Complete Genome Sequencing, Annotation, and Mutational Profiling of the Novel Clade I Human Mpox Virus, Kamituga Strain.

INTRODUCTION: Human Mpox (formerly monkeypox) infection is an emerging zoonotic disease caused by the Mpox virus (MPXV). We describe the complete genome annotation, phylogeny, and mutational profile of a novel, sustained Clade I Mpox outbreak in the city of Kamituga in Eastern Democratic Republic of the Congo (DRC). METHODOLOGY: A cross-sectional, observational, cohort study was performed among patients of all ages admitted to the Kamituga Hospital with Mpox infection symptoms between late September 2023 and late January 2024. DNA was isolated from Mpox swabbed lesions and sequenced followed by phylogenetic analysis, genome annotation, and mutational profiling. RESULTS: We describe an ongoing Clade I Mpox outbreak in the city of Kamituga, South Kivu Province, Democratic Republic of Congo. Whole-genome sequencing of the viral RNA samples revealed, on average, 201.5 snps, 28 insertions, 81 deletions, 2 indels, 312.5 total variants, 158.3 amino acid changes, 81.66 intergenic variants, 72.16 synonymous mutations, 106 missense variants, 41.16 frameshift variants, and 3.33 inframe deletions across six samples. By assigning mutations at the proteome level for Kamituga MPXV sequences, we observed that seven proteins, namely, C9L (OPG047), I4L (OPG080), L6R (OPG105), A17L (OPG143), A25R (OPG151), A28L (OPG153), and B21R (OPG210) have emerged as hot spot mutations based on the consensuses inframe deletions, frameshift variants, synonymous variants, and amino acids substitutions. Based on the outcome of the annotation, we found a deletion of the D14L (OPG032) gene in all six samples. Following phylogenetic analysis and whole genome assembly, we determined that this cluster of Mpox infections is genetically distinct from previously reported Clade I outbreaks, and thus propose that the Kamituga Mpox outbreak represents a novel subgroup (subgroup VI) of Clade I MPXV. CONCLUSIONS: Here we report the complete viral genome for the ongoing Clade I Mpox Kamituga outbreak for the first time. This outbreak presents a distinct mutational profile from previously sequenced Clade I MPXV oubtreaks, suggesting that this cluster of infections is a novel subgroup (we term this subgroup VI). These findings underscore the need for ongoing vigilance and continued sequencing of novel Mpox threats in endemic regions.

PASC (Post Acute Sequelae of COVID-19) is associated with decreased neutralizing antibody titers in both biological sexes and increased ANG-2 and GM-CSF in females.

Post-acute sequelae of COVID-19 (PASC) or the continuation of COVID-19 (Coronavirus disease 2019) symptoms past 12 weeks may affect as many as 30% of people recovering from a SARS-CoV-2 (severe acute respiratory coronavirus 2) infection. The mechanisms regulating the development of PASC are currently not known; however, hypotheses include virus reservoirs, pre-existing conditions, microblood clots, immune dysregulation, as well as poor antibody responses. Importantly, virus neutralizing antibodies are essential for COVID-19 recovery and protection from reinfection but there is currently limited information on these immune regulators and associated cytokines in PASC patients. Understanding the key drivers of general and specific symptoms associated with Long COVID and the presence of virus neutralizing antibodies in PASC will aid in the development of therapeutics, diagnostics, and vaccines which currently do not exist. We designed a cross-sectional study to investigate systemic antibody and cytokine responses during COVID-19 recovery and PASC. In total, 195 participants were recruited in one of four groups: (1) Those who never had COVID-19 (No COVID); (2) Those in acute COVID-19 recovery (Acute Recovery) (4-12 weeks post infection); (3) Those who recovered from COVID-19 (Recovered) (+ 12 weeks from infection); and (4) those who had PASC (PASC) (+ 12 weeks from infection). Participants completed a questionnaire on health history, sex, gender, demographics, experiences with COVID-19 acute and COVID-19 recovery/continuing symptoms. Serum samples collected were evaluated for antibody binding to viral proteins, virus neutralizing antibody titers, and serum cytokine levels using Ella SimplePlex Immunoassay™ panels. We found participants with PASC reported more pre-existing conditions (e.g. such as hypertension, asthma, and obesity), and PASC symptoms (e.g. fatigue, brain fog, headaches, and shortness of breath) following COVID-19 than COVID-19 Recovered individuals. Importantly, we found PASC individuals to have significantly decreased levels of neutralizing antibodies toward both SARS-CoV-2 and the Omicron BA.1 variant. Sex analysis indicated that female PASC study participants had sustained antibody levels as well as levels of the inflammatory cytokines GM-CSF and ANG-2 over time following COVID-19. Our study reports people experiencing PASC had lower levels of virus neutralizing antibodies; however, the results are limited by the collection time post-COVID-19 and post-vaccination. Moreover, we found females experiencing PASC had sustained levels of GM-CSF and ANG-2. With lower levels of virus neutralizing antibodies, this data suggests that PASC individuals not only have had a suboptimal antibody response during acute SARS-CoV-2 infection but may also have increased susceptibility to subsequent infections which may exacerbate or prolong current PASC illnesses. We also provide evidence suggesting GM-CSF and ANG-2 to play a role in the sex-bias of PASC. Taken together, our findings maybe important for understanding immune molecular drivers of PASC and PASC subgroups.

The impact of public transportation on the transmission of COVID-19 in Rwanda.

Introduction: The onset of the COVID-19 pandemic has placed a significant burden on healthcare systems worldwide, particularly in sub-Saharan regions where healthcare resources are limited. The transmission of SARS-CoV-2 is facilitated by the movement of people from place to place. Therefore, implementing measures that restrict movement of people and contacts is crucial in controlling the spread of the disease. Following the identification of the first COVID-19 case in Rwanda, the government implemented stringent measures, including a complete nationwide lockdown, border closures, curfews, reduced capacity in public transportation and businesses, and mandatory testing. This study aims to assess epidemiological trends in COVID-19 cases in relation to changes in population mobility within the public transportation system. Methods: A descriptive analysis using publicly available data on COVID-19 epidemiological indicators (cases, deaths, vaccinations, and stringency index) and mobility data was conducted. Results: The results reveal a strong correlation between mobility in public transportation and other activities, underscoring Rwanda's reliance on its public transportation system. The study also identifies a pattern where increases in transit station mobility preceded spikes in COVID-19 cases, suggesting that the subsequent rise in public transportation usage may contribute to higher infection rates. Discussion: Therefore, this study emphasizes the importance of ongoing vigilance and regulatory measures regarding public transportation during infectious disease outbreaks.

CDBProm: the Comprehensive Directory of Bacterial Promoters.

The decreasing cost of whole genome sequencing has produced high volumes of genomic information that require annotation. The experimental identification of promoter sequences, pivotal for regulating gene expression, is a laborious and cost-prohibitive task. To expedite this, we introduce the Comprehensive Directory of Bacterial Promoters (CDBProm), a directory of in-silico predicted bacterial promoter sequences. We first identified that an Extreme Gradient Boosting (XGBoost) algorithm would distinguish promoters from random downstream regions with an accuracy of 87%. To capture distinctive promoter signals, we generated a second XGBoost classifier trained on the instances misclassified in our first classifier. The predictor of CDBProm is then fed with over 55 million upstream regions from more than 6000 bacterial genomes. Upon finding potential promoter sequences in upstream regions, each promoter is mapped to the genomic data of the organism, linking the predicted promoter with its coding DNA sequence, and identifying the function of the gene regulated by the promoter. The collection of bacterial promoters available in CDBProm enables the quantitative analysis of a plethora of bacterial promoters. Our collection with over 24 million promoters is publicly available at https://aw.iimas.unam.mx/cdbprom/.

PoxiPred: An Artificial-Intelligence-Based Method for the Prediction of Potential Antigens and Epitopes to Accelerate Vaccine Development Efforts against Poxviruses.

Poxviridae is a family of large, complex, enveloped, and double-stranded DNA viruses. The members of this family are ubiquitous and well known to cause contagious diseases in humans and other types of animals as well. Taxonomically, the poxviridae family is classified into two subfamilies, namely Chordopoxvirinae (affecting vertebrates) and Entomopoxvirinae (affecting insects). The members of the Chordopoxvirinae subfamily are further divided into 18 genera based on the genome architecture and evolutionary relationship. Of these 18 genera, four genera, namely Molluscipoxvirus, Orthopoxvirus, Parapoxvirus, and Yatapoxvirus, are known for infecting humans. Some of the popular members of poxviridae are variola virus, vaccine virus, Mpox (formerly known as monkeypox), cowpox, etc. There is still a pressing demand for the development of effective vaccines against poxviruses. Integrated immunoinformatics and artificial-intelligence (AI)-based methods have emerged as important approaches to design multi-epitope vaccines against contagious emerging infectious diseases. Despite significant progress in immunoinformatics and AI-based techniques, limited methods are available to predict the epitopes. In this study, we have proposed a unique method to predict the potential antigens and T-cell epitopes for multiple poxviruses. With PoxiPred, we developed an AI-based tool that was trained and tested with the antigens and epitopes of poxviruses. Our tool was able to locate 3191 antigen proteins from 25 distinct poxviruses. From these antigenic proteins, PoxiPred redundantly located up to five epitopes per protein, resulting in 16,817 potential T-cell epitopes which were mostly (i.e., 92%) predicted as being reactive to CD8+ T-cells. PoxiPred is able to, on a single run, identify antigens and T-cell epitopes for poxviruses with one single input, i.e., the proteome file of any poxvirus.

Inhibition potential of natural flavonoids against selected omicron (B.1.19) mutations in the spike receptor binding domain of SARS-CoV-2: a molecular modeling approach.

The omicron (B.1.19) variant of contagious severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is considered a variant of concern (VOC) due to its increased transmissibility and highly infectious nature. The spike receptor-binding domain (RBD) is a hotspot of mutations and is regarded as a prominent target for screening drug candidates owing to its crucial role in viral entry and immune evasion. To date, no effective therapy or antivirals have been reported; therefore, there is an urgent need for rapid screening of antivirals. An extensive molecular modelling study has been performed with the primary goal to assess the inhibition potential of natural flavonoids as inhibitors against RBD from a manually curated library. Out of 40 natural flavonoids, five natural flavonoids, namely tomentin A (-8.7 kcal/mol), tomentin C (-8.6 kcal/mol), hyperoside (-8.4 kcal/mol), catechin gallate (-8.3 kcal/mol), and corylifol A (-8.2 kcal/mol), have been considered as the top-ranked compounds based on their binding affinity and molecular interaction profiling. The state-of-the-art molecular dynamics (MD) simulations of these top-ranked compounds in complex with RBD exhibited stable dynamics and structural compactness patterns on 200 nanoseconds. Additionally, complexes of these molecules demonstrated favorable free binding energies and affirmed the docking and simulation results. Moreover, the post-simulation validation of these interacted flavonoids using principal component analysis (PCA) revealed stable interaction patterns with RBD. The integrated results suggest that tomentin A, tomentin C, hyperoside, catechin gallate, and corylifol A might be effective against the emerging variants of SARS-CoV-2 and should be further evaluated using in-vitro and in-vivo experiments.Communicated by Ramaswamy H. Sarma.

Third COVID-19 vaccine dose boosts antibody function in Rwandans with high HIV viral load.

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) causing COVID-19 (coronavirus disease 2019) poses a greater health risk to immunocompromized individuals including people living with HIV (PLWH). However, most studies on PLWH have been conducted in higher-income countries. We investigated the post-vaccination antibody responses of PLWH in Rwanda by collecting peripheral blood from participants after receiving a second or third COVID-19 vaccine. Virus-binding antibodies as well as antibody neutralization ability against all major SARS-CoV-2 variants of concern were analyzed. We found that people with high HIV viral loads and two COVID-19 vaccine doses had lower levels of binding antibodies that were less virus neutralizing and less cross-reactive compared to control groups. A third vaccination increased neutralizing antibody titers. Our data suggest that people with high HIV viral loads require a third dose of vaccine to neutralize SARS-CoV-2 virus and new variants as they emerge.

Host Transcriptome Analysis of Ferret Tissues Following Henipavirus Infection.

Ferrets are commonly used as experimental models of infection for a variety of viruses due to their susceptibility to human respiratory viruses and the close resemblance of pathological outcomes found in human infections. Even though ferret-specific reagents are limited, the use of ferrets as a preclinical experimental model of infection has gained considerable interest since the publication of the ferret transcriptome and draft ferret genome. These advances have made it feasible to easily perform whole-genome gene expression analysis in the ferret infection model. Here, we describe methods for genome-wide gene expression analysis using RNA sequence (RNAseq) data obtained from the lung and brain tissues obtained from experimental infections of Hendra (HeV) and Nipah (NiV) viruses in ferrets. We provide detailed methods for RNAseq and representative data for host gene expression profiles of the lung tissues that show early activation of interferon pathways and later activation of inflammation-related pathways.

RNAseq Analysis of Novel 1,3,4-Oxadiazole Chalcogen Analogues Reveals Anti-Tubulin Properties on Cancer Cell Lines.

1,3,4-Oxadiazole derivatives are among the most studied anticancer drugs. Previous studies have analyzed the action of different 1,3,4-oxadiazole derivatives and their effects on cancer cells. This study investigated the characterization of two new compounds named 6 and 14 on HeLa and PC-3 cancer cell lines. Based on the previously obtained IC50, cell cycle effects were monitored by flow cytometry. RNA sequencing (RNAseq) was performed to identify differentially expressed genes, followed by functional annotation using gene ontology (GO), KEGG signaling pathway enrichment, and protein-protein interaction (PPI) network analyses. The tubulin polymerization assay was used to analyze the interaction of both compounds with tubulin. The results showed that 6 and 14 strongly inhibited the proliferation of cancer cells by arresting them in the G2/M phase of the cell cycle. Transcriptome analysis showed that exposure of HeLa and PC-3 cells to the compounds caused a marked reprograming of gene expression. Functional enrichment analysis indicated that differentially expressed genes were significantly enriched throughout the cell cycle and cancer-related biological processes. Furthermore, PPI network, hub gene, and CMap analyses revealed that compounds 14 and 6 shared target genes with established microtubule inhibitors, indicating points of similarity between the two molecules and microtubule inhibitors in terms of the mechanism of action. They were also able to influence the polymerization process of tubulin, suggesting the potential of these new compounds to be used as efficient chemotherapeutic agents.

Convergence in Mobility Data Sets From Apple, Google, and Meta.

BACKGROUND: The higher movement of people was one of the variables that contributed to the spread of the infectious agent SARS-CoV-2 during the COVID-19 pandemic. Governments worldwide responded to the virus by implementing measures that would restrict people's movements, and consequently, the spread of the disease. During the onset of the pandemic, the technology companies Apple, Google, and Meta used their infrastructure to anonymously gather mobility reports from their users. OBJECTIVE: This study aims to compare mobility data reports collected by Apple, Google, and Meta (formerly Facebook) during the COVID-19 pandemic and a major winter storm in Texas in 2021. We aim to explore the hypothesis that different people exhibit similar mobility trends during dramatic events and to emphasize the importance of this type of data for public health measures. The study also aims to promote evidence for companies to continue releasing mobility trends data, given that all 3 companies have discontinued these services. METHODS: In this study, we collected mobility data spanning from 2020 to 2022 from 3 major tech companies: Apple, Google, and Meta. Our analysis focused on 58 countries that are common to all 3 databases, enabling us to conduct a comprehensive global-scale analysis. By using the winter storm that occurred in Texas in 20201 as a benchmark, we were able to assess the robustness of the mobility data obtained from the 3 companies and ensure the integrity of our findings. RESULTS: Our study revealed convergence in the mobility trends observed across different companies during the onset of significant disasters, such as the first year of the COVID-19 pandemic and the winter storm that impacted Texas in 2021. Specifically, we observed strong positive correlations (r=0.96) in the mobility data collected from different tech companies during the first year of the pandemic. Furthermore, our analysis of mobility data during the 2021 winter storm in Texas showed a similar convergence of trends. Additionally, we found that periods of stay-at-home orders were reflected in the data, with record-low mobility and record-high stay-at-home figures. CONCLUSIONS: Our findings provide valuable insights into the ways in which major disruptive events can impact patterns of human mobility; moreover, the convergence of data across distinct methodologies highlights the potential value of leveraging mobility data from multiple sources for informing public health decision-making. Therefore, we conclude that the use of mobility data is an asset for health authorities to consider during natural disasters, as we determined that the data sets from 3 companies yielded convergent mobility patterns. Comparatively, data obtained from a single source would be limited, and therefore, more difficult to interpret, requiring careful analysis.

Repurposing of drugs against methyltransferase as potential Zika virus therapies.

In recent years, the outbreak of infectious disease caused by Zika Virus (ZIKV) has posed a major threat to global public health, calling for the development of therapeutics to treat ZIKV disease. Several possible druggable targets involved in virus replication have been identified. In search of additional potential inhibitors, we screened 2895 FDA-approved compounds using Non-Structural Protein 5 (NS5) as a target utilizing virtual screening of in-silco methods. The top 28 compounds with the threshold of binding energy -7.2 kcal/mol value were selected and were cross-docked on the three-dimensional structure of NS5 using AutoDock Tools. Of the 2895 compounds screened, five compounds (Ceforanide, Squanavir, Amcinonide, Cefpiramide, and Olmesartan_Medoxomil) ranked highest based on filtering of having the least negative interactions with the NS5 and were selected for Molecular Dynamic Simulations (MDS) studies. Various parameters such as RMSD, RMSF, Rg, SASA, PCA and binding free energy were calculated to validate the binding of compounds to the target, ZIKV-NS5. The binding free energy was found to be -114.53, -182.01, -168.19, -91.16, -122.56, and -150.65 kJ mol-1 for NS5-SFG, NS5-Ceforanide, NS5-Squanavir, NS5-Amcinonide, NS5-Cefpiramide, and NS5-Ol_Me complexes respectively. The binding energy calculations suggested Cefpiramide and Olmesartan_Medoxomil (Ol_Me) as the most stable compounds for binding to NS5, indicating a strong rationale for their use as lead compounds for development of ZIKV inhibitors. As these drugs have been evaluated on pharmacokinetics and pharmacodynamics parameters only, in vitro and in vivo testing and their impact on Zika viral cell culture may suggest their clinical trials on ZIKV patients.

Evaluating the effectiveness of lockdowns and restrictions during SARS-CoV-2 variant waves in the Canadian province of Nova Scotia.

Introduction: After the initial onset of the SARS-CoV-2 pandemic, the government of Canada and provincial health authorities imposed restrictive policies to limit virus transmission and mitigate disease burden. In this study, the pandemic implications in the Canadian province of Nova Scotia (NS) were evaluated as a function of the movement of people and governmental restrictions during successive SARS-CoV-2 variant waves (i.e., Alpha through Omicron). Methods: Publicly available data obtained from community mobility reports (Google), the Bank of Canada Stringency Index, the "COVID-19 Tracker" service, including cases, hospitalizations, deaths, and vaccines, population mobility trends, and governmental response data were used to relate the effectiveness of policies in controlling movement and containing multiple waves of SARS-CoV-2. Results: Our results indicate that the SARS-CoV-2 pandemic inflicted low burden in NS in the initial 2 years of the pandemic. In this period, we identified reduced mobility patterns in the population. We also observed a negative correlation between public transport (-0.78), workplace (-0.69), retail and recreation (-0.68) and governmental restrictions, indicating a tight governmental control of these movement patterns. During the initial 2 years, governmental restrictions were high and the movement of people low, characterizing a 'seek-and-destroy' approach. Following this phase, the highly transmissible Omicron (B.1.1.529) variant began circulating in NS at the end of the second year, leading to increased cases, hospitalizations, and deaths. During this Omicron period, unsustainable governmental restrictions and waning public adherence led to increased population mobility, despite increased transmissibility (26.41-fold increase) and lethality (9.62-fold increase) of the novel variant. Discussion: These findings suggest that the low initial burden caused by the SARS-CoV-2 pandemic was likely a result of enhanced restrictions to contain the movement of people and consequently, the spread of the disease. Easing public health restrictions (as measured by a decline in the BOC index) during periods of high transmissibility of circulating COVID-19 variants contributed to community spread, despite high levels of immunization in NS.

Effect of viral storm in patients admitted to intensive care units with severe COVID-19 in Spain: a multicentre, prospective, cohort study.

BACKGROUND: The contribution of the virus to the pathogenesis of severe COVID-19 is still unclear. We aimed to evaluate associations between viral RNA load in plasma and host response, complications, and deaths in critically ill patients with COVID-19. METHODS: We did a prospective cohort study across 23 hospitals in Spain. We included patients aged 18 years or older with laboratory-confirmed SARS-CoV-2 infection who were admitted to an intensive care unit between March 16, 2020, and Feb 27, 2021. RNA of the SARS-CoV-2 nucleocapsid region 1 (N1) was quantified in plasma samples collected from patients in the first 48 h following admission, using digital PCR. Patients were grouped on the basis of N1 quantity: VIR-N1-Zero (<1 N1 copies per mL), VIR-N1-Low (1-2747 N1 copies per mL), and VIR-N1-Storm (>2747 N1 copies per mL). The primary outcome was all-cause death within 90 days after admission. We evaluated odds ratios (ORs) for the primary outcome between groups using a logistic regression analysis. FINDINGS: 1068 patients met the inclusion criteria, of whom 117 had insufficient plasma samples and 115 had key information missing. 836 patients were included in the analysis, of whom 403 (48%) were in the VIR-N1-Low group, 283 (34%) were in the VIR-N1-Storm group, and 150 (18%) were in the VIR-N1-Zero group. Overall, patients in the VIR-N1-Storm group had the most severe disease: 266 (94%) of 283 patients received invasive mechanical ventilation (IMV), 116 (41%) developed acute kidney injury, 180 (65%) had secondary infections, and 148 (52%) died within 90 days. Patients in the VIR-N1-Zero group had the least severe disease: 81 (54%) of 150 received IMV, 34 (23%) developed acute kidney injury, 47 (32%) had secondary infections, and 26 (17%) died within 90 days (OR for death 0·30, 95% CI 0·16-0·55; p<0·0001, compared with the VIR-N1-Storm group). 106 (26%) of 403 patients in the VIR-N1-Low group died within 90 days (OR for death 0·39, 95% CI 0·26-0·57; p<0·0001, compared with the VIR-N1-Storm group). INTERPRETATION: The presence of a so-called viral storm is associated with increased all-cause death in patients admitted to the intensive care unit with severe COVID-19. Preventing this viral storm could help to reduce poor outcomes. Viral storm could be an enrichment marker for treatment with antivirals or purification devices to remove viral components from the blood. FUNDING: Instituto de Salud Carlos III, Canadian Institutes of Health Research, Li Ka-Shing Foundation, Research Nova Scotia, and European Society of Clinical Microbiology and Infectious Diseases. TRANSLATION: For the Spanish translation of the abstract see Supplementary Materials section.

Drug repurposing for Mpox: Discovery of small molecules as potential inhibitors against DNA-dependent RNA polymerase using molecular modeling approach.

Mpox (formerly Monkeypox), a zoonotic illness caused by the Mpox virus, belongs to the Orthopoxvirus genus in the family Poxviridae. To design and develop effective antiviral therapeutics against DNA viruses, the DNA-dependent RNA polymerase (DdRp) of poxviruses has emerged as a promising drug target. In the present study, we modeled the three-dimensional (3D) structure of DdRp using a template-based homology approach. After modeling, virtual screening was performed to probe the molecular interactions between 1755 Food and Drug Administration-approved small molecule drugs (≤500 molecular weight) and the DdRp of Mpox. Based on the binding affinity and molecular interaction patterns, five drugs, lumacaftor (-11.7 kcal/mol), conivaptan (-11.7 kcal/mol), betulinic acid (-11.6 kcal/mol), fluspirilene (-11.3 kcal/mol), and imatinib (-11.2 kcal/mol), have been ranked as the top drug compounds interacting with Mpox DdRp. Complexes of these shortlisted drugs with DdRp were further evaluated using state-of-the-art all-atoms molecular dynamics (MD) simulations on 200 nanoseconds followed by principal component analysis (PCA). MD simulations and PCA results revealed highly stable interactions of these small drugs with DdRp. After due validation in wet-lab using available in vitro and in vivo experiments, these repurposed drugs can be further utilized for the treatment of contagious Mpox virus. The outcome of this study may establish a solid foundation to screen repurposed and natural compounds as potential antiviral therapeutics against different highly pathogenic viruses.

Nifuroxazide Activates the Parthanatos to Overcome TMPRSS2:ERG Fusion-Positive Prostate Cancer.

Fusion of the E-26 transformation-specific (ETS)-related gene (ERG) with transmembrane serine protease 2 (TMPRSS2) is a crucial step in the occurrence and progression of approximately 50% of prostate cancers. Despite significant progress in drug discovery, ERG inhibitors have yet to be approved for the clinical treatment of prostate cancer. In this study, we used computer-aided drug design (CADD)-based virtual screening to screen for potential inhibitors of ERG. In vivo and in vitro methods revealed that nifuroxazide (NFZ) inhibited the proliferation of a TMPRSS2:ERG fusion-positive prostate cancer cell line (VCaP) with an IC50 lower than that of ERG-negative prostate cancer cell lines (LNCaP, DU145, and WPMY cells). Poly [ADP-ribose] polymerase 1, the critical mediator of parthanatos, is known to bind ERG and is required for ERG-mediated transcription. NFZ blocked this interaction and overly activated PARP1, leading to cell death that was reduced by olaparib, a PARP1 inhibitor. These results show that NFZ inhibits ERG, leading to parthanatic cell death.

Molecular mechanisms responsible for SARS-CoV-2 antibody waning and vaccine escape in Omicron sublineages BA.4 and BA.5.

Mutations in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome continue to threaten the global landscape of the coronavirus disease 2019 (COVID-19) pandemic. The Omicron variant (B.1.1.529) rapidly displaced previous 'variants of concern' (VoC) in 2021 due to its high rate of transmissibility and multitude of mutations. This global influx of infections saturated healthcare systems, overwhelmed testing capacity and case reporting, and increased the COVID-19 death toll. Global health leaders are now being faced with the most transmissible COVID-19 variants yet, the Omicron sublineages BA.4 and BA.5, which contain additional spike protein (S) mutations from previous Omicron and VoC serotypes. With universally observed antibody waning, increasing vaccine-variant mismatch, and resuming international travel, the stage is set for unprecedented levels of breakthrough infections and superspreading events. In this paper, we raise awareness to these novel variants and provide context for the high likelihood of an upcoming wave of infection capable of inflicting significant disease burden on a global scale.

Potential of Natural Alkaloids From Jadwar (Delphinium denudatum) as Inhibitors Against Main Protease of COVID-19: A Molecular Modeling Approach.

The ongoing pandemic coronavirus disease (COVID-19) caused by a novel corona virus, namely, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has had a major impact on global public health. COVID-19 cases continue to increase across the globe with high mortality rates in immunocompromised patients. There is still a pressing demand for drug discovery and vaccine development against this highly contagious disease. To design and develop antiviral drugs against COVID-19, the main protease (Mpro) has emerged as one of the important drug targets. In this context, the present work explored Jadwar (Delphinium denudatum)-derived natural alkaloids as potential inhibitors against Mpro of SARS-CoV-2 by employing a combination of molecular docking and molecular dynamic simulation-based methods. Molecular docking and interaction profile analysis revealed strong binding on the Mpro functional domain with four natural alkaloids viz. panicutine (-7.4 kcal/mol), vilmorrianone (-7.0 kcal/mol), denudatine (-6.0 kcal/mol), and condelphine (-5.9 kcal/mol). The molecular docking results evaluated by using the MD simulations on 200 nanoseconds confirmed highly stable interactions of these compounds with the Mpro. Additionally, mechanics/generalized Born/Poisson-Boltzmann surface area (MM/G/P/BSA) free energy calculations also affirmed the docking results. Natural alkaloids explored in the present study possess the essential drug-likeness properties, namely, absorption, distribution, metabolism, and excretion (ADME), and are in accordance with Lipinski's rule of five. The results of this study suggest that these four bioactive molecules, namely, condelphine, denudatine, panicutine, and vilmorrianone, might be effective candidates against COVID-19 and can be further investigated using a number of experimental methods.

Genomic Snapshot of SARS-CoV-2 in Migrants Entering Through Mediterranean Sea Routes.

In December 2019, a novel coronavirus emerged in Wuhan, China, rapidly spreading into a global pandemic. Italy was the first European country to experience SARS-CoV-2 epidemic, and one of the most severely affected during the first wave of diffusion. In contrast to the general restriction of people movements in Europe, the number of migrants arriving at Italian borders via the Mediterranean Sea route in the summer of 2020 had increased dramatically, representing a possible, uncontrolled source for the introduction of novel SARS-CoV-2 variants. Importantly, most of the migrants came from African countries showing limited SARS-CoV-2 epidemiological surveillance. In this study, we characterized the SARS-CoV-2 genome isolated from an asymptomatic migrant arrived in Sardinia via the Mediterranean route in September 2020, in comparison with SARS-CoV-2 isolates arrived in Sicily through the Libyan migration route; with SARS-CoV-2 isolates circulating in Sardinia during 2020; and with viral genomes reported in African countries during the same summer. Results showed that our sequence is not phylogenetically related to isolates from migrants arriving in Sicily, nor to isolates circulating in Sardinia territory, having greater similarity to SARS-CoV-2 genomes reported in countries known for being sites of migrant embarkation to Italy. This is in line with the hypothesis that most SARS-CoV-2 infections among migrants have been acquired prior to embarking to Italy, possibly during the travel to or the stay in crowded Libyan immigrant camps. Overall, these observations underline the importance of dedicated SARS-CoV-2 surveillance of migrants arriving in Italy and in Europe through the Mediterranean routes.

Low anti-SARS-CoV-2 S antibody levels predict increased mortality and dissemination of viral components in the blood of critical COVID-19 patients.

BACKGROUND: Anti-SARS-CoV-2 S antibodies prevent viral replication. Critically ill COVID-19 patients show viral material in plasma, associated with a dysregulated host response. If these antibodies influence survival and viral dissemination in ICU-COVID patients is unknown. PATIENTS/METHODS: We studied the impact of anti-SARS-CoV-2 S antibodies levels on survival, viral RNA-load in plasma, and N-antigenaemia in 92 COVID-19 patients over ICU admission. RESULTS: Frequency of N-antigenaemia was >2.5-fold higher in absence of antibodies. Antibodies correlated inversely with viral RNA-load in plasma, representing a protective factor against mortality (adjusted HR [CI 95%], p): (S IgM [AUC ≥ 60]: 0.44 [0.22; 0.88], 0.020); (S IgG [AUC ≥ 237]: 0.31 [0.16; 0.61], <0.001). Viral RNA-load in plasma and N-antigenaemia predicted increased mortality: (N1-viral load [≥2.156 copies/ml]: 2.25 [1.16; 4.36], 0.016); (N-antigenaemia: 2.45 [1.27; 4.69], 0.007). CONCLUSIONS: Low anti-SARS-CoV-2 S antibody levels predict mortality in critical COVID-19. Our findings support that these antibodies contribute to prevent systemic dissemination of SARS-CoV-2.