Augur: a bioinformatics toolkit for phylogenetic analyses of human pathogens

An atlas of continuous adaptive evolution in endemic human viruses

Through antigenic evolution, viruses such as seasonal influenza evade recognition by neutralizing antibodies. This means that a person with antibodies well tuned to an initial infection will not be protected against the same virus years later and that vaccine-mediated protection will decay. To expand our understanding of which endemic human viruses evolve in this fashion, we assess adaptive evolution across the genome of 28 endemic viruses spanning a wide range of viral families and transmission modes. Surface proteins consistently show the highest rates of adaptation, and ten viruses in this panel are estimated to undergo antigenic evolution to selectively fix mutations that enable the escape of prior immunity. Thus, antibody evasion is not an uncommon evolutionary strategy among human viruses, and monitoring this evolution will inform future vaccine efforts. Additionally, by comparing overall amino acid substitution rates, we show that SARS-CoV-2 is accumulating protein-coding changes at substantially faster rates than endemic viruses.

Phylogenetic identification of influenza virus candidates for seasonal vaccines

The seasonal influenza (flu) vaccine is designed to protect against those influenza viruses predicted to circulate during the upcoming flu season, but identifying which viruses are likely to circulate is challenging. We use features from phylogenetic trees reconstructed from hemagglutinin (HA) and neuraminidase (NA) sequences, together with a support vector machine, to predict future circulation. We obtain accuracies of 0.75 to 0.89 (AUC 0.83 to 0.91) over 2016-2020. We explore ways to select potential candidates for a seasonal vaccine and find that the machine learning model has a moderate ability to select strains that are close to future populations. However, consensus sequences among the most recent 3 years also do well at this task. We identify similar candidate strains to those proposed by the World Health Organization, suggesting that this approach can help inform vaccine strain selection.

Clinical Whole-Genome Sequencing Assay for Rapid Mycobacterium tuberculosis Complex First-Line Drug Susceptibility Testing and Phylogenetic Relatedness Analysis

The global rise of drug resistant tuberculosis has highlighted the need for improved diagnostic technologies that provide rapid and reliable drug resistance results. Here, we develop and validate a whole genome sequencing (WGS)-based test for identification of mycobacterium tuberculosis complex (MTB) drug resistance to rifampin, isoniazid, pyrazinamide, ethambutol, and streptomycin. Through comparative analysis of drug resistance results from WGS-based testing and phenotypic drug susceptibility testing (DST) of 38 clinical MTB isolates from patients receiving care in Los Angeles, CA, we found an overall concordance between methods of 97.4% with equivalent performance across culture media. Critically, prospective analysis of 11 isolates showed that WGS-based testing provides results an average of 36 days faster than phenotypic culture-based methods. We showcase the additional benefits of WGS data by investigating a suspected laboratory contamination event and using phylogenetic analysis to search for cryptic local transmission, finding no evidence of community spread amongst our patient population in the past six years. WGS-based testing for MTB drug resistance has the potential to greatly improve diagnosis of drug resistant MTB by accelerating turnaround time while maintaining accuracy and providing additional benefits for infection control, lab safety, and public health applications.

Antigenic and molecular characterization of isolates of the Brazilian genotype BR-I (GI-11) of infectious bronchitis virus supports its recognition as BR-I serotype

The antigenic and molecular characteristics of BR-I infectious bronchitis viruses (IBVs) isolated from Brazil are reported. IBVs isolated from commercial flocks with different clinical manifestations between 2003 and 2019 were submitted to antigenic and molecular characterization. The complete S1 glycoprotein gene of 11 field isolates was amplified and sequenced. The virus neutralization (VN) test showed 94.75% neutralization with a BR-I isolate and 30% or less against other worldwide reference strains. The nucleotide and amino acid sequence analyses revealed 84.3-100% and 83.5-100% identity among them, respectively. The identity values ranged from 57.1 to 82.6% for nucleotides and from 46.6-84.4% for amino acids compared with those of other genotypes. By phylogenetic tree analysis, the Brazilian isolates were branched into the BR-I genotype (lineage GI-11), which was differentiated from foreign reference strains. Selective pressure analyses of BR-I IBVs revealed evolution under purifying selection (negative pressure) for the complete S1 gene but four specific sites (87, 121, 279, and 542) under diversifying selection (positive pressure). Profiles of cleavage sites and potential N-glycosylation sites differed from those of other genotypes. The low molecular relationship among the Brazilian viruses and foreign serotypes was concordant with the VN test results. The low antigenic relatedness (ranging from 5.3-30% between Brazilian genotype BR-I and reference IBV serotypes of North America, Europe, and Asia) indicates that the BR-I genotype is a different serotype, referred to for the first time and hereafter as serotype BR-I. RESEARCH HIGHLIGHTSStrains of the BR-I genotype presented robust antigenic and molecular similarity.BR-I strains evolved under purifying selection mode (negative pressure).The BR-I genotype originated in Brazil and dispersed to other countries.BR-I genotype viruses can be referred to as the BR-I serotype.

The re-emergence of influenza following the COVID-19 pandemic in Victoria, Australia, 2021 to 2022

BackgroundCOVID-19 pandemic mitigation measures, including travel restrictions, limited global circulation of influenza viruses. In Australia, travel bans for non-residents and quarantine requirements for returned travellers were eased in November 2021, providing pathways for influenza viruses to be re-introduced.AimWe aimed to describe the epidemiological and virological characteristics of the re-emergence of influenza in Victoria, Australia to inform public health interventions.MethodsFrom 1 November 2021 to 30 April 2022, we conducted an epidemiological study analysing case notification data from the Victorian Department of Health to describe case demographics, interviewed the first 200 cases to establish probable routes of virus reintroduction and examined phylogenetic and antigenic data to understand virus diversity and susceptibility to current vaccines.ResultsOverall, 1,598 notifications and 1,064 positive specimens were analysed. The majority of cases (61.4%) occurred in the 15-34 years age group. Interviews revealed a higher incidence of international travel exposure during the first month of case detections, and high levels of transmission in university residential colleges were associated with return to campus. Influenza A(H3N2) was the predominant subtype, with a single lineage predominating despite multiple importations.ConclusionEnhanced testing for respiratory viruses during the COVID-19 pandemic provided a more complete picture of influenza virus transmission compared with previous seasons. Returned international travellers were important drivers of influenza reemergence, as were young adults, a group whose role has previously been under-recognised in the establishment of seasonal influenza epidemics. Targeting interventions, including vaccination, to these groups could reduce future influenza transmission.

Sequential viral introductions and spread of BA.1 across Pakistan provinces during the Omicron wave

BACKGROUND

COVID-19 waves caused by specific SARS-CoV-2 variants have occurred globally at different times. We focused on Omicron variants to understand the genomic diversity and phylogenetic relatedness of SARS-CoV-2 strains in various regions of Pakistan.

METHODS

We studied 276,525 COVID-19 cases and 1,031 genomes sequenced from December 2021 to August 2022. Sequences were analyzed and visualized using phylogenetic trees.

RESULTS

The highest case numbers and deaths were recorded in Sindh and Punjab, the most populous provinces in Pakistan. Omicron variants comprised 93% of all genomes, with BA.2 (32.6%) and BA.5 (38.4%) predominating. The first Omicron wave was associated with the sequential identification of BA.1 in Sindh, then Islamabad Capital Territory, Punjab, Khyber Pakhtunkhwa (KP), Azad Jammu Kashmir (AJK), Gilgit-Baltistan (GB) and Balochistan. Phylogenetic analysis revealed Sindh to be the source of BA.1 and BA.2 introductions into Punjab and Balochistan during early 2022. BA.4 was first introduced in AJK and BA.5 in Punjab. Most recent common ancestor (MRCA) analysis revealed relatedness between the earliest BA.1 genome from Sindh with Balochistan, AJK, Punjab and ICT, and that of first BA.1 from Punjab with strains from KPK and GB.

CONCLUSIONS

Phylogenetic analysis provides insights into the introduction and transmission dynamics of the Omicron variant in Pakistan, identifying Sindh as a hotspot for viral dissemination. Such data linked with public health efforts can help limit surges of new infections.

A tale of two waves: Delineating diverse genomic and transmission landscapes driving the COVID-19 pandemic in Pune, India

BACKGROUND

Modern response to pandemics, critical for effective public health measures, is shaped by the availability and integration of diverse epidemiological outbreak data. Tracking variants of concern (VOC) is integral to understanding the evolution of SARS-CoV-2 in space and time, both at the local level and global context. This potentially generates actionable information when integrated with epidemiological outbreak data.

METHODS

A city-wide network of researchers, clinicians, and pathology diagnostic laboratories was formed for genome surveillance of COVID-19 in Pune, India. The genomic landscapes of 10,496 sequenced samples of SARS-CoV-2 driving peaks of infection in Pune between December-2020 to March-2022, were determined. As a modern response to the pandemic, a "band of five" outbreak data analytics approach was used. This integrated the genomic data (Band 1) of the virus through molecular phylogenetics with key outbreak data including sample collection dates and case numbers (Band 2), demographics like age and gender (Band 3-4), and geospatial mapping (Band 5).

RESULTS

The transmission dynamics of VOCs in 10,496 sequenced samples identified B.1.617.2 (Delta) and BA(x) (Omicron formerly known as B.1.1.529) variants as drivers of the second and third peaks of infection in Pune. Spike Protein mutational profiling during pre and post-Omicron VOCs indicated differential rank ordering of high-frequency mutations in specific domains that increased the charge and binding properties of the protein. Time-resolved phylogenetic analysis of Omicron sub-lineages identified a highly divergent BA.1 from Pune in addition to recombinant X lineages, XZ, XQ, and XM.

CONCLUSIONS

The band of five outbreak data analytics approach, which integrates five different types of data, highlights the importance of a strong surveillance system with high-quality meta-data for understanding the spatiotemporal evolution of the SARS-CoV-2 genome in Pune. These findings have important implications for pandemic preparedness and could be critical tools for understanding and responding to future outbreaks.

Accelerating bioinformatics implementation in public health

We have adopted an open bioinformatics ecosystem to address the challenges of bioinformatics implementation in public health laboratories (PHLs). Bioinformatics implementation for public health requires practitioners to undertake standardized bioinformatic analyses and generate reproducible, validated and auditable results. It is essential that data storage and analysis are scalable, portable and secure, and that implementation of bioinformatics fits within the operational constraints of the laboratory. We address these requirements using Terra, a web-based data analysis platform with a graphical user interface connecting users to bioinformatics analyses without the use of code. We have developed bioinformatics workflows for use with Terra that specifically meet the needs of public health practitioners. These Theiagen workflows perform genome assembly, quality control, and characterization, as well as construction of phylogeny for insights into genomic epidemiology. Additonally, these workflows use open-source containerized software and the WDL workflow language to ensure standardization and interoperability with other bioinformatics solutions, whilst being adaptable by the user. They are all open source and publicly available in Dockstore with the version-controlled code available in public GitHub repositories. They have been written to generate outputs in standardized file formats to allow for further downstream analysis and visualization with separate genomic epidemiology software. Testament to this solution meeting the requirements for bioinformatic implementation in public health, Theiagen workflows have collectively been used for over 5 million sample analyses in the last 2 years by over 90 public health laboratories in at least 40 different countries. Continued adoption of technological innovations and development of further workflows will ensure that this ecosystem continues to benefit PHLs.

Genomic screening of 16 UK native bat species through conservationist networks uncovers coronaviruses with zoonotic potential

There has been limited characterisation of bat-borne coronaviruses in Europe. Here, we screened for coronaviruses in 48 faecal samples from 16 of the 17 bat species breeding in the UK, collected through a bat rehabilitation and conservationist network. We recovered nine complete genomes, including two novel coronavirus species, across six bat species: four alphacoronaviruses, a MERS-related betacoronavirus, and four closely related sarbecoviruses. We demonstrate that at least one of these sarbecoviruses can bind and use the human ACE2 receptor for infecting human cells, albeit suboptimally. Additionally, the spike proteins of these sarbecoviruses possess an R-A-K-Q motif, which lies only one nucleotide mutation away from a furin cleavage site (FCS) that enhances infectivity in other coronaviruses, including SARS-CoV-2. However, mutating this motif to an FCS does not enable spike cleavage. Overall, while UK sarbecoviruses would require further molecular adaptations to infect humans, their zoonotic risk warrants closer surveillance.

Large clones of pre-existing T cells drive early immunity against SARS-COV-2 and LCMV infection

T cell responses precede antibody and may provide early control of infection. We analyzed the clonal basis of this rapid response following SARS-COV-2 infection. We applied T cell receptor (TCR) sequencing to define the trajectories of individual T cell clones immediately. In SARS-COV-2 PCR+ individuals, a wave of TCRs strongly but transiently expand, frequently peaking the same week as the first positive PCR test. These expanding TCR CDR3s were enriched for sequences functionally annotated as SARS-COV-2 specific. Epitopes recognized by the expanding TCRs were highly conserved between SARS-COV-2 strains but not with circulating human coronaviruses. Many expanding CDR3s were present at high frequency in pre-pandemic repertoires. Early response TCRs specific for lymphocytic choriomeningitis virus epitopes were also found at high frequency in the preinfection naive repertoire. High-frequency naive precursors may allow the T cell response to respond rapidly during the crucial early phases of acute viral infection.

Apollo Rising: Acute Conjunctivitis Outbreak in India, 2022

Purpose

To identify pathogens associated with the 2022 conjunctivitis outbreak in Tamil Nadu, India.

Methods

This prospective study was conducted in November of 2022. Patients with presumed acute infectious conjunctivitis presenting to the Aravind Eye Clinic in Madurai, India were eligible. Anterior nares and conjunctival samples from participants were obtained and processed for metagenomic RNA deep sequencing (RNA-seq).

Results

Samples from 29 patients were sequenced. A pathogen was identified in 28/29 (97%) patients. Coxsackievirus A24v, a highly infectious RNA virus, was the predominant pathogen and detected in 23/29 patients. Human adenovirus D (HAdV-D), a DNA virus commonly associated with conjunctivitis outbreaks, was detected in the remaining patients (5/29). Hemorrhagic conjunctiva was documented in both HAdV-D and coxsackievirus A24v affected patients but was not the predominant clinical presentation. Phylogenetic analysis of coxsackievirus A24v revealed a recent divergence from the 2015 outbreak.

Conclusions

Coxsackievirus A24v and HAdV-D were co-circulating during the 2022 conjunctivitis outbreak in Tamil Nadu, India. Clinical findings were similar between patients with HAD-V and coxsackievirus A24v associated conjunctivitis. As high-throughput technologies become more readily accessible and cost-effective, unbiased pathogen surveillance may prove useful for outbreak surveillance and control.

Genofunc: genome annotation and identification of genome features for automated pipelining analysis of virus whole genome sequences

BACKGROUND

Viral genomics and epidemiology have been increasingly important tools for analysing the spread of key pathogens affecting daily lives of individuals worldwide. With the rapidly expanding scale of pathogen genome sequencing efforts for epidemics and outbreaks efficient workflows in extracting genomic information are becoming increasingly important for answering key research questions.

RESULTS

Here we present Genofunc, a toolkit offering a range of command line orientated functions for processing of raw virus genome sequences into aligned and annotated data ready for analysis. The tool contains functions such as genome annotation, feature extraction etc. for processing of large genomic datasets both manual or as part of pipeline such as Snakemake or Nextflow ready for down-stream phylogenetic analysis. Originally designed for a large-scale HIV sequencing project, Genofunc has been benchmarked against annotated sequence gene coordinates from the Los Alamos HIV database as validation with downstream phylogenetic analysis result comparable to past literature as case study.

CONCLUSION

Genofunc is implemented fully in Python and licensed under the MIT license. Source code and documentation is available at: https://github.com/xiaoyu518/genofunc .

Rapid evolution of A(H5N1) influenza viruses after intercontinental spread to North America

Highly pathogenic avian influenza A(H5N1) viruses of clade 2.3.4.4b underwent an explosive geographic expansion in 2021 among wild birds and domestic poultry across Asia, Europe, and Africa. By the end of 2021, 2.3.4.4b viruses were detected in North America, signifying further intercontinental spread. Here we show that the western movement of clade 2.3.4.4b was quickly followed by reassortment with viruses circulating in wild birds in North America, resulting in the acquisition of different combinations of ribonucleoprotein genes. These reassortant A(H5N1) viruses are genotypically and phenotypically diverse, with many causing severe disease with dramatic neurologic involvement in mammals. The proclivity of the current A(H5N1) 2.3.4.4b virus lineage to reassort and target the central nervous system warrants concerted planning to combat the spread and evolution of the virus within the continent and to mitigate the impact of a potential influenza pandemic that could originate from similar A(H5N1) reassortants.

Genomic surveillance identifies potential risk factors for SARS-CoV-2 transmission at a mid-sized university in a small rural town

Understanding transmission dynamics of SARS-CoV-2 in institutions of higher education (IHEs) is important because these settings have potential for rapid viral spread. Here, we used genomic surveillance to retrospectively investigate transmission dynamics throughout the 2020-2021 academic year for the University of Idaho ("University"), a mid-sized IHE in a small rural town. We generated genome assemblies for 1168 SARS-CoV-2 samples collected during the academic year, representing 46.8% of positive samples collected from the University population and 49.8% of positive samples collected from the surrounding community ("Community") at the local hospital during this time. Transmission dynamics differed for the University when compared to the Community, with more infection waves that lasted shorter lengths of time, potentially resulting from high-transmission congregate settings along with mitigation efforts implemented by the University to combat outbreaks. We found evidence for low transmission rates between the University and Community, with approximately 8% of transmissions into the Community originating from the University, and approximately 6% of transmissions into the University originating from the Community. Potential transmission risk factors identified for the University included congregate settings such as sorority and fraternity events and residences, holiday travel, and high caseloads in the surrounding community. Knowledge of these risk factors can help the University and other IHEs develop effective mitigation measures for SARS-CoV-2 and similar pathogens.

Tracking the prevalence and emergence of SARS CoV2 variants of concern using a regional genomic surveillance program

SARS-CoV-2 molecular testing coupled with whole genome sequencing is instrumental for real-time genomic surveillance. Genomic surveillance is critical for monitoring the spread of variants of concern (VOC) as well as novel variant discovery. Since the beginning of the pandemic millions of SARS-CoV-2 genomes have been deposited into public sequence databases. This is the result of efforts of both national and regional diagnostic laboratories. Here we describe the results of SARS-CoV-2 genomic surveillance from February 2021 to June 2022 at a metropolitan hospital in the USA. We demonstrate that consistent daily sampling is sufficient to track the regional prevalence and emergence of VOC. Similar sampling efforts should be considered a viable option for local SARS-CoV-2 genomic surveillance at other regional laboratories.

Genomic epidemiology reveals the dominance of Hennepin County in transmission of SARS-CoV-2 in Minnesota from 2020-2022

SARS-CoV-2 has had an unprecedented impact on human health and highlights the need for genomic epidemiology studies to increase our understanding of virus evolution and spread, and to inform policy decisions. We sequenced viral genomes from over 22,000 patient samples tested at Mayo Clinic Laboratories between 2020-2022 and use Bayesian phylodynamics to describe county and regional spread in Minnesota. The earliest introduction into Minnesota was to Hennepin County from a domestic source around January 22, 2020; six weeks before the first confirmed case in the state. This led to the virus spreading to Northern Minnesota, and eventually, the rest of the state. International introductions were most abundant in Hennepin (home to the Minneapolis/St. Paul International (MSP) airport) totaling 45 (out of 107) over the two-year period. Southern Minnesota counties were most common for domestic introductions with 19 (out of 64), potentially driven by bordering states such as Iowa and Wisconsin as well as Illinois which is nearby. Hennepin also was, by far, the most dominant source of in-state transmissions to other Minnesota locations (n=772) over the two-year period. We also analyzed the diversity of the location source of SARS-CoV-2 viruses in each county and noted the timing of state-wide policies as well as trends in clinical cases. Neither the number of clinical cases or major policy decisions, such as the end of the lockdown period in 2020 or the end of all restrictions in 2021, appeared to have impact on virus diversity across each individual county.

HaploCoV: unsupervised classification and rapid detection of novel emerging variants of SARS-CoV-2

Accurate and timely monitoring of the evolution of SARS-CoV-2 is crucial for identifying and tracking potentially more transmissible/virulent viral variants, and implement mitigation strategies to limit their spread. Here we introduce HaploCoV, a novel software framework that enables the exploration of SARS-CoV-2 genomic diversity through space and time, to identify novel emerging viral variants and prioritize variants of potential epidemiological interest in a rapid and unsupervised manner. HaploCoV can integrate with any classification/nomenclature and incorporates an effective scoring system for the prioritization of SARS-CoV-2 variants. By performing retrospective analyses of more than 11.5 M genome sequences we show that HaploCoV demonstrates high levels of accuracy and reproducibility and identifies the large majority of epidemiologically relevant viral variants - as flagged by international health authorities - automatically and with rapid turn-around times.Our results highlight the importance of the application of strategies based on the systematic analysis and integration of regional data for rapid identification of novel, emerging variants of SARS-CoV-2. We believe that the approach outlined in this study will contribute to relevant advances to current and future genomic surveillance methods.

Afro-TB dataset as a large scale genomic data of Mycobacterium tuberuclosis in Africa

Mycobacterium tuberculosis (MTB) is a pathogenic bacterium accountable for 10.6 million new infections with tuberculosis (TB) in 2021. The fact that the genetic sequences of M. tuberculosis vary widely provides a basis for understanding how this bacterium causes disease, how the immune system responds to it, how it has evolved over time, and how it is distributed geographically. However, despite extensive research efforts, the evolution and transmission of MTB in Africa remain poorly understood. In this study, we used 17,641 strains from 26 countries to create the first curated African Mycobacterium tuberculosis (MTB) classification and resistance dataset, containing 13,753 strains. We identified 157 mutations in 12 genes associated with resistance and additional new mutations potentially associated with resistance. The resistance profile was used to classify strains. We also performed a phylogenetic classification of each isolate and prepared the data in a format that can be used for phylogenetic and comparative analysis of tuberculosis worldwide. These genomic data will extend current information for comparative genomic studies to understand the mechanisms and evolution of MTB drug resistance.

State-dependent evolutionary models reveal modes of solid tumour growth

Spatial properties of tumour growth have profound implications for cancer progression, therapeutic resistance and metastasis. Yet, how spatial position governs tumour cell division remains difficult to evaluate in clinical tumours. Here, we demonstrate that faster division on the tumour periphery leaves characteristic genetic patterns, which become evident when a phylogenetic tree is reconstructed from spatially sampled cells. Namely, rapidly dividing peripheral lineages branch more extensively and acquire more mutations than slower-dividing centre lineages. We develop a Bayesian state-dependent evolutionary phylodynamic model (SDevo) that quantifies these patterns to infer the differential division rates between peripheral and central cells. We demonstrate that this approach accurately infers spatially varying birth rates of simulated tumours across a range of growth conditions and sampling strategies. We then show that SDevo outperforms state-of-the-art, non-cancer multi-state phylodynamic methods that ignore differential sequence evolution. Finally, we apply SDevo to single-time-point, multi-region sequencing data from clinical hepatocellular carcinomas and find evidence of a three- to six-times-higher division rate on the tumour edge. With the increasing availability of high-resolution, multi-region sequencing, we anticipate that SDevo will be useful in interrogating spatial growth restrictions and could be extended to model non-spatial factors that influence tumour progression.

Joint visualization of seasonal influenza serology and phylogeny to inform vaccine composition

Seasonal influenza vaccines must be updated regularly to account for mutations that allow influenza viruses to escape our existing immunity. A successful vaccine should represent the genetic diversity of recently circulating viruses and induce antibodies that effectively prevent infection by those recent viruses. Thus, linking the genetic composition of circulating viruses and the serological experimental results measuring antibody efficacy is crucial to the vaccine design decision. Historically, genetic and serological data have been presented separately in the form of static visualizations of phylogenetic trees and tabular serological results to identify vaccine candidates. To simplify this decision-making process, we have created an interactive tool for visualizing serological data that has been integrated into Nextstrain's real-time phylogenetic visualization framework, Auspice. We show how the combined interactive visualizations may be used by decision makers to explore the relationships between complex data sets for both prospective vaccine virus selection and retrospectively exploring the performance of vaccine viruses.

Use of serial testing to interrupt a severe acute respiratory coronavirus virus 2 (SARS-CoV-2) outbreak on a hospital medical floor-Minnesota, October-December 2020

OBJECTIVE

Describe a severe acute respiratory coronavirus virus 2 (SARS-CoV-2) hospital outbreak and the role of serial testing of patients and healthcare personnel (HCP) in interrupting SARS-CoV-2 transmission.

DESIGN

Outbreak investigation.

SETTING

Medical floor of a tertiary-care center in Minnesota.

METHODS

Serial testing for SARS-CoV-2 and whole-genome sequencing (WGS) of positive specimens from HCP and patients were used. An outbreak-associated case was defined as a positive SARS-CoV-2 molecular test in an HCP who worked on the floor prior to testing positive or in a patient who was hospitalized on the medical floor bewteen October 27 and December 1, 2020. WGS was used to determine potential routes of transmission.

RESULTS

The outbreak was detected after a patient hospitalized for 12 days tested positive for SARS-CoV-2. Serial testing of patients and HCP was conducted in response. Overall, 247 HCP and 41 patients participated in serial SARS-CoV-2 testing; 52 HCP (21%) and 19 hospitalized patients (46%) tested positive. One additional HCP tested positive outside serial testing. The WGS of specimens from 27 (51%) HCP and 15 (79%) patients identified 3 distinct transmission clusters. WGS and epidemiologic evidence suggested intrafacility transmission. The proportions of asymptomatic and presymptomatic patients who tested positive (63%) and HCP who worked during their infectious period (75%) highlight the need for serial testing of asymptomatic patients and HCP during outbreaks.

CONCLUSIONS

Coupled with preventive measures such as personal protective equipment use and physical distancing, serial testing of HCP and patients could help detect and prevent transmission within healthcare facilities during outbreaks and when nosocomial transmission is suspected.

Single cell RNA-seq resolution revealed CCR1+/SELL+/XAF+ CD14 monocytes mediated vascular endothelial cell injuries in Kawasaki disease and COVID-19

INTRODUCTION

The COVID-19 pandemic provide the opportunities to explore the numerous similarities in clinical symptoms with Kawasaki disease (KD), including severe vasculitis. Despite this, the underlying mechanisms of vascular injury in both KD and COVID-19 remain elusive. To identify these mechanisms, this study employs single-cell RNA sequencing to explore the molecular mechanisms of immune responses in vasculitis, and validate the results through in vitro experiments.

METHOD

The single-cell RNA sequencing (scRNA-seq) analysis of peripheral blood mononuclear cells (PBMCs) was carried out to investigate the molecular mechanisms of immune responses in vasculitis in KD and COVID-19. The analysis was performed on PBMCs from six children diagnosed with complete KD, three age-matched KD healthy controls (KHC), six COVID-19 patients (COV), three influenza patients (FLU), and four healthy controls (CHC). The results from the scRNA-seq analysis were validated through flow cytometry and immunofluorescence experiments on additional human samples. Subsequently, monocyte adhesion assays, immunofluorescence, and quantitative polymerase chain reaction (qPCR) were used to analyze the damages to endothelial cells post-interaction with monocytes in HUVEC and THP1 cultures.

RESULTS

The scRNA-seq analysis revealed the potential cellular types involved and the alterations in genetic transcriptions in the inflammatory responses. The findings indicated that while the immune cell compositions had been altered in KD and COV patients, and the ratio of CD14+ monocytes were both elevated in KD and COV. While the CD14+ monocytes share a large scale of same differentiated expressed geens between KD and COV. The differential activation of CD14 and CD16 monocytes was found to respond to both endothelial and epithelial dysfunctions. Furthermore, SELL+/CCR1+/XAF1+ CD14 monocytes were seen to enhance the adhesion and damage to endothelial cells. The results also showed that different types of B cells were involved in both KD and COV, while only the activation of T cells was recorded in KD.

CONCLUSION

In conclusion, our study demonstrated the role of the innate immune response in the regulation of endothelial dysfunction in both KD and COVID-19. Additionally, our findings indicate that the adaptive immunity activation differs between KD and COVID-19. Our results demonstrate that monocytes in COVID-19 exhibit adhesion to both endothelial cells and alveolar epithelial cells, thus providing insight into the mechanisms and shared phenotypes between KD and COVID-19.

Accelerated SARS-CoV-2 intrahost evolution leading to distinct genotypes during chronic infection

The chronic infection hypothesis for novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant emergence is increasingly gaining credence following the appearance of Omicron. Here, we investigate intrahost evolution and genetic diversity of lineage B.1.517 during a SARS-CoV-2 chronic infection lasting for 471 days (and still ongoing) with consistently recovered infectious virus and high viral genome copies. During the infection, we find an accelerated virus evolutionary rate translating to 35 nucleotide substitutions per year, approximately 2-fold higher than the global SARS-CoV-2 evolutionary rate. This intrahost evolution results in the emergence and persistence of at least three genetically distinct genotypes, suggesting the establishment of spatially structured viral populations continually reseeding different genotypes into the nasopharynx. Finally, we track the temporal dynamics of genetic diversity to identify advantageous mutations and highlight hallmark changes for chronic infection. Our findings demonstrate that untreated chronic infections accelerate SARS-CoV-2 evolution, providing an opportunity for the emergence of genetically divergent variants.

How the Commonwealth of the Northern Mariana Islands stalled COVID-19 for 22 months and managed its first significant community transmission

Objective

The Commonwealth of the Northern Mariana Islands (CNMI) is a remote Pacific island territory with a population of 47 329 that successfully prevented the significant introduction of coronavirus disease (COVID-19) until late 2021. This study documents how the response to the introduction of COVID-19 in CNMI in 2021 was conducted with limited resources without overwhelming local clinical capacity or compromising health service delivery for the population.

Methods

Data from COVID-19 case investigations, contact tracing, the Commonwealth's immunization registry and whole genome sequencing were collated and analysed as part of this study.

Results

Between 26 March 2020 and 31 December 2021, 3281 cases and 14 deaths due to COVID-19 were reported in CNMI (case fatality rate, 0.4%). While notification rates were highest among younger age groups, hospitalization and mortality rates were disproportionately greater among those aged > 50 years and among the unvaccinated. The first widespread community transmission in CNMI was detected in October 2021, with genomic epidemiology and contact tracing data indicating a single introduction event involving the AY.25 lineage and subsequent rapid community spread. Vaccination coverage was high before widespread transmission occurred in October 2021 and increased further over the study period.

Discussion

Robust preparedness and strong leadership generated resilience within the public health sector such that COVID-19 did not overwhelm CNMI's health system as it did in other jurisdictions and countries around the world. At no point was hospital capacity exceeded, and all patients received adequate care without the need for health-care rationing.

Towards real-time monitoring of COVID-19 nosocomial clusters using SARS-CoV-2 genomes in a university hospital of the French Alps

OBJECTIVES

Experience of Nextstrain [1,2] and its approach adapted to the local context encouraged us to carry out real-time monitoring of COVID-19 nosocomial clusters in our establishment, the Grenoble Alpes University Hospital.

PATIENTS AND METHODS, RESULTS

Through identification from electronic health records of nosocomial pathways and clusters and calculation of genetic distances from sequenced samples of COVID-19 patients, we were able to identify potential nosocomial clusters in very close to real time with a significant time saving compared to classical epidemiological surveillance, and to better understand and characterize nosocomial clusters.

CONCLUSION

Through early detection and characterization of clusters, we may prevent infection of our patients by further implementing the appropriate measures.

Mutational Patterns Observed in SARS-CoV-2 Genomes Sampled From Successive Epochs Delimited by Major Public Health Events in Ontario, Canada: Genomic Surveillance Study

BACKGROUND

The emergence of SARS-CoV-2 variants with mutations associated with increased transmissibility and virulence is a public health concern in Ontario, Canada. Characterizing how the mutational patterns of the SARS-CoV-2 genome have changed over time can shed light on the driving factors, including selection for increased fitness and host immune response, that may contribute to the emergence of novel variants. Moreover, the study of SARS-CoV-2 in the microcosm of Ontario, Canada can reveal how different province-specific public health policies over time may be associated with observed mutational patterns as a model system.

OBJECTIVE

This study aimed to perform a comprehensive analysis of single base substitution (SBS) types, counts, and genomic locations observed in SARS-CoV-2 genomic sequences sampled in Ontario, Canada. Comparisons of mutational patterns were conducted between sequences sampled during 4 different epochs delimited by major public health events to track the evolution of the SARS-CoV-2 mutational landscape over 2 years.

METHODS

In total, 24,244 SARS-CoV-2 genomic sequences and associated metadata sampled in Ontario, Canada from January 1, 2020, to December 31, 2021, were retrieved from the Global Initiative on Sharing All Influenza Data database. Sequences were assigned to 4 epochs delimited by major public health events based on the sampling date. SBSs from each SARS-CoV-2 sequence were identified relative to the MN996528.1 reference genome. Catalogues of SBS types and counts were generated to estimate the impact of selection in each open reading frame, and identify mutation clusters. The estimation of mutational fitness over time was performed using the Augur pipeline.

RESULTS

The biases in SBS types and proportions observed support previous reports of host antiviral defense activity involving the SARS-CoV-2 genome. There was an increase in U>C substitutions associated with adenosine deaminase acting on RNA (ADAR) activity uniquely observed during Epoch 4. The burden of novel SBSs observed in SARS-CoV-2 genomic sequences was the greatest in Epoch 2 (median 5), followed by Epoch 3 (median 4). Clusters of SBSs were observed in the spike protein open reading frame, ORF1a, and ORF3a. The high proportion of nonsynonymous SBSs and increasing dN/dS metric (ratio of nonsynonymous to synonymous mutations in a given open reading frame) to above 1 in Epoch 4 indicate positive selection of the spike protein open reading frame.

CONCLUSIONS

Quantitative analysis of the mutational patterns of the SARS-CoV-2 genome in the microcosm of Ontario, Canada within early consecutive epochs of the pandemic tracked the mutational dynamics in the context of public health events that instigate significant shifts in selection and mutagenesis. Continued genomic surveillance of emergent variants will be useful for the design of public health policies in response to the evolving COVID-19 pandemic.

Tracing the First Days of the SARS-CoV-2 Pandemic in Greece and the Role of the First Imported Group of Travelers

The first SARS-CoV-2 case in Greece was confirmed on February 26, 2020, and since then, multiple strains have circulated the country, leading to regional and country-wide outbreaks. Our aim is to enlighten the events that took place during the first days of the SARS-CoV-2 pandemic in Greece, focusing on the role of the first imported group of travelers. We used whole-genome SARS-CoV-2 sequences obtained from the infected travelers of the group as well as Greece-derived and globally subsampled sequences and applied dedicated phylogenetics and phylodynamics tools as well as in-house-developed bioinformatics pipelines. Our analyses reveal the genetic variants circulating in Greece during the first days of the pandemic and the role of the group's imported strains in the course of the first pandemic wave in Greece. The strain that dominated in Greece throughout the first wave, bearing the D614G mutation, was primarily imported from a certain group of travelers, while molecular and clinical data suggest that the infection of the travelers occurred in Egypt. Founder effects early in the pandemic are important for the success of certain strains, as those arriving early, several times, and to diverse locations lead to the formation of large transmission clusters that can be estimated using molecular epidemiology approaches and can be a useful surveillance tool for the prioritization of nonpharmaceutical interventions and combating present and future outbreaks. IMPORTANCE The strain that dominated in Greece during the first pandemic wave was primarily imported from a group of returning travelers in February 2020, while molecular and clinical data suggest that the origin of the transmission was Egypt. The observed molecular transmission clusters reflect the transmission dynamics of this particular strain bearing the D614G mutation while highlighting the necessity of their use as a surveillance tool for the prioritization of nonpharmaceutical interventions and combating present and future outbreaks.

Reversions to consensus are positively selected in HIV-1 and bias substitution rate estimates

Human immunodeficiency virus 1 (HIV-1) is a rapidly evolving virus able to evade host immunity through rapid adaptation during chronic infection. The HIV-1 group M has diversified since its zoonosis into several subtypes at a rate of the order of 10-3 changes per site per year. This rate varies between different parts of the genome, and its inference is sensitive to the timescale and diversity spanned by the sequence data used. Higher rates are estimated on short timescales and particularly for within-host evolution, while rate estimates spanning decades or the entire HIV-1 pandemic tend to be lower. The underlying causes of this difference are not well understood. We investigate here the role of rapid reversions toward a preferred evolutionary sequence state on multiple timescales. We show that within-host reversion mutations are under positive selection and contribute substantially to sequence turnover, especially at conserved sites. We then use the rates of reversions and non-reversions estimated from longitudinal within-host data to parameterize a phylogenetic sequence evolution model. Sequence simulation of this model on HIV-1 phylogenies reproduces diversity and apparent evolutionary rates of HIV-1 in gag and pol, suggesting that a tendency to rapidly revert to a consensus-like state can explain much of the time dependence of evolutionary rate estimates in HIV-1.

Genomics-informed outbreak investigations of SARS-CoV-2 using civet

The scale of data produced during the SARS-CoV-2 pandemic has been unprecedented, with more than 13 million sequences shared publicly at the time of writing. This wealth of sequence data provides important context for interpreting local outbreaks. However, placing sequences of interest into national and international context is difficult given the size of the global dataset. Often outbreak investigations and genomic surveillance efforts require running similar analyses again and again on the latest dataset and producing reports. We developed civet (cluster investigation and virus epidemiology tool) to aid these routine analyses and facilitate virus outbreak investigation and surveillance. Civet can place sequences of interest in the local context of background diversity, resolving the query into different 'catchments' and presenting the phylogenetic results alongside metadata in an interactive, distributable report. Civet can be used on a fine scale for clinical outbreak investigation, for local surveillance and cluster discovery, and to routinely summarise the virus diversity circulating on a national level. Civet reports have helped researchers and public health bodies feedback genomic information in the appropriate context within a timeframe that is useful for public health.

Surveillance and Molecular Characterization of SARS-CoV-2 Infection in Non-Human Hosts in Gujarat, India

Since December 2019, Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) has been spreading worldwide, triggering one of the most challenging pandemics in the human population. In light of the reporting of this virus in domestic and wild animals from several parts of the world, a systematic surveillance study was conceptualized to detect SARS-CoV-2 among species of veterinary importance. Nasal and/or rectal samples of 413 animals (dogs n= 195, cattle n = 64, horses n = 42, goats n = 41, buffaloes n = 39, sheep n = 19, cats n = 6, camels n = 6, and a monkey n = 1) were collected from different places in the Gujarat state of India. RNA was extracted from the samples and subjected to RT-qPCR-based quantification of the target sequences in viral nucleoprotein (N), spike (S), and ORF1ab genes. A total of 95 (23.79%) animals were found positive, comprised of n = 67 (34.35%) dogs, n= 15 (23.43%) cattle, and n = 13 (33.33%) buffaloes. Whole SARS-CoV-2 genome sequencing was done from one sample (ID-A4N, from a dog), where 32 mutations, including 29 single-nucleotide variations (SNV) and 2 deletions, were detected. Among them, nine mutations were located in the receptor binding domain of the spike (S) protein. The consequent changes in the amino acid sequence revealed T19R, G142D, E156-, F157-, A222V, L452R, T478K, D614G, and P681R mutations in the S protein and D63G, R203M, and D377Y in the N protein. The lineage assigned to this SARS-CoV-2 sequence is B.1.617.2. Thus, the present study highlights the transmission of SARS-CoV-2 infection from human to animals and suggests being watchful for zoonosis.

Genomic and structural mechanistic insight to reveal the differential infectivity of omicron and other variants of concern

BACKGROUND

The genome of SARS-CoV-2, is mutating rapidly and continuously challenging the management and preventive measures adopted and recommended by healthcare agencies. The spike protein is the main antigenic site that binds to the host receptor hACE-2 and is recognised by antibodies. Hence, the mutations in this site were analysed to assess their role in differential infectivity of lineages having these mutations, rendering the characterisation of these lineages as variants of concern (VOC) and variants of interest (VOI).

METHODS

In this work, we examined the genome sequence of SARS-CoV-2 VOCs and their phylogenetic relationships with the other PANGOLIN lineages. The mutational landscape of WHO characterized variants was determined and mutational diversity was compared amongst the different severity groups. We then computationally studied the structural impact of the mutations in receptor binding domain of the VOCs. The binding affinity was quantitatively determined by molecular dynamics simulations and free energy calculations.

RESULTS

The mutational frequency, as well as phylogenetic distance, was maximum in the case of omicron followed by the delta variant. The maximum binding affinity was for delta variant followed by the Omicron variant. The increased binding affinity of delta strain followed by omicron as compared to other variants and wild type advocates high transmissibility and quick spread of these two variants and high severity of delta variant.

CONCLUSION

This study delivers a foundation for discovering the improved binding knacks and structural features of SARS-CoV-2 variants to plan novel therapeutics and vaccine candidates against the virus.

Genomic diversity of SARS-CoV-2 in Pakistan during the fourth wave of pandemic

The emergence of different variants of concern of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in upsurges of coronavirus disease 2019 (COVID-19) cases around the globe. Pakistan faced the fourth wave of COVID-19 from July to August 2021 with 314,786 cases. To understand the genomic diversity of circulating SARS-CoV-2 strains during the fourth wave of the pandemic in Pakistan, this study was conducted. The samples from 140 COVID-19-positive patients were subjected to whole-genome sequencing using the iSeq Sequencer by Illumina. The results showed that 97% (n = 136) of isolates belonged to the delta variant while three isolates belonged to alpha and only one isolate belonged to the beta variant. Among delta variant cases, 20.5% (n = 28) isolates were showing B.1.617.2 while 23.5% (n = 25), 17.59% (n = 19), 14.81% (n = 16), and 13.89% (n = 15) of isolates were showing AY.108, AY.43 AY.127, and AY.125 lineages, respectively. Islamabad was found to be the most affected city with 65% (n = 89) of delta variant cases, followed by Karachi (17%, n = 23), and Rawalpindi (10%, n = 14). Apart from the characteristic spike mutations (T19R, L452R, T478K, P681R, and D950N) of the delta variant, the sublineages exhibited other spike mutations as E156del, G142D, T95I, A222V, G446V, K529N, N532S, Q613H, and V483A. The phylogenetic analysis revealed the introductions from Singapore, the United Kingdom, and Germany. This study highlights the circulation of delta variants (B.1.617.2 and sublineages) during the fourth wave of pandemic in Pakistan.

Contrasting Distribution of SARS-CoV-2 Lineages across Multiple Rounds of Pandemic Waves in West Bengal, the Gateway of East and North-East States of India

The evolution of viral variants and their impact on viral transmission have been an area of considerable importance in this pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We analyzed the viral variants in different phases of the pandemic in West Bengal, a state in India that is important geographically, and compared the variants with other states like Delhi, Maharashtra, and Karnataka, located in other regions of the country. We have identified 57 pango-lineages in 3,198 SARS-CoV-2 genomes, alteration in their distribution, as well as contrasting profiles of amino acid mutational dynamics across different waves in different states. The evolving characteristics of Delta (B.1.617.2) sublineages and alterations in hydrophobicity profiles of the viral proteins caused by these mutations were also studied. Additionally, implications of predictive host miRNA binding/unbinding to emerging spike or nucleocapsid mutations were highlighted. Our results throw considerable light on interesting aspects of the viral genomic variation and provide valuable information for improved understanding of wave-defining mutations in unfolding the pandemic. IMPORTANCE Multiple waves of infection were observed in many states in India during the coronavirus disease 2019 (COVID19) pandemic. Fine-scale evolution of major SARS-CoV-2 lineages and sublineages during four wave-window categories: Pre-Wave 1, Wave 1, Pre-Wave 2, and Wave 2 in four major states of India: Delhi (North), Maharashtra (West), Karnataka (South), and West Bengal (East) was studied using large-scale virus genome sequencing data. Our comprehensive analysis reveals contrasting molecular profiles of the wave-defining mutations and their implications in host miRNA binding/unbinding of the lineages in the major states of India.

Assessing the Impact of SARS-CoV-2 Lineages and Mutations on Patient Survival

OBJECTIVES

More than two years into the COVID-19 pandemic, SARS-CoV-2 still remains a global public health problem. Successive waves of infection have produced new SARS-CoV-2 variants with new mutations for which the impact on COVID-19 severity and patient survival is uncertain.

METHODS

A total of 764 SARS-CoV-2 genomes, sequenced from COVID-19 patients, hospitalized from 19th February 2020 to 30 April 2021, along with their clinical data, were used for survival analysis.

RESULTS

A significant association of B.1.1.7, the alpha lineage, with patient mortality (log hazard ratio (LHR) = 0.51, C.I. = [0.14,0.88]) was found upon adjustment by all the covariates known to affect COVID-19 prognosis. Moreover, survival analysis of mutations in the SARS-CoV-2 genome revealed 27 of them were significantly associated with higher mortality of patients. Most of these mutations were located in the genes coding for the S, ORF8, and N proteins.

CONCLUSIONS

This study illustrates how a combination of genomic and clinical data can provide solid evidence for the impact of viral lineage on patient survival.

Evolutionary traits of Tick-borne encephalitis virus: Pervasive non-coding RNA structure conservation and molecular epidemiology

Tick-borne encephalitis virus (TBEV) is the aetiological agent of tick-borne encephalitis, an infectious disease of the central nervous system that is often associated with severe sequelae in humans. While TBEV is typically classified into three subtypes, recent evidence suggests a more varied range of TBEV subtypes and lineages that differ substantially in the architecture of their 3ʹ untranslated region (3ʹUTR). Building on comparative genomic approaches and thermodynamic modelling, we characterize the TBEV UTR structureome diversity and propose a unified picture of pervasive non-coding RNA structure conservation. Moreover, we provide an updated phylogeny of TBEV, building on more than 220 publicly available complete genomes, and investigate the molecular epidemiology and phylodynamics with Nextstrain, a web-based visualization framework for real-time pathogen evolution.

Accelerated SARS-CoV-2 intrahost evolution leading to distinct genotypes during chronic infection

The chronic infection hypothesis for novel SARS-CoV-2 variant emergence is increasingly gaining credence following the appearance of Omicron. Here we investigate intrahost evolution and genetic diversity of lineage B.1.517 during a SARS-CoV-2 chronic infection lasting for 471 days (and still ongoing) with consistently recovered infectious virus and high viral loads. During the infection, we found an accelerated virus evolutionary rate translating to 35 nucleotide substitutions per year, approximately two-fold higher than the global SARS-CoV-2 evolutionary rate. This intrahost evolution led to the emergence and persistence of at least three genetically distinct genotypes suggesting the establishment of spatially structured viral populations continually reseeding different genotypes into the nasopharynx. Finally, using unique molecular indexes for accurate intrahost viral sequencing, we tracked the temporal dynamics of genetic diversity to identify advantageous mutations and highlight hallmark changes for chronic infection. Our findings demonstrate that untreated chronic infections accelerate SARS-CoV-2 evolution, ultimately providing opportunity for the emergence of genetically divergent and potentially highly transmissible variants as seen with Delta and Omicron.

SARS-COV-2 RBD (Receptor binding domain) mutations and variants (A sectional-analytical study)

An essential step in SARS-CoV-2 infection is binding the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein to the ACE2 receptor on the surface of host cells. Therefore, variation in this region can have crucial effects on clinical outcomes and the emergence of variants of concern (VOCs) and variants of interest (VOIs). In this cross-sectional descriptive study, 54 patients with SARS-COV-2 infection were enrolled. After collecting samples and identifying the virus using the One-Step Real-Time qRT-PCR technique and confirming the viral infection, the region containing the RBD region for detection of any mutations was amplified using the Nested-PCR method. Finally, to identify probable mutations, the Nested-PCR product was sequenced. Our data show that the most mutant strains in circulation in our population are the delta variant (90.74%), alpha variant (5.56%), and omicron variant (3.70%), respectively. Pangolin Lineages strains were B.1.1.7(Alpha variant), B.1.617.2(Delta variant) and B.1.1.529(Omicron variant). Also, the mutation profile of variants suggests that N501Y, T478K, and D614G amino acid substitutions, are the significant mutations in the alpha and delta variants that are common with the Omicron variant. The highest frequency of clinical signs in the patients were: lung involvement (42.59%); fever, chills (40.74%); body pain (15%), and other signs (1.67%). Our data revealed that SARS-COV-2 RBD region variation results in substituting essential amino acids and the emergence of the new variant. We can consider it as a predictor for monitoring the emergence of variants of concerns and viral outcomes.

SARS-CoV-2: Two Years in the Pandemic: What Have We Observed from Genome Sequencing Results in Lithuania?

SARS-CoV-2 has spread vastly throughout the word. In this study, we focus on the patterns of spread in Lithuania. By analysing the genetically sequenced data of different lineages and their first appearances, we were able to compare the dynamics of spreading of the lineages and recognize the main possible cause. The impact of emigration patterns and international travel on the variety of lineages was also assessed. Results showed different patterns of spread, and while a vast variety of different lineages were brought in by international travel, many of the viral outbreaks were caused by local lineages. It can be concluded that international travel had the most impact on the spread of SARS-CoV-2.

Overlapping Delta and Omicron Outbreaks During the COVID-19 Pandemic: Dynamic Panel Data Estimates

BACKGROUND

The Omicron variant of SARS-CoV-2 is more transmissible than prior variants of concern (VOCs). It has caused the largest outbreaks in the pandemic, with increases in mortality and hospitalizations. Early data on the spread of Omicron were captured in countries with relatively low case counts, so it was unclear how the arrival of Omicron would impact the trajectory of the pandemic in countries already experiencing high levels of community transmission of Delta.

OBJECTIVE

The objective of this study is to quantify and explain the impact of Omicron on pandemic trajectories and how they differ between countries that were or were not in a Delta outbreak at the time Omicron occurred.

METHODS

We used SARS-CoV-2 surveillance and genetic sequence data to classify countries into 2 groups: those that were in a Delta outbreak (defined by at least 10 novel daily transmissions per 100,000 population) when Omicron was first sequenced in the country and those that were not. We used trend analysis, survival curves, and dynamic panel regression models to compare outbreaks in the 2 groups over the period from November 1, 2021, to February 11, 2022. We summarized the outbreaks in terms of their peak rate of SARS-CoV-2 infections and the duration of time the outbreaks took to reach the peak rate.

RESULTS

Countries that were already in an outbreak with predominantly Delta lineages when Omicron arrived took longer to reach their peak rate and saw greater than a twofold increase (2.04) in the average apex of the Omicron outbreak compared to countries that were not yet in an outbreak.

CONCLUSIONS

These results suggest that high community transmission of Delta at the time of the first detection of Omicron was not protective, but rather preluded larger outbreaks in those countries. Outbreak status may reflect a generally susceptible population, due to overlapping factors, including climate, policy, and individual behavior. In the absence of strong mitigation measures, arrival of a new, more transmissible variant in these countries is therefore more likely to lead to larger outbreaks. Alternately, countries with enhanced surveillance programs and incentives may be more likely to both exist in an outbreak status and detect more cases during an outbreak, resulting in a spurious relationship. Either way, these data argue against herd immunity mitigating future outbreaks with variants that have undergone significant antigenic shifts.

ClusTRace, a bioinformatic pipeline for analyzing clusters in virus phylogenies

BACKGROUND

SARS-CoV-2 is the highly transmissible etiologic agent of coronavirus disease 2019 (COVID-19) and has become a global scientific and public health challenge since December 2019. Several new variants of SARS-CoV-2 have emerged globally raising concern about prevention and treatment of COVID-19. Early detection and in-depth analysis of the emerging variants allowing pre-emptive alert and mitigation efforts are thus of paramount importance.

RESULTS

Here we present ClusTRace, a novel bioinformatic pipeline for a fast and scalable analysis of sequence clusters or clades in large viral phylogenies. ClusTRace offers several high-level functionalities including lineage assignment, outlier filtering, aligning, phylogenetic tree reconstruction, cluster extraction, variant calling, visualization and reporting. ClusTRace was developed as an aid for COVID-19 transmission chain tracing in Finland with the main emphasis on fast screening of phylogenies for markers of super-spreading events and other features of concern, such as high rates of cluster growth and/or accumulation of novel mutations.

CONCLUSIONS

ClusTRace provides an effective interface that can significantly cut down learning and operating costs related to complex bioinformatic analysis of large viral sequence sets and phylogenies. All code is freely available from https://bitbucket.org/plyusnin/clustrace/.

Assessing and assuring interoperability of a genomics file format

Motivation

Bioinformatics software tools operate largely through the use of specialized genomics file formats. Often these formats lack formal specification, making it difficult or impossible for the creators of these tools to robustly test them for correct handling of input and output. This causes problems in interoperability between different tools that, at best, wastes time and frustrates users. At worst, interoperability issues could lead to undetected errors in scientific results.

Results

We developed a new verification system, Acidbio, which tests for correct behavior in bioinformatics software packages. We crafted tests to unify correct behavior when tools encounter various edge cases—potentially unexpected inputs that exemplify the limits of the format. To analyze the performance of existing software, we tested the input validation of 80 Bioconda packages that parsed the Browser Extensible Data (BED) format. We also used a fuzzing approach to automatically perform additional testing. Of 80 software packages examined, 75 achieved less than 70% correctness on our test suite. We categorized multiple root causes for the poor performance of different types of software. Fuzzing detected other errors that the manually designed test suite could not. We also created a badge system that developers can use to indicate more precisely which BED variants their software accepts and to advertise the software’s performance on the test suite.

Availability and implementation

Acidbio is available at https://github.com/hoffmangroup/acidbio.

Supplementary information

Supplementary data are available at Bioinformatics online.

Genomics of Post-Vaccination SARS-CoV-2 Infections During the Delta Dominated Second Wave of COVID-19 Pandemic, from Mumbai Metropolitan Region (MMR), India

The present study was initiated to understand the proportion of predominant variants of SARS-CoV-2 in post-vaccination infections during the Delta dominated second wave of COVID-19 in the Mumbai Metropolitan Region (MMR) in India and to understand any mutations selected in the post-vaccination infections or showing association with any patient demographics. Samples were collected (n=166) from severe/moderate/mild COVID-19 patients who were either vaccinated (COVISHIELD/COVAXIN - partial/fully vaccinated) or unvaccinated, from a city hospital and from home isolation patients in MMR. A total of 150 viral genomes were sequenced by Oxford Nanopore sequencing and the data of 136 viral genomes were analyzed for clade/lineage and for identifying mutations. The sequences belonged to three clades (21A, 21I and 21J) and their lineage was identified as either Delta (B.1.617.2) or Delta+ (B.1.617.2 + K417N) or sub-lineages of Delta variant (AY.120/AY.38/AY.99). A total of 620 mutations were identified of which 10 mutations showed an increase in trend with time (May-Oct 2021). Associations of 6 mutations (2 in spike, 3 in orf1a and 1 in nucleocapsid) were shown with milder forms of the disease and one mutation (in orf1a) with partial vaccination status. The results indicate a trend towards reduction in disease severity as the wave progressed. This article is protected by copyright. All rights reserved.

Genetic and Antigenic Characterization of an Expanding H3 Influenza A Virus Clade in U.S. Swine Visualized by Nextstrain

Genetically distinct clades of influenza A virus (IAV) in swine undermine efforts to control the disease. Swine producers commonly use vaccines, and vaccine strains are selected by identifying the most common hemagglutinin (HA) gene from viruses detected in a farm or a region.

Distinct mutations and lineages of SARS-CoV-2 virus in the early phase of COVID-19 pandemic and subsequent 1-year global expansion

A novel coronavirus, SARS-CoV-2, has caused over 274 million cases and over 5.3 million deaths worldwide since it occurred in December 2019 in Wuhan, China. Here we conceptualized the temporospatial evolutionary and expansion dynamics of SARS-CoV-2 by taking a series of the cross-sectional view of viral genomes from early outbreak in January 2020 in Wuhan to the early phase of global ignition in early April, and finally to the subsequent global expansion by late December 2020. Based on the phylogenetic analysis of the early patients in Wuhan, Wuhan/WH04/2020 is supposed to be a more appropriate reference genome of SARS-CoV-2, instead of the first sequenced genome Wuhan-Hu-1. By scrutinizing the cases from the very early outbreak, we found a viral genotype from the Seafood Market in Wuhan featured with two concurrent mutations (i.e., M type) had become the overwhelmingly dominant genotype (95.3%) of the pandemic 1 year later. By analyzing 4013 SARS-CoV-2 genomes from different continents by early April, we were able to interrogate the viral genomic composition dynamics of the initial phase of global ignition over a time span of 14 weeks. Eleven major viral genotypes with unique geographic distributions were also identified. WE1 type, a descendant of M and predominantly witnessed in western Europe, consisted of half of all the cases (50.2%) at the time. The mutations of major genotypes at the same hierarchical level were mutually exclusive, which implies that various genotypes bearing the specific mutations were propagated during human-to-human transmission, not by accumulating hot-spot mutations during the replication of individual viral genomes. As the pandemic was unfolding, we also used the same approach to analyze 261 323 SARS-CoV-2 genomes from the world since the outbreak in Wuhan (i.e., including all the publicly available viral genomes) to recapitulate our findings over 1-year time span. By December 25, 2020, 95.3% of global cases were M type and 93.0% of M-type cases were WE1. In fact, at present all the five variants of concern (VOC) are the descendants of WE1 type. This study demonstrates that viral genotypes can be utilized as molecular barcodes in combination with epidemiologic data to monitor the spreading routes of the pandemic and evaluate the effectiveness of control measures. Moreover, the dynamics of viral mutational spectrum in the study may help the early identification of new strains in patients to reduce further spread of infection, guide the development of molecular diagnosis and vaccines against COVID-19, and help assess their accuracy and efficacy in real world at real time.

Phylogenetic-based inference reveals distinct transmission dynamics of SARS-CoV-2 lineages Gamma and P.2 in Brazil

The COVID-19 epidemic in Brazil experienced two major lineage replacements until mid-2021. The first was driven by lineage P.2, in late 2020, and the second by lineage Gamma, in early 2021. To understand how these SARS-CoV-2 lineages spread in Brazil, we analyzed 11,724 genomes collected throughout the country between September 2020 and April 2021. Our findings indicate that lineage P.2 probably emerged in July 2020 in the Rio de Janeiro state and Gamma in November 2020 in the Amazonas state. Both states were the main hubs of viral disseminations to other Brazilian locations. We estimate that Gamma was 1.56-3.06 times more transmissible than P.2 in Rio de Janeiro and that the median effective reproductive number (Re) of Gamma varied according to the geographic context (Re = 1.59-3.55). In summary, our findings support that lineage Gamma was more transmissible and spread faster than P.2 in Brazil.

Rapid and parallel adaptive mutations in spike S1 drive clade success in SARS-CoV-2

The SARS-CoV-2 pandemic has resulted in numerous virus variants, some of which have altered receptor-binding or antigenic phenotypes. Here, we quantify the degree to which adaptive evolution is driving the accumulation of mutations across the genome. We correlate clade growth with mutation accumulation, compare rates of nonsynonymous to synonymous divergence, assess temporal clustering of mutations, and evaluate the evolutionary success of individual mutations. We find that spike S1 is the focus of adaptive evolution but also identify positively selected mutations in other proteins (notably Nsp6) that are sculpting the evolutionary trajectory of SARS-CoV-2. Adaptive changes in S1 accumulated rapidly, resulting in a remarkably high ratio of nonsynonymous to synonymous divergence that is 2.5× greater than that observed in influenza hemagglutinin HA1 at the beginning of the 2009 H1N1 pandemic. These findings uncover a high degree of adaptation in S1 and suggest that SARS-CoV-2 might undergo antigenic drift.

Genomic surveillance reveals the detection of SARS-CoV-2 delta, beta, and gamma VOCs during the third wave in Pakistan

SARS-CoV-2 variants of concern (VOCs) have emerged worldwide and gained significant importance due to their high transmissibility and global spread, thus meriting close monitoring. In Pakistan, limited information is available on circulation of these variants as the alpha variant has been reported the main circulating lineage. The current study was designed to detect and explore the genomic diversity of SARS-CoV-2 lineages circulating during the third wave of the pandemic in the indigenous population. From May 01 to June 09, 2021, a total of 16 689 samples were tested using TaqPath™ COVID-19 kit for the presence of SARS-CoV-2. Overall, 2562 samples (15.4%) were COVID-19 positive. Out of these positive samples, 2124 (12.7%) did not show the spike gene amplification (spike gene target failure ([SGTF]), whereas 438 (2.6%) showed spike gene amplification (non-SGTF). A subset (n = 58/438) of non-SGTF samples were randomly selected for whole-genome sequencing. Among VOCs, 45% (n = 26/58) were delta, 46% (n = 27/58) were beta, and one was gamma variant. The delta variant cases were reported mainly from Islamabad (n = 15; 58%) followed by Rawalpindi and Azad Kashmir (n = 1; 4% each). Beta variant cases originated mainly from Karachi (n = 8; 30%) and Islamabad (n = 11; 41%) and the gamma variant case was reported in a traveler from Italy. The delta, beta, and gamma variants possessed lineage-specific spike mutations. Notably, two rare mutations (E484Q and L5F) were found in the delta variant. Furthermore, in the beta variant, two significant rare non-synonymous spike mutations (A879S and K444R) were also reported. High prevalence of beta and delta variants in local population may increase the number of cases in the near future and provides an early warning to national health authorities to take timely decisions and devise suitable interventions to contain a possible fourth wave.

Transmission from vaccinated individuals in a large SARS-CoV-2 Delta variant outbreak

An outbreak of over 1,000 COVID-19 cases in Provincetown, Massachusetts (MA), in July 2021-the first large outbreak mostly in vaccinated individuals in the US-prompted a comprehensive public health response, motivating changes to national masking recommendations and raising questions about infection and transmission among vaccinated individuals. To address these questions, we combined viral genomic and epidemiological data from 467 individuals, including 40% of outbreak-associated cases. The Delta variant accounted for 99% of cases in this dataset; it was introduced from at least 40 sources, but 83% of cases derived from a single source, likely through transmission across multiple settings over a short time rather than a single event. Genomic and epidemiological data supported multiple transmissions of Delta from and between fully vaccinated individuals. However, despite its magnitude, the outbreak had limited onward impact in MA and the US overall, likely due to high vaccination rates and a robust public health response.

Has Omicron Changed the Evolution of the Pandemic?

BACKGROUND

Variants of the SARS-CoV-2 virus carry differential risks to public health. The Omicron (B.1.1.529) variant, first identified in Botswana on November 11, 2021, has spread globally faster than any previous variant of concern. Understanding the transmissibility of Omicron is vital in the development of public health policy.

OBJECTIVE

The aim of this study is to compare SARS-CoV-2 outbreaks driven by Omicron to those driven by prior variants of concern in terms of both the speed and magnitude of an outbreak.

METHODS

We analyzed trends in outbreaks by variant of concern with validated surveillance metrics in several southern African countries. The region offers an ideal setting for a natural experiment given that most outbreaks thus far have been driven primarily by a single variant at a time. With a daily longitudinal data set of new infections, total vaccinations, and cumulative infections in countries in sub-Saharan Africa, we estimated how the emergence of Omicron has altered the trajectory of SARS-CoV-2 outbreaks. We used the Arellano-Bond method to estimate regression coefficients from a dynamic panel model, in which new infections are a function of infections yesterday and last week. We controlled for vaccinations and prior infections in the population. To test whether Omicron has changed the average trajectory of a SARS-CoV-2 outbreak, we included an interaction between an indicator variable for the emergence of Omicron and lagged infections.

RESULTS

The observed Omicron outbreaks in this study reach the outbreak threshold within 5-10 days after first detection, whereas other variants of concern have taken at least 14 days and up to as many as 35 days. The Omicron outbreaks also reach peak rates of new cases that are roughly 1.5-2 times those of prior variants of concern. Dynamic panel regression estimates confirm Omicron has created a statistically significant shift in viral spread.

CONCLUSIONS

The transmissibility of Omicron is markedly higher than prior variants of concern. At the population level, the Omicron outbreaks occurred more quickly and with larger magnitude, despite substantial increases in vaccinations and prior infections, which should have otherwise reduced susceptibility to new infections. Unless public health policies are substantially altered, Omicron outbreaks in other countries are likely to occur with little warning.

Rapid and parallel adaptive mutations in spike S1 drive clade success in SARS-CoV-2

Given the importance of variant SARS-CoV-2 viruses with altered receptor-binding or antigenic phenotypes, we sought to quantify the degree to which adaptive evolution is driving accumulation of mutations in the SARS-CoV-2 genome. Here we assessed adaptive evolution across genes in the SARS-CoV-2 genome by correlating clade growth with mutation accumulation as well as by comparing rates of nonsynonymous to synonymous divergence, clustering of mutations across the SARS-CoV-2 phylogeny and degree of convergent evolution of individual mutations. We find that spike S1 is the focus of adaptive evolution, but also identify positively-selected mutations in other genes that are sculpting the evolutionary trajectory of SARS-CoV-2. Adaptive changes in S1 accumulated rapidly, resulting in a remarkably high ratio of nonsynonymous to synonymous divergence that is 2.5X greater than that observed in HA1 at the beginning of the 2009 H1N1 pandemic.