The mRNA Vaccine Technology Era and the Future Control of Parasitic Infections.

Despite intensive long-term efforts, with very few exceptions, the development of effective vaccines against parasitic infections has presented considerable challenges, given the complexity of parasite life cycles, the interplay between parasites and their hosts, and their capacity to escape the host immune system and to regulate host immune responses. For many parasitic diseases, conventional vaccine platforms have generally proven ill suited, considering the complex manufacturing processes involved and the costs they incur, the inability to posttranslationally modify cloned target antigens, and the absence of long-lasting protective immunity induced by these antigens. An effective antiparasite vaccine platform is required to assess the effectiveness of novel vaccine candidates at high throughput. By exploiting the approach that has recently been used successfully to produce highly protective COVID mRNA vaccines, we anticipate a new wave of research to advance the use of mRNA vaccines to prevent parasitic infections in the near future. This article considers the characteristics that are required to develop a potent antiparasite vaccine and provides a conceptual foundation to promote the development of parasite mRNA-based vaccines. We review the recent advances and challenges encountered in developing antiparasite vaccines and evaluate the potential of developing mRNA vaccines against parasites, including those causing diseases such as malaria and schistosomiasis, against which vaccines are currently suboptimal or not yet available.

Potential of the CRISPR-Cas system for improved parasite diagnosis: CRISPR-Cas mediated diagnosis in parasitic infections: CRISPR-Cas mediated diagnosis in parasitic infections.

CRISPR-Cas technology accelerates development of fast, accurate, and portable diagnostic tools, typified by recent applications in COVID-19 diagnosis. Parasitic helminths cause devastating diseases afflicting 1.5 billion people globally, representing a significant public health and economic burden, especially in developing countries. Currently available diagnostic tests for worm infection are neither sufficiently sensitive nor field-friendly for use in low-endemic or resource-poor settings, leading to underestimation of true prevalence rates. Mass drug administration programs are unsustainable long-term, and diagnostic tools - required to be rapid, specific, sensitive, cost-effective, and user-friendly without specialized equipment and expertise - are urgently needed for rapid mapping of helminthic diseases and monitoring control programs. We describe the key features of the CRISPR-Cas12/13 system and emphasise its potential for the development of effective tools for the diagnosis of parasitic and other neglected tropical diseases (NTDs), a key recommendation of the NTDs 2021-2030 roadmap released by the World Health Organization.

WEDGE: imputation of gene expression values from single-cell RNA-seq datasets using biased matrix decomposition.

The low capture rate of expressed RNAs from single-cell sequencing technology is one of the major obstacles to downstream functional genomics analyses. Recently, a number of imputation methods have emerged for single-cell transcriptome data, however, recovering missing values in very sparse expression matrices remains a substantial challenge. Here, we propose a new algorithm, WEDGE (WEighted Decomposition of Gene Expression), to impute gene expression matrices by using a biased low-rank matrix decomposition method. WEDGE successfully recovered expression matrices, reproduced the cell-wise and gene-wise correlations and improved the clustering of cells, performing impressively for applications with sparse datasets. Overall, this study shows a potent approach for imputing sparse expression matrix data, and our WEDGE algorithm should help many researchers to more profitably explore the biological meanings embedded in their single-cell RNA sequencing datasets. The source code of WEDGE has been released at https://github.com/QuKunLab/WEDGE.

Single-cell analysis of COVID-19, sepsis, and HIV infection reveals hyperinflammatory and immunosuppressive signatures in monocytes.

The mortality risk of coronavirus disease 2019 (COVID-19) patients has been linked to the cytokine storm caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Understanding the inflammatory responses shared between COVID-19 and other infectious diseases that feature cytokine storms may therefore help in developing improved therapeutic strategies. Here, we use integrative analysis of single-cell transcriptomes to characterize the inflammatory signatures of peripheral blood mononuclear cells from patients with COVID-19, sepsis, and HIV infection. We identify ten hyperinflammatory cell subtypes in which monocytes are the main contributors to the transcriptional differences in these infections. Monocytes from COVID-19 patients share hyperinflammatory signatures with HIV infection and immunosuppressive signatures with sepsis. Finally, we construct a "three-stage" model of heterogeneity among COVID-19 patients, related to the hyperinflammatory and immunosuppressive signatures in monocytes. Our study thus reveals cellular and molecular insights about inflammatory responses to SARS-CoV-2 infection and provides therapeutic guidance to improve treatments for subsets of COVID-19 patients.

COVID-19 immune features revealed by a large-scale single-cell transcriptome atlas.

A dysfunctional immune response in coronavirus disease 2019 (COVID-19) patients is a recurrent theme impacting symptoms and mortality, yet a detailed understanding of pertinent immune cells is not complete. We applied single-cell RNA sequencing to 284 samples from 196 COVID-19 patients and controls and created a comprehensive immune landscape with 1.46 million cells. The large dataset enabled us to identify that different peripheral immune subtype changes are associated with distinct clinical features, including age, sex, severity, and disease stages of COVID-19. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA was found in diverse epithelial and immune cell types, accompanied by dramatic transcriptomic changes within virus-positive cells. Systemic upregulation of S100A8/A9, mainly by megakaryocytes and monocytes in the peripheral blood, may contribute to the cytokine storms frequently observed in severe patients. Our data provide a rich resource for understanding the pathogenesis of and developing effective therapeutic strategies for COVID-19.

Single-cell analysis of two severe COVID-19 patients reveals a monocyte-associated and tocilizumab-responding cytokine storm.

Several studies show that the immunosuppressive drugs targeting the interleukin-6 (IL-6) receptor, including tocilizumab, ameliorate lethal inflammatory responses in COVID-19 patients infected with SARS-CoV-2. Here, by employing single-cell analysis of the immune cell composition of two severe-stage COVID-19 patients prior to and following tocilizumab-induced remission, we identify a monocyte subpopulation that contributes to the inflammatory cytokine storms. Furthermore, although tocilizumab treatment attenuates the inflammation, immune cells, including plasma B cells and CD8+ T cells, still exhibit robust humoral and cellular antiviral immune responses. Thus, in addition to providing a high-dimensional dataset on the immune cell distribution at multiple stages of the COVID-19, our work also provides insights into the therapeutic effects of tocilizumab, and identifies potential target cell populations for treating COVID-19-related cytokine storms.