ISCOMATRIX vaccines mediate CD8+ T-cell cross-priming by a MyD88-dependent signaling pathway

Generating a cytotoxic CD8+ T-cell response that can eradicate malignant cells is the primary objective of cancer vaccine strategies. In this study we have characterized the innate and adaptive immune response to the ISCOMATRIX adjuvant, and the ability of vaccine antigens formulated with this adjuvant to promote antitumor immunity. ISCOMATRIX adjuvant led to a rapid innate immune cell response at the injection site, followed by the activation of natural killer and dendritic cells (DC) in regional draining lymph nodes. Strikingly, major histocompatibility complex (MHC) class I cross-presentation by CD8α+ and CD8α− DCs was enhanced by up to 100-fold when antigen was formulated with ISCOMATRIX adjuvant. These coordinated features enabled efficient CD8+ T-cell cross-priming, which exhibited prophylactic and therapeutic tumoricidal activity. The therapeutic efficacy of an ISCOMATRIX vaccine was further improved when co-administered with an anti-CD40 agonist antibody, suggesting that ISCOMATRIX-based vaccines may combine favorably with other immune modifiers in clinical development to treat cancer. Finally, we identified a requirement for the myeloid differentiation primary response gene 88 (MyD88) adapter protein for both innate and adaptive immune responses to ISCOMATRIX vaccines in vivo. Taken together, our findings support the utility of the ISCOMATRIX adjuvant for use in the development of novel vaccines, particularly those requiring strong CD8+ T-cell immune responses, such as therapeutic cancer vaccines

Wastewater genomic surveillance tracks the spread of the SARS-CoV-2 Omicron variant across England

Background Many countries have moved into a new stage of managing the SARS-CoV-2 pandemic with minimal restrictions and reduced testing in the population, leading to reduced genomic surveillance of virus variants in individuals. Wastewater-based epidemiology (WBE) can provide an alternative means of tracking virus variants in the population but is lacking verifications of its comparability to individual testing data. Methods We analysed more than 19,000 samples from 524 wastewater sites across England at least twice a week between November 2021 and February 2022, capturing sewage from &gt;70% of the English population. We used amplicon-based sequencing and the phylogeny based de-mixing tool Freyja to estimate SARS-CoV-2 variant frequencies and compared these to the variant dynamics observed in individual testing data from clinical and community settings. Findings We show that wastewater data can reconstruct the spread of the Omicron variant across England since November 2021 in close detail and aligns closely with epidemiological estimates from individual testing data. We also show the temporal and spatial spread of Omicron within London. Our wastewater data further reliably track the transition between Omicron subvariants BA1 and BA2 in February 2022 at regional and national levels. Interpretation Our demonstration that WBE can track the fast-paced dynamics of SARS-CoV-2 variant frequencies at a national scale and closely match individual testing data in time shows that WBE can reliably fill the monitoring gap left by reduced individual testing in a more affordable way.</jats:p

Evaluation of variant calling algorithms for wastewater-based epidemiology using mixed populations of SARS-CoV-2 variants in synthetic and wastewater samples

AbstractWastewater-based epidemiology (WBE) has been used extensively throughout the COVID-19 pandemic to detect and monitor the spread and prevalence of SARS-CoV-2 and its variants. It has proven an excellent, complementary tool to clinical sequencing, supporting the insights gained and helping to make informed public health decisions. Consequently, many groups globally have developed bioinformatics pipelines to analyse sequencing data from wastewater. Accurate calling of mutations is critical in this process and in the assignment of circulating variants, yet, to date, the performance of variant-calling algorithms in wastewater samples has not been investigated. To address this, we compared the performance of six variant callers (VarScan, iVar, GATK, FreeBayes, LoFreq and BCFtools), used widely in bioinformatics pipelines, on 19 synthetic samples with known ratios of three different SARS-CoV-2 variants (Alpha, Beta and Delta), as well as 13 wastewater samples collected in London between the 15–18 December 2021. We used the fundamental parameters of recall (sensitivity) and precision (specificity) to confirm the presence of mutational profiles defining specific variants across the six variant callers.Our results show that BCFtools, FreeBayes and VarScan found the expected variants with higher precision and recall than GATK or iVar, although the latter identified more expected defining mutations than other callers. LoFreq gave the least reliable results due to the high number of false-positive mutations detected, resulting in lower precision. Similar results were obtained for both the synthetic and wastewater samples.</jats:p