Microbial Genome Analysis and Interpretation Using Computational Approaches—Second Edition

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

Deadline for manuscript submissions: 31 August 2024 | Viewed by 2039

Special Issue Editor


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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,

This Special Issue is the continuation of our previous Special Issue "Microbial Genome Analysis and Interpretation Using Computational Approaches”.

The focus of this Special Issue is on the computational analysis and interpretation of microbial genomes. Deciphering information obscured within the genomes of microorganisms is critical to understanding factors underlying the 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. For this Special Issue, we invite researchers across the globe to contribute research articles or reviews pertaining to the development and/or application of computational methods to unraveling microbes through (meta)genome analysis.

Dr. Rajeev K. Azad
Guest Editor

Manuscript Submission Information

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Keywords

  • microbial genome
  • whole-genome sequencing
  • bioinformatics

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Published Papers (3 papers)

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Research

16 pages, 5541 KiB  
Article
Deciphering Microbial Shifts in the Gut and Lung Microbiomes of COVID-19 Patients
by Vaidehi Pusadkar, Anirudh Mazumder, Abhijay Azad, Deepti Patil and Rajeev K. Azad
Microorganisms 2024, 12(6), 1058; https://doi.org/10.3390/microorganisms12061058 - 24 May 2024
Viewed by 484
Abstract
COVID-19, caused by SARS-CoV-2, results in respiratory and cardiopulmonary infections. There is an urgent need to understand not just the pathogenic mechanisms of this disease but also its impact on the physiology of different organs and microbiomes. Multiple studies have reported the effects [...] Read more.
COVID-19, caused by SARS-CoV-2, results in respiratory and cardiopulmonary infections. There is an urgent need to understand not just the pathogenic mechanisms of this disease but also its impact on the physiology of different organs and microbiomes. Multiple studies have reported the effects of COVID-19 on the gastrointestinal microbiota, such as promoting dysbiosis (imbalances in the microbiome) following the disease’s progression. Deconstructing the dynamic changes in microbiome composition that are specifically correlated with COVID-19 patients remains a challenge. Motivated by this problem, we implemented a biomarker discovery pipeline to identify candidate microbes specific to COVID-19. This involved a meta-analysis of large-scale COVID-19 metagenomic data to decipher the impact of COVID-19 on the human gut and respiratory microbiomes. Metagenomic studies of the gut and respiratory microbiomes of COVID-19 patients and of microbiomes from other respiratory diseases with symptoms similar to or overlapping with COVID-19 revealed 1169 and 131 differentially abundant microbes in the human gut and respiratory microbiomes, respectively, that uniquely associate with COVID-19. Furthermore, by utilizing machine learning models (LASSO and XGBoost), we demonstrated the power of microbial features in separating COVID-19 samples from metagenomic samples representing other respiratory diseases and controls (healthy individuals), achieving an overall accuracy of over 80%. Overall, our study provides insights into the microbiome shifts occurring in COVID-19 patients, shining a new light on the compositional changes. Full article
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14 pages, 1224 KiB  
Article
In-Host Flat-like Quasispecies: Characterization Methods and Clinical Implications
by Josep Gregori, Sergi Colomer-Castell, Marta Ibañez-Lligoña, Damir Garcia-Cehic, Carolina Campos, Maria Buti, Mar Riveiro-Barciela, Cristina Andrés, Maria Piñana, Alejandra González-Sánchez, Francisco Rodriguez-Frias, Maria Francesca Cortese, David Tabernero, Ariadna Rando-Segura, Tomás Pumarola, Juan Ignacio Esteban, Andrés Antón and Josep Quer
Microorganisms 2024, 12(5), 1011; https://doi.org/10.3390/microorganisms12051011 - 17 May 2024
Cited by 1 | Viewed by 692
Abstract
The repeated failure to treat patients chronically infected with hepatitis E (HEV) and C (HCV) viruses, despite the absence of resistance-associated substitutions (RAS), particularly in response to prolonged treatments with the mutagenic agents of HEV, suggests that quasispecies structure may play a crucial [...] Read more.
The repeated failure to treat patients chronically infected with hepatitis E (HEV) and C (HCV) viruses, despite the absence of resistance-associated substitutions (RAS), particularly in response to prolonged treatments with the mutagenic agents of HEV, suggests that quasispecies structure may play a crucial role beyond single point mutations. Quasispecies structured in a flat-like manner (referred to as flat-like) are considered to possess high average fitness, occupy a significant fraction of the functional genetic space of the virus, and exhibit a high capacity to evade specific or mutagenic treatments. In this paper, we studied HEV and HCV samples using high-depth next-generation sequencing (NGS), with indices scoring the different properties describing flat-like quasispecies. The significance of these indices was demonstrated by comparing the values obtained from these samples with those from acute infections caused by respiratory viruses (betacoronaviruses, enterovirus, respiratory syncytial viruses, and metapneumovirus). Our results revealed that flat-like quasispecies in HEV and HCV chronic infections without RAS are characterized by numerous low-frequency haplotypes with no dominant one. Surprisingly, these low-frequency haplotypes (at the nucleotide level) exhibited a high level of synonymity, resulting in much lower diversity at the phenotypic level. Currently, clinical approaches for managing flat-like quasispecies are lacking. Here, we propose methods to identifying flat-like quasispecies, which represents an essential initial step towards exploring alternative treatment protocols for viruses resistant to conventional therapies. Full article
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19 pages, 13091 KiB  
Article
Comparative Genomics Unveils Functional Diversity, Pangenome Openness, and Underlying Biological Drivers among Bacillus subtilis Group
by Taiquan Wang, Yiling Shi, Mengzhuo Zheng and Jinshui Zheng
Microorganisms 2024, 12(5), 986; https://doi.org/10.3390/microorganisms12050986 - 14 May 2024
Viewed by 646
Abstract
The Bacillus subtilis group (Bs group), with Bacillus subtilis as its core species, holds significant research and economic value in various fields, including science, industrial production, food, and pharmaceuticals. However, most studies have been confined to comparative genomics analyses and exploration within individual [...] Read more.
The Bacillus subtilis group (Bs group), with Bacillus subtilis as its core species, holds significant research and economic value in various fields, including science, industrial production, food, and pharmaceuticals. However, most studies have been confined to comparative genomics analyses and exploration within individual genomes at the level of species, with few conducted within groups across different species. This study focused on Bacillus subtilis, the model of Gram-positive bacteria, and 14 other species with significant research value, employing comparative pangenomics as well as population enrichment analysis to ascertain the functional enrichment and diversity. Through the quantification of pangenome openness, this work revealed the underlying biological drivers and significant correlation between pangenome openness and various factors, including the distribution of toxin–antitoxin- and integrase-related genes, as well as the number of endonucleases, recombinases, repair system-related genes, prophages, integrases, and transfer mobile elements. Furthermore, the functional enrichment results indicated the potential for secondary metabolite, probiotic, and antibiotic exploration in Bacillus licheniformis, Bacillus paralicheniformis, and Bacillus spizizenii, respectively. In general, this work systematically exposed the quantification of pangenome openness, biological drivers, the pivotal role of genomic instability factors, and mobile elements, providing targeted exploration guidance for the Bs group. Full article
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