Metagenomic Analysis of Potential Microbes in Microbial Fermentation and Flavour Formation of Ghanaian Cocoa Beans

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Show simple item record Agyirifo, Daniel Sakyi 2017-04-11T09:34:36Z 2017-04-11T09:34:36Z 2015-08
dc.description A thesis submitted in fulfilment of the requirements for the award of the degree of doctor of philosophy in the department of biochemistry and biotechnology in the school of pure and applied sciences of Kenyatta University, August 2015 en_US
dc.description.abstract Production of cocoa contributes significantly to poverty reduction and generates huge foreign exchange earnings for national development. Fermentation of cocoa beans is the most critical stage in production of cocoa products such as chocolates and its derivatives. Chocolate acquires its desired colour and flavour during fermentation through the activities of a variety of microorganisms including yeasts, lactic acid and acetic acid bacteria. There is a limited understanding of the complex response of microbial diversity during cocoa bean fermentation. Traditional methods for elucidating microbial diversity are time consuming and they focus on the detection of a single microbe or a panel of microbes. However, molecular methods such as whole genome shotgun metagenomics approach sequences DNA directly from the environment bypassing the need for culturing. The aim of the present study was to investigate microbial communities in the cocoa bean fermentation heap using a culture-independent approach to elucidate microbial diversity, structure, functional annotation and mapping unto metabolic pathways. Genomic DNA was purified from four samples of cocoa bean fermentation heap using a modified CTAB method followed by library preparation. Sequence data was generated on Illumina Hiseq 2000 paired-end technology (Macrogen Inc). Normalisation and quality control was performed using FASTQC vO.ll.2. Paired-end sequencing of libraries generated 46 gigabytes (GB) (462,844,468 reads) of data. Quality filtering retained 373,289,474 reads (approximately 38 GB). Sequences were assembled by iterative deBruijn graph algorithm using SOAPdenov02 with an N50 of 2,017 base pairs. Bacterial taxa assignment, rarefaction analysis, and the Shannon alpha-diversity index were calculated using the Metagenome Rapid Annotation using Subsystem Technology (MG-RAST) server. Taxonomic analysis based on genes predicted from the metagenome identified a high percentage of bacteria (88.75%), yeast (7.19%), and bacteriophages (1%) from the cocoa microbiome. The cocoa microbiome was dominated by the following genera: Lactobacillus (20%), Gluconacetobacter (9%), Acetobacter (7%) and Gluconobacter (6%). The mean species diversity, measured by Shannon alpha-diversity index, was estimated at 142.81. Assignment of metagenomic sequences to SEED database categories at 97% sequence similarity identified a genetic profile characteristic of heterotrophic lactic acid fermentation of carbohydrates and aromatic amino acids. Metabolism of aromatic compounds, amino acids and their derivatives and carbohydrates represented 0.7%, 6.2% and 9.6% respectively of the microbiome. Genome coverage of the mapped reads was observed at 2.0X, 1.7X and 0.2X for the recruited A. pasteurianus, Gluconobacter oxydans and L. plantarum respectively. Overall, these results provide insights into the cocoa microbiome, identifying fermentation processes carried out broadly by complex microbial communities and metabolic pathways encoding aromatic compounds such as phenylacetaldehdye, butanediol, acetoin, theobromine and luteolin that are required for flavour and aroma production. The results obtained will help develop targeted inoculations to produce desired chocolate flavour or targeted metabolic pathways for the selection of microbes for good aroma and flavour compounds formation en_US
dc.description.sponsorship Kenyatta University en_US
dc.language.iso en en_US
dc.publisher Kenyatta University en_US
dc.title Metagenomic Analysis of Potential Microbes in Microbial Fermentation and Flavour Formation of Ghanaian Cocoa Beans en_US
dc.type Thesis en_US

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