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Hoa, N. T.

Publications and source records attributed to Hoa, N. T..

7 recordsLinked to original sources

Mapping the evolutionary path towards multi-drug resistance in the pandemic Escherichia coli ST131 lineage

Escherichia coli sequence type (ST) 131 is the most widely studied genetic lineage of the species to date, originally identified in the early 2000s as an increasingly common cause of human urinary tract and bloodstream infections worldwide. This lineage is subdivided into four extant main subclades A, B, C1 and C2 that exhibit distinct features in terms of invasiveness, antibiotic resistance and transmissibility. However, the evolutionary pathway from the generally susceptible ST131-B to the drug-resistant ST131-C clades remains poorly mapped. To fill this knowledge gap, we analysed in detail human clinical isolates obtained in Vietnam, designated as belonging to the generally neglected minor clade ST131-B0. We sequenced them using both short- and long-read technology, and combined these data with a recently published high-resolution genomic collection to provide further insight into the evolutionary process and its timeline. Extensive genomic analyses established ST131-B0 as an intermediary progenitor in the evolutionary path leading from ST131-B to the ST131-C clades, associated with multiple type I pili switches, as well as the loss and gain of specific chromosomal genes representing diverse core functions such as metabolism, transcription, DNA binding and type II toxin-antitoxin systems. Furthermore, all Vietnamese isolates of ST131-B0 unprecedentedly harboured blaCTX-M genes encoding extended-spectrum {beta}-lactamases, a trait dominant in ST131-C clades and not previously observed in ST131-B0. Our study supports the hypothesis that the ST131-C clades have gradually evolved from ST131-B by reducing the host range with better adaptation to colonising humans under selective conditions.

evolutionary biology↗

The emergence and diversification of a zoonotic pathogen from within the microbiota of intensively farmed pigs

The expansion and intensification of livestock production is predicted to promote the emergence of pathogens. As pathogens sometimes jump between species this can affect the health of humans as well as livestock. Here we investigate how livestock microbiota can act as a source of these emerging pathogens through analysis of Streptococcus suis, a ubiquitous component of the respiratory microbiota of pigs that is also a major cause of disease on pig farms and an important zoonotic pathogen. Combining molecular dating, phylogeography and comparative genomic analyses of a large collection of isolates, we find that several pathogenic lineages of S. suis emerged in the 19th and 20th centuries, during an early period of growth in pig farming. These lineages have since spread between countries and continents, mirroring trade in live pigs. They are distinguished by the presence of three genomic islands with putative roles in metabolism and cell adhesion, and an ongoing reduction in genome size, which may reflect their recent shift to a more pathogenic ecology. Reconstructions of the evolutionary histories of these islands reveal constraints on pathogen emergence that could inform control strategies, with pathogenic lineages consistently emerging from one subpopulation of S. suis and acquiring genes through horizontal transfer from other pathogenic lineages. These results shed light on the capacity of the microbiota to rapidly evolve to exploit changes in their host population and suggest that the impact of changes in farming on the pathogenicity and zoonotic potential of S. suis is yet to be fully realised.

evolutionary biology↗

Impact of pathogen genetics on clinical phenotypes in a population of Talaromyces marneffei from Vietnam

Talaromycosis, a severe and invasive fungal infection caused by Talaromyces marneffei, is difficult to treat and impacts those living in endemic regions of southeast Asia, India, and China. While 30% of infections result in mortality, our understanding of the genetic basis of pathogenesis for this fungus is limited. To address this, we apply population genomics and genome wide association study approaches to a cohort of 336 T. marneffei isolates collected from patients who enrolled in the Itraconazole versus Amphotericin B for Talaromycosis (IVAP) trial in Vietnam. We find that isolates from northern and southern Vietnam form two distinct geographical clades, with isolates from southern Vietnam associated with increased disease severity. Leveraging longitudinal isolates, we identify multiple instances of disease relapse linked to unrelated strains, highlighting the potential for multi-strain infections. In more frequent cases of persistent talaromycosis caused by the same strain, we identify variants arising over the course of patient infections that impact genes predicted to function in the regulation of gene expression and secondary metabolite production. By combining genetic variant data with patient metadata for all 336 isolates, we identify pathogen variants significantly associated with multiple clinical phenotypes. In addition, we identify genes and genomic regions under selection across both clades, highlighting loci undergoing rapid evolution, potentially in response to external pressures. With this combination of approaches, we identify links between pathogen genetics and patient outcomes and identify genomic regions that are altered during T. marneffei infection, providing an initial view of how pathogen genetics affects disease outcomes.

genomics↗

Genome-wide association reveals host-specific genomic traits in Escherichia coli

Escherichia coli is an opportunistic pathogen that can colonize or infect various host species. There is a significant gap in our understanding to what extent genetic lineages of E. coli are adapted or restricted to specific hosts. In addition, genomic determinants underlying such host specificity are unknown.By analyzing a randomly sampled collection of 1198 whole-genome sequenced E. coli isolates from four countries (Germany, UK, Spain, and Vietnam), obtained from five host species (human, pig, cattle, chicken, and wild boar) over 16 years, from both healthy and diseased hosts, we demonstrate that certain lineages of E. coli are frequently detected in specific hosts. We report a novel nan gene cluster, designated nan-9, putatively encoding acetylesterases and determinants of uptake and metabolism of sialic acid, to be associated with the human host as identified through genome wide association studies. In silico characterization predicts nan-9 to be involved in sialic acid (Sia) metabolism. In vitro growth experiments with a representative {Delta}nan E. coli mutant strain, using sialic acids 5-N-acetyl neuraminic acid (Neu5Ac) and N-glycolyl neuraminic acid (Neu5Gc) as the sole carbon source, indicate an impaired growth behaviour compared to the wild-type. In addition, we identified several additional E. coli genes that are potentially associated with adaptation to human, cattle and chicken hosts, but not for the pig host. Collectively, this study provides an extensive overview of genetic determinants which may mediate host specificity in E. coli. Our findings should inform risk analysis and epidemiological monitoring of (antimicrobial resistant) E. coli.

genomics↗

Coronavirus testing indicates transmission risk increases along wildlife supply chains for human consumption in Viet Nam, 2013-2014

Outbreaks of emerging coronaviruses in the past two decades and the current pandemic of a novel coronavirus (SARS-CoV-2) that emerged in China highlight the importance of this viral family as a zoonotic public health threat. To gain a better understanding of coronavirus presence and diversity in wildlife at wildlife-human interfaces in three southern provinces in Viet Nam 2013-2014, we used consensus Polymerase Chain Reactions to detect coronavirus sequences. In comparison to previous studies, we observed high proportions of positive samples among field rats (34.0%, 239/702) destined for human consumption and insectivorous bats in guano farms (74.8%, 234/313) adjacent to human dwellings. Most notably among field rats, the odds of coronavirus RNA detection significantly increased along the supply chain from field rats sold by traders (reference group; 20.7% positivity, 39/188) by a factor of 2.2 for field rats sold in large markets (32.0%, 116/363) and 10.0 for field rats sold and served in restaurants (55.6%, 84/151). Coronaviruses were detected in the majority of wildlife farms (60.7%, 17/28) and in the Malayan porcupines (6.0%, 20/331) and bamboo rats (6.3%, 6/96) that are farmed. We identified six known coronaviruses in bats and rodents, clustered in three Coronaviridae genera, including the Alpha-, Beta-, and Gammacoronaviruses. Our analysis also suggested either mixing of animal excreta in the environment or interspecies transmission of coronaviruses, as both bat and avian coronaviruses were detected in rodent feces in the trade. The mixing of multiple coronaviruses, and their apparent amplification along the wildlife supply chain into restaurants, suggests maximal risk for end consumers and likely underpins the mechanisms of zoonotic spillover to people.

microbiology↗

Linking phenotype, genotype and ecology: antimicrobial resistance in the zoonotic pathogen Streptococcus suis

Antimicrobial resistance (AMR) is among the gravest threats to human health and food security worldwide. Pigs receive more antimicrobials than most other livestock, and are a known source of zoonotic disease. We studied AMR in Streptococcus suis, a commensal found in most pigs, but which can also cause serious disease in both pigs and humans. We obtained replicated measures of Minimum Inhibitory Concentration (MIC) for 16 antibiotics, across a panel of 678 isolates, from the major pig-producing regions of the world. For several drugs, there was no natural separation into "resistant" and "susceptible", highlighting the need to treat MIC as a quantitative trait. We found differences in MICs between countries, consistent with their patterns of antimicrobial usage. AMR levels were high even for drugs not used to treat S. suis, with many multi-drug resistant isolates. And similar levels of resistance were found in pigs and humans from zoonotic regions. We next used whole genome sequences for each isolate to identify 43 candidate resistance determinants, 22 of which were novel in S. suis. The presence of these determinants explained most of the variation in MIC. But there were also complications, including epistatic interactions, where known resistance alleles had no effect in some genetic backgrounds. Beta-lactam resistance involved many variants of small effect, appearing in a characteristic order. Our results confirm the potential for genomic data to aid in the fight against AMR, but also demonstrate that it cannot be tackled one species or one drug at a time.

microbiology↗

Diagnostic Cerebrospinal Fluid Biomarker Discovery and Validation in Patients with Central Nervous System Infections

BackgroundCentral nervous system (CNS) infections are common causes of morbidity and mortality worldwide. Rapid, accurate identification of the likely cause is essential for clinical management and the early initiation of antimicrobial therapy, which potentially improves clinical outcome. MethodsWe applied liquid chromatography tandem mass-spectrometry on 45 cerebrospinal fluid (CSF) samples from a cohort of adults with/without CNS infections to discover potential diagnostic protein biomarkers. We then validated the diagnostic performance of a selected biomarker candidate in an independent cohort of 364 consecutively treated adults with CNS infections admitted to a referral hospital in southern Vietnam. ResultsIn the discovery cohort, we identified lipocalin 2 (LCN2) as a potential biomarker of bacterial meningitis. The analysis of the validation cohort showed that LCN2 could discriminate bacterial meningitis from other CNS infections, including tuberculous meningitis, cryptococcal meningitis and viral/antibody-mediated encephalitis (sensitivity: 0.88 (95% confident interval (CI): 0.77-0.94), specificity: 0.91 (95%CI: 0.88-0.94) and diagnostic odd ratio: 73.8 (95%CI: 31.8-171.4)). LCN2 outperformed other CSF markers (leukocytes, glucose, protein and lactate) commonly used in routine care worldwide. The combination of LCN2 and these four routine CSF markers resulted in the highest diagnostic performance for bacterial meningitis (area under receiver-operating-characteristic-curve 0.96; 95%CI: 0.93-0.99). ConclusionsOur results suggest that LCN2 is a sensitive and specific biomarker for discriminating bacterial meningitis from a broad spectrum of CNS infections. A prospective study is needed to further assess the diagnostic utility of LCN2 in the diagnosis and management of CNS infections.

microbiology↗