The Gene Ontology project

Harris, Midori A.; Lomax, Jane; Ireland, Amelia; Clark, Jennifer I.

doi:10.1002/047001153x.g408202

Cited by 36 publications

(31 citation statements)

References 20 publications

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“…GeneMarks (version 4.17) [16] was used to predict protein-coding genes. The Kyoto Encyclopedia of Genes and Genomes (KEGG), Clusters of Orthologous Groups (COG), NCBI-NR and Gene Ontology (GO) databases were used to annotate the function of predicted genes [17][18][19]. Virulent genes were reliably identified by BLAST in the Virulence Factors Database (http://www.mgc.ac.cn/VFs/) with identity > 80% and E-value < 10e-50, and antibiotic-resistant genes were identified using RGI from the Comprehensive Antibiotic Resistance Database (https://card.mcmaster.ca/) with "perfect and strict hits" and "identity > 90%" [20,21].…”

Section: Genome Annotationmentioning

confidence: 99%

“…Functions of the differentially expressed genes between AF18 and AF18-NC were annotated with GO database [17], and the probability of enrichment for each cluster was calculated by using the weight algorithm and Fisher's exact test implemented in topGO package [34]. Clusters with a corrected p value < 0.05 were regarded as significantly enriched.…”

Section: Functions Of Differentially Expressed Genesmentioning

confidence: 99%

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Genomic Characterization of an Emerging Enterobacteriaceae Species: the First Case of Co-infection With a Typical Pathogen in a Human Patient

Zhang

Shi

et al. 2020

Preprint

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Background: Opportunistic pathogens are important for clinical practice as they often cause antibiotic-resistant infections. However, little is documented for many emerging opportunistic pathogens and their biological characteristics. Here, we isolated a strain of extended-spectrum β-lactamase-producing Enterobacteriaceae from a patient with a biliary tract infection. We explored the biological and genomic characteristics of this strain to provide new evidence and detailed information for opportunistic pathogens about the co-infection they may cause.Results: The isolate grew very slowly but conferred strong protection for the co-infected cephalosporin-sensitive Klebsiella pneumoniae. As the initial laboratory testing failed to identify the taxonomy of the strain, great perplexity was caused in the etiological diagnosis and anti-infection treatment for the patient. Rigorous sequencing efforts achieved the complete genome sequence of the isolate which we designated as AF18. AF18 is phylogenetically close to a few strains isolated from soil, clinical sewage, and patients, forming a novel species together, while the taxonomic nomenclature of which is still under discussion. And this is the first report of human infection of this novel species. Like its relatives, AF18 harbors many genes related to cell mobility, various genes adaptive to both the natural environment and animal host, over 30 mobile genetic elements, and a plasmid bearing blaCTX-M-3 gene, indicating its ability to disseminate antimicrobial-resistant genes from the natural environment to patients. Transcriptome sequencing identified two sRNAs that critically regulate the growth rate of AF18, which could serve as targets for novel antimicrobial strategies. Conclusions: Our findings imply that AF18 and its species are not only infection-relevant but also potential disseminators of antibiotic resistance genes, which highlights the need for continuous monitoring for this novel species and efforts to develop treatment strategies.

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Section: Genome Annotationmentioning

confidence: 99%

Section: Functions Of Differentially Expressed Genesmentioning

confidence: 99%

Genomic Characterization of an Emerging Enterobacteriaceae Species: the First Case of Co-infection With a Typical Pathogen in a Human Patient

Zhang

Shi

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…GeneMarks (version 4.17) [35] was used to predict protein-coding genes. The Kyoto Encyclopedia of Genes and Genomes (KEGG), Clusters of Orthologous Groups (COG), NCBI-NR and Gene Ontology (GO) databases were used to annotate the function of predicted genes [36][37][38]. Virulent genes were reliably identified by BLAST in the Virulence Factors Database (http://www.mgc.ac.cn/VFs/) with identity > 80% and E-value < 10e-50, and antibiotic-resistant genes were identified using RGI from the Comprehensive Antibiotic Resistance Database (https://card.mcmaster.ca/) with "perfect and strict hits" and "identity > 90%" [39,40].…”

Section: Genome Annotationmentioning

confidence: 99%

Genomic Characterization of an Emerging Enterobacteriaceae Species: the First Case of Co-infection With a Typical Pathogen in a Human Patient

Zhang

Shi

et al. 2020

Preprint

View full text Add to dashboard Cite

Background Opportunistic pathogens are important for clinical practice as they often cause antibiotic-resistant infections. However, little is documented for many emerging opportunistic pathogens and their biological characteristics. Here, we isolated a novel species strain of extended-spectrum β-lactamase-producing Enterobacteriaceae from a patient of with a biliary tract infection. We explored the biological and genomic characteristics of this strain to provide new evidence and detailed information for opportunistic pathogens about the co-infection they may cause. Results The isolate grows grew very slowly but confers conferred strong protection for the co-infected cephalosporin-sensitive Klebsiella pneumonia pneumoniae . As the initial laboratory testing failed to identify the taxonomy of the strain, great perplexity was caused in the etiological diagnosis , and anti-infection treatment for the patient. Rigorous sequencing efforts achieved the complete genome sequence of the isolate which we designated as AF18. AF18 is phylogenetically close to a few strains respectively isolated from soil, clinical sewage, and patients, forming a novel species together, while the taxonomic nomenclature of which is still under discussion. And this is the first report of human infection of this novel species. Like As its relatives, AF18 harbors many genes related to cell mobility, various genes adaptive to both the natural wild environment and animal host, tens of over 30 mobile genetic mobile elements, and a plasmid bearing bla CTX-M-3 gene, indicating its ability to disseminate antimicrobial - resistant genes from the natural environment to patients. Transcriptome sequencing identified two sRNAs that critically regulate the growth rate of AF18 , which could serve as targets for novel antimicrobial strategies. Conclusions Our findings imply that AF18 and its species are not only infection-relevant but also potential disseminators of antibiotic resistance genes i n transferring antibiotic determinants , which highlights the need for continuous monitoring for this novel species and efforts to develop controlling treatment strategies.

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“…The most widely used ontologies include Gene Ontology (GO) [1], Enzyme Commission (E.C.) [2] and MIPS Functional Catalogue (FunCat) [3].…”

Section: Introductionmentioning

confidence: 99%

Gene Ontology-Based Protein Function Prediction by Using Sequence Composition Information

Dong

Zhou²,

Deng³

et al. 2010

PPL

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The prediction of protein function is a difficult and important problem in computational biology. In this study, an efficient method is presented to predict protein function with sequence composition information. Four kinds of basic building blocks of protein sequences are investigated, including N-grams, binary profiles, PFAM domains and InterPro domains. The protein sequences are mapped into high-dimensional vectors by using the occurrence frequencies of each kind of building blocks. The resulting vectors are then taken as input to support vector machine to predict their function based on gene ontology. Experiments are conducted over the subset of GOA database. The experimental results show that the protein function can be predicted from primary sequence information. The method based on InterPro domains outperforms the other building blocks, and gets an overall accuracy of 0.87 and ROC score is 0.93. We also demonstrate that the use of feature extraction algorithms such as latent semantic analysis and nonnegative matrix factorization, can efficiently remove noise and improve the prediction efficiency without significantly degrading the performance. The results obtained here are helpful for the prediction of protein function by using only sequence information.

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The Gene Ontology project

Cited by 36 publications

References 20 publications

Genomic Characterization of an Emerging Enterobacteriaceae Species: the First Case of Co-infection With a Typical Pathogen in a Human Patient

Genomic Characterization of an Emerging Enterobacteriaceae Species: the First Case of Co-infection With a Typical Pathogen in a Human Patient

Genomic Characterization of an Emerging Enterobacteriaceae Species: the First Case of Co-infection With a Typical Pathogen in a Human Patient

Gene Ontology-Based Protein Function Prediction by Using Sequence Composition Information

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