scholarly journals Whole Genome Sequencing of A(H3N2) Influenza Viruses Reveals Variants Associated with Severity during the 2016–2017 Season

Viruses ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 108 ◽  
Author(s):  
Bruno Simon ◽  
Maxime Pichon ◽  
Martine Valette ◽  
Gwendolyne Burfin ◽  
Mathilde Richard ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Influenza Viruses ◽  
Influenza Surveillance ◽  
Whole Genome ◽  
University Hospitals ◽  
Surveillance Network ◽  
Genetic Traits ◽  
H3n2 Influenza ◽  
The Impact

Influenza viruses cause a remarkable disease burden and significant morbidity and mortality worldwide, and these impacts vary between seasons. To understand the mechanisms associated with these differences, a comprehensive approach is needed to characterize the impact of influenza genomic traits on the burden of disease. During 2016–2017, a year with severe A(H3N2), we sequenced 176 A(H3N2) influenza genomes using next generation sequencing (NGS) for routine surveillance of circulating influenza viruses collected via the French national influenza community-based surveillance network or from patients hospitalized in the intensive care units of the University Hospitals of Lyon, France. Taking into account confounding factors, sequencing and clinical data were used to identify genomic variants and quasispecies associated with influenza severity or vaccine failure. Several amino acid substitutions significantly associated with clinical traits were found, including NA V263I and NS1 K196E which were associated with severity and co-occurred only in viruses from the 3c.2a1 clade. Additionally, we observed that intra-host diversity as a whole and on a specific set of gene segments increased with severity. These results support the use of whole genome sequencing as a tool for the identification of genetic traits associated with severe influenza in the context of influenza surveillance.

scholarly journals The impact of real-time whole genome sequencing in controlling healthcare-associated SARS-CoV-2 outbreaks

2021 ◽  
Author(s):  
Harriet Billam ◽  
Rodric V Francis ◽  
Mitch Clarke ◽  
Carl Yates ◽  
Theocharis Tsoleridis ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Point Of Care ◽  
Patient Flow ◽  
Epidemiological Data ◽  
Control Measures ◽  
Nosocomial Transmission ◽  
Whole Genome ◽  
University Hospitals ◽  
The Impact

Background Nosocomial infections have posed a significant problem during the COVID-19 pandemic, affecting bed capacity and patient flow in hospitals. Effective infection control measures and identifying areas of highest risk is required to reduce the risk of spread to patients who are admitted with other illnesses. This is the first pandemic where whole genome sequencing (WGS) has been readily available. We demonstrate how WGS can be deployed to help identify and control outbreaks. Aims & Methods Swabs performed on patients to detect SARS-CoV-2 underwent RT-PCR on one of multiple different platforms available at Nottingham University Hospitals NHS Trust. Positive samples underwent WGS on the GridION platform using the ARTIC amplicon sequencing protocol at the University of Nottingham. Results Phylogenetic analysis from WGS and epidemiological data was used to identify an initial transmission that occurred in the admissions ward. It also showed high prevalence of asymptomatic staff infection with genetically identical viral sequences which may have contributed to the propagation of the outbreak. Actions were taken to help reduce the risk of nosocomial transmission by the introduction of rapid point of care testing in the admissions ward and introduction of portable HEPA14 filters. WGS was also used in two instances to exclude an outbreak by discerning that the phylotypes were not identical, saving time and resources. Conclusions In conjunction with accurate epidemiological data, timely WGS can identify high risk areas of nosocomial transmission, which would benefit from implementation of appropriate control measures. Conversely, WGS can disprove nosocomial transmission, validating existing control measures and maintaining clinical service, even where epidemiological data is suggestive of an outbreak.

scholarly journals Whole-genome sequencing from the New Zealand Saccharomyces cerevisiae population reveals the genomic impacts of novel microbial range expansion

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Peter Higgins ◽  
Cooper A Grace ◽  
Soon A Lee ◽  
Matthew R Goddard
Keyword(s):  
Saccharomyces Cerevisiae ◽  
New Zealand ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Range Expansion ◽  
Copy Number ◽  
Small Scale ◽  
Whole Genome ◽  
Copy Number Changes ◽  
The Impact

Abstract Saccharomyces cerevisiae is extensively utilized for commercial fermentation, and is also an important biological model; however, its ecology has only recently begun to be understood. Through the use of whole-genome sequencing, the species has been characterized into a number of distinct subpopulations, defined by geographical ranges and industrial uses. Here, the whole-genome sequences of 104 New Zealand (NZ) S. cerevisiae strains, including 52 novel genomes, are analyzed alongside 450 published sequences derived from various global locations. The impact of S. cerevisiae novel range expansion into NZ was investigated and these analyses reveal the positioning of NZ strains as a subgroup to the predominantly European/wine clade. A number of genomic differences with the European group correlate with range expansion into NZ, including 18 highly enriched single-nucleotide polymorphism (SNPs) and novel Ty1/2 insertions. While it is not possible to categorically determine if any genetic differences are due to stochastic process or the operations of natural selection, we suggest that the observation of NZ-specific copy number increases of four sugar transporter genes in the HXT family may reasonably represent an adaptation in the NZ S. cerevisiae subpopulation, and this correlates with the observations of copy number changes during adaptation in small-scale experimental evolution studies.

scholarly journals Piglet Gut and in-Barn Manure from Farms on a Raised without Antibiotics Program Display Reduced Antimicrobial Resistance but an Increased Prevalence of Pathogens

Antibiotics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1152
Author(s):  
Samuel M. Chekabab ◽  
John R. Lawrence ◽  
Alvin C. Alvarado ◽  
Bernardo Z. Predicala ◽  
Darren R. Korber
Keyword(s):  
Antimicrobial Resistance ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Whole Genome ◽  
Fecal Samples ◽  
Time Points ◽  
Conventional Farms ◽  
Production Practices ◽  
On Farm ◽  
The Impact

In response to new stringent regulations in Canada regarding the use of antibiotics in animal production, many farms have implemented practices to produce animals that are raised without antibiotics (RWA) from birth to slaughter. This study aims to assess the impact of RWA production practices on reducing the actual total on-farm use of antibiotics, the occurrence of pathogens, and the prevalence of antimicrobial resistance (AMR). A 28-month longitudinal surveillance of farms that adopted the RWA program and conventional farms using antibiotics in accordance with the new regulations (non-RWA) was conducted by collecting fecal samples from 6-week-old pigs and composite manure from the barn over six time points and applying whole-genome sequencing (WGS) to assess the prevalence of AMR genes as well as the abundance of pathogens. Analysis of in-barn drug use records confirmed the decreased consumption of antibiotics in RWA barns compared to non-RWA barns. WGS analyses revealed that RWA barns had reduced the frequency of AMR genes in piglet feces and in-barn manure. However, metagenomic analyses showed that RWA barns had a significant increase in the frequency of pathogenic Firmicutes in fecal samples and pathogenic Proteobacteria in barn manure samples.

scholarly journals Evaluation of whole genome sequencing for the identification and typing of Vibrio cholerae

2018 ◽  
Author(s):  
David R. Greig ◽  
Ulf Schafer ◽  
Sophie Octavia ◽  
Ebony Hunter ◽  
Marie A. Chattaway ◽  
...  
Keyword(s):  
Public Health ◽  
Whole Genome Sequencing ◽  
Vibrio Cholerae ◽  
Species Identification ◽  
Genome Sequencing ◽  
National Level ◽  
Whole Genome ◽  
Surveillance Programs ◽  
El Tor ◽  
The Impact

AbstractEpidemiological and microbiological data on Vibrio cholerae isolated between 2004 and 2017 (n=836) and held in the Public Health England culture archive were reviewed. The traditional biochemical species identification and serological typing results were compared with the genome derived species identification and serotype for a sub-set of isolates (n=152). Of the 836 isolates, 750 (89.7%) were from faecal specimens, 206 (24.6%) belonged to serogroup O1 and seven (0.8%) were serogroup O139, and 792 (94.7%) isolates from patients reporting recent travel abroad, most commonly to India (n=209) and Pakistan (n=104). Of the 152 isolates of V. cholerae speciated by kmer identification, 149 (98.1%) were concordant with the traditional biochemical approach. Traditional serotyping results were 100% concordant with the whole genome sequencing (WGS) analysis for identification of serogroups O1 and O139 and Classical and El Tor biotypes. ctxA was detected in all isolates of V. cholerae O1 El Tor and O139 belonging to sequence type (ST) 69, and in V. cholerae O1 Classical variants belonging to ST73. A phylogeny of isolates belonging to ST69 from UK travellers clustered geographically, with isolates from India and Pakistan located on separate branches. Moving forward, WGS data from UK travellers will contribute to global surveillance programs, and the monitoring of emerging threats to public health and the global dissemination of pathogenic lineages. At the national level, these WGS data will inform the timely reinforcement of direct public health messaging to travellers and mitigate the impact of imported infections and the associated risks to public health.

scholarly journals Evaluation of Whole-Genome Sequencing for Identification and Typing of Vibrio cholerae

2018 ◽  
Vol 56 (11) ◽  
Author(s):  
David R. Greig ◽  
Ulf Schaefer ◽  
Sophie Octavia ◽  
Ebony Hunter ◽  
Marie A. Chattaway ◽  
...  
Keyword(s):  
Public Health ◽  
Whole Genome Sequencing ◽  
Vibrio Cholerae ◽  
Species Identification ◽  
Genome Sequencing ◽  
National Level ◽  
Whole Genome ◽  
Content Type ◽  
El Tor ◽  
The Impact

ABSTRACT Epidemiological and microbiological data on Vibrio cholerae strains isolated between April 2004 and March 2018 (n = 836) and held at the Public Health England culture archive were reviewed. The traditional biochemical species identification and serological typing results were compared with the genome-derived species identification and serotype for a subset of isolates (n = 152). Of the 836 isolates, 750 (89.7%) were from a fecal specimen, 206 (24.6%) belonged to serogroup O1, and 7 (0.8%) were serogroup O139; 792 (94.7%) isolates were from patients reporting recent travel abroad, most commonly to India (n = 209) and Pakistan (n = 104). Of the 152 V. cholerae isolates identified by use of kmer, 149 (98.1%) were concordant with those identified using the traditional biochemical approach. Traditional serotyping results were 100% concordant with those of the whole-genome sequencing (WGS) analysis for the identification of serogroups O1 and O139 and classical and El Tor biotypes. ctxA was detected in all isolates of V. cholerae O1 El Tor and O139 belonging to sequence type 69 (ST69) and in V. cholerae O1 classical variants belonging to ST73. A phylogeny of isolates belonging to ST69 from U.K. travelers clustered geographically, with isolates from India and Pakistan located on separate branches. Moving forward, WGS data from U.K. travelers will contribute to global surveillance programs and the monitoring of emerging threats to public health and the global dissemination of pathogenic lineages. At the national level, these WGS data will inform the timely reinforcement of direct public health messaging to travelers and mitigate the impact of imported infections and the associated risks to public health.

scholarly journals Assessing reproducibility of inherited variants detected with short-read whole genome sequencing

2022 ◽  
Vol 23 (1) ◽  
Author(s):  
Bohu Pan ◽  
Luyao Ren ◽  
Vitor Onuchic ◽  
Meijian Guan ◽  
Rebecca Kusko ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Precision Medicine ◽  
Genome Sequencing ◽  
Whole Genome ◽  
Single Nucleotide Variants ◽  
Short Read ◽  
Sequencing Platforms ◽  
The Impact ◽  
Two Populations

Abstract Background Reproducible detection of inherited variants with whole genome sequencing (WGS) is vital for the implementation of precision medicine and is a complicated process in which each step affects variant call quality. Systematically assessing reproducibility of inherited variants with WGS and impact of each step in the process is needed for understanding and improving quality of inherited variants from WGS. Results To dissect the impact of factors involved in detection of inherited variants with WGS, we sequence triplicates of eight DNA samples representing two populations on three short-read sequencing platforms using three library kits in six labs and call variants with 56 combinations of aligners and callers. We find that bioinformatics pipelines (callers and aligners) have a larger impact on variant reproducibility than WGS platform or library preparation. Single-nucleotide variants (SNVs), particularly outside difficult-to-map regions, are more reproducible than small insertions and deletions (indels), which are least reproducible when > 5 bp. Increasing sequencing coverage improves indel reproducibility but has limited impact on SNVs above 30×. Conclusions Our findings highlight sources of variability in variant detection and the need for improvement of bioinformatics pipelines in the era of precision medicine with WGS.

scholarly journals Integrating patient and whole genome sequencing data to provide insights into the epidemiology of seasonal influenza A(H3N2) viruses

2017 ◽  
Author(s):  
Emily J. Goldstein ◽  
William T. Harvey ◽  
Gavin S. Wilkie ◽  
Samantha J. Shepherd ◽  
Alasdair R. MacLean ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Influenza A ◽  
Seasonal Influenza ◽  
Epidemiological Data ◽  
Respiratory Illness ◽  
Influenza Surveillance ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data

AbstractGenetic surveillance of seasonal influenza is largely focused upon sequencing of the haemagglutinin gene. Consequently, our understanding of the contribution of the remaining seven gene segments to the evolution and epidemiological dynamics of seasonal influenza is relatively limited. The increased availability of next generation sequencing technologies allows rapid and economic whole genome sequencing (WGS). Here, 150 influenza A(H3N2) positive clinical specimens with linked epidemiological data, from the 2014/15 season in Scotland, were sequenced directly using both Sanger sequencing of the HA1 region and WGS using the Illumina MiSeq platform. Sequences generated by both methods were highly consistent and WGS provided on average >90% whole genome coverage. As reported in other European countries during 2014/15, all strains belonged to genetic group 3C, with subgroup 3C.2a predominating. Inter-subgroup reassortants were identified (9%), including three 3C.3 viruses descended from a single reassortment event, which had persisted in the population. Significant phylogenetic associations with cases of severe acute respiratory illness observed herein warrant further investigation. Severe cases were also more likely to be associated with reassortant viruses (odds ratio: 4.4 (1.3-15.5)) and occur later in the season. These results suggest that increased levels of WGS, linked to clinical and epidemiological data, could improve influenza surveillance.

scholarly journals Efficient whole genome sequencing of influenza A viruses

2019 ◽  
Author(s):  
Marina Escalera-Zamudio ◽  
Ana Georgina Cobián-Güemes ◽  
Blanca Taboada ◽  
Irma López-Martínez ◽  
Joel Armando Vázquez-Pérez ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Influenza A Virus ◽  
Genome Sequencing ◽  
Influenza A ◽  
Genetic Material ◽  
Influenza Viruses ◽  
Epidemiological Surveillance ◽  
Clinical Samples ◽  
Whole Genome ◽  
Influenza A Viruses

ABSTRACTThe constant threat of emergence for novel pathogenic influenza A viruses with pandemic potential, makes full-genome characterization of circulating influenza viral strains a high priority, allowing detection of novel and re-assorting variants. Sequencing the full-length genome of influenza A virus traditionally required multiple amplification rounds, followed by the subsequent sequencing of individual PCR products. The introduction of high-throughput sequencing technologies has made whole genome sequencing easier and faster. We present a simple protocol to obtain whole genome sequences of hypothetically any influenza A virus, even with low quantities of starting genetic material. The complete genomes of influenza A viruses of different subtypes and from distinct sources (clinical samples of pdmH1N1, tissue culture-adapted H3N2 viruses, or avian influenza viruses from cloacal swabs) were amplified with a single multisegment reverse transcription-PCR reaction and sequenced using Illumina sequencing platform. Samples with low quantity of genetic material after initial PCR amplification were re-amplified by an additional PCR using random primers. Whole genome sequencing was successful for 66% of the samples, whilst the most relevant genome segments for epidemiological surveillance (corresponding to the hemagglutinin and neuraminidase) were sequenced with at least 93% coverage (and a minimum 10x) for 98% of the samples. Low coverage for some samples is likely due to an initial low viral RNA concentration in the original sample. The proposed methodology is especially suitable for sequencing a large number of samples, when genetic data is urgently required for strains characterization, and may also be useful for variant analysis.

scholarly journals SeroBA: rapid high-throughput serotyping of Streptococcus pneumoniae from whole genome sequence data

2017 ◽  
Author(s):  
Lennard Epping ◽  
Andries J. van Tonder ◽  
Rebecca A. Gladstone ◽  
Stephen D. Bentley ◽  
Andrew J. Page ◽  
...  
Keyword(s):  
Streptococcus Pneumoniae ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Whole Genome Sequence ◽  
Validation Dataset ◽  
List Type ◽  
Whole Genome ◽  
Link Type ◽  
Computational Performance ◽  
The Impact

ABSTRACTStreptococcus pneumoniae is responsible for 240,000 - 460,000 deaths in children under 5 years of age each year. Accurate identification of pneumococcal serotypes is important for tracking the distribution and evolution of serotypes following the introduction of effective vaccines. Recent efforts have been made to infer serotypes directly from genomic data but current software approaches are limited and do not scale well. Here, we introduce a novel method, SeroBA, which uses a hybrid assembly and mapping approach. We compared SeroBA against real and simulated data and present results on the concordance and computational performance against a validation dataset, the robustness and scalability when analysing a large dataset, and the impact of varying the depth of coverage in the cps locus region on sequence-based serotyping. SeroBA can predict serotypes, by identifying the cps locus, directly from raw whole genome sequencing read data with 98% concordance using a k-mer based method, can process 10,000 samples in just over 1 day using a standard server and can call serotypes at a coverage as low as 10x. SeroBA is implemented in Python3 and is freely available under an open source GPLv3 license from: https://github.com/sanger-pathogens/seroba.DATA SUMMARYThe reference genome Streptococcus pneumoniae ATCC 700669 is available from National Center for Biotechnology Information (NCBI) with the accession number: FM211187Simulated paired end reads for experiment 2 have been deposited in FigShare: https://doi.org/10.6084/m9.figshare.5086054.v1Accession numbers for all other experiments are listed in Supplementary Table S1 and Supplementary Table S2.I/We confirm all supporting data, code and protocols have been provided within the article or through supplementary data files. ⊠IMPACT STATEMENTThis article describes SeroBA, a A-mer based method for predicting the serotypes of Streptococcus pneumoniae from Whole Genome Sequencing (WGS) data. SeroBA can identify 92 serotypes and 2 subtypes with constant memory usage and low computational costs. We showed that SeroBA is able to reliably predict serotypes at a depth of coverage as low as 10x and is scalable to large datasets.

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