Learning about Zika virus epidemiology and diagnostics from blood donor studies

Rational design of B-cell and T-cell multi epitope-based vaccine against Zika virus, an in silico study

The Zika virus (ZKV) is a single-stranded positive-sense, enveloped RNA virus. Zika infection during pregnancy can cause congenital microcephaly, Guillain-Barré syndrome, miscarriage, and other CNS abnormalities. The world needs safe and effective vaccinations to fight against ZIKV infection since vaccination is generally regarded as one of the most effective ways to prevent infectious diseases. In the present work, we used immunoinformatics and docking studies to construct a vaccine containing multi-epitopes using the structural and non-structural proteins of ZKV. The structural models of ZKV proteins (PrE, PrM, NS1, and NS2A) were constructed using Pyre2 and RaptorX servers. The epitopes of B-cell, T-cell (HTL and CTL), and IFN-γ were predicted, and each epitope's immunogenic nature and physiochemical properties were confirmed. As an adjuvant, the CPG-Oligodeoxynucleotide, an agonist of Toll-like receptor 9 (TLR9), is associated to cytotoxic T-lymphocytes (CTL) epitopes via PAPAP linker. To assess the binding affinity and the tendency of the designed vaccine to induce an immune response through TLR9, molecular docking was done. In the next step, molecular dynamics (MD) simulation to 100 nanoseconds (ns) was used to evaluate the stability of the interaction of the designed vaccine with TLR9. The designed vaccine is predicted to be highly antigenic, non-toxic, soluble, and stable with low flexibility in MD simulation. MD studies indicated that the finalized vaccine-TLR9 docked complex was stable during simulation time. The vaccine construct is able to stimulate both humoral and cellular immune responses. We suppose that our constructed model of the vaccine may have the ability to induce the host immune response against ZKV. Further studies, including in vitro and in vivo experimental analyses, are needed to prove the constructed vaccine's efficacy with multi-epitopes.Communicated by Ramaswamy H. Sarma.

Aerosolized Zika Virus Infection in Guinea Pigs

Zika virus (ZIKV) is primarily transmitted through mosquito bites and sexual contact, and vertical transmission of ZIKV has also been observed in humans. In addition, ZIKV infection via unknown transmission routes has been frequently reported in clinical settings. However, whether ZIKV can be transmitted via aerosol routes remains unknown. In this study, we demonstrated that aerosolized ZIKV is fully infectious in vitro and in vivo. Remarkably, intratracheal (i.t.) inoculation with aerosolized ZIKV led to rapid viremia and viral secretion in saliva, as well as robust humoral and innate immune responses in guinea pigs. Transcriptome analysis further revealed that the expression of genes related to viral processes, biological regulation and the immune response was significantly changed. Together, our results confirm that aerosolized ZIKV can result in systemic infection and induce both innate and adaptive immune responses in guinea pigs, highlighting the possibility of ZIKV transmission via aerosols.

How do we…form and coordinate a national serosurvey of SARS-CoV-2 within the blood collection industry?

Background

A national serosurvey of U.S. blood donors conducted in partnership with the Centers for Disease Control and Prevention (CDC) was initiated to estimate the prevalence of SARS‐CoV‐2 infections and vaccinations.

Methods

Beginning in July 2020, the Nationwide Blood Donor Seroprevalence Study collaborated with multiple blood collection organizations, testing labs, and leadership from government partners to capture, test, and analyze approximately 150,000 blood donation specimens per month in a repeated, cross‐sectional seroprevalence survey.

Results

A CDC website (https://covid.cdc.gov/covid-data-tracker/#nationwide-blood-donor-seroprevalence) provided stratified, population‐level results to public health professionals and the general public.

Discussion

The study adapted operations as the pandemic evolved, changing specimen flow and testing algorithms, and collecting additional data elements in response to changing policies on universal blood donation screening and administration of SARS‐CoV‐2 spike‐based vaccines. The national serosurvey demonstrated the utility of serosurveillance testing of residual blood donations and highlighted the role of the blood collection industry in public–private partnerships during a public health emergency.

Modeling time evolving COVID-19 uncertainties with density dependent asymptomatic infections and social reinforcement

The COVID-19 pandemic has posed significant challenges in modeling its complex epidemic transmissions, infection and contagion, which are very different from known epidemics. The challenges in quantifying COVID-19 complexities include effectively modeling its process and data uncertainties. The uncertainties are embedded in implicit and high-proportional undocumented infections, asymptomatic contagion, social reinforcement of infections, and various quality issues in the reported data. These uncertainties become even more apparent in the first 2 months of the COVID-19 pandemic, when the relevant knowledge, case reporting and testing were all limited. Here we introduce a novel hybrid approach SUDR by expanding the foundational compartmental epidemic Susceptible-Infected-Recovered (SIR) model with two compartments to a Susceptible-Undocumented infected-Documented infected-Recovered (SUDR) model. First, SUDR (1) characterizes and distinguishes Undocumented (U) and Documented (D) infections commonly seen during COVID-19 incubation periods and asymptomatic infections. Second, SUDR characterizes the probabilistic density of infections by capturing exogenous processes like clustering contagion interactions, superspreading, and social reinforcement. Lastly, SUDR approximates the density likelihood of COVID-19 prevalence over time by incorporating Bayesian inference into SUDR. Different from existing COVID-19 models, SUDR characterizes the undocumented infections during unknown transmission processes. To capture the uncertainties of temporal transmission and social reinforcement during COVID-19 contagion, the transmission rate is modeled by a time-varying density function of undocumented infectious cases. By sampling from the mean-field posterior distribution with reasonable priors, SUDR handles the randomness, noise and sparsity of COVID-19 observations widely seen in the public COVID-19 case data. The results demonstrate a deeper quantitative understanding of the above uncertainties, in comparison with classic SIR, time-dependent SIR, and probabilistic SIR models.

Persistent, new-onset symptoms and mental health complaints in Long COVID in a Brazilian cohort of non-hospitalized patients

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections lead to acute- and chronic Long COVID (LC) symptoms. However, few studies have addressed LC sequelae on brain functions. This study was aimed to examine if acute symptoms of coronavirus disease 2019 (COVID-19) would persist during LC, and if memory problems would be correlated with sleep, depressive mood, or anxious complaints.

METHODS

Our work followed a cohort of 236 patients from two public hospitals of the Federal District in mid-western Brazil. Patients' interviews checked for clinical symptoms during acute and LC (5-8 months after real-time reverse transcription polymerase chain reaction, RT-qPCR).

RESULTS

Most cases were non-hospitalized individuals (86.3%) with a median age of 41.2 years. While myalgia (50%), hyposmia (48.3%), and dysgeusia (45.8%) were prevalent symptoms in acute phase, fatigue (21.6%) followed by headache (19.1%) and myalgia (16.1%) commonly occurred during LC. In LC, 39.8% of individuals reported memory complaints, 36.9% felt anxious, 44.9% felt depressed, and 45.8% had sleep problems. Furthermore, memory complaints were associated with sleep problems (adjusted OR 3.206; 95% CI 1.723-6.030) and depressive feelings (adjusted OR 3.981; 95% CI 2.068-7.815).

CONCLUSIONS

The SARS-CoV-2 infection leads to persistent symptoms during LC, in which memory problems may be associated with sleep and depressive complaints.

SARS-CoV-2 infection reduces human nasopharyngeal commensal microbiome with inclusion of pathobionts

The microbiota of the nasopharyngeal tract (NT) play a role in host immunity against respiratory infectious diseases. However, scant information is available on interactions of SARS-CoV-2 with the nasopharyngeal microbiome. This study characterizes the effects of SARS-CoV-2 infection on human nasopharyngeal microbiomes and their relevant metabolic functions. Twenty-two (n = 22) nasopharyngeal swab samples (including COVID-19 patients = 8, recovered humans = 7, and healthy people = 7) were collected, and underwent to RNAseq-based metagenomic investigation. Our RNAseq data mapped to 2281 bacterial species (including 1477, 919 and 676 in healthy, COVID-19 and recovered metagenomes, respectively) indicating a distinct microbiome dysbiosis. The COVID-19 and recovered samples included 67% and 77% opportunistic bacterial species, respectively compared to healthy controls. Notably, 79% commensal bacterial species found in healthy controls were not detected in COVID-19 and recovered people. Similar dysbiosis was also found in viral and archaeal fraction of the nasopharyngeal microbiomes. We also detected several altered metabolic pathways and functional genes in the progression and pathophysiology of COVID-19. The nasopharyngeal microbiome dysbiosis and their genomic features determined by our RNAseq analyses shed light on early interactions of SARS-CoV-2 with the nasopharyngeal resident microbiota that might be helpful for developing microbiome-based diagnostics and therapeutics for this novel pandemic disease.