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Extended-spectrum β-lactamase (ESBL)-producing Enterobacteriaceae are a major global public health concern. Presently, Escherichia coli with CTX-Ms are the most common species associated with global ESBLs; CTX-M-15 is the most frequent CTX-M worldwide and is followed by CTX-M-14, which is often found in South-East Asia. Recent surveillance studies showed that CTX-M-27 is emerging in certain parts of the world especially in Japan and Europe. The population structure of ESBL-producing E. coli is dominated globally by an high-risk clone named ST131. Escherichia coli ST131 belongs to three clades (A, B, and C) and three different subclades (C1, C1-M27, and C2). Clade C1-M27 is associated with bla CTX-M-27 , and C2 with bla CTX-M-15 . Recent whole genome sequencing studies have shown that clade C has evolved from clade B in a stepwise fashion, resulting in one of the most influential global antimicrobial resistance clones that has emerged during the 2000’s. Other important E. coli clones that have been detected among ESBL producers include ST405, ST38, ST648, ST410, and ST1193. The INCREMENT project has shown that ertapenem is as effective as other carbapenems for treating serious infections due to ESBL-producing Enterobacteriaceae. The results of the MERINO open-label randomized controlled study has provided clear evidence that piperacillin-tazobactam should be avoided for targeted therapy of blood-stream infections due to ESBL-producing E. coli and K. pneumoniae, regardless of the patient population, source of infection, bacterial species, and susceptibility result of piperacillin-tazobactam. Research is still warranted to define the optimal therapy of less severe infections due to ESBL-producing Enterobactericeae.

In the current era, with increasing availability of results from genetic association studies, finding genetic instruments for inferring causality in observational epidemiology has become apparently simple. Mendelian randomisation (MR) analyses are hence growing in popularity and, in particular, methods that can incorporate multiple instruments are being rapidly developed for these applications. Such analyses have enormous potential, but they all rely on strong, different, and inherently untestable assumptions. These have to be clearly stated and carefully justified for every application in order to avoid conclusions that cannot be replicated. In this article, we review the instrumental variable assumptions and discuss the popular linear additive structural model. We advocate the use of tests for the null hypothesis of ‘no causal effect’ and calculation of the bounds for a causal effect, whenever possible, as these do not rely on parametric modelling assumptions. We clarify the difference between a randomised trial and an MR study and we comment on the importance of validating instruments, especially when considering them for joint use in an analysis. We urge researchers to stand by their convictions, if satisfied that the relevant assumptions hold, and to interpret their results causally since that is the only reason for performing an MR analysis in the first place.

Whole genome sequencing (WGS) of Mycobacterium tuberculosis has rapidly progressed from a research tool to a clinical application for the diagnosis and management of tuberculosis and in public health surveillance. This development has been facilitated by drastic drops in cost, advances in technology and concerted efforts to translate sequencing data into actionable information. There is, however, a risk that, in the absence of a consensus and international standards, the widespread use of WGS technology may result in data and processes that lack harmonization, comparability and validation. In this Review, we outline the current landscape of WGS pipelines and applications, and set out best practices for M.tuberculosis WGS, including standards for bioinformatics pipelines, curated repositories of resistance-causing variants, phylogenetic analyses, quality control and standardized reporting.

Klebsiella pneumoniae is a leading cause of antimicrobial-resistant (AMR) healthcare-associated infections, neonatal sepsis and community-acquired liver abscess, and is associated with chronic intestinal diseases. Its diversity and complex population structure pose challenges for analysis and interpretation of K. pneumoniae genome data. Here we introduce Kleborate, a tool for analysing genomes of K. pneumoniae and its associated species complex, which consolidates interrogation of key features of proven clinical importance. Kleborate provides a framework to support genomic surveillance and epidemiology in research, clinical and public health settings. To demonstrate its utility we apply Kleborate to analyse publicly available Klebsiella genomes, including clinical isolates from a pan-European study of carbapenemase-producing Klebsiella , highlighting global trends in AMR and virulence as examples of what could be achieved by applying this genomic framework within more systematic genomic surveillance efforts. We also demonstrate the application of Kleborate to detect and type K. pneumoniae from gut metagenomes. Klebsiella pneumoniae is a pathogen of increasing public health concern and antimicrobial resistance is becoming more prevalent. Here, the authors describe a K. pneumoniae genotyping tool, Kleborate, that can be used to identify lineages and detect antimicrobial resistance and virulence loci.

Evidence suggests that the PfKelch13 mutations that confer artemisinin resistance in falciparum malaria have multiple independent origins across the Greater Mekong subregion, which has motivated a regional malaria elimination agenda. We aimed to use molecular genotyping to assess antimalarial drug resistance selection and spread in the Greater Mekong subregion. In this observational study, we tested Plasmodium falciparum isolates from Myanmar, northeastern Thailand, southern Laos, and western Cambodia for PfKelch13 mutations and for Pfplasmepsin2 gene amplification (indicating piperaquine resistance). We collected blood spots from patients with microscopy or rapid test confirmed uncomplicated falciparum malaria. We used microsatellite genotyping to assess genetic relatedness. As part of studies on the epidemiology of artemisinin-resistant malaria between Jan 1, 2008, and Dec 31, 2015, we collected 434 isolates. In 2014–15, a single long PfKelch13 C580Y haplotype (−50 to +31·5 kb) lineage, which emerged in western Cambodia in 2008, was detected in 65 of 88 isolates from northeastern Thailand, 86 of 111 isolates from southern Laos, and 14 of 14 isolates from western Cambodia, signifying a hard transnational selective sweep. Pfplasmepsin2 amplification occurred only within this lineage, and by 2015 these closely related parasites were found in ten of the 14 isolates from Cambodia and 15 of 15 isolates from northeastern Thailand. C580Y mutated parasites from Myanmar had a different genetic origin. Our results suggest that the dominant artemisinin-resistant P falciparum C580Y lineage probably arose in western Cambodia and then spread to Thailand and Laos, outcompeting other parasites and acquiring piperaquine resistance. The emergence and spread of fit artemisinin-resistant P falciparum parasite lineages, which then acquire partner drug resistance across the Greater Mekong subregion, threatens regional malaria control and elimination goals. Elimination of falciparum malaria from this region should be accelerated while available antimalarial drugs still remain effective. The Wellcome Trust and the Bill and Melinda Gates Foundation.

The current coronavirus disease 2019 (COVID-19) pandemic is the first to apply whole-genome sequencing near to real time, with over 2 million severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) whole-genome sequences generated and shared through the GISAID platform. This genomic resource informed public health decision-making throughout the pandemic; it also allowed detection of mutations that might affect virulence, pathogenesis, host range or immune escape as well as the effectiveness of SARS-CoV-2 diagnostics and therapeutics. However, genotype-to-phenotype predictions cannot be performed at the rapid pace of genomic sequencing. To prepare for the next phase of the pandemic, a systematic approach is needed to link global genomic surveillance and timely assessment of the phenotypic characteristics of novel variants, which will support the development and updating of diagnostics, vaccines, therapeutics and nonpharmaceutical interventions. This Review summarizes the current knowledge on key viral mutations and variants and looks to the next phase of surveillance of the evolving pandemic.

This multiplex PCR enrichment protocol enables sequencing of Zika and other viral genomes of low abundance from clinical samples using the Illumina platform, or the portable MinION sequencer, facilitating direct application in field situations. Genome sequencing has become a powerful tool for studying emerging infectious diseases; however, genome sequencing directly from clinical samples (i.e., without isolation and culture) remains challenging for viruses such as Zika, for which metagenomic sequencing methods may generate insufficient numbers of viral reads. Here we present a protocol for generating coding-sequence-complete genomes, comprising an online primer design tool, a novel multiplex PCR enrichment protocol, optimized library preparation methods for the portable MinION sequencer (Oxford Nanopore Technologies) and the Illumina range of instruments, and a bioinformatics pipeline for generating consensus sequences. The MinION protocol does not require an Internet connection for analysis, making it suitable for field applications with limited connectivity. Our method relies on multiplex PCR for targeted enrichment of viral genomes from samples containing as few as 50 genome copies per reaction. Viral consensus sequences can be achieved in 1–2 d by starting with clinical samples and following a simple laboratory workflow. This method has been successfully used by several groups studying Zika virus evolution and is facilitating an understanding of the spread of the virus in the Americas. The protocol can be used to sequence other viral genomes using the online Primal Scheme primer designer software. It is suitable for sequencing either RNA or DNA viruses in the field during outbreaks or as an inexpensive, convenient method for use in the lab.

Mendelian randomization (MR) is an epidemiological technique that uses genetic variants to distinguish correlation from causation in observational data. The reliability of a MR investigation depends on the validity of the genetic variants as instrumental variables (IVs). We develop the contamination mixture method, a method for MR with two modalities. First, it identifies groups of genetic variants with similar causal estimates, which may represent distinct mechanisms by which the risk factor influences the outcome. Second, it performs MR robustly and efficiently in the presence of invalid IVs. Compared to other robust methods, it has the lowest mean squared error across a range of realistic scenarios. The method identifies 11 variants associated with increased high-density lipoprotein-cholesterol, decreased triglyceride levels, and decreased coronary heart disease risk that have the same directions of associations with various blood cell traits, suggesting a shared mechanism linking lipids and coronary heart disease risk mediated via platelet aggregation. Mendelian randomization (MR) is a method for inferring causal relationships between risk factors and outcomes via associated genetic variants. Here, Burgess et al. develop the contamination mixture method which yields robust MR results in the presence of invalid instrumental variables and groups variants by their effect estimates.

The rapid emergence of coronavirus disease 2019 (COVID-19) as a global pandemic affecting millions of individuals globally has necessitated sensitive and high-throughput approaches for the diagnosis, surveillance, and determining the genetic epidemiology of SARS-CoV-2. In the present study, we used the COVIDSeq protocol, which involves multiplex-PCR, barcoding, and sequencing of samples for high-throughput detection and deciphering the genetic epidemiology of SARS-CoV-2. We used the approach on 752 clinical samples in duplicates, amounting to a total of 1536 samples which could be sequenced on a single S4 sequencing flow cell on NovaSeq 6000. Our analysis suggests a high concordance between technical duplicates and a high concordance of detection of SARS-CoV-2 between the COVIDSeq as well as RT-PCR approaches. An in-depth analysis revealed a total of six samples in which COVIDSeq detected SARS-CoV-2 in high confidence which were negative in RT-PCR. Additionally, the assay could detect SARS-CoV-2 in 21 samples and 16 samples which were classified inconclusive and pan-sarbeco positive respectively suggesting that COVIDSeq could be used as a confirmatory test. The sequencing approach also enabled insights into the evolution and genetic epidemiology of the SARS-CoV-2 samples. The samples were classified into a total of 3 clades. This study reports two lineages B.1.112 and B.1.99 for the first time in India. This study also revealed 1,143 unique single nucleotide variants and added a total of 73 novel variants identified for the first time. To the best of our knowledge, this is the first report of the COVIDSeq approach for detection and genetic epidemiology of SARS-CoV-2. Our analysis suggests that COVIDSeq could be a potential high sensitivity assay for the detection of SARS-CoV-2, with an additional advantage of enabling the genetic epidemiology of SARS-CoV-2.

The first bacterial genome sequence was published 20 years ago. In this Timeline, Loman and Pallen review the first two decades of bacterial genome sequencing, discussing how advances in sequencing technologies and bioinformatics have furthered our understanding of the biology, diversity and evolution of bacteria. Twenty years ago, the publication of the first bacterial genome sequence, from Haemophilus influenzae , shook the world of bacteriology. In this Timeline, we review the first two decades of bacterial genome sequencing, which have been marked by three revolutions: whole-genome shotgun sequencing, high-throughput sequencing and single-molecule long-read sequencing. We summarize the social history of sequencing and its impact on our understanding of the biology, diversity and evolution of bacteria, while also highlighting spin-offs and translational impact in the clinic. We look forward to a 'sequencing singularity', where sequencing becomes the method of choice for as-yet unthinkable applications in bacteriology and beyond.