Corynebacterium Glutamicum Regulation beyond Transcription: Organizing Principles and Reconstruction of an Extended Regulatory Network Incorporating Regulations Mediated by Small Rna and Protein-Protein Interactions

Corynebacterium glutamicum is a Gram-positive bacterium found in soil where the condition changes demand plasticity of the regulatory interactions, which study at the global scale has been challenged by the lack of data integration. Here, we update the manually-curated C. glutamicum transcriptional regulatory network, now including protein-protein interactions having a direct effect on gene transcription. The network model with regulations supported by any experimental evidence increased by 557 interactions regarding the previous (2018) version. 73 interactions supported by directed experiments were also included in a second model. We included 545 sRNA-mediated regulations in a third model with a total of 5164 interactions. We deposited the three network models in Abasy Atlas v2.4. We study the C. glutamicum regulatory structure by comparing it against the networks for more than 40 species, finding it to contrast in several global structural properties. We analyze the system-level components of the networks, finding that the inclusion of the sRNAs regulations changes their proportions, transferring part of the basal machinery to the modular class and increasing the number of modules while decreasing their size. Finally, we use strong networks of three model organisms to provide insights in future directions of the C. glutamicum network characterization.

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Corynebacterium glutamicum Regulation beyond Transcription: Organizing Principles and Reconstruction of an Extended Regulatory Network Incorporating Regulations Mediated by Small RNA and Protein–Protein Interactions

Microorganisms ◽

10.3390/microorganisms9071395 ◽

2021 ◽

Vol 9 (7) ◽

pp. 1395

Author(s):

Juan M. Escorcia-Rodríguez ◽

Andreas Tauch ◽

Julio A. Freyre-González

Keyword(s):

Corynebacterium Glutamicum ◽

Protein Interactions ◽

Regulatory Network ◽

Regulatory Networks ◽

Network Models ◽

Global Scale ◽

System Level ◽

Model Organisms ◽

Protein Protein Interactions ◽

Regulatory Structure

Corynebacterium glutamicum is a Gram-positive bacterium found in soil where the condition changes demand plasticity of the regulatory machinery. The study of such machinery at the global scale has been challenged by the lack of data integration. Here, we report three regulatory network models for C. glutamicum: strong (3040 interactions) constructed solely with regulations previously supported by directed experiments; all evidence (4665 interactions) containing the strong network, regulations previously supported by nondirected experiments, and protein–protein interactions with a direct effect on gene transcription; sRNA (5222 interactions) containing the all evidence network and sRNA-mediated regulations. Compared to the previous version (2018), the strong and all evidence networks increased by 75 and 1225 interactions, respectively. We analyzed the system-level components of the three networks to identify how they differ and compared their structures against those for the networks of more than 40 species. The inclusion of the sRNA-mediated regulations changed the proportions of the system-level components and increased the number of modules but decreased their size. The C. glutamicum regulatory structure contrasted with other bacterial regulatory networks. Finally, we used the strong networks of three model organisms to provide insights and future directions of the C.glutamicum regulatory network characterization.

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Corynebacterium glutamicum regulation beyond transcription: Organizing principles and reconstruction of an extended regulatory network incorporating regulations mediated by small RNA and protein-protein interactions

10.1101/2021.01.07.423633 ◽

2021 ◽

Author(s):

Juan Miguel Escorcia-Rodríguez ◽

Andreas Tauch ◽

Julio Augusto Freyre-González

Keyword(s):

Corynebacterium Glutamicum ◽

Protein Interactions ◽

Regulatory Network ◽

Regulatory Networks ◽

Network Models ◽

Global Scale ◽

System Level ◽

Model Organisms ◽

Protein Protein Interactions ◽

Regulatory Structure

Corynebacterium glutamicum is a Gram-positive bacterium found in soil where the condition changes demand plasticity of the regulatory machinery. The study of such machinery at the global scale has been challenged by the lack of data integration. Here, we report three regulatory network models for C. glutamicum: strong (3040 interactions) constructed solely with regulations previously supported by directed experiments; all evidence (4665 interactions) containing the strong network, regulations previously supported by non-directed experiments, and protein-protein interactions with a direct effect on gene transcription; and sRNA (5222 interactions) containing the all evidence network and sRNA-mediated regulations. Compared to the previous version (2018), the strong and all evidence networks increased by 75 and 1225 interactions, respectively. We analyzed the system-level components of the three networks to identify how they differ and compared their structures against those for the networks of more than 40 species. The inclusion of the sRNAs regulations changed the proportions of the system-level components and increased the number of modules but decreased their size. The C. glutamicum regulatory structure contrasted with other bacterial regulatory networks. Finally, we used the strong networks of three model organisms to provide insights and future directions of the C. glutamicum regulatory network characterization.

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The tapeworm interactome: inferring confidence scored protein-protein interactions from the proteome of Hymenolepis microstoma

10.1101/668988 ◽

2019 ◽

Cited By ~ 1

Author(s):

Katherine James ◽

Peter D. Olson

Keyword(s):

Transcription Factors ◽

Protein Interaction ◽

Protein Interactions ◽

System Level ◽

Model Organisms ◽

Phylogenetic Distance ◽

Interaction Data ◽

Protein Protein Interactions ◽

Gene Models ◽

Hymenolepis Microstoma

AbstractReference genome and transcriptome assemblies of helminths have reached a level of completion whereby secondary analyses that rely on accurate gene estimation or syntenic relationships can be now conducted with a high level of confidence. Recent public release of the v.3 assembly of the mouse bile-duct tapeworm, Hymenolepis microstoma, provides chromosome-level characterisation of the genome and a stabilised set of protein coding gene models underpinned by both bioinformatic and empirical data. However, interactome data have not been produced. Conserved protein-protein interactions in other organisms, termed interologs, can be used to transfer interactions between species, allowing systems-level analysis in non-model organisms. Here, we describe a probabilistic, integrated network of interologs for the H. microstoma proteome, based on conserved protein interactions found in eukaryote model species. Almost a third of the 10,139 gene models in the v.3 assembly could be assigned interaction data and assessment of the resulting network indicates that topologically-important proteins are related to essential cellular pathways, and that the network clusters into biologically meaningful components. Moreover, network parameters are similar to those of single-species interaction networks that we constructed in the same way for S. cerevisiae, C. elegans and H. sapiens, demonstrating that information-rich, system-level analyses can be conducted even on species separated by a large phylogenetic distance from the major model organisms from which most protein interaction evidence is based. Using the interolog network, we then focused on sub-networks of interactions assigned to discrete suites of genes of interest, including signalling components and transcription factors, germline ‘multipotency’ genes, and differentially-expressed genes between larval and adult worms. These analyses not only showed an expected bias toward highly-conserved proteins, such as components of intracellular signal transduction, but in some cases predicted interactions with transcription factors that aid in identifying their target genes. With the completion of key helminth genomes, such systems level analyses can provide an important predictive framework to guide basic and applied research on helminths and will become increasingly informative as protein-protein interaction data accumulate.

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An Improved Phenotype-Driven Tool for Rare Mendelian Variant Prioritization: Benchmarking Exomiser on Real Patient Whole-Exome Data

Genes ◽

10.3390/genes11040460 ◽

2020 ◽

Vol 11 (4) ◽

pp. 460

Author(s):

Valentina Cipriani ◽

Nikolas Pontikos ◽

Gavin Arno ◽

Panagiotis I. Sergouniotis ◽

Eva Lenassi ◽

...

Keyword(s):

Molecular Diagnosis ◽

Protein Interactions ◽

Model Organisms ◽

Protein Protein Interactions ◽

Sequencing Data ◽

Variant Prioritization ◽

Real Patient ◽

Human Phenotype ◽

Support Tool ◽

Variant Frequency

Next-generation sequencing has revolutionized rare disease diagnostics, but many patients remain without a molecular diagnosis, particularly because many candidate variants usually survive despite strict filtering. Exomiser was launched in 2014 as a Java tool that performs an integrative analysis of patients’ sequencing data and their phenotypes encoded with Human Phenotype Ontology (HPO) terms. It prioritizes variants by leveraging information on variant frequency, predicted pathogenicity, and gene-phenotype associations derived from human diseases, model organisms, and protein–protein interactions. Early published releases of Exomiser were able to prioritize disease-causative variants as top candidates in up to 97% of simulated whole-exomes. The size of the tested real patient datasets published so far are very limited. Here, we present the latest Exomiser version 12.0.1 with many new features. We assessed the performance using a set of 134 whole-exomes from patients with a range of rare retinal diseases and known molecular diagnosis. Using default settings, Exomiser ranked the correct diagnosed variants as the top candidate in 74% of the dataset and top 5 in 94%; not using the patients’ HPO profiles (i.e., variant-only analysis) decreased the performance to 3% and 27%, respectively. In conclusion, Exomiser is an effective support tool for rare Mendelian phenotype-driven variant prioritization.

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A massively parallel barcoded sequencing pipeline enables generation of the first ORFeome and interactome map for rice

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1918068117 ◽

2020 ◽

Vol 117 (21) ◽

pp. 11836-11842 ◽

Cited By ~ 1

Author(s):

Shayne D. Wierbowski ◽

Tommy V. Vo ◽

Pascal Falter-Braun ◽

Timothy O. Jobe ◽

Lars H. Kruse ◽

...

Keyword(s):

Protein Interactions ◽

Massively Parallel ◽

Model Organisms ◽

Protein Protein Interactions ◽

Numerous Model ◽

High Quality Protein ◽

Protein Interactome ◽

Wide Range ◽

Dna Elements ◽

General Tool

Systematic mappings of protein interactome networks have provided invaluable functional information for numerous model organisms. Here we developPCR-mediatedLinkage of barcodedAdaptersTo nucleic acidElements forsequencing (PLATE-seq) that serves as a general tool to rapidly sequence thousands of DNA elements. We validate its utility by generating the ORFeome forOryza sativacovering 2,300 genes and constructing a high-quality protein–protein interactome map consisting of 322 interactions between 289 proteins, expanding the known interactions in rice by roughly 50%. Our work paves the way for high-throughput profiling of protein–protein interactions in a wide range of organisms.

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Regulative interactions of the osmosensing C-terminal domain in the trimeric glycine betaine transporter BetP from Corynebacterium glutamicum

Biological Chemistry ◽

10.1515/bc.2009.068 ◽

2009 ◽

Vol 390 (8) ◽

Cited By ~ 10

Author(s):

Reinhard Krämer ◽

Christine Ziegler

Keyword(s):

Amino Acid ◽

Corynebacterium Glutamicum ◽

Protein Interactions ◽

Regulation Mechanism ◽

Protein Protein Interactions ◽

Molecular Switching ◽

X Ray ◽

X Ray Crystallography ◽

Terminal Domain ◽

Domain Reorientation

Abstract Activation of the osmoregulated trimeric betaine transporter BetP from Corynebacterium glutamicum was shown to depend mainly on the correct folding and integrity of its 55 amino acid long, partly α-helical C-terminal domain. Reorientation of the three C-terminal domains in the BetP trimer indicates different lipid-protein and protein-protein interactions of the C-terminal domain during osmoregulation. A regulation mechanism is suggested where this domain switches the transporter from the inactive to the active state. Interpretation of recently obtained electron and X-ray crystallography data of BetP led to a structure-function based model of C-terminal molecular switching involved in osmoregulation.

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Conserved Central Intraviral Protein Interactome of the Herpesviridae Family

mSystems ◽

10.1128/msystems.00295-19 ◽

2019 ◽

Vol 4 (5) ◽

Cited By ~ 1

Author(s):

Anna Hernández Durán ◽

Kay Grünewald ◽

Maya Topf

Keyword(s):

Protein Interactions ◽

Computational Models ◽

Functional Organization ◽

Driving Forces ◽

Protein Complexes ◽

Structural Features ◽

System Level ◽

Protein Protein Interactions ◽

Protein Interactome ◽

Essential Components

ABSTRACT Protein interactions are major driving forces behind the functional phenotypes of biological processes. As such, evolutionary footprints are reflected in system-level collections of protein-protein interactions (PPIs), i.e., protein interactomes. We conducted a comparative analysis of intraviral protein interactomes for representative species of each of the three subfamilies of herpesviruses (herpes simplex virus 1, human cytomegalovirus, and Epstein-Barr virus), which are highly prevalent etiologic agents of important human diseases. The intraviral interactomes were reconstructed by combining experimentally supported and computationally predicted protein-protein interactions. Using cross-species network comparison, we then identified family-wise conserved interactions and protein complexes, which we defined as a herpesviral “central” intraviral protein interactome. A large number of widely accepted conserved herpesviral protein complexes are present in this central intraviral interactome, encouragingly supporting the biological coherence of our results. Importantly, these protein complexes represent most, if not all, of the essential steps required during a productive life cycle. Hence the central intraviral protein interactome could plausibly represent a minimal infectious interactome of the herpesvirus family across a variety of hosts. Our data, which have been integrated into our herpesvirus interactomics database, HVint2.0, could assist in creating comprehensive system-level computational models of this viral lineage. IMPORTANCE Herpesviruses are an important socioeconomic burden for both humans and livestock. Throughout their long evolutionary history, individual herpesvirus species have developed remarkable host specificity, while collectively the Herpesviridae family has evolved to infect a large variety of eukaryotic hosts. The development of approaches to fight herpesvirus infections has been hampered by the complexity of herpesviruses’ genomes, proteomes, and structural features. The data and insights generated by our study add to the understanding of the functional organization of herpesvirus-encoded proteins, specifically of family-wise conserved features defining essential components required for a productive infectious cycle across different hosts, which can contribute toward the conceptualization of antiherpetic infection strategies with an effect on a broader range of target species. All of the generated data have been made freely available through our HVint2.0 database, a dedicated resource of curated herpesvirus interactomics purposely created to promote and assist future studies in the field.

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Conservation and Variability of Synaptonemal Complex Proteins in Phylogenesis of Eukaryotes

International Journal of Evolutionary Biology ◽

10.1155/2014/856230 ◽

2014 ◽

Vol 2014 ◽

pp. 1-16 ◽

Cited By ~ 20

Author(s):

Tatiana M. Grishaeva ◽

Yuri F. Bogdanov

Keyword(s):

Synaptonemal Complex ◽

Protein Interactions ◽

Phylogenetic Trees ◽

Flowering Plants ◽

Model Organisms ◽

Protein Protein Interactions ◽

Lateral Element ◽

Origin And Evolution ◽

Eukaryotic Proteomes ◽

Related Proteins

The problems of the origin and evolution of meiosis include the enigmatic variability of the synaptonemal complexes (SCs) which, being morphology similar, consist of different proteins in different eukaryotic phyla. Using bioinformatics methods, we monitored all available eukaryotic proteomes to find proteins similar to known SC proteins of model organisms. We found proteins similar to SC lateral element (LE) proteins and possessing the HORMA domain in the majority of the eukaryotic taxa and assume them the most ancient among all SC proteins. Vertebrate LE proteins SYCP2, SYCP3, and SC65 proved to have related proteins in many invertebrate taxa. Proteins of SC central space are most evolutionarily variable. It means that different protein-protein interactions can exist to connect LEs. Proteins similar to the known SC proteins were not found in Euglenophyta, Chrysophyta, Charophyta, Xanthophyta, Dinoflagellata, and primitive Coelomata. We conclude that different proteins whose common feature is the presence of domains with a certain conformation are involved in the formation of the SC in different eukaryotic phyla. This permits a targeted search for orthologs of the SC proteins using phylogenetic trees. Here we consider example of phylogenetic trees for protozoans, fungi, algae, mosses, and flowering plants.

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NGPINT: A Next-generation protein-protein interaction software

10.1101/2020.09.11.277483 ◽

2020 ◽

Cited By ~ 1

Author(s):

Sagnik Banerjee ◽

Valeria Velásquez-Zapata ◽

Gregory Fuerst ◽

J. Mitch Elmore ◽

Roger P. Wise

Keyword(s):

Protein Interactions ◽

Model Organisms ◽

Cdna Libraries ◽

Published Data ◽

Data Sets ◽

Next Generation ◽

Protein Protein Interactions ◽

Protein Protein Interaction ◽

Alternative Approach ◽

Simulated Test

ABSTRACTMapping protein-protein interactions at a proteome scale is critical to understanding how cellular signaling networks respond to stimuli. Since eukaryotic genomes encode thousands of proteins, testing their interactions one-by-one is a challenging prospect. High-throughput yeast-two hybrid (Y2H) assays that employ next-generation sequencing to interrogate cDNA libraries represent an alternative approach that optimizes scale, cost, and effort. We present NGPINT, a robust and scalable software to identify all putative interactors of a protein using Y2H in batch culture. NGPINT combines diverse tools to align sequence reads to target genomes, reconstruct prey fragments and compute gene enrichment under reporter selection. Central to this pipeline is the identification of fusion reads containing sequences derived from both the Y2H expression plasmid and the cDNA of interest. To reduce false positives, these fusion reads are evaluated as to whether the cDNA fragment forms an in-frame translational fusion with the Y2H transcription factor. NGPINT successfully recognized 95% of interactions in simulated test runs. As proof of concept, NGPINT was tested using published data sets and recognized all validated interactions. NGPINT can be used in any organism with an available reference, thus facilitating the discovery of protein-protein interactions in non-model organisms.

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Expanding Interactome Analyses beyond Model Eukaryotes

10.20944/preprints202110.0185.v1 ◽

2021 ◽

Author(s):

Katherine James ◽

Anil Wipat ◽

Simon Cockell

Keyword(s):

Genome Sequence ◽

Protein Interactions ◽

Model Organisms ◽

Protein Protein Interactions ◽

Data Types ◽

Interaction Prediction ◽

Diverse Species ◽

Eukaryotic Species

Interactome analyses have traditionally been applied to yeast, human and other model organisms due to the availability of protein-protein interactions data for these species. Recently these techniques have been applied to more diverse species using computational interaction prediction from genome sequence and other data types. This review describes the various types of computational interactome networks that can be created and how they have been used in diverse eukaryotic species, highlighting some of the key interactome studies in non-model organisms.

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