Literature DB >> 33100921

Laboratory Optimization Tweaks for Sanger Sequencing in a Resource-Limited Setting.

Chika K Onwuamah1, Azuka P Okwuraiwe1, Rahaman A Ahmed1, Judith O Sokei1, Jamda Ponmak1, Leona C Okoli1, Brian A Kagurusi2, Joseph Anejo-Okopi3.   

Abstract

Despite various challenges that hinder the implementation of high-tech molecular methods in resource-limited settings, we have been able to implement and achieve International Organization for Standardization 15189:2012 accreditation for genotypic HIV drug resistance testing in our facility. At the Center for Human Virology and Genomics, Nigerian Institute of Medical Research, Nigeria has recorded a high sequencing success rate and good quality sequence data. This was achieved by optimizing laboratory processes from 2008 to the current date. We have optimized sample preparation, RT-PCR, several post-PCR processes, and the cycle sequencing to improve the sensitivity of amplification even with limited plasma samples and low viral copy numbers. The optimized workflow maximizes output, minimizes reagent wastage, and achieves substantial cost savings without compromising the quality of the sequence data. Our performance at our last external quality assurance program is a testimonial to the efficiency of the workflow. For the 5-sample panel, each with 67-68 mutation points evaluated, we scored 100% for all 5 specimens. Our optimized laboratory workflow is thus documented to support laboratories and to help researchers achieve excellent results the first time and eliminate contamination while minimizing the wastage of costly sequencing reagents. © Association of Biomolecular Resource Facilities.

Entities:  

Keywords:  biomedical research · HIV drug resistance · laboratory workflow · reverse transcriptase polymerase chain reaction

Mesh:

Substances:

Year:  2020        PMID: 33100921      PMCID: PMC7566614          DOI: 10.7171/jbt.20-3104-006

Source DB:  PubMed          Journal:  J Biomol Tech        ISSN: 1524-0215


  11 in total

1.  A Guide to HIV-1 Reverse Transcriptase and Protease Sequencing for Drug Resistance Studies.

Authors:  Robert W Shafer; Kathryn Dupnik; Mark A Winters; Susan H Eshleman
Journal:  HIV Seq Compend       Date:  2001

2.  Development and performance of conventional HIV-1 phenotyping (Antivirogram®) and genotype-based calculated phenotyping assay (virco®TYPE HIV-1) on protease and reverse transcriptase genes to evaluate drug resistance.

Authors:  Theresa Pattery; Yvan Verlinden; Hans De Wolf; David Nauwelaers; Kurt Van Baelen; Margariet Van Houtte; Paula Mc Kenna; Jorge Villacian
Journal:  Intervirology       Date:  2012-01-24       Impact factor: 1.763

Review 3.  The case for expanding access to highly active antiretroviral therapy to curb the growth of the HIV epidemic.

Authors:  Julio S G Montaner; Robert Hogg; Evan Wood; Thomas Kerr; Mark Tyndall; Adrian R Levy; P Richard Harrigan
Journal:  Lancet       Date:  2006-08-05       Impact factor: 79.321

4.  Continued improvement in survival among HIV-infected individuals with newer forms of highly active antiretroviral therapy.

Authors:  Viviane D Lima; Robert S Hogg; P Richard Harrigan; David Moore; Benita Yip; Evan Wood; Julio S G Montaner
Journal:  AIDS       Date:  2007-03-30       Impact factor: 4.177

5.  Affordable HIV drug-resistance testing for monitoring of antiretroviral therapy in sub-Saharan Africa.

Authors:  Seth C Inzaule; Pascale Ondoa; Trevor Peter; Peter N Mugyenyi; Wendy S Stevens; Tobias F Rinke de Wit; Raph L Hamers
Journal:  Lancet Infect Dis       Date:  2016-08-25       Impact factor: 25.071

6.  HIV drug resistance testing by high-multiplex "wide" sequencing on the MiSeq instrument.

Authors:  H R Lapointe; W Dong; G Q Lee; D R Bangsberg; J N Martin; A R Mocello; Y Boum; A Karakas; D Kirkby; A F Y Poon; P R Harrigan; C J Brumme
Journal:  Antimicrob Agents Chemother       Date:  2015-08-17       Impact factor: 5.191

7.  Optimization of a low cost and broadly sensitive genotyping assay for HIV-1 drug resistance surveillance and monitoring in resource-limited settings.

Authors:  Zhiyong Zhou; Nick Wagar; Joshua R DeVos; Erin Rottinghaus; Karidia Diallo; Duc B Nguyen; Orji Bassey; Richard Ugbena; Nellie Wadonda-Kabondo; Michelle S McConnell; Isaac Zulu; Benson Chilima; John Nkengasong; Chunfu Yang
Journal:  PLoS One       Date:  2011-11-23       Impact factor: 3.240

8.  HIV-1 Drug Resistance Mutations: Potential Applications for Point-of-Care Genotypic Resistance Testing.

Authors:  Soo-Yon Rhee; Michael R Jordan; Elliot Raizes; Arlene Chua; Neil Parkin; Rami Kantor; Gert U Van Zyl; Irene Mukui; Mina C Hosseinipour; Lisa M Frenkel; Nicaise Ndembi; Raph L Hamers; Tobias F Rinke de Wit; Carole L Wallis; Ravindra K Gupta; Joseph Fokam; Clement Zeh; Jonathan M Schapiro; Sergio Carmona; David Katzenstein; Michele Tang; Avelin F Aghokeng; Tulio De Oliveira; Annemarie M J Wensing; Joel E Gallant; Mark A Wainberg; Douglas D Richman; Joseph E Fitzgibbon; Marco Schito; Silvia Bertagnolio; Chunfu Yang; Robert W Shafer
Journal:  PLoS One       Date:  2015-12-30       Impact factor: 3.240

9.  HIV drug resistance in sub-Saharan Africa: public health questions and the potential role of real-world data and mathematical modelling.

Authors:  Reneé de Waal; Richard Lessells; Anthony Hauser; Roger Kouyos; Mary-Ann Davies; Matthias Egger; Gilles Wandeler
Journal:  J Virus Erad       Date:  2018-11-15

Review 10.  HIV-1 drug resistance and resistance testing.

Authors:  Dana S Clutter; Michael R Jordan; Silvia Bertagnolio; Robert W Shafer
Journal:  Infect Genet Evol       Date:  2016-08-29       Impact factor: 3.342

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