The promise and challenge of spatial omics in dissecting tumour microenvironment and the role of AI

Growing evidence supports the critical role of tumour microenvironment (TME) in tumour progression, metastases, and treatment response. However, the in-situ interplay among various TME components, particularly between immune and tumour cells, are largely unknown, hindering our understanding of how tumour progresses and responds to treatment. While mainstream single-cell omics techniques allow deep, single-cell phenotyping, they lack crucial spatial information for in-situ cell-cell interaction analysis. On the other hand, tissue-based approaches such as hematoxylin and eosin and chromogenic immunohistochemistry staining can preserve the spatial information of TME components but are limited by their low-content staining. High-content spatial profiling technologies, termed spatial omics, have greatly advanced in the past decades to overcome these limitations. These technologies continue to emerge to include more molecular features (RNAs and/or proteins) and to enhance spatial resolution, opening new opportunities for discovering novel biological knowledge, biomarkers, and therapeutic targets. These advancements also spur the need for novel computational methods to mine useful TME insights from the increasing data complexity confounded by high molecular features and spatial resolution. In this review, we present state-of-the-art spatial omics technologies, their applications, major strengths, and limitations as well as the role of artificial intelligence (AI) in TME studies.

Robust Virus-Specific Adaptive Immunity in COVID-19 Patients with SARS-CoV-2 Δ382 Variant Infection

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) that have become dominant as the pandemic progresses bear the ORF8 mutation together with multiple spike mutations. A 382-nucleotide deletion (Δ382) in the ORF7b and ORF8 regions has been associated with milder disease phenotype and less systemic inflammation in COVID-19 patients. However, its impact on host immunity against SARS-CoV-2 remains undefined. Here, RNA-sequencing was performed to elucidate whole blood transcriptomic profiles and identify contrasting immune signatures between patients infected with either wildtype or Δ382 SARS-CoV-2 variant. Interestingly, the immune landscape of Δ382 SARS-CoV-2 infected patients featured an increased adaptive immune response, evidenced by enrichment of genes related to T cell functionality, a more robust SARS-CoV-2-specific T cell immunity, as well as a more rapid antibody response. At the molecular level, eukaryotic initiation factor 2 signaling was found to be upregulated in patients bearing Δ382, and its associated genes were correlated with systemic levels of T cell-associated and pro-inflammatory cytokines. This study provides more in-depth insight into the host–pathogen interactions of ORF8 with great promise as a therapeutic target to combat SARS-CoV-2 infection.

Use of nanopore sequencing to characterize african horse sickness virus (AHSV) from the African horse sickness outbreak in thailand in 2020

African horse sickness (AHS) is a highly infectious and deadly disease despite availability of vaccines. Molecular characterization of African horse sickness virus (AHSV) detected from the March 2020 Thailand outbreak was carried out by whole-genome sequencing using Nanopore with a Sequence-Independent Single Primer Amplification (SISPA) approach. Nucleotide sequence of the whole genome was compared with closest matching AHSV strains using phylogenetic analyses and the AHSV-1 virus shared high sequence identity with isolates from the same outbreak. Substitution analysis revealed non-synonymous and synonymous substitutions in the VP2 gene as compared to circulating South African strains. The use of sequencing technologies, such as Nanopore with SISPA, has enabled rapid detection, identification and detailed genetic characterization of the AHS virus for informed decision-making and implementation of disease control measures. Active genetic information sharing has also allowed emergence of AHSV to be better monitored on a global basis.