Biology subjects

Tippalagama, R.

Publications and source records attributed to Tippalagama, R..

5 recordsLinked to original sources

bioRxiv2025

Enrichment of a CD4-CD8- NK-like cytotoxic Vδ1/3 T cell subset in tuberculosis disease

Tuberculosis (TB), caused by Mycobacterium tuberculosis, remains a leading cause of global morbidity and mortality. Although gamma-delta ({gamma}{delta}) T cells have increasingly been suggested to contribute to the TB immune response, quantitative and qualitative differences in this immune cell compartment between healthy and TB diseased individuals are not well-characterized. In this study, we used single-cell RNA sequencing to provide a high-resolution characterization of CD4-CD8- {gamma}{delta} T cells in peripheral blood across healthy Mtb-non-sensitized, healthy Mtb-sensitized, and TB disease pre-/post-treatment cohorts. We found upregulation of an activated and cytotoxic gene signature in {gamma}{delta} T cells of TB disease compared to both healthy cohorts. Strikingly, these differences persisted through one year following diagnosis of TB disease (corresponding to six months after completion of anti-TB therapy). We found that these transcriptomic differences were largely mediated by an NK-like cytotoxic V{delta}1 and V{delta}3 subset that was enriched in TB disease, with a unique V{delta}3 TCR gene usage. Our findings suggest long-lasting changes in the CD4-CD8- {gamma}{delta} T cell compartment and highlight V{delta}3 cells, a previously underappreciated {gamma}{delta} T cell subset, as potentially important in TB.

immunology↗

bioRxiv2025

Peptide Driven Identification of TCRs (PDI-TCR) reveals dynamics and phenotypes of CD4 T cells in tuberculosis

Assigning antigen specificity to T cell receptor (TCR) sequences is challenging due to the TCR repertoires diversity and the complexity of TCR:antigen recognition. We developed the Peptide-Driven Identification of TCRs (PDI-TCR) assay that combines in vitro expansion of cells with peptide pools, bulk TCR sequencing, and statistical analysis to identify antigen-specific TCRs from human blood. A key feature of PDI-TCR is the ability to distinguish true antigen-specific TCR clonotypes from TCRs associated with unspecific bystander activation by comparing responses to non-overlapping peptide pools. We applied PDI-TCR to Tuberculosis (TB) patients, sampling blood at diagnosis and throughout treatment, and Mycobacterium tuberculosis (Mtb)-sensitized healthy individuals (IGRA+). We identified hundreds of Mtb-specific TCRs, as well as unspecific TCRs, and characterized their phenotype in each cohort by single-cell RNA sequencing ex vivo. Mtb-specific T cells were highly diverse, with short-lived effector phenotypes only present in TB at diagnosis, while memory phenotypes were maintained through treatment. In contrast, unspecific expanded T cells were more clonally restricted, had a cytotoxic phenotype, and were maintained throughout treatment. This showcases PDI-TCR as a powerful tool for identifying antigen-specific TCRs, which enables direct ex vivo identification and monitoring of antigen-specific T cells.

immunology↗

bioRxiv2024

A novel method for characterizing cell-cell interactions at single-cell resolution reveals unique signatures in blood T cell-monocyte complexes during infection

Communication between immune cells through direct contact is a critical feature of immune responses. Here, we developed a novel high-throughput method to study the transcriptome and adaptive immune receptor repertoire of single cells forming complexes without needing bioinformatic deconvolution. We found that T cells and monocytes forming complexes in blood during active tuberculosis (TB) and dengue hold unique transcriptomic signatures indicative of TCR/MCH-II immune synapses. Additionally, T cells in complexes showed enrichment for effector phenotypes, imaging and transcriptomic features of active TCR signaling, and increased immune activity at diagnosis compared to after anti-TB therapy. We also found evidence for bidirectional RNA exchange between T cells and monocytes, since complexes were markedly enriched for "dual-expressing" cells (i.e., co-expressing T cell and monocyte genes). Thus, studying immune cell complexes at a single-cell resolution offers novel perspectives on immune synaptic interactions occurring in blood during infection. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=59 SRC="FIGDIR/small/612103v1_ufig1.gif" ALT="Figure 1"> View larger version (17K): org.highwire.dtl.DTLVardef@f90023org.highwire.dtl.DTLVardef@178007corg.highwire.dtl.DTLVardef@167e53corg.highwire.dtl.DTLVardef@1faff48_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2018

No cell is an island: circulating T cell:monocyte complexes are markers of immune perturbations

Our results highlight for the first time that a significant proportion of cell doublets in flow cytometry, previously believed to be the result of technical artefacts and thus ignored in data acquisition and analysis, are the result of true biological interaction between immune cells. In particular, we show that cell:cell doublets pairing a T cell and a monocyte can be directly isolated from human blood, and high resolution microscopy shows polarized distribution of LFA1/ICAM1 in many doublets, suggesting in vivo formation. Intriguingly, T cell:monocyte complex frequency and phenotype fluctuate with the onset of immune perturbations such as infection or immunization, reflecting expected polarization of immune responses. Overall these data suggest that cell doublets reflecting T cell-monocyte in vivo immune interactions can be detected in human blood and that the common approach in flow cytometry to avoid studying cell:cell complexes should be revisited.

immunology↗

bioRxiv2018

Emergence of a Dengue virus serotype 2 causing the largest ever dengue epidemic in Sri Lanka

BackgroundSri Lanka experienced the largest ever dengue outbreak in year 2017, which coincided with the shift of the predominant circulating dengue virus (DENV) 1 to DENV2 after 9 years. As it was felt that more patients appeared to develop complications and severe dengue, we compared clinical features of patients with acute dengue, with the previous circulating serotype (DENV1) and also sequenced the new virus, to determine the lineage of the virus.\n\nMethodology/Principal findingsWe studied the clinical and laboratory features of 172 adult patients with acute DENV1 (n=79) and DENV2 (n=93) infection. 65 (82.3%) of those with DENV1 and 86 (92.4%) of those with DENV2 were experiencing a secondary infection. The risk of developing dengue haemorrhagic fever (DHF) was significantly higher (=0.005, odds ratio=2.5) in those infected with DENV2 (54.8%) when compared to DENV1(32.9%), even though similar proportions of patients had a secondary dengue infection. Patients with DENV2 infection developed leakage significantly earlier (p<0.0001, median= 3, days) when compared to those with a DENV1 infection (median 5 days) and were more likely to develop significant bleeding and to require blood transfusions. Furthermore, patients with DENV2 were more likely to have significantly lower platelet counts during day 3, 4 and 5 since onset of illness.\n\nWhole genome sequencing showed that these DENV-2 isolates belonged to a cosmopolitan strain and was genetically more distant than the DENV-2 strains that circulated from 1981 to 2004 in Sri Lanka.\n\nConclusions/significanceSince this DENV2 strain appears to cause more severe forms of clinical disease, it would be important to determine variations in the virus genome or other factors that could have contributed to severe disease.\n\nAuthor summarySri Lanka experienced the largest ever dengue outbreak in year 2017, which coincided with the shift of the predominant circulating dengue virus (DENV) 1 to DENV2 after 9 years. We studied the clinical and laboratory features of 172 adult patients with acute DENV1 (n=79) and DENV2 (n=93) infection. The risk of developing dengue haemorrhagic fever was significantly higher (=0.005, odds ratio=2.5) in those infected with DENV2 (54.8%) when compared to DENV1(32.9%), even though similar proportions of patients had a secondary dengue infection. Patients with DENV2 infection developed leakage significantly earlier (p<0.0001, median= 3, days) when compared to those with a DENV1 infection (median 5 days) and were more likely to develop significant bleeding. Whole genome sequencing showed that these DENV-2 isolates belonged to cosmopolitan strain and was genetically more distant to the DENV-2 strains that circulated from 1981 to 2004 in Sri Lanka.

epidemiology↗