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Basharat Z, Sattar S, Bahauddin AA, Al Mouslem AK, Alotaibi G. Screening Marine Microbial Metabolites as Promising Inhibitors of Borrelia garinii: A Structural Docking Approach towards Developing Novel Lyme Disease Treatment. BIOMED RESEARCH INTERNATIONAL 2024; 2024:9997082. [PMID: 38456098 PMCID: PMC10919988 DOI: 10.1155/2024/9997082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/23/2023] [Revised: 01/26/2024] [Accepted: 02/13/2024] [Indexed: 03/09/2024]
Abstract
Lyme disease caused by the Borrelia species is a growing health concern in many parts of the world. Current treatments for the disease may have side effects, and there is also a need for new therapies that can selectively target the bacteria. Pathogens responsible for Lyme disease include B. burgdorferi, B. afzelii, and B. garinii. In this study, we employed structural docking-based screening to identify potential lead-like inhibitors against the bacterium. We first identified the core essential genome fraction of the bacterium, using 37 strains. Later, we screened a library of lead-like marine microbial metabolites (n = 4730) against the arginine deiminase (ADI) protein of Borrelia garinii. This protein plays a crucial role in the survival of the bacteria, and inhibiting it can kill the bacterium. The prioritized lead compounds demonstrating favorable binding energies and interactions with the active site of ADI were then evaluated for their drug-like and pharmacokinetic parameters to assess their suitability for development as drugs. Results from molecular dynamics simulation (100 ns) and other scoring parameters suggest that the compound CMNPD18759 (common name: aureobasidin; IUPAC name: 2-[(4R,6R)-4,6-dihydroxydecanoyl]oxypropan-2-yl (3S,5R)-3,5-dihydroxydecanoate) holds promise as a potential drug candidate for the treatment of Lyme disease, caused by B. garinii. However, further experimental studies are needed to validate the efficacy and safety of this compound in vivo.
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Affiliation(s)
| | - Sadia Sattar
- Molecular Virology Labs, Department of Biosciences, COMSATS University Islamabad, Islamabad Campus, Islamabad 45550, Pakistan
| | | | - Abdulaziz K. Al Mouslem
- Department of Pharmaceutical Sciences, College of Clinical Pharmacy, King Faisal University, Al Ahsa 31982, Saudi Arabia
| | - Ghallab Alotaibi
- Department of Pharmacology, College of Pharmacy, Al-Dawadmi Campus, Shaqra University, Shaqra, Saudi Arabia
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Li Y, Chen S, Yu Z, Yao J, Jia Y, Liao C, Chen J, Wei Y, Guo R, He L, Ding K. A Novel Bacillus Velezensis for Efficient Degradation of Zearalenone. Foods 2024; 13:530. [PMID: 38397507 PMCID: PMC10888444 DOI: 10.3390/foods13040530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Revised: 02/03/2024] [Accepted: 02/06/2024] [Indexed: 02/25/2024] Open
Abstract
Zearalenone (ZEN) is considered one of the most serious mycotoxins contaminating grains and their by-products, causing significant economic losses in the feed and food industries. Biodegradation pathways are currently considered the most efficient solution to remove ZEN contamination from foods. However, low degradation rates and vulnerability to environmental impacts limit the application of biodegradation pathways. Therefore, the main research objective of this article was to screen strains that can efficiently degrade ZEN and survive under harsh conditions. This study successfully isolated a new strain L9 which can efficiently degrade ZEN from 108 food ingredients. The results of sequence alignment showed that L9 is Bacillus velezensis. Meanwhile, we found that the L9 degradation rate reached 91.14% at 24 h and confirmed that the primary degradation mechanism of this strain is biodegradation. The strain exhibits resistance to high temperature, acid, and 0.3% bile salts. The results of whole-genome sequencing analysis showed that, it is possible that the strain encodes the key enzyme, such as chitinase, carboxylesterases, and lactone hydrolase, that work together to degrade ZEN. In addition, 227 unique genes in this strain are primarily involved in its replication, recombination, repair, and protective mechanisms. In summary, we successfully excavated a ZEN-degrading, genetically distinct strain of Bacillus velezensis that provides a solid foundation for the detoxification of feed and food contamination in the natural environment.
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Affiliation(s)
- Yijia Li
- Luoyang Key Laboratory of Live Carrier Biomaterial and Animal Disease Prevention and Control, College of Animal Science and Technology, Henan University of Science and Technology, Luoyang 471023, China; (Y.L.); (S.C.); (Z.Y.); (J.Y.); (Y.J.); (C.L.); (J.C.); (Y.W.); (R.G.); (L.H.)
- Laboratory of Functional Microbiology and Animal Health, College of Animal Science and Technology, Henan University of Science and Technology, Luoyang 471003, China
| | - Songbiao Chen
- Luoyang Key Laboratory of Live Carrier Biomaterial and Animal Disease Prevention and Control, College of Animal Science and Technology, Henan University of Science and Technology, Luoyang 471023, China; (Y.L.); (S.C.); (Z.Y.); (J.Y.); (Y.J.); (C.L.); (J.C.); (Y.W.); (R.G.); (L.H.)
- Laboratory of Functional Microbiology and Animal Health, College of Animal Science and Technology, Henan University of Science and Technology, Luoyang 471003, China
- Ministry of Education Key Laboratory for Animal Pathogens and Biosafety, Zhengzhou 450000, China
| | - Zuhua Yu
- Luoyang Key Laboratory of Live Carrier Biomaterial and Animal Disease Prevention and Control, College of Animal Science and Technology, Henan University of Science and Technology, Luoyang 471023, China; (Y.L.); (S.C.); (Z.Y.); (J.Y.); (Y.J.); (C.L.); (J.C.); (Y.W.); (R.G.); (L.H.)
- Laboratory of Functional Microbiology and Animal Health, College of Animal Science and Technology, Henan University of Science and Technology, Luoyang 471003, China
| | - Jie Yao
- Luoyang Key Laboratory of Live Carrier Biomaterial and Animal Disease Prevention and Control, College of Animal Science and Technology, Henan University of Science and Technology, Luoyang 471023, China; (Y.L.); (S.C.); (Z.Y.); (J.Y.); (Y.J.); (C.L.); (J.C.); (Y.W.); (R.G.); (L.H.)
- Laboratory of Functional Microbiology and Animal Health, College of Animal Science and Technology, Henan University of Science and Technology, Luoyang 471003, China
| | - Yanyan Jia
- Luoyang Key Laboratory of Live Carrier Biomaterial and Animal Disease Prevention and Control, College of Animal Science and Technology, Henan University of Science and Technology, Luoyang 471023, China; (Y.L.); (S.C.); (Z.Y.); (J.Y.); (Y.J.); (C.L.); (J.C.); (Y.W.); (R.G.); (L.H.)
- Laboratory of Functional Microbiology and Animal Health, College of Animal Science and Technology, Henan University of Science and Technology, Luoyang 471003, China
- Ministry of Education Key Laboratory for Animal Pathogens and Biosafety, Zhengzhou 450000, China
| | - Chengshui Liao
- Luoyang Key Laboratory of Live Carrier Biomaterial and Animal Disease Prevention and Control, College of Animal Science and Technology, Henan University of Science and Technology, Luoyang 471023, China; (Y.L.); (S.C.); (Z.Y.); (J.Y.); (Y.J.); (C.L.); (J.C.); (Y.W.); (R.G.); (L.H.)
- Laboratory of Functional Microbiology and Animal Health, College of Animal Science and Technology, Henan University of Science and Technology, Luoyang 471003, China
| | - Jian Chen
- Luoyang Key Laboratory of Live Carrier Biomaterial and Animal Disease Prevention and Control, College of Animal Science and Technology, Henan University of Science and Technology, Luoyang 471023, China; (Y.L.); (S.C.); (Z.Y.); (J.Y.); (Y.J.); (C.L.); (J.C.); (Y.W.); (R.G.); (L.H.)
- Laboratory of Functional Microbiology and Animal Health, College of Animal Science and Technology, Henan University of Science and Technology, Luoyang 471003, China
| | - Ying Wei
- Luoyang Key Laboratory of Live Carrier Biomaterial and Animal Disease Prevention and Control, College of Animal Science and Technology, Henan University of Science and Technology, Luoyang 471023, China; (Y.L.); (S.C.); (Z.Y.); (J.Y.); (Y.J.); (C.L.); (J.C.); (Y.W.); (R.G.); (L.H.)
- Laboratory of Functional Microbiology and Animal Health, College of Animal Science and Technology, Henan University of Science and Technology, Luoyang 471003, China
| | - Rongxian Guo
- Luoyang Key Laboratory of Live Carrier Biomaterial and Animal Disease Prevention and Control, College of Animal Science and Technology, Henan University of Science and Technology, Luoyang 471023, China; (Y.L.); (S.C.); (Z.Y.); (J.Y.); (Y.J.); (C.L.); (J.C.); (Y.W.); (R.G.); (L.H.)
- Laboratory of Functional Microbiology and Animal Health, College of Animal Science and Technology, Henan University of Science and Technology, Luoyang 471003, China
| | - Lei He
- Luoyang Key Laboratory of Live Carrier Biomaterial and Animal Disease Prevention and Control, College of Animal Science and Technology, Henan University of Science and Technology, Luoyang 471023, China; (Y.L.); (S.C.); (Z.Y.); (J.Y.); (Y.J.); (C.L.); (J.C.); (Y.W.); (R.G.); (L.H.)
- Laboratory of Functional Microbiology and Animal Health, College of Animal Science and Technology, Henan University of Science and Technology, Luoyang 471003, China
| | - Ke Ding
- Luoyang Key Laboratory of Live Carrier Biomaterial and Animal Disease Prevention and Control, College of Animal Science and Technology, Henan University of Science and Technology, Luoyang 471023, China; (Y.L.); (S.C.); (Z.Y.); (J.Y.); (Y.J.); (C.L.); (J.C.); (Y.W.); (R.G.); (L.H.)
- Laboratory of Functional Microbiology and Animal Health, College of Animal Science and Technology, Henan University of Science and Technology, Luoyang 471003, China
- Ministry of Education Key Laboratory for Animal Pathogens and Biosafety, Zhengzhou 450000, China
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Miranda RP, Turrini PCG, Bonadio DT, Zerillo MM, Berselli AP, Creste S, Van Sluys MA. Genome Organization of Four Brazilian Xanthomonas albilineans Strains Does Not Correlate with Aggressiveness. Microbiol Spectr 2023; 11:e0280222. [PMID: 37052486 PMCID: PMC10269729 DOI: 10.1128/spectrum.02802-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2022] [Accepted: 03/03/2023] [Indexed: 04/14/2023] Open
Abstract
An integrative approach combining genomics, transcriptomics, and cell biology is presented to address leaf scald disease, a major problem for the sugarcane industry. To gain insight into the biology of the causal agent, the complete genome sequences of four Brazilian Xanthomonas albilineans strains with differing virulence capabilities are presented and compared to the GPEPC73 reference strain and FJ1. Based on the aggressiveness index, different strains were compared: Xa04 and Xa11 are highly aggressive, Xa26 is intermediate, and Xa21 is the least, while, based on genome structure, Xa04 shares most of its genomic features with Xa26, and Xa11 share most of its genomic features with Xa21. In addition to presenting more clustered regularly interspaced short palindromic repeats (CRISPR) clusters, four more novel prophage insertions are present than the previously sequenced GPEPC73 and FJ1 strains. Incorporating the aggressiveness index and in vitro cell biology into these genome features indicates that disease establishment is not a result of a single determinant factor, as in most other Xanthomonas species. The Brazilian strains lack the previously described plasmids but present more prophage regions. In pairs, the most virulent and the least virulent share unique prophages. In vitro transcriptomics shed light on the 54 most highly expressed genes among the 4 strains compared to ribosomal proteins (RPs), of these, 3 outer membrane proteins. Finally, comparative albicidin inhibition rings and in vitro growth curves of the four strains also do not correlate with pathogenicity. In conclusion, the results disclose that leaf scald disease is not associated with a single shared characteristic between the most or the least pathogenic strains. IMPORTANCE An integrative approach is presented which combines genomics, transcriptomics, and cell biology to address leaf scald disease. The results presented here disclose that the disease is not associated with a single shared characteristic between the most pathogenic strains or a unique genomic pattern. Sequence data from four Brazilian strains are presented that differ in pathogenicity index: Xa04 and Xa11 are highly virulent, Xa26 is intermediate, and Xa21 is the least pathogenic strain, while, based on genome structure, Xa04 shares with Xa26, and Xa11 shares with X21 most of the genome features. Other than presenting more CRISPR clusters and prophages than the previously sequenced strains, the integration of aggressiveness and cell biology points out that disease establishment is not a result of a single determinant factor as in other xanthomonads.
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Affiliation(s)
- Raquel P. Miranda
- Departamento de Botânica, Instituto de Biociências, Universidade de São Paulo (USP), Butanta, São Paulo, Brazil
| | - Paula C. G. Turrini
- Departamento de Botânica, Instituto de Biociências, Universidade de São Paulo (USP), Butanta, São Paulo, Brazil
| | - Dora T. Bonadio
- Departamento de Botânica, Instituto de Biociências, Universidade de São Paulo (USP), Butanta, São Paulo, Brazil
| | - Marcelo M. Zerillo
- Departamento de Botânica, Instituto de Biociências, Universidade de São Paulo (USP), Butanta, São Paulo, Brazil
| | - Arthur P. Berselli
- Departamento de Botânica, Instituto de Biociências, Universidade de São Paulo (USP), Butanta, São Paulo, Brazil
| | - Silvana Creste
- Centro de Cana, Instituto Agronômico de Campinas (IAC), Campinas, São Paulo, Brazil
| | - Marie-Anne Van Sluys
- Departamento de Botânica, Instituto de Biociências, Universidade de São Paulo (USP), Butanta, São Paulo, Brazil
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Mendoza RM, Kim SH, Vasquez R, Hwang IC, Park YS, Paik HD, Moon GS, Kang DK. Bioinformatics and its role in the study of the evolution and probiotic potential of lactic acid bacteria. Food Sci Biotechnol 2023; 32:389-412. [PMID: 36911331 PMCID: PMC9992694 DOI: 10.1007/s10068-022-01142-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 06/30/2022] [Accepted: 07/13/2022] [Indexed: 11/04/2022] Open
Abstract
Due to their numerous well-established applications in the food industry, there have been many studies regarding the adaptation and evolution of lactic acid bacteria (LAB) in a wide variety of hosts and environments. Progress in sequencing technology and continual decreases in its costs have led to the availability of LAB genome sequence data. Bioinformatics has been central to the extraction of valuable information from these raw genome sequence data. This paper presents the roles of bioinformatics tools and databases in understanding the adaptation and evolution of LAB, as well as the bioinformatics methods used in the initial screening of LAB for probiotic potential. Moreover, the advantages, challenges, and limitations of employing bioinformatics for these purposes are discussed.
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Affiliation(s)
- Remilyn M. Mendoza
- Department of Animal Resources Science, Dankook University, 119 Dandae-ro, Cheonan, 31116 Republic of Korea
| | - Sang Hoon Kim
- Department of Animal Resources Science, Dankook University, 119 Dandae-ro, Cheonan, 31116 Republic of Korea
| | - Robie Vasquez
- Department of Animal Resources Science, Dankook University, 119 Dandae-ro, Cheonan, 31116 Republic of Korea
| | - In-Chan Hwang
- Department of Animal Resources Science, Dankook University, 119 Dandae-ro, Cheonan, 31116 Republic of Korea
| | - Young-Seo Park
- Department of Food Science and Biotechnology, Gachon University, Seongnam, 13120 Republic of Korea
| | - Hyun-Dong Paik
- Department of Food Science and Biotechnology of Animal Resource, Konkuk University, Seoul, 05029 Republic of Korea
| | - Gi-Seong Moon
- Division of Food Science and Biotechnology, Korea National University of Transportation, Jeungpyeong, 27909 Republic of Korea
| | - Dae-Kyung Kang
- Department of Animal Resources Science, Dankook University, 119 Dandae-ro, Cheonan, 31116 Republic of Korea
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Dereeper A, Summo M, Meyer DF. PanExplorer: a web-based tool for exploratory analysis and visualization of bacterial pan-genomes. Bioinformatics 2022; 38:4412-4414. [PMID: 35916725 PMCID: PMC9477528 DOI: 10.1093/bioinformatics/btac504] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Revised: 07/09/2022] [Accepted: 07/29/2022] [Indexed: 12/24/2022] Open
Abstract
MOTIVATION As pan-genome approaches are largely employed for bacterial comparative genomics and evolution analyses, but still difficult to be carried out by non-bioinformatician biologists, there is a need for an innovative tool facilitating the exploration of bacterial pan-genomes. RESULTS PanExplorer is a web application providing various genomic analyses and reports, giving intuitive views that enable a better understanding of bacterial pan-genomes. As an example, we produced the pan-genome for 121 Anaplasmataceae strains (including 30 Ehrlichia, 15 Anaplasma, 68 Wolbachia). AVAILABILITY AND IMPLEMENTATION PanExplorer is written in Perl CGI and relies on several JavaScript libraries for visualization (hotmap.js, MauveViewer, CircosJS). It is freely available at http://panexplorer.southgreen.fr. The source code has been released in a GitHub repository https://github.com/SouthGreenPlatform/PanExplorer. A documentation section is available on PanExplorer website.
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Affiliation(s)
| | - Marilyne Summo
- French Institute of Bioinformatics (IFB)—South Green Bioinformatics Platform, Bioversity, CIRAD, INRAE, IRD, F-34398 Montpellier, France,CIRAD, UMR AGAP, F-34398 Montpellier, France
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Schulz T, Wittler R, Stoye J. Sequence-based pangenomic core detection. iScience 2022; 25:104413. [PMID: 35663029 PMCID: PMC9160775 DOI: 10.1016/j.isci.2022.104413] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Revised: 04/20/2022] [Accepted: 05/09/2022] [Indexed: 11/17/2022] Open
Abstract
One of the most basic kinds of analysis to be performed on a pangenome is the detection of its core, i.e., the information shared among all members. Pangenomic core detection is classically done on the gene level and many tools focus exclusively on core detection in prokaryotes. Here, we present a new method for sequence-based pangenomic core detection. Our model generalizes from a strict core definition allowing us to flexibly determine suitable core properties depending on the research question and the dataset under consideration. We propose an algorithm based on a colored de Bruijn graph that runs in linear time with respect to the number of k-mers in the graph. An implementation of our method is called Corer. Because of the usage of a colored de Bruijn graph, it works alignment-free, is provided with a small memory footprint, and accepts as input assembled genomes as well as sequencing reads. Pangenomic core detection for large collections of prokaryotes or higher eukaryotes Whole-genome analysis with assemblies or even read data as input Alignment-free, linear time algorithm with small memory footprint Variation tolerance and quorum for flexible core detection
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Affiliation(s)
- Tizian Schulz
- Faculty of Technology and Center for Biotechnology (CeBiTec), Bielefeld University, Bielefeld, Germany
- Bielefeld Institute for Bioinformatics Infrastructure (BIBI), Bielefeld University, Bielefeld, Germany
- Graduate School “Digital Infrastructure for the Life Sciences” (DILS), Bielefeld University, Bielefeld, Germany
| | - Roland Wittler
- Faculty of Technology and Center for Biotechnology (CeBiTec), Bielefeld University, Bielefeld, Germany
- Bielefeld Institute for Bioinformatics Infrastructure (BIBI), Bielefeld University, Bielefeld, Germany
| | - Jens Stoye
- Faculty of Technology and Center for Biotechnology (CeBiTec), Bielefeld University, Bielefeld, Germany
- Bielefeld Institute for Bioinformatics Infrastructure (BIBI), Bielefeld University, Bielefeld, Germany
- Corresponding author
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Pronozin AY, Bragina MK, Salina EA. Crop pangenomes. Vavilovskii Zhurnal Genet Selektsii 2021; 25:57-63. [PMID: 34901703 PMCID: PMC8629360 DOI: 10.18699/vj21.007] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2020] [Revised: 12/27/2020] [Accepted: 01/03/2021] [Indexed: 11/19/2022] Open
Abstract
Progress in genome sequencing, assembly and analysis allows for a deeper study of agricultural plants' chromosome structures, gene identification and annotation. The published genomes of agricultural plants proved to be a valuable tool for studing gene functions and for marker-assisted and genomic selection. However, large structural genome changes, including gene copy number variations (CNVs) and gene presence/absence variations (PAVs), prevail in crops. These genomic variations play an important role in the functional set of genes and the gene composition in individuals of the same species and provide the genetic determination of the agronomically important crops properties. A high degree of genomic variation observed indicates that single reference genomes do not represent the diversity within a species, leading to the pangenome concept. The pangenome represents information about all genes in a taxon: those that are common to all taxon members and those that are variable and are partially or completely specific for particular individuals. Pangenome sequencing and analysis technologies provide a large-scale study of genomic variation and resources for an evolutionary research, functional genomics and crop breeding. This review provides an analysis of agricultural plants' pangenome studies. Pangenome structural features, methods and programs for bioinformatic analysis of pangenomic data are described.
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Affiliation(s)
- A Yu Pronozin
- Institute of Cytology and Genetics of Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - M K Bragina
- Institute of Cytology and Genetics of Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia Kurchatov Genomic Center of the Institute of Cytology and Genetics of Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - E A Salina
- Institute of Cytology and Genetics of Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia Kurchatov Genomic Center of the Institute of Cytology and Genetics of Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
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Liang Q, Lonardi S. Reference-agnostic representation and visualization of pan-genomes. BMC Bioinformatics 2021; 22:502. [PMID: 34656081 PMCID: PMC8520301 DOI: 10.1186/s12859-021-04424-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Accepted: 10/04/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The pan-genome of a species is the union of the genes and non-coding sequences present in all individuals (cultivar, accessions, or strains) within that species. RESULTS Here we introduce PGV, a reference-agnostic representation of the pan-genome of a species based on the notion of consensus ordering. Our experimental results demonstrate that PGV enables an intuitive, effective and interactive visualization of a pan-genome by providing a genome browser that can elucidate complex structural genomic variations. CONCLUSIONS The PGV software can be installed via conda or downloaded from https://github.com/ucrbioinfo/PGV . The companion PGV browser at http://pgv.cs.ucr.edu can be tested using example bed tracks available from the GitHub page.
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Affiliation(s)
- Qihua Liang
- Department of Computer Science and Engineering, University of California, Riverside, CA, 92521, USA.
| | - Stefano Lonardi
- Department of Computer Science and Engineering, University of California, Riverside, CA, 92521, USA
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9
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Song HC, Yang BT, Zhao T, Sun YF, Zhou JH, Shan XF, Qian AD, Sun WC, Kang YH. Comparative genomics analysis of strains from diverse sources reveals the evolutionary relationship of Aeromonas veronii. Microb Pathog 2021; 159:105134. [PMID: 34400283 DOI: 10.1016/j.micpath.2021.105134] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 07/27/2021] [Accepted: 08/07/2021] [Indexed: 10/20/2022]
Abstract
Aeromonas veronii (A. veronii, AV) strains are emerging zoonotic and aquatic pathogens, yet we know very little about their genomics. This study aims to utilize comparative genomics to investigate the intraspecific genetic diversity, differences in virulence factors and evolutionary mechanisms of A. veronii strains from diverse sources and to fundamentally demonstrate their pathogenic mechanisms. We conducted comparative genomics analysis of 39 A. veronii strains from different sources and found that 1993 core genes are shared by these strains and that these shared core genes may be necessary to maintain the basic characteristics of A. veronii. Additionally, phylogenetic relationship analysis based on these shared genes revealed that a distant relationship between the AMC34 strain and the other 38 strains but that, the genetic relationship among the 38 strains is relatively close, indicating that AMC34 may not belong to A. veronii. Furthermore, analysis of shared core genes and average nucleotide identity (ANI) values showed no obvious correlation with the location of A. veronii isolation and genetic relationship. Our research indicates the evolutionary mechanism of A. veronii from different sources and provides new insights for a deeper understanding of its pathogenic mechanism.
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Affiliation(s)
- Hai-Chao Song
- College of Veterinary Medicine, College of Animal Science and Technology, Jilin Provincial Engineering Research Center of Animal Probiotics, Key Laboratory of Animal Production and Product Quality Safety of Ministry of Education, Jilin Agricultural University, Changchun, Jilin, 130118, China
| | - Bin-Tong Yang
- College of Veterinary Medicine, College of Animal Science and Technology, Jilin Provincial Engineering Research Center of Animal Probiotics, Key Laboratory of Animal Production and Product Quality Safety of Ministry of Education, Jilin Agricultural University, Changchun, Jilin, 130118, China
| | - Tong Zhao
- College of Veterinary Medicine, College of Animal Science and Technology, Jilin Provincial Engineering Research Center of Animal Probiotics, Key Laboratory of Animal Production and Product Quality Safety of Ministry of Education, Jilin Agricultural University, Changchun, Jilin, 130118, China
| | - Yu-Feng Sun
- College of Veterinary Medicine, College of Animal Science and Technology, Jilin Provincial Engineering Research Center of Animal Probiotics, Key Laboratory of Animal Production and Product Quality Safety of Ministry of Education, Jilin Agricultural University, Changchun, Jilin, 130118, China
| | - Jin-Hua Zhou
- College of Veterinary Medicine, College of Animal Science and Technology, Jilin Provincial Engineering Research Center of Animal Probiotics, Key Laboratory of Animal Production and Product Quality Safety of Ministry of Education, Jilin Agricultural University, Changchun, Jilin, 130118, China
| | - Xiao-Feng Shan
- College of Veterinary Medicine, College of Animal Science and Technology, Jilin Provincial Engineering Research Center of Animal Probiotics, Key Laboratory of Animal Production and Product Quality Safety of Ministry of Education, Jilin Agricultural University, Changchun, Jilin, 130118, China
| | - Ai-Dong Qian
- College of Veterinary Medicine, College of Animal Science and Technology, Jilin Provincial Engineering Research Center of Animal Probiotics, Key Laboratory of Animal Production and Product Quality Safety of Ministry of Education, Jilin Agricultural University, Changchun, Jilin, 130118, China
| | - Wen-Chao Sun
- Institute of Virology, Wenzhou University, Wenzhou, Zhejiang, 325035, China.
| | - Yuan-Huan Kang
- College of Veterinary Medicine, College of Animal Science and Technology, Jilin Provincial Engineering Research Center of Animal Probiotics, Key Laboratory of Animal Production and Product Quality Safety of Ministry of Education, Jilin Agricultural University, Changchun, Jilin, 130118, China.
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Razzaq A, Kaur P, Akhter N, Wani SH, Saleem F. Next-Generation Breeding Strategies for Climate-Ready Crops. FRONTIERS IN PLANT SCIENCE 2021; 12:620420. [PMID: 34367194 PMCID: PMC8336580 DOI: 10.3389/fpls.2021.620420] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Accepted: 06/14/2021] [Indexed: 05/17/2023]
Abstract
Climate change is a threat to global food security due to the reduction of crop productivity around the globe. Food security is a matter of concern for stakeholders and policymakers as the global population is predicted to bypass 10 billion in the coming years. Crop improvement via modern breeding techniques along with efficient agronomic practices innovations in microbiome applications, and exploiting the natural variations in underutilized crops is an excellent way forward to fulfill future food requirements. In this review, we describe the next-generation breeding tools that can be used to increase crop production by developing climate-resilient superior genotypes to cope with the future challenges of global food security. Recent innovations in genomic-assisted breeding (GAB) strategies allow the construction of highly annotated crop pan-genomes to give a snapshot of the full landscape of genetic diversity (GD) and recapture the lost gene repertoire of a species. Pan-genomes provide new platforms to exploit these unique genes or genetic variation for optimizing breeding programs. The advent of next-generation clustered regularly interspaced short palindromic repeat/CRISPR-associated (CRISPR/Cas) systems, such as prime editing, base editing, and de nova domestication, has institutionalized the idea that genome editing is revamped for crop improvement. Also, the availability of versatile Cas orthologs, including Cas9, Cas12, Cas13, and Cas14, improved the editing efficiency. Now, the CRISPR/Cas systems have numerous applications in crop research and successfully edit the major crop to develop resistance against abiotic and biotic stress. By adopting high-throughput phenotyping approaches and big data analytics tools like artificial intelligence (AI) and machine learning (ML), agriculture is heading toward automation or digitalization. The integration of speed breeding with genomic and phenomic tools can allow rapid gene identifications and ultimately accelerate crop improvement programs. In addition, the integration of next-generation multidisciplinary breeding platforms can open exciting avenues to develop climate-ready crops toward global food security.
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Affiliation(s)
- Ali Razzaq
- Centre of Agricultural Biochemistry and Biotechnology (CABB), University of Agriculture, Faisalabad, Pakistan
| | - Parwinder Kaur
- UWA School of Agriculture and Environment, The University of Western Australia, Perth, WA, Australia
| | - Naheed Akhter
- College of Allied Health Professional, Faculty of Medical Sciences, Government College University Faisalabad, Faisalabad, Pakistan
| | - Shabir Hussain Wani
- Mountain Research Center for Field Crops, Khudwani, Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, Srinagar, India
| | - Fozia Saleem
- Centre of Agricultural Biochemistry and Biotechnology (CABB), University of Agriculture, Faisalabad, Pakistan
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11
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Abstract
A description of the genetic makeup of a species based on a single genome is often insufficient because it ignores the variability in gene repertoire among multiple strains. The estimation of the pangenome of a species is a solution to this issue as it provides an overview of genes that are shared by all strains and genes that are present in only some of the genomes. These different sets of genes can then be analyzed functionally to explore correlations with unique phenotypes and adaptations. This protocol presents the usage of Roary, a Linux-native pangenome application. Roary is a straightforward software that provides 1) an overview about core and accessory genes for those interested in general trends and, also, 2) detailed information on gene presence/absence in each genome for in-depth analyses. Results are provided both in text and graphic format.
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Affiliation(s)
- Farrah Sitto
- Department of Biological Sciences, Oakland University, Rochester, MI
| | - Fabia U Battistuzzi
- Department of Biological Sciences, Oakland University, Rochester, MI
- Center for Data Science and Big Data Analytics, Oakland University, Rochester, MI
- Corresponding author: E-mail:
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12
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Yan F, Gao F. A systematic strategy for the investigation of vaccines and drugs targeting bacteria. Comput Struct Biotechnol J 2020; 18:1525-1538. [PMID: 32637049 PMCID: PMC7327267 DOI: 10.1016/j.csbj.2020.06.008] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Revised: 06/02/2020] [Accepted: 06/03/2020] [Indexed: 02/07/2023] Open
Abstract
Infectious and epidemic diseases induced by bacteria have historically caused great distress to people, and have even resulted in a large number of deaths worldwide. At present, many researchers are working on the discovery of viable drug and vaccine targets for bacteria through multiple methods, including the analyses of comparative subtractive genome, core genome, replication-related proteins, transcriptomics and riboswitches, which plays a significant part in the treatment of infectious and pandemic diseases. The 3D structures of the desired target proteins, drugs and epitopes can be predicted and modeled through target analysis. Meanwhile, molecular dynamics (MD) analysis of the constructed drug/epitope-protein complexes is an important standard for testing the suitability of these screened drugs and vaccines. Currently, target discovery, target analysis and MD analysis are integrated into a systematic set of drug and vaccine analysis strategy for bacteria. We hope that this comprehensive strategy will help in the design of high-performance vaccines and drugs.
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Affiliation(s)
- Fangfang Yan
- Department of Physics, School of Science, Tianjin University, Tianjin 300072, China
| | - Feng Gao
- Department of Physics, School of Science, Tianjin University, Tianjin 300072, China
- Frontiers Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), Tianjin University, Tianjin 300072, China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin 300072, China
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13
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Current status of pan-genome analysis for pathogenic bacteria. Curr Opin Biotechnol 2020; 63:54-62. [DOI: 10.1016/j.copbio.2019.12.001] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2019] [Revised: 11/16/2019] [Accepted: 12/02/2019] [Indexed: 02/07/2023]
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14
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Rajkumari J, Chakraborty S, Pandey P. Distinctive features gleaned from the comparative genomes analysis of clinical and non-clinical isolates of Klebsiella pneumoniae. Bioinformation 2020; 16:256-268. [PMID: 32308268 PMCID: PMC7147497 DOI: 10.6026/97320630016256] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Revised: 03/10/2020] [Accepted: 03/15/2020] [Indexed: 11/23/2022] Open
Abstract
It is of interest to describe the distinctive features gleaned from the comparative genome analysis of clinical and non-clinical isolates of Klebsiella pneumoniae. The core genome of K. pneumoinae consisted of 3568 genes. Comparative genome analysis shows that mdtABCD, toxin-antitoxin systems are unique to clinical isolates and catB, benA, and transporter genes for citrate utilization are exclusive to non-clinical isolates. We further noted aromatic compound degrading genes in non-clinical isolates unlike in the later isolates. We grouped 88 core genes into 3 groups linked to infections, drug-resistance or xenobiotic metabolism using codon usage variation analysis. It is inferred using the neutrality plot analysis of GC12 with GC3 that codon usage variation is dominant over mutation pressure. Thus, we document data to distinguish clinical and non-clinical isolates of K. pneumoniae using comparative genomes analysis for understanding of genome diversity during speciation.
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Affiliation(s)
- Jina Rajkumari
- Department of Microbiology, Assam University, Silchar 788011, Assam, India
| | | | - Piyush Pandey
- Department of Microbiology, Assam University, Silchar 788011, Assam, India
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15
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Li J, Wang LH, Xiang FG, Ding WL, Xi LJ, Wang MQ, Xiao ZJ, Liu JG. Pseudomonas phragmitis sp. nov., isolated from petroleum polluted river sediment. Int J Syst Evol Microbiol 2020; 70:364-372. [PMID: 31661054 DOI: 10.1099/ijsem.0.003763] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
A Gram-stain-negative, rod-shaped bacterium, motile by means of a single polar flagellum, designated S-6-2T, was isolated from petroleum polluted river sediment in Huangdao, Shandong Province, PR China. The 16S rRNA gene sequence analysis revealed that S-6-2T represented a member of the genus Pseudomonas, sharing the highest sequence similarities with Pseudomonas parafulva (97.5 %) and Pseudomonas fulva (97.5 %). Phylogenetic analysis based on 16S rRNA gene, concatenated 16S rRNA, gyrB, rpoB and rpoD genes and genome core-genes indicated that S-6-2T was affiliated with the members of the Pseudomonas pertucinogena group. The average nucleotide identity (ANI) and genome-to-genome distance between the whole genome sequences of S-6-2T and closely related species of the genus Pseudomonas within the P. pertucinogena group were less than 77.94 % and 20.5 %, respectively. Differences in phenotypic characteristics were also found between S-6-2T and the closely related species. The major cellular fatty acids (>10 %) were summed feature 8 (C18 : 1ω7c/ C18 : 1ω6c), C16 : 0, C17 : 0cyclo and C12 : 0. The predominant respiratory quinone was ubiquinone 9. The major polar lipids were diphosphatidylglycerol (DPG), phosphatidylglycerol (PG), phosphatidylethanolamine (PE), one unidentified lipid (L1), two unidentified phospholipids (PL1 and PL2) and an aminophospholipid (APL). The DNA G+C content of the genome of S-6-2T was 60.1 mol%. On the basis of the evidence from the polyphasic taxonomic study, strain S-6-2T can be classified as representative of a novel species of the genus Pseudomonas, for which the name Pseudomonas phragmitis sp. nov. is proposed. The type strain is S-6-2T (=CGMCC 1.15798T=KCTC 52539T).
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Affiliation(s)
- Jing Li
- State Key Laboratory of Heavy Oil Processing & Center for Bioengineering and Biotechnology, College of Chemical Engineering, China University of Petroleum (East China), Qingdao 266580, PR China
| | - Lin-Hui Wang
- State Key Laboratory of Heavy Oil Processing & Center for Bioengineering and Biotechnology, College of Chemical Engineering, China University of Petroleum (East China), Qingdao 266580, PR China
| | - Fan-Gqin Xiang
- State Key Laboratory of Heavy Oil Processing & Center for Bioengineering and Biotechnology, College of Chemical Engineering, China University of Petroleum (East China), Qingdao 266580, PR China
| | - Wen-Long Ding
- State Key Laboratory of Heavy Oil Processing & Center for Bioengineering and Biotechnology, College of Chemical Engineering, China University of Petroleum (East China), Qingdao 266580, PR China
| | - Li-Jun Xi
- State Key Laboratory of Heavy Oil Processing & Center for Bioengineering and Biotechnology, College of Chemical Engineering, China University of Petroleum (East China), Qingdao 266580, PR China
| | - Ming-Qing Wang
- Shandong Peanut Research Institute, Qingdao 266100, PR China.,State Key Laboratory of Heavy Oil Processing & Center for Bioengineering and Biotechnology, College of Chemical Engineering, China University of Petroleum (East China), Qingdao 266580, PR China
| | - Zi-Jun Xiao
- State Key Laboratory of Heavy Oil Processing & Center for Bioengineering and Biotechnology, College of Chemical Engineering, China University of Petroleum (East China), Qingdao 266580, PR China
| | - Jian-Guo Liu
- State Key Laboratory of Heavy Oil Processing & Center for Bioengineering and Biotechnology, College of Chemical Engineering, China University of Petroleum (East China), Qingdao 266580, PR China
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16
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He Y, Zhou X, Chen Z, Deng X, Gehring A, Ou H, Zhang L, Shi X. PRAP: Pan Resistome analysis pipeline. BMC Bioinformatics 2020; 21:20. [PMID: 31941435 PMCID: PMC6964052 DOI: 10.1186/s12859-019-3335-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2019] [Accepted: 12/23/2019] [Indexed: 01/01/2023] Open
Abstract
Background Antibiotic resistance genes (ARGs) can spread among pathogens via horizontal gene transfer, resulting in imparities in their distribution even within the same species. Therefore, a pan-genome approach to analyzing resistomes is necessary for thoroughly characterizing patterns of ARGs distribution within particular pathogen populations. Software tools are readily available for either ARGs identification or pan-genome analysis, but few exist to combine the two functions. Results We developed Pan Resistome Analysis Pipeline (PRAP) for the rapid identification of antibiotic resistance genes from various formats of whole genome sequences based on the CARD or ResFinder databases. Detailed annotations were used to analyze pan-resistome features and characterize distributions of ARGs. The contribution of different alleles to antibiotic resistance was predicted by a random forest classifier. Results of analysis were presented in browsable files along with a variety of visualization options. We demonstrated the performance of PRAP by analyzing the genomes of 26 Salmonella enterica isolates from Shanghai, China. Conclusions PRAP was effective for identifying ARGs and visualizing pan-resistome features, therefore facilitating pan-genomic investigation of ARGs. This tool has the ability to further excavate potential relationships between antibiotic resistance genes and their phenotypic traits.
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Affiliation(s)
- Yichen He
- Department of Food Science and Technology, MOST-USDA Joint Research Center for Food Safety, School of Agriculture & Biology, and State Key Lab of Microbial Metabolism, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China
| | - Xiujuan Zhou
- Department of Food Science and Technology, MOST-USDA Joint Research Center for Food Safety, School of Agriculture & Biology, and State Key Lab of Microbial Metabolism, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China
| | - Ziyan Chen
- Department of Food Science and Technology, MOST-USDA Joint Research Center for Food Safety, School of Agriculture & Biology, and State Key Lab of Microbial Metabolism, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China
| | - Xiangyu Deng
- Center for Food Safety, Department of Food Science and Technology, University of Georgia, Griffin, GA, 30223, USA
| | - Andrew Gehring
- United States Department of Agriculture, Agricultural Research Service, Eastern Regional Research Center, 600 East Mermaid Lane, Wyndmoor, PA, 19038, USA
| | - Hongyu Ou
- Department of Food Science and Technology, MOST-USDA Joint Research Center for Food Safety, School of Agriculture & Biology, and State Key Lab of Microbial Metabolism, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China
| | - Lida Zhang
- Department of Food Science and Technology, MOST-USDA Joint Research Center for Food Safety, School of Agriculture & Biology, and State Key Lab of Microbial Metabolism, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China
| | - Xianming Shi
- Department of Food Science and Technology, MOST-USDA Joint Research Center for Food Safety, School of Agriculture & Biology, and State Key Lab of Microbial Metabolism, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China.
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17
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Huang W, Wang G, Yin C, Chen D, Dhand A, Chanza M, Dimitrova N, Fallon JT. Optimizing a Whole-Genome Sequencing Data Processing Pipeline for Precision Surveillance of Health Care-Associated Infections. Microorganisms 2019; 7:microorganisms7100388. [PMID: 31554234 PMCID: PMC6843764 DOI: 10.3390/microorganisms7100388] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2019] [Revised: 09/04/2019] [Accepted: 09/20/2019] [Indexed: 11/16/2022] Open
Abstract
The surveillance of health care-associated infection (HAI) is an essential element of the infection control program. While whole-genome sequencing (WGS) has widely been adopted for genomic surveillance, its data processing remains to be improved. Here, we propose a three-level data processing pipeline for the precision genomic surveillance of microorganisms without prior knowledge: species identification, multi-locus sequence typing (MLST), and sub-MLST clustering. The former two are closely connected to what have widely been used in current clinical microbiology laboratories, whereas the latter one provides significantly improved resolution and accuracy in genomic surveillance. Comparing to a broadly used reference-dependent alignment/mapping method and an annotation-dependent pan-/core-genome analysis, we implemented our reference- and annotation-independent, k-mer-based, simplified workflow to a collection of Acinetobacter and Enterococcus clinical isolates for tests. By taking both single nucleotide variants and genomic structural changes into account, the optimized k-mer-based pipeline demonstrated a global view of bacterial population structure in a rapid manner and discriminated the relatedness between bacterial isolates in more detail and precision. The newly developed WGS data processing pipeline would facilitate WGS application to the precision genomic surveillance of HAI. In addition, the results from such a WGS-based analysis would be useful for the precision laboratory diagnosis of infectious microorganisms.
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Affiliation(s)
- Weihua Huang
- Department of Pathology, New York Medical College, Valhalla, NY 10595, USA.
| | - Guiqing Wang
- Department of Pathology, New York Medical College, Valhalla, NY 10595, USA.
- Department of Pathology and Clinical Laboratories, Westchester Medical Center, Valhalla, NY 10595, USA.
| | - Changhong Yin
- Department of Pathology, New York Medical College, Valhalla, NY 10595, USA.
| | - Donald Chen
- Department of Medicine, New York Medical College, Valhalla, NY 10595, USA.
- Department of Infection Prevention and Control, Westchester Medical Center, Valhalla, NY 10595, USA.
| | - Abhay Dhand
- Department of Medicine, New York Medical College, Valhalla, NY 10595, USA.
| | - Melissa Chanza
- Department of Pathology, New York Medical College, Valhalla, NY 10595, USA.
| | | | - John T Fallon
- Department of Pathology, New York Medical College, Valhalla, NY 10595, USA.
- Department of Pathology and Clinical Laboratories, Westchester Medical Center, Valhalla, NY 10595, USA.
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18
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Santiago CRDN, Assis RDAB, Moreira LM, Digiampietri LA. Gene Tags Assessment by Comparative Genomics (GTACG): A User-Friendly Framework for Bacterial Comparative Genomics. Front Genet 2019; 10:725. [PMID: 31507629 PMCID: PMC6718126 DOI: 10.3389/fgene.2019.00725] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2019] [Accepted: 07/10/2019] [Indexed: 12/04/2022] Open
Abstract
Genomics research has produced an exponential amount of data. However, the genetic knowledge pertaining to certain phenotypic characteristics is lacking. Also, a considerable part of these genomes have coding sequences (CDSs) with unknown functions, posing additional challenges to researchers. Phylogenetically close microorganisms share much of their CDSs, and certain phenotypes unique to a set of microorganisms may be the result of the genes found exclusively in those microorganisms. This study presents the GTACG framework, an easy-to-use tool for identifying in the subgroups of bacterial genomes whose microorganisms have common phenotypic characteristics, to find data that differentiates them from other associated genomes in a simple and fast way. The GTACG analysis is based on the formation of homologous CDS clusters from local alignments. The front-end is easy to use, and the installation packages have been developed to enable users lacking knowledge of programming languages or bioinformatics analyze high-throughput data using the tool. The validation of the GTACG framework has been carried out based on a case report involving a set of 161 genomes from the Xanthomonadaceae family, in which 19 families of orthologous proteins were found in 90% of the plant-associated genomes, allowing the identification of the proteins potentially associated with adaptation and virulence in plant tissue. The results show the potential use of GTACG in the search for new targets for molecular studies, and GTACG can be used as a research tool by biologists who lack advanced knowledge in the use of computational tools for bacterial comparative genomics.
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Affiliation(s)
| | - Renata de Almeida Barbosa Assis
- Biotecnology Graduate Program, Núcleo de Pesquisas em Ciências Biológicas, Federal University of Ouro Preto, Ouro Preto, Brazil
| | - Leandro Marcio Moreira
- Biotecnology Graduate Program, Núcleo de Pesquisas em Ciências Biológicas, Federal University of Ouro Preto, Ouro Preto, Brazil
- Department of Biological Sciences, Federal University of Ouro Preto, Ouro Preto, Brazil
| | - Luciano Antonio Digiampietri
- Bioinformatics Graduate Program, University of Sao Paulo, Sao Paulo, Brazil
- School of Arts, Science, and Humanities, University of Sao Paulo, Sao Paulo, Brazil
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19
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Chen X, Zhang Y, Zhang Z, Zhao Y, Sun C, Yang M, Wang J, Liu Q, Zhang B, Chen M, Yu J, Wu J, Jin Z, Xiao J. PGAweb: A Web Server for Bacterial Pan-Genome Analysis. Front Microbiol 2018; 9:1910. [PMID: 30186253 PMCID: PMC6110895 DOI: 10.3389/fmicb.2018.01910] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2018] [Accepted: 07/30/2018] [Indexed: 01/22/2023] Open
Abstract
An astronomical increase in microbial genome data in recent years has led to strong demand for bioinformatic tools for pan-genome analysis within and across species. Here, we present PGAweb, a user-friendly, web-based tool for bacterial pan-genome analysis, which is composed of two main pan-genome analysis modules, PGAP and PGAP-X. PGAweb provides key interactive and customizable functions that include orthologous clustering, pan-genome profiling, sequence variation and evolution analysis, and functional classification. PGAweb presents features of genomic structural dynamics and sequence diversity with different visualization methods that are helpful for intuitively understanding the dynamics and evolution of bacterial genomes. PGAweb has an intuitive interface with one-click setting of parameters and is freely available at http://PGAweb.vlcc.cn/.
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Affiliation(s)
- Xinyu Chen
- Computer Network Information Center, Chinese Academy of Sciences, Beijing, China
| | - Yadong Zhang
- BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.,CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Zhewen Zhang
- BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.,CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Yongbing Zhao
- Lymphocyte Nuclear Biology, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, MD, United States
| | - Chen Sun
- Department of Computer Science and Engineering, The Pennsylvania State University, University Park, PA, United States
| | - Ming Yang
- Office of General Affairs, Chinese Academy of Sciences, Beijing, China
| | - Jinyue Wang
- BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.,CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Qian Liu
- Computer Network Information Center, Chinese Academy of Sciences, Beijing, China.,Center of Scientific Computing Applications and Research, Chinese Academy of Sciences, Beijing, China
| | - Baohua Zhang
- Computer Network Information Center, Chinese Academy of Sciences, Beijing, China.,Center of Scientific Computing Applications and Research, Chinese Academy of Sciences, Beijing, China
| | - Meili Chen
- BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.,CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Jun Yu
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Jiayan Wu
- CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China
| | - Zhong Jin
- Computer Network Information Center, Chinese Academy of Sciences, Beijing, China.,Center of Scientific Computing Applications and Research, Chinese Academy of Sciences, Beijing, China
| | - Jingfa Xiao
- BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.,CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
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Schönbach C, Li J, Ma L, Horton P, Sjaugi MF, Ranganathan S. A bioinformatics potpourri. BMC Genomics 2018; 19:920. [PMID: 29363432 PMCID: PMC5780851 DOI: 10.1186/s12864-017-4326-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
The 16th International Conference on Bioinformatics (InCoB) was held at Tsinghua University, Shenzhen from September 20 to 22, 2017. The annual conference of the Asia-Pacific Bioinformatics Network featured six keynotes, two invited talks, a panel discussion on big data driven bioinformatics and precision medicine, and 66 oral presentations of accepted research articles or posters. Fifty-seven articles comprising a topic assortment of algorithms, biomolecular networks, cancer and disease informatics, drug-target interactions and drug efficacy, gene regulation and expression, imaging, immunoinformatics, metagenomics, next generation sequencing for genomics and transcriptomics, ontologies, post-translational modification, and structural bioinformatics are the subject of this editorial for the InCoB2017 supplement issues in BMC Genomics, BMC Bioinformatics, BMC Systems Biology and BMC Medical Genomics. New Delhi will be the location of InCoB2018, scheduled for September 26-28, 2018.
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Affiliation(s)
- Christian Schönbach
- International Research Center for Medical Sciences, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, 860-0811 Japan
| | - Jinyan Li
- The Advanced Analytics Institute, University of Technology Sydney, Sydney, NSW 2007 Australia
| | - Lan Ma
- Graduate School at Shenzhen, Tsinghua University, Shenzhen, 518055 People’s Republic of China
| | - Paul Horton
- Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology, Tokyo, 135-0064 Japan
| | | | - Shoba Ranganathan
- Department of Chemistry and Biomolecular Sciences, Macquarie University, Sydney, NSW 2109 Australia
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