A laboratory framework for ongoing optimization of amplification-based genomic surveillance programs.

IMPORTANCE: This study provides a laboratory framework to ensure ongoing relevance and performance of amplification-based whole genome sequencing to strengthen public health surveillance during extended outbreaks or pandemics. The framework integrates regular reviews of the performance of a genomic surveillance system and highlights the importance of ongoing monitoring and the identification and implementation of improvements to whole genome sequencing methods to enhance public health responses to pathogen outbreaks.

SABRes: in silico detection of drug resistance conferring mutations in subpopulations of SARS-CoV-2 genomes.

The emergence of resistance to antiviral drugs increasingly used to treat SARS-CoV-2 infections has been recognised as a significant threat to COVID-19 control. In addition, some SARS-CoV-2 variants of concern appear to be intrinsically resistant to several classes of these antiviral agents. Therefore, there is a critical need for rapid recognition of clinically relevant polymorphisms in SARS-CoV-2 genomes associated with significant reduction of drug activity in virus neutralisation experiments. Here we present SABRes, a bioinformatic tool, which leverages on expanding public datasets of SARS-CoV-2 genomes and allows detection of drug resistance mutations in consensus genomes as well as in viral subpopulations. We have applied SABRes to detect resistance-conferring mutations in 25,197 genomes generated over the course of the SARS-CoV-2 pandemic in Australia and identified 299 genomes containing resistance conferring mutations to the five antiviral therapeutics that retain effectiveness against currently circulating strains of SARS-CoV-2 - Sotrovimab, Bebtelovimab, Remdesivir, Nirmatrelvir and Molnupiravir. These genomes accounted for a 1.18% prevalence of resistant isolates discovered by SABRes, including 80 genomes with resistance conferring mutations found in viral subpopulations. Timely recognition of these mutations within subpopulations is critical as these mutations can provide an advantage under selective pressure and presents an important step forward in our ability to monitor SARS-CoV-2 drug resistance.

Genome entropy and network centrality contrast exploration and exploitation in evolution of foodborne pathogens.

Modelling evolution of foodborne pathogens is crucial for mitigation and prevention of outbreaks. We apply network-theoretic and information-theoretic methods to trace evolutionary pathways ofSalmonellaTyphimurium in New South Wales, Australia, by studying whole genome sequencing surveillance data over a five-year period which included several outbreaks. The study derives both undirected and directed genotype networks based on genetic proximity, and relates the network's structural property (centrality) to its functional property (prevalence). The centrality-prevalence space derived for the undirected network reveals a salient exploration-exploitation distinction across the pathogens, further quantified by the normalised Shannon entropy and the Fisher information of the corresponding shell genome. This distinction is also analysed by tracing the probability density along evolutionary paths in the centrality-prevalence space. We quantify the evolutionary pathways, and show that pathogens exploring the evolutionary search-space during the considered period begin to exploit their environment (their prevalence increases resulting in outbreaks), but eventually encounter a bottleneck formed by epidemic containment measures.

Pangenome Analysis of a Salmonella Enteritidis Population Links a Major Outbreak to a Gifsy-1-Like Prophage Containing Anti-Inflammatory Gene gogB.

A major outbreak of the globally significant Salmonella Enteritidis foodborne pathogen was identified within a large clinical data set by a program of routine WGS of clinical presentations of salmonellosis in New South Wales, Australia. Pangenome analysis helped to quantify and isolate prophage content within the accessory partition of the pangenome. A prophage similar to Gifsy-1 (henceforth GF-1L) was found to occur in all isolates of the outbreak core SNP cluster, and in three other isolates. Further analysis revealed that the GF-1L prophage carried the gogB virulence factor. These observations suggest that GF-1L may be an important marker of virulence for S. Enteritidis population screening and, that anti-inflammatory, gogB-mediated virulence currently associated with Salmonella Typhimurium may also be displayed by S. Enteritidis. IMPORTANCE We examined 5 years of genomic and epidemiological data for the significant global foodborne pathogen, Salmonella enterica. Although Salmonella enterica subspecies enterica serovar Enteritidis (S. Enteritidis) is the leading cause of salmonellosis in the USA and Europe, prior to 2018 it was not endemic in the southern states of Australia. However, in 2018 a large outbreak led to the endemicity of S. Enteritidis in New South Wales, Australia, and a unique opportunity to study this phenomenon. Using pangenome analysis we uncovered that this clone contained a Gifsy-1-like prophage harboring the known virulence factor gogB. The prophage reported has not previously been described in S. Enteritidis isolates.

Guiding the design of SARS-CoV-2 genomic surveillance by estimating the resolution of outbreak detection.

Genomic surveillance of SARS-CoV-2 has been essential to inform public health response to outbreaks. The high incidence of infection has resulted in a smaller proportion of cases undergoing whole genome sequencing due to finite resources. We present a framework for estimating the impact of reduced depths of genomic surveillance on the resolution of outbreaks, based on a clustering approach using pairwise genetic and temporal distances. We apply the framework to simulated outbreak data to show that outbreaks are detected less frequently when fewer cases are subjected to whole genome sequencing. The impact of sequencing fewer cases depends on the size of the outbreaks, and on the genetic and temporal similarity of the index cases of the outbreaks. We also apply the framework to an outbreak of the SARS-CoV-2 Delta variant in New South Wales, Australia. We find that the detection of clusters in the outbreak would have been delayed if fewer cases had been sequenced. Existing recommendations for genomic surveillance estimate the minimum number of cases to sequence in order to detect and monitor new virus variants, assuming representative sampling of cases. Our method instead measures the resolution of clustering, which is important for genomic epidemiology, and accommodates sampling biases.

Improved Neutralisation of the SARS-CoV-2 Omicron Variant following a Booster Dose of Pfizer-BioNTech (BNT162b2) COVID-19 Vaccine.

In late November 2021, the World Health Organization declared the SARS-CoV-2 lineage B.1.1.529 the fifth variant of concern, Omicron. This variant has acquired over 30 mutations in the spike protein (with 15 in the receptor-binding domain), raising concerns that Omicron could evade naturally acquired and vaccine-derived immunity. We utilized an authentic virus, multicycle neutralisation assay to demonstrate that sera collected one, three, and six months post-two doses of Pfizer-BioNTech BNT162b2 had a limited ability to neutralise SARS-CoV-2. However, four weeks after a third dose, neutralising antibody titres were boosted. Despite this increase, neutralising antibody titres were reduced fourfold for Omicron compared to lineage A.2.2 SARS-CoV-2.

Development and Validation of an In-House Real-Time Reverse-Transcriptase Polymerase Chain Reaction Assay for SARS-CoV-2 Omicron Lineage Subtyping between BA.1 and BA.2.

In order to rapidly differentiate sublineages BA.1 and BA.2 of the SARS-CoV-2 variant of concern Omicron, we developed a real-time reverse-transcriptase polymerase chain reaction to target the discriminatory spike protein deletion at amino acid position 69-70 (S:del69-70). Compared to the gold standard of whole genome sequencing, the candidate assay was 100% sensitive and 99.4% specific. Sublineage typing by RT-PCR can provide a rapid, high throughput and cost-effective method to enhance surveillance as well as potentially guiding treatment and infection control decisions.

Emergence of Japanese encephalitis in Australia: a diagnostic perspective.

The unprecedented emergence of Japanese encephalitis (JE) in mainland Australia represents an outbreak of high clinical and public health significance. JE is a zoonosis spread by mosquitoes and is one of the most important causes of endemic viral encephalitis in South-East Asia and the Indian subcontinent. While occasional cases of human Japanese encephalitis virus (JEV) infection have occurred in far north Australia, its detection in pigs and the substantial number of locally acquired human cases across multiple jurisdictions in early 2022 prompted the declaration of this outbreak as a Communicable Disease Incident of National Significance. Laboratory testing for JEV is complex, and most cases are diagnosed by serology, for which interpretation is difficult. This review provides a comprehensive outline of currently available methods for JEV diagnosis including serology, nucleic acid amplification testing, virus isolation, sequencing and metagenomics. The relative advantages and disadvantages of the diagnostic tests are presented, as well as their value in clinical and public health contexts. This review also explores the role of mosquito, veterinary and human surveillance as part of the laboratory response to JEV. As JEV may become endemic in Australia, a collaborative and coordinated One Health approach involving animal, human and environmental health is required for optimal disease response and control.

SARS-CoV-2 Within-Host and in vitro Genomic Variability and Sub-Genomic RNA Levels Indicate Differences in Viral Expression Between Clinical Cohorts and in vitro Culture.

Background: Low frequency intrahost single nucleotide variants (iSNVs) of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) have been increasingly recognised as predictive indicators of positive selection. Particularly as growing numbers of SARS-CoV-2 variants of interest (VOI) and concern (VOC) emerge. However, the dynamics of subgenomic RNA (sgRNA) expression and its impact on genomic diversity and infection outcome remain poorly understood. This study aims to investigate and quantify iSNVs and sgRNA expression in single and longitudinally sampled cohorts over the course of mild and severe SARS-CoV-2 infection, benchmarked against an in vitro infection model. Methods: Two clinical cohorts of SARS-CoV-2 positive cases in New South Wales, Australia collected between March 2020 and August 2021 were sequenced. Longitudinal samples from cases hospitalised due to SARS-CoV-2 infection (severe) (n = 16) were analysed and compared with cases that presented with SARS-CoV-2 symptoms but were not hospitalised (mild) (n = 23). SARS-CoV-2 genomic diversity profiles were also examined from daily sampling of culture experiments for three SARS-CoV-2 variants (Lineage A, B.1.351, and B.1.617.2) cultured in VeroE6 C1008 cells (n = 33). Results: Intrahost single nucleotide variants were detected in 83% (19/23) of the mild cohort cases and 100% (16/16) of the severe cohort cases. SNP profiles remained relatively fixed over time, with an average of 1.66 SNPs gained or lost, and an average of 4.2 and 5.9 low frequency variants per patient were detected in severe and mild infection, respectively. sgRNA was detected in 100% (25/25) of the mild genomes and 92% (24/26) of the severe genomes. Total sgRNA expressed across all genes in the mild cohort was significantly higher than that of the severe cohort. Significantly higher expression levels were detected in the spike and the nucleocapsid genes. There was significantly less sgRNA detected in the culture dilutions than the clinical cohorts. Discussion and Conclusion: The positions and frequencies of iSNVs in the severe and mild infection cohorts were dynamic overtime, highlighting the importance of continual monitoring, particularly during community outbreaks where multiple SARS-CoV-2 variants may co-circulate. sgRNA levels can vary across patients and the overall level of sgRNA reads compared to genomic RNA can be less than 1%. The relative contribution of sgRNA to the severity of illness warrants further investigation given the level of variation between genomes. Further monitoring of sgRNAs will improve the understanding of SARS-CoV-2 evolution and the effectiveness of therapeutic and public health containment measures during the pandemic.

Co-infection with SARS-CoV-2 Omicron and Delta variants revealed by genomic surveillance.

Co-infections with different variants of SARS-CoV-2 are a key precursor to recombination events that are likely to drive SARS-CoV-2 evolution. Rapid identification of such co-infections is required to determine their frequency in the community, particularly in populations at-risk of severe COVID-19, which have already been identified as incubators for punctuated evolutionary events. However, limited data and tools are currently available to detect and characterise the SARS-CoV-2 co-infections associated with recognised variants of concern. Here we describe co-infection with the SARS-CoV-2 variants of concern Omicron and Delta in two epidemiologically unrelated adult patients with chronic kidney disease requiring maintenance haemodialysis. Both variants were co-circulating in the community at the time of detection. Genomic surveillance based on amplicon- and probe-based sequencing using short- and long-read technologies identified and quantified subpopulations of Delta and Omicron viruses in respiratory samples. These findings highlight the importance of integrated genomic surveillance in vulnerable populations and provide diagnostic pathways to recognise SARS-CoV-2 co-infection using genomic data.

Assessment of Inter-Laboratory Differences in SARS-CoV-2 Consensus Genome Assemblies between Public Health Laboratories in Australia.

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.

Genome-wide networks reveal emergence of epidemic strains of Salmonella Enteritidis.

OBJECTIVES: To enhance monitoring of high-burden foodborne pathogens, there is opportunity to combine pangenome data with network analysis. METHODS: Salmonella enterica subspecies Enterica serovar Enteritidis isolates were referred to the New South Wales (NSW) Enteric Reference Laboratory between August 2015 and December 2019 (1033 isolates in total), inclusive of a confirmed outbreak. All isolates underwent whole genome sequencing. Distances between genomes were quantified by in silico multiple-locus variable-number tandem repeat analysis (MLVA) as well as core single nucleotide polymorphisms (SNPs), which informed the construction of undirected networks. Centrality-prevalence spaces were generated from the undirected networks. Components on the undirected SNP network were considered alongside a phylogenetic tree representation. RESULTS: Outbreak isolates were identified as distinct components on the MLVA and SNP networks. The MLVA network-based centrality-prevalence space did not delineate the outbreak, whereas the outbreak was delineated in the SNP network-based centrality-prevalence space. Components on the undirected SNP network showed a high concordance to the SNP clusters based on phylogenetic analysis. CONCLUSIONS: Bacterial whole-genome data in network-based analysis can improve the resolution of population analysis. High concordance of network components and SNP clusters is promising for rapid population analyses of foodborne Salmonella spp. owing to the low overhead of network analysis.

Documenting elimination of co-circulating COVID-19 clusters using genomics in New South Wales, Australia.

OBJECTIVE: To adapt 'fishplots' to describe real-time evolution of SARS-CoV-2 genomic clusters. RESULTS: This novel analysis adapted the fishplot to depict the size and duration of circulating genomic clusters over time in New South Wales, Australia. It illuminated the effectiveness of interventions on the emergence, spread and eventual elimination of clusters and distilled genomic data into clear information to inform public health action.

SARS-CoV-2 neutralizing antibodies: Longevity, breadth, and evasion by emerging viral variants.

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) antibody neutralization response and its evasion by emerging viral variants and variant of concern (VOC) are unknown, but critical to understand reinfection risk and breakthrough infection following vaccination. Antibody immunoreactivity against SARS-CoV-2 antigens and Spike variants, inhibition of Spike-driven virus-cell fusion, and infectious SARS-CoV-2 neutralization were characterized in 807 serial samples from 233 reverse transcription polymerase chain reaction (RT-PCR)-confirmed Coronavirus Disease 2019 (COVID-19) individuals with detailed demographics and followed up to 7 months. A broad and sustained polyantigenic immunoreactivity against SARS-CoV-2 Spike, Membrane, and Nucleocapsid proteins, along with high viral neutralization, was associated with COVID-19 severity. A subgroup of "high responders" maintained high neutralizing responses over time, representing ideal convalescent plasma donors. Antibodies generated against SARS-CoV-2 during the first COVID-19 wave had reduced immunoreactivity and neutralization potency to emerging Spike variants and VOC. Accurate monitoring of SARS-CoV-2 antibody responses would be essential for selection of optimal responders and vaccine monitoring and design.

Genetic diversity of SARS-CoV-2 and clinical, epidemiological characteristics of COVID-19 patients in Hanoi, Vietnam.

A second cluster of COVID-19 cases imported from Europe occured in Vietnam from early March 2020. We describe 44 SARS-CoV-2 RT-PCR positive patients (cycle threshold value <30) admitted to the National Hospital for Tropical Diseases in Hanoi between March 6 and April 15 2020. Whole SARS-CoV-2 genomes from these patients were sequenced using Illumina Miseq and analysed for common genetic variants and relationships to local and globally circulating strains. Results showed that 32 cases were Vietnamese with a median age of 37 years (range 15-74 years), and 23 were male. Most cases were acquired outside Vietnam, mainly from the UK (n = 15), other European countries (n = 14), Russia (n = 6) and countries in Asia (n = 3). No cases had travelled from China. Forty-one cases had symptoms at admission, typically dry cough (n = 36), fever (n = 20), sore throat (n = 14) and diarrhoea (n = 12). Hospitalisation was long with a median of 25 days, most commonly from 20-29 days. All SARS-CoV-2 genomes were similar (92-100% sequence homology) to the reference sequence Wuhan_1 (NC_045512), and 32 strains belonged to the B.1.1 lineage. The three most common variants were linked, and included C3037T, C14408T (nsp12: P323L) and A23403G (S: D614G) mutations. This group of mutations often accompanied variant C241T (39/44 genomes) or GGG 28881..28883 AAC (33/44 genomes). The prevalence of the former reflected probable European origin of viruses, and the transition D614G was dominant in Vietnam. New variants were identified; however, none could be associated with disease severity.

Complete microbial genomes for public health in Australia and the Southwest Pacific.

Complete genomes of microbial pathogens are essential for the phylogenomic analyses that increasingly underpin core public health laboratory activities. Here, we announce a BioProject (PRJNA556438) dedicated to sharing complete genomes chosen to represent a range of pathogenic bacteria with regional importance to Australia and the Southwest Pacific; enriching the catalogue of globally available complete genomes for public health while providing valuable strains to regional public health microbiology laboratories. In this first step, we present 26 complete high-quality bacterial genomes. Additionally, we describe here a framework for reconstructing complete microbial genomes and highlight some of the challenges and considerations for accurate and reproducible genome reconstruction.

Revealing COVID-19 transmission in Australia by SARS-CoV-2 genome sequencing and agent-based modeling.

In January 2020, a novel betacoronavirus (family Coronaviridae), named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was identified as the etiological agent of a cluster of pneumonia cases occurring in Wuhan City, Hubei Province, China1,2. The disease arising from SARS-CoV-2 infection, coronavirus disease 2019 (COVID-19), subsequently spread rapidly causing a worldwide pandemic. Here we examine the added value of near real-time genome sequencing of SARS-CoV-2 in a subpopulation of infected patients during the first 10 weeks of COVID-19 containment in Australia and compare findings from genomic surveillance with predictions of a computational agent-based model (ABM). Using the Australian census data, the ABM generates over 24 million software agents representing the population of Australia, each with demographic attributes of an anonymous individual. It then simulates transmission of the disease over time, spreading from specific infection sources, using contact rates of individuals within different social contexts. We report that the prospective sequencing of SARS-CoV-2 clarified the probable source of infection in cases where epidemiological links could not be determined, significantly decreased the proportion of COVID-19 cases with contentious links, documented genomically similar cases associated with concurrent transmission in several institutions and identified previously unsuspected links. Only a quarter of sequenced cases appeared to be locally acquired and were concordant with predictions from the ABM. These high-resolution genomic data are crucial to track cases with locally acquired COVID-19 and for timely recognition of independent importations once border restrictions are lifted and trade and travel resume.

Genomic Surveillance Enables Suitability Assessment of Salmonella Gene Targets Used for Culture-Independent Diagnostic Testing.

Salmonella is a highly diverse genus consisting of over 2,600 serovars responsible for high-burden food- and waterborne gastroenteritis worldwide. Sensitivity and specificity of PCR-based culture-independent diagnostic testing (CIDT) systems for Salmonella, which depend on a highly conserved gene target, can be affected by single nucleotide polymorphisms (SNPs), indels, and genomic rearrangements within primer and probe sequences. This report demonstrates the value of prospectively collected genomic data for verifying CIDT targets. We utilized the genomes of 3,165 Salmonella isolates prospectively collected and sequenced in Australia. The sequences of Salmonella CIDT PCR gene targets (ttrA, spaO, and invA) were systematically interrogated to measure nucleotide dissimilarity. Analysis of 52 different serovars and 79 multilocus sequencing types (MLST) demonstrated dissimilarity within and between PCR gene targets ranging between 0 and 81.3 SNP/kbp (0 and 141 SNPs). The lowest average dissimilarity was observed in the ttrA target gene used by the Roche LightMix at 2.0 SNP/kbp (range, 0 to 46.7); however, entropy across the gene demonstrates that it may not be the most stable CIDT target. While debate continues over the benefits and pitfalls of replacing bacterial culture with molecular assays, the growing volumes of genomic surveillance data enable periodic regional reassessment and validation of CIDT targets against both prevalent and emerging serovars. If PCR systems are to become the primary screening and diagnostic tool for laboratory diagnosis of salmonellosis, ongoing monitoring of the genomic diversity in PCR target regions is warranted, as is the potential inclusion of two Salmonella PCR targets in frontline diagnostic systems.

Deep Sequencing of Urine Specimens Detects Two BK Polyomavirus Genotypes in a Hematopoietic Stem Cell Transplant Recipient.

BK polyomavirus (BKPyV) is an important pathogen in transplant recipients. We report four draft BKPyV genomes, three of BKPyV genotype I (subtype I-b2) (AUS-105, AUS-106, and AUS-108) and one of genotype II (AUS-107). These draft genomes were identified in longitudinal urine samples collected from a single hematopoietic stem cell transplant recipient.

Complete Genome Sequences, Derived by Next-Generation Sequencing, of JC Polyomavirus Strains Isolated from Vietnamese Renal Transplant Recipients.

JC polyomavirus (JCPyV) may cause clinical syndromes such as progressive multifocal leukoencephalopathy in immunocompromised patients. Here, we report seven complete genome sequences of JCPyV genotype 7A, generated directly from urine samples from Vietnamese renal transplant recipients by using rolling-circle amplification and next-generation sequencing.