Misfolded species of superoxide dismutase 1 (SOD1) are associated with increased death in amyotrophic lateral sclerosis (ALS) models compared to insoluble protein aggregates. The mechanism by which structurally independent SOD1 trimers cause cellular toxicity is unknown but may drive disease pathology. Here, we uncovered the SOD1 trimer interactome-a map of potential tissue-selective protein-binding partners in the brain, spinal cord, and skeletal muscle. We identified binding partners and key pathways associated with SOD1 trimers and found that trimers may affect normal cellular functions such as dendritic spine morphogenesis and synaptic function in the central nervous system and cellular metabolism in skeletal muscle. We discovered SOD1 trimer-selective enrichment of genes. We performed detailed computational and biochemical characterization of SOD1 trimer protein binding for septin-7. Our investigation highlights key proteins and pathways within distinct tissues, revealing a plausible intersection of genetic and pathophysiological mechanisms in ALS through interactions involving SOD1 trimers.

Autophagy initiation is regulated by the ULK1 kinase complex. To gain insights into functions of the holo-complex, we generated a deep interactome by combining affinity purification- and proximity labeling-mass spectrometry of all four complex members: ULK1, ATG13, ATG101, and RB1CC1/FIP200. Under starvation conditions, the ULK1 complex interacts with several protein and lipid kinases and phosphatases, implying the formation of a signalosome. Interestingly, several selective autophagy receptors also interact with ULK1, indicating the activation of selective autophagy pathways by nutrient starvation. One effector of the ULK1 complex is the HSC/HSP70 co-chaperone BAG2, which regulates the subcellular localization of the VPS34 lipid kinase complex member AMBRA1. Depending on the nutritional status, BAG2 has opposing roles. In growth conditions, the unphosphorylated form of BAG2 sequesters AMBRA1, attenuating autophagy induction. In starvation conditions, ULK1 phosphorylates BAG2 on Ser31, which supports the recruitment of AMBRA1 to the ER membrane, positively affecting autophagy.

One of the most recent advances in the analysis of viral RNA-cellular protein interactions is the Comprehensive Identification of RNA-binding Proteins by Mass Spectrometry (ChIRP-MS). Here, we used ChIRP-MS in mock-infected and Zika-infected wild-type cells and cells knockout for the zinc finger CCCH-type antiviral protein 1 (ZAP). We characterized \'ZAP-independent\' and \'ZAP-dependent\' cellular protein interactomes associated with flavivirus RNA and found that ZAP affects cellular proteins associated with Zika virus RNA. The ZAP-dependent interactome identified with ChIRP-MS provides potential ZAP co-factors for antiviral activity against Zika virus and possibly other viruses. Identifying the full spectrum of ZAP co-factors and mechanisms of how they act will be critical to understanding the ZAP antiviral system and may contribute to the development of antivirals.

Growing evidence supports the transcription of enhancer RNAs (eRNAs) and their important roles in gene regulation. However, their interactions with other biomolecules and their corresponding functionality remain poorly understood. In an attempt to facilitate mechanistic research, this study presents eRNA-IDO, the first integrative computational platform for the identification, interactome discovery, and functional annotation of human eRNAs. eRNA-IDO comprises two modules: eRNA-ID and eRNA-Anno. Functionally, eRNA-ID can identify eRNAs from de novo assembled transcriptomes. eRNA-ID includes 8 kinds of enhancer makers, enabling users to customize enhancer regions flexibly and conveniently. In addition, eRNA-Anno provides cell-specific/tissue-specific functional annotation for both new and known eRNAs by analyzing the eRNA interactome from prebuilt or user-defined networks between eRNA and coding gene. The prebuilt networks include the Genotype-Tissue Expression (GTEx)-based co-expression networks in normal tissues, The Cancer Genome Atlas (TCGA)-based co-expression networks in cancer tissues, and omics-based eRNA-centric regulatory networks. eRNA-IDO can facilitate research on the biogenesis and functions of eRNAs. The eRNA-IDO server is freely available at http://bioinfo.szbl.ac.cn/eRNA_IDO/.

Network inference or reconstruction algorithms play an integral role in successfully analyzing and identifying causal relationships between omics hits for detecting dysregulated and altered signaling components in various contexts, encompassing disease states and drug perturbations. However, accurate representation of signaling networks and identification of context-specific interactions within sparse omics datasets in complex interactomes pose significant challenges in integrative approaches. To address these challenges, we present pyPARAGON (PAgeRAnk-flux on Graphlet-guided network for multi-Omic data integratioN), a novel tool that combines network propagation with graphlets. pyPARAGON enhances accuracy and minimizes the inclusion of nonspecific interactions in signaling networks by utilizing network rather than relying on pairwise connections among proteins. Through comprehensive evaluations on benchmark signaling pathways, we demonstrate that pyPARAGON outperforms state-of-the-art approaches in node propagation and edge inference. Furthermore, pyPARAGON exhibits promising performance in discovering cancer driver networks. Notably, we demonstrate its utility in network-based stratification of patient tumors by integrating phosphoproteomic data from 105 breast cancer tumors with the interactome and demonstrating tumor-specific signaling pathways. Overall, pyPARAGON is a novel tool for analyzing and integrating multi-omic data in the context of signaling networks. pyPARAGON is available at https://github.com/netlab-ku/pyPARAGON.

The human immunodeficiency virus (HIV-1) is highly dependent on a variety of host factors. Beside proteins, host RNA molecules are reported to aid HIV-1 replication and latency maintenance. Here, we implement multiple workflows of native RNA immunoprecipitation and sequencing (nRIPseq) to determine direct host RNA interaction partners of all 18 HIV-1 (poly)proteins. We identify 1,727 HIV-1 protein - human RNA interactions in the Jurkat cell line and 1,558 interactions in SupT1 cells for a subset of proteins, and discover distinct cellular pathways that seem to be used or controlled by HIV-1 on the RNA level: Tat binds mRNAs of proteins involved in the super elongation complex (AFF1-4, Cyclin-T1). Correlation of the interaction scores (based on binding abundancy) allows identifying the highest confidence interactions, for which we perform a small-scale knockdown screen that leads to the identification of three HIV-1 protein binding RNA interactors involved in HIV-1 replication (AFF2, H4C9 and RPLP0).

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The sensitivity of phosphorylation site identification by mass spectrometry (MS)-based phosphoproteomics has improved significantly. However, the lack of kinase-substrate relationship (KSR) data has hindered improvement of the range and accuracy of kinase activity prediction using phosphoproteome data. We herein describe the application of a systematic identification of KSR by integrated phosphoproteome and interactome analysis using doxycycline (Dox)-induced target kinase-overexpressing HEK-293 cells.

Hepatitis B virus (HBV) infects hepatocytes that are in the G0/G1 phase with intact nuclear membrane and organized chromosome architecture. In the nucleus of the infected cells, HBV covalently closed circular (ccc) DNA, an episomal minichromosome, serves as the template for all viral transcripts and the reservoir of persistent infection. Nuclear positioning of cccDNA can be assessed by the spatial distance between viral DNA and host chromosomal DNA through Circular Chromosome Conformation Capture (4C) combined with high-throughput sequencing (4C-seq). The 4C-seq analysis relies on proximity ligation and is commonly used for mapping genomic DNA regions that communicate within a host chromosome. The method has been tailored for studying nuclear localization of HBV episomal cccDNA in relation to the host chromosomes. In this study, we present a step-by-step protocol for 4C-seq analysis of HBV infection, including sample collection and fixation, 4C DNA library preparation, sequence library preparation, and data analysis. Although limited by proximity ligation of DNA fragments, 4C-seq analysis provides useful information of HBV localization in 3D genome, and aids the understanding of viral transcription in light of host chromatin conformation.

UNASSIGNED: Betel nut/areca nut/Areca catechu is one of the most commonly used psychoactive substance, and is also a major preventable cause of cancer. Unlike other psychoactive substances, such as nicotine, the mechanisms underlying addiction to areca nuts and related oncogenesis remain elusive. Recent reports suggest a possible overlap in the mechanisms of action of nicotine and areca nuts in the human body. Thus, this study aimed to investigate the interactome of human proteins associated with areca nut exposure and the intricate similarities and differences in the effects of the two psychoactive substances on humans.
UNASSIGNED: A list of proteins associated with areca nut use was obtained from the available literature using terms from Medical Subject Headings (MeSH). Protein-protein interaction (PPI) networks and functional enrichment were analyzed. The results obtained for both psychoactive substances were compared.
UNASSIGNED: Given the limited number of common proteins (36/226, 16%) in the two sets, a substantial overlap (612/1176 nodes, 52%) was observed in the PPI networks, as well as in Gene Ontology. Areca nuts mainly affect signaling pathways through three hub proteins (alpha serine/threonine-protein kinase, tumor protein 53, and interleukin-6), which are common to both psychoactive substances, as well as two unique hub proteins (epidermal growth factor receptor and master regulator of cell cycle entry and proliferative metabolism). Areca nut-related proteins are associated with unique pathways, such as extracellular matrix organization, lipid storage, and metabolism, which are not found in nicotine-associated proteins.
UNASSIGNED: Areca nuts affect regulatory mechanisms, leading to systemic toxicity and oncogenesis. Areca nuts also affect unique pathways that can be studied as potential markers of exposure, as well as targets for anticancer therapeutic agents.