Host genomics of SARS-CoV-2 infection

Host factors of SARS-CoV-2 in infection, pathogenesis, and long-term effects

SARS-CoV-2 is the causative virus of the devastating COVID-19 pandemic that results in an unparalleled global health and economic crisis. Despite unprecedented scientific efforts and therapeutic interventions, the fight against COVID-19 continues as the rapid emergence of different SARS-CoV-2 variants of concern and the increasing challenge of long COVID-19, raising a vast demand to understand the pathomechanisms of COVID-19 and its long-term sequelae and develop therapeutic strategies beyond the virus per se. Notably, in addition to the virus itself, the replication cycle of SARS-CoV-2 and clinical severity of COVID-19 is also governed by host factors. In this review, we therefore comprehensively overview the replication cycle and pathogenesis of SARS-CoV-2 from the perspective of host factors and host-virus interactions. We sequentially outline the pathological implications of molecular interactions between host factors and SARS-CoV-2 in multi-organ and multi-system long COVID-19, and summarize current therapeutic strategies and agents targeting host factors for treating these diseases. This knowledge would be key for the identification of new pathophysiological aspects and mechanisms, and the development of actionable therapeutic targets and strategies for tackling COVID-19 and its sequelae.

Lack of association between HLA and asymptomatic SARS-CoV-2 infection

Human genetic studies of critical COVID-19 pneumonia have revealed the essential role of type I interferon-dependent innate immunity to SARS-CoV-2 infection. Conversely, an association between the HLA-B*15:01 allele and asymptomatic SARS-CoV-2 infection in unvaccinated individuals was recently reported, suggesting a contribution of pre-existing T cell-dependent adaptive immunity. We report a lack of association of classical HLA alleles, including HLA-B*15:01, with pre-omicron asymptomatic SARS-CoV-2 infection in unvaccinated participants in a prospective population-based study in the US (191 asymptomatic vs. 945 symptomatic COVID-19 cases). Moreover, we found no such association in the international COVID Human Genetic Effort cohort (206 asymptomatic vs. 574 mild or moderate COVID-19 cases and 1,625 severe or critical COVID-19 cases). Finally, in the Human Challenge Characterisation study, the three HLA-B*15:01 individuals infected with SARS-CoV-2 developed symptoms. As with other acute primary infections, no classical HLA alleles favoring an asymptomatic course of SARS-CoV-2 infection were identified. These findings suggest that memory T-cell immunity to seasonal coronaviruses does not strongly influence the outcome of SARS-CoV-2 infection in unvaccinated individuals.

A Flexible Regression Modeling Approach Applied to Observational Laboratory Virological Data Suggests That SARS-CoV-2 Load in Upper Respiratory Tract Samples Changes with COVID-19 Epidemiology

(1) Background. Exploring the evolution of SARS-CoV-2 load and clearance from the upper respiratory tract samples is important to improving COVID-19 control. Data were collected retrospectively from a laboratory dataset on SARS-CoV-2 load quantified in leftover nasal pharyngeal swabs (NPSs) collected from symptomatic/asymptomatic individuals who tested positive to SARS-CoV-2 RNA detection in the framework of testing activities for diagnostic/screening purpose during the 2020 and 2021 winter epidemic waves. (2) Methods. A Statistical approach (quantile regression and survival models for interval-censored data), novel for this kind of data, was applied. We included in the analysis SARS-CoV-2-positive adults >18 years old for whom at least two serial NPSs were collected. A total of 262 SARS-CoV-2-positive individuals and 784 NPSs were included: 193 (593 NPSs) during the 2020 winter wave (before COVID-19 vaccine introduction) and 69 (191 NPSs) during the 2021 winter wave (all COVID-19 vaccinated). We estimated the trend of the median value, as well as the 25th and 75th centiles of the viral load, from the index episode (i.e., first SARS-CoV-2-positive test) until the sixth week (2020 wave) and the third week (2021 wave). Interval censoring methods were used to evaluate the time to SARS-CoV-2 clearance (defined as Ct < 35). (3) Results. At the index episode, the median value of viral load in the 2021 winter wave was 6.25 log copies/mL (95% CI: 5.50-6.70), and the median value in the 2020 winter wave was 5.42 log copies/mL (95% CI: 4.95-5.90). In contrast, 14 days after the index episode, the median value of viral load was 3.40 log copies/mL (95% CI: 3.26-3.54) for individuals during the 2020 winter wave and 2.93 Log copies/mL (95% CI: 2.80-3.19) for those of the 2021 winter wave. A significant difference in viral load shapes was observed among age classes (p = 0.0302) and between symptomatic and asymptomatic participants (p = 0.0187) for the first wave only; the median viral load value is higher at the day of episode index for the youngest (18-39 years) as compared to the older (40-64 years and >64 years) individuals. In the 2021 epidemic, the estimated proportion of individuals who can be considered infectious (Ct < 35) was approximately half that of the 2020 wave. (4) Conclusions. In case of the emergence of new SARS-CoV-2 variants, the application of these statistical methods to the analysis of virological laboratory data may provide evidence with which to inform and promptly support public health decision-makers in the modification of COVID-19 control measures.

Saliva microbiome in relation to SARS-CoV-2 infection in a prospective cohort of healthy US adults

BACKGROUND

The clinical outcomes of SARS-CoV-2 infection vary in severity, potentially influenced by the resident human microbiota. There is limited consensus on conserved microbiome changes in response to SARS-CoV-2 infection, with many studies focusing on severely ill individuals. This study aimed to assess the variation in the upper respiratory tract microbiome using saliva specimens in a cohort of individuals with primarily mild to moderate disease.

METHODS

In early 2020, a cohort of 831 adults without known SARS-CoV-2 infection was followed over a six-month period to assess the occurrence and natural history of SARS-CoV-2 infection. From this cohort, 81 participants with a SARS-CoV-2 infection, along with 57 unexposed counterparts were selected with a total of 748 serial saliva samples were collected for analysis. Total bacterial abundance, composition, population structure, and gene function of the salivary microbiome were measured using 16S rRNA gene and shotgun metagenomic sequencing.

FINDINGS

The salivary microbiome remained stable in unexposed individuals over the six-month study period, as evidenced by all measured metrics. Similarly, participants with mild to moderate SARS-CoV-2 infection showed microbiome stability throughout and after their infection. However, there were significant reductions in microbiome diversity among SARS-CoV-2-positive participants with severe symptoms early after infection. Over time, the microbiome diversity in these participants showed signs of recovery.

INTERPRETATION

These findings demonstrate the resilience of the salivary microbiome in relation to SARS-CoV-2 infection. Mild to moderate infections did not significantly disrupt the stability of the salivary microbiome, suggesting its ability to maintain its composition and function. However, severe SARS-CoV-2 infection was associated with temporary reductions in microbiome diversity, indicating the limits of microbiome resilience in the face of severe infection.

FUNDING

This project was supported in part by Danone North America and grants from the National Institutes of Health, United States.

Genome-Wide Mining of Selaginella moellendorffii for Hevein-like Lectins and Their Potential Molecular Mimicry with SARS-CoV-2 Spike Glycoprotein

Multidisciplinary research efforts on potential COVID-19 vaccine and therapeutic candidates have increased since the pandemic outbreak of SARS-CoV-2 in 2019. This search has become imperative due to the increasing emergences and limited widely available medicines. The presence of bioactive anti-SARS-CoV-2 molecules was examined from various plant sources. Among them is a group of proteins called lectins that can bind carbohydrate moieties. In this article, we present ten novel, chitin-specific Hevein-like lectins that were derived from Selaginella moellendorffii v1.0's genome. The capacity of these lectin homologs to bind with the spike protein of SARS-CoV-2 was examined. Using the HDOCK server, 3D-modeled Hevein-domains were docked to the spike protein's receptor binding domain (RBD). The Smo446851, Smo125663, and Smo99732 interacted with Asn343-located complex N-glycan and RBD residues, respectively, with binding free energies of -17.5, -13.0, and -26.5 Kcal/mol. The molecular dynamics simulation using Desmond and the normal-state analyses via torsional coordinate association for the Smo99732-RBD complex using iMODS is characterized by overall higher stability and minimum deformity than the other lectin complexes. The three lectins interacting with carbohydrates were docked against five individual mutations that frequently occur in major SARS-CoV-2 variants. These were in the spike protein's receptor-binding motif (RBM), while Smo125663 and Smo99732 only interacted with the spike glycoprotein in a protein-protein manner. The precursors for the Hevein-like homologs underwent additional characterization, and their expressional profile in different tissues was studied. These in silico findings offered potential lectin candidates targeting key N-glycan sites crucial to the virus's virulence and infection.

Constructing a full, multiple-layer interactome for SARS-CoV-2 in the context of lung disease: Linking the virus with human genes and microbes

The COVID-19 pandemic caused by the SARS-CoV-2 virus has resulted in millions of deaths worldwide. The disease presents with various manifestations that can vary in severity and long-term outcomes. Previous efforts have contributed to the development of effective strategies for treatment and prevention by uncovering the mechanism of viral infection. We now know all the direct protein-protein interactions that occur during the lifecycle of SARS-CoV-2 infection, but it is critical to move beyond these known interactions to a comprehensive understanding of the "full interactome" of SARS-CoV-2 infection, which incorporates human microRNAs (miRNAs), additional human protein-coding genes, and exogenous microbes. Potentially, this will help in developing new drugs to treat COVID-19, differentiating the nuances of long COVID, and identifying histopathological signatures in SARS-CoV-2-infected organs. To construct the full interactome, we developed a statistical modeling approach called MLCrosstalk (multiple-layer crosstalk) based on latent Dirichlet allocation. MLCrosstalk integrates data from multiple sources, including microbes, human protein-coding genes, miRNAs, and human protein-protein interactions. It constructs "topics" that group SARS-CoV-2 with genes and microbes based on similar patterns of co-occurrence across patient samples. We use these topics to infer linkages between SARS-CoV-2 and protein-coding genes, miRNAs, and microbes. We then refine these initial linkages using network propagation to contextualize them within a larger framework of network and pathway structures. Using MLCrosstalk, we identified genes in the IL1-processing and VEGFA-VEGFR2 pathways that are linked to SARS-CoV-2. We also found that Rothia mucilaginosa and Prevotella melaninogenica are positively and negatively correlated with SARS-CoV-2 abundance, a finding corroborated by analysis of single-cell sequencing data.

The rs17713054 and rs1800629 polymorphisms of genes LZTFL1 and TNF are associated with COVID-19 severity

Both genetic and non-genetic factors are responsible for high interindividual variability in response to SARS-CoV-2. Despite the fact that multiple genetic polymorphisms have been identified as risk factors of severe COVID-19, such polymorphisms are still insufficiently studied in the Russian population. The study was aimed to identify genetic determinants associated with severe COVID-19 in the sample of patients from the Russian Federation. The correlation of the rs17713054 polymorphism in gene LZTFL1 and rs1800629 polymorphism in gene TNF (tumor necrosis factor) with the COVID-19 severity was assessed. DNA samples obtained from 713 patients (324 males and 389 females) aged 18‒95 with COVID-19 of varying severity were analyzed. The rs1800629 polymorphism of gene TNF (OR = 1.5; p = 0.02) and rs17713054 polymorphism of gene LZTFL1 (OR = 1.60; p = 0.0043) were identified as risk factors of severe disease. The TNF polymorphism rs1800629 and LZTFL1 polymorphism rs17713054 could be considered as potential predictive biomarkers. The rs17713054 G > A polymorphism was strongly associated with severe disease. In the future the findings may provide the basis for the development of test-systems for prediction of the risk of severe viral respiratory diseases.