Examining microbial communities and biotransformation processes in dairy through the application of next generation sequencing technologies

Simple item page
dc.check.chapterOfThesisChapter 3, titled "Investigating the role of bacterial raw milk community members in chlorate reduction" which would be sections 3.1 to 3.8 (included), i.e., page numbers 135 to 186 (as provided on the word document), as this Chapter is a manuscript under prepration and is yet to be submitted as pre-print or for publication. An embrago has been placed on this Chapter for one year on the Intention to Submit form.en
dc.check.date2026-12-31
dc.contributor.advisorvan Sinderen, Douwe
dc.contributor.advisorCotter, Paul
dc.contributor.advisorexternalKenny, John
dc.contributor.advisorexternalO'Sullivan, Orla
dc.contributor.authorSrinivas, Meghanaen
dc.contributor.funderTeagasc
dc.contributor.funderScience Foundation Ireland
dc.date.accessioned2025-10-07T15:33:16Z
dc.date.available2025-10-07T15:33:16Z
dc.date.issued2024
dc.date.submitted2024
dc.description.abstractAdvancements 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.en
dc.description.statusNot peer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationSrinivas, M. 2024. Examining microbial communities and biotransformation processes in dairy through the application of next generation sequencing technologies. PhD Thesis, University College Cork.
dc.identifier.endpage290
dc.identifier.urihttps://hdl.handle.net/10468/17976
dc.language.isoenen
dc.publisherUniversity College Corken
dc.relation.projectTeagasc (Walsh Scholars Programme, ref no. 2020018)
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/SFI Rapid Response Supplemental Grant for Displaced Researchers - Ukraine/12/RC/2273_P2 (S1)/IE/12/RC/2273_P2 Supplemen
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Centres Programme::Phase 1/16/RC/3835/IE/VistaMilk Centre/
dc.rights© 2024, Meghana Srinivas.
dc.rights.urihttps://creativecommons.org/licenses/by-nd/4.0/
dc.subjectNext generation sequencing
dc.subjectLong read sequencing
dc.subject16S-ITS-23S sequencing
dc.subjectRRN sequencing
dc.subjectMicrobiome
dc.subjectDairy
dc.subjectChlorate
dc.subjectChlorate reducing bacteria
dc.titleExamining microbial communities and biotransformation processes in dairy through the application of next generation sequencing technologies
dc.typeDoctoral thesisen
dc.type.qualificationlevelDoctoralen
dc.type.qualificationnamePhD - Doctor of Philosophyen
Files
Original bundle
Now showing 1 - 3 of 3
Thumbnail Image
Name:
SrinivasM_PhD2024.pdf
Size:
7.02 MB
Format:
Adobe Portable Document Format
Description:
Full Text E-thesis
Thumbnail Image
Name:
SrinivasM_PhD2024.docx
Size:
9.94 MB
Format:
Microsoft Word XML
Description:
Full Text E-thesis (Word)
Thumbnail Image
Name:
SrinivasM_PhD2024_Submission for examination form.pdf
Size:
3.36 MB
Format:
Adobe Portable Document Format
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
5.2 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Research Theses
College of Science, Engineering and Food Science - Doctoral Theses
Microbiology - Doctoral Theses