Dataset Information

Whole-Genome k-mer Topic Modeling AssociatesBacterial Families.

ABSTRACT: Alignment-free k-mer-based algorithms in whole genome sequence comparisons remainan ongoing challenge. Here, we explore the possibility to use Topic Modeling for organismwhole-genome comparisons. We analyzed 30 complete genomes from three bacterial families bytopic modeling. For this, each genome was considered as a document and 13-mer nucleotiderepresentations as words. Latent Dirichlet allocation was used as the probabilistic modeling of thecorpus. We where able to identify the topic distribution among analyzed genomes, which is highlyconsistent with traditional hierarchical classification. It is possible that topic modeling may be appliedto establish relationships between genome's composition and biological phenomena.

SUBMITTER: Borrayo-Carbajal E

PROVIDER: S-EPMC7074292 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Whole-Genome <i>k</i>-mer Topic Modeling AssociatesBacterial Families.

Borrayo-Carbajal Ernesto E May-Canche Isaias I Paredes Omar O Morales J Alejandro JA Romo-Vázquez Rebeca R Vélez-Pérez Hugo H

Genes 20200214 2

Alignment-free k-mer-based algorithms in whole genome sequence comparisons remainan ongoing challenge. Here, we explore the possibility to use Topic Modeling for organismwhole-genome comparisons. We analyzed 30 complete genomes from three bacterial families bytopic modeling. For this, each genome was considered as a document and 13-mer nucleotiderepresentations as words. Latent Dirichlet allocation was used as the probabilistic modeling of thecorpus. We where able to identify the topic distribut ...[more]

PMID: 32075081

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Project description:Cryptococcus neoformans is the most common cause of fungal meningitis, with high mortality and morbidity. The reason for the frequent occurrence of Cryptococcus infection in the central nervous system (CNS) is poorly understood. In this study, we find that inositol plays an important role in the transversal of Cryptococcus across the blood-brain barrier (BBB) both in an in vitro human BBB model and in vivo animal models. The inositol stimulation of BBB crossing is dependent upon fungal inositol transporters. The upregulation of genes involved in the inositol catabolism pathway is evident in a microarray analysis. The expression of CPS1, a gene encoding the hyaluronic acid synthase in Cryptococcus, is also upregulated by the inositol treatment. The production of hyaluronic acid increased in cells treated with inositol, which leads to the enhanced binding ability of Cryptococcus cells to the human brain microvascular endothelial cells (HBMECs) constituting the BBB. Overall, our studies provide a mechanism for inositol-dependent Cryptococcus transversal of the BBB, supporting our hypothesis that host inositol utilization by the fungus contributes to Cryptococcus CNS infection. To understand the effect of inositol on gene expression profiles during cell development, microarray experiments were performed to monitor the genes regulated by inositol. H99 overnight culture was washed with dH2O once, and cells were inoculated on SD medium with or without inositol. Cells were collected from SD plates 24 hr post-inoculation, washed with dH2O, and total RNA was purified. Total RNAs were extracted using Trizol Reagents (Invitrogen) and purified using the Qiagen RNeasy cleanup kit (Qiagen). Cy3 and Cy5-labeled cDNA were generated by incorporating amino-allyl-dUTP during reverse transcription of 5 Âµg of total RNA as described previously and competitively hybridized to a JEC21 whole-genome array generated previously at Washington University in Saint Louis. After hybridization, arrays were scanned with a GenePix 4000B scanner (Axon Instruments, http://www.axon.com) and analyzed by using GenePix Pro version 4.0 and BRB array tools (developed by Richard Simon and Amy Peng Lam at the National Cancer Institute; http://linus.nci.nih.gov/BRB-ArrayTools.html)

Dataset Information

Whole-Genome k-mer Topic Modeling AssociatesBacterial Families.

Publications

Whole-Genome <i>k</i>-mer Topic Modeling AssociatesBacterial Families.

Similar Datasets

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