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Aqueel R, Badar A, Roy N, Mushtaq Q, Ali AF, Bashir A, Ijaz UZ, Malik KA. Cotton microbiome profiling and Cotton Leaf Curl Disease (CLCuD) suppression through microbial consortia associated with Gossypium arboreum. NPJ Biofilms Microbiomes 2023; 9:100. [PMID: 38097579 PMCID: PMC10721634 DOI: 10.1038/s41522-023-00470-9] [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: 08/09/2023] [Accepted: 11/28/2023] [Indexed: 12/17/2023] Open
Abstract
The failure of breeding strategies has caused scientists to shift to other means where the new approach involves exploring the microbiome to modulate plant defense mechanisms against Cotton Leaf Curl Disease (CLCuD). The cotton microbiome of CLCuD-resistant varieties may harbor a multitude of bacterial genera that significantly contribute to disease resistance and provide information on metabolic pathways that differ between the susceptible and resistant varieties. The current study explores the microbiome of CLCuD-susceptible Gossypium hirsutum and CLCuD-resistant Gossypium arboreum using 16 S rRNA gene amplification for the leaf endophyte, leaf epiphyte, rhizosphere, and root endophyte of the two cotton species. This revealed that Pseudomonas inhabited the rhizosphere while Bacillus was predominantly found in the phyllosphere of CLCuV-resistant G. arboreum. Using salicylic acid-producing Serratia spp. and Fictibacillus spp. isolated from CLCuD-resistant G. arboreum, and guided by our analyses, we have successfully suppressed CLCuD in the susceptible G. hirsutum through pot assays. The applied strains exhibited less than 10% CLCuD incidence as compared to control group where it was 40% at 40 days post viral inoculation. Through detailed analytics, we have successfully demonstrated that the applied microbes serve as a biocontrol agent to suppress viral disease in Cotton.
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Affiliation(s)
- Rhea Aqueel
- Kauser Abdulla Malik School of Life Sciences, Forman Christian College (A Chartered University), Ferozepur Road, Lahore, 54600, Pakistan
- Water & Environment Research Group, University of Glasgow, Mazumdar-Shaw Advanced Research Centre, Glasgow, G11 6EW, UK
| | - Ayesha Badar
- Kauser Abdulla Malik School of Life Sciences, Forman Christian College (A Chartered University), Ferozepur Road, Lahore, 54600, Pakistan
| | - Nazish Roy
- Kauser Abdulla Malik School of Life Sciences, Forman Christian College (A Chartered University), Ferozepur Road, Lahore, 54600, Pakistan
| | - Qandeel Mushtaq
- Kauser Abdulla Malik School of Life Sciences, Forman Christian College (A Chartered University), Ferozepur Road, Lahore, 54600, Pakistan
| | - Aimen Fatima Ali
- Kauser Abdulla Malik School of Life Sciences, Forman Christian College (A Chartered University), Ferozepur Road, Lahore, 54600, Pakistan
| | - Aftab Bashir
- Kauser Abdulla Malik School of Life Sciences, Forman Christian College (A Chartered University), Ferozepur Road, Lahore, 54600, Pakistan
| | - Umer Zeeshan Ijaz
- Water & Environment Research Group, University of Glasgow, Mazumdar-Shaw Advanced Research Centre, Glasgow, G11 6EW, UK.
- National University of Ireland, Galway, University Road, Galway, H91 TK33, Ireland.
- Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool, L69 7BE, UK.
| | - Kauser Abdulla Malik
- Kauser Abdulla Malik School of Life Sciences, Forman Christian College (A Chartered University), Ferozepur Road, Lahore, 54600, Pakistan.
- Pakistan Academy of Sciences, Islamabad, Pakistan.
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Beyond Basic Diversity Estimates-Analytical Tools for Mechanistic Interpretations of Amplicon Sequencing Data. Microorganisms 2022; 10:microorganisms10101961. [PMID: 36296237 PMCID: PMC9609705 DOI: 10.3390/microorganisms10101961] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 09/29/2022] [Accepted: 09/30/2022] [Indexed: 11/07/2022] Open
Abstract
Understanding microbial ecology through amplifying short read regions, typically 16S rRNA for prokaryotic species or 18S rRNA for eukaryotic species, remains a popular, economical choice. These methods provide relative abundances of key microbial taxa, which, depending on the experimental design, can be used to infer mechanistic ecological underpinnings. In this review, we discuss recent advancements in in situ analytical tools that have the power to elucidate ecological phenomena, unveil the metabolic potential of microbial communities, identify complex multidimensional interactions between species, and compare stability and complexity under different conditions. Additionally, we highlight methods that incorporate various modalities and additional information, which in combination with abundance data, can help us understand how microbial communities respond to change in a typical ecosystem. Whilst the field of microbial informatics continues to progress substantially, our emphasis is on popular methods that are applicable to a broad range of study designs. The application of these methods can increase our mechanistic understanding of the ongoing dynamics of complex microbial communities.
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Chen Y, Li J, Zhang Y, Zhang M, Sun Z, Jing G, Huang S, Su X. Parallel-Meta Suite: Interactive and rapid microbiome data analysis on multiple platforms. IMETA 2022; 1:e1. [PMID: 38867729 PMCID: PMC10989749 DOI: 10.1002/imt2.1] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 12/13/2021] [Accepted: 12/17/2021] [Indexed: 06/14/2024]
Abstract
Massive microbiome sequencing data has been generated, which elucidates associations between microbes and their environmental phenotypes such as host health or ecosystem status. Outstanding bioinformatic tools are the basis to decipher the biological information hidden under microbiome data. However, most approaches placed difficulties on the accessibility to nonprofessional users. On the other side, the computing throughput has become a significant bottleneck of many analytical pipelines in processing large-scale datasets. In this study, we introduce Parallel-Meta Suite (PMS), an interactive software package for fast and comprehensive microbiome data analysis, visualization, and interpretation. It covers a wide array of functions for data preprocessing, statistics, visualization by state-of-the-art algorithms in a user-friendly graphical interface, which is accessible to diverse users. To meet the rapidly increasing computational demands, the entire procedure of PMS has been optimized by a parallel computing scheme, enabling the rapid processing of thousands of samples. PMS is compatible with multiple platforms, and an installer has been integrated for full-automatic installation.
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Affiliation(s)
- Yuzhu Chen
- College of Computer Science and TechnologyQingdao UniversityQingdaoShandongChina
| | - Jian Li
- College of Computer Science and TechnologyQingdao UniversityQingdaoShandongChina
| | - Yufeng Zhang
- College of Computer Science and TechnologyQingdao UniversityQingdaoShandongChina
| | - Mingqian Zhang
- College of Computer Science and TechnologyQingdao UniversityQingdaoShandongChina
| | - Zheng Sun
- Single‐Cell Center, Qingdao Institute of BioEnergy and Bioprocess TechnologyChinese Academy of SciencesQingdaoShandongChina
| | - Gongchao Jing
- Single‐Cell Center, Qingdao Institute of BioEnergy and Bioprocess TechnologyChinese Academy of SciencesQingdaoShandongChina
| | - Shi Huang
- Faculty of DentistryThe University of Hong KongHong KongHong Kong SARChina
| | - Xiaoquan Su
- College of Computer Science and TechnologyQingdao UniversityQingdaoShandongChina
- Single‐Cell Center, Qingdao Institute of BioEnergy and Bioprocess TechnologyChinese Academy of SciencesQingdaoShandongChina
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