Generalized linear models provide a measure of virulence for specific mutations in SARS-CoV-2 strains

Modulation of biophysical properties of nucleocapsid protein in the mutant spectrum of SARS-CoV-2

Genetic diversity is a hallmark of RNA viruses and the basis for their evolutionary success. Taking advantage of the uniquely large genomic database of SARS-CoV-2, we examine the impact of mutations across the spectrum of viable amino acid sequences on the biophysical phenotypes of the highly expressed and multifunctional nucleocapsid protein. We find variation in the physicochemical parameters of its extended intrinsically disordered regions (IDRs) sufficient to allow local plasticity, but also observe functional constraints that similarly occur in related coronaviruses. In biophysical experiments with several N-protein species carrying mutations associated with major variants, we find that point mutations in the IDRs can have nonlocal impact and modulate thermodynamic stability, secondary structure, protein oligomeric state, particle formation, and liquid-liquid phase separation. In the Omicron variant, distant mutations in different IDRs have compensatory effects in shifting a delicate balance of interactions controlling protein assembly properties, and include the creation of a new protein-protein interaction interface in the N-terminal IDR through the defining P13L mutation. A picture emerges where genetic diversity is accompanied by significant variation in biophysical characteristics of functional N-protein species, in particular in the IDRs.

Impact of mutations on the stability of SARS-CoV-2 nucleocapsid protein structure

The nucleocapsid (N) protein of SARS-CoV-2 is known to participate in various host cellular processes, including interferon inhibition, RNA interference, apoptosis, and regulation of virus life cycles. Additionally, it has potential as a diagnostic antigen and/or immunogen. Our research focuses on examining structural changes caused by mutations in the N protein. We have modeled the complete tertiary structure of native and mutated forms of the N protein using Alphafold2. Notably, the N protein contains 3 disordered regions. The focus was on investigating the impact of mutations on the stability of the protein's dimeric structure based on binding free energy calculations (MM-PB/GB-SA) and RMSD fluctuations after MD simulations. The results demonstrated that 28 mutations out of 37 selected mutations analyzed, compared with wild-type N protein, resulted in a stable dimeric structure, while 9 mutations led to destabilization. Our results are important to understand the tertiary structure of the N protein dimer of SARS-CoV-2 and the effect of mutations on it, their behavior in the host cell, as well as for the research of other viruses belonging to the same genus additionally, to anticipate potential strategies for addressing this viral illness․.

COV2Var, a function annotation database of SARS-CoV-2 genetic variation

The COVID-19 pandemic, caused by the coronavirus SARS-CoV-2, has resulted in the loss of millions of lives and severe global economic consequences. Every time SARS-CoV-2 replicates, the viruses acquire new mutations in their genomes. Mutations in SARS-CoV-2 genomes led to increased transmissibility, severe disease outcomes, evasion of the immune response, changes in clinical manifestations and reducing the efficacy of vaccines or treatments. To date, the multiple resources provide lists of detected mutations without key functional annotations. There is a lack of research examining the relationship between mutations and various factors such as disease severity, pathogenicity, patient age, patient gender, cross-species transmission, viral immune escape, immune response level, viral transmission capability, viral evolution, host adaptability, viral protein structure, viral protein function, viral protein stability and concurrent mutations. Deep understanding the relationship between mutation sites and these factors is crucial for advancing our knowledge of SARS-CoV-2 and for developing effective responses. To fill this gap, we built COV2Var, a function annotation database of SARS-CoV-2 genetic variation, available at http://biomedbdc.wchscu.cn/COV2Var/. COV2Var aims to identify common mutations in SARS-CoV-2 variants and assess their effects, providing a valuable resource for intensive functional annotations of common mutations among SARS-CoV-2 variants.

ORF3c is expressed in SARS-CoV-2-infected cells and inhibits innate sensing by targeting MAVS

Most SARS-CoV-2 proteins are translated from subgenomic RNAs (sgRNAs). While the majority of these sgRNAs are monocistronic, some viral mRNAs encode more than one protein. One example is the ORF3a sgRNA that also encodes ORF3c, an enigmatic 41-amino-acid peptide. Here, we show that ORF3c is expressed in SARS-CoV-2-infected cells and suppresses RIG-I- and MDA5-mediated IFN-β induction. ORF3c interacts with the signaling adaptor MAVS, induces its C-terminal cleavage, and inhibits the interaction of RIG-I with MAVS. The immunosuppressive activity of ORF3c is conserved among members of the subgenus sarbecovirus, including SARS-CoV and coronaviruses isolated from bats. Notably, however, the SARS-CoV-2 delta and kappa variants harbor premature stop codons in ORF3c, demonstrating that this reading frame is not essential for efficient viral replication in vivo and is likely compensated by other viral proteins. In agreement with this, disruption of ORF3c does not significantly affect SARS-CoV-2 replication in CaCo-2, CaLu-3, or Rhinolophus alcyone cells. In summary, we here identify ORF3c as an immune evasion factor of SARS-CoV-2 that suppresses innate sensing in infected cells.

SARS-CoV-2 Variants by Whole-Genome Sequencing in a University Hospital in Bangkok: First to Third COVID-19 Waves

BACKGROUND

Multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants emerged globally during the recent coronavirus disease (COVID-19) pandemic. From April 2020 to April 2021, Thailand experienced three COVID-19 waves, and each wave was driven by different variants. Therefore, we aimed to analyze the genetic diversity of circulating SARS-CoV-2 using whole-genome sequencing analysis.

METHODS

A total of 33 SARS-CoV-2 positive samples from three consecutive COVID-19 waves were collected and sequenced by whole-genome sequencing, of which, 8, 10, and 15 samples were derived from the first, second, and third waves, respectively. The genetic diversity of variants in each wave and the correlation between mutations and disease severity were explored.

RESULTS

During the first wave, A.6, B, B.1, and B.1.375 were found to be predominant. The occurrence of mutations in these lineages was associated with low asymptomatic and mild symptoms, providing no transmission advantage and resulting in extinction after a few months of circulation. B.1.36.16, the predominant lineage of the second wave, caused more symptomatic COVID-19 cases and contained a small number of key mutations. This variant was replaced by the VOC alpha variant, which later became dominant in the third wave. We found that B.1.1.7 lineage-specific mutations were crucial for increasing transmissibility and infectivity, but not likely associated with disease severity. There were six additional mutations found only in severe COVID-19 patients, which might have altered the virus phenotype with an inclination toward more highly pathogenic SARS-CoV-2.

CONCLUSION

The findings of this study highlighted the importance of whole-genome analysis in tracking newly emerging variants, exploring the genetic determinants essential for transmissibility, infectivity, and pathogenicity, and helping better understand the evolutionary process in the adaptation of viruses in humans.

SARS-CoV-2 nucleocapsid: Biological functions and implication for disease diagnosis and vaccine design

The coronavirus disease 2019 (COVID-19) pandemic is transmitted by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and has affected millions of people all around the world, leading to more than 6.5 million deaths. The nucleocapsid (N) phosphoprotein plays important roles in modulating viral replication and transcription, virus-infected cell cycle progression, apoptosis, and regulation of host innate immunity. As an immunodominant protein, N protein induces strong humoral and cellular immune responses in COVID-19 patients, making it a key marker for studying N-specific B cell and T cell responses and the development of diagnostic serological assays and efficient vaccines. In this review, we focus on the structural and functional features and the kinetic and epitope mapping of B cell and T cell responses against SARS-CoV-2 N protein to extend our understanding on the development of sensitive and specific diagnostic immunological tests and effective vaccines.

Statistical analysis supports UTR (untranslated region) deletion theory in SARS-CoV-2

It was noticed that the mortality rate of SARS-CoV-2 infection experienced a significant declination in the early stage of the epidemic. We suspect that the sharp deterioration of virus toxicity is related to the deletion of the untranslated region (UTR) of the virus genome. It was found that the genome length of SARS-CoV-2 engaged a significant truncation due to UTR deletion after a mega-sequence analysis. Sequence similarity analysis further indicated that short UTR strains originated from its long UTR ancestors after an irreversible deletion. A good correlation was discovered between genome length and mortality, which demonstrated that the deletion of the virus UTR significantly affected the toxicity of the virus. This correlation was further confirmed in a significance analysis of the genetic influence on the clinical outcomes. The viral genome length of hospitalized patients was significantly more extensive than that of asymptomatic patients. In contrast, the viral genome length of asymptomatic was considerably longer than that of ordinary patients with symptoms. A genome-level mutation scanning was performed to systematically evaluate the influence of mutations at each position on virulence. The results indicated that UTR deletion was the primary driving force in alternating virus virulence in the early evolution. In the end, we proposed a mathematical model to explain why this UTR deletion was not continuous.

Genomic Analysis of SARS-CoV-2 Alpha, Beta and Delta Variants of Concern Uncovers Signatures of Neutral and Non-Neutral Evolution

Due to the emergence of new variants of the SARS-CoV-2 coronavirus, the question of how the viral genomes evolved, leading to the formation of highly infectious strains, becomes particularly important. Three major emergent strains, Alpha, Beta and Delta, characterized by a significant number of missense mutations, provide a natural test field. We accumulated and aligned 4.7 million SARS-CoV-2 genomes from the GISAID database and carried out a comprehensive set of analyses. This collection covers the period until the end of October 2021, i.e., the beginnings of the Omicron variant. First, we explored combinatorial complexity of the genomic variants emerging and their timing, indicating very strong, albeit hidden, selection forces. Our analyses show that the mutations that define variants of concern did not arise gradually but rather co-evolved rapidly, leading to the emergence of the full variant strain. To explore in more detail the evolutionary forces at work, we developed time trajectories of mutations at all 29,903 sites of the SARS-CoV-2 genome, week by week, and stratified them into trends related to (i) point substitutions, (ii) deletions and (iii) non-sequenceable regions. We focused on classifying the genetic forces active at different ranges of the mutational spectrum. We observed the agreement of the lowest-frequency mutation spectrum with the Griffiths-Tavaré theory, under the Infinite Sites Model and neutrality. If we widen the frequency range, we observe the site frequency spectra much more consistently with the Tung-Durrett model assuming clone competition and selection. The coefficients of the fitting model indicate the possibility of selection acting to promote gradual growth slowdown, as observed in the history of the variants of concern. These results add up to a model of genomic evolution, which partly fits into the classical drift barrier ideas. Certain observations, such as mutation "bands" persistent over the epidemic history, suggest contribution of genetic forces different from mutation, drift and selection, including recombination or other genome transformations. In addition, we show that a "toy" mathematical model can qualitatively reproduce how new variants (clones) stem from rare advantageous driver mutations, and then acquire neutral or disadvantageous passenger mutations which gradually reduce their fitness so they can be then outcompeted by new variants due to other driver mutations.

Time Series Analysis of SARS-CoV-2 Genomes and Correlations among Highly Prevalent Mutations

The efforts of the scientific community to tame the recent pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seem to have been diluted by the emergence of new viral strains. Therefore, it is imperative to understand the effect of mutations on viral evolution. We performed a time series analysis on 59,541 SARS-CoV-2 genomic sequences from around the world to gain insights into the kinetics of the mutations arising in the viral genomes. These 59,541 genomes were grouped according to month (January 2020 to March 2021) based on the collection date. Meta-analysis of these data led us to identify significant mutations in viral genomes. Pearson correlation of these mutations led us to the identification of 16 comutations. Among these comutations, some of the individual mutations have been shown to contribute to viral replication and fitness, suggesting a possible role of other unexplored mutations in viral evolution. We observed that the mutations 241C>T in the 5' untranslated region (UTR), 3037C>T in nsp3, 14408C>T in the RNA-dependent RNA polymerase (RdRp), and 23403A>G in spike are correlated with each other and were grouped in a single cluster by hierarchical clustering. These mutations have replaced the wild-type nucleotides in SARS-CoV-2 sequences. Additionally, we employed a suite of computational tools to investigate the effects of T85I (1059C>T), P323L (14408C>T), and Q57H (25563G>T) mutations in nsp2, RdRp, and the ORF3a protein of SARS-CoV-2, respectively. We observed that the mutations T85I and Q57H tend to be deleterious and destabilize the respective wild-type protein, whereas P323L in RdRp tends to be neutral and has a stabilizing effect. IMPORTANCE We performed a meta-analysis on SARS-CoV-2 genomes categorized by collection month and identified several significant mutations. Pearson correlation analysis of these significant mutations identified 16 comutations having absolute correlation coefficients of >0.4 and a frequency of >30% in the genomes used in this study. The correlation results were further validated by another statistical tool called hierarchical clustering, where mutations were grouped in clusters on the basis of their similarity. We identified several positive and negative correlations among comutations in SARS-CoV-2 isolates from around the world which might contribute to viral pathogenesis. The negative correlations among some of the mutations in SARS-CoV-2 identified in this study warrant further investigations. Further analysis of mutations such as T85I in nsp2 and Q57H in ORF3a protein revealed that these mutations tend to destabilize the protein relative to the wild type, whereas P323L in RdRp is neutral and has a stabilizing effect. Thus, we have identified several comutations which can be further characterized to gain insights into SARS-CoV-2 evolution.

Multifaceted Assessment of Wastewater-Based Epidemiology for SARS-CoV-2 in Selected Urban Communities in Davao City, Philippines: A Pilot Study

Over 60 countries have integrated wastewater-based epidemiology (WBE) in their COVID-19 surveillance programs, focusing on wastewater treatment plants (WWTP). In this paper, we piloted the assessment of SARS-CoV-2 WBE as a complementary public health surveillance method in susceptible communities in a highly urbanized city without WWTP in the Philippines by exploring the extraction and detection methods, evaluating the contribution of physico-chemical–anthropogenic factors, and attempting whole-genome sequencing (WGS). Weekly wastewater samples were collected from sewer pipes or creeks in six communities with moderate-to-high risk of COVID-19 transmission, as categorized by the City Government of Davao from November to December 2020. Physico-chemical properties of the wastewater and anthropogenic conditions of the sites were noted. Samples were concentrated using a PEG-NaCl precipitation method and analyzed by RT-PCR to detect the SARS-CoV-2 N, RdRP, and E genes. A subset of nine samples were subjected to WGS using the Minion sequencing platform. SARS-CoV-2 RNA was detected in twenty-two samples (91.7%) regardless of the presence of new cases. Cycle threshold values correlated with RNA concentration and attack rate. The lack of a sewershed map in the sampled areas highlights the need to integrate this in the WBE planning. A combined analysis of wastewater physico-chemical parameters such as flow rate, surface water temperature, salinity, dissolved oxygen, and total dissolved solids provided insights on the ideal sampling location, time, and method for WBE, and their impact on RNA recovery. The contribution of fecal matter in the wastewater may also be assessed through the coliform count and in the context of anthropogenic conditions in the area. Finally, our attempt on WGS detected single-nucleotide polymorphisms (SNPs) in wastewater which included clinically reported and newly identified mutations in the Philippines. This exploratory report provides a contextualized framework for applying WBE surveillance in low-sanitation areas.

Functional mutations of SARS-CoV-2: implications to viral transmission, pathogenicity and immune escape

The pandemic of coronavirus disease 2019 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to major public health challenges globally. The increasing viral lineages identified indicate that the SARS-CoV-2 genome is evolving at a rapid rate. Viral genomic mutations may cause antigenic drift or shift, which are important ways by which SARS-CoV-2 escapes the human immune system and changes its transmissibility and virulence. Herein, we summarize the functional mutations in SARS-CoV-2 genomes to characterize its adaptive evolution to inform the development of vaccination, treatment as well as control and intervention measures.

First report and genome sequencing of SARS-CoV-2 in a cat (Felis catus) in Colombia

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a virus of zoonotic origin that can bind to ACE2 receptors on the cells of many wild and domestic mammals. Studies have shown that the virus can circulate among animals mutate, lead to animal-to-human zoonotic jump, and further onward spread between humans. Infection in pets is unusual, and there are few human-to-pet transmission reports worldwide.

OBJECTIVE

To describe the SARS-CoV-2 infection in a domestic animal in Córdoba, Colombian Caribbean region.

METHODS

A cross-sectional molecular surveillance study was carried out, oral and rectal swabs were taken from cats and dogs living with people diagnosed with coronavirus disease 2019 (COVID-19).

RESULTS

SARS-CoV-2 was found in a cat living with a person with COVID-19. Genome sequencing showed that the B.1.111 lineage caused the infection in the cat. The owner's sample could not be sequenced. The lineage is predominant in Colombia, and this variant is characterised by the presence of the D614D and Q57H mutation.

CONCLUSION

The present work is the first report of an infected cat with SARS-CoV-2 with whole-genome sequencing in Colombia. It highlights the importance of detecting SARS-CoV-2 mutations that could promote the transmissibility of this new coronavirus. There is still a significant information gap on human-to-cat-to-human infection; we encourage self-isolation measures between COVID-19 patients and companion animals. The findings of this study give a preliminary view of the current panorama of SARS-CoV-2 infection in animals in Colombia.

Awaiting a cure for COVID-19: therapeutic approach in patients with different severity levels of COVID-19

COVID-19 is an unpredictable infectious disease caused by SARS-CoV-2. The development of effective anti-COVID-19 vaccines has enormously minimized the risk of severe illness in most immunocompetent patients. However, unvaccinated patients and non-responders to the COVID-19 vaccine are at risk of shortand long-term consequences. In these patients, the outcome of COVID-19 relies on an interplay of multiple factors including age, immunocompetence, comorbidities, inflammatory response triggered by the virus as well as the virulence of SARS-CoV-2 variants. Generally, COVID-19 is asymptomatic or mildly symptomatic in young people, but it may manifest with respiratory insufficiency requiring mechanical ventilation in certain susceptible groups of patients. Furthermore, severe SARS-CoV-2 infection induces multiorgan failure syndrome by affecting liver, kidney heart and nervous system. Since December 2019, multiple drugs have been tested to treat COVID-19, but only a few have been proven effective to mitigate the course of the disease that continues to cause death and comorbidity worldwide. Current treatment of COVID-19 patients is essentially based on the administration of supportive oxygen therapy and the use of specific drugs such as steroids, anticoagulants, antivirals, anti-SARS-CoV-2 antibodies and immunomodulators. However, the rapid spread of new variants and the release of new data coming from the numerous ongoing clinical trials have created the conditions for maintaining a continuous updating of the therapeutic management of COVID-19 patients. Furthermore, we believe that a well-established therapeutic strategy along with the continuum of medical care for all patients with COVID-19 is pivotal to improving disease outcomes and restoring healthcare care fragmentation caused by the pandemic. This narrative review, focusing on the therapeutic management of COVID-19 patients, aimed to provide an overview of current therapies for (i) asymptomatic or mildly/moderate symptomatic patients, (ii) hospitalized patients requiring low-flow oxygen, (iii) high-flow oxygen and (iv) mechanical ventilation.

Emergence of the novel SARS-CoV-2 lineage VUI-NP13L and massive spread of P.2 in South Brazil

In this study, we analyzed 340 whole genomes of SARS-CoV-2, which were sampled between April and November 2020 in 33 cities of Rio Grande do Sul, South Brazil. We demonstrated the circulation of two novel emergent lineages, VUI-NP13L and VUI-NP13L-like, and five major lineages that had already been assigned (B.1.1.33, B.1.1.28, P.2, B.1.91, B.1.195). P.2 and VUI-NP13L demonstrated a massive spread in October 2020. Constant and consistent genomic surveillance is crucial to identify newly emerging SARS-CoV-2 lineages in Brazil and to guide decision making in the Brazilian Public Healthcare System.

In depth analysis of Cyprus-specific mutations of SARS-CoV-2 strains using computational approaches

BACKGROUND

This study aims to characterize SARS-CoV-2 mutations which are primarily prevalent in the Cypriot population. Moreover, using computational approaches, we assess whether these mutations are associated with changes in viral virulence.

METHODS

We utilize genetic data from 144 sequences of SARS-CoV-2 strains from the Cypriot population obtained between March 2020 and January 2021, as well as all data available from GISAID. We combine this with countries' regional information, such as deaths and cases per million, as well as COVID-19-related public health austerity measure response times. Initial indications of selective advantage of Cyprus-specific mutations are obtained by mutation tracking analysis. This entails calculating specific mutation frequencies within the Cypriot population and comparing these with their prevalence world-wide throughout the course of the pandemic. We further make use of linear regression models to extrapolate additional information that may be missed through standard statistical analysis.

RESULTS

We report a single mutation found in the ORF1ab gene (nucleotide position 18,440) that appears to be significantly enriched within the Cypriot population. The amino acid change is denoted as S6059F, which maps to the SARS-CoV-2 NSP14 protein. We further analyse this mutation using regression models to investigate possible associations with increased deaths and cases per million. Moreover, protein structure prediction tools show that the mutation infers a conformational change to the protein that significantly alters its structure when compared to the reference protein.

CONCLUSIONS

Investigating Cyprus-specific mutations for SARS-CoV-2 can lead to a better understanding of viral pathogenicity. Researching these mutations can generate potential links between viral-specific mutations and the unique genomics of the Cypriot population. This can not only lead to important findings from which to battle the pandemic on a national level, but also provide insights into viral virulence worldwide.

Variants in SARS-CoV-2 associated with mild or severe outcome

Introduction

The coronavirus disease 2019 (COVID-19) pandemic is a global public health emergency causing a disparate burden of death and disability around the world. The viral genetic variants associated with outcome severity are still being discovered.

Methods

We downloaded 155 958 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from GISAID. Of these genomes, 3637 samples included useable metadata on patient outcomes. Using this subset, we evaluated whether SARS-CoV-2 viral genomic variants improved prediction of reported severity beyond age and region. First, we established whether including genomic variants as model features meaningfully increased the predictive power of our model. Next, we evaluated specific variants in order to determine the magnitude of association with severity and the frequency of these variants among SARS-CoV-2 genomes.

Results

Logistic regression models that included viral genomic variants outperformed other models (area under the curve = 0.91 as compared with 0.68 for age and gender alone; P < 0.001). We found 84 variants with odds ratios greater than 2 for outcome severity (17 and 67 for higher and lower severity, respectively). The median frequency of associated variants was 0.15% (interquartile range 0.09-0.45%). Altogether 85% of genomes had at least one variant associated with patient outcome.

Conclusion

Numerous SARS-CoV-2 variants have 2-fold or greater association with odds of mild or severe outcome and collectively, these variants are common. In addition to comprehensive mitigation efforts, public health measures should be prioritized to control the more severe manifestations of COVID-19 and the transmission chains linked to these severe cases.Lay summary: This study explores which, if any, SARS-CoV-2 viral genomic variants are associated with mild or severe COVID-19 patient outcomes. Our results suggest that there are common genomic variants in SARS-CoV-2 that are more often associated with negative patient outcomes, which may impact downstream public health measures.

SARS-CoV-2 biology and variants: anticipation of viral evolution and what needs to be done

The global propagation of SARS-CoV-2 and the detection of a large number of variants, some of which have replaced the original clade to become dominant, underscores the fact that the virus is actively exploring its evolutionary space. The longer high levels of viral multiplication occur - permitted by high levels of transmission -, the more the virus can adapt to the human host and find ways to success. The third wave of the COVID-19 pandemic is starting in different parts of the world, emphasizing that transmission containment measures that are being imposed are not adequate. Part of the consideration in determining containment measures is the rationale that vaccination will soon stop transmission and allow a return to normality. However, vaccines themselves represent a selection pressure for evolution of vaccine-resistant variants, so the coupling of a policy of permitting high levels of transmission/virus multiplication during vaccine roll-out with the expectation that vaccines will deal with the pandemic, is unrealistic. In the absence of effective antivirals, it is not improbable that SARS-CoV-2 infection prophylaxis will involve an annual vaccination campaign against 'dominant' viral variants, similar to influenza prophylaxis. Living with COVID-19 will be an issue of SARS-CoV-2 variants and evolution. It is therefore crucial to understand how SARS-CoV-2 evolves and what constrains its evolution, in order to anticipate the variants that will emerge. Thus far, the focus has been on the receptor-binding spike protein, but the virus is complex, encoding 26 proteins which interact with a large number of host factors, so the possibilities for evolution are manifold and not predictable a priori. However, if we are to mount the best defence against COVID-19, we must mount it against the variants, and to do this, we must have knowledge about the evolutionary possibilities of the virus. In addition to the generic cellular interactions of the virus, there are extensive polymorphisms in humans (e.g. Lewis, HLA, etc.), some distributed within most or all populations, some restricted to specific ethnic populations and these variations pose additional opportunities for/constraints on viral evolution. We now have the wherewithal - viral genome sequencing, protein structure determination/modelling, protein interaction analysis - to functionally characterize viral variants, but access to comprehensive genome data is extremely uneven. Yet, to develop an understanding of the impacts of such evolution on transmission and disease, we must link it to transmission (viral epidemiology) and disease data (patient clinical data), and the population granularities of these. In this editorial, we explore key facets of viral biology and the influence of relevant aspects of human polymorphisms, human behaviour, geography and climate and, based on this, derive a series of recommendations to monitor viral evolution and predict the types of variants that are likely to arise.