Functional gene networks based on the gene neighborhood in metagenomes

Kim, Chan Yeong; Lee, Insuk

doi:10.1080/19768354.2017.1382388

Cited by 8 publications

(6 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Thus, we generated two functional networks using probability- and distance-based measures of gene neighborhood. We also found that distance-based gene neighborhoods across metagenomes correlated with functional associations (32). We could infer two functional networks by gene neighborhood analysis using 754 human microbiomes (27) and 242 ocean metagenomes (28).…”

Section: Network Database Improvementmentioning

confidence: 79%

HumanNet v2: human gene networks for disease research

Hwang

Kim

Yang

et al. 2018

Nucleic Acids Research

Self Cite

184

152

View full text Add to dashboard Cite

Human gene networks have proven useful in many aspects of disease research, with numerous network-based strategies developed for generating hypotheses about gene-disease-drug associations. The ability to predict and organize genes most relevant to a specific disease has proven especially important. We previously developed a human functional gene network, HumanNet, by integrating diverse types of omics data using Bayesian statistics framework and demonstrated its ability to retrieve disease genes. Here, we present HumanNet v2 (http://www.inetbio.org/humannet), a database of human gene networks, which was updated by incorporating new data types, extending data sources and improving network inference algorithms. HumanNet now comprises a hierarchy of human gene networks, allowing for more flexible incorporation of network information into studies. HumanNet performs well in ranking disease-linked gene sets with minimal literature-dependent biases. We observe that incorporating model organisms’ protein–protein interactions does not markedly improve disease gene predictions, suggesting that many of the disease gene associations are now captured directly in human-derived datasets. With an improved interactive user interface for disease network analysis, we expect HumanNet will be a useful resource for network medicine.

show abstract

Section: Network Database Improvementmentioning

confidence: 79%

HumanNet v2: human gene networks for disease research

Hwang

Kim

Yang

et al. 2018

Nucleic Acids Research

Self Cite

184

152

View full text Add to dashboard Cite

show abstract

“…It has been proposed that proteins that are functionally related tend to be encoded in close proximity to each other on the genome (31)(32)(33)(34)(35). Identifying genes in the neighborhood of the gene of interest that are conserved across various species can be a helpful inference of potential physical interactions and functional relationships among them (31)(32)(33)(34)(35). To identify a potential interacting partner of PrbP Las , the genomic context of prbP Las was examined using the Joint Genome Institute (JGI) IMG genome viewer and SEED (Markowitz et al [36]).…”

Section: Resultsmentioning

confidence: 99%

The Ferredoxin-Like Protein FerR Regulates PrbP Activity in Liberibacter asiaticus

Ling

Silva

Pagliai

et al. 2019

Appl Environ Microbiol

View full text Add to dashboard Cite

In Liberibacter asiaticus, PrbP is an important transcriptional accessory protein that regulates gene expression through interactions with the RNA polymerase β-subunit and a specific sequence on the promoter region. The constitutive expression of prbP observed upon chemical inactivation of PrbP-DNA interactions in vivo indicated that the expression of prbP was not autoregulated at the level of transcription. This observation suggested that a modulatory mechanism via protein-protein interactions may be involved. In silico genome association analysis identified FerR (CLIBASIA_01505), a putative ferredoxin-like protein, as a PrbP-interacting protein. Using a bacterial two-hybrid system and immunoprecipitation assays, interactions between PrbP and FerR were confirmed. In vitro transcription assays were used to show that FerR can increase the activity of PrbP by 16-fold when present in the PrbP-RNA polymerase reaction mixture. The FerR protein-protein interaction surface was predicted by structural modeling and followed by site-directed mutagenesis. Amino acids V20, V23, and C40 were identified as the most important residues in FerR involved in the modulation of PrbP activity in vitro. The regulatory mechanism of FerR abundance was examined at the transcription level. In contrast to prbP of L. asiaticus (prbPLas), mRNA levels of ferR of L. asiaticus (ferRLas) are induced by an increase in osmotic pressure. The results of this study revealed that the activity of the transcriptional activator PrbPLas is modulated via interactions with FerRLas. The induction of ferRLas expression by osmolarity provides insight into the mechanisms of adjusting gene expression in response to host environmental signals in L. asiaticus. IMPORTANCE The rapid spread and aggressive progression of huanglongbing (HLB) in the major citrus-producing areas have raised global recognition of and vigilance to this disease. As a result, the causative agent, Liberibacter asiaticus, has been investigated from various perspectives. However, gene expression regulatory mechanisms that are important for the survival and persistence of this intracellular pathogen remain largely unexplored. PrbP is a transcriptional accessory protein important for L. asiaticus survival in the plant host. In this study, we investigated the interactions between PrbP in L. asiaticus (PrbPLas) and a ferredoxin-like protein (FerR) in L. asiaticus, FerRLas. We show that the presence of FerR stabilizes and augments the activity of PrbPLas. In addition, we demonstrate that the expression of ferR is induced by increases in osmolarity in Liberibacter crescens. Altogether, these results suggest that FerRLas and PrbPLas may play important roles in the regulation of gene expression in response to changing environmental signals during L. asiaticus infection in the citrus host.

show abstract

“…We inferred cofunctional links based on the gene neighborhood across the 1,747 archaeal and bacterial genomes with two complementary measures of gene neighborhood: distance-based measures and probability-based measures (18). In addition, a metagenome-based gene neighborhood method (38) was used for KlebNet. We utilized contig sequences from the Human Microbiome Project (39) and TARA Ocean Project (40).…”

Section: Methodsmentioning

confidence: 99%

Network Integrative Genomic and Transcriptomic Analysis of Carbapenem-Resistant Klebsiella pneumoniae Strains Identifies Genes for Antibiotic Resistance and Virulence

et al. 2019

Self Cite

View full text Add to dashboard Cite

Global increases in the use of carbapenems have resulted in several strains of Gram-negative bacteria acquiring carbapenem resistance, thereby limiting treatment options. Klebsiella pneumoniae is a common carbapenem-resistant pathogenic bacterium that is widely studied to identify novel antibiotic resistance mechanisms and drug targets. Antibiotic-resistant clinical isolates generally harbor many genetic alterations, and the identification of responsible mutations would provide insights into the molecular mechanisms of antibiotic resistance. We propose a method to prioritize mutated genes responsible for antibiotic resistance on the basis of expression changes in their local subnetworks, hypothesizing that mutated genes that show significant expression changes among the corresponding functionally associated genes are more likely to be involved in the carbapenem resistance. For network-based gene prioritization, we developed KlebNet (www.inetbio.org/klebnet), a genome-scale cofunctional network of K. pneumoniae genes. Using KlebNet, we reconstructed the functional modules for carbapenem resistance and virulence and identified the functional association between antibiotic resistance and virulence. Using complementation assays with the top candidate genes, we were able to validate a novel gene that negatively regulated carbapenem resistance and four novel genes that positively regulated virulence in Galleria mellonella larvae. Therefore, our study demonstrated the feasibility of network-based identification of genes required for antibiotic resistance and virulence of human-pathogenic bacteria. IMPORTANCE Klebsiella pneumoniae is a major bacterial pathogen that causes pneumonia and urinary tract infections in human. K. pneumoniae infections are treated with carbapenem, but carbapenem-resistant K. pneumoniae has been spreading worldwide. We are able to identify antimicrobial-resistant genes among mutated genes of the antibiotic-resistant clinical isolates. However, they usually harbor many mutated genes, including those that cause weak or neutral functional effects. Therefore, we need to prioritize the mutated genes to identify the more likely candidates for the follow-up functional analysis. For this study, we present a functional network of K. pneumoniae genes and propose a network-based method of prioritizing the mutated genes of the resistant clinical isolates. We also reconstructed the network-based functional modules for carbapenem resistance and virulence and retrieved the functional association between antibiotic resistance and virulence. This study demonstrated the feasibility of network-based analysis of clinical genomics data for the study of K. pneumoniae infection.

show abstract

Functional gene networks based on the gene neighborhood in metagenomes

Cited by 8 publications

References 20 publications

HumanNet v2: human gene networks for disease research

HumanNet v2: human gene networks for disease research

The Ferredoxin-Like Protein FerR Regulates PrbP Activity in Liberibacter asiaticus

Network Integrative Genomic and Transcriptomic Analysis of Carbapenem-Resistant Klebsiella pneumoniae Strains Identifies Genes for Antibiotic Resistance and Virulence

Contact Info

Product

Resources

About