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Examining microbial communities and biotransformation processes in dairy through the application of next generation sequencing technologies
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Date
2024
Authors
Srinivas, Meghana
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Publisher
University College Cork
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Abstract
Advancements in sequencing technologies have enabled the study of microbiomes rather than individual isolates, shedding light on the community behaviour of microbes. In this thesis, high-throughput sequencing and associated computational methods were developed and applied to achieve two primary objectives, described below: (i) identify chlorate-reducing bacteria in the context of the dairy supply chain to develop chlorate mitigation strategies, and (ii) develop and benchmark 16S-ITS-23S rRNA operon (RRN) sequencing to improve species-level resolution of microbial communities.
Chlorate has emerged as a residue of concern in the dairy supply chain, which is introduced into milk and milk products through the use of chlorine-based detergents during cleaning processes. Chlorate consumption has been linked to thyroid issues, particularly in vulnerable populations like infants and young children. In response, the European Food Safety Authority (EFSA) has set a maximum residual limit of 0.10 mg/kg for chlorate in milk. Although Ireland has adopted "chlorine-free" cleaning alternatives to mitigate chlorate contamination, chlorate is still detected in milk and dairy products, likely due to the use of chlorinated water. While chlorate bioremediation strategies have been applied in soil and wastewater, they have not yet been explored in the dairy supply chain. Chapter 2 and Chapter 3 address this issue by investigating the presence of chlorate-reducing bacteria in milk. Chapter 2 employed culture-based methods, identifying Hafnia paralvei isolates that significantly reduced chlorate levels in milk. Genomic analysis of the H. paralvei isolates revealed genes encoding the enzyme NarG, which has been previously reported in literature to carry out chlorate reduction, suggesting its role in the chlorate reduction process in H. paralvei. Chapter 3 used shotgun metagenomics to study the effects of incubation temperature and chlorate presence on the raw milk microbiome, finding that incubation temperature had a significant impact, whereas chlorate presence had no effect. Genes linked to various pathways associated with chlorate reduction were identified, suggesting multiple metabolic routes through which chlorate can be reduced by members of the milk microbial community. However, many of these pathways were identified as incomplete in the metagenome-assembled genomes (MAGs) of the various genera present in the milk samples, indicating the possibility of metabolic cross-feeding among community members.
Short-read sequencing platforms like Illumina have been widely used for amplicon sequencing but are limited to genus-level resolution due to length restrictions. Long-read sequencing platforms such as PacBio and Oxford Nanopore Technologies (ONT) have made strides in accuracy, allowing full-length 16S rRNA sequencing, which improves species-level resolution. However, distinguishing closely related species remains a challenge even with full-length 16S rRNA sequencing. To overcome this, the scope of long-read sequencing has expanded, targeting the entire 16S-ITS-23S rRNA operon (RRN) for enhanced species-level resolution. In Chapter 4, an RRN database called GROND was developed, incorporating rrn operons from genomes in the GTDB and RefSeq databases. Chapter 5 evaluated the GROND database alongside other RRN databases, assessing the performance of various primer pairs, long-read sequencing platforms, and classifiers. As detailed in Chapter 5, primer pairs and sequencing platforms did not significantly impact species-level resolution, while classifiers and databases had a significant effect. The combination of Minimap2 and the GROND database consistently performed well in terms of F1 score, precision, recall, and Bray Curtis Dissimilarity metrics, followed closely by Minimap2 paired with the publicly available MIrROR database.
Overall, this thesis demonstrates the application of high-throughput sequencing technologies to identify chlorate-reducing bacteria in milk, aiming to develop strategies to reduce chlorate contamination and ensure the safety of dairy products. Additionally, it advances the field of RRN sequencing, providing a rapid and cost-effective method for achieving precise species-level resolution in microbial communities.
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Keywords
Next generation sequencing , Long read sequencing , 16S-ITS-23S sequencing , RRN sequencing , Microbiome , Dairy , Chlorate , Chlorate reducing bacteria
Citation
Srinivas, M. 2024. Examining microbial communities and biotransformation processes in dairy through the application of next generation sequencing technologies. PhD Thesis, University College Cork.