Screening of β-glucoside kinase directed evolution library to form a sulfur-phosphorus bond

Glycoscience is a field that explores the structures and functions of glycans promising great advances in an array of applications. The objective of this research is to form a sulfur-phosphorus bond at the position 6’ of the sugar involved in many biological processes. A directed evolution strategy was adopted with error-prone PCR technique to create random mutagenesis of recombinant plasmid library of the β-glucoside kinase (βglk) recloned into a pTrcHisB plasmid and transformed into Escherichia coli. Following the creation of libraries, high throughput screening by 96-well microplate using fluorescent activated cell sorting (FACS) techniques were carried out. Positive clones were selected, sequenced for identification and enzyme expression and characterization were carried out

Bioprospecting novel cellulose-degrading enzymes from pome metagenomic DNA libraries by enrichment strategy

Green technology is the environment-friendly way to protect the Earth’s natural resources and the environment we inhabit. The functionalmetagenomic approach has proven to be a powerful tool to identify novel biocatalysts indispensables in green technology of biofuel production from plant’s biomass through metagenomic DNA library construction and high-throughput screening. Culture enrichment strategies are additional pre-screening methods to provide an attractive mean of enhancing the screening hit rate. In this work metagenomic DNA libraries were made from Malaysian palm oil mill effluent (POME) microorganisms after culture enrichment experiment based on natural selection principle. Metagenomic DNA was extracted from both enriched and non-enriched cultures and cloned to pCC1FOS fosmid and transformed into EPI300™-T1RE. coli.Qualitative and quantitative analysis of metagenomic DNA and recombinant clones are provided to confirm the efficiency of enrichment strategy

Palm oil mill effluent metagenome for cellulose-degrading enzymes

Abstract: Functional metagenomic approach incorporating metagenomic DNA library construction and high-throughput screening has proven to be a powerful tool for identifying novel biocatalysts (Wouters et al. 2014). Culture enrichment strategies are additional pre-screening methods employed to provide an attractive means of enhancing the screening hit rate. In this work metagenomic DNA libraries were generated from Malaysian palm oil mill effluent (POME) microorganisms. Three different samples, namely fresh, ambient-cooled and anaerobic POME microorganisms were inoculated in a medium under controlled temperature, light and pH conditions, and in the presence of carboxymethylcellulose (CMC) for short incubation time in order to allow growth of microorganisms with cellulose-degrading capabilities. Quantitative and qualitative metagenomic DNA tests indicate the presence of high number of microbes in anaerobic POME compared to other samples which guided us to use this particular sample in further experiments. Titer test also showed that the number of enriched-library clones is 5 to 7 times higher than non-enriched anaerobic POME. The use of such a combination of enrichment strategy with metagenomics greatly improves the screening process for biocatalysts

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

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. ********************************************************** 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 algoritma graf 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