Deep sequencing approach for investigating infectious agents causing fever
Susilawati, T.N., Jex, A.R., Cantacessi, C., Pearson, M., Navarro, S., Susianto, A., Loukas, A.C., and McBride, W.J.H. (2016) Deep sequencing approach for investigating infectious agents causing fever. European Journal of Clinical Microbiology and Infectious Diseases, 35 (7). pp. 1137-1149.
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Abstract
Acute undifferentiated fever (AUF) poses a diagnostic challenge due to the variety of possible aetiologies. While the majority of AUFs resolve spontaneously, some cases become prolonged and cause significant morbidity and mortality, necessitating improved diagnostic methods. This study evaluated the utility of deep sequencing in fever investigation. DNA and RNA were isolated from plasma/sera of AUF cases being investigated at Cairns Hospital in northern Australia, including eight control samples from patients with a confirmed diagnosis. Following isolation, DNA and RNA were bulk amplified and RNA was reverse transcribed to cDNA. The resulting DNA and cDNA amplicons were subjected to deep sequencing on an Illumina HiSeq 2000 platform. Bioinformatics analysis was performed using the program Kraken and the CLC assembly-alignment pipeline. The results were compared with the outcomes of clinical tests. We generated between 4 and 20 million reads per sample. The results of Kraken and CLC analyses concurred with diagnoses obtained by other means in 87.5 % (7/8) and 25 % (2/8) of control samples, respectively. Some plausible causes of fever were identified in ten patients who remained undiagnosed following routine hospital investigations, including Escherichia coli bacteraemia and scrub typhus that eluded conventional tests. Achromobacter xylosoxidans, Alteromonas macleodii and Enterobacteria phage were prevalent in all samples. A deep sequencing approach of patient plasma/serum samples led to the identification of aetiological agents putatively implicated in AUFs and enabled the study of microbial diversity in human blood. The application of this approach in hospital practice is currently limited by sequencing input requirements and complicated data analysis.
| Item ID: | 44697 |
|---|---|
| Item Type: | Article (Research - C1) |
| ISSN: | 1435-4373 |
| Additional Information: | This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
| Funders: | James Cook University, Far North Queensland Hospital Foundation |
| Date Deposited: | 21 Jul 2016 02:12 |
| FoR Codes: | 32 BIOMEDICAL AND CLINICAL SCIENCES > 3202 Clinical sciences > 320211 Infectious diseases @ 50% 32 BIOMEDICAL AND CLINICAL SCIENCES > 3204 Immunology > 320402 Applied immunology (incl. antibody engineering, xenotransplantation and t-cell therapies) @ 50% |
| SEO Codes: | 86 MANUFACTURING > 8608 Human Pharmaceutical Products > 860802 Human Diagnostics @ 34% 92 HEALTH > 9201 Clinical Health (Organs, Diseases and Abnormal Conditions) > 920109 Infectious Diseases @ 33% 92 HEALTH > 9202 Health and Support Services > 920203 Diagnostic Methods @ 33% |
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