SARS-CoV-2 B.1.214.1, B.1.214.2 and B.1.620 are predominant lineages between December 2020 and July 2021 in the Republic of Congo.

Background: : SARS-CoV-2 variants have been emerging and are shown to increase transmissibility, pathogenicity, and decreased vaccine efficacies. The objective of this study was to determine the distribution, prevalence, and dynamics of SARS-CoV-2 variants circulating in Brazzaville, the Republic of Congo (ROC). Methods: : Between December 2020 and July 2021, a total of n=600 oropharyngeal specimens collected in the community were tested for COVID-19. Of the samples tested, 317 (53%) were SARS-CoV-2 positive. All samples that had a threshold of Ct <30 (n=182) were sequenced by next-generation sequencing (NGS), and all complete sequenced genomes were submitted to GISAID; lineages were assigned using pangolin nomenclature and a phylogenetic tree was reconstructed. In addition, the global prevalence of the predominant lineages was analysed using data from GISAID and Outbreak databases. Results: : A total of 15 lineages circulated with B.1.214.2 (26%), B.1.214.1 (19%) and B.1.620 (18%) being predominant. The variants of concern (VOC) alpha (B.1.1.7) (6%) and for the first time in June delta (B.1.617.2) (4%) were observed. In addition, the B.1.214.1 lineage first reported from ROC was observed to be spreading locally and regionally. Phylogenetic analysis suggests that the B.1.620 variant (VUM) under observation may have originated from either Cameroon or the Central African Republic. SARS-CoV-2 lineages were heterogeneous, with the densely populated districts of Poto-Poto and Moungali likely the epicenter of spread. Conclusion: : Longitudinal monitoring and molecular surveillance across time and space are critical to understanding viral phylodynamics, which could have important implications for transmissibility and impact infection prevention and control measures.

Host genetic loci LZTFL1 and CCL2 associated with SARS-CoV-2 infection and severity of COVID-19.

OBJECTIVES: Host genetic factors contribute to the variable severity of COVID-19. We examined genetic variants from genome-wide association studies and candidate gene association studies in a cohort of patients with COVID-19 and investigated the role of early SARS-CoV-2 strains in COVID-19 severity. METHODS: This case-control study included 123 COVID-19 cases (hospitalized or ambulatory) and healthy controls from the state of Baden-Wuerttemberg, Germany. We genotyped 30 single nucleotide polymorphisms, using a custom-designed panel. Cases were also compared with the 1000 genomes project. Polygenic risk scores were constructed. SARS-CoV-2 genomes from 26 patients with COVID-19 were sequenced and compared between ambulatory and hospitalized cases, and phylogeny was reconstructed. RESULTS: Eight variants reached nominal significance and two were significantly associated with at least one of the phenotypes "susceptibility to infection", "hospitalization", or "severity": rs73064425 in LZTFL1 (hospitalization and severity, P <0.001) and rs1024611 near CCL2 (susceptibility, including 1000 genomes project, P = 0.001). The polygenic risk score could predict hospitalization. Most (23/26, 89%) of the SARS-CoV-2 genomes were classified as B.1 lineage. No associations of SARS-CoV-2 mutations or lineages with severity were observed. CONCLUSION: These host genetic markers provide insights into pathogenesis and enable risk classification. Variants which reached nominal significance should be included in larger studies.

SARS-CoV-2-reactive T-cell receptors isolated from convalescent COVID-19 patients confer potent T-cell effector function.

Both B cells and T cells are involved in an effective immune response to SARS-CoV-2, the disease-causing virus of COVID-19. While B cells-with the indispensable help of CD4+ T cells-are essential to generate neutralizing antibodies, T cells on their own have been recognized as another major player in effective anti-SARS-CoV-2 immunity. In this report, we provide insights into the characteristics of individual HLA-A*02:01- and HLA-A*24:02-restricted SARS-CoV-2-reactive TCRs, isolated from convalescent COVID-19 patients. We observed that SARS-CoV-2-reactive T-cell populations were clearly detectable in convalescent samples and that TCRs isolated from these T cell clones were highly functional upon ectopic re-expression. The SARS-CoV-2-reactive TCRs described in this report mediated potent TCR signaling in reporter assays with low nanomolar EC50 values. We further demonstrate that these SARS-CoV-2-reactive TCRs conferred powerful T-cell effector function to primary CD8+ T cells as evident by a robust anti-SARS-CoV-2 IFN-γ response and in vitro cytotoxicity. We also provide an example of a long-lasting anti-SARS-CoV-2 memory response by reisolation of one of the retrieved TCRs 5 months after initial sampling. Taken together, these findings contribute to a better understanding of anti-SARS-CoV-2 T-cell immunity and may contribute to paving the way toward immunotherapeutics approaches targeting SARS-CoV-2.

SARS-CoV-2 infection paralyzes cytotoxic and metabolic functions of the immune cells.

The SARS-CoV-2 virus is the causative agent of the global COVID-19 infectious disease outbreak, which can lead to acute respiratory distress syndrome (ARDS). However, it is still unclear how the virus interferes with immune cell and metabolic functions in the human body. In this study, we investigated the immune response in acute or convalescent COVID-19 patients. We characterized the peripheral blood mononuclear cells (PBMCs) using flow cytometry and found that CD8+ T cells were significantly subsided in moderate COVID-19 and convalescent patients. Furthermore, characterization of CD8+ T cells suggested that convalescent patients have significantly diminished expression of both perforin and granzyme A. Using 1H-NMR spectroscopy, we characterized the metabolic status of their autologous PBMCs. We found that fructose, lactate and taurine levels were elevated in infected (mild and moderate) patients compared with control and convalescent patients. Glucose, glutamate, formate and acetate levels were attenuated in COVID-19 (mild and moderate) patients. In summary, our report suggests that SARS-CoV-2 infection leads to disrupted CD8+ T cytotoxic functions and changes the overall metabolic functions of immune cells.

Swarm Learning for decentralized and confidential clinical machine learning.

Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine1,2. Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes3. However, there is an increasing divide between what is technically possible and what is allowed, because of privacy legislation4,5. Here, to facilitate the integration of any medical data from any data owner worldwide without violating privacy laws, we introduce Swarm Learning-a decentralized machine-learning approach that unites edge computing, blockchain-based peer-to-peer networking and coordination while maintaining confidentiality without the need for a central coordinator, thereby going beyond federated learning. To illustrate the feasibility of using Swarm Learning to develop disease classifiers using distributed data, we chose four use cases of heterogeneous diseases (COVID-19, tuberculosis, leukaemia and lung pathologies). With more than 16,400 blood transcriptomes derived from 127 clinical studies with non-uniform distributions of cases and controls and substantial study biases, as well as more than 95,000 chest X-ray images, we show that Swarm Learning classifiers outperform those developed at individual sites. In addition, Swarm Learning completely fulfils local confidentiality regulations by design. We believe that this approach will notably accelerate the introduction of precision medicine.

Genomic surveillance of SARS-CoV-2 in the Republic of Congo.

OBJECTIVE: The aim of this study was to carry out whole-genome sequencing (WGS) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), using samples collected from Congolese individuals between April and July 2020. METHODS: Ninety-six samples were screened for SARS-CoV-2 using RT-PCR, and 19 samples with Ct values <30 were sequenced using Illumina Next-Generation Sequencing (NGS). The genomes were annotated and screened for mutations using the web tool 'coronapp'. Subsequently, different SARS-CoV-2 lineages were assigned using PANGOLIN and Nextclade. RESULTS: Eleven SARS-CoV-2 genomes were successfully sequenced and submitted to the GSAID database. All genomes carried the spike mutation D614G and were classified as part of the GH clade. The Congolese SARS-CoV-2 sequences were shown to belong to lineage B1 and Nextclade 20A and 20C, which split them into distinct clusters, indicating two separate introductions of the virus into the Republic of Congo. CONCLUSION: This first study provides valuable information on SARS CoV-2 transmission in the central African region, contributing to SARS CoV-2 surveillance on a temporal and spatial scale.