Culture-Independent Metagenomics Characterisation of Infection

Mwaigwisya, Solomon (2018) Culture-Independent Metagenomics Characterisation of Infection. Doctoral thesis, University of East Anglia.

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Next-generation sequencing (NGS) technologies are revolutionising our ability to study and characterise microorganisms and investigate infectious diseases. The potential of metagenomics sequencing for use as a single, all-inclusive diagnostic test for comprehensive detection of pathogens, resistance genes and virulence markers directly from clinical samples has been discussed at length in the literature in recent years. However, implementation has been slow as there are several challenges associated with applying metagenomics sequencing to clinical microbiology. These include the large number of human cells, the often low proportion of pathogen cells/DNA and, in some cases, the high background of normal microbiological flora present in clinical samples. Here we report rapid, culture-independent metagenomics workflows that overcome these challenges.

Metagenomics pipelines were developed and evaluated in three model samples: i) blood, for the diagnosis of sepsis, ii) urine, for the diagnosis of urinary tract infections, and iii) stool, for the diagnosis of Clostridioides difficile infection. Developed workflows comprised of rapid depletion of unwanted cells/DNA (human and normal flora (in stool)), genomic DNA extraction from remaining microorganisms, whole genome amplification (in blood), rapid nanopore library preparation and real-time metagenomics analysis.

These pipelines enabled comprehensive detection of pathogens and resistance genes in clinical blood samples within eight hours and in clinical urine samples within four hours. The C. difficile pipeline could enrich for and sequence the pathogen directly from stool within 24 hours. However, further optimisation of this pipeline is required to increase genome coverage before it can be utilised for typing C. difficile directly from stool.

The rapid host depletion and metagenomics sequencing pipelines developed here demonstrate that this technology can provide clinicians with the necessary information to tailor antibiotic therapy for the specific infecting pathogen before second dose of empiric therapy is administered (usually eight-hour intervals), thereby improving patient outcomes and antibiotic stewardship.

Item Type: Thesis (Doctoral)
Faculty \ School: Faculty of Medicine and Health Sciences > Norwich Medical School
Depositing User: Jennifer Whitaker
Date Deposited: 21 Jan 2019 14:31
Last Modified: 17 Dec 2019 01:38


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