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Omics and Bioinformatics
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Omics and Bioinformatics

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Bioinformatics".

Deadline for manuscript submissions: closed (25 October 2023) | Viewed by 11293

Special Issue Editors

Dr. Bijay Kumar Behera

E-Mail Website
Guest Editor
College of Fisheries, Rani Lakshmi Bai Central Agricultural University, Gwalior Road, Near Pahuj Dam, Jhansi 284003, Uttar Pradesh, India
Interests: metagenomics; bacteriophage; microbial diversity; probiotics and metatranscriptomics
Dr. Ajaya Kumar Rout

E-Mail Website
Guest Editor
Department of Biosciences & Biotechnology, Fakir Mohan University, Vyasa Vihar, Nuapadhi, Balasore, Odisha 756089, India
Interests: metagenomics; microbial diversity; genomics; metatranscriptomics and antibiotics resistance genes

Special Issue Information

Dear Colleagues,

Omics is a rapidly developing field, with new possibilities for investigating genomes, proteomes, and microbiomes for ecological, phylogenetic, clinical, and biotechnological purposes. Despite massive sequencing and sampling activities by the research community, we are still a long way from fully characterizing many genes. Bioinformatic tools should be continually improved, and new methods must be developed to increase data resolution due to the enormous amount of data being collected. The purpose of this Special Issue is to focus on the use of NGS-based sequence analysis techniques such as genomics, metagenomics, proteomics, metatranscriptomics and transcriptomics in the study of microbial diversity and function in the environment, clinical, and other allied sciences. It encourages cutting-edge and state-of-the-art publications that will provide readers with current knowledge of recent and upcoming research in the discipline.

Dr. Bijay Kumar Behera
Dr. Ajaya Kumar Rout
Guest Editors

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. Genes 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 2600 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

  • metagenomics and metatranscriptomics
  • functional genomics and transcriptomics
  • microbial ecosystems
  • antibiotics resistance genes
  • probiotics and bacteriophage
  • clinical microbiology
  • bioremediation
  • environmental microbiology
  • geo microbiology

Published Papers (5 papers)

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Research

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23 pages, 3188 KiB  
Article
Predictive Role of Cluster Bean (Cyamopsis tetragonoloba) Derived miRNAs in Human and Cattle Health
by Sarika Sahu, Atmakuri Ramakrishna Rao, Tanmaya Kumar Sahu, Jaya Pandey, Shivangi Varshney, Archna Kumar and Kishor Gaikwad
Genes 2024, 15(4), 448; https://doi.org/10.3390/genes15040448 - 1 Apr 2024
Viewed by 894
Abstract
MicroRNAs (miRNAs) are small non-coding conserved molecules with lengths varying between 18-25nt. Plants miRNAs are very stable, and probably they might have been transferred across kingdoms via food intake. Such miRNAs are also called exogenous miRNAs, which regulate the gene expression in host [...] Read more.
MicroRNAs (miRNAs) are small non-coding conserved molecules with lengths varying between 18-25nt. Plants miRNAs are very stable, and probably they might have been transferred across kingdoms via food intake. Such miRNAs are also called exogenous miRNAs, which regulate the gene expression in host organisms. The miRNAs present in the cluster bean, a drought tolerant legume crop having high commercial value, might have also played a regulatory role for the genes involved in nutrients synthesis or disease pathways in animals including humans due to dietary intake of plant parts of cluster beans. However, the predictive role of miRNAs of cluster beans for gene–disease association across kingdoms such as cattle and humans are not yet fully explored. Thus, the aim of the present study is to (i) find out the cluster bean miRNAs (cb-miRs) functionally similar to miRNAs of cattle and humans and predict their target genes’ involvement in the occurrence of complex diseases, and (ii) identify the role of cb-miRs that are functionally non-similar to the miRNAs of cattle and humans and predict their targeted genes’ association with complex diseases in host systems. Here, we predicted a total of 33 and 15 functionally similar cb-miRs (fs-cb-miRs) to human and cattle miRNAs, respectively. Further, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed the participation of targeted genes of fs-cb-miRs in 24 and 12 different pathways in humans and cattle, respectively. Few targeted genes in humans like LCP2, GABRA6, and MYH14 were predicted to be associated with disease pathways of Yesinia infection (hsa05135), neuroactive ligand-receptor interaction (hsa04080), and pathogenic Escherichia coli infection (hsa05130), respectively. However, targeted genes of fs-cb-miRs in humans like KLHL20, TNS1, and PAPD4 are associated with Alzheimer’s, malignant tumor of the breast, and hepatitis C virus infection disease, respectively. Similarly, in cattle, targeted genes like ATG2B and DHRS11 of fs-cb-miRs participate in the pathways of Huntington disease and steroid biosynthesis, respectively. Additionally, the targeted genes like SURF4 and EDME2 of fs-cb-miRs are associated with mastitis and bovine osteoporosis, respectively. We also found a few cb-miRs that do not have functional similarity with human and cattle miRNAs but are found to target the genes in the host organisms and as well being associated with human and cattle diseases. Interestingly, a few genes such as NRM, PTPRE and SUZ12 were observed to be associated with Rheumatoid Arthritis, Asthma and Endometrial Stromal Sarcoma diseases, respectively, in humans and genes like SCNN1B associated with renal disease in cattle. Full article
(This article belongs to the Special Issue Omics and Bioinformatics)
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16 pages, 2412 KiB  
Article
Sequencing and Characterization of M. morganii Strain UM869: A Comprehensive Comparative Genomic Analysis of Virulence, Antibiotic Resistance, and Functional Pathways
by Dibyajyoti Uttameswar Behera, Sangita Dixit, Mahendra Gaur, Rukmini Mishra, Rajesh Kumar Sahoo, Maheswata Sahoo, Bijay Kumar Behera, Bharat Bhusan Subudhi, Sutar Suhas Bharat and Enketeswara Subudhi
Genes 2023, 14(6), 1279; https://doi.org/10.3390/genes14061279 - 16 Jun 2023
Cited by 1 | Viewed by 1961
Abstract
Morganella morganii is a Gram-negative opportunistic Enterobacteriaceae pathogen inherently resistant to colistin. This species causes various clinical and community-acquired infections. This study investigated the virulence factors, resistance mechanisms, functional pathways, and comparative genomic analysis of M. morganii strain UM869 with 79 publicly available [...] Read more.
Morganella morganii is a Gram-negative opportunistic Enterobacteriaceae pathogen inherently resistant to colistin. This species causes various clinical and community-acquired infections. This study investigated the virulence factors, resistance mechanisms, functional pathways, and comparative genomic analysis of M. morganii strain UM869 with 79 publicly available genomes. The multidrug resistance strain UM869 harbored 65 genes associated with 30 virulence factors, including efflux pump, hemolysin, urease, adherence, toxin, and endotoxin. Additionally, this strain contained 11 genes related to target alteration, antibiotic inactivation, and efflux resistance mechanisms. Further, the comparative genomic study revealed a high genetic relatedness (98.37%) among the genomes, possibly due to the dissemination of genes between adjoining countries. The core proteome of 79 genomes contains the 2692 core, including 2447 single-copy orthologues. Among them, six were associated with resistance to major antibiotic classes manifested through antibiotic target alteration (PBP3, gyrB) and antibiotic efflux (kpnH, rsmA, qacG; rsmA; CRP). Similarly, 47 core orthologues were annotated to 27 virulence factors. Moreover, mostly core orthologues were mapped to transporters (n = 576), two-component systems (n = 148), transcription factors (n = 117), ribosomes (n = 114), and quorum sensing (n = 77). The presence of diversity in serotypes (type 2, 3, 6, 8, and 11) and variation in gene content adds to the pathogenicity, making them more difficult to treat. This study highlights the genetic similarity among the genomes of M. morganii and their restricted emergence, mostly in Asian countries, in addition to their growing pathogenicity and resistance. However, steps must be taken to undertake large-scale molecular surveillance and to direct suitable therapeutic interventions. Full article
(This article belongs to the Special Issue Omics and Bioinformatics)
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20 pages, 33493 KiB  
Article
Unravelling the Evolutionary Dynamics of High-Risk Klebsiella pneumoniae ST147 Clones: Insights from Comparative Pangenome Analysis
by Suchanda Dey, Mahendra Gaur, Ellen M. E. Sykes, Monica Prusty, Selvakumar Elangovan, Sangita Dixit, Sanghamitra Pati, Ayush Kumar and Enketeswara Subudhi
Genes 2023, 14(5), 1037; https://doi.org/10.3390/genes14051037 - 2 May 2023
Cited by 2 | Viewed by 2628
Abstract
Background: The high prevalence and rapid emergence of antibiotic resistance in high-risk Klebsiella pneumoniae (KP) ST147 clones is a global health concern and warrants molecular surveillance. Methods: A pangenome analysis was performed using publicly available ST147 complete genomes. The characteristics and evolutionary relationships [...] Read more.
Background: The high prevalence and rapid emergence of antibiotic resistance in high-risk Klebsiella pneumoniae (KP) ST147 clones is a global health concern and warrants molecular surveillance. Methods: A pangenome analysis was performed using publicly available ST147 complete genomes. The characteristics and evolutionary relationships among ST147 members were investigated through a Bayesian phylogenetic analysis. Results: The large number of accessory genes in the pangenome indicates genome plasticity and openness. Seventy-two antibiotic resistance genes were found to be linked with antibiotic inactivation, efflux, and target alteration. The exclusive detection of the blaOXA-232 gene within the ColKp3 plasmid of KP_SDL79 suggests its acquisition through horizontal gene transfer. The association of seventy-six virulence genes with the acrAB efflux pump, T6SS system and type I secretion system describes its pathogenicity. The presence of Tn6170, a putative Tn7-like transposon in KP_SDL79 with an insertion at the flanking region of the tnsB gene, establishes its transmission ability. The Bayesian phylogenetic analysis estimates ST147’s initial divergence in 1951 and the most recent common ancestor for the entire KP population in 1621. Conclusions: Present study highlights the genetic diversity and evolutionary dynamics of high-risk clones of K. pneumoniae. Further inter-clonal diversity studies will help us understand its outbreak more precisely and pave the way for therapeutic interventions. Full article
(This article belongs to the Special Issue Omics and Bioinformatics)
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23 pages, 3887 KiB  
Article
CNN_FunBar: Advanced Learning Technique for Fungi ITS Region Classification
by Ritwika Das, Anil Rai and Dwijesh Chandra Mishra
Genes 2023, 14(3), 634; https://doi.org/10.3390/genes14030634 - 3 Mar 2023
Cited by 2 | Viewed by 2942
Abstract
Fungal species identification from metagenomic data is a highly challenging task. Internal Transcribed Spacer (ITS) region is a potential DNA marker for fungi taxonomy prediction. Computational approaches, especially deep learning algorithms, are highly efficient for better pattern recognition and classification of large datasets [...] Read more.
Fungal species identification from metagenomic data is a highly challenging task. Internal Transcribed Spacer (ITS) region is a potential DNA marker for fungi taxonomy prediction. Computational approaches, especially deep learning algorithms, are highly efficient for better pattern recognition and classification of large datasets compared to in silico techniques such as BLAST and machine learning methods. Here in this study, we present CNN_FunBar, a convolutional neural network-based approach for the classification of fungi ITS sequences from UNITE+INSDC reference datasets. Effects of convolution kernel size, filter numbers, k-mer size, degree of diversity and category-wise frequency of ITS sequences on classification performances of CNN models have been assessed at all taxonomic levels (species, genus, family, order, class and phylum). It is observed that CNN models can produce >93% average accuracy for classifying ITS sequences from balanced datasets with 500 sequences per category and 6-mer frequency features at all levels. The comparative study has revealed that CNN_FunBar can outperform machine learning-based algorithms (SVM, KNN, Naïve-Bayes and Random Forest) as well as existing fungal taxonomy prediction software (funbarRF, Mothur, RDP Classifier and SINTAX). The present study will be helpful for fungal taxonomy classification using large metagenomic datasets. Full article
(This article belongs to the Special Issue Omics and Bioinformatics)
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12 pages, 1587 KiB  
Brief Report
Comprehensive Evaluation of Genome Gap-Filling Tools Utilizing Long Reads
by Xianjia Zhao, Fang Liu and Weihua Pan
Genes 2024, 15(1), 127; https://doi.org/10.3390/genes15010127 - 20 Jan 2024
Viewed by 1060
Abstract
The availability of the complete genome of an organism plays a crucial role in the comprehensive analysis of the entire biological entity. Despite the rapid advancements in sequencing technologies, the inherent complexities of genomes inevitably lead to gaps during genome assembly. To obviate [...] Read more.
The availability of the complete genome of an organism plays a crucial role in the comprehensive analysis of the entire biological entity. Despite the rapid advancements in sequencing technologies, the inherent complexities of genomes inevitably lead to gaps during genome assembly. To obviate this, numerous genome gap-filling tools utilizing long reads have emerged. However, a comprehensive evaluation of these tools is currently lacking. In this study, we evaluated seven software under various ploidy levels and different data generation methods, and assessing them using QUAST and two additional criteria such as accuracy and completeness. Our findings revealed that the performance of the different tools varied across diverse ploidy levels. Based on accuracy and completeness, FGAP emerged as the top-performing tool, excelling in both haploid and tetraploid scenarios. This evaluation of commonly used genome gap-filling tools aims to provide users with valuable insights for tool selection, assisting them in choosing the most suitable genome gap-filling tool for their specific needs. Full article
(This article belongs to the Special Issue Omics and Bioinformatics)
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