Search bioRxiv⌕ Search

Biology subjects

Currenti, J.

Publications and source records attributed to Currenti, J..

2 recordsLinked to original sources

Adaptive-like NK cell responses to influenza correlate with humoral immunity and are influenced by age and sex

Influenza remains a global health threat, infecting approximately one billion people annually and causing significant mortality, particularly among older adults. While hemagglutination inhibition (HAI) antibody titers are a standard correlate of immunity against influenza, they do not reliably predict protection in high-risk populations. Using multiomic single-cell profiling, we identified a distinct subset of adaptive-like NK cells that respond to influenza antigen, predominantly in younger females. These TNFSF10+LGALS9+ NK cells exhibit features of adaptive NK cells but lack classical cytomegalovirus-driven markers observed in previous studies. Notably, their increased frequency correlates with high pre-existing HAI titers, suggesting a link between adaptive-like NK responses and humoral immunity. Together, our findings identify an NK subset influenced by age and sex that may contribute to influenza protection, expanding the known diversity of adaptive-like NK cells. These insights could inform future vaccine strategies, particularly for aging populations, by integrating NK responses into assessments of vaccine efficacy.

immunology↗

STOmics-GenX: CRISPR based approach to improve cell identity specific gene detection from spatially resolved transcriptomics

The spatial organisation of cells defines the biological functions of tissue ecosystems from development to disease. Recently, an array of technologies have been developed to query gene expression in a spatial context. These include techniques such as employing barcoded oligonucleotides, single-molecule fluorescence in situ hybridization (smFISH), and DNA nanoball (DNB)-patterned arrays. However, resolution and efficiency vary across platforms and technologies. To obtain spatially relevant biological information from spatially resolved transcriptomics, we combined the Stereo-seq workflow with CRISPRclean technology to develop the STOmics-GenX pipeline. STOmics-GenX not only allowed us to reduce genomic, mitochondrial, and ribosomal reads, but also lead to a [~]2.1-fold increase in the number of detected genes when compared to conventional Stereo-seq (STOmics). Additionally, the STOmics-GenX pipeline resulted in an improved detection of cell type specific genes, thereby improving cellular annotations. Most importantly, STOmics-GenX allowed for enhanced detection of clinically relevant biomarkers such as Alpha-fetoprotein (AFP), enabling the identification of two spatially distinct subsets of hepatocytes in hepatocellular carcinoma tissue. Thereby, combining CRISPRclean technology with STOmics not only allowed improved gene detection but also paved the way for spatial precision oncology by improved detection of clinically relevant biomarkers.

molecular biology↗