| Literature DB >> 26360259 |
Masako Nishizawa1, Masakazu Matsuda2, Junko Hattori2, Teiichiro Shiino3, Tetsuro Matano1, Walid Heneine4, Jeffrey A Johnson4, Wataru Sugiura5.
Abstract
BACKGROUND: Drug-resistant HIV are more prevalent and persist longer than previously demonstrated by bulk sequencing due to the ability to detect low-frequency variants. To clarify a clinical benefit to monitoring minority-level drug resistance populations as a guide to select active drugs for salvage therapy, we retrospectively analyzed the dynamics of low-frequency drug-resistant population in antiretroviral (ARV)-exposed drug resistant individuals.Entities:
Mesh:
Year: 2015 PMID: 26360259 PMCID: PMC4567277 DOI: 10.1371/journal.pone.0135941
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Demographics and clinical data.
| Patient ID | Gender | Subtype | Viral load(copies/mL) | CD4 count | Observation period(month) | 1st regimen | ARVs included in the regimens | Resistance mutations by bulk-sequencing | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| min | max | median | min | max | median | NRTI | NNRTI | NRTI | NNRTI | |||||
| 1 | M | B | 100 | 130700 | 10300 | 151 | 227 | 180 | 65 | d4T/3TC | AZT, d4T, 3TC, ABC, TDF | NVP, EFV | M41L, M184V, T215Y | K103N, Y181C |
| 2 | M | B | 100 | 1200000 | 45850 | 184 | 319 | 199 | 103 | d4T | AZT, ddI, ddC, d4T, 3TC ABC | NVP | M41L, K70R, M184V, T215Y | Y181C |
| 3 | M | B | 2000 | 60100 | 10450 | 42.6 | 262 | 109 | 85 | AZT,3TC, IDV | AZT, 3TC, TDF | EFV | M41L, K70R, M184V | K103N |
| 4 | M | B | 900 | 358800 | 33900 | 80 | 1999 | 265 | 104 | ddI | d4T, ddI, 3TC, TDF | EFV | M41L, M184V, T215F | K103N |
| 5 | M | B | 100 | 849500 | 26300 | 36 | 434 | 80 | 101 | AZT | AZT, ddI, ddC, d4T, 3TC, ABC, TDF | EFV | M41L, M184V, T215Y | K103N, Y181C |
| 6 | M | B | 2000 | 443500 | 36500 | 126 | 569 | 371 | 102 | AZT | AZT, ddI, ddC, d4T, 3TC, ABC, TDF | NVP, EFV | M41L, M184V, T215Y | K103N, Y181C |
Fig 1Chronologies of ART regimens, drug resistance mutations detected by bulk sequencing and AS-PCR, and change in viral loads in enrolled individuals.
The chronological tables of (i) drug resistance mutations, (ii) viral load and (iii) ART regimens are depicted for each individual (A-F). (i) Resistance mutations detected: Bulk sequencing and AS-PCR results are shown in solid bars and closed circles, respectively. Their colors are matched with corresponding antiretrovirals shown in the ART regimen part of the table. (ii) Viral load: The arrows in each graph indicate the point that minor-drug resistance mutations were detected. The numbers indicated the ID of samples (S2–S6 Tables). (iii) ART regimens: Solid circles indicate the starting point of each regimen and the arrows indicate the period of each regimen.
Fig 2Phylogenetic analyses of AS-PCR amplicon and bulk sequences.
Genetic relationships between pre-existing minority drug resistance populations and majority-level drug resistant populations that subsequently arose were analyzed by Maximum Likelihood phylogeny inferred by MEGA6. Numbers next to each symbol indicates the collecting point IDs of each patient (S4 Table and S5 Table). Italic numbers at the tree-nodes indicate bootstrap values of the taxa analyzed. (A) Analysis of K103N populations in Individual 3: Solid and open circles indicate K103N positive and negative bulk sequence results, respectively. A solid triangle indicates K103N-positive amplicon at ID 9. ID 9 samples are highlighted with red. (B) Analysis of T215I populations in Individual 3: Solid and open circles indicate T215I positive and negative bulk sequence results, respectively. Two solid triangles indicate T215I-positive AS-PCR amplicon from ID 17 and 21 samples. ID17 and 21 are highlighted with red. (C) Analysis of K103N populations in Individual 4: Solid and open circles indicate K103N positive and negative bulk sequence results, respectively. A solid triangle indicates sequence data of K103N-positive amplicon derived from ID 2 sample. Red letters; ID 2 samples are highlighted with red.