Bibliographic Details
| Title: |
Multi-Locus Next-Generation Sequence Typing of DNA Extracted From Pooled Colonies Detects Multiple Unrelated Candida albicans Strains in a Significant Proportion of Patient Samples |
| Authors: |
Ningxin Zhang, David Wheeler, Mauro Truglio, Cristina Lazzarini, Jenine Upritchard, Wendy McKinney, Karen Rogers, Anna Prigitano, Anna M. Tortorano, Richard D. Cannon, Roland S. Broadbent, Sally Roberts, Jan Schmid |
| Source: |
Frontiers in Microbiology, Vol 9 (2018) |
| Publisher Information: |
Frontiers Media S.A., 2018. |
| Publication Year: |
2018 |
| Collection: |
LCC:Microbiology |
| Subject Terms: |
Candida albicans, next generation-multi locus sequence typing (NGS-MLST), detection of multiple strains in patient samples, candidemia, endogenous sources of infection, transmission, Microbiology, QR1-502 |
| More Details: |
The yeast Candida albicans is an important opportunistic human pathogen. For C. albicans strain typing or drug susceptibility testing, a single colony recovered from a patient sample is normally used. This is insufficient when multiple strains are present at the site sampled. How often this is the case is unclear. Previous studies, confined to oral, vaginal and vulvar samples, have yielded conflicting results and have assessed too small a number of colonies per sample to reliably detect the presence of multiple strains. We developed a next-generation sequencing (NGS) modification of the highly discriminatory C. albicans MLST (multilocus sequence typing) method, 100+1 NGS-MLST, for detection and typing of multiple strains in clinical samples. In 100+1 NGS-MLST, DNA is extracted from a pool of colonies from a patient sample and also from one of the colonies. MLST amplicons from both DNA preparations are analyzed by high-throughput sequencing. Using base call frequencies, our bespoke DALMATIONS software determines the MLST type of the single colony. If base call frequency differences between pool and single colony indicate the presence of an additional strain, the differences are used to computationally infer the second MLST type without the need for MLST of additional individual colonies. In mixes of previously typed pairs of strains, 100+1 NGS-MLST reliably detected a second strain. Inferred MLST types of second strains were always more similar to their real MLST types than to those of any of 59 other isolates (22 of 31 inferred types were identical to the real type). Using 100+1 NGS-MLST we found that 7/60 human samples, including three superficial candidiasis samples, contained two unrelated strains. In addition, at least one sample contained two highly similar variants of the same strain. The probability of samples containing unrelated strains appears to differ considerably between body sites. Our findings indicate the need for wider surveys to determine if, for some types of samples, routine testing for the presence of multiple strains is warranted. 100+1 NGS-MLST is effective for this purpose. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
1664-302X |
| Relation: |
https://www.frontiersin.org/article/10.3389/fmicb.2018.01179/full; https://doaj.org/toc/1664-302X |
| DOI: |
10.3389/fmicb.2018.01179 |
| Access URL: |
https://doaj.org/article/2ad23eb74f2d4f2385c0b3b6e958210f |
| Accession Number: |
edsdoj.2ad23eb74f2d4f2385c0b3b6e958210f |
| Database: |
Directory of Open Access Journals |
