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  1. Article ; Online: Genome characterization of influenza A and B viruses in New South Wales, Australia, in 2019: A retrospective study using high-throughput whole genome sequencing.

    Wang, Xinye / Kim, Ki Wook / Walker, Gregory / Stelzer-Braid, Sacha / Scotch, Matthew / Rawlinson, William D

    Influenza and other respiratory viruses

    2024  Volume 18, Issue 1, Page(s) e13252

    Abstract: Background: During the 2019 severe influenza season, New South Wales (NSW) experienced the highest number of cases in Australia. This study retrospectively investigated the genetic characteristics of influenza viruses circulating in NSW in 2019 and ... ...

    Abstract Background: During the 2019 severe influenza season, New South Wales (NSW) experienced the highest number of cases in Australia. This study retrospectively investigated the genetic characteristics of influenza viruses circulating in NSW in 2019 and identified genetic markers related to antiviral resistance and potential virulence.
    Methods: The complete genomes of influenza A and B viruses were amplified using reverse transcription-polymerase chain reaction (PCR) and sequenced with an Illumina MiSeq platform.
    Results: When comparing the sequencing data with the vaccine strains and reference sequences, the phylogenetic analysis revealed that most NSW A/H3N2 viruses (n = 68; 94%) belonged to 3C.2a1b and a minority (n = 4; 6%) belonged to 3C.3a. These viruses all diverged from the vaccine strain A/Switzerland/8060/2017. All A/H1N1pdm09 viruses (n = 20) showed genetic dissimilarity from vaccine strain A/Michigan/45/2015, with subclades 6B.1A.5 and 6B.1A.2 identified. All B/Victoria-lineage viruses (n = 21) aligned with clade V1A.3, presenting triple amino acid deletions at positions 162-164 in the hemagglutinin protein, significantly diverging from the vaccine strain B/Colorado/06/2017. Multiple amino acid substitutions were also found in the internal proteins of influenza viruses, some of which have been previously reported in hospitalized influenza patients in Thailand. Notably, the oseltamivir-resistant marker H275Y was present in one immunocompromised patient infected with A/H1N1pdm09 and the resistance-related mutation I222V was detected in another A/H3N2-infected patient.
    Conclusions: Considering antigenic drift and the constant evolution of circulating A and B strains, we believe continuous monitoring of influenza viruses in NSW via the high-throughput sequencing approach provides timely and pivotal information for both public health surveillance and clinical treatment.
    MeSH term(s) Humans ; Influenza, Human ; Retrospective Studies ; Herpesvirus 1, Cercopithecine/genetics ; Influenza A Virus, H3N2 Subtype/genetics ; New South Wales/epidemiology ; Phylogeny ; Hemagglutinin Glycoproteins, Influenza Virus/genetics ; Influenza Vaccines ; Australia ; Seasons ; Whole Genome Sequencing
    Chemical Substances Hemagglutinin Glycoproteins, Influenza Virus ; Influenza Vaccines
    Language English
    Publishing date 2024-01-30
    Publishing country England
    Document type Journal Article
    ZDB-ID 2274538-5
    ISSN 1750-2659 ; 1750-2640
    ISSN (online) 1750-2659
    ISSN 1750-2640
    DOI 10.1111/irv.13252
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Detection of respiratory viruses directly from clinical samples using next-generation sequencing: A literature review of recent advances and potential for routine clinical use.

    Wang, Xinye / Stelzer-Braid, Sacha / Scotch, Matthew / Rawlinson, William D

    Reviews in medical virology

    2022  Volume 32, Issue 5, Page(s) e2375

    Abstract: Acute respiratory infection is the third most frequent cause of mortality worldwide, causing over 4.25 million deaths annually. Although most diagnosed acute respiratory infections are thought to be of viral origin, the aetiology often remains unclear. ... ...

    Abstract Acute respiratory infection is the third most frequent cause of mortality worldwide, causing over 4.25 million deaths annually. Although most diagnosed acute respiratory infections are thought to be of viral origin, the aetiology often remains unclear. The advent of next-generation sequencing (NGS) has revolutionised the field of virus discovery and identification, particularly in the detection of unknown respiratory viruses. We systematically reviewed the application of NGS technologies for detecting respiratory viruses from clinical samples and outline potential barriers to the routine clinical introduction of NGS. The five databases searched for studies published in English from 01 January 2010 to 01 February 2021, which led to the inclusion of 52 studies. A total of 14 different models of NGS platforms were summarised from included studies. Among these models, second-generation sequencing platforms (e.g., Illumina sequencers) were used in the majority of studies (41/52, 79%). Moreover, NGS platforms have proven successful in detecting a variety of respiratory viruses, including influenza A/B viruses (9/52, 17%), SARS-CoV-2 (21/52, 40%), parainfluenza virus (3/52, 6%), respiratory syncytial virus (1/52, 2%), human metapneumovirus (2/52, 4%), or a viral panel including other respiratory viruses (16/52, 31%). The review of NGS technologies used in previous studies indicates the advantages of NGS technologies in novel virus detection, virus typing, mutation identification, and infection cluster assessment. Although there remain some technical and ethical challenges associated with NGS use in clinical laboratories, NGS is a promising future tool to improve understanding of respiratory viruses and provide a more accurate diagnosis with simultaneous virus characterisation.
    MeSH term(s) COVID-19 ; High-Throughput Nucleotide Sequencing ; Humans ; Influenza A virus ; Influenza B virus ; Respiratory Tract Infections/diagnosis ; SARS-CoV-2
    Language English
    Publishing date 2022-07-01
    Publishing country England
    Document type Journal Article ; Review ; Systematic Review ; Research Support, Non-U.S. Gov't
    ZDB-ID 1086043-5
    ISSN 1099-1654 ; 1052-9276
    ISSN (online) 1099-1654
    ISSN 1052-9276
    DOI 10.1002/rmv.2375
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Outbreaks of acute flaccid myelitis in the US.

    Stelzer-Braid, Sacha / Rawlinson, William

    BMJ (Clinical research ed.)

    2018  Volume 363, Page(s) k5246

    MeSH term(s) Acute Disease ; Centers for Disease Control and Prevention (U.S.) ; Child ; Disease Outbreaks/statistics & numerical data ; Enterovirus D, Human/isolation & purification ; Enterovirus Infections/epidemiology ; Enterovirus Infections/virology ; Humans ; Myelitis/epidemiology ; Myelitis/virology ; United States/epidemiology
    Language English
    Publishing date 2018-12-19
    Publishing country England
    Document type Editorial
    ZDB-ID 1362901-3
    ISSN 1756-1833 ; 0959-8154 ; 0959-8146 ; 0959-8138 ; 0959-535X ; 1759-2151
    ISSN (online) 1756-1833
    ISSN 0959-8154 ; 0959-8146 ; 0959-8138 ; 0959-535X ; 1759-2151
    DOI 10.1136/bmj.k5246
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Preventing upper respiratory tract infections with prophylactic nasal carrageenan: a feasibility study.

    Halley, Caroline / Honeywill, Claire / Kang, Janice / Pierse, Nevil / Robertson, Oliver / Rawlinson, William / Stelzer-Braid, Sacha / Willink, Robin / Crane, Julian

    Future microbiology

    2023  Volume 18, Page(s) 1319–1328

    Abstract: Aim: ...

    Abstract Aim:
    MeSH term(s) Adult ; Humans ; Carrageenan/therapeutic use ; Feasibility Studies ; Respiratory Tract Infections/drug therapy ; Respiratory Tract Infections/prevention & control ; Nose ; Nasal Sprays ; Double-Blind Method
    Chemical Substances Carrageenan (9000-07-1) ; Nasal Sprays
    Language English
    Publishing date 2023-10-13
    Publishing country England
    Document type Randomized Controlled Trial ; Journal Article
    ZDB-ID 2254620-0
    ISSN 1746-0921 ; 1746-0913
    ISSN (online) 1746-0921
    ISSN 1746-0913
    DOI 10.2217/fmb-2021-0122
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Machine Learning Color Feature Analysis of a High Throughput Nanoparticle Conjugate Sensing Assay.

    Bennett, Danielle / Chen, Xueqian / Walker, Gregory J / Stelzer-Braid, Sacha / Rawlinson, William D / Hibbert, D Brynn / Tilley, Richard D / Gooding, J Justin

    Analytical chemistry

    2023  Volume 95, Issue 16, Page(s) 6550–6558

    Abstract: Plasmonic nanoparticles are finding applications within the single molecule sensing field in a "dimer" format, where interaction of the target with hairpin DNA causes a decrease in the interparticle distance, leading to a localized surface plasmon ... ...

    Abstract Plasmonic nanoparticles are finding applications within the single molecule sensing field in a "dimer" format, where interaction of the target with hairpin DNA causes a decrease in the interparticle distance, leading to a localized surface plasmon resonance shift. While this shift may be detected using spectroscopy, achieving statistical relevance requires the measurement of thousands of nanoparticle dimers and the timescales required for spectroscopic analysis are incompatible with point-of-care devices. However, using dark-field imaging of the dimer structures, simultaneous digital analysis of the plasmonic resonance shift after target interaction of thousands of dimer structures may be achieved in minutes. The main challenge of this digital analysis on the single-molecule scale was the occurrence of false signals caused by non-specifically bound clusters of nanoparticles. This effect may be reduced by digitally separating dimers from other nanoconjugate types. Variation in image intensity was observed to have a discernible impact on the color analysis of the nanoconjugate constructs and thus the accuracy of the digital separation. Color spaces wherein intensity may be uncoupled from the color information (hue, saturation, and value (HSV) and luminance, a* vector, and b* vector (LAB) were contrasted to a color space which cannot uncouple intensity (RGB) to train a classifier algorithm. Each classifier algorithm was validated to determine which color space produced the most accurate digital separation of the nanoconjugate types. The LAB-based learning classifier demonstrated the highest accuracy for digitally separating nanoparticles. Using this classifier, nanoparticle conjugates were monitored for their plasmonic color shift after interaction with a synthetic RNA target, resulting in a platform with a highly accurate yes/no response with a true positive rate of 88% and a true negative rate of 100%. The sensor response of tested single stranded RNA (ssRNA) samples was well above control responses for target concentrations in the range of 10 aM-1 pM.
    MeSH term(s) Color ; Machine Learning ; Nanoconjugates ; Nanotechnology/methods ; Surface Plasmon Resonance/methods
    Chemical Substances Nanoconjugates
    Language English
    Publishing date 2023-04-10
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 1508-8
    ISSN 1520-6882 ; 0003-2700
    ISSN (online) 1520-6882
    ISSN 0003-2700
    DOI 10.1021/acs.analchem.2c05292
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Clinical, Genomic, and Immunological Characterization of RSV Surge in Sydney, Australia, 2022.

    Walker, Gregory J / Foster, Charles S P / Sevendal, Andrea / Domazetovska, Ana / Kamalakkannan, Abbish / Williams, Phoebe C M / Kim, Ki Wook / Condylios, Anna / Stelzer-Braid, Sacha / Bartlett, Adam W / Rawlinson, William

    Pediatrics

    2024  Volume 153, Issue 2

    Abstract: Objectives: The 2022 seasonal respiratory syncytial virus (RSV) epidemic in Sydney, Australia saw an unprecedented number of RSV detections. We aimed to characterize genomic and immunologic factors associated with the surge in RSV cases.: Methods: ... ...

    Abstract Objectives: The 2022 seasonal respiratory syncytial virus (RSV) epidemic in Sydney, Australia saw an unprecedented number of RSV detections. We aimed to characterize genomic and immunologic factors associated with the surge in RSV cases.
    Methods: Whole genome sequences of RSV were generated from 264 RSV-infected infants and linked to case-matched clinical data from the 2022 southern hemisphere RSV season. We then performed an immunologic analysis of baseline RSV-specific humoral immunity in women of childbearing age before and throughout the coronavirus disease 2019 pandemic.
    Results: Clinical analysis revealed a high burden of disease across patients of all health backgrounds. More than one-half of RSV-related health care visits by infants resulted in hospitalization, and one-quarter required high-flow respiratory support or a higher level of care. Viral phylogenetic analyses revealed that 2022 Sydney RSV sequences were closely related to viruses that had been circulating globally since 2017, including those detected in recent US outbreaks. Nonsynonymous mutations within the palivizumab and nirsevimab binding sites were detected at low frequencies. There was no difference in baseline RSV-neutralizing antibody titers between 2020 and 2022.
    Conclusions: Collectively, these findings suggest that neither the emergence of a novel RSV genotype nor hypothesized immune debt was associated with the surge of RSV cases and hospitalizations in 2022. Continued genomic and immunologic surveillance is required to further understand the factors driving outbreaks of RSV globally, and to inform guidelines for the rollout and ongoing use of recently developed immunotherapeutics and vaccines.
    MeSH term(s) Infant ; Humans ; Female ; Respiratory Syncytial Viruses ; Antiviral Agents/therapeutic use ; Respiratory Syncytial Virus Infections/drug therapy ; Phylogeny ; Palivizumab ; Genomics
    Chemical Substances Antiviral Agents ; Palivizumab (DQ448MW7KS)
    Language English
    Publishing date 2024-01-15
    Publishing country United States
    Document type Journal Article
    ZDB-ID 207677-9
    ISSN 1098-4275 ; 0031-4005
    ISSN (online) 1098-4275
    ISSN 0031-4005
    DOI 10.1542/peds.2023-063667
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Correction to "Machine Learning Color Feature Analysis of a High Throughput Nanoparticle Conjugate Sensing Assay.

    Bennett, Danielle / Chen, Xueqian / Walker, Gregory J / Mehdipour, Milad / Stelzer-Braid, Sacha / Rawlinson, William D / Hibbert, D Brynn / Tilley, Richard D / Gooding, J Justin

    Analytical chemistry

    2023  Volume 95, Issue 21, Page(s) 8393

    Language English
    Publishing date 2023-05-15
    Publishing country United States
    Document type Published Erratum
    ZDB-ID 1508-8
    ISSN 1520-6882 ; 0003-2700
    ISSN (online) 1520-6882
    ISSN 0003-2700
    DOI 10.1021/acs.analchem.3c01892
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Global epidemiology of nonpolio enteroviruses causing severe neurological complications: A systematic review and meta-analysis.

    Suresh, Sarika / Rawlinson, William D / Andrews, Peter Ian / Stelzer-Braid, Sacha

    Reviews in medical virology

    2019  Volume 30, Issue 1, Page(s) e2082

    Abstract: Enteroviruses are RNA viruses found as commensals in the human gut and respiratory system, which may cause a wide spectrum of disease. Enteroviruses may cause severe neurologic complications including acute flaccid paralysis (AFP) and encephalitis and ... ...

    Abstract Enteroviruses are RNA viruses found as commensals in the human gut and respiratory system, which may cause a wide spectrum of disease. Enteroviruses may cause severe neurologic complications including acute flaccid paralysis (AFP) and encephalitis and are the most commonly diagnosed agents of viral meningitis. Outbreaks of more severe disease are often associated with particular genotypes, such as enterovirus-A71 causing rhombencephalitis and AFP. There are more than 300 described genotypes of human enterovirus, with overlaps in clinical phenotypes between genotypes, and uncertainty about which genotypes are more prevalent in neurological manifestations. A systematic review of observational studies was conducted to evaluate the most prevalent enterovirus genotypes causing AFP, encephalitis, and meningitis. The genotyping methods and sampling sites were compiled as secondary outcomes. Sources included MEDLINE, Embase (publications until January 2019), and references selected from included studies. Meta-analyses using a random effects model were performed to calculate the pooled proportion of enterovirus genotypes in each disease. Ninety-six publications met the eligibility criteria, comprising 3779 AFP cases, 1140 encephalitis cases, and 32 810 meningitis cases. Enterovirus-A71 was most frequently associated with AFP (pooled proportion 0.12, 95% CI, 0.05-0.20) and encephalitis (0.77, 95% CI, 0.61-0.91). Echovirus 30 (0.35, 95% CI, 0.27-0.42) was the most predominant genotype in meningitis cases. Genotypes were most commonly determined using VP1 RT- reverse transcription-polymerase chain reaction, and most samples assessed were cerebrospinal fluid. With the emergence of enteroviruses as an increasing cause of neurological diseases, surveillance and testing need to increase to identify the aetiology of the most common and most severe disorders.
    MeSH term(s) Disease Outbreaks ; Disease Susceptibility ; Enterovirus/classification ; Enterovirus/physiology ; Enterovirus Infections/complications ; Enterovirus Infections/epidemiology ; Enterovirus Infections/virology ; Genotype ; Global Health ; Humans ; Nervous System Diseases/diagnosis ; Nervous System Diseases/epidemiology ; Nervous System Diseases/etiology ; Population Surveillance ; Species Specificity
    Language English
    Publishing date 2019-10-06
    Publishing country England
    Document type Journal Article ; Meta-Analysis ; Systematic Review
    ZDB-ID 1086043-5
    ISSN 1099-1654 ; 1052-9276
    ISSN (online) 1099-1654
    ISSN 1052-9276
    DOI 10.1002/rmv.2082
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Machine Learning Color Feature Analysis of a High Throughput Nanoparticle Conjugate Sensing Assay

    Bennett, Danielle / Chen, Xueqian / Walker, Gregory J. / Stelzer-Braid, Sacha / Rawlinson, William D. / Hibbert, D. Brynn / Tilley, Richard D. / Gooding, J. Justin

    Analytical Chemistry. 2023 Apr. 10, v. 95, no. 16, p. 6550–6558

    2023  , Page(s) 6550

    Abstract: Plasmonic nanoparticles are finding applications within the single molecule sensing field in a “dimer” format, where interaction of the target with hairpin DNA causes a decrease in the interparticle distance, leading to a localized surface plasmon ... ...

    Abstract Plasmonic nanoparticles are finding applications within the single molecule sensing field in a “dimer” format, where interaction of the target with hairpin DNA causes a decrease in the interparticle distance, leading to a localized surface plasmon resonance shift. While this shift may be detected using spectroscopy, achieving statistical relevance requires the measurement of thousands of nanoparticle dimers and the timescales required for spectroscopic analysis are incompatible with point-of-care devices. However, using dark-field imaging of the dimer structures, simultaneous digital analysis of the plasmonic resonance shift after target interaction of thousands of dimer structures may be achieved in minutes. The main challenge of this digital analysis on the single-molecule scale was the occurrence of false signals caused by non-specifically bound clusters of nanoparticles. This effect may be reduced by digitally separating dimers from other nanoconjugate types. Variation in image intensity was observed to have a discernible impact on the color analysis of the nanoconjugate constructs and thus the accuracy of the digital separation. Color spaces wherein intensity may be uncoupled from the color information (hue, saturation, and value (HSV) and luminance, a* vector, and b* vector (LAB) were contrasted to a color space which cannot uncouple intensity (RGB) to train a classifier algorithm. Each classifier algorithm was validated to determine which color space produced the most accurate digital separation of the nanoconjugate types. The LAB-based learning classifier demonstrated the highest accuracy for digitally separating nanoparticles. Using this classifier, nanoparticle conjugates were monitored for their plasmonic color shift after interaction with a synthetic RNA target, resulting in a platform with a highly accurate yes/no response with a true positive rate of 88% and a true negative rate of 100%. The sensor response of tested single stranded RNA (ssRNA) samples was well above control responses for target concentrations in the range of 10 aM–1 pM.
    Keywords DNA ; RNA ; algorithms ; analytical chemistry ; color ; nanoparticles ; point-of-care systems ; spectral analysis ; spectroscopy ; surface plasmon resonance
    Language English
    Dates of publication 2023-0410
    Size p. 6550–6558
    Publishing place American Chemical Society
    Document type Article ; Online
    ZDB-ID 1508-8
    ISSN 1520-6882 ; 0003-2700
    ISSN (online) 1520-6882
    ISSN 0003-2700
    DOI 10.1021/acs.analchem.2c05292
    Database NAL-Catalogue (AGRICOLA)

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  10. Article ; Online: Assessment of Inter-Laboratory Differences in SARS-CoV-2 Consensus Genome Assemblies between Public Health Laboratories in Australia.

    Foster, Charles S P / Stelzer-Braid, Sacha / Deveson, Ira W / Bull, Rowena A / Yeang, Malinna / Au, Jane-Phan / Ruiz Silva, Mariana / van Hal, Sebastiaan J / Rockett, Rebecca J / Sintchenko, Vitali / Kim, Ki Wook / Rawlinson, William D

    Viruses

    2022  Volume 14, Issue 2

    Abstract: Whole-genome sequencing of viral isolates is critical for informing transmission patterns and for the ongoing evolution of pathogens, especially during a pandemic. However, when genomes have low variability in the early stages of a pandemic, the impact ... ...

    Abstract Whole-genome sequencing of viral isolates is critical for informing transmission patterns and for the ongoing evolution of pathogens, especially during a pandemic. However, when genomes have low variability in the early stages of a pandemic, the impact of technical and/or sequencing errors increases. We quantitatively assessed inter-laboratory differences in consensus genome assemblies of 72 matched SARS-CoV-2-positive specimens sequenced at different laboratories in Sydney, Australia. Raw sequence data were assembled using two different bioinformatics pipelines in parallel, and resulting consensus genomes were compared to detect laboratory-specific differences. Matched genome sequences were predominantly concordant, with a median pairwise identity of 99.997%. Identified differences were predominantly driven by ambiguous site content. Ignoring these produced differences in only 2.3% (5/216) of pairwise comparisons, each differing by a single nucleotide. Matched samples were assigned the same Pango lineage in 98.2% (212/216) of pairwise comparisons, and were mostly assigned to the same phylogenetic clade. However, epidemiological inference based only on single nucleotide variant distances may lead to significant differences in the number of defined clusters if variant allele frequency thresholds for consensus genome generation differ between laboratories. These results underscore the need for a unified, best-practices approach to bioinformatics between laboratories working on a common outbreak problem.
    MeSH term(s) Australia ; Computational Biology/methods ; Computational Biology/standards ; Consensus ; Genome, Viral ; Humans ; Laboratories/standards ; Phylogeny ; Public Health ; SARS-CoV-2/classification ; SARS-CoV-2/genetics ; Whole Genome Sequencing
    Language English
    Publishing date 2022-01-19
    Publishing country Switzerland
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2516098-9
    ISSN 1999-4915 ; 1999-4915
    ISSN (online) 1999-4915
    ISSN 1999-4915
    DOI 10.3390/v14020185
    Database MEDical Literature Analysis and Retrieval System OnLINE

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