Viral Sequences Research Articles

A Systematic Bioinformatics Approach for Mapping the Minimal Set of a Viral Peptidome

AbstractSequence changes in viral genomes generate protein sequence diversity that enables viruses to evade the host immune system, hindering the development of effective preventive and therapeutic interventions. The massive proliferation of sequence data provides unprecedented opportunities to study viral adaptation and evolution. An alignment‐free approach removes various restrictions posed by an alignment‐dependent approach for studying sequence diversity. The publicly available tool, UNIQmin, offers an alignment‐free approach for studying viral sequence diversity at any given rank of taxonomy lineage and is big data ready. The tool performs an exhaustive search to determine the minimal set of sequences required to capture the peptidome diversity within a given dataset. This compression is possible through the removal of identical sequences and unique sequences that do not contribute effectively to the peptidome diversity pool. Herein, we describe a detailed four‐part protocol utilizing UNIQmin to generate the minimal set for the purpose of viral diversity analyses, alignment‐free at any rank of the taxonomy lineage, using the recent global public health threat Monkeypox virus (MPX) sequence data as a case study. The protocol enables a systematic bioinformatics approach to study sequence diversity across taxonomic lineages, which is crucial for our future preparedness against viral epidemics. This is particularly important when data are abundant, freely available, and alignment is not an option. © 2024 Wiley Periodicals LLC.Basic Protocol 1: Tool installation and input file preparationBasic Protocol 2: Generation of a minimal set of sequences for a given datasetBasic Protocol 3: Comparative minimal set analysis across taxonomic lineage ranksBasic Protocol 4: Factors affecting the minimal set of sequences

Prediction of viral families and hosts of single-stranded RNA viruses based on K-Mer coding from phylogenetic gene sequences

There are billions of virus species worldwide, and viruses, the smallest parasitic entities, pose a serious threat. Therefore, fighting associated disorders requires an understanding of the genetic structure of viruses. Considering the wide diversity and rapid evolution of viruses, there is a critical need to quickly and accurately classify viral species and their potential hosts to better understand transmission dynamics, facilitating the development of targeted therapies. Recognizing this, this study has investigated the classes of RNA viruses based on their genomic sequences using Machine Learning (ML) and Deep Learning (DL) models. The PhyVirus dataset, consisting of pathogenic Single-stranded RNA viruses of Baltimore group four (+ssRNA) and five (-ssRNA) with different hosts and species, was analyzed. The dataset containing viral gene sequences was analyzed using the K-Mer coding technique, which is based on base words of various lengths. The study used classical ML algorithms (Random Forest, Gradient Boosting and Extra Trees) and the Fully Connected Deep Neural Network, a Deep Learning algorithm, to predict viral families and hosts. Detailed analyses were performed on the classifier performance in scenarios with different train-test ratios and different word lengths (k-values) for K-Mer. The observed results show that Fully Connected Deep Neural Network has a high success rate of 99.60 % in predicting virus families. In predicting virus hosts, the Extra Trees classifier achieved the highest success rate of 81.53 %. This study is considered to be the first classification study in the literature on this dataset, which has a very large family and host diversity consisting of gene sequences of Single-stranded RNA viruses. Our detailed investigations on how varying word lengths based on K-Mer coding in gene sequences affect the classification into viral families and hosts make this study particularly valuable. This study shows that ML and DL methods have the potential to produce valuable results in phylogenetic studies. In addition, the results and high-performance values show that these methods can be successfully used in regenerative applications of gene sequences or in studies such as the elimination of losses in gene sequences.

Viral sequencing to inform the global elimination of dog-mediated rabies - a systematic review

Viral sequencing to inform the global elimination of dog-mediated rabies - a systematic review

A metagenomic analysis of the phase 2 Anopheles gambiae 1000 genomes dataset reveals a wide diversity of cobionts associated with field collected mosquitoes

The Anopheles gambiae 1000 Genomes (Ag1000G) Consortium previously utilized deep sequencing methods to catalogue genetic diversity across African An. gambiae populations. We analyzed the complete datasets of 1142 individually sequenced mosquitoes through Microsoft Premonition’s Bayesian mixture model based (BMM) metagenomics pipeline. All specimens were confirmed as either An. gambiae sensu stricto (s.s.) or An. coluzzii with a high degree of confidence ( > 98% identity to reference). Homo sapiens DNA was identified in all specimens indicating contamination may have occurred either at the time of specimen collection, preparation and/or sequencing. We found evidence of vertebrate hosts in 162 specimens. 59 specimens contained validated Plasmodium falciparum reads. Human hepatitis B and primate erythroparvovirus-1 viral sequences were identified in fifteen and three mosquito specimens, respectively. 478 of the 1,142 specimens were found to contain bacterial reads and bacteriophage-related contigs were detected in 27 specimens. This analysis demonstrates the capacity of metagenomic approaches to elucidate important vector-host-pathogen interactions of epidemiological significance.

Characterization of genotype V Japanese encephalitis virus isolates from Republic of Korea

ABSTRACT Japanese encephalitis (JE), caused by the Japanese encephalitis virus (JEV) infection, continues to pose significant public health challenges worldwide despite efficient vaccines. The virus is classified into five genotypes, among which genotype V (GV) was not detected for a long period after its initial isolation in 1952, until reports emerged from China and the Republic of Korea (ROK) since 2009. The characteristics of the virus are crucial in estimating its potential epidemiological impact. However, characterization of GV JEVs has so far been limited to two strains: Muar, the original isolate, and XZ0934, isolated in China. Two additional ROK GV JEV isolates, NCCP 43279 and NCCP 43413, are currently available, but their characteristics have not been explored. Our phylogenetic analysis revealed that GV virus sequences from the ROK segregate into two clades. NCCP 43279 and NCCP 43413 belong to different clades and exhibit distinct in vitro phenotypes. NCCP 43279 forms larger plaques but demonstrates inefficient propagation in cell culture compared to NCCP 43413. In vivo, NCCP 43279 induces higher morbidity and mortality in mice than NCCP 43413. Notably, NCCP 43279 shows more severe blood–brain barrier damage, suggesting superior brain invasion capabilities. Consistent with its higher virulence, NCCP 43279 displays more pronounced histopathological and immunopathological outcomes. In conclusion, our study confirms that the two ROK isolates are not only classified into different clades but also exhibit distinct in vitro and in vivo characteristics.

IAVCP (Influenza A Virus Consensus and Phylogeny): Automatic Identification of the Genomic Sequence of the Influenza A Virus from High-Throughput Sequencing Data.

Recently, high-throughput sequencing of influenza A viruses has become a routine test. It should be noted that the extremely high diversity of the influenza A virus complicates the task of determining the sequences of all eight genome segments. For a fast and accurate analysis, it is necessary to select the most suitable reference for each segment. At the same time, there is no standardized method in the field of decoding sequencing results that allows the user to update the sequence databases to which the reads obtained by virus sequencing are compared. The IAVCP (influenza A virus consensus and phylogeny) was developed with the goal of automatically analyzing high-throughput sequencing data of influenza A viruses. Its goals include the extraction of a consensus genome directly from paired raw reads. In addition, the pipeline enables the identification of potential reassortment events in the evolutionary history of the virus of interest by analyzing the topological structure of phylogenetic trees that are automatically reconstructed.

Genomic characterization of circulating human respiratory syncytial viruses A and B in Kuwait using whole-genome sequencing.

The human respiratory syncytial virus (RSV) is considered one of the most common viruses that infect children globally. The virus is known to have extensive gene sequence variability within and between RSV groups A and B globally; however, there is no information on the whole-genome characterization and diversity of RSV in Kuwait. Therefore, this study aimed to sequence the entire genome of RSV strains isolated from patients with acute respiratory tract infection (ARTI) in Kuwait. Therefore, this study aimed to sequence the entire genome of RSV strains isolated from patients with ARTI in Kuwait. Between January 2020 and September 2022, 7,093 respiratory samples were collected from hospitalized infants, children, and adults and were analyzed for respiratory viruses by multiplex real-time PCR. Whole-genome sequencing using the Oxford Nanopore sequencing technology was performed on 84 RSV-positive samples. The results revealed a higher prevalence of group A (76%) than group B (24%) RSV isolates. Phylogenetic analysis showed that RSV-A strains clustered with the GA2.3.5 sub-genotype and RSV-B strains clustered with the GB5.0.5a sub-genotype; however, forming new lineages of RSV-A and RSV-B circulated in Kuwait during this period. Genetic variability was higher among the group A viruses than group B viruses, and the rate of synonymous and missense mutations was high in genes other than the G protein-coding gene. We also detected several known and unique molecular markers in different protein-coding genes. This is the first study in Kuwait to characterize the whole genomes of RSV A and B to identify the circulating genotypes, comprehend the genetic diversity and the evolution of the virus, and identify important genetic markers associated with specific genotypes.IMPORTANCEWhole-genome sequencing of respiratory syncytial virus (RSV) strains in Kuwait using MinION Nanopore technology was used to characterize and analyze the genotypes and sub-genotypes of the RSV circulating among patients with acute respiratory tract infections in Kuwait. This study also identified known and unknown gene mutations and imported genetic markers associated with specific genotypes. These results will assist in establishing a framework for RSV classification and allow for a better consideration of the mechanisms leading to the generation of diversity of RSV. In addition, these data will allow a comparison of vaccine viruses with those in Kuwait, providing useful insights into future vaccine and therapy strategies for RSV in Kuwait.

Impact of viral telomeric repeat sequences on herpesvirus vector vaccine integration and persistence.

Marek's disease virus (MDV) vaccines were the first vaccines that protected against cancer. The avirulent turkey herpesvirus (HVT) was widely employed and protected billions of chickens from a deadly MDV infection. It is also among the most common vaccine vectors providing protection against a plethora of pathogens. HVT establishes latency in T-cells, allowing the vaccine virus to persist in the host for life. Intriguingly, the HVT genome contains telomeric repeat arrays (TMRs) at both ends; however, their role in the HVT life cycle remains elusive. We have previously shown that similar TMRs in the MDV genome facilitate its integration into host telomeres, which ensures efficient maintenance of the virus genome during latency and tumorigenesis. In this study, we investigated the role of the TMRs in HVT genome integration, latency, and reactivation in vitro and in vivo. Additionally, we examined HVT infection of feather follicles. We generated an HVT mutant lacking both TMRs (vΔTMR) that efficiently replicated in cell culture. We could demonstrate that wild type HVT integrates at the ends of chromosomes containing the telomeres in T-cells, while integration was severely impaired in the absence of the TMRs. To assess the role of TMRs in vivo, we infected one-day-old chickens with HVT or vΔTMR. vΔTMR loads were significantly reduced in the blood and hardly any virus was transported to the feather follicle epithelium where the virus is commonly shed. Strikingly, latency in the spleen and reactivation of the virus were severely impaired in the absence of the TMRs, indicating that the TMRs are crucial for the establishment of latency and reactivation of HVT. Our findings revealed that the TMRs facilitate integration of the HVT genome into host chromosomes, which ensures efficient persistence in the host, reactivation, and transport of the virus to the skin.

Discovery of novel RNA viruses through analysis of fungi-associated next-generation sequencing data

BackgroundLike all other species, fungi are susceptible to infection by viruses. The diversity of fungal viruses has been rapidly expanding in recent years due to the availability of advanced sequencing technologies. However, compared to other virome studies, the research on fungi-associated viruses remains limited.ResultsIn this study, we downloaded and analyzed over 200 public datasets from approximately 40 different Bioprojects to explore potential fungal-associated viral dark matter. A total of 12 novel viral sequences were identified, all of which are RNA viruses, with lengths ranging from 1,769 to 9,516 nucleotides. The amino acid sequence identity of all these viruses with any known virus is below 70%. Through phylogenetic analysis, these RNA viruses were classified into different orders or families, such as Mitoviridae, Benyviridae, Botourmiaviridae, Deltaflexiviridae, Mymonaviridae, Bunyavirales, and Partitiviridae. It is possible that these sequences represent new taxa at the level of family, genus, or species. Furthermore, a co-evolution analysis indicated that the evolutionary history of these viruses within their groups is largely driven by cross-species transmission events.ConclusionsThese findings are of significant importance for understanding the diversity, evolution, and relationships between genome structure and function of fungal viruses. However, further investigation is needed to study their interactions.

Whole-Genome Sequencing and Genetic Diversity of Human Respiratory Syncytial Virus in Patients with Influenza-like Illness in Sicily (Italy) from 2017 to 2023.

Monitoring the genetic variability of human respiratory syncytial virus (hRSV) is of paramount importance, especially for the potential implication of key antigenic mutations on the emergence of immune escape variants. Thus, to describe the genetic diversity and evolutionary dynamics of hRSV circulating in Sicily (Italy), a total of 153 hRSV whole-genome sequences collected from 770 hRSV-positive subjects between 2017 and 2023, before the introduction of expanded immunization programs into the population, were investigated. The phylogenetic analyses indicated that the genotypes GA.2.3.5 (ON1) for hRSV-A and GB.5.0.5a (BA9) for hRSV-B co-circulated in our region. Amino acid (AA) substitutions in the surface and internal proteins were evaluated, including the F protein antigenic sites, as the major targets of immunoprophylactic monoclonal antibodies and vaccines. Overall, the proportion of AA changes ranged between 1.5% and 22.6% among hRSV-A, whereas hRSV-B varied in the range 0.8-16.9%; the latter was more polymorphic than hRSV-A within the key antigenic sites. No AA substitutions were found at site III of both subgroups. Although several non-synonymous mutations were found, none of the polymorphisms known to potentially affect the efficacy of current preventive measures were documented. These findings provide new insights into the global hRSV molecular epidemiology and highlight the importance of defining a baseline genomic picture to monitor for future changes that might be induced by the selective pressures of immunological preventive measures, which will soon become widely available.

Metagenomic analysis reveals ecological and functional signatures of oral phageome associated with severe early childhood caries

ObjectivesSevere early childhood caries (S-ECC) is highly prevalent, affecting children's oral health. S-ECC development is closely associated with the complex oral microbial microbiome and its microorganism interactions, such as the imbalance of bacteriophages and bacteria. Till now, little is known about oral phageome on S-ECC. Therefore, this study aimed to investigate the potential role of the oral phageome in the pathogenesis of S-ECC. MethodsUnstimulated saliva (2 mL) was collected from 20 children with and without S-ECC for metagenomics analysis. Metagenomics sequencing and bioinformatic analysis were performed to determine the two groups’ phageome diversity, taxonomic and functional annotations. Statistical analysis and visualization were performed with R and SPSS Statistics software. Results85.7 % of the extracted viral sequences were predicted from phages, in which most phages were classified into Myoviridae, Siphoviridae, and Podoviridae. Alpha diversity decreased, and Beta diversity increased in the S-ECC phageome compared to the healthy group. The abundance of Podoviridae phages increased, and the abundance of Inoviridae, Herelleviridae, and Streptococcus phages decreased in the S-ECC group. Functional annotation revealed increased annotation on glycoside hydrolases and nucleotide metabolism, decreased glycosyl transferases, carbohydrate-binding modules, and biogenic metabolism in the S-ECC phageome. ConclusionsMetagenomic analysis revealed reduced Streptococcus phages and significant changes in functional annotations within the S-ECC phageome. These findings suggest a potential weakening of the regulatory influence of oral bacteria, which may indicate the development of innovative prevention and treatment strategies for S-ECC. These implications deserve further investigation and hold promise for advancing our understanding and management of S-ECC. Clinical significanceThe findings of this study indicate that oral phageomes are associated with bacterial genomes and metabolic processes, affecting the development of S-ECC. The reduced modulatory effect of the oral phageome in counteracting S-ECC's cariogenic activity suggests a new avenue for the prevention and treatment of S-ECC.

Closing the Diagnostic Gap in Encephalitis and Acute Disseminated Encephalomyelitis through Digital Case Classification and Viral Metagenomics

Encephalitis and acute disseminated encephalomyelitis (ADEM) are often caused or triggered by viruses—but the specific pathogen commonly remains unidentified in routine care. We explored the use of viral metagenomic next-generation sequencing (mNGS) in addition to PCR testing of non-invasive stool samples to see if unbiased testing could potentially increase diagnostic yield. To identify specific clinical cases at the point of care, we took advantage of a previously published digital app allowing instant clinical case classification based on consensus case criteria, the VACC-Tool. This hospital-based prospective digital surveillance program assessed 100 pediatric patients (mean age: 11 years, range: 0.15–17.85; 49% male) with case-confirmed encephalitis and/or ADEM. Analysis of case classification at the point of care revealed that in routine care, 96% of confirmed encephalitis/ADEM cases had been missed. Overall agreement of routine care diagnoses with digital encephalitis/ADEM case classification was <50%. Also in routine care, only 13% of cases held a virus-related diagnosis, i.e., herpesvirus (n = 8) and enterovirus infection (n = 5). Use of mNGS increased the yield of virus detection by 77% (n = 23 virus hits). Specifically, mNGS identified 10 additional virus species beyond herpes- and enteroviruses. Of the additional 23 virus hits detected with mNGS, PCR confirmation was possible post hoc in 14 cases (61%). Linking digital case classification, mNGS, and PCR testing may not be feasible in routine care at this point but may help to provide hints to the pathogenesis of encephalitis/ADEM in childhood, warranting further research and exploration.

High-throughput sequencing for plant virology diagnostics and its potential in plant health certification

High-throughput sequencing (HTS) technologies have revolutionized plant virology through simultaneous detection of mixed viral infections. HTS advances have uncovered and improved understanding of virus biology, ecology, and evolution which is vital for viral disease management. Plant viruses continue to threaten global agricultural productivity and strict quarantine measures are essential to prevent the introduction and spread of virulent viruses around the world. The gradual decrease in HTS operational costs, including improved computational systems and automation through robotics, has facilitated the adoption of this tool for plant diagnostics, including its use in surveillance and quarantine programs. However, the speed of technology advancements and distinct HTS chemistries, laboratory procedures, data management, and bioinformatic analyses have proven challenging. In addition, the lack of viral species reference sequences, compared with the estimated number of distinct viral taxa, makes classification and identification of novel viruses difficult. There is a need for standardized HTS testing, especially within plant health programs. In this review, we consider the application of HTS in plant virology, explore the technical challenges faced and the opportunities for HTS in plant health certification. We propose standards for overcoming current barriers and for ensuring reliable and reproducible results. These efforts will impact global plant health by reducing the risk of introduction and the spread of damaging novel viruses.

Differences between the intestinal microbial communities of healthy dogs from plateau and those of plateau dogs infected with Echinococcus

ObjectiveCystic echinococcosis (CE) represents a profoundly perilous zoonotic disease. The advent of viral macrogenomics has facilitated the exploration of hitherto uncharted viral territories. In the scope of this investigation, our objective is to scrutinize disparities in the intestinal microbiotic ecosystems of canines dwelling in elevated terrains and those afflicted by Echinococcus infection, employing the tool of viral macrogenomics.MethodsIn this study, we collected a comprehensive total of 1,970 fecal samples from plateau dogs infected with Echinococcus, as well as healthy control plateau dogs from the Yushu and Guoluo regions in the highland terrain of China. These samples were subjected to viral macrogenomic analysis to investigate the viral community inhabiting the canine gastrointestinal tract.ResultsOur meticulous analysis led to the identification of 136 viral genomic sequences, encompassing eight distinct viral families.ConclusionThe outcomes of this study hold the potential to enhance our comprehension of the intricate interplay between hosts, parasites, and viral communities within the highland canine gut ecosystem. Through the examination of phage presence, it may aid in early detection or assessment of infection severity, providing valuable insights into Echinococcus infection and offering prospects for potential treatment strategies.

Nucleic acid degradation after long-term dried blood spot storage.

Collecting and preserving biological samples in the field, particularly in remote areas in tropical forests, prior to laboratory analysis is challenging. Blood samples in many cases are used for nucleic acid-based species determination, genomics or pathogen research. In most cases, maintaining a cold chain is impossible and samples remain at ambient temperature for extended periods of time before controlled storage conditions become available. Dried blood spot (DBS) storage, blood stored on cellulose-based paper, has been widely applied to facilitate sample collection and preservation in the field for decades. However, it is unclear how long-term storage on this substrate affects nucleic acid concentration and integrity. We analysed nucleic acid quality from DBS stored on Whatman filter paper no. 3 and FTA cards for up to 15 years in comparison to cold-chain stored samples using four nucleic acid extraction methods. We examined the ability to identify viral sequences from samples of 12 free-ranging primates in the Amazon forest, using targeted hybridization capture, and determined if mitochondrial genomes could be retrieved. The results suggest that even after extended periods of storage, DBS will be suitable for some genomic applications but may be of limited use for viral pathogen research, particularly RNA viruses.

Utilizing profile hidden Markov model databases for discovering viruses from metagenomic data: a comprehensive review.

Profile hidden Markov models (pHMMs) are able to achieve high sensitivity in remote homology search, making them popular choices for detecting novel or highly diverged viruses in metagenomic data. However, many existing pHMM databases have different design focuses, making it difficult for users to decide the proper one to use. In this review, we provide a thorough evaluation and comparison for multiple commonly used profile HMM databases for viral sequence discovery in metagenomic data. We characterized the databases by comparing their sizes, their taxonomic coverage, and the properties of their models using quantitative metrics. Subsequently, we assessed their performance in virus identification across multiple application scenarios, utilizing both simulated and real metagenomic data. We aim to offer researchers a thorough and critical assessment of the strengths and limitations of different databases. Furthermore, based on the experimental results obtained from the simulated and real metagenomic data, we provided practical suggestions for users to optimize their use of pHMM databases, thus enhancing the quality and reliability of their findings in the field of viral metagenomics.

Development and application of EpitopeScan, a Python3 toolset for mutation tracking in SARS-CoV-2 immunogenic epitopes.

Outbreaks of coronaviruses and especially the recent COVID-19 pandemic emphasize the importance of immunological research in this area to mitigate the effect of future incidents. Bioinformatics approaches are capable of providing multisided insights from virus sequencing data, although currently available software options are not entirely suitable for a specific task of mutation surveillance within immunogenic epitopes of SARS-CoV-2. Here, we describe the development of a mutation tracker, EpitopeScan, a Python3 package with command line and graphical user interface tools facilitating the investigation of the mutation dynamics in SARS-CoV-2 epitopes via analysis of multiple-sequence alignments of genomes over time. We provide an application case by examining three Spike protein-derived immunodominant CD4+ T-cell epitopes restricted by HLA-DRB1*04:01, an allele strongly associated with susceptibility to rheumatoid arthritis (RA). Mutations in these peptides are relevant for immune monitoring of CD4+ T-cell responses against SARS-CoV-2 spike protein in patients with RA. The analysis focused on 2.3 million SARS-CoV-2 genomes sampled in England. We detail cases of epitope conservation over time, partial loss of conservation, and complete divergence from the wild type following the emergence of the N969K Omicron-specific mutation in November 2021. The wild type and the mutated peptide represent potential candidates to monitor variant-specific CD4+ T-cell responses. EpitopeScan is available via GitHub repository https://github.com/Aleksandr-biochem/EpitopeScan.

Lavender Harbors More Viruses than Previously Thought: First Report of Raspberry Ringspot Virus and Phlox Virus M in Lavandula × intermedia.

Plants of the genus Lavandula are thought to be rarely infected by viruses. To date, only alfalfa mosaic virus, cucumber mosaic virus, tobacco mosaic virus, and tomato spotted wilt virus have been reported in this host. In this study, we identified for the first time raspberry ringspot virus (RpRSV) and phlox virus M (PhlVM) in lavender using herbaceous indexing, enzyme-linked immunosorbent assay, and high-throughput sequencing. Nearly complete genome sequences for both viruses were determined. Phylogenetic and serological characterizations suggest that the obtained RpRSV isolate is a raspberry strain. A preliminary survey of 166 samples indicated RpRSV was spread only in the lavender cultivar 'Grosso', while PhlVM was detected in multiple lavender cultivars. Although RpRSV raspberry strain may have spread throughout Auckland and nearby areas in New Zealand, it is very likely restricted to the genus Lavandula or even to the cultivar 'Grosso' due to the absence or limited occurrence of the nematode vector. Interestingly, all infected lavender plants, regardless of their infection status (by RpRSV, PhlVM, or both) were asymptomatic. RpRSV is an important virus that infects horticultural crops including grapevine, cherry, berry fruits, and rose. It remains on the list of regulated pests in New Zealand. RpRSV testing is mandatory for imported Fragaria, Prunus, Ribes, Rosa, Rubus, and Vitis nursery stock and seeds for sowing, while this is not required for Lavandula importation. Our study revealed that lavender could play a role not only as a reservoir but also as an uncontrolled import pathway of viruses that pose a threat to New Zealand's primary industries.

Detection of Hemagglutinin H5 Influenza A Virus Sequence in Municipal Wastewater Solids at Wastewater Treatment Plants with Increases in Influenza A in Spring, 2024

Detection of Hemagglutinin H5 Influenza A Virus Sequence in Municipal Wastewater Solids at Wastewater Treatment Plants with Increases in Influenza A in Spring, 2024

Pseudotyped virus infection of multiplexed ACE2 libraries reveals SARS-CoV-2 variant shifts in receptor usage.

Pairwise compatibility between virus and host proteins can dictate the outcome of infection. During transmission, both inter- and intraspecies variabilities in receptor protein sequences can impact cell susceptibility. Many viruses possess mutable viral entry proteins and the patterns of host compatibility can shift as the viral protein sequence changes. This combinatorial sequence space between virus and host is poorly understood, as traditional experimental approaches lack the throughput to simultaneously test all possible combinations of protein sequences. Here, we created a pseudotyped virus infection assay where a multiplexed target-cell library of host receptor variants can be assayed simultaneously using a DNA barcode sequencing readout. We applied this assay to test a panel of 30 ACE2 orthologs or human sequence mutants for infectability by the original SARS-CoV-2 spike protein or the Alpha, Beta, Gamma, Delta, and Omicron BA1 variant spikes. We compared these results to an analysis of the structural shifts that occurred for each variant spike's interface with human ACE2. Mutated residues were directly involved in the largest shifts, although there were also widespread indirect effects altering interface structure. The N501Y substitution in spike conferred a large structural shift for interaction with ACE2, which was partially recreated by indirect distal substitutions in Delta, which does not harbor N501Y. The structural shifts from N501Y greatly influenced the set of animal orthologs the variant spike was capable of interacting with. Out of the thirteen non-human orthologs, ten exhibited unique patterns of variant-specific compatibility, demonstrating that spike sequence changes during human transmission can toggle ACE2 compatibility and potential susceptibility of other animal species, and cumulatively increase overall compatibilities as new variants emerge. These experiments provide a blueprint for similar large-scale assessments of protein compatibility during entry by diverse viruses. This dataset demonstrates the complex compatibility relationships that occur between variable interacting host and virus proteins.