Microbial Genome Analysis and Interpretation Using Computational Approaches

A special issue of Microorganisms (ISSN 2076-2607). This special issue belongs to the section "Systems Microbiology".

Deadline for manuscript submissions: closed (30 September 2023) | Viewed by 13900

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Guest Editor
1. Department of Biological Sciences, University of North Texas, Denton, TX 76203, USA
2. BioDiscovery Institute, University of North Texas, Denton, TX 76203, USA
3. Department of Mathematics, University of North Texas, Denton, TX 76203, USA
Interests: plants bioinformatics; computational genomics, genome evolution, pathogenomics, metagenomics; gene prediction, structural variation detection, disease gene identification
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Special Issue Information

Dear Colleagues,

The focus of this special issue is on computational analysis and interpretation of microbial genomes. Deciphering information obscured within the genomes of microorganisms is critical to understanding factors underlying versatile phenotypic traits they possess. Interrogation of genomes or metagenomes also provides insights into interactions among microorganisms and between organisms and the environments they dwell in. We invite researchers across the globe to contribute to this special issue research articles or reviews pertaining to development and/or application of computational methods to unraveling microbes through (meta)genome analysis.

Dr. Rajeev K. Azad
Guest Editor

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Published Papers (8 papers)

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Research

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11 pages, 586 KiB  
Article
Mutational Dynamics Related to Antibiotic Resistance in M. tuberculosis Isolates from Serial Samples of Patients with Tuberculosis and Type 2 Diabetes Mellitus
by Gustavo A. Bermúdez-Hernández, Damián Pérez-Martínez, Maria Cristina Ortiz-León, Raquel Muñiz-Salazar, Cuauhtemoc Licona-Cassani and Roberto Zenteno-Cuevas
Microorganisms 2024, 12(2), 324; https://doi.org/10.3390/microorganisms12020324 - 3 Feb 2024
Viewed by 994
Abstract
Genetic variation in tuberculosis is influenced by the host environment, patients with comorbidity, and tuberculosis–type 2 diabetes mellitus (TB-T2DM) and implies a higher risk of treatment failure and development of drug resistance. Considering the above, this study aimed to evaluate the influence of [...] Read more.
Genetic variation in tuberculosis is influenced by the host environment, patients with comorbidity, and tuberculosis–type 2 diabetes mellitus (TB-T2DM) and implies a higher risk of treatment failure and development of drug resistance. Considering the above, this study aimed to evaluate the influence of T2DM on the dynamic of polymorphisms related to antibiotic resistance in TB. Fifty individuals with TB-T2DM and TB were initially characterized, and serial isolates of 29 of these individuals were recovered on day 0 (diagnosis), 30, and 60. Genomes were sequenced, variants related to phylogeny and drug resistance analyzed, and mutation rates calculated and compared between groups. Lineage X was predominant. At day 0 (collection), almost all isolates from the TB group were sensitive, apart from four isolates from the TB-T2DM group showing the mutation katG S315T, from which one isolate had the mutations rpoB S450L, gyrA A90G, and gyrA D94G. This pattern was observed in a second isolate at day 30. The results provide a first overview of the dynamics of mutations in resistance genes from individuals with TB-T2DM, describing an early development of resistance to isoniazid and a rapid evolution of resistance to other drugs. Although preliminary, these results help to explain the increased risk of drug resistance in individuals with TB and T2DM. Full article
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14 pages, 2869 KiB  
Article
Using Machine Learning to Predict Genes Underlying Differentiation of Multipartite and Unipartite Traits in Bacteria
by Fatemah Almalki, Janak Sunuwar and Rajeev K. Azad
Microorganisms 2023, 11(11), 2756; https://doi.org/10.3390/microorganisms11112756 - 13 Nov 2023
Viewed by 1145
Abstract
Since the discovery of the second chromosome in the Rhodobacter sphaeroides 2.4.1 by Suwanto and Kaplan in 1989 and the revelation of gene sequences, multipartite genomes have been reported in over three hundred bacterial species under nine different phyla. This phenomenon shattered the [...] Read more.
Since the discovery of the second chromosome in the Rhodobacter sphaeroides 2.4.1 by Suwanto and Kaplan in 1989 and the revelation of gene sequences, multipartite genomes have been reported in over three hundred bacterial species under nine different phyla. This phenomenon shattered the dogma of a unipartite genome (a single circular chromosome) in bacteria. Recently, Artificial Intelligence (AI), machine learning (ML), and Deep Learning (DL) have emerged as powerful tools in the investigation of big data in a plethora of disciplines to decipher complex patterns in these data, including the large-scale analysis and interpretation of genomic data. An important inquiry in bacteriology pertains to the genetic factors that underlie the structural evolution of multipartite and unipartite bacterial species. Towards this goal, here we have attempted to leverage machine learning as a means to identify the genetic factors that underlie the differentiation of, in general, bacteria with multipartite genomes and bacteria with unipartite genomes. In this study, deploying ML algorithms yielded two gene lists of interest: one that contains 46 discriminatory genes obtained following an assessment on all gene sets, and another that contains 35 discriminatory genes obtained based on an investigation of genes that are differentially present (or absent) in the genomes of the multipartite bacteria and their respective close relatives. Our study revealed a small pool of genes that discriminate bacteria with multipartite genomes and their close relatives with single-chromosome genomes. Machine learning thus aided in uncovering the genetic factors that underlie the differentiation of bacterial multipartite and unipartite traits. Full article
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13 pages, 1883 KiB  
Article
Clinical Whole-Genome Sequencing Assay for Rapid Mycobacterium tuberculosis Complex First-Line Drug Susceptibility Testing and Phylogenetic Relatedness Analysis
by Bennett Shaw, Benjamin von Bredow, Allison Tsan, Omai Garner and Shangxin Yang
Microorganisms 2023, 11(10), 2538; https://doi.org/10.3390/microorganisms11102538 - 11 Oct 2023
Cited by 2 | Viewed by 1253
Abstract
The global rise of drug resistant tuberculosis has highlighted the need for improved diagnostic technologies that provide rapid and reliable drug resistance results. Here, we develop and validate a whole genome sequencing (WGS)-based test for identification of mycobacterium tuberculosis complex (MTB) drug resistance [...] Read more.
The global rise of drug resistant tuberculosis has highlighted the need for improved diagnostic technologies that provide rapid and reliable drug resistance results. Here, we develop and validate a whole genome sequencing (WGS)-based test for identification of mycobacterium tuberculosis complex (MTB) drug resistance to rifampin, isoniazid, pyrazinamide, ethambutol, and streptomycin. Through comparative analysis of drug resistance results from WGS-based testing and phenotypic drug susceptibility testing (DST) of 38 clinical MTB isolates from patients receiving care in Los Angeles, CA, we found an overall concordance between methods of 97.4% with equivalent performance across culture media. Critically, prospective analysis of 11 isolates showed that WGS-based testing provides results an average of 36 days faster than phenotypic culture-based methods. We showcase the additional benefits of WGS data by investigating a suspected laboratory contamination event and using phylogenetic analysis to search for cryptic local transmission, finding no evidence of community spread amongst our patient population in the past six years. WGS-based testing for MTB drug resistance has the potential to greatly improve diagnosis of drug resistant MTB by accelerating turnaround time while maintaining accuracy and providing additional benefits for infection control, lab safety, and public health applications. Full article
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18 pages, 1576 KiB  
Article
Benchmarking Metagenomic Classifiers on Simulated Ancient and Modern Metagenomic Data
by Vaidehi Pusadkar and Rajeev K. Azad
Microorganisms 2023, 11(10), 2478; https://doi.org/10.3390/microorganisms11102478 - 2 Oct 2023
Viewed by 2068
Abstract
Taxonomic profiling of ancient metagenomic samples is challenging due to the accumulation of specific damage patterns on DNA over time. Although a number of methods for metagenome profiling have been developed, most of them have been assessed on modern metagenomes or simulated metagenomes [...] Read more.
Taxonomic profiling of ancient metagenomic samples is challenging due to the accumulation of specific damage patterns on DNA over time. Although a number of methods for metagenome profiling have been developed, most of them have been assessed on modern metagenomes or simulated metagenomes mimicking modern metagenomes. Further, a comparative assessment of metagenome profilers on simulated metagenomes representing a spectrum of degradation depth, from the extremity of ancient (most degraded) to current or modern (not degraded) metagenomes, has not yet been performed. To understand the strengths and weaknesses of different metagenome profilers, we performed their comprehensive evaluation on simulated metagenomes representing human dental calculus microbiome, with the level of DNA damage successively raised to mimic modern to ancient metagenomes. All classes of profilers, namely, DNA-to-DNA, DNA-to-protein, and DNA-to-marker comparison-based profilers were evaluated on metagenomes with varying levels of damage simulating deamination, fragmentation, and contamination. Our results revealed that, compared to deamination and fragmentation, human and environmental contamination of ancient DNA (with modern DNA) has the most pronounced effect on the performance of each profiler. Further, the DNA-to-DNA (e.g., Kraken2, Bracken) and DNA-to-marker (e.g., MetaPhlAn4) based profiling approaches showed complementary strengths, which can be leveraged to elevate the state-of-the-art of ancient metagenome profiling. Full article
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15 pages, 3582 KiB  
Article
Genomic Characteristics and Functional Analysis of Brucella sp. Strain WY7 Isolated from Antarctic Krill
by Zhengqi Feng, Yuanyuan Wang, Lingbo Ma, Shanzi Huang, Lumin Wang, Jianguo He and Changjun Guo
Microorganisms 2023, 11(9), 2281; https://doi.org/10.3390/microorganisms11092281 - 11 Sep 2023
Cited by 1 | Viewed by 1384
Abstract
Antarctic krill (Euphausia superba) is a key species of the Antarctic ecosystem whose unique ecological status and great development potential have attracted extensive attention. However, the genomic characteristics and potential biological functions of the symbiotic microorganisms of Antarctic krill remain unknown. [...] Read more.
Antarctic krill (Euphausia superba) is a key species of the Antarctic ecosystem whose unique ecological status and great development potential have attracted extensive attention. However, the genomic characteristics and potential biological functions of the symbiotic microorganisms of Antarctic krill remain unknown. In this study, we cultured and identified a strain of Brucella sp. WY7 from Antarctic krill using whole-genome sequencing and assembly, functional annotation, and comparative genomics analysis. First, based on 16S rDNA sequence alignment and phylogenetic tree analysis, we identified strain WY7 as Brucella. The assembled genome of strain WY7 revealed that it has two chromosomes and a plasmid, with a total genome length of 4,698,850 bp and an average G + C content of 57.18%. The DNA—DNA hybridization value and average nucleotide identity value of strain WY7 and Brucella anthropi ATCC® 49188TM, a type strain isolated from human clinical specimens, were 94.8% and 99.07%, respectively, indicating that strain WY7 is closely related to Brucella anthropi. Genomic island prediction showed that the strain has 60 genomic islands, which may produce HigB and VapC toxins. AntiSMASH analysis results showed that strain WY7 might produce many secondary metabolites, such as terpenes, siderophores and ectoine. Moreover, the genome contains genes involved in the degradation of aromatic compounds, suggesting that strain WY7 can use aromatic compounds in its metabolism. Our work will help to understand the genomic characteristics and metabolic potential of bacterial strains isolated from Antarctic krill, thereby revealing their roles in Antarctic krill and marine ecosystems. Full article
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16 pages, 3491 KiB  
Article
Yeast Deletomics to Uncover Gadolinium Toxicity Targets and Resistance Mechanisms
by Nicolas Grosjean, Marie Le Jean, Jordan Ory and Damien Blaudez
Microorganisms 2023, 11(8), 2113; https://doi.org/10.3390/microorganisms11082113 - 19 Aug 2023
Cited by 1 | Viewed by 1797
Abstract
Among the rare earth elements (REEs), a crucial group of metals for high-technologies. Gadolinium (Gd) is the only REE intentionally injected to human patients. The use of Gd-based contrasting agents for magnetic resonance imaging (MRI) is the primary route for Gd direct exposure [...] Read more.
Among the rare earth elements (REEs), a crucial group of metals for high-technologies. Gadolinium (Gd) is the only REE intentionally injected to human patients. The use of Gd-based contrasting agents for magnetic resonance imaging (MRI) is the primary route for Gd direct exposure and accumulation in humans. Consequently, aquatic environments are increasingly exposed to Gd due to its excretion through the urinary tract of patients following an MRI examination. The increasing number of reports mentioning Gd toxicity, notably originating from medical applications of Gd, necessitates an improved risk–benefit assessment of Gd utilizations. To go beyond toxicological studies, unravelling the mechanistic impact of Gd on humans and the ecosystem requires the use of genome-wide approaches. We used functional deletomics, a robust method relying on the screening of a knock-out mutant library of Saccharomyces cerevisiae exposed to toxic concentrations of Gd. The analysis of Gd-resistant and -sensitive mutants highlighted the cell wall, endosomes and the vacuolar compartment as cellular hotspots involved in the Gd response. Furthermore, we identified endocytosis and vesicular trafficking pathways (ESCRT) as well as sphingolipids homeostasis as playing pivotal roles mediating Gd toxicity. Finally, tens of yeast genes with human orthologs linked to renal dysfunction were identified as Gd-responsive. Therefore, the molecular and cellular pathways involved in Gd toxicity and detoxification uncovered in this study underline the pleotropic consequences of the increasing exposure to this strategic metal. Full article
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Review

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12 pages, 1429 KiB  
Review
Analysis of the Intestinal and Faecal Bacterial Microbiota of the Cervidae Family Using 16S Next-Generation Sequencing: A Review
by Irene Pacheco-Torres, David Hernández-Sánchez, Cristina García-De la Peña, Luis A. Tarango-Arámbula, María M. Crosby-Galván and Paulino Sánchez-Santillán
Microorganisms 2023, 11(7), 1860; https://doi.org/10.3390/microorganisms11071860 - 24 Jul 2023
Cited by 2 | Viewed by 1722
Abstract
The Cervidae family has a wide distribution due to its adaptation to numerous ecological environments, which allows it to develop a diverse microbial community in its digestive tract. Recently, research has focused on the taxonomic composition and functionality of the intestinal and faecal [...] Read more.
The Cervidae family has a wide distribution due to its adaptation to numerous ecological environments, which allows it to develop a diverse microbial community in its digestive tract. Recently, research has focused on the taxonomic composition and functionality of the intestinal and faecal microbiota of different cervid species worldwide, as well as their microbial diversity and variation under different associated factors such as age, sex, diet, distribution, and seasonal variation. In addition, there is special interest in knowing how cervids act as reservoirs of zoonotic pathogenic microorganisms, which represent a threat to public health. This review provides a synthesis of the growing field of microbiota determination in cervids worldwide, focusing on intestinal and faecal samples using 16S next-generation sequencing. It also documents factors influencing microbial diversity and composition, the microorganisms reported as pathogenic/zoonotic, and the perspectives regarding the conservation of these species. Knowing the interactions between bacteria and cervid health can drive management and conservation strategies for these species and help develop an understanding of their evolutionary history and the interaction with emerging disease-causing microorganisms. Full article
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Other

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22 pages, 1388 KiB  
Systematic Review
Genome-Wide Association Studies (GWAS) Approaches for the Detection of Genetic Variants Associated with Antibiotic Resistance: A Systematic Review
by Jeanneth Mosquera-Rendón, Claudia Ximena Moreno-Herrera, Jaime Robledo and Uriel Hurtado-Páez
Microorganisms 2023, 11(12), 2866; https://doi.org/10.3390/microorganisms11122866 - 27 Nov 2023
Cited by 2 | Viewed by 2653
Abstract
Antibiotic resistance is a significant threat to public health worldwide. Genome-wide association studies (GWAS) have emerged as a powerful tool to identify genetic variants associated with this antibiotic resistance. By analyzing large datasets of bacterial genomes, GWAS can provide valuable insights into the [...] Read more.
Antibiotic resistance is a significant threat to public health worldwide. Genome-wide association studies (GWAS) have emerged as a powerful tool to identify genetic variants associated with this antibiotic resistance. By analyzing large datasets of bacterial genomes, GWAS can provide valuable insights into the resistance mechanisms and facilitate the discovery of new drug targets. The present study aimed to undertake a systematic review of different GWAS approaches used for detecting genetic variants associated with antibiotic resistance. We comprehensively searched the PubMed and Scopus databases to identify relevant studies published from 2013 to February 2023. A total of 40 studies met our inclusion criteria. These studies explored a wide range of bacterial species, antibiotics, and study designs. Notably, most of the studies were centered around human pathogens such as Mycobacterium tuberculosis, Escherichia coli, Neisseria gonorrhoeae, and Staphylococcus aureus. The review seeks to explore the several GWAS approaches utilized to investigate the genetic mechanisms associated with antibiotic resistance. Furthermore, it examines the contributions of GWAS approaches in identifying resistance-associated genetic variants through binary and continuous phenotypes. Overall, GWAS holds great potential to enhance our understanding of bacterial resistance and improve strategies to combat infectious diseases. Full article
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