Effects of aluminum-salt, CpG and emulsion adjuvants on the stability and immunogenicity of a virus-like particle displaying the SARS-CoV-2 receptor binding domain (RBD) (preprint)

Second-generation COVID-19 vaccines with improved immunogenicity (e.g., breadth, duration) and availability (e.g., lower costs, refrigerator stable) are needed to enhance global coverage. In this work, we formulated a clinical-stage SARS-CoV-2 receptor binding domain (RBD) virus-like particle (VLP) vaccine candidate (IVX-411) with widely available adjuvants. Specifically, we assessed the in vitro storage stability and in vivo mouse immunogenicity of IVX-411 formulated with aluminum-salt adjuvants (Alhydrogel, AH and Adjuphos, AP), without or with the TLR-9 agonist CpG-1018 (CpG), and compared these profiles to IVX-411 adjuvanted with an oil-in-water nano-emulsion (AddaVax, AV). Although IVX-411 bound both AH and AP, lower binding strength of antigen to AP was observed by Langmuir binding isotherms. Interestingly, AH- and AP-adsorbed IVX-411 had similar storage stability profiles as measured by antigen binding assays (competitive ELISAs), but the latter displayed higher pseudovirus neutralizing titers (pNT) in mice, at levels comparable to titers elicited by AV-adjuvanted IVX-411. CpG addition to alum (AP or AH) resulted in a marginal trend of improved pNTs in stressed samples only, yet did not impact the storage stability profiles of IVX-411. In contrast, previous work with AH-formulations of a monomeric RBD antigen showed greatly improved immunogenicity and decreased stability upon CpG addition to alum. At elevated temperatures (25, 37{degrees}C), IVX-411 formulated with AH or AP displayed decreased in vitro stability compared to AV-formulated IVX-411and this rank-ordering correlated with in vivo performance (mouse pNT values). This case study highlights the importance of optimizing antigen-adjuvant interactions to develop low cost, aluminum-salt adjuvanted recombinant subunit vaccine candidates.

Formulation development and comparability studies with an aluminum-salt adjuvanted SARS-CoV-2 Spike ferritin nanoparticle vaccine antigen produced from two different cell lines (preprint)

The development of safe and effective second-generation COVID-19 vaccines to improve affordability and storage stability requirements remains a high priority to expand global coverage. In this report, we describe formulation development and comparability studies with a self-assembled SARS-CoV-2 spike ferritin nanoparticle vaccine antigen (called DCFHP), when produced in two different cell lines and formulated with an aluminum-salt adjuvant (Alhydrogel, AH). Varying levels of phosphate buffer altered the extent and strength of antigen-adjuvant interactions, and these formulations were evaluated for their (1) in vivo performance in mice and (2) in vitro stability profiles. Unadjuvanted DCFHP produced minimal immune responses while AH-adjuvanted formulations elicited greatly enhanced pseudovirus neutralization titers independent of ~100%, ~40% or ~10% of the DCFHP antigen adsorbed to AH. These formulations differed, however, in their in vitro stability properties as determined by biophysical studies and a competitive ELISA for measuring ACE2 receptor binding of AH-bound antigen. Interestingly, after one month of 4C storage, small increases in antigenicity with concomitant decreases in the ability to desorb the antigen from the AH were observed. Finally, we performed a comparability assessment of DCFHP antigen produced in Expi293 and CHO cells, which displayed expected differences in their N-linked oligosaccharide profiles. Despite consisting of different DCFHP glycoforms, these two preparations were highly similar in their key quality attributes including molecular size, structural integrity, conformational stability, binding to ACE2 receptor and mouse immunogenicity profiles. Taken together, these studies support future preclinical and clinical development of an AH-adjuvanted DCFHP vaccine candidate produced in CHO cells.

SARS-CoV2 Induced Biochemical Mechanisms in Liver Damage and Intestinal Lesions. (preprint)

Introduction: Multiple pathogenic mechanisms are found in SARS-CoV2 systemic inflammation. Oxidative stress, altered proteolysis, hypercoagulation, and metabolic disorders are significant in virus-induced lesions. The study aimed to investigate the biochemical mechanism of virus-induced disorders and determine the biochemical features in SARS-CoV2-associated liver damage and intestine lesions. Methods: . A retrospective case series of ninety-two patients diagnosed with COVID-19. The ACE, α1-proteinase inhibitor, trypsin-like proteinase, and elastase activity were measured by FAPGG hydrolysis. Nitrites level was detected in reaction with Griess reagent. The ELISA kit measured Troponin, C-peptide, leptin, adiponectin, PAR4, and neuropilin level. Results: . ACE activity and nitrites ions content increase in SARS-CoV2 pneumonia. The hyperglycemia with an increase in adipose tissue-derived hormones is specific for virus-induced disorders and affects the development of unfavorable outcomes. Cardiac failure was detected in patients with ARDS. AH patients with COVID-19 had more pronounced hyperglycemia and increased ACE activity and NO ions level. Activation of proteolysis was revealed in SARS-CoV2 pneumonia. The found molecular event was accompanied by hyperglycemia induction. Liver damage was specific for patients co-infected with COVID-19 with severe ARDS and heart failure. But the intestinal lesions were associated with the proteolysis activation. The obtained data shows the prevalence of the neuropilin-dependent axis in damage of the intestine with more pronounced inflammation. Growth in adipose tissue hormones, nitrites, and neuropilin levels is triggered by prolonged inflammation. Conclusions: . The impaired metabolism, SARS-CoV2 associated hyperglycemia influence on SARS-CoV2 multiple mechanisms of virus invasion. Gastrointestinal manifestations in SARS-CoV2 infection are related to various and varied tools. ACE2 receptors axis is prevalent for liver damage, but NRP-1 protein (neuropilin), NO derivatives, and adipose tissue-derived hormones are essential for intestinal lesions.

Immunoinformatics approach for a novel multi-epitope vaccine construct against spike protein of human coronaviruses (preprint)

Spike (S) proteins are an attractive target as it mediates the binding of the SARS-CoV-2 to the host through ACE-2 receptors. We hypothesize that the screening of S protein sequences of all the HCoVs would result in the identification of potential multi-epitope vaccine candidates capable of conferring immunity against various HCoVs. In the present study, several machine learning-based in-silico tools were employed to design a broad-spectrum multi-epitope vaccine candidate against S protein of human coronaviruses. To the best of our knowledge, it is one of the first study, where multiple B-cell epitopes and T-cell epitopes (CTL and HTL) were predicted from the S protein sequences of all seven known HCoVs and linked together with an adjuvant to construct a potential broad-spectrum vaccine candidate. Secondary and tertiary structures were predicted, validated and the refined 3D-model was docked with an immune receptor. The vaccine candidate was evaluated for antigenicity, allergenicity, solubility, and its ability to achieve high-level expression in bacterial hosts. Finally, the immune simulation was carried out to evaluate the immune response after three vaccine doses. The designed vaccine is antigenic (with or without the adjuvant), non-allergenic, binds well with TLR-3 receptor and might elicit a diverse and strong immune response.

Applying high throughput and comprehensive immunoinformatics approaches to design a trivalentsubunit vaccine forinduction of immune response against human emerging coronaviruses SARS-CoV, MERS-CoV and SARS-CoV2 (preprint)

Background Coronaviruses (CoV) cause diseases such as severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS) and Coronavirus disease 2019 (COVID-19). Therefore, this study was conducted to contrast a trivalent subunit vaccine against SARS, MERS and COVID-19. The CTL, HTL, MHC I, and IFN-γ epitopes were predicted. Moreover, to stimulate strong helper T lymphocytes (HTLs) responses, Pan HLA DR-binding epitope (PADRE) was used. Also, for boosting immune response, β-defensin 2 was added to the construct as an adjuvant. Furthermore, TAT was applied in the vaccine to facilitate the intracellular delivery.Results Based on the predicted epitopes, a trivalent multi-epitope vaccine with a molecular weight of 74.8 kDa as a strong antigen, a non-allergenic, and soluble protein was constructed. Furtheremore, analyses validated the stability of the proposed vaccine. The binding affinity of the vaccine construct with the TLR3 was confirmed by molecular docking and, stability of the docked complex was simulated. The predicted epitopes demonstrated strong potential to stimulate T and B-cell mediated immune responses. Furthermore, codon optimization and in silico cloning guaranteed increased expression.Conclusions In this work, immunoinformatics investigations demonstrated that this next-generation approach may provide a new horizon for the development of a highly immunogenic vaccine against SARS-CoV, MERS‐CoV, and SARS-CoV-2.

Ensemble Machine Learning of Factors Influencing COVID-19 Across US Counties (preprint)

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) the causal agent for COVID-19, is a communicable disease spread through close contact. It is known to disproportionately infect certain communities due to both biological susceptibility and inequitable exposure. In this study, we investigate the most important health, social, and environmental factors impacting both the early and later phases of COVID-19 transmission and mortality in US counties.Methods: We aggregate county-level physical and mental health, environmental pollution, access to health care, demographic characteristics, vulnerable population scores, and other epidemiological data to create a large feature set to analyze COVID-19 outcomes. Because of the high-dimensionality and multicollinearity of the data, we use ensemble machine learning and marginal prediction methods to identify the most salient factors associated with several COVID-19 outbreak measures.Findings: Our variable importance results show that measures of ethnicity, public transportation and preventable diseases are the strongest drivers for both incidence and mortality. Specifically, the CDC measures for minority populations, CDC measures for limited English, and proportion of Black/African-American individuals in a county were the most important features for COVID-19 cases at day 25 and to date. For mortality at day 100 and total to date, we find that public transportation use and proportion of Black/African-American individuals in a county are the strongest predictors. The methods predict that, keeping all other factors fixed, a 10% increase in public transportation use increases mortality at day 100 by 2012 (95% CI [1972, 2356]) and likewise a 10% increase in the proportion of Black/African-American individuals in a county increases total deaths to date by 2067 (95% CI [1189, 2654]). In terms of cases to date, ethnicity turns out to almost twice as important as the next most important factors, which are location, disease prevalence, and transit factors.Interpretations: Our findings indicate that a more focused approach should be taken when managing COVID-19, by considering features of the economy most responsible for transmission and sectors of society most vulnerable to infection and mortality. In particular, our results strongly reinforce others pointing to the disproportionate impact of COVID-19 on minority populations. They also suggests that mitigation measures, including rolling out vaccinations as they become available, will be most efficacious for the US population as a whole when, beyond healthcare workers and first responders, are focused first on the highest-risk communities.Funding: UC Berkeley, Biomedical Big Data Training Fellowship; NSF Grant 2032264 to WMG and AH.

Efficacy and Safety of Sofosbuvir/Daclatasvir in the Treatment of COVID-19: A Randomized, Controlled Study (preprint)

BACKGROUND: Data from molecular docking, in-vitro experiments and 2 published small clinical studies suggested a potential therapeutic benefit for the anti-hepatitis C drugs, sofosbuvir (SOF) and daclatasvir (DCV), to repurpose for the treatment of COVID-19. We planned this study to evaluate efficacy and safety of dual SOF/DCV as add-on treatment to the standard of care (SOC) in patients with COVID-19, initially hospitalized to a non-intensive care setting.METHODS: Eighty nine consecutive eligible patients presenting to a single center in Cairo were included in the study and randomly assigned to two treatment groups. The experimental group was treated with the SOC therapy (as per the Egyptian ministry of health protocol) in addition to one 400 mg tablet SOF and one 60 mg DCV daily for 10 days; while the control group was treated with the SOC therapy alone. Baseline clinical, laboratory and imaging data were measured and followed up for 21 days. Data were compared between the two treatment groups.FINDINGS: The proportion of cumulative clinical recovery in the experimental group at day 21 was numerically greater than the control group (40/44 (91%; CI: 78.8-96.4%) versus 35/45 (77.8%; 63.7-87.5%)). The Hazard Ratio (HR) for time to clinical recovery adjusted for baseline severity by a Cox-regression model was statistically significant: HR: 1.59 (CI: 1.001-2.5), signifying nearly 1.6 times higher probability of clinical recovery in the experimental group than the control at any time point during the study. Concordantly, the experimental group also showed trends to greater numerical improvement in other efficacy endpoints including the mean 8 points ordinal scale score, the mean severity of lung lesions score and the case fatality rate (4.5% versus 11.1%) than the control group. All these effects, though did not reach statistical significance at the study sample size, but being all concordant with the HR, they support the study concept. No serious or severe adverse events were reported in both groups and the treatment was well tolerated.INTERPRETATION: This study provides support to the potential benefits and safety of sofosbuvir combined with daclatasvir in the treatment of COVID-19. It is hoped to encourage further large sized multinational studies to confirm these encouraging results.Trial Registration: The study protocol was registered in the German clinical trial database repository (DRKS00022203) before the study initiation.Funding Statement: This study was funded by Pharco Corporate.Declaration of Interests: SH and OE are employees of Pharco, SH holds stock in Pharco. MY, AH conducted clinical studies and provided consultations for Pharco. Others have nothing to declare. Ethics Approval Statement: The study protocol was reviewed and approved by the Research Ethics Committee of Faculty of Medicine, Alexandria University (IRB00007555) and the Central Egyptian Ministry of Health and People Research Ethics Committee according to the Declaration of Helsinki. All subjects gave written informed consent before any treatment interventions were performed.

Significance between Air pollutants, Meteorological Factors and COVID-19 Infections: Probable Evidences in India (preprint)

SARS-CoV-2 (Coronavirus) disease represents the causative agent with a potentially fatal risk which is having great global human health concern. Earlier studies suggested that air pollutants and meteorological factors were considered as the risk factors for acute respiratory infection, which carries harmful pathogens and affects the immunity. The study intended to explore the correlation between air pollutants, meteorological factors and the daily reported infection cases caused by novel coronavirus in India. The daily positive infected cases, air pollution and meteorological factors in 288 districts were collected from January 30, 2020 to April 23, 2020 in India. Speraman’s correlation and generalised additive model were applied to investigate the correlations of four air pollutants (PM2.5, PM10, NO2 and SO2) and eight meteorological factors (Temp, DTR, RH, AH, AP, RF, WS and WD) with COVID-19 infected cases. The study indicated that a 10 µg/m3 increase during (Lag0-14) in PM2.5, PM10 and NO2 was resulted in 2.21% (95%CI: 1.13 to 3.29), 2.67% (95% CI: 0.33 to 5.01) and 4.56 (95% CI: 2.22 to 6.90) increase in daily counts of COVID 19 infected cases respectively. However, only 1 unit increase in meteorological factor levels in case of daily mean temperature and DTR during (Lag0-14) associated with 3.78% (95%CI: 1.81 to 5.75) and 1.82% (95% CI: -1.74 to 5.38) rise of COVID-19 infected cases respectively. In addition, SO2 and relative humidity were negatively associated with COVID-19 infected cases at Lag0-14 with decrease of 7.23% (95% CI: -10.99 to -3.47) and 1.11% (95% CI: -3.45 to 1.23) for SO2 and for relative humidity respectively. The study recommended that there is significant relationship between air pollutants and meteorological factors with COVID-19 infected cases, which substantially explain the effect of national lockdown and suggested positive implications for control and prevention of the spread of SARS-CoV-2 disease. 

Is there a role for blood purification therapies targeting cytokine storm syndrome in critically severe COVID-19 patients?

The coronavirus disease-19 (COVID-19) has spread over many countries and regions since the end of 2019, becoming the most severe public health event at present. Most of the critical cases developed multiple organ dysfunction, including acute kidney injury (AKI). Cytokine storm syndrome (CSS) may complicate the process of severe COVID-19 patients. This manuscript reviews the different aspects of blood purification in critically ill patients with AKI and increased inflammatory factors, and examines its potential role in severe COVID-19 treatment. Continuous renal replacement therapy (CRRT) has been practiced in many sepsis patients with AKI. Still, the timing and dosing need further robust evidence. In addition to the traditional CRRT, the high-throughput membrane with adsorption function and cytokine adsorption column are two representatives of recently emerging novel membrane technologies. Their potential in removing inflammatory factors and other toxins prospects for the treatment of severe COVID-19.

Will COVID-19 pandemic diminish by summer-monsoon in India? Lesson from the first lockdown (preprint)

The novel Coronavirus (2019-nCoV) was identified in Wuhan, Hubei Province, China, in December 2019 and has created a medical emergency worldwide. It has spread rapidly to multiple countries and has been declared a pandemic by the World Health Organization. In India, it is already reported more than 18 thousand cases and more than 600 deaths due to Coronavirus disease 2019 (COVID-19) till April 20, 2020. Previous studies on various viral infections like influenza have supported an epidemiological hypothesis that the cold and dry (low absolute humidity) environments favor the survival and spread of droplet-mediated viral diseases. These viral transmissions found attenuated in warm and humid (high absolute humidity) environments. However, the role of temperature, humidity, and absolute humidity in the transmission of COVID-19 has not yet been well established. Therefore the study to investigate the meteorological condition for incidence and spread of COVID-19 infection, to predict the epidemiology of the infectious disease, and to provide a scientific basis for prevention and control measures against the new disease is required for India. In this work, we analyze the local weather patterns of the Indian region affected by the COVID-19 virus for March and April months, 2020. We have investigated the effect of meteorological parameters like Temperature, relative humidity, and absolute humidity on the rate of spread of COVID-19 using daily confirm cases in India. We have used daily averaged meteorological data for the last three years (2017-2019) for March and April month and the same for the year 2020 for March 1 to April 15. We found a positive association (Pearsons r=0.56) between temperature and daily COVID-19 cases over India. We found a negative association of humidity (RH and AH) with daily COVID-19 Cases (Persons r=-0.62, -0.37). We have also investigated the role of aerosol in spreading the pandemic across India because its possible airborne nature. For this, we have investigated the association of aerosols (AOD) and other pollutions (NO2) with COVID-19 cases during the study period and also during the first lockdown period (25 March-15 April) in India. We found a negative association in March when there were few cases, but in April, it shows positive association when the number of cases is more (for AOD it was r=-0.41 and r=0.28 respectively). During the lockdown period, aerosols (AOD) and other pollutants (NO2; an indicator of PM2.5) reduced sharply with a percentage drop of about 36 and 37, respectively. This reduction may have reduced the risk for COVID-19 through air transmission due to the unavailability of aerosol particles as a base. HYSPLIT forward trajectory model also shows that surface aerosols may travel up to 4 km according to wind and direction within three h of its generation. If coronavirus becomes airborne as suggested by many studies, then it may have a higher risk of transmission by aerosols particles. So relaxing in the lockdown and environmental rules in terms of pollutant emissions from power plants, factories, and other facilities would be a wrong choice and could result in more COVID-19 incidences and deaths in India. Therefore the current study, although limited, suggests that it is doubtful that the spread of COVID-19 would slow down in India due to meteorological factors, like high temperature and high humidity. Because a large number of cases have already been reported in the range of high Tem, high Relative, and high absolute humidity regions of India. Thus our results in no way suggest that COVID-19 would not spread in warm, humid regions or during summer/monsoon. So effective public health interventions should be implemented across India to slow down the transmission of COVID-19. If COVID-19 is indeed sensitive to environmental factors, it could be tested in the coming summer-monsoon for India. So the only summer is not going to help India until monsoon is coming. Only government mitigations strategies would be helpful, whether its lockdown, aggressive and strategic testing, medical facilities, imposing social distancing, encouraging to use face mask or monitoring by a mobile application (Aarogya Setu).

Structural basis to design multi-epitope vaccines against Novel Coronavirus 19 (COVID19) infection, the ongoing pandemic emergency: an in silico approach (preprint)

The 2019 novel coronavirus (COVID19 / Wuhan coronavirus), officially named as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is a positive-sense single-stranded RNA coronavirus. SARS-CoV-2 causes the contagious COVID19 disease also known as 2019-nCoV acute respiratory disease and has led to the ongoing 2019-20 pandemic COVID19 outbreak. The effective counter measures against SARS-CoV-2 infection require the design and development of specific and effective vaccine candidate. In the present study, we have screened and shortlisted 38 CTL, 33 HTL and 12 B cell epitopes from the eleven Protein sequences of SARS-CoV-2 by utilizing different in silico tools. The screened epitopes were further validated for their binding with their respective HLA allele binders and TAP (Transporter associated with antigen processing) molecule by molecular docking. The shortlisted screened epitopes were further utilized to design novel two multi-epitope vaccines (MEVs) composed of CTL, HTL and B cell epitopes overlaps with potential to elicit humoral as well as cellular immune response against SARS-CoV-2. To enhance the immune response for our vaccine design, truncated (residues 10-153) Onchocerca volvulus activation-associated secreted protein-1 (Ov-ASP-1) has been utilized as an adjuvant at N terminal of both the MEVs. Further molecular models for both the MEVs were prepared and validated for their stable molecular interactions with Toll-Like Receptor 3 (TLR 3). The codon-optimized cDNA of both the MEVs were further analyzed for their potential of high level of expression in a human cell line. The present study is very significant in terms of molecular designing of prospective CTL and HTL vaccine against SARS-CoV-2 infection with the potential to elicit cellular as well as humoral immune response. (SARS-CoV-2), Coronavirus, Human Transporter associated with antigen processing (TAP), Toll-Like Receptor (TLR), Epitope, Immunoinformatics, Molecular Docking, Molecular dynamics simulation, Multi-epitope Vaccine Graphical abstractThe designed CTL (Cytotoxic T lymphocyte) and HTL (Helper T lymphocyte) multi-epitope vaccines (MEV) against COVID19 infection. Both the CTL and HTL MEV models show a very stable and well fit conformational complex formation tendency with the Toll like receptor 3. CTL and HTL MEVs: ribbon; Toll like receptor 3: gray cartoon; Adjuvant [truncated (residues 10-153) Onchocerca volvulus activation-associated secreted protein-1]: orange ribbon regions; Epitopes: cyan ribbons regions; 6xHis Tag: magenta ribbon regions. O_FIG O_LINKSMALLFIG WIDTH=87 HEIGHT=200 SRC="FIGDIR/small/019299v2_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@6cb749org.highwire.dtl.DTLVardef@1752d54org.highwire.dtl.DTLVardef@1f2fc16org.highwire.dtl.DTLVardef@18415a9_HPS_FORMAT_FIGEXP M_FIG C_FIG

Design of a Peptide-Based Subunit Vaccine against Novel Coronavirus SARS-CoV-2 (preprint)

Coronavirus disease 2019 (COVID-19) is an emerging infectious disease that was first reported in Wuhan, China and has subsequently spread worldwide. In the absence of any antiviral or immunomodulatory therapies, the disease is spreading at an alarming rate. 5 to 10% of recovered patients in Wuhan test positive again; this suggest that for controlling COVID-19, vaccines may be better option than drugs. A clinical trial to evaluate an anti-COVID-19 vaccine has started recently. However, its efficacy and potency have to be evaluated and validated. As an alternative, we are presenting a first-of-its-kind, designed multi-peptide subunit based epitope vaccine against COVID-19. The vaccine construct comprise an adjuvant, CTL, HTL, and B-cell epitopes joined by linkers. The vaccine is non-toxic, non-allergenic, thermostable and immunogenic with the capability to elicit a humoral and cell-mediated immune response. The findings are validated with high-end computation-based methods. This unique vaccine is made up of 33 highly antigenic epitopes from three proteins that have a prominent role in host receptor recognition, viral entry, and pathogenicity. We advocate this vaccine must be synthesized and tested urgently as public health priority.