Elucidating the lignocellulose digestion mechanism Coptotermes curvignathus based on carbohydrate-active enzymes profile using the meta-transcriptomic approach

Termites are efficient lignocellulose decomposers that thrive on woody materials and contribute to carbon mineralization in both tropical and subtropical regions. Due to hydrolytic stability and crosslinking between the polysaccharides (cellulose & hemicellulose) and the lignin via ester and eth...

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Main Authors: Hoe, Pik Kheng, King, Jie Hung, Ong, Kian Huat, Bong, Choon Fah, Mahadi, Nor Muhammad
Format: Article
Published: Persatuan Biologi Gunaan Malaysia 2023
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author Hoe, Pik Kheng
King, Jie Hung
Ong, Kian Huat
Bong, Choon Fah
Mahadi, Nor Muhammad
author_facet Hoe, Pik Kheng
King, Jie Hung
Ong, Kian Huat
Bong, Choon Fah
Mahadi, Nor Muhammad
author_sort Hoe, Pik Kheng
collection UPM
description Termites are efficient lignocellulose decomposers that thrive on woody materials and contribute to carbon mineralization in both tropical and subtropical regions. Due to hydrolytic stability and crosslinking between the polysaccharides (cellulose & hemicellulose) and the lignin via ester and ether linkages, termites would require a large variety of enzymes to degrade lignocellulose. Coptotermes curvignathus, an endemic species of termite from Southeast Asia, has been classified as an urban pest in the region and is known as the largest and most aggressive among the oriental Coptotermes spp. Its Carbohydrate-Active enzymes (CAZymes) are the main interest of this study. RNA of C. curvignathus was extracted and sequenced using Illumina Hiseq 2000 sequencing platform, and de novo assembled with Trinity pipeline. There were 101 CAZymes families in C. curvignathus digestome. CAZymes break down complex carbohydrates and glycoconjugates for a large body of biological roles and perform their function, usually with high specificity. Enzymes coding for glycosyl hydrolase (GH) families had the highest transcript abundance, accounting for about 93% of the total CAZymes reads. This was followed by CBM (≈1%), GT family (≈4%), CE family (<1%), AA family (<2%), and PL family (<1%). Due to the carbohydrate diversity exceeding the number of protein folds, CAZymes have evolved from a limited number of progenitors by acquiring novel specificities at substrate and product levels. Such a dizzying array of substrates and enzymes makes C. curvignathus a high-performance lignocellulose degrader.
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spelling upm.eprints-1076502024-09-12T04:03:33Z http://psasir.upm.edu.my/id/eprint/107650/ Elucidating the lignocellulose digestion mechanism Coptotermes curvignathus based on carbohydrate-active enzymes profile using the meta-transcriptomic approach Hoe, Pik Kheng King, Jie Hung Ong, Kian Huat Bong, Choon Fah Mahadi, Nor Muhammad Termites are efficient lignocellulose decomposers that thrive on woody materials and contribute to carbon mineralization in both tropical and subtropical regions. Due to hydrolytic stability and crosslinking between the polysaccharides (cellulose & hemicellulose) and the lignin via ester and ether linkages, termites would require a large variety of enzymes to degrade lignocellulose. Coptotermes curvignathus, an endemic species of termite from Southeast Asia, has been classified as an urban pest in the region and is known as the largest and most aggressive among the oriental Coptotermes spp. Its Carbohydrate-Active enzymes (CAZymes) are the main interest of this study. RNA of C. curvignathus was extracted and sequenced using Illumina Hiseq 2000 sequencing platform, and de novo assembled with Trinity pipeline. There were 101 CAZymes families in C. curvignathus digestome. CAZymes break down complex carbohydrates and glycoconjugates for a large body of biological roles and perform their function, usually with high specificity. Enzymes coding for glycosyl hydrolase (GH) families had the highest transcript abundance, accounting for about 93% of the total CAZymes reads. This was followed by CBM (≈1%), GT family (≈4%), CE family (<1%), AA family (<2%), and PL family (<1%). Due to the carbohydrate diversity exceeding the number of protein folds, CAZymes have evolved from a limited number of progenitors by acquiring novel specificities at substrate and product levels. Such a dizzying array of substrates and enzymes makes C. curvignathus a high-performance lignocellulose degrader. Persatuan Biologi Gunaan Malaysia 2023-12-15 Article PeerReviewed Hoe, Pik Kheng and King, Jie Hung and Ong, Kian Huat and Bong, Choon Fah and Mahadi, Nor Muhammad (2023) Elucidating the lignocellulose digestion mechanism Coptotermes curvignathus based on carbohydrate-active enzymes profile using the meta-transcriptomic approach. Malaysian Applied Biology, 52 (5). pp. 177-186. ISSN 0126-8643; ESSN: 2462-151X https://jms.mabjournal.com/index.php/mab/article/view/2927 10.55230/mabjournal.v52i5.icfic13
spellingShingle Hoe, Pik Kheng
King, Jie Hung
Ong, Kian Huat
Bong, Choon Fah
Mahadi, Nor Muhammad
Elucidating the lignocellulose digestion mechanism Coptotermes curvignathus based on carbohydrate-active enzymes profile using the meta-transcriptomic approach
title Elucidating the lignocellulose digestion mechanism Coptotermes curvignathus based on carbohydrate-active enzymes profile using the meta-transcriptomic approach
title_full Elucidating the lignocellulose digestion mechanism Coptotermes curvignathus based on carbohydrate-active enzymes profile using the meta-transcriptomic approach
title_fullStr Elucidating the lignocellulose digestion mechanism Coptotermes curvignathus based on carbohydrate-active enzymes profile using the meta-transcriptomic approach
title_full_unstemmed Elucidating the lignocellulose digestion mechanism Coptotermes curvignathus based on carbohydrate-active enzymes profile using the meta-transcriptomic approach
title_short Elucidating the lignocellulose digestion mechanism Coptotermes curvignathus based on carbohydrate-active enzymes profile using the meta-transcriptomic approach
title_sort elucidating the lignocellulose digestion mechanism coptotermes curvignathus based on carbohydrate active enzymes profile using the meta transcriptomic approach
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