Publications by authors named "Claire Chewapreecha"

Purpose Of Review: Bacterial infections and antibiotic resistance contribute to global mortality. Despite many infections being preventable and treatable, the lack of reliable and accessible diagnostic tools exacerbates these issues. CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats)-based diagnostics has emerged as a promising solution.

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Article Synopsis
  • Melioidosis is a severe tropical disease linked to the bacterium Burkholderia pseudomallei, which uses host cell mechanisms for mobility.
  • The study examined genetic variations of BimA and BimC in B. pseudomallei by analyzing 1,294 clinical isolates from northeast Thailand between 2015 and 2018.
  • Results showed conserved 3D structures of BimA and BimC variants across strains and confirmed their ability to form plaques and develop actin tails in host cells, providing insights into their role in bacterial virulence.
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Melioidosis is an often-fatal neglected tropical disease caused by an environmental bacterium Burkholderia pseudomallei. However, our understanding of the disease-causing bacterial lineages, their dissemination, and adaptive mechanisms remains limited. To address this, we conduct a comprehensive genomic analysis of 1,391 B.

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In September 2021, a total of 25 patients diagnosed with COVID-19 developed acute melioidosis after (median 7 days) admission to a COVID-19 field hospital in Thailand. Eight nonpotable tap water samples and 6 soil samples were culture-positive for Burkholderia pseudomallei. Genomic analysis suggested contaminated tap water as the likely cause of illness.

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Background: Melioidosis is a neglected but often fatal tropical disease. The disease has broad clinical manifestations, which makes diagnosis challenging and time consuming. To improve diagnosis, we aimed to evaluate the performance of the CRISPR-Cas12a system (CRISPR-BP34) to detect Burkholderia pseudomallei DNA across clinical specimens from patients suspected to have melioidosis.

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Melioidosis is an often-fatal neglected tropical disease caused by an environmental bacterium . However, our understanding of the disease-causing bacterial lineages, their dissemination, and adaptive mechanisms remains limited. To address this, we conducted a comprehensive genomic analysis of 1,391 isolates collected from nine hospitals in northeast Thailand between 2015 and 2018, and contemporaneous isolates from neighbouring countries, representing the most densely sampled collection to date.

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Background: Melioidosis is a frequently fatal disease caused by an environmental bacterium . The disease is prevalent in northeast Thailand, particularly among rice field farmers who are at risk of bacterial exposure through contact with contaminated soil and water. However, not all exposure results in disease, and infection can manifest diverse outcomes.

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The bacterium is the causative agent of melioidosis, a severe tropical disease associated with high mortality and relapse and persistent infections. Treatment of melioidosis requires prolonged antibiotic therapy; however, little is known about relapse and persistent infections, particularly the phenotypic and genetic alterations of in patients. In this study, we performed pulsed-field gel electrophoresis (PFGE) to compare the bacterial genotype between the initial isolate and the subsequent isolate from each of 23 suspected recurrent and persistent melioidosis patients in Northeast Thailand.

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Point-of-care (POC) nucleic acid detection technologies are poised to aid gold-standard technologies in controlling the COVID-19 pandemic, yet shortcomings in the capability to perform critically needed complex detection-such as multiplexed detection for viral variant surveillance-may limit their widespread adoption. Herein, we developed a robust multiplexed clustered regularly interspaced short palindromic repeats (CRISPR)-based detection using LwaCas13a and PsmCas13b to simultaneously diagnose severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and pinpoint the causative SARS-CoV-2 variant of concern (VOC)-including globally dominant VOCs Delta (B.1.

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Article Synopsis
  • Scientists studied the genetic differences of a bacteria called Streptococcus pneumoniae in babies and their moms to learn how it spreads and changes.
  • They used a super advanced method called deep sequencing to find more cases of the bacteria than previous tests could.
  • The study found that babies are more likely to get and keep a tough, resistant version of the bacteria after taking medicine, revealing important details about how these germs behave in the body.
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Detection of Burkholderia pseudomallei, a causative bacterium for melioidosis, remains a challenging undertaking due to long assay time, laboratory requirements, and the lack of specificity and sensitivity of many current assays. In this study, we are presenting a novel method that circumvents those issues by utilizing CRISPR-Cas12a coupled with isothermal amplification to identify B. pseudomallei DNA from clinical isolates.

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The soil bacterium Burkholderia pseudomallei is the causative agent of melioidosis and a significant cause of human morbidity and mortality in many tropical and subtropical countries. The species notoriously survives harsh environmental conditions but the genetic architecture for these adaptations remains unclear. Here we employed a powerful combination of genome-wide epistasis and co-selection studies (2,011 genomes), condition-wide transcriptome analyses (82 diverse conditions), and a gene knockout assay to uncover signals of "co-selection"-that is a combination of genetic markers that have been repeatedly selected together through B.

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Melioidosis is an often fatal infection in tropical regions caused by an environmental bacterium, Current recommended melioidosis treatment requires intravenous β-lactam antibiotics such as ceftazidime (CAZ), meropenem (MEM) or amoxicillin-clavulanic acid (AMC) and oral trimethoprim-sulfamethoxazole. Emerging antibiotic resistance could lead to therapy failure and high mortality. We performed a prospective multicentre study in northeast Thailand during 2015-2018 to evaluate antibiotic susceptibility and characterize β-lactam resistance in clinical isolates.

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A better understanding of co-evolution between pathogens and hosts holds promise for better prevention and control strategies. This review will explore the interactions between , an environmental and opportunistic pathogen, and the human host immune system. causes "Melioidosis," a rapidly fatal tropical infectious disease predicted to affect 165,000 cases annually worldwide, of which 89,000 are fatal.

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The extent to which evolution is constrained by the rate at which horizontal gene transfer (HGT) allows DNA to move between genetic lineages is an open question, which we address in the context of antibiotic resistance in . We analyze microbiological, genomic, and epidemiological data from the largest-to-date sequenced pneumococcal carriage study in 955 infants from a refugee camp on the Thailand-Myanmar border. Using a unified framework, we simultaneously test prior hypotheses on rates of HGT and a key evolutionary covariate (duration of carriage) as determinants of resistance frequencies.

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The environmental bacterium causes melioidosis, an important endemic human disease in tropical and sub-tropical countries. This bacterium occupies broad ecological niches including soil, contaminated water, single-cell microbes, plants and infection in a range of animal species. Here, we performed genome-wide association studies for genetic determinants of environmental and human adaptation using a combined dataset of 1,010 whole genome sequences of from Northeast Thailand and Australia, representing two major disease hotspots.

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Covariance-based discovery of polymorphisms under co-selective pressure or epistasis has received considerable recent attention in population genomics. Both statistical modeling of the population level covariation of alleles across the chromosome and model-free testing of dependencies between pairs of polymorphisms have been shown to successfully uncover patterns of selection in bacterial populations. Here we introduce a model-free method, SpydrPick, whose computational efficiency enables analysis at the scale of pan-genomes of many bacteria.

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A recent modelling study estimated that there are 2800 deaths due to melioidosis in Thailand yearly. The Thailand Melioidosis Network (formed in 2012) has been working closely with the Ministry of Public Health (MoPH) to investigate and reduce the burden of this disease. Based on updated data, the incidence of melioidosis is still high in Northeast Thailand.

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Diversity of the polysaccharide capsule in Streptococcus pneumoniae-main surface antigen and the target of the currently used pneumococcal vaccines-constitutes a major obstacle in eliminating pneumococcal disease. Such diversity is genetically encoded by almost 100 variants of the capsule biosynthesis locus, cps. However, the evolutionary dynamics of the capsule remains not fully understood.

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Recent advances in the scale and diversity of population genomic datasets for bacteria now provide the potential for genome-wide patterns of co-evolution to be studied at the resolution of individual bases. Here we describe a new statistical method, genomeDCA, which uses recent advances in computational structural biology to identify the polymorphic loci under the strongest co-evolutionary pressures. We apply genomeDCA to two large population data sets representing the major human pathogens Streptococcus pneumoniae (pneumococcus) and Streptococcus pyogenes (group A Streptococcus).

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The environmental bacterium Burkholderia pseudomallei causes an estimated 165,000 cases of human melioidosis per year worldwide and is also classified as a biothreat agent. We used whole genome sequences of 469 B. pseudomallei isolates from 30 countries collected over 79 years to explore its geographic transmission.

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Bacterial genomes vary extensively in terms of both gene content and gene sequence. This plasticity hampers the use of traditional SNP-based methods for identifying all genetic associations with phenotypic variation. Here we introduce a computationally scalable and widely applicable statistical method (SEER) for the identification of sequence elements that are significantly enriched in a phenotype of interest.

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