Integrative analysis identified common and unique molecular signatures in hepatobiliary cancers

Hepatobiliary cancers (HBCs) are the most aggressive and sixth most diagnosed cancers globally. Biomarkers for timely diagnosis and targeted therapy in HBCs are still limited. Considering the gap, our objective is to identify unique and overlapping molecular signatures associated with HBCs. We analyzed publicly available transcriptomic datasets on Gallbladder cancer (GBC), Hepatocellular carcinoma (HCC), and Intrahepatic cholangiocarcinoma (ICC) to identify potential biomarkers using integrative systems approaches. An effective Common and Unique Molecular Signature Identification (CUMSI) approach has been employed, which contains analysis of differential gene expression (DEG), gene co-expression networks (GCN), and protein-protein interactions (PPIs) networks. Functional analysis of the DEGs unique for GBC, HCC, and ICC indicated that GBC is associated with cellular processes, HCC is associated with immune signaling pathways, and ICC is associated with lipid metabolic pathways. Our findings shows that the hub genes and pathways identified for each individual cancer type of the HBS are related with the primary function of each organ and each cancer exhibit unique expression patterns despite being part of the same organ system.

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Shared Blood Transcriptomic Signatures between Alzheimer’s Disease and Diabetes Mellitus

Biomedicines ◽

10.3390/biomedicines9010034 ◽

2021 ◽

Vol 9 (1) ◽

pp. 34

Author(s):

Taesic Lee ◽

Hyunju Lee

Keyword(s):

Diabetes Mellitus ◽

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Protein Interactions ◽

Expression Patterns ◽

Protein Protein Interactions ◽

Hub Genes ◽

Gene Modules ◽

Gene Regulatory ◽

The Brain

Alzheimer’s disease (AD) and diabetes mellitus (DM) are known to have a shared molecular mechanism. We aimed to identify shared blood transcriptomic signatures between AD and DM. Blood expression datasets for each disease were combined and a co-expression network was used to construct modules consisting of genes with similar expression patterns. For each module, a gene regulatory network based on gene expression and protein-protein interactions was established to identify hub genes. We selected one module, where COPS4, PSMA6, GTF2B, GTF2F2, and SSB were identified as dysregulated transcription factors that were common between AD and DM. These five genes were also differentially co-expressed in disease-related tissues, such as the brain in AD and the pancreas in DM. Our study identified gene modules that were dysregulated in both AD and DM blood samples, which may contribute to reveal common pathophysiology between two diseases.

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Roles of the 14-3-3 gene family in cotton flowering

BMC Plant Biology ◽

10.1186/s12870-021-02923-9 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Na Sang ◽

Hui Liu ◽

Bin Ma ◽

Xianzhong Huang ◽

Lu Zhuo ◽

...

Keyword(s):

Gene Family ◽

Protein Interactions ◽

Leucine Zipper ◽

Expression Patterns ◽

Bimolecular Fluorescence Complementation ◽

Structural Motif ◽

Virus Induced Gene Silencing ◽

Protein Protein Interactions ◽

Basic Leucine Zipper ◽

Genome Wide

Abstract Background In plants, 14-3-3 proteins, also called GENERAL REGULATORY FACTORs (GRFs), encoded by a large multigene family, are involved in protein–protein interactions and play crucial roles in various physiological processes. No genome-wide analysis of the GRF gene family has been performed in cotton, and their functions in flowering are largely unknown. Results In this study, 17, 17, 31, and 17 GRF genes were identified in Gossypium herbaceum, G. arboreum, G. hirsutum, and G. raimondii, respectively, by genome-wide analyses and were designated as GheGRFs, GaGRFs, GhGRFs, and GrGRFs, respectively. A phylogenetic analysis revealed that these proteins were divided into ε and non-ε groups. Gene structural, motif composition, synteny, and duplicated gene analyses of the identified GRF genes provided insights into the evolution of this family in cotton. GhGRF genes exhibited diverse expression patterns in different tissues. Yeast two-hybrid and bimolecular fluorescence complementation assays showed that the GhGRFs interacted with the cotton FLOWERING LOCUS T homologue GhFT in the cytoplasm and nucleus, while they interacted with the basic leucine zipper transcription factor GhFD only in the nucleus. Virus-induced gene silencing in G. hirsutum and transgenic studies in Arabidopsis demonstrated that GhGRF3/6/9/15 repressed flowering and that GhGRF14 promoted flowering. Conclusions Here, 82 GRF genes were identified in cotton, and their gene and protein features, classification, evolution, and expression patterns were comprehensively and systematically investigated. The GhGRF3/6/9/15 interacted with GhFT and GhFD to form florigen activation complexs that inhibited flowering. However, GhGRF14 interacted with GhFT and GhFD to form florigen activation complex that promoted flowering. The results provide a foundation for further studies on the regulatory mechanisms of flowering.

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Structure, Function, Involvement in Diseases and Targeting of 14-3-3 Proteins: An Update

Current Medicinal Chemistry ◽

10.2174/0929867324666170426095015 ◽

2018 ◽

Vol 25 (1) ◽

pp. 5-21 ◽

Cited By ~ 25

Author(s):

Ylenia Cau ◽

Daniela Valensin ◽

Mattia Mori ◽

Sara Draghi ◽

Maurizio Botta

Keyword(s):

Protein Interactions ◽

Molecular Mechanisms ◽

Physiological Role ◽

Specific Protein ◽

Protein Protein Interactions ◽

Cellular Processes ◽

Protein Partners ◽

High Sequence Homology ◽

Small Molecule Modulators

14-3-3 is a class of proteins able to interact with a multitude of targets by establishing protein-protein interactions (PPIs). They are usually found in all eukaryotes with a conserved secondary structure and high sequence homology among species. 14-3-3 proteins are involved in many physiological and pathological cellular processes either by triggering or interfering with the activity of specific protein partners. In the last years, the scientific community has collected many evidences on the role played by seven human 14-3-3 isoforms in cancer or neurodegenerative diseases. Indeed, these proteins regulate the molecular mechanisms associated to these diseases by interacting with (i) oncogenic and (ii) pro-apoptotic proteins and (iii) with proteins involved in Parkinson and Alzheimer diseases. The discovery of small molecule modulators of 14-3-3 PPIs could facilitate complete understanding of the physiological role of these proteins, and might offer valuable therapeutic approaches for these critical pathological states.

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Visual detection of binary, ternary, and quaternary protein interactions in fission yeast by Pil1 co-tethering assay

Journal of Cell Science ◽

10.1242/jcs.258774 ◽

2021 ◽

Author(s):

Zhong-Qiu Yu ◽

Xiao-Man Liu ◽

Dan Zhao ◽

Dan-Dan Xu ◽

Li-Lin Du

Keyword(s):

Fission Yeast ◽

Protein Interactions ◽

Visual Detection ◽

Protein Protein Interactions ◽

Phosphatidylinositol 3 Kinase ◽

Basic Form ◽

Bait Protein ◽

Cellular Processes ◽

Prey Protein ◽

Versatile Tool

Protein-protein interactions are vital for executing nearly all cellular processes. To facilitate the detection of protein-protein interactions in living cells of the fission yeast Schizosaccharomyces pombe, here we present an efficient and convenient method termed the Pil1 co-tethering assay. In its basic form, we tether a bait protein to mCherry-tagged Pil1, which forms cortical filamentary structures, and examine whether a GFP-tagged prey protein colocalizes with the bait. We demonstrate that this assay is capable of detecting pairwise protein-protein interactions of cytosolic proteins and nuclear proteins. Furthermore, we show that this assay can be used for detecting not only binary protein-protein interactions, but also ternary and quaternary protein-protein interactions. Using this assay, we systematically characterized the protein-protein interactions in the Atg1 complex and in the phosphatidylinositol 3-kinase (PtdIns3K) complexes and found that Atg38 is incorporated into the PtdIns3K complex I via an Atg38-Vps34 interaction. Our data show that this assay is a useful and versatile tool and should be added to the routine toolbox of fission yeast researchers.

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Protein–protein interactions in bacteria: a promising and challenging avenue towards the discovery of new antibiotics

Beilstein Journal of Organic Chemistry ◽

10.3762/bjoc.14.267 ◽

2018 ◽

Vol 14 ◽

pp. 2881-2896 ◽

Cited By ~ 7

Author(s):

Laura Carro

Keyword(s):

Protein Interactions ◽

Bacterial Infections ◽

Multidrug Resistant ◽

Resistant Bacteria ◽

Protein Protein Interactions ◽

Lead Discovery ◽

Antibiotic Development ◽

Cellular Processes ◽

Ppi Networks ◽

New Antibiotics

Antibiotics are potent pharmacological weapons against bacterial infections; however, the growing antibiotic resistance of microorganisms is compromising the efficacy of the currently available pharmacotherapies. Even though antimicrobial resistance is not a new problem, antibiotic development has failed to match the growth of resistant pathogens and hence, it is highly critical to discover new anti-infective drugs with novel mechanisms of action which will help reducing the burden of multidrug-resistant microorganisms. Protein–protein interactions (PPIs) are involved in a myriad of vital cellular processes and have become an attractive target to treat diseases. Therefore, targeting PPI networks in bacteria may offer a new and unconventional point of intervention to develop novel anti-infective drugs which can combat the ever-increasing rate of multidrug-resistant bacteria. This review describes the progress achieved towards the discovery of molecules that disrupt PPI systems in bacteria for which inhibitors have been identified and whose targets could represent an alternative lead discovery strategy to obtain new anti-infective molecules.

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Assay Systems for Profiling Deubiquitinating Activity

International Journal of Molecular Sciences ◽

10.3390/ijms21165638 ◽

2020 ◽

Vol 21 (16) ◽

pp. 5638

Author(s):

Jinhong Cho ◽

Jinyoung Park ◽

Eunice EunKyeong Kim ◽

Eun Joo Song

Keyword(s):

Protein Degradation ◽

Protein Interactions ◽

Live Cells ◽

Deubiquitinating Enzyme ◽

Protein Protein Interactions ◽

Deubiquitinating Enzymes ◽

Cell Lysates ◽

Cellular Processes

Deubiquitinating enzymes regulate various cellular processes, particularly protein degradation, localization, and protein–protein interactions. The dysregulation of deubiquitinating enzyme (DUB) activity has been linked to several diseases; however, the function of many DUBs has not been identified. Therefore, the development of methods to assess DUB activity is important to identify novel DUBs, characterize DUB selectivity, and profile dynamic DUB substrates. Here, we review various methods of evaluating DUB activity using cell lysates or purified DUBs, as well as the types of probes used in these methods. In addition, we introduce some techniques that can deliver DUB probes into the cells and cell-permeable activity-based probes to directly visualize and quantify DUB activity in live cells. This review could contribute to the development of DUB inhibitors by providing important information on the characteristics and applications of various probes used to evaluate and detect DUB activity in vitro and in vivo.

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Deep learning based prediction of reversible HAT/HDAC-specific lysine acetylation

Briefings in Bioinformatics ◽

10.1093/bib/bbz107 ◽

2019 ◽

Vol 21 (5) ◽

pp. 1798-1805 ◽

Cited By ~ 1

Author(s):

Kai Yu ◽

Qingfeng Zhang ◽

Zekun Liu ◽

Yimeng Du ◽

Xinjiao Gao ◽

...

Keyword(s):

Deep Learning ◽

Protein Interactions ◽

Web Server ◽

Data Sets ◽

Lysine Acetylation ◽

Protein Acetylation ◽

Protein Protein Interactions ◽

Cellular Processes ◽

Protein Lysine Acetylation ◽

Specific Regulation

Abstract Protein lysine acetylation regulation is an important molecular mechanism for regulating cellular processes and plays critical physiological and pathological roles in cancers and diseases. Although massive acetylation sites have been identified through experimental identification and high-throughput proteomics techniques, their enzyme-specific regulation remains largely unknown. Here, we developed the deep learning-based protein lysine acetylation modification prediction (Deep-PLA) software for histone acetyltransferase (HAT)/histone deacetylase (HDAC)-specific acetylation prediction based on deep learning. Experimentally identified substrates and sites of several HATs and HDACs were curated from the literature to generate enzyme-specific data sets. We integrated various protein sequence features with deep neural network and optimized the hyperparameters with particle swarm optimization, which achieved satisfactory performance. Through comparisons based on cross-validations and testing data sets, the model outperformed previous studies. Meanwhile, we found that protein–protein interactions could enrich enzyme-specific acetylation regulatory relations and visualized this information in the Deep-PLA web server. Furthermore, a cross-cancer analysis of acetylation-associated mutations revealed that acetylation regulation was intensively disrupted by mutations in cancers and heavily implicated in the regulation of cancer signaling. These prediction and analysis results might provide helpful information to reveal the regulatory mechanism of protein acetylation in various biological processes to promote the research on prognosis and treatment of cancers. Therefore, the Deep-PLA predictor and protein acetylation interaction networks could provide helpful information for studying the regulation of protein acetylation. The web server of Deep-PLA could be accessed at http://deeppla.cancerbio.info.

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Distinct p53 acetylation cassettes differentially influence gene-expression patterns and cell fate

The Journal of Cell Biology ◽

10.1083/jcb.200512059 ◽

2006 ◽

Vol 173 (4) ◽

pp. 533-544 ◽

Cited By ~ 171

Author(s):

Chad D. Knights ◽

Jason Catania ◽

Simone Di Giovanni ◽

Selen Muratoglu ◽

Ricardo Perez ◽

...

Keyword(s):

Gene Expression ◽

Cell Fate ◽

Protein Interactions ◽

Posttranslational Modifications ◽

Biological Activities ◽

Expression Profiles ◽

Expression Patterns ◽

Gene Expression Profiles ◽

P53 Gene ◽

Protein Protein Interactions

The activity of the p53 gene product is regulated by a plethora of posttranslational modifications. An open question is whether such posttranslational changes act redundantly or dependently upon one another. We show that a functional interference between specific acetylated and phosphorylated residues of p53 influences cell fate. Acetylation of lysine 320 (K320) prevents phosphorylation of crucial serines in the NH2-terminal region of p53; only allows activation of genes containing high-affinity p53 binding sites, such as p21/WAF; and promotes cell survival after DNA damage. In contrast, acetylation of K373 leads to hyperphosphorylation of p53 NH2-terminal residues and enhances the interaction with promoters for which p53 possesses low DNA binding affinity, such as those contained in proapoptotic genes, leading to cell death. Further, acetylation of each of these two lysine clusters differentially regulates the interaction of p53 with coactivators and corepressors and produces distinct gene-expression profiles. By analogy with the “histone code” hypothesis, we propose that the multiple biological activities of p53 are orchestrated and deciphered by different “p53 cassettes,” each containing combination patterns of posttranslational modifications and protein–protein interactions.

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Systematic identification of signal integration by protein kinase A

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1409938112 ◽

2015 ◽

Vol 112 (14) ◽

pp. 4501-4506 ◽

Cited By ~ 37

Author(s):

Marie Filteau ◽

Guillaume Diss ◽

Francisco Torres-Quiroz ◽

Alexandre K. Dubé ◽

Andrea Schraffl ◽

...

Keyword(s):

Protein Kinase ◽

Protein Kinase A ◽

Protein Interactions ◽

Carbon Sources ◽

Biological Processes ◽

Protein Protein Interactions ◽

Cellular Processes ◽

Protein Complex Formation ◽

Growth And Aging ◽

Kinase A

Cellular processes and homeostasis control in eukaryotic cells is achieved by the action of regulatory proteins such as protein kinase A (PKA). Although the outbound signals from PKA directed to processes such as metabolism, growth, and aging have been well charted, what regulates this conserved regulator remains to be systematically identified to understand how it coordinates biological processes. Using a yeast PKA reporter assay, we identified genes that influence PKA activity by measuring protein–protein interactions between the regulatory and the two catalytic subunits of the PKA complex in 3,726 yeast genetic-deletion backgrounds grown on two carbon sources. Overall, nearly 500 genes were found to be connected directly or indirectly to PKA regulation, including 80 core regulators, denoting a wide diversity of signals regulating PKA, within and beyond the described upstream linear pathways. PKA regulators span multiple processes, including the antagonistic autophagy and methionine biosynthesis pathways. Our results converge toward mechanisms of PKA posttranslational regulation by lysine acetylation, which is conserved between yeast and humans and that, we show, regulates protein complex formation in mammals and carbohydrate storage and aging in yeast. Taken together, these results show that the extent of PKA input matches with its output, because this kinase receives information from upstream and downstream processes, and highlight how biological processes are interconnected and coordinated by PKA.

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Identification and characterization of interactions between the vertebrate polycomb-group protein BMI1 and human homologs of polyhomeotic.

Molecular and Cellular Biology ◽

10.1128/mcb.17.4.2326 ◽

1997 ◽

Vol 17 (4) ◽

pp. 2326-2335 ◽

Cited By ~ 107

Author(s):

M J Gunster ◽

D P Satijn ◽

K M Hamer ◽

J L den Blaauwen ◽

D de Bruijn ◽

...

Keyword(s):

Protein Interactions ◽

Expression Patterns ◽

Polycomb Group ◽

Polycomb Group Protein ◽

Protein Protein Interactions ◽

Human Proteins ◽

Group Protein ◽

The Individual ◽

Domain I ◽

Homology Domains

In Drosophila melanogaster, the Polycomb-group (PcG) genes have been identified as repressors of gene expression. They are part of a cellular memory system that is responsible for the stable transmission of gene activity to progeny cells. PcG proteins form a large multimeric, chromatin-associated protein complex, but the identity of its components is largely unknown. Here, we identify two human proteins, HPH1 and HPH2, that are associated with the vertebrate PcG protein BMI1. HPH1 and HPH2 coimmunoprecipitate and cofractionate with each other and with BMI1. They also colocalize with BMI1 in interphase nuclei of U-2 OS human osteosarcoma and SW480 human colorectal adenocarcinoma cells. HPH1 and HPH2 have little sequence homology with each other, except in two highly conserved domains, designated homology domains I and II. They share these homology domains I and II with the Drosophila PcG protein Polyhomeotic (Ph), and we, therefore, have named the novel proteins HPH1 and HPH2. HPH1, HPH2, and BMI1 show distinct, although overlapping expression patterns in different tissues and cell lines. Two-hybrid analysis shows that homology domain II of HPH1 interacts with both homology domains I and II of HPH2. In contrast, homology domain I of HPH1 interacts only with homology domain II of HPH2, but not with homology domain I of HPH2. Furthermore, BMI1 does not interact with the individual homology domains. Instead, both intact homology domains I and II need to be present for interactions with BMI1. These data demonstrate the involvement of homology domains I and II in protein-protein interactions and indicate that HPH1 and HPH2 are able to heterodimerize.

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