yellow B (AHSYB), salvianolic acid B (SAB), and rutin could combine with COVID-19 crucial proteins, and then played the role of anti-inflammatory, antiviral and immune response to treat COVID-19. This study revealed the multiple active components, multiple targets, and multiple pathways of XBJ injection in the treatment of COVID-19, which provided a new perspective for the study of the mechanism of traditional Chinese medicine (TCM) in the treatment of COVID-19.

Systems structural biology measurements by in vivo cross-linking with mass spectrometry.

This protocol describes a workflow for utilizing large-scale cross-linking with mass spectrometry (XL-MS) to make systems-level structural biology measurements in complex biological samples, including cells, isolated organelles, and tissue samples. XL-MS is a structural biology technique that provides information on the molecular structure of proteins and protein complexes using chemical probes that report the proximity of probe-reactive amino acids within proteins, typically lysine residues. Information gained through XL-MS studies is often complementary to more traditional methods, such as X-ray crystallography, nuclear magnetic resonance, and cryo-electron microscopy. The use of MS-cleavable cross-linkers, including protein interaction reporter (PIR) technologies, enables XL-MS studies on protein structures and interactions in extremely complex biological samples, including intact living cells. PIR cross-linkers are designed to contain chemical bonds at specific locations within the cross-linker molecule that can be selectively cleaved by collision-induced dissociation or UV light. When broken, these bonds release the intact peptides that were cross-linked, as well as a reporter ion. Conservation of mass dictates that the sum of the two released peptide masses and the reporter mass equals the measured precursor mass. This relationship is used to identify cross-linked peptide pairs. Release of the individual peptides permits accurate measurement of their masses and independent amino acid sequence determination by tandem MS, allowing the use of standard proteomics search engines such as Comet for peptide sequence assignment, greatly simplifying data analysis of cross-linked peptide pairs. Search results are processed with XLinkProphet for validation and can be uploaded into XlinkDB for interaction network and structural analysis.

BioID: A Method to Generate a History of Protein Associations.

Proximity-dependent labeling methods for detecting candidate protein-protein interactions (PPIs) or mapping the protein constituency of subcellular domains have become increasingly utilized by the scientific community. One such method, BioID, allows for the identification of not only strong interactions but also weak and transient associations between a protein of interest (POI) or targeting motif and adjacent proteins. A promiscuous biotin ligase is fused to a POI or targeting motif, expressed in living cells, and induced to biotinylate proximal proteins during a defined labeling period by biotin supplementation. This generates a history of protein-protein associations that occurred with the POI or the protein constituency within a discrete subcellular domain during the labeling period. Biotinylated proteins are subsequently isolated, identified via mass spectrometry, and investigated as candidate interactors with the POI or as constituents within a subcellular domain. The BioID method has been utilized by numerous research groups and is continually being optimized, applied to new models, and modified for use in novel applications. Here we describe a protocol by which a BioID fusion protein can be validated and utilized for BioID pull-downs.

Improved sensitivity and resolution of in-cell NMR spectra.

In-cell NMR spectroscopy is a powerful tool to study protein structures and interactions under near physiological conditions in both prokaryotic and eukaryotic living cells. The low sensitivity and resolution of in-cell NMR spectra and limited lifetime of cells over the course of an in-cell experiment have presented major hurdles to wide acceptance of the technique, limiting it to a few select systems. These issues are addressed by introducing the use of the CRINEPT pulse sequence to increase the sensitivity and resolution of in-cell NMR spectra and the use of a bioreactor to maintain cell viability for up to 24h. Application of advanced pulse sequences and bioreactor during in-cell NMR experiments will facilitate the exploration of a wide range of biological processes.

Proximity-dependent biotinylation mediated by TurboID to identify protein-protein interaction networks in yeast.

The use of proximity-dependent biotinylation assays coupled to mass spectrometry (PDB-MS) has changed the field of protein-protein interaction studies. However, despite the recurrent and successful use of BioID-based protein-protein interactions screening in mammalian cells, the implementation of PDB-MS in yeast has not been effective. Here, we report a simple and rapid approach in yeast to effectively screen for proximal and interacting proteins in their natural cellular environment by using TurboID, a recently described version of the BirA biotin ligase. Using the protein arginine methyltransferase Rmt3 and the RNA exosome subunits, Rrp6 and Dis3, the application of PDB-MS in yeast by using TurboID was able to recover protein-protein interactions previously identified using other biochemical approaches and provided new complementary information for a given protein bait. The development of a rapid and effective PDB assay that can systematically analyze protein-protein interactions in living yeast cells opens the way for large-scale proteomics studies in this powerful model organism.