Biology subjects

Richard, A. C.

Publications and source records attributed to Richard, A. C..

5 recordsLinked to original sources

bioRxiv2026

T cell receptor-ligand affinity quantitatively tunes transcriptome remodelling in vivo, inversely regulating cell division and interferon response

The strength of T cell receptor (TCR) engagement by antigenic ligands governs naive T cell activation, expansion and differentiation. However, the molecular changes underpinning this process in vivo remain incompletely understood. To address this, we coupled an influenza infection model of varied TCR-ligand affinity with high-dimensional protein and RNA measurements. As previously reported, high affinity stimulation drove greater expansion, with disproportionately abundant effector subsets. Experiments using a KLRG1-fate reporter showed that differentiation state biases affected cells from both direct and indirect memory differentiation trajectories. Early post-infection, these biases manifested in differential metabolic and proliferative activities. Examination of T cells showing signs of initial priming in vivo revealed that TCR-ligand affinity primarily changed the magnitude of TCR-induced transcriptome remodelling, not the genes involved. This quantitative tuning drove affinity-dependent amplification of ribosome biogenesis and suppression of interferon response genes before mitogenic diversion, and was associated with elevated TCR-induced transcription factor activity. Together, these data demonstrate the in vivo underpinnings of affinity-dependent responses and reveal how accumulation of TCR-induced signalling outputs translates binding properties into appropriate differentiation outcomes.

immunology↗

bioRxiv2024

Pathogenesis and immune response to respiratory coronaviruses in their natural porcine host

Porcine respiratory coronavirus (PRCV) is a naturally occurring pneumotropic coronavirus in the pig, providing a valuable large animal model to study acute respiratory disease. PRCV pathogenesis and the resulting immune response was investigated in pigs, the natural large animal host. We compared two strains, ISU-1 and 135, which induced differing levels of pathology in the respiratory tract to elucidate the mechanisms leading to mild or severe disease. The 135 strain induced greater pathology which was associated with higher viral load and stronger spike-specific antibody and T cell responses. In contrast, the ISU-1 strain triggered mild pathology with a more balanced immune response and greater abundance of T regulatory cells. A higher frequency of putative T follicular helper cells was observed in animals infected with strain 135 at 11 days post-infection. Single-cell RNA-sequencing of bronchoalveolar lavage revealed differential gene expression in B and T cells between animals infected with 135 and ISU-1 at 1 day post infection. These genes were associated with cell adhesion, migration, and immune regulation. Along with increased IL-6 and IL-12 production, these data suggest that heightened inflammatory responses to the 135 strain may contribute to pronounced pneumonia. Among BAL immune cell populations, B cells and plasma cells exhibited the most gene expression divergence between pigs infected with different PRCV strains, highlighting their potential role in maintaining immune homeostasis in the respiratory tract. These findings indicate the potential of the PRCV model for studying coronavirus induced respiratory disease and identifying mechanisms that determine infection outcomes. Author summaryUnderstanding how our immune system reacts to respiratory viruses, like SARS-CoV-2, is crucial to developing better treatments. While most COVID-19 infections are mild, some cases lead to severe lung damage, but we do not fully understand why. To study this, we used pigs, which respond more like humans compared to small animals, to explore how the immune system deals with respiratory coronaviruses. We tested two porcine respiratory coronavirus strains that caused different levels of lung damage. The more severe strain triggered a strong immune response and high inflammation, leading to lung pathology similar to that seen in severe COVID-19 cases. By contrast, the milder strain caused a balanced immune response, including more regulatory T cells that help control inflammation. We also found changes in genes related to antibody-producing cells, which may be important for controlling respiratory pathology. Interestingly, changes in immune responses and gene expression lasted long after the virus was cleared, potentially making individuals more vulnerable to future infections - similar to the "long COVID" symptoms seen in people. We propose that this pig model could help us study coronavirus-induced lung damage and test new therapies to prevent severe disease.

immunology↗

bioRxiv2023

Single-cell analysis reveals lasting immunological consequences of influenza infection and respiratory immunisation in the pig lung

The pig is a natural host for influenza viruses and integrally involved in virus evolution through interspecies transmissions between humans and swine. Swine have many physiological, anatomical, and immunological similarities to humans, and are an excellent model for human influenza. Here, we employed single RNA-sequencing (scRNA-seq) and flow cytometry to characterize the major leucocyte subsets in bronchoalveolar lavage (BAL), twenty-one days after H1N1pdm09 infection or respiratory immunization with an adenoviral vector vaccine expressing haemagglutinin and nucleoprotein with or without IL-1{beta}. Mapping scRNA-seq clusters from BAL onto those previously described in peripheral blood facilitated annotation and highlighted differences between tissue resident and circulating immune cells. ScRNA-seq data and functional assays revealed lasting impacts of immune challenge on BAL populations. First, mucosal administration of IL-1{beta} reduced the number of functionally active Treg. Second, influenza infection upregulated IFI6 in BAL cells, decreasing their susceptibility to virus replication in vitro. Our data provides a reference map of porcine BAL cells and reveals lasting immunological consequences of influenza infection and respiratory immunisation in a highly relevant large animal model for respiratory virus infection. Author SummaryPigs and humans have a similar anatomy and physiology. In humans, cells from lung-washes are used to study immune responses and it was shown that these cells are crucial in protection against respiratory diseases such as influenza and COVID-19. To better understand lung immunity, we compared genes expressed in cells of pig lung-wash to white blood cells, providing an atlas for future studies of immunity in the lung. We also tested a vaccine given to the lung containing IL-1{beta}, a strong immune activator that protects mice against influenza virus infection. However, although IL-1{beta} increased pig immune responses it did not protect pigs against infection. We also showed that the number of immune cells that dampen immune responses (regulatory T cells) is reduced. In addition, we demonstrated increased expression of a protein, IFI6, 21 days after infection showing that while immune cells in the lung have common properties, the invading organisms influence them significantly. Our study elucidates why some vaccines fail despite inducing powerful immune responses, emphasizes the need for caution when applying results from small animals like mice to humans, and indicates the importance of the pig as a model to study disease in humans and livestock.

immunology↗

bioRxiv2017

Robust expression variability testing reveals heterogeneous T cell responses

Cell-to-cell transcriptional variability in otherwise homogeneous cell populations plays a crucial role in tissue function and development. Single-cell RNA sequencing can characterise this variability in a transcriptome-wide manner. However, technical variation and the confounding between variability and mean expression estimates hinders meaningful comparison of expression variability between cell populations. To address this problem, we introduce a novel analysis approach that extends the BASiCS statistical framework to derive a residual measure of variability that is not confounded by mean expression. Moreover, we introduce a new and robust procedure for quantifying technical noise in experiments where technical spike-in molecules are not available. We illustrate how our method provides biological insight into the dynamics of cell-to-cell expression variability, highlighting a synchronisation of the translational machinery in immune cells upon activation. Additionally, our approach identifies new patterns of variability across CD4+ T cell differentiation.

bioinformatics↗

bioRxiv2017

Detection and removal of barcode swapping in single-cell RNA-seq data

Barcode swapping results in the mislabeling of sequencing reads between multiplexed samples on the new patterned flow cell Illumina sequencing machines. This may compromise the validity of numerous genomic assays, especially for single-cell studies where many samples are routinely multiplexed together. The severity and consequences of barcode swapping for single-cell transcriptomic studies remain poorly understood. We have used two statistical approaches to robustly quantify the fraction of swapped reads in each of two plate-based single-cell RNA sequencing datasets. We found that approximately 2.5% of reads were mislabeled between samples on the HiSeq 4000 machine, which is lower than previous reports. We observed no correlation between the swapped fraction of reads and the concentration of free barcode across plates. Furthermore, we have demonstrated that barcode swapping may generate complex but artefactual cell libraries in droplet-based single-cell RNA sequencing studies. To eliminate these artefacts, we have developed an algorithm to exclude individual molecules that have swapped between samples in 10X Genomics experiments, exploiting the combinatorial complexity present in the data. This permits the continued use of cutting-edge sequencing machines for droplet-based experiments while avoiding the confounding effects of barcode swapping.

genomics↗