scholarly journals Development of a new barcode-based, multiplex-PCR, next-generation-sequencing assay and data processing and analytical pipeline for multiplicity of infection detection of Plasmodium falciparum

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Rebecca M. Mitchell ◽  
Zhiyong Zhou ◽  
Mili Sheth ◽  
Sheila Sergent ◽  
Michael Frace ◽  
...  
Keyword(s):  
Plasmodium Falciparum ◽  
Next Generation Sequencing ◽  
Dried Blood Spots ◽  
Multiplicity Of Infection ◽  
Next Generation ◽  
Bioinformatics Pipeline ◽  
Western Kenya ◽  
Multiplex Pcrs ◽  
Field Samples ◽  
Generation Sequencing

Abstract Background Simultaneous infection with multiple malaria parasite strains is common in high transmission areas. Quantifying the number of strains per host, or the multiplicity of infection (MOI), provides additional parasite indices for assessing transmission levels but it is challenging to measure accurately with current tools. This paper presents new laboratory and analytical methods for estimating the MOI of Plasmodium falciparum. Methods Based on 24 single nucleotide polymorphisms (SNPs) previously identified as stable, unlinked targets across 12 of the 14 chromosomes within P. falciparum genome, three multiplex PCRs of short target regions and subsequent next generation sequencing (NGS) of the amplicons were developed. A bioinformatics pipeline including B4Screening pathway removed spurious amplicons to ensure consistent frequency calls at each SNP location, compiled amplicons by SNP site diversity, and performed algorithmic haplotype and strain reconstruction. The pipeline was validated by 108 samples generated from cultured-laboratory strain mixtures in different proportions and concentrations, with and without pre-amplification, and using whole blood and dried blood spots (DBS). The pipeline was applied to 273 smear-positive samples from surveys conducted in western Kenya, then providing results into StrainRecon Thresholding for Infection Multiplicity (STIM), a novel MOI estimator. Results The 24 barcode SNPs were successfully identified uniformly across the 12 chromosomes of P. falciparum in a sample using the pipeline. Pre-amplification and parasite concentration, while non-linearly associated with SNP read depth, did not influence the SNP frequency calls. Based on consistent SNP frequency calls at targeted locations, the algorithmic strain reconstruction for each laboratory-mixed sample had 98.5% accuracy in dominant strains. STIM detected up to 5 strains in field samples from western Kenya and showed declining MOI over time (q < 0.02), from 4.32 strains per infected person in 1996 to 4.01, 3.56 and 3.35 in 2001, 2007 and 2012, and a reduction in the proportion of samples with 5 strains from 57% in 1996 to 18% in 2012. Conclusion The combined approach of new multiplex PCRs and NGS, the unique bioinformatics pipeline and STIM could identify 24 barcode SNPs of P. falciparum correctly and consistently. The methodology could be applied to field samples to reliably measure temporal changes in MOI.

scholarly journals Rapid assessment of phytoplankton assemblages using Next Generation Sequencing – Barcode of Life database: a widely applicable toolkit to monitor biodiversity and harmful algal blooms (HABs)

2019 ◽  
Author(s):  
Natalia V. Ivanova ◽  
L. Cynthia Watson ◽  
Jérôme Comte ◽  
Kyrylo Bessonov ◽  
Arusyak Abrahamyan ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Rapid Assessment ◽  
Algal Species ◽  
Reference Database ◽  
Next Generation ◽  
Bioinformatics Pipeline ◽  
Field Samples ◽  
Generation Sequencing

AbstractHarmful algal blooms have important implications for the health, functioning and services of aquatic ecosystems. Our ability to detect and monitor these events is often challenged by the lack of rapid and cost-effective methods to identify bloom-forming organisms and their potential for toxin production, Here, we developed and applied a combination of DNA barcoding and Next Generation Sequencing (NGS) for the rapid assessment of phytoplankton community composition with focus on two important indicators of ecosystem health: toxigenic bloom-forming cyanobacteria and impaired planktonic biodiversity. To develop this molecular toolset for identification of cyanobacterial and algal species present in HABs (Harmful Algal Blooms), hereafter called HAB-ID, we optimized NGS protocols, applied a newly developed bioinformatics pipeline and constructed a BOLD (Barcode of Life Data System) 16S reference database from cultures of 203 cyanobacterial and algal strains representing 101 species with particular focus on bloom and toxin producing taxa. Using the new reference database of 16S rDNA sequences and constructed mock communities of mixed strains for protocol validation we developed new NGS primer set which can recover 16S from both cyanobacteria and eukaryotic algal chloroplasts. We also developed DNA extraction protocols for cultured algal strains and environmental samples, which match commercial kit performance and offer a cost-efficient solution for large scale ecological assessments of harmful blooms while giving benefits of reproducibility and increased accessibility. Our bioinformatics pipeline was designed to handle low taxonomic resolution for problematic genera of cyanobacteria such as the Anabaena-Aphanizomenon-Dolichospermum species complex, two clusters of Anabaena (I and II), Planktothrix and Microcystis. This newly developed HAB-ID toolset was further validated by applying it to assess cyanobacterial and algal composition in field samples from waterbodies with recurrent HABs events.

scholarly journals Next generation sequencing of RB1gene for the molecular diagnosis of ethnic minority with retinoblastoma in Yunnan

2020 ◽  
Author(s):  
Huaiyu Gu ◽  
Zhen Zhang ◽  
Yi-shuang Xiao ◽  
Ru Shen ◽  
Hong-chao Jiang ◽  
...  
Keyword(s):  
Genetic Testing ◽  
Next Generation Sequencing ◽  
Low Income ◽  
Eastern China ◽  
Low Income Countries ◽  
Next Generation ◽  
Single Nucleotide Variants ◽  
Bioinformatics Pipeline ◽  
Generation Sequencing

Abstract Background: Retinoblastoma is a rare intraocular malignancy and typically initiated by inactivating biallelic mutations of RB1 gene. Each year, ~8,000 children worldwide are diagnosed for retinoblastoma. In high-income countries, patient survival is over 95% while low-income countries is ~30%.If disease is diagnosed early and treated in centers specializing in retinoblastoma, the survival might exceed 95% and many eyes could be safely treated and support a lifetime of good vision. In China, approximate 1,100 newly diagnosed cases are expected annually and 28 hospitals covering 25 provinces established centers classified by expertise and resources for better treatment options and follow-up. Comparing with other province of eastern China, Yunnan province is remote geographically. This might result that healthcare staff have low awareness of the role of genetic testing in management and screening in families.Methods: The patients with retinoblastoma were selected in Yunnan. DNA from blood was used for targeted gene sequencing. Then, an in-house bioinformatics pipeline was done to detect both single nucleotide variants and small insertions/deletions. The pathogenic mutations were identified and further confirmed by conventional methods and cosegregation in families.Results: Using our approach, targeted next generation sequencing was used to detect the mutation of these 12 probands. Bioinformatic predictions showed that nine mutations were found in our study and four were novel pathogenic variants in these nine mutations.Conclusions: It’s the first report to describe RB1 mutations in Yunnan children with retinoblastoma. This study would improve role of genetic testing for management and family screening.

scholarly journals DNase SISPA-Next Generation Sequencing Confirms Schmallenberg Virus in Belgian Field Samples and Identifies Genetic Variation in Europe

PLoS ONE ◽  
2012 ◽  
Vol 7 (7) ◽  
pp. e41967 ◽  
Author(s):  
Toon Rosseel ◽  
Matthias Scheuch ◽  
Dirk Höper ◽  
Nick De Regge ◽  
Ann Brigitte Caij ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Next Generation Sequencing ◽  
Schmallenberg Virus ◽  
Next Generation ◽  
Field Samples ◽  
Generation Sequencing

scholarly journals Next Generation Sequencing to Detect Variation in the Plasmodium falciparum Circumsporozoite Protein

2012 ◽  
Vol 86 (5) ◽  
pp. 775-781 ◽  
Author(s):  
Kavita Gandhi ◽  
Ando B. Guindo ◽  
Drissa Coulibaly ◽  
Ogobara K. Doumbo ◽  
Karim Traoré ◽  
...  
Keyword(s):  
Plasmodium Falciparum ◽  
Next Generation Sequencing ◽  
Circumsporozoite Protein ◽  
Next Generation ◽  
Generation Sequencing

scholarly journals Analytical validation and performance characteristics of a 48-gene next-generation sequencing panel for detecting potentially actionable genomic alterations in myeloid neoplasms

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0243683
Author(s):  
Sun Hee Rosenthal ◽  
Anna Gerasimova ◽  
Charles Ma ◽  
Hai-Rong Li ◽  
Andrew Grupe ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Myeloproliferative Neoplasms ◽  
Simultaneous Detection ◽  
Molecular Testing ◽  
Next Generation ◽  
Analytical Validation ◽  
Bioinformatics Pipeline ◽  
Myeloid Neoplasms ◽  
Clinically Significant ◽  
Generation Sequencing

Identification of genomic mutations by molecular testing plays an important role in diagnosis, prognosis, and treatment of myeloid neoplasms. Next-generation sequencing (NGS) is an efficient method for simultaneous detection of clinically significant genomic mutations with high sensitivity. Various NGS based in-house developed and commercial myeloid neoplasm panels have been integrated into routine clinical practice. However, some genes frequently mutated in myeloid malignancies are particularly difficult to sequence with NGS panels (e.g., CEBPA, CARL, and FLT3). We report development and validation of a 48-gene NGS panel that includes genes that are technically challenging for molecular profiling of myeloid neoplasms including acute myeloid leukemia (AML), myelodysplastic syndrome (MDS), and myeloproliferative neoplasms (MPN). Target regions were captured by hybridization with complementary biotinylated DNA baits, and NGS was performed on an Illumina NextSeq500 instrument. A bioinformatics pipeline that was developed in-house was used to detect single nucleotide variations (SNVs), insertions/deletions (indels), and FLT3 internal tandem duplications (FLT3-ITD). An analytical validation study was performed on 184 unique specimens for variants with allele frequencies ≥5%. Variants identified by the 48-gene panel were compared to those identified by a 35-gene hematologic neoplasms panel using an additional 137 unique specimens. The developed assay was applied to a large cohort (n = 2,053) of patients with suspected myeloid neoplasms. Analytical validation yielded 99.6% sensitivity (95% CI: 98.9–99.9%) and 100% specificity (95% CI: 100%). Concordance of variants detected by the 2 tested panels was 100%. Among patients with suspected myeloid neoplasms (n = 2,053), 54.5% patients harbored at least one clinically significant mutation: 77% in AML patients, 48% in MDS, and 45% in MPN. Together, these findings demonstrate that the assay can identify mutations associated with diagnosis, prognosis, and treatment options of myeloid neoplasms even in technically challenging genes.

Sign in / Sign up

Export Citation Format

Share Document