Quantifying influenza virus diversity and transmission in humans

Quantifying the impact of vaccination on transmission and diversity of influenza A variants in pigs

Global evolutionary dynamics of influenza A virus (IAV) are fundamentally driven by the extent of virus diversity generated, transmitted, and shaped in individual hosts. How vaccination affects the degree of IAV genetic diversity that can be transmitted and expanded in pigs is unknown. To evaluate the effect of vaccination on the transmission of genetically distinct IAV variants and their diversity after transmission in pigs, we examined the whole genome of IAV recovered from the nasal cavities of pigs vaccinated with different influenza immunization regimens after being infected simultaneously by H1N1 and H3N2 IAVs using a seeder pig model. We found that the seeder pigs harbored more diversified virus populations than the contact pigs. Among contact pigs, H3N2 and H1N1 viruses recovered from pigs vaccinated with a single dose of an unmatched modified live vaccine generally accumulated more extensive genetic mutations than non-vaccinated pigs. Furthermore, the non-sterilizing immunity elicited by the single-dose-modified live vaccine may have exerted positive selection on H1 antigenic regions as we detected significantly higher nonsynonymous but lower synonymous evolutionary rates in H1 antigenic regions than non-antigenic regions. In addition, we observed that the vaccinated pigs shared significantly less proportion of H3N2 variants with seeder pigs than unvaccinated pigs. These results indicated that vaccination might reduce the impact of transmitted influenza variants on the overall diversity of IAV populations harbored in recipient pigs and that within-host genetic selection of IAV is more likely to occur in pigs vaccinated with improperly matched vaccines.IMPORTANCEUnderstanding how vaccination shapes the diversity of influenza variants that transmit and propagate among pigs is essential for designing effective IAV surveillance and control programs. Current knowledge about the transmission of IAV variants has primarily been explored in humans during natural infection. However, how immunity elicited by improperly matched vaccines affects the degree of IAV genetic diversity that can be transmitted and expanded in pigs at the whole-genome level is unknown. We analyzed IAV sequences from samples collected daily from experimentally infected pigs vaccinated with various protocols in a field-represented IAV co-infection model. We found that vaccine-induced non-sterilizing immunity might promote genetic variation on the IAV genome and drive positive selection at antigenic sites during infection. In addition, a smaller proportion of H3N2 viral variants were shared between seeder pigs and vaccinated pigs, suggesting the influence of vaccination on shaping the virus genomic diversity in recipient pigs during the transmission events.

Identification of potential antiviral compounds from Egyptian marine algae against influenza A virus

Influenza is a contagious viral infection of the respiratory tract, affecting nearly 10% of the world's population, each year. The aim of this study was to extract and identify antiviral compounds against the influenza-A virus (H1N1) from different species of Egyptian marine algae. Three samples of marine macroalgae species were extracted and the antiviral activity of the extracts were tested on Madin Darby Canine Kidney cells. The bioactive compounds present in the most active fractions were identified using gas chromatography-mass spectrometry (GC-MS), then the binding potentials of the identified compounds were examined towards neuraminidase (NA) of the influenza-A virus using molecular docking. The methanolic extract of Sargassum aquifolium showed promising in-vitro antiviral activity with a selectivity index (SI) value of 101. The GC-MS analysis showed twelve compounds and the molecular docking analysis found that tetradecanoic acid showed the strongest binding affinities towards the NA enzyme.

Spillover: Mechanisms, Genetic Barriers, and the Role of Reservoirs in Emerging Pathogens

Viral spillover represents the transmission of pathogen viruses from one species to another that can give rise to an outbreak. It is a critical concept that has gained increasing attention, particularly after the SARS-CoV-2 pandemic. However, the term is often used inaccurately to describe events that do not meet the true definition of spillover. This review aims to clarify the proper use of the term and provides a detailed analysis of the mechanisms driving zoonotic spillover, with a focus on the genetic and environmental factors that enable viruses to adapt to new hosts. Key topics include viral genetic variability in reservoir species, biological barriers to cross-species transmission, and the factors that influence viral adaptation and spread in novel hosts. The review also examines the role of evolutionary processes such as mutation and epistasis, alongside ecological conditions that facilitate the emergence of new pathogens. Ultimately, it underscores the need for more accurate predictive models and improved surveillance to better anticipate and mitigate future spillover events.

Transmission Bottleneck Size Estimation from De Novo Viral Genetic Variation

Sequencing of viral infections has become increasingly common over the last decade. Deep sequencing data in particular have proven useful in characterizing the roles that genetic drift and natural selection play in shaping within-host viral populations. They have also been used to estimate transmission bottleneck sizes from identified donor-recipient pairs. These bottleneck sizes quantify the number of viral particles that establish genetic lineages in the recipient host and are important to estimate due to their impact on viral evolution. Current approaches for estimating bottleneck sizes exclusively consider the subset of viral sites that are observed as polymorphic in the donor individual. However, these approaches have the potential to substantially underestimate true transmission bottleneck sizes. Here, we present a new statistical approach for instead estimating bottleneck sizes using patterns of viral genetic variation that arise de novo within a recipient individual. Specifically, our approach makes use of the number of clonal viral variants observed in a transmission pair, defined as the number of viral sites that are monomorphic in both the donor and the recipient but carry different alleles. We first test our approach on a simulated dataset and then apply it to both influenza A virus sequence data and SARS-CoV-2 sequence data from identified transmission pairs. Our results confirm the existence of extremely tight transmission bottlenecks for these 2 respiratory viruses.

The hidden risk of microplastic-associated pathogens in aquatic environments

Increasing studies of plastisphere have raised public concern about microplastics (MPs) as vectors for pathogens, especially in aquatic environments. However, the extent to which pathogens affect human health through MPs remains unclear, as controversies persist regarding the distinct pathogen colonization on MPs as well as the transmission routes and infection probability of MP-associated pathogens from water to humans. In this review, we critically discuss whether and how pathogens approach humans via MPs, shedding light on the potential health risks involved. Drawing on cutting-edge multidisciplinary research, we show that some MPs may facilitate the growth and long-range transmission of specific pathogens in aquatic environments, ultimately increasing the risk of infection in humans. We identify MP- and pathogen-rich settings, such as wastewater treatment plants, aquaculture farms, and swimming pools, as possible sites for human exposure to MP-associated pathogens. This review emphasizes the need for further research and targeted interventions to better understand and mitigate the potential health risks associated with MP-mediated pathogen transmission.

Transmission bottleneck size estimation from de novo viral genetic variation

Sequencing of viral infections has become increasingly common over the last decade. Deep sequencing data in particular have proven useful in characterizing the roles that genetic drift and natural selection play in shaping within-host viral populations. They have also been used to estimate transmission bottleneck sizes from identified donor-recipient pairs. These bottleneck sizes quantify the number of viral particles that establish genetic lineages in the recipient host and are important to estimate due to their impact on viral evolution. Current approaches for estimating bottleneck sizes exclusively consider the subset of viral sites that are observed as polymorphic in the donor individual. However, allele frequencies can change dramatically over the course of an individual's infection, such that sites that are polymorphic in the donor at the time of transmission may not be polymorphic in the donor at the time of sampling and allele frequencies at donor-polymorphic sites may change dramatically over the course of a recipient's infection. Because of this, transmission bottleneck sizes estimated using allele frequencies observed at a donor's polymorphic sites may be considerable underestimates of true bottleneck sizes. Here, we present a new statistical approach for instead estimating bottleneck sizes using patterns of viral genetic variation that arose de novo within a recipient individual. Specifically, our approach makes use of the number of clonal viral variants observed in a transmission pair, defined as the number of viral sites that are monomorphic in both the donor and the recipient but carry different alleles. We first test our approach on a simulated dataset and then apply it to both influenza A virus sequence data and SARS-CoV-2 sequence data from identified transmission pairs. Our results confirm the existence of extremely tight transmission bottlenecks for these two respiratory viruses, using an approach that does not tend to underestimate transmission bottleneck sizes.

Vaccination for seasonal flu, pneumococcal infection, and SARS-CoV-2 in patients with solid tumors: recommendations of the Associazione Italiana di Oncologia Medica (AIOM)

Patients with cancer have a well-known and higher risk of vaccine-preventable diseases (VPDs). VPDs may cause severe complications in this setting due to the immune system impairment, malnutrition and oncological treatments. Despite this evidence, vaccination rates are inadequate. The Italian Association of Medical Oncology (AIOM) has been involved in vaccination awareness since 2014. Based on a careful review of the available data about the immunogenicity, effectiveness and safety of flu, pneumococcal and anti-SARS-CoV-2 vaccines, we report the recommendations of the Associazione Italiana di Oncologia Medica about these vaccinations in adult patients with solid tumors. AIOM recommends comprehensive education on the issue of VPDs. We believe that a multidisciplinary care model may improve the vaccination coverage in immunocompromised patients. Continued surveillance, implementation of preventive practices and future well-designed immunological prospective studies are essential for a better management of our patients with cancer.

High-throughput droplet-based analysis of influenza A virus genetic reassortment by single-virus RNA sequencing

The segmented RNA genome of influenza A viruses (IAVs) enables viral evolution through genetic reassortment after multiple IAVs coinfect the same cell, leading to viruses harboring combinations of eight genomic segments from distinct parental viruses. Existing data indicate that reassortant genotypes are not equiprobable; however, the low throughput of available virology techniques does not allow quantitative analysis. Here, we have developed a high-throughput single-cell droplet microfluidic system allowing encapsulation of IAV-infected cells, each cell being infected by a single progeny virion resulting from a coinfection process. Customized barcoded primers for targeted viral RNA sequencing enabled the analysis of 18,422 viral genotypes resulting from coinfection with two circulating human H1N1pdm09 and H3N2 IAVs. Results were highly reproducible, confirmed that genetic reassortment is far from random, and allowed accurate quantification of reassortants including rare events. In total, 159 out of the 254 possible reassortant genotypes were observed but with widely varied prevalence (from 0.038 to 8.45%). In cells where eight segments were detected, all 112 possible pairwise combinations of segments were observed. The inclusion of data from single cells where less than eight segments were detected allowed analysis of pairwise cosegregation between segments with very high confidence. Direct coupling analysis accurately predicted the fraction of pairwise segments and full genotypes. Overall, our results indicate that a large proportion of reassortant genotypes can emerge upon coinfection and be detected over a wide range of frequencies, highlighting the power of our tool for systematic and exhaustive monitoring of the reassortment potential of IAVs.

Lipopolysaccharide aggravates canine influenza a (H3N2) virus infection and lung damage via mTOR/autophagy in vivo and in vitro

Influenza A (H3N2) accounts for the majority of influenza worldwide and continues to challenge human health. Disturbance in the gut microbiota caused by many diseases leads to increased production of lipopolysaccharide (LPS), and LPS induces sepsis and conditions associated with local or systemic inflammation. However, to date, little attention has been paid to the potential impact of LPS on influenza A (H3N2) infection and the potential mechanism. Hence, in this study we used canine influenza A (H3N2) virus (CIV) as a model of influenza A virus to investigate the effect of low-dose of LPS on CIV replication and lung damage and explore the underlying mechanism in mice and A549 and HPAEpiC cells. The results showed that LPS (25 μg/kg) increased CIV infection and lung damage in mice, as indicated by pulmonary virus titer, viral NP levels, lung index, and pulmonary histopathology. LPS (1 μg/ml) also increased CIV replication in A549 cells as indicated by the above same parameters. Furthermore, low doses of LPS reduced CIV-induced p-mTOR protein expression and enhanced CIV-induced autophagy-related mRNA/protein expressions in vivo and in vitro. In addition, the use of the mTOR activator, MHY1485, reversed CIV-induced autophagy and CIV replication in A549 and HPAEpiC cells, respectively. siATG5 alleviated CIV replication exacerbated by LPS in the two lines. In conclusion, LPS aggravates CIV infection and lung damage via mTOR/autophagy.

Rapid transmission and tight bottlenecks constrain the evolution of highly transmissible SARS-CoV-2 variants

Transmission bottlenecks limit the spread of novel mutations and reduce the efficiency of selection along a transmission chain. While increased force of infection, receptor binding, or immune evasion may influence bottleneck size, the relationship between transmissibility and the transmission bottleneck is unclear. Here we compare the transmission bottleneck of non-VOC SARS-CoV-2 lineages to those of Alpha, Delta, and Omicron. We sequenced viruses from 168 individuals in 65 households. Most virus populations had 0-1 single nucleotide variants (iSNV). From 64 transmission pairs with detectable iSNV, we identify a per clade bottleneck of 1 (95% CI 1-1) for Alpha, Delta, and Omicron and 2 (95% CI 2-2) for non-VOC. These tight bottlenecks reflect the low diversity at the time of transmission, which may be more pronounced in rapidly transmissible variants. Tight bottlenecks will limit the development of highly mutated VOC in transmission chains, adding to the evidence that selection over prolonged infections may drive their evolution.

Rapid transmission and tight bottlenecks constrain the evolution of highly transmissible SARS-CoV-2 variants

Transmission bottlenecks limit the spread of novel mutations and reduce the efficiency of natural selection along a transmission chain. Many viruses exhibit tight bottlenecks, and studies of early SARS-CoV-2 lineages identified a bottleneck of 1-3 infectious virions. While increased force of infection, host receptor binding, or immune evasion may influence bottleneck size, the relationship between transmissibility and the transmission bottleneck is unclear. Here, we compare the transmission bottleneck of non-variant-of-concern (non-VOC) SARS-CoV-2 lineages to those of the Alpha, Delta, and Omicron variants. We sequenced viruses from 168 individuals in 65 multiply infected households in duplicate to high depth of coverage. In 110 specimens collected close to the time of transmission, within-host diversity was extremely low. At a 2% frequency threshold, 51% had no intrahost single nucleotide variants (iSNV), and 42% had 1-2 iSNV. In 64 possible transmission pairs with detectable iSNV, we identified a bottleneck of 1 infectious virion (95% CI 1-1) for Alpha, Delta, and Omicron lineages and 2 (95% CI 2-2) in non-VOC lineages. The latter was driven by a single iSNV shared in one non-VOC household. The tight transmission bottleneck in SARS-CoV-2 is due to low genetic diversity at the time of transmission, a relationship that may be more pronounced in rapidly transmissible variants. The tight bottlenecks identified here will limit the development of highly mutated VOC in typical transmission chains, adding to the evidence that selection over prolonged infections in immunocompromised patients may drive their evolution.

Performance Evaluation of TaqMan SARS-CoV-2, Flu A/B, RSV RT-PCR Multiplex Assay for the Detection of Respiratory Viruses

Purpose

To detect and differentiate co-infection with influenza and respiratory syncytial virus during the COVID pandemic, a rapid method that can detect multiple pathogens in a single test is a significant diagnostic advance to analyze the outcomes and clinical implications of co-infection. Therefore, we validated and evaluated the performance characteristics of TaqMan SARS-CoV-2, Flu A/B, RSV RT-PCR multiplex assay for the detection of SARS-CoV-2, Flu A/B, and RSV using nasopharyngeal and saliva samples.

Materials and Methods

The method validation was performed by using culture fluids of Influenza A virus (H3N2) (A/Wisconsin/67/2005), Influenza B virus (B/Virginia/ATCC4/2009), RSV A2 cpts-248, SARS-CoV-2 (USA-WA1/2020) and quantitative RNA controls of Influenza A virus (H1N1) strain A/PR/8/34 (VR-95DQ), RSV A2 (VR-1540DQ) and SARS-CoV-2 (MN908947.3 Wuhan-Hu-1) from ATCC and Zeptometrix, NY, USA. A total of 110 nasopharyngeal specimens and 70 saliva samples were used for the SARS-CoV-2 detection, and a total of 70 nasopharyngeal specimens were used for Influenza and RSV detection. Total RNA was extracted from all the samples and multiplex PCR was performed using TaqMan SARS-CoV-2, Flu A/B, RSV RT-PCR multiplex assay. The assay was used for SARS-CoV-2 variant (B.1.1.7_601443, B.1.617.1_1662307, P.1_792683, B.1.351_678597, B.1.1.529/BA.1).

Results

Validation controls showed accurate and precise results. The correlation study found the accuracy of 96.38 to 100% (95% CI) in nasopharyngeal and 94.87 to 100% (95% CI) in saliva for SARS-CoV-2 and 91.1 to 100% (95% CI) for both Influenza A/B and RSV. The diagnostic efficiency of this assay was not affected by SARS-CoV-2 variant, including Omicron.

Conclusion

The TaqMan SARS-CoV-2, Flu A/B, RSV RT-PCR multiplex assay is a rapid method to detect and differentiate SAR-CoV-2, Flu A and B, and RSV in nasopharyngeal and saliva samples. It has a significant role in the diagnosis and management of respiratory illnesses and the clinical implications of co-infection.

COVID-19 infection and transmission includes complex sequence diversity

SARS-CoV-2 whole genome sequencing has played an important role in documenting the emergence of polymorphisms in the viral genome and its continuing evolution during the COVID-19 pandemic. Here we present data from over 360 patients to characterize the complex sequence diversity of individual infections identified during multiple variant surges (e.g., Alpha and Delta). Across our survey, we observed significantly increasing SARS-CoV-2 sequence diversity during the pandemic and frequent occurrence of multiple biallelic sequence polymorphisms in all infections. This sequence polymorphism shows that SARS-CoV-2 infections are heterogeneous mixtures. Convention for reporting microbial pathogens guides investigators to report a majority consensus sequence. In our study, we found that this approach would under-report sequence variation in all samples tested. As we find that this sequence heterogeneity is efficiently transmitted from donors to recipients, our findings illustrate that infection complexity must be monitored and reported more completely to understand SARS-CoV-2 infection and transmission dynamics. Many of the nucleotide changes that would not be reported in a majority consensus sequence have now been observed as lineage defining SNPs in Omicron BA.1 and/or BA.2 variants. This suggests that minority alleles in earlier SARS-CoV-2 infections may play an important role in the continuing evolution of new variants of concern.

Next-generation T cell-activating vaccination increases influenza virus mutation prevalence

To determine the potential for viral adaptation to T cell responses, we probed the full influenza virus genome by next-generation sequencing directly ex vivo from infected mice, in the context of an experimental T cell-based vaccine, an H5N1-based viral vectored vaccinia vaccine Wyeth/IL-15/5Flu, versus the current standard-of-care, seasonal inactivated influenza vaccine (IIV) and unvaccinated conditions. Wyeth/IL-15/5Flu vaccination was coincident with increased mutation incidence and frequency across the influenza genome; however, mutations were not enriched within T cell epitope regions, but high allele frequency mutations within conserved hemagglutinin stem regions and PB2 mammalian adaptive mutations arose. Depletion of CD4⁺ and CD8⁺ T cell subsets led to reduced frequency of mutants in vaccinated mice; therefore, vaccine-mediated T cell responses were important drivers of virus diversification. Our findings suggest that Wyeth/IL-15/5Flu does not generate T cell escape mutants but increases stochastic events for virus adaptation by stringent bottlenecks.

Swine H1N1 Influenza Virus Variants with Enhanced Polymerase Activity and HA Stability Promote Airborne Transmission in Ferrets

Diverse IAVs circulate in animals, yet few acquire the viral traits needed to start a human pandemic. A stabilized HA and mammalian-adapted polymerase have been shown to promote the adaptation of IAVs to humans and ferrets (the gold-standard model for IAV replication, pathogenicity, and transmissibility).

Temporal and Gene Reassortment Analysis of Influenza C Virus Outbreaks in Hong Kong, SAR, China

From 2014 to week 07/2020 the Centre for Health Protection in Hong Kong conducted screening for influenza C virus (ICV). A retrospective analysis of ICV detections to week 26/2019 revealed persistent low-level circulation with outbreaks occurring biennially in the winters of 2015 to 2016 and 2017 to 2018 (R. S. Daniels et al., J Virol 94:e01051-20, 2020, https://doi.org/10.1128/JVI.01051-20). Here, we report on an outbreak occurring in 2019 to 2020, reinforcing the observation of biennial seasonality in Hong Kong. All three outbreaks occurred in similar time frames, were subsequently dwarfed by seasonal epidemics of influenza types A and B, and were caused by similar proportions of C/Kanagawa/1/76 (K)-lineage and C/São Paulo/378/82 S1- and S2-sublineage viruses. Ongoing genetic drift was observed in all genes, with some evidence of amino acid substitution in the hemagglutinin-esterase-fusion (HEF) glycoprotein possibly associated with antigenic drift. A total of 61 ICV genomes covering the three outbreaks were analyzed for reassortment, and 9 different reassortant constellations were identified, 1 K-lineage, 4 S1-sublineage, and 4 S2-sublineage, with 6 of these being identified first in the 2019-1920 outbreak (2 S2-lineage and 4 S1-lineage). The roles that virus interference/enhancement, ICV persistent infection, genome evolution, and reassortment might play in the observed seasonality of ICV in Hong Kong are discussed. IMPORTANCE Influenza C virus (ICV) infection of humans is common, with the great majority of people being infected during childhood, though reinfection can occur throughout life. While infection normally results in "cold-like" symptoms, severe disease cases have been reported in recent years. However, knowledge of ICV is limited due to poor systematic surveillance and an inability to propagate the virus in large amounts in the laboratory. Following recent systematic surveillance in Hong Kong SAR, China, and direct ICV gene sequencing from clinical specimens, a 2-year cycle of disease outbreaks (epidemics) has been identified, with gene mixing playing a significant role in ICV evolution. Studies like those reported here are key to developing an understanding of the impact of influenza C virus infection in humans, notably where comorbidities exist and severe respiratory disease can develop.

Inferring the distribution of fitness effects in patient-sampled and experimental virus populations: two case studies

We here propose an analysis pipeline for inferring the distribution of fitness effects (DFE) from either patient-sampled or experimentally-evolved viral populations, that explicitly accounts for non-Wright-Fisher and non-equilibrium population dynamics inherent to pathogens. We examine the performance of this approach via extensive power and performance analyses, and highlight two illustrative applications - one from an experimentally-passaged RNA virus, and the other from a clinically-sampled DNA virus. Finally, we discuss how such DFE inference may shed light on major research questions in virus evolution, ranging from a quantification of the population genetic processes governing genome size, to the role of Hill-Robertson interference in dictating adaptive outcomes, to the potential design of novel therapeutic approaches to eradicate within-patient viral populations via induced mutational meltdown.

Viral infection and transmission in a large, well-traced outbreak caused by the SARS-CoV-2 Delta variant

The SARS-CoV-2 Delta variant has spread rapidly worldwide. To provide data on its virological profile, we here report the first local transmission of Delta in mainland China. All 167 infections could be traced back to the first index case. Daily sequential PCR testing of quarantined individuals indicated that the viral loads of Delta infections, when they first become PCR-positive, were on average ~1000 times greater compared to lineage A/B infections during the first epidemic wave in China in early 2020, suggesting potentially faster viral replication and greater infectiousness of Delta during early infection. The estimated transmission bottleneck size of the Delta variant was generally narrow, with 1-3 virions in 29 donor-recipient transmission pairs. However, the transmission of minor iSNVs resulted in at least 3 of the 34 substitutions that were identified in the outbreak, highlighting the contribution of intra-host variants to population-level viral diversity during rapid spread.

Viral infection and transmission in a large, well-traced outbreak caused by the SARS-CoV-2 Delta variant

The SARS-CoV-2 Delta variant has spread rapidly worldwide. To provide data on its virological profile, we here report the first local transmission of Delta in mainland China. All 167 infections could be traced back to the first index case. Daily sequential PCR testing of quarantined individuals indicated that the viral loads of Delta infections, when they first become PCR-positive, were on average ~1000 times greater compared to lineage A/B infections during the first epidemic wave in China in early 2020, suggesting potentially faster viral replication and greater infectiousness of Delta during early infection. The estimated transmission bottleneck size of the Delta variant was generally narrow, with 1-3 virions in 29 donor-recipient transmission pairs. However, the transmission of minor iSNVs resulted in at least 3 of the 34 substitutions that were identified in the outbreak, highlighting the contribution of intra-host variants to population-level viral diversity during rapid spread.

Viral infection and transmission in a large, well-traced outbreak caused by the SARS-CoV-2 Delta variant

The SARS-CoV-2 Delta variant has spread rapidly worldwide. To provide data on its virological profile, we here report the first local transmission of Delta in mainland China. All 167 infections could be traced back to the first index case. Daily sequential PCR testing of quarantined individuals indicated that the viral loads of Delta infections, when they first become PCR-positive, were on average ~1000 times greater compared to lineage A/B infections during the first epidemic wave in China in early 2020, suggesting potentially faster viral replication and greater infectiousness of Delta during early infection. The estimated transmission bottleneck size of the Delta variant was generally narrow, with 1-3 virions in 29 donor-recipient transmission pairs. However, the transmission of minor iSNVs resulted in at least 3 of the 34 substitutions that were identified in the outbreak, highlighting the contribution of intra-host variants to population-level viral diversity during rapid spread.

Viral infection and transmission in a large, well-traced outbreak caused by the SARS-CoV-2 Delta variant

The SARS-CoV-2 Delta variant has spread rapidly worldwide. To provide data on its virological profile, we here report the first local transmission of Delta in mainland China. All 167 infections could be traced back to the first index case. Daily sequential PCR testing of quarantined individuals indicated that the viral loads of Delta infections, when they first become PCR-positive, were on average ~1000 times greater compared to lineage A/B infections during the first epidemic wave in China in early 2020, suggesting potentially faster viral replication and greater infectiousness of Delta during early infection. The estimated transmission bottleneck size of the Delta variant was generally narrow, with 1-3 virions in 29 donor-recipient transmission pairs. However, the transmission of minor iSNVs resulted in at least 3 of the 34 substitutions that were identified in the outbreak, highlighting the contribution of intra-host variants to population-level viral diversity during rapid spread.

DeepFlu: a deep learning approach for forecasting symptomatic influenza A infection based on pre-exposure gene expression

BACKGROUND AND OBJECTIVE

Not everyone gets sick after an exposure to influenza A viruses (IAV). Although KLRD1 has been identified as a potential biomarker for influenza susceptibility, it remains unclear whether forecasting symptomatic flu infection based on pre-exposure host gene expression might be possible.

METHOD

To examine this hypothesis, we developed DeepFlu using the state-of-the-art deep learning approach on the human gene expression data infected with IAV subtype H1N1 or H3N2 viruses to forecast who would catch the flu prior to an exposure to IAV.

RESULTS

The results indicated that such forecast is possible and, in other words, gene expression could reflect the strength of host immunity. In the leave-one-person-out cross-validation, DeepFlu based on deep neural network outperformed the models using convolutional neural network, random forest, or support vector machine, achieving 70.0% accuracy, 0.787 AUROC, and 0.758 AUPR for H1N1 and 73.8% accuracy, 0.847 AUROC, and 0.901 AUPR for H3N2. In the external validation, DeepFlu also reached 71.4% accuracy, 0.700 AUROC, and 0.723 AUPR for H1N1 and 73.5% accuracy, 0.732 AUROC, and 0.749 AUPR for H3N2, surpassing the KLRD1 biomarker. In addition, DeepFlu which was trained only by pre-exposure data worked the best than by other time spans and mixed training data of H1N1 and H3N2 did not necessarily enhance prediction. DeepFlu is available at https://github.com/ntou-compbio/DeepFlu.

CONCLUSIONS

DeepFlu is a prognostic tool that can moderately recognize individuals susceptible to the flu and may help prevent the spread of IAV.

Characterization of SARS-CoV-2 ORF6 deletion variants detected in a nosocomial cluster during routine genomic surveillance, Lyon, France

During routine molecular surveillance of SARS-CoV-2 performed at the National Reference Center of Respiratory Viruses (Lyon, France) (n = 229 sequences collected February-April 2020), two frameshifting deletions were detected in the open reading frame 6, at the same position (27267). While a 26-nucleotide deletion variant (D26) was only found in one nasopharyngeal sample in March 2020, the 34-nucleotide deletion (D34) was found within a single geriatric hospital unit in 5/9 patients and one health care worker in April 2020. Phylogeny analysis strongly suggested a nosocomial transmission of D34, with potential fecal transmission, as also identified in a stool sample. No difference in disease severity was observed between patients hospitalized in the geriatric unit infected with WT or D34. In vitro D26 and D34 characterization revealed comparable replication kinetics with the wild-type (WT), but differential host immune responses. While interferon-stimulated genes were similarly upregulated after infection with WT and ORF6 variants, the latter specifically induced overexpression of 9 genes coding for inflammatory cytokines in the NF-kB pathway, including CCL2/MCP1, PTX3, and TNFα, for which high plasma levels have been associated with severe COVID-19. Our findings emphasize the need to monitor the occurrence of ORF6 deletions and assess their impact on the host immune response.

Contribution of Nanotechnologies to Vaccine Development and Drug Delivery against Respiratory Viruses

According to the Center for Disease Control and Prevention (CDC), the coronavirus disease 2019, a respiratory viral illness linked to significant morbidity, mortality, production loss, and severe economic depression, was the third-largest cause of death in 2020. Respiratory viruses such as influenza, respiratory syncytial virus, SARS-CoV-2, and adenovirus, are among the most common causes of respiratory illness in humans, spreading as pandemics or epidemics throughout all continents. Nanotechnologies are particles in the nanometer range made from various compositions. They can be lipid-based, polymer-based, protein-based, or inorganic in nature, but they are all bioinspired and virus-like. In this review, we aimed to present a short review of the different nanoparticles currently studied, in particular those which led to publications in the field of respiratory viruses. We evaluated those which could be beneficial for respiratory disease-based viruses; those which already have contributed, such as lipid nanoparticles in the context of COVID-19; and those which will contribute in the future either as vaccines or antiviral drug delivery systems. We present a short assessment based on a critical selection of evidence indicating nanotechnology's promise in the prevention and treatment of respiratory infections.

Review of Influenza Virus Vaccines: The Qualitative Nature of Immune Responses to Infection and Vaccination Is a Critical Consideration

Influenza viruses have affected the world for over a century, causing multiple pandemics. Throughout the years, many prophylactic vaccines have been developed for influenza; however, these viruses are still a global issue and take many lives. In this paper, we review influenza viruses, associated immunological mechanisms, current influenza vaccine platforms, and influenza infection, in the context of immunocompromised populations. This review focuses on the qualitative nature of immune responses against influenza viruses, with an emphasis on trained immunity and an assessment of the characteristics of the host–pathogen that compromise the effectiveness of immunization. We also highlight innovative immunological concepts that are important considerations for the development of the next generation of vaccines against influenza viruses.

Distinct patterns of within-host virus populations between two subgroups of human respiratory syncytial virus

Human respiratory syncytial virus (RSV) is a major cause of lower respiratory tract infection in young children globally, but little is known about within-host RSV diversity. Here, we characterised within-host RSV populations using deep-sequencing data from 319 nasopharyngeal swabs collected during 2017-2020. RSV-B had lower consensus diversity than RSV-A at the population level, while exhibiting greater within-host diversity. Two RSV-B consensus sequences had an amino acid alteration (K68N) in the fusion (F) protein, which has been associated with reduced susceptibility to nirsevimab (MEDI8897), a novel RSV monoclonal antibody under development. In addition, several minor variants were identified in the antigenic sites of the F protein, one of which may confer resistance to palivizumab, the only licensed RSV monoclonal antibody. The differences in within-host virus populations emphasise the importance of monitoring for vaccine efficacy and may help to explain the different prevalences of monoclonal antibody-escape mutants between the two subgroups.

Use of hemagglutinin and neuraminidase amplicon-based high-throughput sequencing with variant analysis to detect co-infection and resolve identical consensus sequences of seasonal influenza in a university setting

Background

Local transmission of seasonal influenza viruses (IVs) can be difficult to resolve. Here, we study if coupling high-throughput sequencing (HTS) of hemagglutinin (HA) and neuraminidase (NA) genes with variant analysis can resolve strains from local transmission that have identical consensus genome. We analyzed 24 samples collected over four days in January 2020 at a large university in the US. We amplified complete hemagglutinin (HA) and neuraminidase (NA) genomic segments followed by Illumina sequencing. We identified consensus complete HA and NA segments using BLASTn and performed variant analysis on strains whose HA and NA segments were 100% similar.

Results

Twelve of the 24 samples were PCR positive, and we detected complete HA and/or NA segments by de novo assembly in 83.33% (10/12) of them. Similarity and phylogenetic analysis showed that 70% (7/10) of the strains were distinct while the remaining 30% had identical consensus sequences. These three samples also had IAV and IBV co-infection. However, subsequent variant analysis showed that they had distinct variant profiles. While the IAV HA of one sample had no variant, another had a T663C mutation and another had both C1379T and C1589A.

Conclusion

In this study, we showed that HTS coupled with variant analysis of only HA and NA genes can help resolve variants that are closely related. We also provide evidence that during a short time period in the 2019–2020 season, co-infection of IAV and IBV occurred on the university campus and both 2020/2021 and 2021/2022 WHO recommended H1N1 vaccine strains were co-circulating.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-06526-5.

Within-host evolutionary dynamics of seasonal and pandemic human influenza A viruses in young children

The evolution of influenza viruses is fundamentally shaped by within-host processes. However, the within-host evolutionary dynamics of influenza viruses remain incompletely understood, in part because most studies have focused on infections in healthy adults based on single timepoint data. Here, we analyzed the within-host evolution of 82 longitudinally sampled individuals, mostly young children, infected with A/H1N1pdm09 or A/H3N2 viruses between 2007 and 2009. For A/H1N1pdm09 infections during the 2009 pandemic, nonsynonymous minority variants were more prevalent than synonymous ones. For A/H3N2 viruses in young children, early infection was dominated by purifying selection. As these infections progressed, nonsynonymous variants typically increased in frequency even when within-host virus titers decreased. Unlike the short-lived infections of adults where de novo within-host variants are rare, longer infections in young children allow for the maintenance of virus diversity via mutation-selection balance creating potentially important opportunities for within-host virus evolution.

Transmissibility and transmission of respiratory viruses

Human respiratory virus infections lead to a spectrum of respiratory symptoms and disease severity, contributing to substantial morbidity, mortality and economic losses worldwide, as seen in the COVID-19 pandemic. Belonging to diverse families, respiratory viruses differ in how easy they spread (transmissibility) and the mechanism (modes) of transmission. Transmissibility as estimated by the basic reproduction number (R0) or secondary attack rate is heterogeneous for the same virus. Respiratory viruses can be transmitted via four major modes of transmission: direct (physical) contact, indirect contact (fomite), (large) droplets and (fine) aerosols. We know little about the relative contribution of each mode to the transmission of a particular virus in different settings, and how its variation affects transmissibility and transmission dynamics. Discussion on the particle size threshold between droplets and aerosols and the importance of aerosol transmission for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza virus is ongoing. Mechanistic evidence supports the efficacies of non-pharmaceutical interventions with regard to virus reduction; however, more data are needed on their effectiveness in reducing transmission. Understanding the relative contribution of different modes to transmission is crucial to inform the effectiveness of non-pharmaceutical interventions in the population. Intervening against multiple modes of transmission should be more effective than acting on a single mode.

Genomic epidemiology of SARS-CoV-2 in the UAE reveals novel virus mutation, patterns of co-infection and tissue specific host immune response

To unravel the source of SARS-CoV-2 introduction and the pattern of its spreading and evolution in the United Arab Emirates, we conducted meta-transcriptome sequencing of 1067 nasopharyngeal swab samples collected between May 9th and Jun 29th, 2020 during the first peak of the local COVID-19 epidemic. We identified global clade distribution and eleven novel genetic variants that were almost absent in the rest of the world and that defined five subclades specific to the UAE viral population. Cross-settlement human-to-human transmission was related to the local business activity. Perhaps surprisingly, at least 5% of the population were co-infected by SARS-CoV-2 of multiple clades within the same host. We also discovered an enrichment of cytosine-to-uracil mutation among the viral population collected from the nasopharynx, that is different from the adenosine-to-inosine change previously reported in the bronchoalveolar lavage fluid samples and a previously unidentified upregulation of APOBEC4 expression in nasopharynx among infected patients, indicating the innate immune host response mediated by ADAR and APOBEC gene families could be tissue-specific. The genomic epidemiological and molecular biological knowledge reported here provides new insights for the SARS-CoV-2 evolution and transmission and points out future direction on host-pathogen interaction investigation.

Quantitative measures of within-host viral genetic diversity

The genetic diversity of virus populations within their hosts is known to influence disease progression, treatment outcome, drug resistance, cell tropism, and transmission risk, and the study of dynamic changes of genetic heterogeneity can provide insights into the evolution of viruses. Several measures to quantify within-host genetic diversity capturing different aspects of diversity patterns in a sample or population are used, based on incidence, relative frequencies, pairwise distances, or phylogenetic trees. Here, we review and compare several of these measures.

A(H1N1)pdm09 influenza viruses replicating in ferret upper or lower respiratory tract differed in onward transmission potential by air

BACKGROUND

A(H1N1)pdm09 influenza viruses replicate efficiently in respiratory epithelia and are transmitted via respiratory droplets and aerosols expelled by infected hosts. The relative onward transmission potential of influenza viruses replicating in the upper and lower respiratory epithelial cells has not been fully defined.

METHODS

Wild-type and barcoded A(H1N1)pdm09 viruses that differed by 2 synonymous mutations per gene segment were inoculated into ferrets via intra-nasal and intra-tracheal routes. Naïve recipients were exposed to the exhaled breath of inoculated donors for 8 hours on day 2 post-inoculation. Onward transmission potential of wild-type and barcoded genotypes were monitored by next generation sequencing.

RESULTS

Transmissible airborne particles were respired from the upper but not the lower respiratory epithelial cells of donor ferrets. There was limited mixing of viral populations replicating in the upper and lower respiratory tissues.

CONCLUSIONS

The ferret upper respiratory epithelium was mapped as the anatomic site that generated influenza virus-laden particles mediating onward transmission by air. Our results suggest that vaccines and antivirals should aim to reduce viral loads in the upper respiratory tract for prevention of influenza transmission.

Analysis of Hepatitis B Virus Haplotype Diversity Detects Striking Sequence Conservation Across Genotypes and Chronic Disease Phase

BACKGROUND AND AIMS

We conducted haplotype analysis of complete hepatitis B virus (HBV) genomes following deep sequencing from 368 patients across multiple phases of chronic hepatitis B (CHB) infection from four major genotypes (A-D), analyzing 4,110 haplotypes to identify viral variants associated with treatment outcome and disease progression.

APPROACH AND RESULTS

Between 18.2% and 41.8% of nucleotides and between 5.9% and 34.3% of amino acids were 100% conserved in all genotypes and phases examined, depending on the region analyzed. Hepatitis B e antigen (HBeAg) loss by week 192 was associated with different haplotype populations at baseline. Haplotype populations differed across the HBV genome and CHB history, this being most pronounced in the precore/core gene. Mean number of haplotypes (frequency) per patient was higher in immune-active, HBeAg-positive chronic hepatitis phase 2 (11.8) and HBeAg-negative chronic hepatitis phase 4 (16.2) compared to subjects in the "immune-tolerant," HBeAg-positive chronic infection phase 1 (4.3, P< 0.0001). Haplotype frequency was lowest in genotype B (6.2, P< 0.0001) compared to the other genotypes (A = 11.8, C = 11.8, D = 13.6). Haplotype genetic diversity increased over the course of CHB history, being lowest in phase 1, increasing in phase 2, and highest in phase 4 in all genotypes except genotype C. HBeAg loss by week 192 of tenofovir therapy was associated with different haplotype populations at baseline.

CONCLUSIONS

Despite a degree of HBV haplotype diversity and heterogeneity across the phases of CHB natural history, highly conserved sequences in key genes and regulatory regions were identified in multiple HBV genotypes that should be further investigated as targets for antiviral therapies and predictors of treatment response.

SARS-CoV-2 genomic diversity and the implications for qRT-PCR diagnostics and transmission

The COVID-19 pandemic has sparked an urgent need to uncover the underlying biology of this devastating disease. Though RNA viruses mutate more rapidly than DNA viruses, there are a relatively small number of single nucleotide polymorphisms (SNPs) that differentiate the main SARS-CoV-2 lineages that have spread throughout the world. In this study, we investigated 129 RNA-seq data sets and 6928 consensus genomes to contrast the intra-host and inter-host diversity of SARS-CoV-2. Our analyses yielded three major observations. First, the mutational profile of SARS-CoV-2 highlights intra-host single nucleotide variant (iSNV) and SNP similarity, albeit with differences in C > U changes. Second, iSNV and SNP patterns in SARS-CoV-2 are more similar to MERS-CoV than SARS-CoV-1. Third, a significant fraction of insertions and deletions contribute to the genetic diversity of SARS-CoV-2. Altogether, our findings provide insight into SARS-CoV-2 genomic diversity, inform the design of detection tests, and highlight the potential of iSNVs for tracking the transmission of SARS-CoV-2.

Subgrouping and analysis of relationships between classical swine fever virus identified during the 2018-2020 epidemic in Japan by a novel approach using shared genomic variants

Classical swine fever (CSF) is a worldwide devastating disease of the pig industry caused by classical swine fever virus (CSFV). In September 2018, an outbreak of CSF occurred in Japan where the disease had been eradicated and was officially designated a CSF-free country since 2015. Following the detection of the first 2018 case on a farm in Gifu Prefecture, the disease spread among both farm pigs and wild boars and still continues. Epigenome analysis using whole-genome information is helpful in identifying the infection route, but the current approaches provide an insufficient resolution. In this study, a novel method of using single-nucleotide variants (SNVs) was employed to identify the associations among 158 isolates (65 from farms and 93 from wild boars). The identified groups of CSFV strains were plotted in different colours on a map, identifying the location where each strain was collected. The lack of an SNV set shared between the index case and the other strains suggested the first infection in Japan during the outbreak occurred in wild boars, not at the index farm. For the Atsumi Peninsula outbreaks, where nine farms were found infected within a 10-km radius area, the farm strains were assembled into three groups, suggesting these outbreaks resulted from at least three different infection events in this area. For the infections in the area around Saitama Prefecture, an area remote from the epicentre, strains from both the farms and wild boars were identified as being in the same group, suggesting they resulted from one viral introduction. Likewise, seven infected farms in Okinawa Prefecture, almost 1,500 km from Gifu Prefecture, were identified as being in a common, but separate group. By demonstrating the variety of transmission routes and possibility of long-distance infection, these results will help improve disease control measures.

VERSO: A comprehensive framework for the inference of robust phylogenies and the quantification of intra-host genomic diversity of viral samples

We introduce VERSO, a two-step framework for the characterization of viral evolution from sequencing data of viral genomes, which is an improvement on phylogenomic approaches for consensus sequences. VERSO exploits an efficient algorithmic strategy to return robust phylogenies from clonal variant profiles, also in conditions of sampling limitations. It then leverages variant frequency patterns to characterize the intra-host genomic diversity of samples, revealing undetected infection chains and pinpointing variants likely involved in homoplasies. On simulations, VERSO outperforms state-of-the-art tools for phylogenetic inference. Notably, the application to 6,726 amplicon and RNA sequencing samples refines the estimation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) evolution, while co-occurrence patterns of minor variants unveil undetected infection paths, which are validated with contact tracing data. Finally, the analysis of SARS-CoV-2 mutational landscape uncovers a temporal increase of overall genomic diversity and highlights variants transiting from minor to clonal state and homoplastic variants, some of which fall on the spike gene. Available at: https://github.com/BIMIB-DISCo/VERSO.

Mutational signatures and heterogeneous host response revealed via large-scale characterization of SARS-CoV-2 genomic diversity

To dissect the mechanisms underlying the inflation of variants in the Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2) genome, we present a large-scale analysis of intra-host genomic diversity, which reveals that most samples exhibit heterogeneous genomic architectures, due to the interplay between host-related mutational processes and transmission dynamics. The decomposition of minor variants profiles unveils three non-overlapping mutational signatures related to nucleotide substitutions and likely ruled by APOlipoprotein B Editing Complex (APOBEC), Reactive Oxygen Species (ROS), and Adenosine Deaminase Acting on RNA (ADAR), highlighting heterogeneous host responses to SARS-CoV-2 infections. A corrected-for-signatures dN/dS analysis demonstrates that such mutational processes are affected by purifying selection, with important exceptions. In fact, several mutations appear to transit toward clonality, defining new clonal genotypes that increase the overall genomic diversity. Furthermore, the phylogenomic analysis shows the presence of homoplasies and supports the hypothesis of transmission of minor variants. This study paves the way for the integrated analysis of intra-host genomic diversity and clinical outcomes of SARS-CoV-2 infections.

Population Bottlenecks and Intra-host Evolution During Human-to-Human Transmission of SARS-CoV-2

The emergence of the novel human coronavirus, SARS-CoV-2, causes a global COVID-19 (coronavirus disease 2019) pandemic. Here, we have characterized and compared viral populations of SARS-CoV-2 among COVID-19 patients within and across households. Our work showed an active viral replication activity in the human respiratory tract and the co-existence of genetically distinct viruses within the same host. The inter-host comparison among viral populations further revealed a narrow transmission bottleneck between patients from the same households, suggesting a dominated role of stochastic dynamics in both inter-host and intra-host evolutions.

V-pipe: a computational pipeline for assessing viral genetic diversity from high-throughput data

Motivation

High-throughput sequencing technologies are used increasingly not only in viral genomics research but also in clinical surveillance and diagnostics. These technologies facilitate the assessment of the genetic diversity in intra-host virus populations, which affects transmission, virulence and pathogenesis of viral infections. However, there are two major challenges in analysing viral diversity. First, amplification and sequencing errors confound the identification of true biological variants, and second, the large data volumes represent computational limitations.

Results

To support viral high-throughput sequencing studies, we developed V-pipe, a bioinformatics pipeline combining various state-of-the-art statistical models and computational tools for automated end-to-end analyses of raw sequencing reads. V-pipe supports quality control, read mapping and alignment, low-frequency mutation calling, and inference of viral haplotypes. For generating high-quality read alignments, we developed a novel method, called ngshmmalign, based on profile hidden Markov models and tailored to small and highly diverse viral genomes. V-pipe also includes benchmarking functionality providing a standardized environment for comparative evaluations of different pipeline configurations. We demonstrate this capability by assessing the impact of three different read aligners (Bowtie 2, BWA MEM, ngshmmalign) and two different variant callers (LoFreq, ShoRAH) on the performance of calling single-nucleotide variants in intra-host virus populations. V-pipe supports various pipeline configurations and is implemented in a modular fashion to facilitate adaptations to the continuously changing technology landscape.

Availabilityand implementation

V-pipe is freely available at https://github.com/cbg-ethz/V-pipe.

Supplementary information

Supplementary data are available at Bioinformatics online.

Next-Generation Sequencing Analysis of the Within-Host Genetic Diversity of Influenza A(H1N1)pdm09 Viruses in the Upper and Lower Respiratory Tracts of Patients with Severe Influenza

The influenza A(H1N1)pdm09 virus emerged in April 2009 with an unusual incidence of severe disease and mortality, and currently circulates as a seasonal influenza virus. Previous studies using consensus viral genome sequencing data have overlooked the viral genomic and phenotypic diversity. Next-generation sequencing (NGS) may instead be used to characterize viral populations in an unbiased manner and to measure within-host genetic diversity. In this study, we used NGS analysis to investigate the within-host genetic diversity of influenza A(H1N1)pdm09 virus in the upper and lower respiratory samples from nine patients who were admitted to the intensive care unit (ICU). A total of 47 amino acid substitution positions were found to differ between the upper and lower respiratory tract samples from all patients. However, the D222G/N substitution in hemagglutinin (HA) protein was the only amino acid substitution common to multiple patients. Furthermore, the substitution was detected only in the six samples from the lower respiratory tract. Therefore, it is important to investigate influenza A(H1N1)pdm09 virus populations using multiple paired samples from the upper and lower respiratory tract to avoid overlooking potentially important substitutions, especially in patients with severe disease.IMPORTANCE The D222G/N substitution in the hemagglutinin (HA) protein of influenza A(H1N1)pdm09 virus has been reported to be associated with disease severity and mortality in numerous previous studies. In the present study, 75% of lower respiratory samples contained heterogeneous influenza populations that carried different amino acids at position 222 of the HA protein, whereas all upper respiratory samples only contained the wild-type 222D. These results suggest the influenza A(H1N1)pdm09 virus has diversified inside the host owing to differences in tissue specificity. In this study, the within-host genetic diversity of influenza A(H1N1)pdm09 virus was investigated for the first time using next-generation sequencing analysis of the viral whole-genome in samples extracted from the upper and lower respiratory tracts of patients with severe disease.

Cross-scale dynamics and the evolutionary emergence of infectious diseases

When emerging pathogens encounter new host species for which they are poorly adapted, they must evolve to escape extinction. Pathogens experience selection on traits at multiple scales, including replication rates within host individuals and transmissibility between hosts. We analyze a stochastic model linking pathogen growth and competition within individuals to transmission between individuals. Our analysis reveals a new factor, the cross-scale reproductive number of a mutant virion, that quantifies how quickly mutant strains increase in frequency when they initially appear in the infected host population. This cross-scale reproductive number combines with viral mutation rates, single-strain reproductive numbers, and transmission bottleneck width to determine the likelihood of evolutionary emergence, and whether evolution occurs swiftly or gradually within chains of transmission. We find that wider transmission bottlenecks facilitate emergence of pathogens with short-term infections, but hinder emergence of pathogens exhibiting cross-scale selective conflict and long-term infections. Our results provide a framework to advance the integration of laboratory, clinical, and field data in the context of evolutionary theory, laying the foundation for a new generation of evidence-based risk assessment of emergence threats.

Genomic epidemiology of superspreading events in Austria reveals mutational dynamics and transmission properties of SARS-CoV-2

Superspreading events shaped the coronavirus disease 2019 (COVID-19) pandemic, and their rapid identification and containment are essential for disease control. Here, we provide a national-scale analysis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) superspreading during the first wave of infections in Austria, a country that played a major role in initial virus transmissions in Europe. Capitalizing on Austria's well-developed epidemiological surveillance system, we identified major SARS-CoV-2 clusters during the first wave of infections and performed deep whole-genome sequencing of more than 500 virus samples. Phylogenetic-epidemiological analysis enabled the reconstruction of superspreading events and charts a map of tourism-related viral spread originating from Austria in spring 2020. Moreover, we exploited epidemiologically well-defined clusters to quantify SARS-CoV-2 mutational dynamics, including the observation of low-frequency mutations that progressed to fixation within the infection chain. Time-resolved virus sequencing unveiled viral mutation dynamics within individuals with COVID-19, and epidemiologically validated infector-infectee pairs enabled us to determine an average transmission bottleneck size of 103 SARS-CoV-2 particles. In conclusion, this study illustrates the power of combining epidemiological analysis with deep viral genome sequencing to unravel the spread of SARS-CoV-2 and to gain fundamental insights into mutational dynamics and transmission properties.

Primary Swine Respiratory Epithelial Cell Lines for the Efficient Isolation and Propagation of Influenza A Viruses

Influenza virus isolation from clinical samples is critical for the identification and characterization of circulating and emerging viruses. Yet efficient isolation can be difficult. In these studies, we isolated primary swine nasal and tracheal respiratory epithelial cells and immortalized swine nasal epithelial cells (siNEC) and tracheal epithelial cells (siTEC) that retained the abilities to form tight junctions and cilia and to differentiate at the air-liquid interface like primary cells. Critically, both human and swine influenza viruses replicated in the immortalized cells, which generally yielded higher-titer viral isolates from human and swine nasal swabs, supported the replication of isolates that failed to grow in Madin-Darby canine kidney (MDCK) cells, and resulted in fewer dominating mutations during viral passaging than MDCK cells.IMPORTANCE Robust in vitro culture systems for influenza virus are critically needed. MDCK cells, the most widely used cell line for influenza isolation and propagation, do not adequately model the respiratory tract. Therefore, many clinical isolates, both animal and human, are unable to be isolated and characterized, limiting our understanding of currently circulating influenza viruses. We have developed immortalized swine respiratory epithelial cells that retain the ability to differentiate and can support influenza replication and isolation. These cell lines can be used as additional tools to enhance influenza research and vaccine development.

Modeling Competitive Mixtures With the Lotka-Volterra Framework for More Complex Fitness Assessment Between Strains

With increasing resolution of microbial diversity at the genomic level, experimental and modeling frameworks that translate such diversity into phenotypes are highly needed. This is particularly important when comparing drug-resistant with drug-sensitive pathogen strains, when anticipating epidemiological implications of microbial diversity, and when designing control measures. Classical approaches quantify differences between microbial strains using the exponential growth model, and typically report a selection coefficient for the relative fitness differential between two strains. The apparent simplicity of such approaches comes with the costs of limiting the range of biological scenarios that can be captured, and biases strain fitness estimates to polarized extremes of competitive exclusion. Here, we propose a mathematical and statistical framework based on the Lotka-Volterra model, that can capture frequency-dependent competition between microbial strains within-host and upon transmission. As a proof-of-concept, the model is applied to a previously-published dataset from in-vivo competitive mixture experiments with influenza strains in ferrets (McCaw et al., 2011). We show that for the same data, our model predicts a scenario of coexistence between strains, and supports a higher bottleneck size in the range of 35–145 virions transmitted from donor to recipient host. Thanks to its simplicity and generality, such framework could be applied to other ecological scenarios of microbial competition, enabling a more complex and nuanced view of possible outcomes between two strains, beyond competitive exclusion.

A large effective population size for established within-host influenza virus infection

Strains of the influenza virus form coherent global populations, yet exist at the level of single infections in individual hosts. The relationship between these scales is a critical topic for understanding viral evolution. Here we investigate the within-host relationship between selection and the stochastic effects of genetic drift, estimating an effective population size of infection Ne for influenza infection. Examining whole-genome sequence data describing a chronic case of influenza B in a severely immunocompromised child we infer an Ne of 2.5 × 107 (95% confidence range 1.0 × 107 to 9.0 × 107) suggesting that genetic drift is of minimal importance during an established influenza infection. Our result, supported by data from influenza A infection, suggests that positive selection during within-host infection is primarily limited by the typically short period of infection. Atypically long infections may have a disproportionate influence upon global patterns of viral evolution.

Infectious Disease Research in the Era of Big Data

Infectious disease research spans scales from the molecular to the global—from specific mechanisms of pathogen drug resistance, virulence, and replication to the movement of people, animals, and pathogens around the world. All of these research areas have been impacted by the recent growth of large-scale data sources and data analytics. Some of these advances rely on data or analytic methods that are common to most biomedical data science, while others leverage the unique nature of infectious disease, namely its communicability. This review outlines major research progress in the past few years and highlights some remaining opportunities, focusing on data or methodological approaches particular to infectious disease.

Modeling analysis revealed the distinct global transmission patterns of influenza A viruses and their influencing factors

Influenza A virus has caused huge damage to human health and poultry production worldwide, but its global transmission patterns and influencing factors remain unclear. Here, by using the Nearest Genetic Distance Approach with genetic sequences data, we reconstructed the global transmission patterns of 4 most common subtypes of influenza A virus (H1N1, H3N2, H5N1, and H7N9) and analyzed associations of transmission velocity of these influenza viruses with environmental factors. We found that the transmission patterns of influenza viruses and their associations with environmental factors were closely related to their host properties. H1N1 and H3N2, which are mainly held by humans, are transmitted between regions at high velocity and over long distances, which may be due to human transportation via airplane; while H5N1 and H7N9, which are mainly carried by animals, are transmitted locally at short distances and at low velocity, which may be facilitated by poultry transportation via railways or high ways. H1N1 and H3N2 spread faster in cold seasons, while H5N1 spread faster in both cold and warm seasons, and H7N9 spread faster in wet seasons. H1N1, H3N2, and H5N1 spread faster in places with both high and low human densities. Our study provided novel insights into the global transmission patterns, processes, and management strategies for influenza under accelerated global change.

Hidden genomic diversity of SARS-CoV-2: implications for qRT-PCR diagnostics and transmission

The COVID-19 pandemic has sparked an urgent need to uncover the underlying biology of this devastating disease. Though RNA viruses mutate more rapidly than DNA viruses, there are a relatively small number of single nucleotide polymorphisms (SNPs) that differentiate the main SARS-CoV-2 clades that have spread throughout the world. In this study, we investigated over 7,000 SARS-CoV-2 datasets to unveil both intrahost and interhost diversity. Our intrahost and interhost diversity analyses yielded three major observations. First, the mutational profile of SARS-CoV-2 highlights iSNV and SNP similarity, albeit with high variability in C>T changes. Second, iSNV and SNP patterns in SARS-CoV-2 are more similar to MERS-CoV than SARS-CoV-1. Third, a significant fraction of small indels fuel the genetic diversity of SARS-CoV-2. Altogether, our findings provide insight into SARS-CoV-2 genomic diversity, inform the design of detection tests, and highlight the potential of iSNVs for tracking the transmission of SARS-CoV-2.

Inferring Transmission Bottleneck Size from Viral Sequence Data Using a Novel Haplotype Reconstruction Method

Viral populations undergo a repeated cycle of within-host growth followed by transmission. Viral evolution is affected by each stage of this cycle. The number of viral particles transmitted from one host to another, known as the transmission bottleneck, is an important factor in determining how the evolutionary dynamics of the population play out, restricting the extent to which the evolved diversity of the population can be passed from one host to another. Previous study of viral sequence data has suggested that the transmission bottleneck size for influenza A transmission between human hosts is small. Reevaluating these data using a novel and improved method, we largely confirm this result, albeit that we infer a slightly higher bottleneck size in some cases, of between 1 and 13 virions. While a tight bottleneck operates in human influenza transmission, it is not extreme in nature; some diversity can be meaningfully retained between hosts.

The transmission bottleneck is defined as the number of viral particles that transmit from one host to establish an infection in another. Genome sequence data have been used to evaluate the size of the transmission bottleneck between humans infected with the influenza virus; however, the methods used to make these estimates have some limitations. Specifically, viral allele frequencies, which form the basis of many calculations, may not fully capture a process which involves the transmission of entire viral genomes. Here, we set out a novel approach for inferring viral transmission bottlenecks; our method combines an algorithm for haplotype reconstruction with maximum likelihood methods for bottleneck inference. This approach allows for rapid calculation and performs well when applied to data from simulated transmission events; errors in the haplotype reconstruction step did not adversely affect inferences of the population bottleneck. Applied to data from a previous household transmission study of influenza A infection, we confirm the result that the majority of transmission events involve a small number of viruses, albeit with slightly looser bottlenecks being inferred, with between 1 and 13 particles transmitted in the majority of cases. While influenza A transmission involves a tight population bottleneck, the bottleneck is not so tight as to universally prevent the transmission of within-host viral diversity.

IMPORTANCE Viral populations undergo a repeated cycle of within-host growth followed by transmission. Viral evolution is affected by each stage of this cycle. The number of viral particles transmitted from one host to another, known as the transmission bottleneck, is an important factor in determining how the evolutionary dynamics of the population play out, restricting the extent to which the evolved diversity of the population can be passed from one host to another. Previous study of viral sequence data has suggested that the transmission bottleneck size for influenza A transmission between human hosts is small. Reevaluating these data using a novel and improved method, we largely confirm this result, albeit that we infer a slightly higher bottleneck size in some cases, of between 1 and 13 virions. While a tight bottleneck operates in human influenza transmission, it is not extreme in nature; some diversity can be meaningfully retained between hosts.