Journal articles: 'Quantitative analysis of interactomes'

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Kohli, Priyanka, Malte P. Bartram, Sandra Habbig, Caroline Pahmeyer, Tobias Lamkemeyer, Thomas Benzing, Bernhard Schermer, and Markus M. Rinschen. "Label-free quantitative proteomic analysis of the YAP/TAZ interactome." American Journal of Physiology-Cell Physiology 306, no. 9 (May 1, 2014): C805—C818. http://dx.doi.org/10.1152/ajpcell.00339.2013.

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The function of an individual protein is typically defined by protein-protein interactions orchestrating the formation of large complexes critical for a wide variety of biological processes. Over the last decade the analysis of purified protein complexes by mass spectrometry became a key technique to identify protein-protein interactions. We present a fast and straightforward approach for analyses of interacting proteins combining a Flp-in single-copy cellular integration system and single-step affinity purification with single-shot mass spectrometry analysis. We applied this protocol to the analysis of the YAP and TAZ interactome. YAP and TAZ are the downstream effectors of the mammalian Hippo tumor suppressor pathway. Our study provides comprehensive interactomes for both YAP and TAZ and does not only confirm the majority of previously described interactors but, strikingly, revealed uncharacterized interaction partners that affect YAP/TAZ TEAD-dependent transcription. Among these newly identified candidates are Rassf8, thymopoetin, and the transcription factors CCAAT/enhancer-binding protein (C/EBP)β/δ and core-binding factor subunit β (Cbfb). In addition, our data allowed insights into complex stoichiometry and uncovered discrepancies between the YAP and TAZ interactomes. Taken together, the stringent approach presented here could help to significantly sharpen the understanding of protein-protein networks.

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Hannigan, Molly M., Alyson M. Hoffman, J. Will Thompson, Tianli Zheng, and Christopher V. Nicchitta. "Quantitative Proteomics Links the LRRC59 Interactome to mRNA Translation on the ER Membrane." Molecular & Cellular Proteomics 19, no. 11 (August 11, 2020): 1826–49. http://dx.doi.org/10.1074/mcp.ra120.002228.

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Protein synthesis on the endoplasmic reticulum (ER) requires the dynamic coordination of numerous cellular components. Together, resident ER membrane proteins, cytoplasmic translation factors, and both integral membrane and cytosolic RNA-binding proteins operate in concert with membrane-associated ribosomes to facilitate ER-localized translation. Little is known, however, regarding the spatial organization of ER-localized translation. This question is of growing significance as it is now known that ER-bound ribosomes contribute to secretory, integral membrane, and cytosolic protein synthesis alike. To explore this question, we utilized quantitative proximity proteomics to identify neighboring protein networks for the candidate ribosome interactors SEC61β (subunit of the protein translocase), RPN1 (oligosaccharyltransferase subunit), SEC62 (translocation integral membrane protein), and LRRC59 (ribosome binding integral membrane protein). Biotin labeling time course studies of the four BioID reporters revealed distinct labeling patterns that intensified but only modestly diversified as a function of labeling time, suggesting that the ER membrane is organized into discrete protein interaction domains. Whereas SEC61β and RPN1 reporters identified translocon-associated networks, SEC62 and LRRC59 reporters revealed divergent protein interactomes. Notably, the SEC62 interactome is enriched in redox-linked proteins and ER luminal chaperones, with the latter likely representing proximity to an ER luminal chaperone reflux pathway. In contrast, the LRRC59 interactome is highly enriched in SRP pathway components, translation factors, and ER-localized RNA-binding proteins, uncovering a functional link between LRRC59 and mRNA translation regulation. Importantly, analysis of the LRRC59 interactome by native immunoprecipitation identified similar protein and functional enrichments. Moreover, [35S]-methionine incorporation assays revealed that siRNA silencing of LRRC59 expression reduced steady state translation levels on the ER by ca. 50%, and also impacted steady state translation levels in the cytosol compartment. Collectively, these data reveal a functional domain organization for the ER and identify a key role for LRRC59 in the organization and regulation of local translation.

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Chou, Chung-Lin, Gloria Hwang, Daniel J. Hageman, Lichy Han, Prashasti Agrawal, Trairak Pisitkun, and Mark A. Knepper. "Identification of UT-A1- and AQP2-interacting proteins in rat inner medullary collecting duct." American Journal of Physiology-Cell Physiology 314, no. 1 (January 1, 2018): C99—C117. http://dx.doi.org/10.1152/ajpcell.00082.2017.

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The urea channel UT-A1 and the water channel aquaporin-2 (AQP2) mediate vasopressin-regulated transport in the renal inner medullary collecting duct (IMCD). To identify the proteins that interact with UT-A1 and AQP2 in native rat IMCD cells, we carried out chemical cross-linking followed by detergent solubilization, immunoprecipitation, and LC-MS/MS analysis of the immunoprecipitated material. The analyses revealed 133 UT-A1-interacting proteins and 139 AQP2-interacting proteins, each identified in multiple replicates. Fifty-three proteins that were present in both the UT-A1 and the AQP2 interactomes can be considered as mediators of housekeeping interactions, likely common to all plasma membrane proteins. Among proteins unique to the UT-A1 list were those involved in posttranslational modifications: phosphorylation (protein kinases Cdc42bpb, Phkb, Camk2d, and Mtor), ubiquitylation/deubiquitylation (Uba1, Usp9x), and neddylation (Nae1 and Uba3). Among the proteins unique to the AQP2 list were several Rab proteins (Rab1a, Rab2a, Rab5b, Rab5c, Rab7a, Rab11a, Rab11b, Rab14, Rab17) involved in membrane trafficking. UT-A1 was found to interact with UT-A3, although quantitative proteomics revealed that most UT-A1 molecules in the cell are not bound to UT-A3. In vitro incubation of UT-A1 peptides with the protein kinases identified in the UT-A1 interactome revealed that all except Mtor were capable of phosphorylating known sites in UT-A1. Overall, the UT-A1 and AQP2 interactomes provide a snapshot of a dynamic process in which UT-A1 and AQP2 are produced in the rough endoplasmic reticulum, processed through the Golgi apparatus, delivered to endosomes that move into and out of the plasma membrane, and are regulated in the plasma membrane.

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Hiebel, Christof, Elisabeth Stürner, Meike Hoffmeister, Georg Tascher, Mario Schwarz, Heike Nagel, Christian Behrends, Christian Münch, and Christian Behl. "BAG3 Proteomic Signature under Proteostasis Stress." Cells 9, no. 11 (November 4, 2020): 2416. http://dx.doi.org/10.3390/cells9112416.

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The multifunctional HSP70 co-chaperone BAG3 (BCL-2-associated athanogene 3) represents a key player in the quality control of the cellular proteostasis network. In response to stress, BAG3 specifically targets aggregation-prone proteins to the perinuclear aggresome and promotes their degradation via BAG3-mediated selective macroautophagy. To adapt cellular homeostasis to stress, BAG3 modulates and functions in various cellular processes and signaling pathways. Noteworthy, dysfunction and deregulation of BAG3 and its pathway are pathophysiologically linked to myopathies, cancer, and neurodegenerative disorders. Here, we report a BAG3 proteomic signature under proteostasis stress. To elucidate the dynamic and multifunctional action of BAG3 in response to stress, we established BAG3 interactomes under basal and proteostasis stress conditions by employing affinity purification combined with quantitative mass spectrometry. In addition to the identification of novel potential BAG3 interactors, we defined proteins whose interaction with BAG3 was altered upon stress. By functional annotation and protein-protein interaction enrichment analysis of the identified potential BAG3 interactors, we confirmed the multifunctionality of BAG3 and highlighted its crucial role in diverse cellular signaling pathways and processes, ensuring cellular proteostasis and cell viability. These include protein folding and degradation, gene expression, cytoskeleton dynamics (including cell cycle and transport), as well as granulostasis, in particular.

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Sadeesh, Nithin, Mauro Scaravilli, and Leena Latonen. "Proteomic Landscape of Prostate Cancer: The View Provided by Quantitative Proteomics, Integrative Analyses, and Protein Interactomes." Cancers 13, no. 19 (September 27, 2021): 4829. http://dx.doi.org/10.3390/cancers13194829.

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Prostate cancer is the second most frequent cancer of men worldwide. While the genetic landscapes and heterogeneity of prostate cancer are relatively well-known already, methodological developments now allow for studying basic and dynamic proteomes on a large scale and in a quantitative fashion. This aids in revealing the functional output of cancer genomes. It has become evident that not all aberrations at the genetic and transcriptional level are translated to the proteome. In addition, the proteomic level contains heterogeneity, which increases as the cancer progresses from primary prostate cancer (PCa) to metastatic and castration-resistant prostate cancer (CRPC). While multiple aspects of prostate adenocarcinoma proteomes have been studied, less is known about proteomes of neuroendocrine prostate cancer (NEPC). In this review, we summarize recent developments in prostate cancer proteomics, concentrating on the proteomic landscapes of clinical prostate cancer, cell line and mouse model proteomes interrogating prostate cancer-relevant signaling and alterations, and key prostate cancer regulator interactomes, such as those of the androgen receptor (AR). Compared to genomic and transcriptomic analyses, the view provided by proteomics brings forward changes in prostate cancer metabolism, post-transcriptional RNA regulation, and post-translational protein regulatory pathways, requiring the full attention of studies in the future.

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Scifo, Enzo, Agnieszka Szwajda, Rabah Soliymani, Francesco Pezzini, Marzia Bianchi, Arvydas Dapkunas, Janusz Dębski, et al. "Quantitative analysis of PPT1 interactome in human neuroblastoma cells." Data in Brief 4 (September 2015): 207–16. http://dx.doi.org/10.1016/j.dib.2015.05.016.

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Buneeva, Olga, Arthur Kopylov, Oksana Gnedenko, Marina Medvedeva, Alexander Veselovsky, Alexis Ivanov, Victor Zgoda, and Alexei Medvedev. "Proteomic Profiling of Mouse Brain Pyruvate Kinase Binding Proteins: A Hint for Moonlighting Functions of PKM1?" International Journal of Molecular Sciences 24, no. 8 (April 21, 2023): 7634. http://dx.doi.org/10.3390/ijms24087634.

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Affinity-based proteomic profiling is widely used for the identification of proteins involved in the formation of various interactomes. Since protein–protein interactions (PPIs) reflect the role of particular proteins in the cell, identification of interaction partners for a protein of interest can reveal its function. The latter is especially important for the characterization of multifunctional proteins, which can play different roles in the cell. Pyruvate kinase (PK), a classical glycolytic enzyme catalyzing the last step of glycolysis, exists in four isoforms: PKM1, PKM2, PKL, and PKR. The enzyme isoform expressed in actively dividing cells, PKM2, exhibits many moonlighting (noncanonical) functions. In contrast to PKM2, PKM1, predominantly expressed in adult differentiated tissues, lacks well-documented moonlighting functions. However, certain evidence exists that it can also perform some functions unrelated to glycolysis. In order to evaluate protein partners, bound to PKM1, in this study we have combined affinity-based separation of mouse brain proteins with mass spectrometry identification. The highly purified PKM1 and a 32-mer synthetic peptide (PK peptide), sharing high sequence homology with the interface contact region of all PK isoforms, were used as the affinity ligands. This proteomic profiling resulted in the identification of specific and common proteins bound to both affinity ligands. Quantitative affinity binding to the affinity ligands of selected identified proteins was validated using a surface plasmon resonance (SPR) biosensor. Bioinformatic analysis has shown that the identified proteins, bound to both full-length PKM1 and the PK peptide, form a protein network (interactome). Some of these interactions are relevant for the moonlighting functions of PKM1. The proteomic dataset is available via ProteomeXchange with the identifier PXD041321.

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Velásquez-Zapata, Valeria, J. Mitch Elmore, Sagnik Banerjee, Karin S. Dorman, and Roger P. Wise. "Next-generation yeast-two-hybrid analysis with Y2H-SCORES identifies novel interactors of the MLA immune receptor." PLOS Computational Biology 17, no. 4 (April 2, 2021): e1008890. http://dx.doi.org/10.1371/journal.pcbi.1008890.

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Protein-protein interaction networks are one of the most effective representations of cellular behavior. In order to build these models, high-throughput techniques are required. Next-generation interaction screening (NGIS) protocols that combine yeast two-hybrid (Y2H) with deep sequencing are promising approaches to generate interactome networks in any organism. However, challenges remain to mining reliable information from these screens and thus, limit its broader implementation. Here, we present a computational framework, designated Y2H-SCORES, for analyzing high-throughput Y2H screens. Y2H-SCORES considers key aspects of NGIS experimental design and important characteristics of the resulting data that distinguish it from RNA-seq expression datasets. Three quantitative ranking scores were implemented to identify interacting partners, comprising: 1) significant enrichment under selection for positive interactions, 2) degree of interaction specificity among multi-bait comparisons, and 3) selection of in-frame interactors. Using simulation and an empirical dataset, we provide a quantitative assessment to predict interacting partners under a wide range of experimental scenarios, facilitating independent confirmation by one-to-one bait-prey tests. Simulation of Y2H-NGIS enabled us to identify conditions that maximize detection of true interactors, which can be achieved with protocols such as prey library normalization, maintenance of larger culture volumes and replication of experimental treatments. Y2H-SCORES can be implemented in different yeast-based interaction screenings, with an equivalent or superior performance than existing methods. Proof-of-concept was demonstrated by discovery and validation of novel interactions between the barley nucleotide-binding leucine-rich repeat (NLR) immune receptor MLA6, and fourteen proteins, including those that function in signaling, transcriptional regulation, and intracellular trafficking.

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Serrao, Simone, Cristina Contini, Giulia Guadalupi, Alessandra Olianas, Greca Lai, Irene Messana, Massimo Castagnola, et al. "Salivary Cystatin D Interactome in Patients with Systemic Mastocytosis: An Exploratory Study." International Journal of Molecular Sciences 24, no. 19 (September 27, 2023): 14613. http://dx.doi.org/10.3390/ijms241914613.

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Mastocytosis, a rare blood disorder characterized by the proliferation of clonal abnormal mast cells, has a variegated clinical spectrum and diagnosis is often difficult and delayed. Recently we proposed the cathepsin inhibitor cystatin D-R26 as a salivary candidate biomarker of systemic mastocytosis (SM). Its C26 variant is able to form multiprotein complexes (mPCs) and since protein–protein interactions (PPIs) are crucial for studying disease pathogenesis, potential markers, and therapeutic targets, we aimed to define the protein composition of the salivary cystatin D-C26 interactome associated with SM. An exploratory affinity purification-mass spectrometry method was applied on pooled salivary samples from SM patients, SM patient subgroups with and without cutaneous symptoms (SM+C and SM−C), and healthy controls (Ctrls). Interactors specifically detected in Ctrls were found to be implicated in networks associated with cell and tissue homeostasis, innate system, endopeptidase regulation, and antimicrobial protection. Interactors distinctive of SM−C patients participate to PPI networks related to glucose metabolism, protein S-nitrosylation, antibacterial humoral response, and neutrophil degranulation, while interactors specific to SM+C were mainly associated with epithelial and keratinocyte differentiation, cytoskeleton rearrangement, and immune response pathways. Proteins sensitive to redox changes, as well as proteins with immunomodulatory properties and activating mast cells, were identified in patients; many of them were involved directly in cytoskeleton rearrangement, a process crucial for mast cell activation. Although preliminary, these results demonstrate that PPI alterations of the cystatin D-C26 interactome are associated with SM and provide a basis for future investigations based on quantitative proteomic analysis and immune validation.

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Narushima, Yuta, Hiroko Kozuka-Hata, Kouhei Tsumoto, Jun-Ichiro Inoue, and Masaaki Oyama. "Quantitative phosphoproteomics-based molecular network description for high-resolution kinase-substrate interactome analysis." Bioinformatics 32, no. 14 (March 24, 2016): 2083–88. http://dx.doi.org/10.1093/bioinformatics/btw164.

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Ouyang, Haiping, Xinyu (Cindy) How, Xiaorong (Sherry) Wang, Yao Gong, Lan Huang, Yue Chen, and David Bernlohr. "Abstract 1295 Application of Crosslinking-based technology in Quantitative Analysis of PHD2 Interactome." Journal of Biological Chemistry 300, no. 3 (March 2024): 106858. http://dx.doi.org/10.1016/j.jbc.2024.106858.

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Cutler, Jevon, Rahia Tahir, Jingnan Han, Raja Sekhar Nirujogi, Tai-Chung Huang, Xianrong Wong, Saradhi Mallampati, et al. "Differential Signaling through p190 and p210 Forms of BCR-ABL Fusion Proteins Revealed By Proteomic Analysis." Blood 126, no. 23 (December 3, 2015): 3651. http://dx.doi.org/10.1182/blood.v126.23.3651.3651.

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Abstract Chromosomal translocations involving chromosome 9q34 and 22q11 generate the BCR-ABL1 fusion gene. The location of the translocation within the BCR gene dictates which exons are excluded or included in the resulting fusion with the ABL1 gene. The most common translocations produce three main protein products with molecular weights of 190, 210, and 230 kD. Interestingly, the p190 and p210 BCR-ABL1 forms are associated with different clinical characteristics. Specifically, BCR-ABL1+ acute lymphoblastic leukemia (ALL) cases typically harbor the p190 form, whereas chronic myelogenous leukemia (CML) cases typically harbor the p210 form. Despite a great deal of study over many decades devoted to the BCR-ABL1 molecule, neither phosphorylation of putative target proteins at site-specific resolution nor protein-protein interaction differences between the p190 and the p210 forms is well understood, preventing thorough understanding of the signaling programs employed by these variants. Therefore, to examine signaling differences between p190 and p210 we chose a homogeneous system to investigate global phosphorylation of tyrosine residues. Ba/F3 cell lines, which are normally dependent on IL-3 for growth, were transduced with either the p190 or p210 form of BCR-ABL1. Subsequently, these cell lines were selected for successful growth in cytokine free media, indicating that the BCR-ABL1 fusions were signaling and inducing aberrant growth. These two BCR-ABL1 cell lines, as well as the parental Ba/F3 line, were grown in SILAC (stable isotope labeling by amino acids in cell culture) media and lysates were enriched for phosphotyrosine (pTyr) peptides and submitted for mass spectrometric analysis. The resulting 3-state SILAC dataset includes quantitation on 355 pTyr sites in three pairwise comparisons; p190 vs. p210 as well as each BCR-ABL1 cell line vs. its parental control. Many of the known BCR-ABL1 associated phosphorylation sites are recapitulated in our dataset. To our knowledge we report the first data on pTyr site-specific differences between p190 and p210 forms within in the same cell type. Surprisingly, 78 pTyr sites are differentially regulated between p190 and p210, with notable examples including pTyr sites on TEC, SHC1, PEAK1, PTPN6 and LYN. Additionally, sites in the kinase domain of JAK2 and the DNA binding domain of STAT6 showed a reciprocal relationship in p190 vs. p210, suggesting the differential involvement of JAK-STAT pathway. Notably, 28 pTyr sites were differentially regulated exclusively in either p190 or p210 BCR-ABL1 Ba/F3 cells, suggesting that there may be signaling pathways unique to p190 and p210, respectively. To attempt to identify direct substrates of BCR-ABL1 and detect differential binding of p190 and p210, we used the BioID system (Roux et al., JBC 2012). In this system, a specialized biotin ligase (BirA) is used to label adjacent or interacting proteins with a biotin moiety on lysine residues. Specifically, Ba/F3 cells transduced with BirA-tagged p190 or untagged p190 were grown in SILAC media and whole cell lysates were subjected streptavidin immunoprecipitation followed by mass spectrometry. Forty-four proteins were enriched over the control and known interactors such as SHC1, DOK2, and GAB1 were detected, along with several putative novel interactors. Combining both the phosphorylation and interactome datasets revealed all these proteins are hyper-phosphorylated compared to parental cell lines, suggesting these are direct substrates or in proximal complexes with p190 BCR-ABL1. A direct comparison of p190 and p210 interactomes using BioID is pending, and will further elucidate potential differences between these important fusion protein isoforms. In sum, our data suggests that p190 and p210 have at least partially independent signaling cascades that are mediated by differential protein-protein interactions, which may help explain the observed association of p190 with BCR-ABL1+ ALL and p210 with CML. Disclosures No relevant conflicts of interest to declare.

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Jung, WooRam, Emma Sierecki, Michele Bastiani, Ailis O’Carroll, Kirill Alexandrov, James Rae, Wayne Johnston, et al. "Cell-free formation and interactome analysis of caveolae." Journal of Cell Biology 217, no. 6 (May 1, 2018): 2141–65. http://dx.doi.org/10.1083/jcb.201707004.

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Caveolae have been linked to the regulation of signaling pathways in eukaryotic cells through direct interactions with caveolins. Here, we describe a cell-free system based on Leishmania tarentolae (Lt) extracts for the biogenesis of caveolae and show its use for single-molecule interaction studies. Insertion of expressed caveolin-1 (CAV1) into Lt membranes was analogous to that of caveolin in native membranes. Electron tomography showed that caveolins generate domains of precise size and curvature. Cell-free caveolae were used in quantitative assays to test the interaction of membrane-inserted caveolin with signaling proteins and to determine the stoichiometry of interactions. Binding of membrane-inserted CAV1 to several proposed binding partners, including endothelial nitric-oxide synthase, was negligible, but a small number of proteins, including TRAF2, interacted with CAV1 in a phosphorylation-(CAV1Y14)–stimulated manner. In cells subjected to oxidative stress, phosphorylated CAV1 recruited TRAF2 to the early endosome forming a novel signaling platform. These findings lead to a novel model for cellular stress signaling by CAV1.

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Baucum, Anthony J., Brian C. Shonesy, Kristie L. Rose, and Roger J. Colbran. "Quantitative Proteomics Analysis of CaMKII Phosphorylation and the CaMKII Interactome in the Mouse Forebrain." ACS Chemical Neuroscience 6, no. 4 (February 24, 2015): 615–31. http://dx.doi.org/10.1021/cn500337u.

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Dreijerink, Koen Marie Anton, Ezgi Ozyerli-Goknar, Stefanie Koidl, Ewoud Van der Lelij, Priscilla Van den Heuvel, Jeffrey Kooijman, Martin Biniossek, Kees Rodenburg, Sheikh Nizamuddin, and Marc Timmers. "LBODP106 Multi-omics Analyses Of MEN1 Missense Mutations Identify Disruption Of Menin-MLL And Menin-JunD Interactions As Critical Requirements For Molecular Pathogenicity." Journal of the Endocrine Society 6, Supplement_1 (November 1, 2022): A865. http://dx.doi.org/10.1210/jendso/bvac150.1788.

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Abstract Loss-of-function mutations of the multiple endocrine neoplasia type 1 (MEN1) gene are causal to the MEN1 endocrine tumor syndrome, but they are also commonly found in sporadic pancreatic neuroendocrine tumors and other types of cancers. The MEN1 gene product, menin, is involved in transcriptional and chromatin regulation, most prominently as an integral component of KMT2A/MLL1 and KMT2B/MLL2 containing COMPASS-like histone H3K4 methyltransferase complexes. In a mutually exclusive fashion, menin also interacts with the JunD subunit of the AP-1 and ATF/CREB transcription factors. After in silico screening of 253 disease-related MEN1 missense mutations, we selected a set of nine menin mutations in surface-exposed residues. The protein interactomes of these mutants were assessed by quantitative mass spectrometry, which indicated that seven of the nine mutants disrupt interactions with both MLL1/2 and JunD complexes. Interestingly, we identified three missense mutations, R52G, E255K and E359K, which predominantly reduce the interaction with MLL1 compared to JunD. This observation was supported by a pronounced loss of binding of the R52G, E255K and E359K mutant proteins at unique MLL1 genomic binding sites with less effect on unique JunD sites. These findings support the general importance of the menin-MLL1 and menin-JunD interactions in MEN1 gene-associated pathogenic conditions. Presentation: No date and time listed

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Giss, Dominic, Simon Kemmerling, Venkata Dandey, Henning Stahlberg, and Thomas Braun. "Exploring the Interactome: Microfluidic Isolation of Proteins and Interacting Partners for Quantitative Analysis by Electron Microscopy." Analytical Chemistry 86, no. 10 (April 28, 2014): 4680–87. http://dx.doi.org/10.1021/ac4027803.

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Bu, Hengtao, Qiang Song, Jiexiu Zhang, Yuang Wei, and Bianjiang Liu. "Development of a Novel KCNN4-Related ceRNA Network and Prognostic Model for Renal Clear Cell Carcinoma." Analytical Cellular Pathology 2023 (January 24, 2023): 1–26. http://dx.doi.org/10.1155/2023/2533992.

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Background. Clear cell renal cell carcinoma (ccRCC) accounts for more than 80% of renal cell carcinomas. Yet, it has not been fully understood about the derivation and progression of the tumor, as well as the long-term benefits from multimodality therapy. Therefore, reliable and applicable molecular markers are urgently needed for the prediction of diagnosis and prognosis of ccRCC patients. Methods. Genetic and clinical information of 533 ccRCC patients from The Cancer Genome Atlas database was collected for comprehensive bioinformatic analyses. UALCAN was used to detect gene expression in paired tumor samples. Two data sets from Gene Expression Omnibus database were analyzed to identify differentially expressed genes (DEGs), and Gene Set Enrichment Analysis was applied for the functional enrichment of DEGs. Tumor Immune Single Cell Hub and Tumor IMmune Estimation Resource databases were separately used for analyses of single-immune cell and immune cell infiltration. Encyclopedia of RNA Interactomes database was explored to predict targeted microRNAs (miRNAs) and corresponding long non-coding RNAs (lncRNAs). Cox regression analysis was performed for the construction of risk signature and prognosis model. Finally, quantitative real-time polymerase chain reaction and western blot were conducted for KCNN4 expression detection in cell lines and clinical samples. Small interfering RNA was employed to knock down KCNN4, and corresponding functional experiments were conducted on ccRCC cells as well. Results. KCNN4 showed elevated expression in tumors and prominent clinical correlation in ccRCC. In total, 41 KCNN4-related genes were enriched, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses showed they were intimately related to immune-related signaling pathways. Spearman’s analysis revealed the significantly positive correlation of KCNN4 with immune cell infiltration. By integrating hub miRNA-let-7e-5p and four critical lncRNA, a competitive endogenous RNA network-based risk signature was constructed. The prognosis model derived from it showed considerable predictive value for survival of ccRCC patients. Finally, in vitro experiments confirmed the remarkable tumor-promoting role of KCNN4 in ccRCC cells. Conclusion. KCNN4 significantly affected the immune status of tumor microenvironment and immunotherapy elements, through which it promoted tumor progression in ccRCC, and it could be a potential biomarker for prognosis and immunotherapy effects of ccRCC patients.

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Jiang, Zheng, Lei Shen, Jie He, Lihui Du, Xin Xia, Longhao Zhang, and Xu Yang. "Functional Analysis of SmMYB39 in Salt Stress Tolerance of Eggplant (Solanum melongena L.)." Horticulturae 9, no. 8 (July 25, 2023): 848. http://dx.doi.org/10.3390/horticulturae9080848.

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Eggplant (Solanum melongena L.), a widely cultivated vegetable of the Solanaceae family, faces significant challenges in growth and yield due to soil salinization. This study aimed to investigate the functional role of the transcription factor SmMYB39 in salt stress tolerance in eggplant. This investigation was conducted through the utilization of bioinformatics analysis, quantitative real-time polymerase chain reaction (qRT-PCR), subcellular localization, validation of transcriptional activation activity, Virus-Induced Gene Silencing (VIGS), and protein interactome analysis. Bioinformatics analysis revealed that SmMYB39 has the closest relationship with SlMYB41, and its promoter contains multiple stress-responsive elements. qRT-PCR results demonstrated that SmMYB39 was significantly upregulated after 12 h of salt stress. Subcellular localization results indicated that the SmMYB39 protein is localized in the nucleus and exhibits transcriptional activation activity. Using VIGS, we observed that silencing of SmMYB39 led to reduced salt stress tolerance in eggplant. In addition, we have conducted research on the protein interactome of SmMYB39. In conclusion, our study demonstrates that SmMYB39 is a crucial transcription factor involved in salt stress response and has the potential to enhance salt tolerance in eggplant.

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Skarra, Dana V., Marilyn Goudreault, Hyungwon Choi, Michael Mullin, Alexey I. Nesvizhskii, Anne-Claude Gingras, and Richard E. Honkanen. "Label-free quantitative proteomics and SAINT analysis enable interactome mapping for the human Ser/Thr protein phosphatase 5." PROTEOMICS 11, no. 8 (February 25, 2011): 1508–16. http://dx.doi.org/10.1002/pmic.201000770.

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Martino, Camillo, Alessio Di Luca, Francesca Bennato, Andrea Ianni, Fabrizio Passamonti, Elisa Rampacci, Michael Henry, Paula Meleady, and Giuseppe Martino. "Label-Free Quantitative Analysis of Pig Liver Proteome after Hepatitis E Virus Infection." Viruses 16, no. 3 (March 6, 2024): 408. http://dx.doi.org/10.3390/v16030408.

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Hepatitis E represents an emerging zoonotic disease caused by the Hepatitis E virus (HEV), for which the main route of transmission is foodborne. In particular, infection in humans has been associated with the consumption of contaminated undercooked meat of pig origin. The aim of this study was to apply comparative proteomics to determine if porcine liver protein profiles could be used to distinguish between pigs seropositive and seronegative for HEV. Preliminarily, an ELISA was used to evaluate the presence of anti-HEV antibodies in the blood serum of 136 animals sent to slaughter. Among the analyzed samples, a seroprevalence of 72.8% was estimated, and it was also possible to identify 10 animals, 5 positive and 5 negative, coming from the same farm. This condition created the basis for the quantitative proteomics comparison between homogeneous animals, in which only the contact with HEV should represent the discriminating factor. The analysis of the proteome in all samples of liver exudate led to the identification of 554 proteins differentially expressed between the two experimental groups, with 293 proteins having greater abundance in positive samples and 261 more represented in negative exudates. The pathway enrichment analysis allowed us to highlight the effect of the interaction between HEV and the host biological system in inducing the potential enrichment of 69 pathways. Among these, carbon metabolism stands out with the involvement of 41 proteins, which were subjected to interactomic analysis. This approach allowed us to focus our attention on three enzymes involved in glycolysis: glucose-6-phosphate isomerase (GPI), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), and fructose-bisphosphate aldolase A (ALDOA). It therefore appears that infection with HEV induced a strengthening of the process, which involves the breakdown of glucose to obtain energy and carbon residues useful for the virus’s survival. In conclusion, the label-free LC-MS/MS approach showed effectiveness in highlighting the main differences induced on the porcine liver proteome by the interaction with HEV, providing crucial information in identifying a viral signature on the host metabolism.

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Yang, Xin, Liqun Lu, Chan Wu, and Feng Zhang. "ATP2B1-AS1 exacerbates sepsis-induced cell apoptosis and inflammation by regulating miR-23a-3p/TLR4 axis." Allergologia et Immunopathologia 51, no. 2 (March 1, 2023): 17–26. http://dx.doi.org/10.15586/aei.v51i2.782.

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Background: Sepsis is a life-threatening disease with dominant mortality. Its early diagnosis and treatment can improve prognosis and reduce mortality. Long noncoding RNAs (lncRNAs) ATPase plasma membrane Ca2+ transporting 1 antisense RNA 1 (ATP2B1-AS1) is dysregulated and is involved in the progression of various diseases. Nevertheless, the role of ATP2B1-AS1 in sepsis remains unclear. Methods: A human monocytic cell line, THP-1 cells, was stimulated to induce a model of sepsis in vitro. The levels of ATP2B1-AS1, miR-23a-3p, and TLR4 were assessed by real-time quantitative polymerase chain reaction. The role of ATP2B1-AS1 in cell apoptosis and inflammation was explored by flow cytometry, Western blot analysis and enzyme-linked immunosorbent serologic assay. The binding sites between ATP2B1-AS1 and miR-23a-3p, and between miR-23a-3p and TLR4 were predicted by BiBiServ and the Encyclopedia of RNA Interactomes (ENCORI) online sites, respectively, and confirmed by the luciferase assay. Results: The level of ATP2B1-AS1 was increased in lipopolysaccharide (LPS)-treated THP-1 cells. LPS increased apoptosis ratio, relative protein expressions of pro-apoptotic factors, and relative messenger RNA (mRNA) level and concentrations of pro-inflammatory cytokines, but decreased the relative expression of anti-apoptosis protein and relative mRNA level and concentrations of anti-inflammatory factor. All these alterations were reversed with transfection of shATP2B1-AS1 into THP-1 cells. Moreover, ATP2B1-AS1 directly bound miR-23a-3p and negatively modulated the level of miR-23a-3p. Meanwhile, TLR4 was directly targeted by miR-23a-3p, and negatively and positively modulated by miR-23a-3p and ATP2B1-AS1, respectively. Conclusion: ATP2B1-AS1 aggravated apoptosis and inflammation by modulating miR-23a-3p/TLR4 axis in LPS-treated THP-1 cells.

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Lobert, Sharon, Mary E. Graichen, Robert D. Hamilton, Karen T. Pitman, Michael R. Garrett, Chindo Hicks, and Tejaswi Koganti. "Prognostic biomarkers for HNSCC using quantitative real-time PCR and microarray analysis: β-tubulin isotypes and the p53 interactome." Cytoskeleton 71, no. 11 (November 2014): 628–37. http://dx.doi.org/10.1002/cm.21195.

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Namboodiri, Saritha, and Alessandro Giuliani. "Looking Into the Binary Interactome of Enterobacteriaceae Family of Bacteria." International Journal of Applied Research in Bioinformatics 9, no. 1 (January 2019): 50–65. http://dx.doi.org/10.4018/ijarb.2019010104.

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Protein-protein interactions (PPIs) regulate most of the biological activities within a cell. A set of pairwise PPIs in seven genera of bacterial pathogens (Salmonella, Escherichia, Shigella, Yersinia, Klebsiella, Photorhabdus, and Pantoea) of Enterobacteriaceae family was analysed. At genotypic level, the correlation coefficient analysis of the mutation spectra of the ten sets of directly interacting protein partners in Escherichia coli recognised all the ‘interacting partners' in Escherichia coli. Extending the correlation analysis to include strains from the rest of the bacterial genera decreased the recognition efficiency providing quantitative evidence that binary interactome have incomplete superposition across species. At phenotype level, a reliable classification of bacterial pathogens was obtained by measuring PPI variations in terms of between phylogenetic distance correlation distances among ten sets of proteins partners. This forces us to rethink upon the possibility of PPI rewiring with a consequent change in physiological role of the same protein.

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Yi, Zhou, Marion Manil-Ségalen, Laila Sago, Annie Glatigny, Virginie Redeker, Renaud Legouis, and Marie-Hélène Mucchielli-Giorgi. "SAFER, an Analysis Method of Quantitative Proteomic Data, Reveals New Interactors of the C. elegans Autophagic Protein LGG-1." Journal of Proteome Research 15, no. 5 (April 6, 2016): 1515–23. http://dx.doi.org/10.1021/acs.jproteome.5b01158.

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Urooj, Tabinda, Bushra Wasim, Shamim Mushtaq, Ghulam Haider, Syed N. N. Shah, Rubina Ghani, and Muhammad F. H. Qureshi. "Increased NID1 Expression among Breast Cancer Lung Metastatic Women; A Comparative Analysis between Naive and Treated Cases." Recent Patents on Anti-Cancer Drug Discovery 15, no. 1 (May 14, 2020): 59–69. http://dx.doi.org/10.2174/1574892815666200302115438.

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Background: Lungs are the second most common reported site of distant metastasis in Breast cancer after bone. Mostly the studies were conducted in cell lines and animal model. To date, there is no blood biomarker reported that could determine the breast cancer progression in terms of lung metastasis. Objective: The aim of this study is to determine Nidogen-1 (NID1)’s mRNA and protein expressions in non-invasive blood samples of breast cancer, in early (II) and lung metastasis advanced stages (III & IV) of naive and treated groups. To determine the functional association of NID1, we employed an in silico analysis, STRING database version 11. Methods: A total of n = 175 cases of breast cancer were recruited in our study. Real time quantitative PCR and ELISA were performed to analyze the mRNA and protein expressions of NID1 respectively. An in silico method is also used to assess NID1’s interactome. Some significant patents related to this topic were also studied and discussed in this research paper. Results: The results show high levels of NID1’s mRNA in the naive group (Group A) as compared to treated group (Group B). Similar trend of increased NID1’s protein expressions was also observed among naive and treated groups, respectively. Our results also show the significant impact of treatment on NID1’s gene and protein expressions. In silico analysis has revealed the functional association of NID1 with its different interactome protein partners. Conclusions: The increased expression of NID1 in early to advanced naive as compared to the treated groups with lung metastasis makes it a promising marker which has pro-metastatic role in breast cancer.

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Kaluzhskiy, L. A., P. V. Ershov, K. S. Kurpedinov, D. S. Sonina, E. O. Yablokov, T. V. Shkel, I. V. Haidukevich, G. V. Sergeev, S. A. Usanov, and A. S. Ivanov. "SPR analysis of protein-protein interactions with P450 cytochromes and cytochrome b5 integrated into lipid membrane." Biomeditsinskaya Khimiya 65, no. 5 (2019): 374–79. http://dx.doi.org/10.18097/pbmc20196505374.

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Identification of new protein-protein interactions (PPI) and characterization of quantitative parameters of complex formation represent one of central tasks of protein interactomics. This work is a logical continuation of the cycle of our previous works devoted to the study of PPIs among the components of cytochrome P450-dependent monooxygenase system. Using an optical biosensor of Surface Plasmon Resonance (SPR biosensor), a comparative analysis on the determination of kinetic and equilibrium parameters of complex formation between the membrane-bound hemoprotein cytochrome b5 with cytochrome P450s was performed using two different protocols for protein immobilization: 1) covalent non-oriented one on to the carboxymethyl dextran chip type CM and 2) non-covalent oriented immobilization in the lipid environment on the chip type L1 with internal control of liposomes surface distribution. In the second protocol it was shown that the complex formation was characterized by 2.5 times higher affinity due to an decrease in rate dissociation constants. The appropriateness of using both experimental models is discussed.

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Rajagopal, Varshni, Astrid-Solveig Loubal, Niklas Engel, Elsa Wassmer, Jeanette Seiler, Oliver Schilling, Maiwen Caudron-Herger, and Sven Diederichs. "Proteome-Wide Identification of RNA-Dependent Proteins in Lung Cancer Cells." Cancers 14, no. 24 (December 12, 2022): 6109. http://dx.doi.org/10.3390/cancers14246109.

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Following the concept of RNA dependence and exploiting its application in the R-DeeP screening approach, we have identified RNA-dependent proteins in A549 lung adenocarcinoma cells. RNA-dependent proteins are defined as proteins whose interactome depends on RNA and thus entails RNA-binding proteins (RBPs) as well as proteins in ribonucleoprotein complexes (RNPs) without direct RNA interaction. With this proteome-wide technique based on sucrose density gradient ultracentrifugation and fractionation followed by quantitative mass spectrometry and bioinformatic analysis, we have identified 1189 RNA-dependent proteins including 170 proteins which had never been linked to RNA before. R-DeeP provides quantitative information on the fraction of a protein being RNA-dependent as well as it allows the reconstruction of protein complexes based on co-segregation. The RNA dependence of three newly identified RNA-dependent proteins, DOCK5, ELMO2, also known as CED12A, and ABRAXAS1, also known as CCDC98, was validated using western blot analysis, and the direct RNA interaction was verified by iCLIP2 for the migration-related protein DOCK5 and the mitosis-related protein ABRAXAS1. The R-DeeP 2.0 database provides proteome-wide and cell line-specific information from A549 and HeLa S3 cells on proteins and their RNA dependence to contribute to understanding the functional role of RNA and RNA-binding proteins in cancer cells.

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Zhang, Weiwen, Feng Li, and Lei Nie. "Integrating multiple ‘omics’ analysis for microbial biology: application and methodologies." Microbiology 156, no. 2 (February 1, 2010): 287–301. http://dx.doi.org/10.1099/mic.0.034793-0.

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Recent advances in various ‘omics’ technologies enable quantitative monitoring of the abundance of various biological molecules in a high-throughput manner, and thus allow determination of their variation between different biological states on a genomic scale. Several popular ‘omics’ platforms that have been used in microbial systems biology include transcriptomics, which measures mRNA transcript levels; proteomics, which quantifies protein abundance; metabolomics, which determines abundance of small cellular metabolites; interactomics, which resolves the whole set of molecular interactions in cells; and fluxomics, which establishes dynamic changes of molecules within a cell over time. However, no single ‘omics’ analysis can fully unravel the complexities of fundamental microbial biology. Therefore, integration of multiple layers of information, the multi-‘omics’ approach, is required to acquire a precise picture of living micro-organisms. In spite of this being a challenging task, some attempts have been made recently to integrate heterogeneous ‘omics’ datasets in various microbial systems and the results have demonstrated that the multi-‘omics’ approach is a powerful tool for understanding the functional principles and dynamics of total cellular systems. This article reviews some basic concepts of various experimental ‘omics’ approaches, recent application of the integrated ‘omics’ for exploring metabolic and regulatory mechanisms in microbes, and advances in computational and statistical methodologies associated with integrated ‘omics’ analyses. Online databases and bioinformatic infrastructure available for integrated ‘omics’ analyses are also briefly discussed.

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James, Rachel, James L. Searcy, Thierry Le Bihan, Sarah F. Martin, Catherine M. Gliddon, Joanne Povey, Ruth F. Deighton, Lorraine E. Kerr, James McCulloch, and Karen Horsburgh. "Proteomic Analysis of Mitochondria in APOE Transgenic Mice and in Response to an Ischemic Challenge." Journal of Cerebral Blood Flow & Metabolism 32, no. 1 (August 31, 2011): 164–76. http://dx.doi.org/10.1038/jcbfm.2011.120.

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Apolipoprotein E (APOE)-ɛ4 is associated with a deleterious outcome after ischemic brain injury, which may involve abnormal regulation of mitochondrial function. We have assessed the mitochondrial proteomic response of APOE-ɛ3 and APOE-ɛ4 transgenic mice to transient global ischemic injury in the hippocampus. A genotype-dependent increase in ApoE levels in mitochondria was observed after ischemia, with APOE-ɛ4 mice showing significantly greater increases than APOE-ɛ3 mice. Quantitative analysis of the mitochondria-enriched fractions was performed using liquid-chromatography mass spectrometry coupled to label-free analysis. Of the 1,067 identified proteins, 274 were mitochondria associated. Mitochondrial protein expression was significantly different between genotypes under basal conditions as well as in response to global ischemia. A total of 12 mitochondrial proteins (including respiratory chain proteins NDUFA11, NDUFS3, NDUF5B, ATP5J, as well as ETFA, CYB5B, ATP6V1A, HSPA1B, OXR1, GLUL, IARS2, and PHYHIPL) were significantly altered with respect to genotype, global ischemia, or their interaction ( P<0.01). A compelling interactome, created using proteins found to be significantly modulated by global ischemia ( P<0.05), involved proteins that regulate energy production and oxidative stress. Thus, APOE genotype has a differential effect on the mitochondrial protein expression in the absence and presence of an injury, which may underlie the differing genotype susceptibility.

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Gole, Boris, and Uroš Potočnik. "Pre-Treatment Biomarkers of Anti-Tumour Necrosis Factor Therapy Response in Crohn’s Disease—A Systematic Review and Gene Ontology Analysis." Cells 8, no. 6 (May 28, 2019): 515. http://dx.doi.org/10.3390/cells8060515.

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The most prominent treatment for the serious cases of Crohn’s disease (CD) are biological tumour necrosis factor (TNF) inhibitors. Unfortunately, therapy nonresponse is still a serious issue in ~1/3 of CD patients. Accurate prediction of responsiveness prior to therapy start would therefore be of great value. Clinical predictors have, however, proved insufficient. Here, we integrate genomic and expression data on potential pre-treatment biomarkers of anti-TNF nonresponse. We show that there is almost no overlap between genomic (annotated with tissue-specific expression quantitative trait loci data) and transcription (RNA and protein data) biomarkers. Furthermore, using interaction networks we demonstrate there is little direct interaction between the proposed biomarkers, though a majority do have common interactors connecting them into networks. Our gene ontology analysis shows that these networks have roles in apoptotic signalling, response to oxidative stress and inflammation pathways. We conclude that a more systematic approach with genome-wide search of genomic and expression biomarkers in the same patients is needed in future studies.

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Kalkhof, Stefan, Stefan Schildbach, Conny Blumert, Friedemann Horn, Martin von Bergen, and Dirk Labudde. "PIPINO: A Software Package to Facilitate the Identification of Protein-Protein Interactions from Affinity Purification Mass Spectrometry Data." BioMed Research International 2016 (2016): 1–13. http://dx.doi.org/10.1155/2016/2891918.

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The functionality of most proteins is regulated by protein-protein interactions. Hence, the comprehensive characterization of the interactome is the next milestone on the path to understand the biochemistry of the cell. A powerful method to detect protein-protein interactions is a combination of coimmunoprecipitation or affinity purification with quantitative mass spectrometry. Nevertheless, both methods tend to precipitate a high number of background proteins due to nonspecific interactions. To address this challenge the software Protein-Protein-Interaction-Optimizer (PIPINO) was developed to perform an automated data analysis, to facilitate the selection of bona fide binding partners, and to compare the dynamic of interaction networks. In this study we investigated the STAT1 interaction network and its activation dependent dynamics. Stable isotope labeling by amino acids in cell culture (SILAC) was applied to analyze the STAT1 interactome after streptavidin pull-down of biotagged STAT1 from human embryonic kidney 293T cells with and without activation. Starting from more than 2,000 captured proteins 30 potential STAT1 interaction partners were extracted. Interestingly, more than 50% of these were already reported or predicted to bind STAT1. Furthermore, 16 proteins were found to affect the binding behavior depending on STAT1 phosphorylation such as STAT3 or the importin subunits alpha 1 and alpha 6.

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Corbo, Vincenzo, Irene Dalai, Maria Scardoni, Stefano Barbi, Stefania Beghelli, Samantha Bersani, Luca Albarello, et al. "MEN1 in pancreatic endocrine tumors: analysis of gene and protein status in 169 sporadic neoplasms reveals alterations in the vast majority of cases." Endocrine-Related Cancer 17, no. 3 (September 2010): 771–83. http://dx.doi.org/10.1677/erc-10-0028.

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Pancreatic endocrine tumors (PETs) may be part of hereditary multiple endocrine neoplasia type 1 (MEN1) syndrome. While MEN1 gene mutation is the only ascertained genetic anomaly described in PETs, no data exist on the cellular localization of MEN1-encoded protein, menin, in normal pancreas and PETs. A total of 169 PETs were used to assess the i) MEN1 gene mutational status in 100 clinically sporadic PETs by direct DNA sequencing, ii) immunohistochemical expression of menin in normal pancreas and 140 PETs, including 71 cases screened for gene mutations, and iii) correlation of these findings with clinical–pathological parameters. Twenty-seven PETs showed mutations that were somatic in 25 patients and revealed to be germline in 2 patients. Menin immunostaining showed strong nuclear and very faint cytoplasmic signal in normal islet cells, whereas it displayed abnormal location and expression levels in 80% of tumors. PETs harboring MEN1 truncating mutations lacked nuclear protein, and most PETs with MEN1 missense mutations showed a strong cytoplasmic positivity for menin. Menin was also misplaced in a significant number of cases lacking MEN1 mutations. In conclusion, the vast majority of PETs showed qualitative and/or quantitative alterations in menin localization. In 30% of cases, this was associated with MEN1 mutations affecting sequences involved in nuclear localization or protein–protein interaction. In cases lacking MEN1 mutations, the alteration of one of the menin interactors may have prevented its proper localization, as suggested by recent data showing that menin protein shuttles between the nucleus and cytoplasm and also affects the subcellular localization of its interactors.

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Wilhelmus, Micha M. M., Elisa Tonoli, Clare Coveney, David J. Boocock, Cornelis A. M. Jongenelen, John J. P. Brevé, Elisabetta A. M. Verderio, and Benjamin Drukarch. "The Transglutaminase-2 Interactome in the APP23 Mouse Model of Alzheimer’s Disease." Cells 11, no. 3 (January 24, 2022): 389. http://dx.doi.org/10.3390/cells11030389.

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Amyloid-beta (Aβ) deposition in the brain is closely linked with the development of Alzheimer’s disease (AD). Unfortunately, therapies specifically targeting Aβ deposition have failed to reach their primary clinical endpoints, emphasizing the need to broaden the search strategy for alternative targets/mechanisms. Transglutaminase-2 (TG2) catalyzes post-translational modifications, is present in AD lesions and interacts with AD-associated proteins. However, an unbiased overview of TG2 interactors is lacking in both control and AD brain. Here we aimed to identify these interactors using a crossbreed of the AD-mimicking APP23 mouse model with wild type and TG2 knock-out (TG2−/−) mice. We found that absence of TG2 had no (statistically) significant effect on Aβ pathology, soluble brain levels of Aβ1–40 and Aβ1–42, and mRNA levels of TG family members compared to APP23 mice at 18 months of age. Quantitative proteomics and network analysis revealed a large cluster of TG2 interactors involved in synaptic transmission/assembly and cell adhesion in the APP23 brain typical of AD. Comparative proteomics of wild type and TG2−/− brains revealed a TG2-linked pathological proteome consistent with alterations in both pathways. Our data show that TG2 deletion leads to considerable network alterations consistent with a TG2 role in (dys)regulation of synaptic transmission and cell adhesion in APP23 brains.

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Basha, Omer, Chanan M. Argov, Raviv Artzy, Yazeed Zoabi, Idan Hekselman, Liad Alfandari, Vered Chalifa-Caspi, and Esti Yeger-Lotem. "Differential network analysis of multiple human tissue interactomes highlights tissue-selective processes and genetic disorder genes." Bioinformatics 36, no. 9 (January 21, 2020): 2821–28. http://dx.doi.org/10.1093/bioinformatics/btaa034.

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Abstract Motivation Differential network analysis, designed to highlight network changes between conditions, is an important paradigm in network biology. However, differential network analysis methods have been typically designed to compare between two conditions and were rarely applied to multiple protein interaction networks (interactomes). Importantly, large-scale benchmarks for their evaluation have been lacking. Results Here, we present a framework for assessing the ability of differential network analysis of multiple human tissue interactomes to highlight tissue-selective processes and disorders. For this, we created a benchmark of 6499 curated tissue-specific Gene Ontology biological processes. We applied five methods, including four differential network analysis methods, to construct weighted interactomes for 34 tissues. Rigorous assessment of this benchmark revealed that differential analysis methods perform well in revealing tissue-selective processes (AUCs of 0.82–0.9). Next, we applied differential network analysis to illuminate the genes underlying tissue-selective hereditary disorders. For this, we curated a dataset of 1305 tissue-specific hereditary disorders and their manifesting tissues. Focusing on subnetworks containing the top 1% differential interactions in disease-relevant tissue interactomes revealed significant enrichment for disorder-causing genes in 18.6% of the cases, with a significantly high success rate for blood, nerve, muscle and heart diseases. Summary Altogether, we offer a framework that includes expansive manually curated datasets of tissue-selective processes and disorders to be used as benchmarks or to illuminate tissue-selective processes and genes. Our results demonstrate that differential analysis of multiple human tissue interactomes is a powerful tool for highlighting processes and genes with tissue-selective functionality and clinical impact. Availability and implementation Datasets are available as part of the Supplementary data. Supplementary information Supplementary data are available at Bioinformatics online.

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Emdal, Kristina B., Anna-Kathrine Pedersen, Dorte B. Bekker-Jensen, Alicia Lundby, Shana Claeys, Katleen De Preter, Frank Speleman, Chiara Francavilla, and Jesper V. Olsen. "Integrated proximal proteomics reveals IRS2 as a determinant of cell survival in ALK-driven neuroblastoma." Science Signaling 11, no. 557 (November 20, 2018): eaap9752. http://dx.doi.org/10.1126/scisignal.aap9752.

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Oncogenic anaplastic lymphoma kinase (ALK) is one of the few druggable targets in neuroblastoma, and therapy resistance to ALK-targeting tyrosine kinase inhibitors (TKIs) comprises an inevitable clinical challenge. Therefore, a better understanding of the oncogenic signaling network rewiring driven by ALK is necessary to improve and guide future therapies. Here, we performed quantitative mass spectrometry–based proteomics on neuroblastoma cells treated with one of three clinically relevant ALK TKIs (crizotinib, LDK378, or lorlatinib) or an experimentally used ALK TKI (TAE684) to unravel aberrant ALK signaling pathways. Our integrated proximal proteomics (IPP) strategy included multiple signaling layers, such as the ALK interactome, phosphotyrosine interactome, phosphoproteome, and proteome. We identified the signaling adaptor protein IRS2 (insulin receptor substrate 2) as a major ALK target and an ALK TKI–sensitive signaling node in neuroblastoma cells driven by oncogenic ALK. TKI treatment decreased the recruitment of IRS2 to ALK and reduced the tyrosine phosphorylation of IRS2. Furthermore, siRNA-mediated depletion of ALK or IRS2 decreased the phosphorylation of the survival-promoting kinase Akt and of a downstream target, the transcription factor FoxO3, and reduced the viability of three ALK-driven neuroblastoma cell lines. Collectively, our IPP analysis provides insight into the proximal architecture of oncogenic ALK signaling by revealing IRS2 as an adaptor protein that links ALK to neuroblastoma cell survival through the Akt-FoxO3 signaling axis.

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Astarita, Jillian L., Shilpa Keerthivasan, Bushra Husain, Yasin Şenbabaoğlu, Erik Verschueren, Sarah Gierke, Victoria C. Pham, et al. "The neutrophil protein CD177 is a novel PDPN receptor that regulates human cancer-associated fibroblast physiology." PLOS ONE 16, no. 12 (December 8, 2021): e0260800. http://dx.doi.org/10.1371/journal.pone.0260800.

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The cancer-associated fibroblast (CAF) marker podoplanin (PDPN) is generally correlated with poor clinical outcomes in cancer patients and thus represents a promising therapeutic target. Despite its biomedical relevance, basic aspects of PDPN biology such as its cellular functions and cell surface ligands remain poorly uncharacterized, thus challenging drug development. Here, we utilize a high throughput platform to elucidate the PDPN cell surface interactome, and uncover the neutrophil protein CD177 as a new binding partner. Quantitative proteomics analysis of the CAF phosphoproteome reveals a role for PDPN in cell signaling, growth and actomyosin contractility, among other processes. Moreover, cellular assays demonstrate that CD177 is a functional antagonist, recapitulating the phenotype observed in PDPN-deficient CAFs. In sum, starting from the unbiased elucidation of the PDPN co-receptome, our work provides insights into PDPN functions and reveals the PDPN/CD177 axis as a possible modulator of fibroblast physiology in the tumor microenvironment.

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Stojanović, Stevan D., Maximilian Fuchs, Jan Fiedler, Ke Xiao, Anna Meinecke, Annette Just, Andreas Pich, Thomas Thum, and Meik Kunz. "Comprehensive Bioinformatics Identifies Key microRNA Players in ATG7-Deficient Lung Fibroblasts." International Journal of Molecular Sciences 21, no. 11 (June 9, 2020): 4126. http://dx.doi.org/10.3390/ijms21114126.

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Background: Deficient autophagy has been recently implicated as a driver of pulmonary fibrosis, yet bioinformatics approaches to study this cellular process are lacking. Autophagy-related 5 and 7 (ATG5/ATG7) are critical elements of macro-autophagy. However, an alternative ATG5/ATG7-independent macro-autophagy pathway was recently discovered, its regulation being unknown. Using a bioinformatics proteome profiling analysis of ATG7-deficient human fibroblasts, we aimed to identify key microRNA (miR) regulators in autophagy. Method: We have generated ATG7-knockout MRC-5 fibroblasts and performed mass spectrometry to generate a large-scale proteomics dataset. We further quantified the interactions between various proteins combining bioinformatics molecular network reconstruction and functional enrichment analysis. The predicted key regulatory miRs were validated via quantitative polymerase chain reaction. Results: The functional enrichment analysis of the 26 deregulated proteins showed decreased cellular trafficking, increased mitophagy and senescence as the major overarching processes in ATG7-deficient lung fibroblasts. The 26 proteins reconstitute a protein interactome of 46 nodes and miR-regulated interactome of 834 nodes. The miR network shows three functional cluster modules around miR-16-5p, miR-17-5p and let-7a-5p related to multiple deregulated proteins. Confirming these results in a biological setting, serially passaged wild-type and autophagy-deficient fibroblasts displayed senescence-dependent expression profiles of miR-16-5p and miR-17-5p. Conclusions: We have developed a bioinformatics proteome profiling approach that successfully identifies biologically relevant miR regulators from a proteomics dataset of the ATG-7-deficient milieu in lung fibroblasts, and thus may be used to elucidate key molecular players in complex fibrotic pathological processes. The approach is not limited to a specific cell-type and disease, thus highlighting its high relevance in proteome and non-coding RNA research.

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Contini, Cristina, Simone Serrao, Barbara Manconi, Alessandra Olianas, Federica Iavarone, Giulia Guadalupi, Irene Messana, et al. "Characterization of Cystatin B Interactome in Saliva from Healthy Elderly and Alzheimer’s Disease Patients." Life 13, no. 3 (March 10, 2023): 748. http://dx.doi.org/10.3390/life13030748.

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Cystatin B is a small, multifunctional protein involved in the regulation of inflammation, innate immune response, and neuronal protection and found highly abundant in the brains of patients with Alzheimer’s disease (AD). Recently, our study demonstrated a significant association between the level of salivary cystatin B and AD. Since the protein is able to establish protein-protein interaction (PPI) in different contexts and aggregation-prone proteins and the PPI networks are relevant for AD pathogenesis, and due to the relevance of finding new AD markers in peripheral biofluids, we thought it was interesting to study the possible involvement of cystatin B in PPIs in saliva and to evaluate differences and similarities between AD and age-matched elderly healthy controls (HC). For this purpose, we applied a co-immunoprecipitation procedure and a bottom-up proteomics analysis to purify, identify, and quantify cystatin B interactors. Results demonstrated for the first time the existence of a salivary cystatin B-linked multi-protein complex composed by 82 interactors and largely expressed in the body. Interactors are involved in neutrophil activation, antimicrobial activity, modulation of the cytoskeleton and extra-cellular matrix (ECM), and glucose metabolism. Preliminary quantitative data showed significantly lower levels of triosophosphate isomerase 1 and higher levels of mucin 7, BPI, and matrix Gla protein in AD with respect to HC, suggesting implications associated with AD of altered glucose metabolism, antibacterial activities, and calcification-associated processes. Data are available via ProteomeXchange with identifiers PXD039286 and PXD030679.

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Ramirez, Oscar, Anil Kesarwani, Gupta Abhishek, Alex C. Minella, and Manoj M. Pillai. "Integrative Analysis of RNA-Interactome and Translatome Reveal Functional Targets of MSI2 in Myeloid Leukemia." Blood 128, no. 22 (December 2, 2016): 1881. http://dx.doi.org/10.1182/blood.v128.22.1881.1881.

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Abstract Musashi 2 (MSI2) is an RNA binding protein (RBP) that regulates asymmetric cell division and cell fate of several cell types including hematopoietic stem and progenitor cells. MSI2 was recently shown to be transcriptionally up-regulated in aggressive myeloid leukemia including chronic myelogenous leukemia in blast crisis (CML-BC) and acute myeloid leukemia (AML). Loss-of-function studies have confirmed an important role for MSI2 in the aggressive biology of these leukemia, but the precise molecular mechanisms remain undefined. MSI2 is thought to bind to the 3' untranslated region (3'UTR) of target mRNA in a sequence-specific fashion and inhibit their translation, but functional targets of MSI2 are not known. We implemented two transcriptome-wide techniques to define these targets: iCLIP (individual nucleotide-resolution cross-link and immunoprecipitation) and polysome profiling. We first defined the RNA interactome of MSI2 in a CML-BC cell line (K562) by iCLIP of FLAG-tagged MSI2. iCLIP relies on the ability of ultraviolet (UV) radiation to cross-link RBPs to interacting RNA allowing for stringent immunoprecipitation of RBP-RNA complexes and subsequent analysis by next generation sequencing. iCLIP analysis revealed direct binding of MSI2 to transcripts of 5036 genes, specifically enriched in the 3'UTR. These iCLIP peaks were also enriched in UAG, the minimal sequence motif of MSI2 previously defined through biochemical assays. Given that MSI2 is ubiquitously expressed, but has very specific cellular functions, we hypothesized that only a small fraction of the direct targets demonstrable by iCLIP are functionally relevant. To determine those target mRNA, we performed translatome profiling of K562 cells (MSI2 knock-down and control cells) with polysome profiling. Polyribosomes or polysomes are aggregates of ribosomes assembled on efficiently translated transcripts. Comparing change in abundance of polysome-associated transcripts (polysome profiling) allows determination of quantitative changes to translation. Using polysome profiling, we found that transcripts from only 413 genes underwent translational up-regulation (without a corresponding change in total transcript abundance) in response to MSI2 knock-down, of which 319 were deemed to be direct MSI2 targets from iCLIP analysis. Translational targets thus defined were highly enriched in biological pathways such as differentiation, cell-cycling, DNA damage response and apoptosis. Specific transcripts thus identified included transcription factors critical to myeloid and leukemia biology (cJUN, MYC and SP1) and cell-cycle regulators (CDK1, CDKN1B, RAD21 and RB1). Using expression profiles of 91 CML patient samples (reported in Radich JP et al PNAS 2006 Feb 21;103(8)) we tested if changes in gene-expression during disease progression (from chronic phase to blast crisis) reflect the change in translation of transcription factors as predicted by the translatome analysis. Accordingly, we found that transcripts down-regulated in CML-BC were highly enriched in targets of JUN and SP1, confirming a primary role for MSI2 targets in progression of CML. In summary, our novel approach that integrates two transcriptome-wide techniques show that while thousands of transcripts are directly bound by MSI2, only a small proportion of these undergo translational repression. Functional targets thus identified include transcription factors and cell-cycle regulators critical to progression of myeloid leukemia. Our results will form the basis of further studies to explore therapeutic targeting of MSI2 in myeloid leukemia. Disclosures No relevant conflicts of interest to declare.

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Cain, Margo P., Belinda J. Hernandez, and Jichao Chen. "Quantitative single-cell interactomes in normal and virus-infected mouse lungs." Disease Models & Mechanisms 13, no. 6 (May 27, 2020): dmm044404. http://dx.doi.org/10.1242/dmm.044404.

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N. M., Prashant, Hongyu Liu, Pavlos Bousounis, Liam Spurr, Nawaf Alomran, Helen Ibeawuchi, Justin Sein, Dacian Reece-Stremtan, and Anelia Horvath. "Estimating the Allele-Specific Expression of SNVs From 10× Genomics Single-Cell RNA-Sequencing Data." Genes 11, no. 3 (February 25, 2020): 240. http://dx.doi.org/10.3390/genes11030240.

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With the recent advances in single-cell RNA-sequencing (scRNA-seq) technologies, the estimation of allele expression from single cells is becoming increasingly reliable. Allele expression is both quantitative and dynamic and is an essential component of the genomic interactome. Here, we systematically estimate the allele expression from heterozygous single nucleotide variant (SNV) loci using scRNA-seq data generated on the 10×Genomics Chromium platform. We analyzed 26,640 human adipose-derived mesenchymal stem cells (from three healthy donors), sequenced to an average of 150K sequencing reads per cell (more than 4 billion scRNA-seq reads in total). High-quality SNV calls assessed in our study contained approximately 15% exonic and >50% intronic loci. To analyze the allele expression, we estimated the expressed variant allele fraction (VAFRNA) from SNV-aware alignments and analyzed its variance and distribution (mono- and bi-allelic) at different minimum sequencing read thresholds. Our analysis shows that when assessing positions covered by a minimum of three unique sequencing reads, over 50% of the heterozygous SNVs show bi-allelic expression, while at a threshold of 10 reads, nearly 90% of the SNVs are bi-allelic. In addition, our analysis demonstrates the feasibility of scVAFRNA estimation from current scRNA-seq datasets and shows that the 3′-based library generation protocol of 10×Genomics scRNA-seq data can be informative in SNV-based studies, including analyses of transcriptional kinetics.

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Persico, Maria. "Systematic Analysis of Interactomes in Sequence Properties Space." Current Bioinformatics 8, no. 3 (May 1, 2013): 315–27. http://dx.doi.org/10.2174/1574893611308030007.

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Drummond, Eleanor, Geoffrey Pires, Claire MacMurray, Manor Askenazi, Shruti Nayak, Marie Bourdon, Jiri Safar, Beatrix Ueberheide, and Thomas Wisniewski. "Phosphorylated tau interactome in the human Alzheimer’s disease brain." Brain 143, no. 9 (August 19, 2020): 2803–17. http://dx.doi.org/10.1093/brain/awaa223.

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Abstract Accumulation of phosphorylated tau is a key pathological feature of Alzheimer’s disease. Phosphorylated tau accumulation causes synaptic impairment, neuronal dysfunction and formation of neurofibrillary tangles. The pathological actions of phosphorylated tau are mediated by surrounding neuronal proteins; however, a comprehensive understanding of the proteins that phosphorylated tau interacts with in Alzheimer’s disease is surprisingly limited. Therefore, the aim of this study was to determine the phosphorylated tau interactome. To this end, we used two complementary proteomics approaches: (i) quantitative proteomics was performed on neurofibrillary tangles microdissected from patients with advanced Alzheimer’s disease; and (ii) affinity purification-mass spectrometry was used to identify which of these proteins specifically bound to phosphorylated tau. We identified 542 proteins in neurofibrillary tangles. This included the abundant detection of many proteins known to be present in neurofibrillary tangles such as tau, ubiquitin, neurofilament proteins and apolipoprotein E. Affinity purification-mass spectrometry confirmed that 75 proteins present in neurofibrillary tangles interacted with PHF1-immunoreactive phosphorylated tau. Twenty-nine of these proteins have been previously associated with phosphorylated tau, therefore validating our proteomic approach. More importantly, 34 proteins had previously been associated with total tau, but not yet linked directly to phosphorylated tau (e.g. synaptic protein VAMP2, vacuolar-ATPase subunit ATP6V0D1); therefore, we provide new evidence that they directly interact with phosphorylated tau in Alzheimer’s disease. In addition, we also identified 12 novel proteins, not previously known to be physiologically or pathologically associated with tau (e.g. RNA binding protein HNRNPA1). Network analysis showed that the phosphorylated tau interactome was enriched in proteins involved in the protein ubiquitination pathway and phagosome maturation. Importantly, we were able to pinpoint specific proteins that phosphorylated tau interacts with in these pathways for the first time, therefore providing novel potential pathogenic mechanisms that can be explored in future studies. Combined, our results reveal new potential drug targets for the treatment of tauopathies and provide insight into how phosphorylated tau mediates its toxicity in Alzheimer’s disease.

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Kumar, Raman, Karthik S. Kamath, Luke Carroll, Peter Hoffmann, Jozef Gecz, and Lachlan A. Jolly. "Endogenous protein interactomes resolved through immunoprecipitation-coupled quantitative proteomics in cell lines." STAR Protocols 3, no. 4 (December 2022): 101693. http://dx.doi.org/10.1016/j.xpro.2022.101693.

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Poorgholi Belverdi, Mohammad, Carola Krause, Asja Guzman, and Petra Knaus. "Comprehensive analysis of TGF-β and BMP receptor interactomes." European Journal of Cell Biology 91, no. 4 (April 2012): 287–93. http://dx.doi.org/10.1016/j.ejcb.2011.05.004.

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Kruse, Kevin, Jeff Klomp, Mitchell Sun, Zhang Chen, Dianicha Santana, Fei Huang, Pinal Kanabar, Mark Maienschein-Cline, and Yulia A. Komarova. "Analysis of biological networks in the endothelium with biomimetic microsystem platform." American Journal of Physiology-Lung Cellular and Molecular Physiology 317, no. 3 (September 1, 2019): L392—L401. http://dx.doi.org/10.1152/ajplung.00392.2018.

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Here we describe a novel method for studying the protein “interactome” in primary human cells and apply this method to investigate the effect of posttranslational protein modifications (PTMs) on the protein’s functions. We created a novel “biomimetic microsystem platform” (Bio-MSP) to isolate the protein complexes in primary cells by covalently attaching purified His-tagged proteins to a solid microscale support. Using this Bio-MSP, we have analyzed the interactomes of unphosphorylated and phosphomimetic end-binding protein-3 (EB3) in endothelial cells. Pathway analysis of these interactomes demonstrated the novel role of EB3 phosphorylation at serine 162 in regulating the protein’s function. We showed that phosphorylation “switches” the EB3 biological network to modulate cellular processes such as cell-to-cell adhesion whereas dephosphorylation of this site promotes cell proliferation. This novel technique provides a useful tool to study the role of PTMs or single point mutations in activating distinct signal transduction networks and thereby the biological function of the protein in health and disease.

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Wang, Li-Jie, Chia-Wei Hsu, Chiu-Chin Chen, Ying Liang, Lih-Chyang Chen, David M. Ojcius, Ngan-Ming Tsang, Chuen Hsueh, Chih-Ching Wu, and Yu-Sun Chang. "Interactome-wide Analysis Identifies End-binding Protein 1 as a Crucial Component for the Speck-like Particle Formation of Activated Absence in Melanoma 2 (AIM2) Inflammasomes." Molecular & Cellular Proteomics 11, no. 11 (August 6, 2012): 1230–44. http://dx.doi.org/10.1074/mcp.m112.020594.

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Inflammasomes are cytoplasmic receptors that can recognize intracellular pathogens or danger signals and are critical for interleukin 1β production. Although several key components of inflammasome activation have been identified, there has not been a systematic analysis of the protein components found in the stimulated complex. In this study, we used the isobaric tags for relative and absolute quantification approach to systemically analyze the interactomes of the NLRP3, AIM2, and RIG-I inflammasomes in nasopharyngeal carcinoma cells treated with specific stimuli of these interactomes (H2O2, poly (dA:dT), and EBV noncoding RNA, respectively). We identified a number of proteins that appeared to be involved in the interactomes and also could be precipitated with anti-apoptosis-associated speck-like protein containing caspase activation and recruitment domain antibodies after stimulation. Among them, end binding protein 1 was an interacting component in all three interactomes. Silencing of end binding protein 1 expression by small interfering RNA inhibited the activation of the three inflammasomes, as indicated by reduced levels of interleukin 1β secretion. We confirmed that end binding protein 1 directly interacted with AIM2 and ASC in vitro and in vivo. Most importantly, fluorescence confocal microscopy showed that end binding protein 1 was required for formation of the speck-like particles that represent activation of the AIM2 inflammasome. In nasopharyngeal carcinoma tissues, immunohistochemical staining showed that end binding protein 1 expression was elevated and significantly correlated with AIM2 and ASC expression in nasopharyngeal carcinoma tumor cells. In sum, we profiled the interactome components of three inflammasomes and show for the first time that end binding protein 1 is crucial for the speck-like particle formation that represents activated inflammasomes.

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Zheng, Lu-Lu, Chunyan Li, Jie Ping, Yanhong Zhou, Yixue Li, and Pei Hao. "The Domain Landscape of Virus-Host Interactomes." BioMed Research International 2014 (2014): 1–13. http://dx.doi.org/10.1155/2014/867235.

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Viral infections result in millions of deaths in the world today. A thorough analysis of virus-host interactomes may reveal insights into viral infection and pathogenic strategies. In this study, we presented a landscape of virus-host interactomes based on protein domain interaction. Compared to the analysis at protein level, this domain-domain interactome provided a unique abstraction of protein-protein interactome. Through comparisons among DNA, RNA, and retrotranscribing viruses, we identified a core of human domains, that viruses used to hijack the cellular machinery and evade the immune system, which might be promising antiviral drug targets. We showed that viruses preferentially interacted with host hub and bottleneck domains, and the degree and betweenness centrality among three categories of viruses are significantly different. Further analysis at functional level highlighted that different viruses perturbed the host cellular molecular network by common and unique strategies. Most importantly, we creatively proposed a viral disease network among viral domains, human domains and the corresponding diseases, which uncovered several unknown virus-disease relationships that needed further verification. Overall, it is expected that the findings will help to deeply understand the viral infection and contribute to the development of antiviral therapy.

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Andrew, Robert J., Kate Fisher, Kate J. Heesom, Katherine A. B. Kellett, and Nigel M. Hooper. "Quantitative interaction proteomics reveals differences in the interactomes of amyloid precursor protein isoforms." Journal of Neurochemistry 149, no. 3 (February 14, 2019): 399–412. http://dx.doi.org/10.1111/jnc.14666.

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Truman, Andrew W., Kolbrun Kristjansdottir, Donald Wolfgeher, Natalia Ricco, Anoop Mayampurath, Samuel L. Volchenboum, Josep Clotet, and Stephen J. Kron. "The quantitative changes in the yeast Hsp70 and Hsp90 interactomes upon DNA damage." Data in Brief 2 (March 2015): 12–15. http://dx.doi.org/10.1016/j.dib.2014.10.006.

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Journal articles on the topic 'Quantitative analysis of interactomes'

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