Higher entropy observed in SARS-CoV-2 genomes from the first COVID-19 wave in Pakistan

EVOLVE: A Web Platform for AI-Based Protein Mutation Prediction and Evolutionary Phase Exploration

While predicting structure-function relationships from sequence data is fundamental in biophysical chemistry, identifying prospective single-point and collective mutation sites in proteins can help us stay ahead in understanding their potential effects on protein structure and function. Addressing the challenges of large sequence-space analysis, we present EVOLVE, a web tool enabling researchers to explore prospective mutation sites and their collective behavior. EVOLVE integrates a statistical mechanics-guided machine learning algorithms to predict probable mutational sites, with statistical mechanics calculating mutational entropy to accurately identify mutational hotspots. Validation against a number of viral protein sequences confirms its ability to predict mutations and their functional consequences. By leveraging statistical mechanics of phase transition concept, EVOLVE also quantifies mutational entropy fluctuations, offering a quantitative foundation for identifying Variants of Concern (VOC) or Variants under Monitoring (VUM) as per World Health Organization (WHO) guidelines. EVOLVE streamlines data upload and analysis with a user-friendly interface and comprehensive tutorials. Access EVOLVE free at https://evolve-iiserkol.com.

Evidence of rapid rise in population immunity from SARS-CoV-2 subclinical infections through pre-vaccination serial serosurveys in Pakistan

Background

Understanding factors associated with protective immunity against emerging viral infections is crucial for global health. Pakistan reported its first COVID-19 case on 26 February 2020, but experienced relatively low COVID-19-related morbidity and mortality between 2020 and 2022. The underlying reasons for this remain unclear, and our research aims to shed light on this crucial issue.

Methods

We conducted a serial population-based serosurvey over 16 months (rounds 1-4, July 2020 to November 2021) across households in urban (Karachi) and rural (Matiari) Sindh, sampling 1100 households and 3900 individuals. We measured antibodies in sera and tested a subset of respiratory samples for COVID-19 using polymerase chain reaction (PCR) and antigen tests, also measuring haemoglobin (Hb), C-reactive protein (CRP), vitamin D, and zinc in round 1.

Results

Participants showed 23% (95% confidence interval (CI) = 21.9-24.5) antibody seroprevalence in round 1, increasing across rounds 2-4 to 29% (95% CI = 27.4-30.6), 49% (95% CI = 47.2-50.9), and 79% (95% CI = 77.4-80.8), respectively. Urban residents had 2.6 times (95% CI = 1.9-3.6) higher odds of seropositivity than rural residents. Seropositivity did not differ between genders. Individuals aged 20-49 years had 7.5 (95% CI = 4.6-12.4) times higher odds of seropositivity compared to children aged 0-4 years. Most participants had no symptoms associated with COVID-19, with no reported mortality. Vitamin D deficiency was linked to seroprevalence. COVID-19 was confirmed in 1.8% of individuals tested via RT-PCR and antigen tests.

Conclusions

The data suggests a steady increase in humoral immunity in Pakistan, likely due to increased transmission and associated asymptomatic disease. Overall, this reflects the longitudinal trend of protection against severe acute respiratory syndrome coronavirus 2, leading to the relatively low morbidity and mortality observed in the population.

SARS-CoV-2 variants induce increased inflammatory gene expression but reduced interferon responses and heme synthesis as compared with wild type strains

SARS-CoV-2 variants of concern (VOC) have been associated with increased viral transmission and disease severity. We investigated the mechanisms of pathogenesis caused by variants using a host blood transcriptome profiling approach. We analysed transcriptional signatures of COVID-19 patients comparing those infected with wildtype (wt), alpha, delta or omicron strains seeking insights into infection in Asymptomatic cases.Comparison of transcriptional profiles of Symptomatic and Asymptomatic COVID-19 cases showed increased differentially regulated gene (DEGs) of inflammatory, apoptosis and blood coagulation pathways, with decreased T cell and Interferon stimulated genes (ISG) activation. Between SARS-CoV-2 strains, an increasing number of DEGs occurred in comparisons between wt and alpha (196), delta (1425) or, omicron (2313) infections. COVID-19 cases with alpha or, delta variants demonstrated suppression transcripts of innate immune pathways. EGR1 and CXCL8 were highly upregulated in those infected with VOC; heme biosynthetic pathway genes (ALAS2, HBB, HBG1, HBD9) and ISGs were downregulated. Delta and omicron infections upregulated ribosomal pathways, reflecting increased viral RNA translation. Asymptomatic COVID-19 cases infected with delta infections showed increased cytokines and ISGs expression. Overall, increased inflammation, with reduced host heme synthesis was associated with infections caused by VOC infections, with raised type I interferon in cases with less severe disease.

Disparities in age and gender-specific SARS-CoV-2 diagnostic testing trends: a retrospective study from Pakistan

BACKGROUND

Pakistan reported 1.57 million COVID-19 cases between 2020 and 2022, based on approximately 30.6 million SARS-CoV-2 RT-PCR (reverse-transcription polymerase chain reaction) tests conducted. This study utilized data from one of the largest in-country testing facilities, Aga Khan University Hospital (AKUH) in Karachi, Pakistan, to explore gender and age-related in RT-PCR testing patterns.

METHODS

We conducted a retrospective review of SARS-CoV-2 RT-PCR test data extracted from AKUH clinical laboratory records between February 2020 and February 2022. Gender and age distributions were examined in the context of testing patterns across the period. Multivariate regression models assessed independent associations between COVID-19 positivity and key variables.

RESULTS

We reviewed 470,249 RT-PCR tests, finding that most tests were in those aged 21-40 years (48.1%). Overall, COVID-19 test positivity was 20.6%. In all, 57.7% were performed for males, predominant amongst those tested across all age groups and waves. Females had significantly lower odds of testing positive for COVID-19 (OR: 0.9; 95% CI: 0.9-1.0). However, when adjusted for gender, age and pandemic phases, the positivity rates between males and females were the same. The odds of a positive result increased significantly with age; individuals aged > 80 years had 2.5 times higher odds of testing positive than those aged 0-10 years (aOR 2.5, 95% CI 2.3-2.7).

CONCLUSIONS

The analysis indicates a consistent male dominance in COVID-19 testing, with higher positivity rates in older age groups. Our study highlight the importance of examining demographic characteristics in disease associated data especially, representation of females amongst cohorts.

An entropy-based study on the mutational landscape of SARS-CoV-2 in USA: Comparing different variants and revealing co-mutational behavior of proteins

COVID-19 emergency has pushed the international scientific community to use every resource to combat the spread of the virus, to understand its biology and predict its possible evolution in terms of new variants. Since the first SARS-CoV-2 virus nucleotide and amino acid sequences were made available, information theory was used to study how viral information content was changing over time and then trace the evolution of its mutational landscape. In this work we analyzed SARS-CoV-2 sequences collected mainly in the USA in a period from March 2020 until December 2022 and computed mutation profiles of viral proteins over time through an entropy-based approach using Shannon Entropy and Hellinger distance. This representation allows an at-a-glance view of the mutational landscape of viral proteins over time and can provide new insights on the evolution of the virus from different points of view. Non-structural proteins typically showed flat mutation profiles, characterized by a very low Average mutation Entropy, while accessory and structural proteins showed mostly non uniform and high mutation profiles, often coupled with the predominance of variants. Interestingly NSP2 protein, whose function is currently still debated, falls in the same branch of NSP14 and NSP10 in the phylogenetic tree of mutations constructed through correlations of mutation profiles, suggesting a co-evolution of those proteins and a possible functional link with each other. To the best of our knowledge this is the first study based on a massive amount of data (n = 107,939,973) that analyzes from an entropy point of view the mutational landscape of SARS-CoV-2 over time and depicts a mutational temporal profile of each protein of the virus.

Risk factors for mortality in hospitalized COVID-19 patients across five waves in Pakistan

This retrospective cohort study aims to describe the clinical characteristics and outcomes and assess risk factors for mortality across the epidemic waves in hospitalized COVID-19 patients in a major tertiary-care center in Pakistan. A total of 5368 patients with COVID-19, hospitalized between March 2020 and April 2022 were included. The median age was 58 years (IQR: 44-69), 41% were females, and the overall mortality was 12%. Comparative analysis of COVID-19 waves showed that the proportion of patients aged ≥ 60 years was highest during the post-wave 4 period (61.4%) and Wave 4 (Delta) (50%) (p < 0.001). Male predominance decreased from 65.2% in Wave 2 to 44.2% in Wave 5 (Omicron) (p < 0.001). Mortality rate was lowest at 9.4% in wave 5 and highest at 21.6% in the post-wave 4 period (p = 0.041). In multivariable analysis for risk factors of mortality, acute respiratory distress syndrome (ARDS) was most strongly associated with mortality (aOR 22.98, 95% CI 15.28-34.55, p < 0.001), followed by need for mechanical ventilation (aOR 6.81, 95% CI 5.13-9.05, p < 0.001). Other significant risk factors included acute kidney injury (aOR 3.05, 95% CI 2.38-3.91, p < 0.001), stroke (aOR 2.40, 95% CI 1.26-4.60, p = 0.008), pulmonary embolism (OR 2.07, 95% CI 1.28-3.35, p = 0.003), and age ≥ 60 years (aOR 2.45, 95% CI 1.95-3.09, p < 0.001). Enoxaparin use was associated with lower mortality odds (aOR 0.45, 95% CI 0.35-0.60, p < 0.001. Patients hospitalized during Wave 4 (aOR 2.22, 95% CI 1.39-3.56, p < 0.001) and the post-wave 4 period (aOR 2.82, 95% CI 1.37-5.80, p = 0.005) had higher mortality odds compared to other waves. The study identifies higher mortality risk in patients admitted in Delta wave and post-wave, aged ≥ 60 years, and with respiratory and renal complications, and lower risk with anticoagulation during COVID-19 waves.

Shift in SARS-CoV-2 variants of concern from Delta to Omicron was associated with reduced hospitalizations, increased risk of breakthrough infections but lesser disease severity

BACKGROUND

COVID-19 epidemiology changed with the emergence of SARS-CoV-2 variants of concern (VOC). Pakistan administered mostly inactivated vaccines. We investigated the association between VOC and breakthrough infections in a mixed-vaccination-status population of Karachi.

METHODS

We investigated SARS-CoV-2 VOC tested in 392 respiratory specimens collected between May and December 2021. Data for age, sex, hospital admission, vaccinations, together with CT values of the diagnostic PCR test were analyzed.

RESULTS

The median age of COVID-19 cases tested was 40 (27-57) years and 43.4% were female. Delta variants were most common (56.4%) followed by Alpha (15.9%), Omicron (12.2%), Beta/Gamma (11.3%), and others (4.3%). Eighteen percent of cases were hospitalized whereby, predominant VOC were Beta/Gamma (40.8%), Alpha (35.2%) and Delta (22.5%). Overall, 55.4% of individuals were fully vaccinated, 7.4% were partially vaccinated and 37.2% were unvaccinated. Most (74.6%) inpatients were unvaccinated. Vaccines comprised inactivated (85.34%), single-shot vector (8.62%), two-shot vector (3.02%) and mRNA (3.02%) types. Omicron variants showed lower viral loads as compared to Alpha, Beta/Gamma, and Delta (p = 0.017). The risk of infection with Delta and Omicron variants was higher, 8 weeks after vaccination. The majority of those with breakthrough infections after receiving inactivated vaccines acquired COVID-19 within 4 months of vaccination.

CONCLUSION

Our data highlights the shifting of VOC from Delta to Omicron during 2021 and that COVID-19 vaccinations reduced both hospitalizations and viral transmission. It informs on the increased risk of breakthrough infection within 8 weeks of vaccination, indicating the need for booster vaccinations.

Secondary attack rates and determinants of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) household transmission in Pakistan: A case-ascertained prospective, longitudinal study

BACKGROUND

Households are considered ideal settings for studying the transmission dynamics of an infectious disease.

METHODS

A prospective study was conducted, based on the World Health Organization FFX protocol from October 2020 to January,2021. Household contacts of laboratory-confirmed index cases were followed up for their symptomatic history, nasal swabs for RT-PCR,and blood samples for anti-SARS CoV-2 antibodies were collected at enrollment and days 7, 14 and 28. We estimated secondary attack rate (SAR), effective household case cluster size and determinants of secondary infection among susceptible household contacts using multivariable logistic regression.

RESULTS

We enrolled 77 index cases and their 543 contacts. Out of these, 252 contacts were susceptible at the time of enrollment. There were 77 household clusters, out of which, transmission took place in 20 (25.9%) giving rise to 34 cases. The acquired secondary attack rate (SAR) was 14.0% (95% CI 9.0-18.0). The effective household case cluster size was 0.46 (95%CI 0.33,0.56). Reported symptoms of nausea and vomiting (aOR, 7.9; 95% CI, 1.4-45.5) and fatigue (aOR, 9.3; 95% CI, 3.8-22.7) were associated with SARS-CoV-2 transmission.

CONCLUSIONS

We observed a low SARS-CoV-2 secondary attack rate in the backdrop of high seroprevalence and asymptomatic transmission among households in Karachi, Pakistan.

Design and Development of an Antigen Test for SARS-CoV-2 Nucleocapsid Protein to Validate the Viral Quality Assurance Panels

The continuing mutability of the SARS-CoV-2 virus can result in failures of diagnostic assays. To address this, we describe a generalizable bioinformatics-to-biology pipeline developed for the calibration and quality assurance of inactivated SARS-CoV-2 variant panels provided to Radical Acceleration of Diagnostics programs (RADx)-radical program awardees. A heuristic genetic analysis based on variant-defining mutations demonstrated the lowest genetic variance in the Nucleocapsid protein (Np)-C-terminal domain (CTD) across all SARS-CoV-2 variants. We then employed the Shannon entropy method on (Np) sequences collected from the major variants, verifying the CTD with lower entropy (less prone to mutations) than other Np regions. Polyclonal and monoclonal antibodies were raised against this target CTD antigen and used to develop an Enzyme-linked immunoassay (ELISA) test for SARS-CoV-2. Blinded Viral Quality Assurance (VQA) panels comprised of UV-inactivated SARS-CoV-2 variants (XBB.1.5, BF.7, BA.1, B.1.617.2, and WA1) and distractor respiratory viruses (CoV 229E, CoV OC43, RSV A2, RSV B, IAV H1N1, and IBV) were assembled by the RADx-rad Diagnostics core and tested using the ELISA described here. The assay tested positive for all variants with high sensitivity (limit of detection: 1.72-8.78 ng/mL) and negative for the distractor virus panel. Epitope mapping for the monoclonal antibodies identified a 20 amino acid antigenic peptide on the Np-CTD that an in-silico program also predicted for the highest antigenicity. This work provides a template for a bioinformatics pipeline to select genetic regions with a low propensity for mutation (low Shannon entropy) to develop robust 'pan-variant' antigen-based assays for viruses prone to high mutational rates.

Building Research Capacity in Low- and Middle-Income Countries and Pandemic Preparedness: Lessons Learned and Future Directions

Research capacity is a critical component of pandemic preparedness, as highlighted by the challenges faced during the Ebola outbreak in West Africa. Recent global initiatives, such as the Research & Development Task Force of the Global Health Security Agenda and the World Health Assembly's resolution on strengthening clinical trials, emphasize the need for robust research capabilities. This Perspective discusses the experiences of leaders in infectious disease research and capacity building in low- and middle-income countries, focusing on Colombia, Jamaica, and Pakistan. These case studies underscore the importance of collaborative efforts, interdisciplinary training, and global partnerships in pandemic response. The experiences highlight the necessity for rapid pathogen identification, capacity for genomic sequencing, and proactive engagement with policymakers. Challenges faced, including the shortage of trained staff and reliance on imported reagents, emphasize the ongoing need for building research capacity.

Unraveling the genetic variations underlying virulence disparities among SARS-CoV-2 strains across global regions: insights from Pakistan

Over the course of the COVID-19 pandemic, several SARS-CoV-2 variants have emerged that may exhibit different etiological effects such as enhanced transmissibility and infectivity. However, genetic variations that reduce virulence and deteriorate viral fitness have not yet been thoroughly investigated. The present study sought to evaluate the effects of viral genetic makeup on COVID-19 epidemiology in Pakistan, where the infectivity and mortality rate was comparatively lower than other countries during the first pandemic wave. For this purpose, we focused on the comparative analyses of 7096 amino-acid long polyprotein pp1ab. Comparative sequence analysis of 203 SARS-CoV-2 genomes, sampled from Pakistan during the first wave of the pandemic revealed 179 amino acid substitutions in pp1ab. Within this set, 38 substitutions were identified within the Nsp3 region of the pp1ab polyprotein. Structural and biophysical analysis of proteins revealed that amino acid variations within Nsp3's macrodomains induced conformational changes and modified protein-ligand interactions, consequently diminishing the virulence and fitness of SARS-CoV-2. Additionally, the epistatic effects resulting from evolutionary substitutions in SARS-CoV-2 proteins may have unnoticed implications for reducing disease burden. In light of these findings, further characterization of such deleterious SARS-CoV-2 mutations will not only aid in identifying potential therapeutic targets but will also provide a roadmap for maintaining vigilance against the genetic variability of diverse SARS-CoV-2 strains circulating globally. Furthermore, these insights empower us to more effectively manage and respond to potential viral-based pandemic outbreaks of a similar nature in the future.

Systematic detection of co-infection and intra-host recombination in more than 2 million global SARS-CoV-2 samples

Systematic monitoring of SARS-CoV-2 co-infections between different lineages and assessing the risk of intra-host recombinant emergence are crucial for forecasting viral evolution. Here we present a comprehensive analysis of more than 2 million SARS-CoV-2 raw read datasets submitted to the European COVID-19 Data Portal to identify co-infections and intra-host recombination. Co-infection was observed in 0.35% of the investigated cases. Two independent procedures were implemented to detect intra-host recombination. We show that sensitivity is predominantly determined by the density of lineage-defining mutations along the genome, thus we used an expanded list of mutually exclusive defining mutations of specific variant combinations to increase statistical power. We call attention to multiple challenges rendering recombinant detection difficult and provide guidelines for the reduction of false positives arising from chimeric sequences produced during PCR amplification. Additionally, we identify three recombination hotspots of Delta - Omicron BA.1 intra-host recombinants.

Optimal entropic properties of SARS-CoV-2 RNA sequences

The reaction of the scientific community against the COVID-19 pandemic has generated a huge (approx. 106 entries) dataset of genome sequences collected worldwide and spanning a relatively short time window. These unprecedented conditions together with the certain identification of the reference viral genome sequence allow for an original statistical study of mutations in the virus genome. In this paper, we compute the Shannon entropy of every sequence in the dataset as well as the relative entropy and the mutual information between the reference sequence and the mutated ones. These functions, originally developed in information theory, measure the information content of a sequence and allows us to study the random character of mutation mechanism in terms of its entropy and information gain or loss. We show that this approach allows us to set in new format known features of the SARS-CoV-2 mutation mechanism like the CT bias, but also to discover new optimal entropic properties of the mutation process in the sense that the virus mutation mechanism track closely theoretically computable lower bounds for the entropy decrease and the information transfer.

Exploring the relationship between SARS-CoV-2 variants, illness severity at presentation, in-hospital mortality and COVID-19 vaccination in a low middle-income country: A retrospective cross-sectional study

Background and Aims

COVID-19 morbidity and mortality varied globally through the pandemic. We studied the relationship of SARS-CoV-2 variants of concern (VOC) with COVID-19 severity and mortality among hospitalized patients in Pakistan.

Methods

A retrospective review of clinical, laboratory, and vaccination data of 197 COVID-19 adult patients at the Aga Khan University Hospital, Karachi between April 2021, and February 2022 was performed. SARS-CoV-2 VOC identified in respiratory samples were analyzed. Univariate and multivariate analysis was conducted to identify factors associated with COVID-19 outcomes.

Results

The median age of cases was 55 years and 51.8% were males. Twenty-four percent of females were pregnant. Of COVID-19 cases, 48.2% had nonsevere disease, while 52.8% had severe/critical disease. Hypertension (48%) and diabetes mellitus (41%) were common comorbids. SARS-CoV-2 VOC identified comprised; Omicron (55.3%), Beta (14.7%), Alpha (13.7%), Delta (12.7%), and Gamma (3.6%) variants. Most (59.7%) study subjects were unvaccinated. Of vaccines, 88% had received inactivated virus COVID-19 vaccines. Increased risk of severe disease was associated with age ≥50 years (odds ratio [OR]: 5.73; 95% confidence interval [CI]: [2.45-13.7]), as well as with diabetes mellitus (OR: 4.24; 95% CI: [1.82-9.85]). Full vaccination (OR: 0.25; 95% CI: [0.11-0.58]) or infection with Omicron (OR: 0.42; 95% CI: [0.23-0.74]) was associated with reduced disease severity. The risk of mortality increased with age ≥50 years (OR: 5.07; 95% CI: [1.92-13.42]) and a history of myocardial infarction (OR: 5.11; 95% CI: [1.45-17.93]) whilst, infection with Omicron was found to reduce the risk (OR: 0.22; 95% CI: [0.10-0.53]).

Conclusion

Our study describes the relationship between the severity of COVID-19, in-hospital mortality in relation to SARS-CoV-2 variants, and the impact of COVID-19 vaccination in Pakistan. Outcomes were more favorable in younger individuals, after vaccinations and with Omicron variant infections. Most cases received inactivated virus vaccines therefore these data highlight the protection provided against severe COVID-19.

Humoral and T cell responses to SARS-CoV-2 reveal insights into immunity during the early pandemic period in Pakistan

BACKGROUND

Protection against SARS-CoV-2 is mediated by humoral and T cell responses. Pakistan faced relatively low morbidity and mortality from COVID-19 through the pandemic. To examine the role of prior immunity in the population, we studied IgG antibody response levels, virus neutralizing activity and T cell reactivity to Spike protein in a healthy control group (HG) as compared with COVID-19 cases and individuals from the pre-pandemic period (PP).

METHODS

HG and COVID-19 participants were recruited between October 2020 and May 2021. Pre-pandemic sera was collected before 2018. IgG antibodies against Spike and its Receptor Binding Domain (RBD) were determined by ELISA. Virus neutralization activity was determined using a PCR-based micro-neutralization assay. T cell - IFN-γ activation was assessed by ELISpot.

RESULTS

Overall, the magnitude of anti-Spike IgG antibody levels as well as seropositivity was greatest in COVID-19 cases (90%) as compared with HG (39.8%) and PP (12.2%). During the study period, Pakistan experienced three COVID-19 waves. We observed that IgG seropositivity to Spike in HG increased from 10.3 to 83.5% during the study, whilst seropositivity to RBD increased from 7.5 to 33.3%. IgG antibodies to Spike and RBD were correlated positively in all three study groups. Virus neutralizing activity was identified in sera of COVID-19, HG and PP. Spike reactive T cells were present in COVID-19, HG and PP groups. Individuals with reactive T cells included those with and without IgG antibodies to Spike.

CONCLUSIONS

Antibody and T cell responses to Spike protein in individuals from the pre-pandemic period suggest prior immunity against SARS-CoV-2, most likely from cross-reactive responses. The rising seroprevalence observed in healthy individuals through the pandemic without known COVID-19 may be due to the activation of adaptive immunity from cross-reactive memory B and T cells. This may explain the more favourable COVID-19 outcomes observed in this population.

Substitution spectra of SARS-CoV-2 genome from Pakistan reveals insights into the evolution of variants across the pandemic

Changing morbidity and mortality due to COVID-19 across the pandemic has been linked with factors such as the emergence of SARS-CoV-2 variants and vaccination. Mutations in the Spike glycoprotein enhanced viral transmission and virulence. We investigated whether SARS-CoV-2 mutation rates and entropy were associated COVID-19 in Pakistan, before and after the introduction of vaccinations. We analyzed 1,705 SARS-CoV-2 genomes using the Augur phylogenetic pipeline. Substitution rates and entropy across the genome, and in the Spike glycoprotein were compared between 2020, 2021 and 2022 (as periods A, B and C). Mortality was greatest in B whilst cases were highest during C. In period A, G clades were predominant, and substitution rate was 5.25 × 10-4 per site per year. In B, Delta variants dominated, and substitution rates increased to 9.74 × 10-4. In C, Omicron variants led to substitution rates of 5.02 × 10-4. Genome-wide entropy was the highest during B particularly, at Spike E484K and K417N. During C, genome-wide mutations increased whilst entropy was reduced. Enhanced SARS-CoV-2 genome substitution rates were associated with a period when more virulent SARS-CoV-2 variants were prevalent. Reduced substitution rates and stabilization of genome entropy was subsequently evident when vaccinations were introduced. Whole genome entropy analysis can help predict virus evolution to guide public health interventions.

Investigating the impact of prior COVID-19 on IgG antibody and interferon γ responses after BBIBP-CorV vaccination in a disease endemic population: A prospective observational study

Background and Aims

COVID-19 vaccinations have reduced morbidity and mortality from the disease. Antibodies against severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) have been associated with immune protection. Seroprevalence studies revealed high immunoglobulin G (IgG) antibody levels to SARS-CoV-2 in the Pakistani population before vaccinations. We investigated the effect of BBIBP-CorV vaccination on circulating IgG antibodies and interferon (IFN)-γ from T cells measured in a cohort of healthy individuals, with respect to age, gender, and history of COVID-19.

Methods

The study was conducted between April and October 2021. BBIBP-CorV vaccinated participants were followed up to 24 weeks. Antibodies to SARS-CoV-2 Spike protein and its receptor-binding domain (RBD) were measured. IFNγ secreted by whole blood stimulation of Spike protein and extended genome antigens was determined.

Results

Study participants with a history of prior COVID-19 displayed a higher magnitude of IgG antibodies to Spike and RBD. IgG seropositivity was greater in those with prior COVID-19, aged 50 years or younger and in females. At 24 weeks after vaccination, 37.4% of participants showed IFN-γ responses to SARS-CoV-2 antigens. T cell IFN-γ release was higher in those with prior COVID-19 and those aged 50 years or less. Highest IFN-γ release was observed to extended genome antigens in individuals both with and without prior COVID-19.

Conclusion

We found that IgG seropositivity to both Spike and RBD was affected by prior COVID-19, age and gender. Importantly, seropositive responses persisted up to 24 weeks after vaccination. Persistence of vaccine induced IgG antibodies may be linked to the high seroprevalence observed earlier in unvaccinated individuals. Increased T cell reactivity to Spike and extended genome antigens reflects cellular activation induced by BBIBP-CorV. COVID-19 vaccination may have longer lasting immune responses in populations with a higher seroprevalence. These data inform on vaccination booster policies for high-risk groups.

Evolution of Sequence and Structure of SARS-CoV-2 Spike Protein: A Dynamic Perspective

Novel coronavirus (SARS-CoV-2) enters its host cell through a surface spike protein. The viral spike protein has undergone several modifications/mutations at the genomic level, through which it modulated its structure-function and passed through several variants of concern. Recent advances in high-resolution structure determination and multiscale imaging techniques, cost-effective next-generation sequencing, and development of new computational methods (including information theory, statistical methods, machine learning, and many other artificial intelligence-based techniques) have hugely contributed to the characterization of sequence, structure, function of spike proteins, and its different variants to understand viral pathogenesis, evolutions, and transmission. Laying on the foundation of the sequence-structure-function paradigm, this review summarizes not only the important findings on structure/function but also the structural dynamics of different spike components, highlighting the effects of mutations on them. As dynamic fluctuations of three-dimensional spike structure often provide important clues for functional modulation, quantifying time-dependent fluctuations of mutational events over spike structure and its genetic/amino acidic sequence helps identify alarming functional transitions having implications for enhanced fusogenicity and pathogenicity of the virus. Although these dynamic events are more difficult to capture than quantifying a static, average property, this review encompasses those challenging aspects of characterizing the evolutionary dynamics of spike sequence and structure and their implications for functions.

L-shaped distribution of the relative substitution rate (c/μ) observed for SARS-COV-2's genome, inconsistent with the selectionist theory, the neutral theory and the nearly neutral theory but a near-neutral balanced selection theory: Implication on "neutralist-selectionist" debate

The genomic substitution rate (GSR) of SARS-CoV-2 exhibits a molecular clock feature and does not change under fluctuating environmental factors such as the infected human population (10°-107), vaccination etc. The molecular clock feature is believed to be inconsistent with the selectionist theory (ST). The GSR shows lack of dependence on the effective population size, suggesting Ohta's nearly neutral theory (ONNT) is not applicable to this virus. Big variation of the substitution rate within its genome is also inconsistent with Kimura's neutral theory (KNT). Thus, all three existing evolution theories fail to explain the evolutionary nature of this virus. In this paper, we proposed a Segment Substitution Rate Model (SSRM) under non-neutral selections and pointed out that a balanced mechanism between negative and positive selection of some segments that could also lead to the molecular clock feature. We named this hybrid mechanism as near-neutral balanced selection theory (NNBST) and examined if it was followed by SARS-CoV-2 using the three independent sets of SARS-CoV-2 genomes selected by the Nextstrain team. Intriguingly, the relative substitution rate of this virus exhibited an L-shaped probability distribution consisting with NNBST rather than Poisson distribution predicted by KNT or an asymmetric distribution predicted by ONNT in which nearly neutral sites are believed to be slightly deleterious only, or the distribution that is lack of nearly neutral sites predicted by ST. The time-dependence of the substitution rates for some segments and their correlation with the vaccination were observed, supporting NNBST. Our relative substitution rate method provides a tool to resolve the long standing "neutralist-selectionist" controversy. Implications of NNBST in resolving Lewontin's Paradox is also discussed.

Molecular characterisation and tracking of severe acute respiratory syndrome coronavirus 2 in Thailand, 2020-2022

The global COVID-19 pandemic, caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was first detected in China in December 2019. To date, there have been approximately 3.4 million reported cases of COVID-19 and over 24,000 deaths in Thailand. In this study, we investigated the molecular characteristics and evolution of SARS-CoV-2 in Thailand from 2020 to 2022. Two hundred sixty-eight SARS-CoV-2 isolates, collected mostly in Bangkok from COVID-19 patients, were characterised by partial genome sequencing. Moreover, the viruses in 5,627 positive SARS-CoV-2 samples were identified as viral variants - B.1.1.7 (Alpha), B.1.617.2 (Delta), B.1.1.529 (Omicron/BA.1), or B.1.1.529 (Omicron/BA.2) - by multiplex real-time reverse transcription polymerase chain reaction (RT-PCR) assays. The results revealed that B.1.36.16 caused the predominant outbreak in the second wave (December 2020-January 2021), B.1.1.7 (Alpha) in the third wave (April-June 2021), B.1.617.2 (Delta) in the fourth wave (July-December 2021), and B.1.1.529 (Omicron) in the fifth wave (January-March 2022). The evolutionary rate of the viral genome was 2.60 × 10-3 (95% highest posterior density [HPD], 1.72 × 10-3 to 3.62 × 10-3) nucleotide substitutions per site per year. Continued molecular surveillance of SARS-CoV-2 is crucial for monitoring emerging variants with the potential to cause new COVID-19 outbreaks.

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.

Quantifying Mutational Response to Track the Evolution of SARS-CoV-2 Spike Variants: Introducing a Statistical-Mechanics-Guided Machine Learning Method

The emergence of SARS-CoV-2 and its variants that critically affect global public health requires characterization of mutations and their evolutionary pattern from specific Variants of Interest (VOIs) to Variants of Concern (VOCs). Leveraging the concept of equilibrium statistical mechanics, we introduce a new responsive quantity defined as "Mutational Response Function (MRF)" aptly quantifying domain-wise average entropy-fluctuation in the spike glycoprotein sequence of SARS-CoV-2 based on its evolutionary database. As the evolution transits from a specific variant to VOC, we find that the evolutionary crossover is accompanied by a dramatic change in MRF, upholding the characteristic of a dynamic phase transition. With this entropic information, we have developed an ancestral-based machine learning method that helps predict future domain-specific mutations. The feedforward binary classification model pinpoints possible residues prone to future mutations that have implications for enhanced fusogenicity and pathogenicity of the virus. We believe such MRF analyses followed by a statistical mechanics augmented ML approach could help track different evolutionary stages of such species and identify a critical evolutionary transition that is alarming.

VOC-alarm: mutation-based prediction of SARS-CoV-2 variants of concern

SUMMARY

Mutation is the key for a variant of concern (VOC) to overcome selective pressures, but this process is still unclear. Understanding the association of the mutational process with VOCs is an unmet need. Motivation: Here, we developed VOC-alarm, a method to predict VOCs and their caused COVID surges, using mutations of about 5.7 million SARS-CoV-2 complete sequences. We found that VOCs rely on lineage-level entropy value of mutation numbers to compete with other variants, suggestive of the importance of population-level mutations in the virus evolution. Thus, we hypothesized that VOCs are a result of a mutational process across the globe. Results: Analyzing the mutations from January 2020 to December 2021, we simulated the mutational process by estimating the pace of evolution, and thus divided the time period, January 2020-March 2022, into eight stages. We predicted Alpha, Delta, Delta Plus (AY.4.2) and Omicron (B.1.1.529) by their mutational entropy values in the Stages I, III, V and VII with accelerated paces, respectively. In late November 2021, VOC-alarm alerted that Omicron strongly competed with Delta and Delta plus to become a highly transmissible variant. Using simulated data, VOC-alarm also predicted that Omicron could lead to another COVID surge from January 2022 to March 2022.

AVAILABILITY AND IMPLEMENTATION

Our software implementation is available at https://github.com/guangxujin/VOC-alarm.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Evolutionary History and Introduction of SARS-CoV-2 Alpha VOC/B.1.1.7 in Pakistan Through International Travelers

SARS-CoV-2 variants continue to emerge, and their identification is important for the public health response to COVID-19. Genomic sequencing provides robust information but may not always be accessible and therefore rapid mutation-based PCR approaches can be used to identify known variants. International travelers arriving in Karachi between December 2020 and February 2021 were tested for SARS-CoV-2 by PCR. A subset of positive samples was tested for S-Gene Target Failure (SGTF) on TaqPathTM COVID-19 (Thermo Fisher Scientific) and for mutations using the GSD NovaType SARS-CoV-2 (Eurofins Technologies) assays. Sequencing was conducted on the MinION platform (Oxford Nanopore Technologies (ONT). Bayesian phylogeographic inference was performed integrating the patients’ travel history information. Of the thirty-five COVID-19 cases screened, thirteen had isolates with SGTF. The travelers transmitted infection to sixty-eight contact cases. The B.1.1.7 lineage was confirmed through sequencing and PCR. Phylogenetic analysis of sequence data available for six cases included four B.1.1.7 strains and one B.1.36 and B.1.1.212 lineage isolate, respectively. Phylogeographic modeling estimated at least three independent B.1.1.7 introductions into Karachi, Pakistan, originating from the UK. B.1.1.212 and B.1.36 were inferred to be introduced either from the UK or the travelers’ layover location. We report the introduction of SARS-CoV-2 B.1.1.7 and other lineages in Pakistan by international travelers arriving via different flight routes. This highlights SARS-CoV-2 transmission through travel, importance of testing and quarantine post-travel to prevent transmission of new strains, as well as recording detailed patients’ metadata. Such results help inform policies on restricting travel from destinations where new highly transmissible variants have emerged.

A fractal scaling analysis of the SARS-CoV-2 genome sequence

An approach based on fractal scaling analysis to characterize the organization of the SARS-CoV-2 genome sequence was used. The method is based on the detrended fluctuation analysis (DFA) implemented on a sliding window scheme to detect variations of long-range correlations over the genome sequence regions. The nucleotides sequence is mapped in a numerical sequence by using four different assignation rules: amino-keto, purine-pyrimidine, hydrogen-bond and hydrophobicity patterns. The originally reported sequence from Wuhan isolates (Wuhan Hu-1) was considered as a reference to contrast the structure of the 2002-2004 SARS-CoV-1 strain. Long-range correlations, quantified in terms of a scaling exponent, depended on both the mapping rule and the sequence region. Deviations from randomness were attributed to serial correlations or anti-correlations, which can be ascribed to ordered regions of the genome sequence. It was found that the Wuhan Hu-1 sequence was more random than the SARS-CoV-1 sequence, which suggests that the SARS-CoV-2 possesses a more efficient genomic structure for replication and infection. In general, the virus isolated in the early 2020 months showed slight correlation differences with the Wuhan Hu-1 sequence. However, early isolates from India and Italy presented visible differences that led to a more ordered sequence organization. It is apparent that the increased sequence order, particularly in the spike region, endowed some early variants with a more efficient mechanism to spreading, replicating and infecting. Overall, the results showed that the DFA provides a suitable framework to assess long-term correlations hidden in the internal organization of the SARS-CoV-2 genome sequence.

An entropy-based study on mutational trajectory of SARS-CoV-2 in India

The pandemic of COVID-19 has been haunting us for almost the past two years. Although, the vaccination drive is in full swing throughout the world, different mutations of the SARS-CoV-2 virus are making it very difficult to put an end to the pandemic. The second wave in India, one of the worst sufferers of this pandemic, can be mainly attributed to the Delta variant i.e. B.1.617.2. Thus, it is very important to analyse and understand the mutational trajectory of SARS-CoV-2 through the study of the 26 virus proteins. In this regard, more than 17,000 protein sequences of Indian SARS-CoV-2 genomes are analysed using entropy-based approach in order to find the monthly mutational trajectory. Furthermore, Hellinger distance is also used to show the difference of the mutation events between the consecutive months for each of the 26 SARS-CoV-2 protein. The results show that the mutation rates and the mutation events of the viral proteins though changing in the initial months, start stabilizing later on for mainly the four structural proteins while the non-structural proteins mostly exhibit a more constant trend. As a consequence, it can be inferred that the evolution of the new mutative configurations will eventually reduce.

Upregulated type I interferon responses in asymptomatic COVID-19 infection are associated with improved clinical outcome

Understanding key host protective mechanisms against SARS-CoV-2 infection can help improve treatment modalities for COVID-19. We used a blood transcriptome approach to study biomarkers associated with differing severity of COVID-19, comparing severe and mild Symptomatic disease with Asymptomatic COVID-19 and uninfected Controls. There was suppression of antigen presentation but upregulation of inflammatory and viral mRNA translation associated pathways in Symptomatic as compared with Asymptomatic cases. In severe COVID-19, CD177 a neutrophil marker, was upregulated while interferon stimulated genes (ISGs) were downregulated. Asymptomatic COVID-19 cases displayed upregulation of ISGs and humoral response genes with downregulation of ICAM3 and TLR8. Compared across the COVID-19 disease spectrum, we found type I interferon (IFN) responses to be significantly upregulated (IFNAR2, IRF2BP1, IRF4, MAVS, SAMHD1, TRIM1), or downregulated (SOCS3, IRF2BP2, IRF2BPL) in Asymptomatic as compared with mild and severe COVID-19, with the dysregulation of an increasing number of ISGs associated with progressive disease. These data suggest that initial early responses against SARS-CoV-2 may be effectively controlled by ISGs. Therefore, we hypothesize that treatment with type I interferons in the early stage of COVID-19 may limit disease progression by limiting SARS-CoV-2 in the host.