scholarly journals Evolution and expansion of multidrug resistant malaria in Southeast Asia: a genomic epidemiology study

2019 ◽  
Author(s):  
William L Hamilton ◽  
Roberto Amato ◽  
Rob W van der Pluijm ◽  
Christopher G Jacob ◽  
Huynh Hong Quang ◽  
...  
Keyword(s):  
Southeast Asia ◽  
International Development ◽  
Genetic Relatedness ◽  
Multidrug Resistant ◽  
Added Value ◽  
Chloroquine Resistance ◽  
Clinical Samples ◽  
Whole Genome Sequencing Data ◽  
Sequencing Data ◽  
Drug Pressure

SummaryBackgroundA multidrug resistant co-lineage of Plasmodium falciparum malaria, named KEL1/PLA1, spread across Cambodia c.2008-2013, causing high treatment failure rates to the frontline combination therapy dihydroartemisinin-piperaquine. Here, we report on the evolution and spread of KEL1/PLA1 in subsequent years.MethodsWe analysed whole genome sequencing data from 1,673 P. falciparum clinical samples collected in 2008-2018 from northeast Thailand, Laos, Cambodia and Vietnam. By investigating genome-wide relatedness between parasites, we inferred patterns of shared ancestry in the KEL1/PLA1 population.FindingsKEL1/PLA1 spread rapidly from 2015 into all of the surveyed countries and now exceeds 80% of the P. falciparum population in several regions. These parasites maintained a high level of genetic relatedness reflecting their common origin. However, several genetic subgroups have recently emerged within this co-lineage with diverse geographical distributions. Some of these emerging KEL1/PLA1 subgroups carry recent mutations in the chloroquine resistance transporter (crt) gene, which arise on a specific genetic background comprising multiple genomic regions.InterpretationAfter emerging and circulating for several years within Cambodia, the P. falciparum KEL1/PLA1 co-lineage diversified into multiple subgroups and acquired new genetic features including novel crt mutations. These subgroups have rapidly spread into neighbouring countries, suggesting enhanced fitness. These findings highlight the urgent need for elimination of this increasingly drug-resistant parasite co-lineage, and the importance of genetic surveillance in accelerating elimination efforts.FundingWellcome Trust, Bill & Melinda Gates Foundation, UK Medical Research Council, UK Department for International Development.Research in contextEvidence before this studyThis study updates our previous work describing the emergence and spread of a multidrug resistant P. falciparum co-lineage (KEL1/PLA1) within Cambodia up to 2013. Since then, a regional genetic surveillance project, GenRe-Mekong, has reported that markers of dihydroartemisinin-piperaquine (DHA-PPQ) resistance have increased in frequency in neighbouring countries. A PubMed search (terms: “artemisinin”, “piperaquine”, “resistance”, “southeast asia”) for articles listed since our previous study (from 30/10/2017 to 05/01/2019) yielded 28 results, including reports of a recent sharp decline in DHA-PPQ clinical efficacy in Vietnam; the spread of genetic markers of DHA-PPQ resistance into neighbouring countries by Imwong and colleagues; and multiple reports associating mutations in the crt gene with piperaquine resistance, including newly emerging crt variants in Southeast Asia.Added value of this studyWe analysed P. falciparum whole genomes collected up to early 2018 from Eastern Southeast Asia (Cambodia and surrounding regions), describing the fine-scale epidemiology of multiple KEL1/PLA1 genetic subgroups that have spread out from Cambodia since 2015 and taken over indigenous parasite populations in northeastern Thailand, southern and central Vietnam and parts of southern Laos. Several newly emerging crt mutations accompanied the spread and expansion of KEL1/PLA1 subgroups, suggesting an active proliferation of biologically fit, multidrug resistant parasites.Implications of all the available evidenceThe problem of P. falciparum multidrug resistance has dramatically worsened in Eastern Southeast Asia since previous reports. KEL1/PLA1 has diversified and spread widely across Eastern Southeast Asia since 2015, becoming the predominant parasite group in several regions. This may have been fuelled by continued parasite exposure to DHA-PPQ, resulting in sustained selection after KEL1/PLA1 became established. Continued drug pressure enabled the acquisition of further mutations, resulting in higher levels of resistance. These data demonstrate the value of pathogen genetic surveillance and the urgent need to eliminate these dangerous parasites.

scholarly journals Outbreak of Shiga toxin-producing Escherichia coli O157:H7 linked to raw drinking milk resolved by rapid application of advanced pathogen characterisation methods, England, August to October 2017

2019 ◽  
Vol 24 (16) ◽  
Author(s):  
Juli Treacy ◽  
Claire Jenkins ◽  
Karthik Paranthaman ◽  
Frieda Jorgensen ◽  
Doris Mueller-Doblies ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Shiga Toxin ◽  
Genetic Relatedness ◽  
Control Measures ◽  
Public Access ◽  
Epidemiological Surveillance ◽  
Effective Control ◽  
Whole Genome Sequencing Data ◽  
Sequencing Data ◽  
Drinking Milk

An outbreak of Shiga toxin-producing Escherichia coli (STEC) O157:H7 occurred on the Isle of Wight between August and October 2017. Of the seven cases linked to the outbreak, five were identified through the statutory notification process and two were identified through national surveillance of whole genome sequencing data. Enhanced surveillance questionnaires established a common link to a farm, and link to the likely food vehicle, raw drinking milk (RDM). Microbiological investigations, including PCR, identified the presence of STEC O157:H7 in samples of RDM. Analysis of core genome single nucleotide polymorphism (SNP) data of STEC O157:H7 from human stool specimens, animal faecal samples and RDM demonstrated a one SNP difference between isolates, and therefore close genetic relatedness. Control measures that were put in place included suspension of sales and recall of RDM, as well as restrictions on public access to parts of the farm. Successful integration of traditional epidemiological surveillance and advanced laboratory methods for the detection and characterisation of STEC O157:H7 from human, animal and environmental samples enabled prompt identification of the outbreak vehicle and provided evidence to support the outbreak control team’s decision-making, leading to implementation of effective control measures in a timely manner.

scholarly journals Discordant bioinformatic predictions of antimicrobial resistance from whole-genome sequencing data of bacterial isolates: An inter-laboratory study

2019 ◽  
Author(s):  
Ronan M. Doyle ◽  
Denise M. O’Sullivan ◽  
Sean D. Aller ◽  
Sebastian Bruchmann ◽  
Taane Clark ◽  
...  
Keyword(s):  
Antimicrobial Resistance ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Laboratory Study ◽  
Clinical Microbiology ◽  
Sequence Data ◽  
Clinical Samples ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data

AbstractBackgroundAntimicrobial resistance (AMR) poses a threat to public health. Clinical microbiology laboratories typically rely on culturing bacteria for antimicrobial susceptibility testing (AST). As the implementation costs and technical barriers fall, whole-genome sequencing (WGS) has emerged as a ‘one-stop’ test for epidemiological and predictive AST results. Few published comparisons exist for the myriad analytical pipelines used for predicting AMR. To address this, we performed an inter-laboratory study providing sets of participating researchers with identical short-read WGS data sequenced from clinical isolates, allowing us to assess the reproducibility of the bioinformatic prediction of AMR between participants and identify problem cases and factors that lead to discordant results.MethodsWe produced ten WGS datasets of varying quality from cultured carbapenem-resistant organisms obtained from clinical samples sequenced on either an Illumina NextSeq or HiSeq instrument. Nine participating teams (‘participants’) were provided these sequence data without any other contextual information. Each participant used their own pipeline to determine the species, the presence of resistance-associated genes, and to predict susceptibility or resistance to amikacin, gentamicin, ciprofloxacin and cefotaxime.ResultsIndividual participants predicted different numbers of AMR-associated genes and different gene variants from the same clinical samples. The quality of the sequence data, choice of bioinformatic pipeline and interpretation of the results all contributed to discordance between participants. Although much of the inaccurate gene variant annotation did not affect genotypic resistance predictions, we observed low specificity when compared to phenotypic AST results but this improved in samples with higher read depths. Had the results been used to predict AST and guide treatment a different antibiotic would have been recommended for each isolate by at least one participant.ConclusionsWe found that participants produced discordant predictions from identical WGS data. These challenges, at the final analytical stage of using WGS to predict AMR, suggest the need for refinements when using this technology in clinical settings. Comprehensive public resistance sequence databases and standardisation in the comparisons between genotype and resistance phenotypes will be fundamental before AST prediction using WGS can be successfully implemented in standard clinical microbiology laboratories.

scholarly journals JuLI: accurate detection of DNA fusions in clinical sequencing for precision oncology

2019 ◽  
Author(s):  
Hyun-Tae Shin ◽  
Nayoung K. D. Kim ◽  
Jae Won Yun ◽  
Boram Lee ◽  
Sungkyu Kyung ◽  
...  
Keyword(s):  
High Throughput Sequencing ◽  
False Negative ◽  
Detection Algorithm ◽  
Clinical Samples ◽  
Whole Genome Sequencing Data ◽  
Precision Oncology ◽  
Sequencing Data ◽  
Clinical Sequencing ◽  
Accurate Detection ◽  
High Depth

ABSTRACTAccurate detection of genomic fusions by high-throughput sequencing in clinical samples with inadequate tumor purity and formalin-fixed paraffin embedded (FFPE) tissue is an essential task in precise oncology. We developed the fusion detection algorithm Junction Location Identifier (JuLI) for optimization of high-depth clinical sequencing. We implemented novel filtering steps to minimize false positives and a joint calling function to increase sensitivity in clinical setting. We comprehensively validated the algorithm using high-depth sequencing data from cancer cell lines and clinical samples and whole genome sequencing data from NA12878. We showed that JuLI outperformed state-of-the-art fusion callers in cases with high-depth clinical sequencing and rescued a driver fusion from false negative in plasma cell-free DNA. JuLI is freely available via GitHub (https://github.com/sgilab/JuLI).

scholarly journals regentrans: a framework and R package for using genomics to study regional pathogen transmission

2021 ◽  
Author(s):  
Sophie Hoffman ◽  
Zena Lapp ◽  
Joyce Wang ◽  
Evan Snitkin
Keyword(s):  
R Package ◽  
Multidrug Resistant ◽  
Pathogen Transmission ◽  
Regional Level ◽  
Whole Genome Sequencing Data ◽  
Sequencing Data ◽  
Transmission Networks ◽  
Carbapenem Resistant ◽  
One Year

Increasing evidence of regional pathogen transmission networks highlights the importance of investigating the dissemination of multidrug-resistant organisms (MDROs) across a region to identify where transmission is happening and how pathogens move across regions. We developed a framework for investigating MDRO regional transmission dynamics using whole-genome sequencing data and created regentrans, an easy-to-use, open source R package that implements these methods (https://github.com/Snitkin-Lab-Umich/regentrans). Using a dataset of over 400 carbapenem-resistant Klebsiella pneumoniae isolates collected from patients in 21 long-term acute care hospitals (LTACHs) over a one-year period, we demonstrate how to use our framework to gain insights into differences in inter- and intra-facility transmission across different LTACHs and over time. These tools will allow investigators to better understand the origins and transmission patterns of MDROs, which is the first step in understanding how to stop transmission at the regional level.

scholarly journals Strategy to Develop and Evaluate a Multiplex RT-ddPCR in Response to SARS-CoV-2 Genomic Evolution

2021 ◽  
Vol 43 (3) ◽  
pp. 1937-1949
Author(s):  
Laura A. E. Van Poelvoorde ◽  
Mathieu Gand ◽  
Marie-Alice Fraiture ◽  
Sigrid C. J. De Keersmaecker ◽  
Bavo Verhaegen ◽  
...  
Keyword(s):  
In Silico ◽  
Virus Evolution ◽  
Clinical Samples ◽  
Whole Genome Sequencing Data ◽  
Preliminary Evaluation ◽  
Whole Genome ◽  
Sequencing Data ◽  
Method Performance ◽  
The World ◽  
Pcr Assays

The worldwide emergence and spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) since 2019 has highlighted the importance of rapid and reliable diagnostic testing to prevent and control the viral transmission. However, inaccurate results may occur due to false negatives (FN) caused by polymorphisms or point mutations related to the virus evolution and compromise the accuracy of the diagnostic tests. Therefore, PCR-based SARS-CoV-2 diagnostics should be evaluated and evolve together with the rapidly increasing number of new variants appearing around the world. However, even by using a large collection of samples, laboratories are not able to test a representative collection of samples that deals with the same level of diversity that is continuously evolving worldwide. In the present study, we proposed a methodology based on an in silico and in vitro analysis. First, we used all information offered by available whole-genome sequencing data for SARS-CoV-2 for the selection of the two PCR assays targeting two different regions in the genome, and to monitor the possible impact of virus evolution on the specificity of the primers and probes of the PCR assays during and after the development of the assays. Besides this first essential in silico evaluation, a minimal set of testing was proposed to generate experimental evidence on the method performance, such as specificity, sensitivity and applicability. Therefore, a duplex reverse-transcription droplet digital PCR (RT-ddPCR) method was evaluated in silico by using 154 489 whole-genome sequences of SARS-CoV-2 strains that were representative for the circulating strains around the world. The RT-ddPCR platform was selected as it presented several advantages to detect and quantify SARS-CoV-2 RNA in clinical samples and wastewater. Next, the assays were successfully experimentally evaluated for their sensitivity and specificity. A preliminary evaluation of the applicability of the developed method was performed using both clinical and wastewater samples.

scholarly journals Origins of the current outbreak of multidrug resistant malaria in Southeast Asia: a retrospective genetic study

2017 ◽  
Author(s):  
Roberto Amato ◽  
Richard D. Pearson ◽  
Jacob Almagro-Garcia ◽  
Chanaki Amaratunga ◽  
Pharath Lim ◽  
...  
Keyword(s):  
Southeast Asia ◽  
International Development ◽  
Sequence Data ◽  
Artemisinin Resistance ◽  
Multidrug Resistant ◽  
Resistance Locus ◽  
First Line ◽  
Genetic Changes ◽  
Current Outbreak ◽  
Gates Foundation

AbstractBackgroundAntimalarial failure is rapidly spreading across parts of Southeast Asia where dihydroartemisinin-piperaquine (DHA-PPQ) is used as first line treatment. The first published reports came from western Cambodia in 2013. Here we analyse genetic changes in the Plasmodium falciparum population of western Cambodia in the six years prior to that.MethodsWe analysed genome sequence data on 1492 P. falciparum samples from Southeast Asia, including 464 collected in western Cambodia between 2007 and 2013. Different epidemiological origins of resistance were identified by haplotypic analysis of the kelch13 artemisinin resistance locus and the plasmepsin 2-3 piperaquine resistance locus.FindingsWe identified over 30 independent origins of artemisinin resistance, of which the KEL1 lineage accounted for 91% of DHA-PPQ-resistant parasites. In 2008, KEL1 combined with PLA1, the major lineage associated with piperaquine resistance. By 2012, the KEL1/PLA1 co-lineage had reached over 60% frequency in western Cambodia and had spread to northern Cambodia.InterpretationThe KEL1/PLA1 co-lineage emerged in the same year that DHA-PPQ became the first line antimalarial drug in western Cambodia and spread aggressively thereafter, displacing other artemisinin-resistant parasite lineages. These findings have significant implications for management of the global health risk associated with the current outbreak.FundingWellcome Trust, Bill & Melinda Gates Foundation, Medical Research Council, UK Department for International Development, and Intramural Research Program of the US National Institute of Allergy and Infectious Diseases, National Institutes of Health.

scholarly journals Molecular characterization of multidrug resistant Enterobacterales strains isolated from liver and kidney transplant recipients in Spain

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Marta Fernández-Martínez ◽  
Claudia González-Rico ◽  
Mónica Gozalo-Margüello ◽  
Francesc Marco ◽  
Irene Gracia-Ahufinger ◽  
...  
Keyword(s):  
Genetic Relatedness ◽  
Solid Organ Transplantation ◽  
Multidrug Resistant ◽  
Clinical Samples ◽  
Solid Organ ◽  
Transplant Recipients ◽  
Post Transplantation ◽  
Extended Spectrum ◽  
Number Of Patients ◽  
Rectal Swabs

AbstractThe objective of this study was to analyse the mechanisms of resistance to carbapenems and other extended-spectrum-β-lactams and to determine the genetic relatedness of multidrug-resistant Enterobacterales (MDR-E) causing colonization or infection in solid-organ transplantation (SOT) recipients. Prospective cohort study in kidney (n = 142), liver (n = 98) or kidney/pancreas (n = 7) transplant recipients between 2014 and 2018 in seven Spanish hospitals. We included 531 MDR-E isolates from rectal swabs obtained before transplantation and weekly for 4–6 weeks after the procedure and 10 MDR-E from clinical samples related to an infection. Overall, 46.2% Escherichia coli, 35.3% Klebsiella pneumoniae, 6.5% Enterobacter cloacae, 6.3% Citrobacter freundii and 5.7% other species were isolated. The number of patients with MDR-E colonization post-transplantation (176; 71.3%) was 2.5-fold the number of patients colonized pre-transplantation (71; 28.7%). Extended-spectrum β-lactamases (ESBLs) and carbapenemases were detected in 78.0% and 21.1% of MDR-E isolates respectively. In nine of the 247 (3.6%) transplant patients, the microorganism causing an infection was the same strain previously cultured from surveillance rectal swabs. In our study we have observed a low rate of MDR-E infection in colonized patients 4–6 weeks post-transplantation. E. coli producing blaCTX-M-G1 and K. pneumoniae harbouring blaOXA-48 alone or with blaCTX-M-G1 were the most prevalent MDR-E colonization strains in SOT recipients.

scholarly journals Identifying differentially methylated sites in samples with varying tumor purity

2018 ◽  
Author(s):  
Antti Häkkinen ◽  
Amjad Alkodsi ◽  
Chiara Facciotto ◽  
Kaiyang Zhang ◽  
Katja Kaipio ◽  
...  
Keyword(s):  
Normal Cell ◽  
Computational Method ◽  
Clinical Samples ◽  
Whole Genome Sequencing Data ◽  
Sequencing Data ◽  
Cell Control ◽  
Tumor Purity ◽  
Wide Range ◽  
Cancer Types ◽  
Control Samples

AbstractDNA methylation aberrations are common in many cancer types. A major challenge hindering comparison of patient-derived samples is that they comprise of heterogeneous collection of cancer and microenvironment cells. We present a computational method that allows comparing cancer methylomes in two or more heterogeneous tumor samples featuring differing, unknown fraction of cancer cells. The method is unique in that it allows comparison also in the absence of normal cell control samples and without prior tumor purity estimates, as these are often unavailable or unreliable in clinical samples. We use simulations and next-generation methylome, RNA, and whole-genome sequencing data from two cancer types to demonstrate that the method is accurate and outperforms alternatives. The results show that our method adapts well to various cancer types and to a wide range of tumor content, and works robustly without a control or with controls derived from various sources. The method is freely available at https://bitbucket.org/anthakki/dmml.

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