Characterization of Acute HCV Infection and Transmission Networks in People Who Currently Inject Drugs in Catalonia: Usefulness of Dried Blood Spots.

BACKGROUND AND AIMS: Accurate identification of recent HCV infections is critical for tracing the extent and mechanisms of ongoing transmission. We aimed to validate dried blood spot (DBS) samples for the assessment of Hepatitis C virus (HCV) genetic diversity and to determine epidemiological parameters including incidence, determinants of acute infection, and phylogenetic clustering in people who inject drugs (PWID). APPROACH AND RESULTS: HCV nonstructural protein 5B next-generation sequencing was performed from plasma and/or DBS in 220 viremic PWID from the HepCdetect II study. No significant differences were found in consensus sequences or Shannon entropy (SE) intrahost diversity estimate between paired plasma/DBS specimens. SE values were used to identify acute infections with 93.3% sensitivity (95% CI, 0.81-1.06) and 95.0% specificity (95% CI, 0.88-1.02) in a set of well-defined controls. An acute HCV infection (either primary infection or reinfection) was detected in 13.5% of viremic participants and was associated with age ≤30 years (OR, 8.09), injecting less than daily (OR, 4.35), ≤5 years of injected drug use (OR, 3.43), sharing cocaine snorting straws (OR, 2.89), and being unaware of their HCV status (OR, 3.62). Annualized HCV incidence was estimated between 31 and 59/100 person-years. On phylogenetic analysis, 46.8% of viremic cases were part of a transmission pair or cluster; age ≤30 years (OR, 6.16), acute infection (OR, 5.73), and infection with subtype 1a (OR, 4.78) were independently associated with this condition. CONCLUSIONS: The results obtained from plasma and DBS characterize PWID with acute infection and those involved in ongoing HCV transmission and allow estimating incidence from cross-sectional data. This information is critical for the design and assessment of targeted harm reduction programs and test-and-treat interventions and to facilitate monitoring of HCV elimination in this key population.

Variable routes to genomic and host adaptation among coronaviruses.

Natural selection operating on the genomes of viral pathogens in different host species strongly contributes to adaptation facilitating host colonization. Here, we analyse, quantify and compare viral adaptation in genomic sequence data derived from seven zoonotic events in the Coronaviridae family among primary, intermediate and human hosts. Rates of nonsynonymous (dN ) and synonymous (dS ) changes on specific amino acid positions were quantified for each open reading frame (ORF). Purifying selection accounted for 77% of all sites under selection. Diversifying selection was most frequently observed in viruses infecting the primary hosts of each virus and predominantly occurred in the orf1ab genomic region. Within all four intermediate hosts, diversifying selection on the spike gene was observed either solitarily or in combination with orf1ab and other genes. Consistent with previous evidence, pervasive diversifying selection on coronavirus spike genes corroborates the role this protein plays in host cellular entry, adaptation to new hosts and evasion of host cellular immune responses. Structural modelling of spike proteins identified a significantly higher proportion of sites for SARS-CoV-2 under positive selection in close proximity to sites of glycosylation relative to the other coronaviruses. Among human coronaviruses, there was a significant inverse correlation between the number of sites under positive selection and the estimated years since the virus was introduced into the human population. Abundant diversifying selection observed in SARS-CoV-2 suggests the virus remains in the adaptive phase of the host switch, typical of recent host switches. A mechanistic understanding of where, when and how genomic adaptation occurs in coronaviruses following a host shift is crucial for vaccine design, public health responses and predicting future pandemics.

Differentiation of acute from chronic hepatitis C virus infection by nonstructural 5B deep sequencing: a population-level tool for incidence estimation.

UNLABELLED: The ability to classify acute versus chronic hepatitis C virus (HCV) infections at the time of diagnosis is desirable to improve the quality of surveillance information. The aim of this study was to differentiate acute from chronic HCV infections utilizing deep sequencing. HCV nonstructural 5B (NS5B) amplicons (n = 94) were generated from 77 individuals (13 acute and 64 chronic HCV infections) in British Columbia, Canada, with documented seroconversion time frames. Amplicons were deep sequenced and HCV genomic diversity was measured by Shannon entropy (SE) and a single nucleotide variant (SNV) analysis. The relationship between each diversity measure and the estimated days since infection was assessed using linear mixed models, and the ability of each diversity measure to differentiate acute from chronic infections was assessed using generalized estimating equations. Both SE and the SNV diversity measures were significantly different for acute versus chronic infections (P < 0.009). NS5B nucleotide diversity continued to increase for at least 3 years postinfection. Among individuals with the least uncertainty with regard to duration of infection (n = 39), the area under the receiver operating characteristic curve (AUROC) was high (0.96 for SE; 0.98 for SNV). Although the AUROCs were lower (0.86 for SE; 0.80 for SNV) when data for all individuals were included, they remain sufficiently high for epidemiological purposes. Synonymous mutations were the primary discriminatory variable accounting for over 78% of the measured genetic diversity. CONCLUSIONS: NS5B sequence diversity assessed by deep sequencing can differentiate acute from chronic HCV infections and, with further validation, could become a powerful population-level surveillance tool for incidence estimation.

Genomic Analysis of a Serotype 5 Streptococcus pneumoniae Outbreak in British Columbia, Canada, 2005-2009.

Background. Streptococcus pneumoniae can cause a wide spectrum of disease, including invasive pneumococcal disease (IPD). From 2005 to 2009 an outbreak of IPD occurred in Western Canada, caused by a S. pneumoniae strain with multilocus sequence type (MLST) 289 and serotype 5. We sought to investigate the incidence of IPD due to this S. pneumoniae strain and to characterize the outbreak in British Columbia using whole-genome sequencing. Methods. IPD was defined according to Public Health Agency of Canada guidelines. Two isolates representing the beginning and end of the outbreak were whole-genome sequenced. The sequences were analyzed for single nucleotide variants (SNVs) and putative genomic islands. Results. The peak of the outbreak in British Columbia was in 2006, when 57% of invasive S. pneumoniae isolates were serotype 5. Comparison of two whole-genome sequenced strains showed only 10 SNVs between them. A 15.5 kb genomic island was identified in outbreak strains, allowing the design of a PCR assay to track the spread of the outbreak strain. Discussion. We show that the serotype 5 MLST 289 strain contains a distinguishing genomic island, which remained genetically consistent over time. Whole-genome sequencing holds great promise for real-time characterization of outbreaks in the future and may allow responses tailored to characteristics identified in the genome.

Genomic epidemiology of the first two waves of SARS-CoV-2 in Canada.

Tracking the emergence and spread of SARS-CoV-2 lineages using phylogenetics has proven critical to inform the timing and stringency of COVID-19 public health interventions. We investigated the effectiveness of international travel restrictions at reducing SARS-CoV-2 importations and transmission in Canada in the first two waves of 2020 and early 2021. Maximum likelihood phylogenetic trees were used to infer viruses' geographic origins, enabling identification of 2263 (95% confidence interval: 2159-2366) introductions, including 680 (658-703) Canadian sublineages, which are international introductions resulting in sampled Canadian descendants, and 1582 (1501-1663) singletons, introductions with no sampled descendants. Of the sublineages seeded during the first wave, 49% (46-52%) originated from the USA and were primarily introduced into Quebec (39%) and Ontario (36%), while in the second wave, the USA was still the predominant source (43%), alongside a larger contribution from India (16%) and the UK (7%). Following implementation of restrictions on the entry of foreign nationals on 21 March 2020, importations declined from 58.5 (50.4-66.5) sublineages per week to 10.3-fold (8.3-15.0) lower within 4 weeks. Despite the drastic reduction in viral importations following travel restrictions, newly seeded sublineages in summer and fall 2020 contributed to the persistence of COVID-19 cases in the second wave, highlighting the importance of sustained interventions to reduce transmission. Importations rebounded further in November, bringing newly emergent variants of concern (VOCs). By the end of February 2021, there had been an estimated 30 (19-41) B.1.1.7 sublineages imported into Canada, which increasingly displaced previously circulating sublineages by the end of the second wave.Although viral importations are nearly inevitable when global prevalence is high, with fewer importations there are fewer opportunities for novel variants to spark outbreaks or outcompete previously circulating lineages.

Impact of SARS-CoV-2 lockdown on expansion of HIV transmission clusters among key populations: A retrospective phylogenetic analysis.

Background: Public health measures designed to reduce SARS-CoV-2 transmission led to reduced access to care and prevention services for people living with or at risk of acquiring HIV, particularly during the initial introduction of extensive restrictions. This reduction in access may have contributed to increases in HIV transmission not outweighed by decreases in transmission occurring as a result of reduced contact rates promoted by the same public health measures. Methods: We synthesize available province-wide HIV data in British Columbia, Canada, together with public mobility data to phylogenetically investigate the early impacts of SARS-CoV-2 on HIV transmission. Cluster growth, coalescent branching events and lineage-level diversification rates were assessed in "pre-lockdown" (January 22-March 21, 2020), "lockdown" (March 22-May 20, 2020) and "post-lockdown" (May 21-July 19, 2020) to facilitate comparison of transmission trends across key populations. Findings: Results reveal increased HIV transmission in a limited number of clusters in association with reduced access to health services during the initial introduction of SARS-CoV-2-related restrictions. In particular, clusters associated with people who inject drugs (PWID) show rapid growth, extensive branching events in phylogenetic trees during and following the lockdown period, and elevated median change in individuals' viral diversification rates during lockdown compared to clusters associated with men who have sex with men (MSM), consistent with increased transmission rates between PWID. Interpretation: Increased vigilance and innovative targeted solutions are critical to offset potential negative impacts of SARS-CoV-2 or future pandemic-related restrictions on HIV epidemic dynamics. Funding: Funding sources include Genome Canada and Genome BC, the Public Health Agency of Canada, the BC Centre for Excellence in HIV/AIDS, and the Canadian Institutes of Health Research Coronavirus Rapid Response Programme. Student funding includes a NSERC CREATE scholarship and a Canadian Institutes of Health Research graduate fellowship.

Intra-host evolutionary dynamics of the hepatitis C virus among people who inject drugs.

Most individuals chronically infected with hepatitis C virus (HCV) are asymptomatic during the initial stages of infection and therefore the precise timing of infection is often unknown. Retrospective estimation of infection duration would improve existing surveillance data and help guide treatment. While intra-host viral diversity quantifications such as Shannon entropy have previously been utilized for estimating duration of infection, these studies characterize the viral population from only a relatively short segment of the HCV genome. In this study intra-host diversities were examined across the HCV genome in order to identify the region most reflective of time and the degree to which these estimates are influenced by high-risk activities including those associated with HCV acquisition. Shannon diversities were calculated for all regions of HCV from 78 longitudinally sampled individuals with known seroconversion timeframes. While the region of the HCV genome most accurately reflecting time resided within the NS3 gene, the gene region with the highest capacity to differentiate acute from chronic infections was identified within the NS5b region. Multivariate models predicting duration of infection from viral diversity significantly improved upon incorporation of variables associated with recent public, unsupervised drug use. These results could assist the development of strategic population treatment guidelines for high-risk individuals infected with HCV and offer insights into variables associated with a likelihood of transmission.

Phylogenetic surveillance of travel-related Zika virus infections through whole-genome sequencing methods.

In 2018, the World Health Organization identified the Zika virus (ZIKV) as a pathogen that should be prioritized for public health research due to its epidemic potential. In this study, whole-genome sequencing (WGS) of travel-acquired ZIKV infections was used to examine the limitations of phylogenetic analysis. WGS and phylogenetic analysis were performed to investigate geographic clustering of samples from five Canadians with travel-acquired ZIKV infections and to assess the limitations of phylogenetic analysis of ZIKV sequences using a phylogenetic cluster approach. Genomic variability of ZIKV samples was assessed and for context, compared with hepatitis C virus (HCV) samples. Phylogenetic analysis confirmed the suspected region of ZIKV infection for one of five samples and one sample failed to cluster with sequences from its suspected country of infection. Travel-acquired ZIKV samples depicted low genomic variability relative to HCV samples. A floating patristic distance threshold classified all pre-2000 ZIKV sequences into separate clusters, while only Cambodian, Peruvian, Malaysian, and South Korean sequences were similarly classifiable. While phylogenetic analysis of ZIKV data can identify the broad geographical region of ZIKV infection, ZIKV's low genomic variability is likely to limit precise interpretations of phylogenetic analysis of the origins of travel-related cases.

A systematic, deep sequencing-based methodology for identification of mixed-genotype hepatitis C virus infections.

Hepatitis C virus (HCV) mixed genotype infections can affect treatment outcomes and may have implications for vaccine design and disease progression. Previous studies demonstrate 0-39% of high-risk, HCV-infected individuals harbor mixed genotypes however standardized, sensitive methods of detection are lacking. This study compared PCR amplicon, random primer (RP), and probe enrichment (PE)-based deep sequencing methods coupled with a custom sequence analysis pipeline to detect multiple HCV genotypes. Mixed infection cutoff values, based on HCV read depth and coverage, were identified using receiver operating characteristic curve analysis. The methodology was validated using artificially mixed genotype samples and then applied to two clinical trials of HCV treatment in high-risk individuals (ACTIVATE, 114 samples from 90 individuals; DARE-C II, 26 samples from 18 individuals) and a cohort of HIV/HCV co-infected individuals (Canadian Coinfection Cohort (CCC), 3 samples from 2 individuals with suspected mixed genotype infections). Amplification bias of genotype (G)1b, G2, G3 and G5 was observed in artificially mixed samples using the PCR method while no genotype bias was observed using RP and PE. RP and PE sequencing of 140 ACTIVATE and DARE-C II samples identified the following primary genotypes: 15% (n = 21) G1a, 76% (n = 106) G3, and 9% (n = 13) G2. Sequencing of ACTIVATE and DARE-C II demonstrated, on average, 2% and 1% of HCV reads mapping to a second genotype using RP and PE, respectively, however none passed the mixed infection cutoff criteria and phylogenetics confirmed no mixed infections. From CCC, one mixed infection was confirmed while the other was determined to be a recombinant genotype. This study underlines the risk for false identification of mixed HCV infections and stresses the need for standardized methods to improve prevalence estimates and to understand the impact of mixed infections for management and elimination of HCV.

Deep sequencing increases hepatitis C virus phylogenetic cluster detection compared to Sanger sequencing.

Effective surveillance and treatment strategies are required to control the hepatitis C virus (HCV) epidemic. Phylogenetic analyses are powerful tools for reconstructing the evolutionary history of viral outbreaks and identifying transmission clusters. These studies often rely on Sanger sequencing which typically generates a single consensus sequence for each infected individual. For rapidly mutating viruses such as HCV, consensus sequencing underestimates the complexity of the viral quasispecies population and could therefore generate different phylogenetic tree topologies. Although deep sequencing provides a more detailed quasispecies characterization, in-depth phylogenetic analyses are challenging due to dataset complexity and computational limitations. Here, we apply deep sequencing to a characterized population to assess its ability to identify phylogenetic clusters compared with consensus Sanger sequencing. For deep sequencing, a sample specific threshold determined by the 50th percentile of the patristic distance distribution for all variants within each individual was used to identify clusters. Among seven patristic distance thresholds tested for the Sanger sequence phylogeny ranging from 0.005-0.06, a threshold of 0.03 was found to provide the maximum balance between positive agreement (samples in a cluster) and negative agreement (samples not in a cluster) relative to the deep sequencing dataset. From 77 HCV seroconverters, 10 individuals were identified in phylogenetic clusters using both methods. Deep sequencing analysis identified an additional 4 individuals and excluded 8 other individuals relative to Sanger sequencing. The application of this deep sequencing approach could be a more effective tool to understand onward HCV transmission dynamics compared with Sanger sequencing, since the incorporation of minority sequence variants improves the discrimination of phylogenetically linked clusters.

Metagenomic Investigation of Plasma in Individuals with ME/CFS Highlights the Importance of Technical Controls to Elucidate Contamination and Batch Effects.

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a debilitating disease causing indefinite fatigue. ME/CFS has long been hypothesised to have an infectious cause; however, no specific infectious agent has been identified. We used metagenomics to analyse the RNA from plasma samples from 25 individuals with ME/CFS and compare their microbial content to technical controls as well as three control groups: individuals with alternatively diagnosed chronic Lyme syndrome (N = 13), systemic lupus erythematosus (N = 11), and healthy controls (N = 25). We found that the majority of sequencing reads were removed during host subtraction, thus there was very low microbial RNA content in the plasma. The effects of sample batching and contamination during sample processing proved to outweigh the effects of study group on microbial RNA content, as the few differences in bacterial or viral RNA abundance we did observe between study groups were most likely caused by contamination and batch effects. Our results highlight the importance of including negative controls in all metagenomic analyses, since there was considerable overlap between bacterial content identified in study samples and control samples. For example, Proteobacteria, Firmicutes, Actinobacteria, and Bacteriodes were found in both study samples and plasma-free negative controls. Many of the taxonomic groups we saw in our plasma-free negative control samples have previously been associated with diseases, including ME/CFS, demonstrating how incorrect conclusions may arise if controls are not used and batch effects not accounted for.

A molecular phylogenetics-based approach for identifying recent hepatitis C virus transmission events.

UNLABELLED: Improved surveillance methods are needed to better understand the current hepatitis C virus (HCV) disease burden and to monitor the impact of prevention and treatment interventions on HCV transmission dynamics. Sanger sequencing (HCV NS5B, HVR1 and Core-E1-HVR1) and phylogenetics were applied to samples from individuals diagnosed with HCV in British Columbia, Canada in 2011. This included individuals with two or three sequential samples collected <1 year apart. Patristic distances between sequential samples were used to set cutoffs to identify recent transmission clusters. Factors associated with transmission clustering were analyzed using logistic regression. From 618 individuals, 646 sequences were obtained. Depending on the cutoff used, 63 (10%) to 92 (15%) unique individuals were identified within transmission clusters of predicted recent origin. Clustered individuals were more likely to be <40 years old (Adjusted Odds Ratio (AOR) 2.12, 95% CI 1.21-3.73), infected with genotype 1a (AOR 6.60, 95% CI 1.98-41.0), and to be seroconverters with estimated infection duration of <1 year (AOR 3.13, 95% CI 1.29-7.36) or >1 year (AOR 2.19, 95% CI 1.22-3.97). CONCLUSION: Systematic application of molecular phylogenetics may be used to enhance traditional surveillance methods through identification of recent transmission clusters.

Carriage of methicillin-resistant Staphylococcus aureus by wild urban Norway rats (Rattus norvegicus).

Methicillin-resistant Staphylococcus aureus (MRSA) is an important cause of multi-drug-resistant infections in people, particularly indigent populations. MRSA can be transmitted between people and domestic animals, but the potential for transmission between people and commensal pests, particularly rodents, had not been investigated. The objective of this study was to identify the presence and characterize the ecology of MRSA in rats (Rattus spp.) from in an impoverished, inner-city neighborhood. Oropharyngeal swabs were collected from rats trapped in 33 city blocks and one location within the adjacent port. Bacterial culture was performed and MRSA isolates were characterized using a variety of methods, including whole-genome sequencing (WGS). The ecology of MRSA in rats was described using phylogenetic analysis, geospatial analysis, and generalized linear mixed models. MRSA was identified 22 of 637 (3.5%) rats tested, although prevalence varied from 0 - 50% among blocks. Isolates belonged to 4 clusters according to WGS, with the largest cluster (n = 10) containing isolates that were genetically indistinguishable from community-acquired USA300 MRSA strains isolated from people within the study area. MRSA strains demonstrated both geographic clustering and dispersion. The odds of an individual rat carrying MRSA increased with increased body fat (OR = 2.53, 95% CI = 1.33-4.82), and in the winter (OR = 5.29, 95% CI = 1.04-26.85) and spring (OR = 5.50, 95% CI = 1.10-27.58) compared to the fall. The results show that urban rats carried the same MRSA lineages occurring in local human and/or animal populations, supporting recent transmission from external sources. MRSA carriage was influenced by season, most likely as a result of temporal variation in rat behavior and rat-human interactions.

Metagenomics for pathogen detection in public health.

Traditional pathogen detection methods in public health infectious disease surveillance rely upon the identification of agents that are already known to be associated with a particular clinical syndrome. The emerging field of metagenomics has the potential to revolutionize pathogen detection in public health laboratories by allowing the simultaneous detection of all microorganisms in a clinical sample, without a priori knowledge of their identities, through the use of next-generation DNA sequencing. A single metagenomics analysis has the potential to detect rare and novel pathogens, and to uncover the role of dysbiotic microbiomes in infectious and chronic human disease. Making use of advances in sequencing platforms and bioinformatics tools, recent studies have shown that metagenomics can even determine the whole-genome sequences of pathogens, allowing inferences about antibiotic resistance, virulence, evolution and transmission to be made. We are entering an era in which more novel infectious diseases will be identified through metagenomics-based methods than through traditional laboratory methods. The impetus is now on public health laboratories to integrate metagenomics techniques into their diagnostic arsenals.