Sains Malaysiana 47(12)(2018): 2951–2960

http://dx.doi.org/10.17576/jsm-2018-4712-03

 

Next Generation Sequencing-Data Analysis for Cellulose- and Xylan-Degrading Enzymes from Pome Metagenome

(Analisis Data-Penjujukan Generasi Seterusnya bagi Enzim Selulosa dan Xilan Mendegradasi daripada Metagenom Pome)

 

FARAH FADWA BENBELGACEM¹, MOHD NOOR MAT ISA², MUHAMMAD ALFATIH MUDDATHIR ABDELRAHIM³, AFIDALINA TUMIAN³, OUALID ABDELKADER BELLAG1, ADIBAH PARMAN¹, IBRAHIM ALI NOORBATCHA¹ & HAMZAH MOHD SALLEH⁴*

 

¹Bioprocess & Molecular Engineering Research Unit (BPMERU), Department of Biotechnology Engineering, Kulliyyah of Engineering, International Islamic University Malaysia, Jalan Gombak, 53100 Kuala Lumpur, Federal Territory, Malaysia

 

²Malaysia Genome Institute, Jalan Bangi, 43000 Kajang, Selangor Darul Ehsan, Malaysia

 

³Department of Computer Science, Kulliyyah of Information and Communication Technology, International Islamic University Malaysia, Jalan Gombak, 53100 Kuala Lumpur, Federal Territory, Malaysia

 

⁴International Institute for Halal Research and Training (INHART), International Islamic University Malaysia, Jalan Gombak, 53100 Kuala Lumpur, Federal Territory, Malaysia

 

Diserahkan: 30 Mei 2018/Diterima: 18 September 2018

 

ABSTRACT

Metagenomic DNA library from palm oil mill effluent (POME) was constructed and subjected to high-throughput screening to find genes encoding cellulose- and xylan-degrading enzymes. DNA of 30 positive fosmid clones were sequenced with next generation sequencing technology and the raw data (short insert-paired) was analyzed with bioinformatic tools. First, the quality of 64,821,599 reverse and forward sequences of 101 bp length raw data was tested using Fastqc and SOLEXA. Then, raw data filtering was carried out by trimming low quality values and short reads and the vector sequences were removed and again the output was checked and the trimming was repeated until a high quality read sets was obtained. The second step was the de novo assembly of sequences to reconstruct 2900 contigs following de Bruijn graph algorithm. Pre-assembled contigs were arranged in order, the distances between contigs were identified and oriented with SSPACE, where 2139 scaffolds have been reconstructed. 16,386 genes have been identified after gene prediction using Prodigal and putative ID assignment with Blastp vs NR protein. The acceptable strategy to handle metagenomic NGS-data in order to detect known and potentially unknown genes is presented and we showed the computational efficiency of de Bruijn graph algorithm of de novo assembly to 21 bioprospect genes encoding cellulose-degrading enzymes and 6 genes encoding xylan-degrading enzymes of 30.3% to 100% identity percentage.

 

Keywords: de Bruijn; de novo assembly; metagenomics; scaffold; SSPACE

 

ABSTRAK

Sebuah pangkalan data yang menyimpan DNA metagenom daripada efluen kilang minyak kelapa sawit telah dibina dan disaring dengan menggunakan kaedah penyaringan berskala besar untuk mencari enzim selulosa dan xilan. DNA daripada fosmid berklon positif telah disusun dengan menggunakan teknologi penjujukan berskala besar dan data mentah (dalam susunan pendek berpasangan) telah dianalisis dengan kaedah bioinformatik. Pertama, kualiti susunan 64,821,599 balikan dan ke depan sebanyak 101 bp panjang data mentah telah diuji menggunakan Fastqc dan SOLEXA. Kemudian, penyaringan data mentah dilakukan dengan memotong susunan yang berkualiti rendah dan pendek. Malah, vektor juga telah dikeluarkan dan susunan output telah diperiksa dan ditrim berulang kali sehingga set bacaan berkualiti tinggi diperoleh. Langkah kedua adalah himpunan de novo iaitu untuk menyusun semula 2900 contigs mengikut de Bruijn. Contigs awal sebelum himpunan telah diatur mengikut susunan, jarak antara contigs telah dikenal pasti berorientasikan SSPACE dengan 2139 perancah telah dibina. 16,386 gen telah dikenal pasti selepas kaedah peramalan gen menggunakan Prodigal dan penugasan ID putatif dengan Blastp vs protein NR. Strategi yang betul dalam mengendalikan data NGS-metagenom untuk mengesan gen-gen yang diketahui dan juga yang berpotensi tetapi masih belum diketahui telah ditunjukkan. Dalam kajian ini, kami menunjukkan kecekapan pengiraan komputer berdasarkan algoritma graf himpunan de Bruijn de novo kepada bioprospek 21 gen yang mengekodkan enzim selulosa dan 6 gen yang mengekod enzim xilan daripada 30.3% kepada 100% peratusan identiti yang serupa.

 

Kata kunci: de Bruijn; himpunan de novo; metagenom; perancah; SSPACE

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*Pengarang untuk surat-menyurat; email: hamzah@iium.edu.my