Microbial genotype–phenotype mapping by class association rule mining

Tamura, Makio; D’haeseleer, Patrik

doi:10.1093/bioinformatics/btn210

Cited by 33 publications

(40 citation statements)

References 30 publications

(40 reference statements)

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“…In functional annotation, we often differentiate between two subtypes of homologs, orthologs and paralogs [e.g., 26]. According to the standard model of genome evolution, paralogs—pairs of genes diverged through a duplication event—could obtain a new function [e.g., 27].…”

Section: Discussionmentioning

confidence: 99%

Phyletic Profiling with Cliques of Orthologs Is Enhanced by Signatures of Paralogy Relationships

et al. 2013

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New microbial genomes are sequenced at a high pace, allowing insight into the genetics of not only cultured microbes, but a wide range of metagenomic collections such as the human microbiome. To understand the deluge of genomic data we face, computational approaches for gene functional annotation are invaluable. We introduce a novel model for computational annotation that refines two established concepts: annotation based on homology and annotation based on phyletic profiling. The phyletic profiling-based model that includes both inferred orthologs and paralogs—homologs separated by a speciation and a duplication event, respectively—provides more annotations at the same average Precision than the model that includes only inferred orthologs. For experimental validation, we selected 38 poorly annotated Escherichia coli genes for which the model assigned one of three GO terms with high confidence: involvement in DNA repair, protein translation, or cell wall synthesis. Results of antibiotic stress survival assays on E. coli knockout mutants showed high agreement with our model's estimates of accuracy: out of 38 predictions obtained at the reported Precision of 60%, we confirmed 25 predictions, indicating that our confidence estimates can be used to make informed decisions on experimental validation. Our work will contribute to making experimental validation of computational predictions more approachable, both in cost and time. Our predictions for 998 prokaryotic genomes include ∼400000 specific annotations with the estimated Precision of 90%, ∼19000 of which are highly specific—e.g. “penicillin binding,” “tRNA aminoacylation for protein translation,” or “pathogenesis”—and are freely available at http://gorbi.irb.hr/.

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Section: Discussionmentioning

confidence: 99%

Phyletic Profiling with Cliques of Orthologs Is Enhanced by Signatures of Paralogy Relationships

et al. 2013

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“…Although association rule mining is most often used in marketing analyses, such as "market basket" analysis [67,68], this technique has been successfully applied to several biological problems (e.g., [69-71]), including discovery of highly conserved CTL epitopes [44]. …”

Section: Methodsmentioning

confidence: 99%

Frequent associations between CTL and T-Helper epitopes in HIV-1 genomes and implications for multi-epitope vaccine designs

Paul

Piontkivska

2010

BMC Microbiology

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BackgroundEpitope vaccines have been suggested as a strategy to counteract viral escape and development of drug resistance. Multiple studies have shown that Cytotoxic T-Lymphocyte (CTL) and T-Helper (Th) epitopes can generate strong immune responses in Human Immunodeficiency Virus (HIV-1). However, not much is known about the relationship among different types of HIV epitopes, particularly those epitopes that can be considered potential candidates for inclusion in the multi-epitope vaccines.ResultsIn this study we used association rule mining to examine relationship between different types of epitopes (CTL, Th and antibody epitopes) from nine protein-coding HIV-1 genes to identify strong associations as potent multi-epitope vaccine candidates. Our results revealed 137 association rules that were consistently present in the majority of reference and non-reference HIV-1 genomes and included epitopes of two different types (CTL and Th) from three different genes (Gag, Pol and Nef). These rules involved 14 non-overlapping epitope regions that frequently co-occurred despite high mutation and recombination rates, including in genomes of circulating recombinant forms. These epitope regions were also highly conserved at both the amino acid and nucleotide levels indicating strong purifying selection driven by functional and/or structural constraints and hence, the diminished likelihood of successful escape mutations.ConclusionsOur results provide a comprehensive systematic survey of CTL, Th and Ab epitopes that are both highly conserved and co-occur together among all subtypes of HIV-1, including circulating recombinant forms. Several co-occurring epitope combinations were identified as potent candidates for inclusion in multi-epitope vaccines, including epitopes that are immuno-responsive to different arms of the host immune machinery and can enable stronger and more efficient immune responses, similar to responses achieved with adjuvant therapies. Signature of strong purifying selection acting at the nucleotide level of the associated epitopes indicates that these regions are functionally critical, although the exact reasons behind such sequence conservation remain to be elucidated.

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“…Indeed, AD is no longer seen as a disease of single discrete lesions, but as a perturbation of altered cortical networks by pathological processes in interlinked pathways. Hence, the application of systems biology methods to the discovery and characterization of novel biomarkers [8][9][10][11][12][13][14][15][16][17][18][19][20] has taken on greater promise and urgency.…”

Section: Introductionmentioning

confidence: 99%

Characterizing Gene and Protein Crosstalks in Subjects at Risk of Developing Alzheimer’s Disease: A New Computational Approach

et al. 2017

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Alzheimer's disease (AD) is a major public health threat; however, despite decades of research, the disease mechanisms are not completely understood, and there is a significant dearth of predictive biomarkers. The availability of systems biology approaches has opened new avenues for understanding disease mechanisms at a pathway level. However, to the best of our knowledge, no prior study has characterized the nature of pathway crosstalks in AD, or examined their utility as biomarkers for diagnosis or prognosis. In this paper, we build the first computational crosstalk model of AD incorporating genetics, antecedent knowledge, and biomarkers from a national study to create a generic pathway crosstalk reference map and to characterize the nature of genetic and protein pathway crosstalks in mild cognitive impairment (MCI) subjects. We perform initial studies of the utility of incorporating these crosstalks as biomarkers for assessing the risk of MCI progression to AD dementia. Our analysis identified Single Nucleotide Polymorphism-enriched pathways representing six of the seven Kyoto Encyclopedia of Genes and Genomes pathway categories. Integrating pathway crosstalks as a predictor improved the accuracy by 11.7% compared to standard clinical parameters and apolipoprotein E ε4 status alone. Our findings highlight the importance of moving beyond discrete biomarkers to studying interactions among complex biological pathways.

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Microbial genotype–phenotype mapping by class association rule mining

Cited by 33 publications

References 30 publications

Phyletic Profiling with Cliques of Orthologs Is Enhanced by Signatures of Paralogy Relationships

Phyletic Profiling with Cliques of Orthologs Is Enhanced by Signatures of Paralogy Relationships

Frequent associations between CTL and T-Helper epitopes in HIV-1 genomes and implications for multi-epitope vaccine designs

Characterizing Gene and Protein Crosstalks in Subjects at Risk of Developing Alzheimer’s Disease: A New Computational Approach

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