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Microorganisms
Special Issues
Bioinformatics and Omic Data Analysis in Microbial Research
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Bioinformatics and Omic Data Analysis in Microbial Research

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

Deadline for manuscript submissions: 30 September 2024 | Viewed by 3230

Special Issue Editor

Prof. Dr. Douglas D. Rhoads

E-Mail Website
Guest Editor
1. Director of Interdisciplinary Graduate Program in Cell and Molecular Biology, University of Arkansas, Fayetteville, AR 72701, USA
2. Department of Biological Sciences, University of Arkansas, Fayetteville, AR 72701, USA
Interests: genomics; molecular genetics in eukaryotes and prokaryotes; bacterial diseases affecting poultry.

Special Issue Information

Dear Colleagues,

This Special Issue explores the current applications of omics to understand the interplay/function of microbes in ecology, agriculture, disease, homeostasis, and industry. We solicit papers covering new research or reviews related to software development, pipeline development, or application of bioinformatics to address important current topics concerning microorganisms. Papers may focus on any group of microorganisms including viruses, bacteria, fungi, protists, etc., using bioinformatics to decipher biologically relevant understandings through genomics, proteomics, metabolomics, transcriptomics, or any combination. Given the important biological roles of microorganisms, the application of omics in these organisms is critical to elicit a deeper understanding. Relevant areas of interest might include speciation and species complexes, and pan genome analyses including gene transfer, gene networks, microbiomes, symbiosis and pathogenesis.

Prof. Dr. Douglas D. Rhoads
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Microorganisms is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • bioinformatics
  • microorganisms
  • genomics
  • proteomics
  • metabolomics
  • software pipelines

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (4 papers)

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Research

16 pages, 1518 KiB  
Article
Phylogenomic Analyses of Three Distinct Lineages Uniting Staphylococcus cohnii and Staphylococcus urealyticus from Diverse Hosts
by L. Caroline House, Amer Hasan, Andi Asnayanti, Adnan A. K. Alrubaye, Jeff Pummill and Douglas Rhoads
Microorganisms 2024, 12(8), 1549; https://doi.org/10.3390/microorganisms12081549 - 29 Jul 2024
Viewed by 431
Abstract
We sequenced and assembled genomes for 17 isolates of Staphylococcus cohnii isolated from osteomyelitis lesions in young broilers from two separate experiments where we induced lameness using a hybrid wire-litter flooring system. Whole genome comparisons using three different methods support a close relationship [...] Read more.
We sequenced and assembled genomes for 17 isolates of Staphylococcus cohnii isolated from osteomyelitis lesions in young broilers from two separate experiments where we induced lameness using a hybrid wire-litter flooring system. Whole genome comparisons using three different methods support a close relationship of genomes from both S. cohnii and Staphylococcus urealyticus. The data support three different lineages, which we designated as Lineage 1, Lineage 2, and Lineage 3, uniting these two species within an evolving complex. We present evidence for horizontal transfer between lineages of genomic regions from 50–440 kbp. The transfer of a 186 kbp region from Lineage 1 to Lineage 2 appears to have generated Lineage 3. Human-associated isolates appear to be limited to Lineages 2 and 3 but Lineage 2 appears to contain a higher number of human pathogenic isolates. The chicken isolates from our lameness trials included genomically diverse isolates from both Lineage 1 and 2, and isolates from both lineages were obtained from osteomyelitis lesions of individual birds. Our results expand the diversity of Staphylococci associated with osteomyelitis in poultry and suggest a high diversity in the microbiome of day-old chicks. Our data also support a reevaluation and unification of the taxonomic classifications of S. cohnii and S. urealyticus. Full article
(This article belongs to the Special Issue Bioinformatics and Omic Data Analysis in Microbial Research)
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9 pages, 836 KiB  
Communication
Isolation and Genomic Analysis of a Case of Staphylococcus argenteus ST2250 Related to Sepsis in Italy
by Giulia Gatti, Francesca Taddei, Anna Marzucco, Maria Sofia Montanari, Giorgio Dirani, Silvia Zannoli, Laura Grumiro, Martina Brandolini, Claudia Colosimo, Laura Dionisi, Ludovica Ingletto, Alessandra Mistral De Pascali, Alessandra Scagliarini, Vittorio Sambri and Monica Cricca
Microorganisms 2024, 12(7), 1485; https://doi.org/10.3390/microorganisms12071485 - 20 Jul 2024
Viewed by 567
Abstract
Staphylococcus argenteus, identified in 2006, represents a challenging case of bacterial taxonomic identification because of its high similarity to Staphylococcus aureus. In this context, neither mass spectrometry (MS) nor 16S gene analysis cannot precisely reveal the difference between the two species. [...] Read more.
Staphylococcus argenteus, identified in 2006, represents a challenging case of bacterial taxonomic identification because of its high similarity to Staphylococcus aureus. In this context, neither mass spectrometry (MS) nor 16S gene analysis cannot precisely reveal the difference between the two species. In our study, the sensitivity to antibiotics of S. argenteus isolated from blood culture was tested, and the investigation of the bacterial genome was performed by Multi-Locus Sequence Typing (MLST) and Whole-Genome Next-Generation Sequencing (WG-NGS). The pathogen was identified as ST2250 and presented perfectly matched resistance genes, namely aph(3′)-III, mgrA, and sepA, whereas the virulence gene detected was scn. Two plasmids were found: the pSAS plasmid, belonging to the family of Inc18, and plasmid pN315, belonging to the Rep3 group. The epidemiological distribution and the spread of S. argenteus infection are scarcely documented, particularly when associated with sepsis. Therefore, a correct taxonomy identification, antibiogram, and resistance gene analysis may help in acquiring knowledge about this bacterium and implement its detection and treatment. Full article
(This article belongs to the Special Issue Bioinformatics and Omic Data Analysis in Microbial Research)
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14 pages, 1945 KiB  
Article
Whole-Genome Deep Sequencing of the Healthy Adult Nasal Microbiome
by Mark Cannon, Gustavo Ferrer, Mari Tesch and Matthew Schipma
Microorganisms 2024, 12(7), 1407; https://doi.org/10.3390/microorganisms12071407 - 12 Jul 2024
Viewed by 1394
Abstract
This study aimed to determine shifts in microbial populations regarding richness and diversity from the daily use of a popular over-the-counter nasal spray. In addition, the finding of nasal commensal bacterial species that overlap with the oral microbiome may prove to be potential [...] Read more.
This study aimed to determine shifts in microbial populations regarding richness and diversity from the daily use of a popular over-the-counter nasal spray. In addition, the finding of nasal commensal bacterial species that overlap with the oral microbiome may prove to be potential probiotics for the “gateway microbiomes”. Nasal swab samples were obtained before and after using the most popular over-the-counter (OTC) nasal spray in 10 participants aged 18–48. All participants were healthy volunteers with no significant medical histories. The participants were randomly assigned a number by randomizing software and consisted of five men and five women. The sampling consisted of placing a nasal swab atraumatically into the nasal cavity. The samples were preserved and sent to Northwestern University Sequencing Center for whole-genome deep sequencing. After 21 days of OTC nasal spray use twice daily, the participants returned for further nasal microbiome sampling. The microbial analysis included all bacteria, archaea, viruses, molds, and yeasts via deep sequencing for species analysis. The Northwestern University Sequencing Center utilized artificial intelligence analysis to determine shifts in species and strains following nasal spray use that resulted in changes in diversity and richness. Full article
(This article belongs to the Special Issue Bioinformatics and Omic Data Analysis in Microbial Research)
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18 pages, 1418 KiB  
Article
Exploring Pathogen Presence Prediction in Pastured Poultry Farms through Transformer-Based Models and Attention Mechanism Explainability
by Athish Ram Das, Nisha Pillai, Bindu Nanduri, Michael J. Rothrock, Jr. and Mahalingam Ramkumar
Microorganisms 2024, 12(7), 1274; https://doi.org/10.3390/microorganisms12071274 - 23 Jun 2024
Viewed by 426
Abstract
In this study, we explore how transformer models, which are known for their attention mechanisms, can improve pathogen prediction in pastured poultry farming. By combining farm management practices with microbiome data, our model outperforms traditional prediction methods in terms of the F1 score—an [...] Read more.
In this study, we explore how transformer models, which are known for their attention mechanisms, can improve pathogen prediction in pastured poultry farming. By combining farm management practices with microbiome data, our model outperforms traditional prediction methods in terms of the F1 score—an evaluation metric for model performance—thus fulfilling an essential need in predictive microbiology. Additionally, the emphasis is on making our model’s predictions explainable. We introduce a novel approach for identifying feature importance using the model’s attention matrix and the PageRank algorithm, offering insights that enhance our comprehension of established techniques such as DeepLIFT. Our results showcase the efficacy of transformer models in pathogen prediction for food safety and mark a noteworthy contribution to the progress of explainable AI within the biomedical sciences. This study sheds light on the impact of effective farm management practices and highlights the importance of technological advancements in ensuring food safety. Full article
(This article belongs to the Special Issue Bioinformatics and Omic Data Analysis in Microbial Research)
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