Biology subjects

Luciani, F.

Publications and source records attributed to Luciani, F..

17 recordsLinked to original sources

bioRxiv2026

Single-cell multi-omics maps clonal IEL expansion and epithelial remodelling in refractory coeliac disease

Background Refractory coeliac disease type 1 (RCD1) lacks defining molecular markers, and the immune and epithelial mechanisms sustaining intestinal injury remain poorly understood. Objective To define the clonal immune and epithelial states that distinguish RCD1 from active coeliac disease (ACD) and determine their spatial organisation in the duodenal mucosa. Design We integrated single-cell RNA sequencing, CITE-seq surface proteomics and paired T-cell receptor sequencing of duodenal immune and epithelial compartments from Healthy controls (n = 6), ACD (n = 7), RCD1 (n = 9) and RCD2 (n = 2), with spatial transcriptomics in a subset of biopsies. Results RCD1 showed widespread TCR{beta} and TCR{gamma}{delta} clonal expansion across multiple IEL states, extending beyond previously defined mutation-bearing aberrant clones. Distinct IEL populations converged on a shared programme of adaptive persistence, innate-like signalling, metabolic fitness and cytoskeletal remodelling; GZMK expression marked both clonally expanded and non-clonal disease-associated states. In parallel, RCD1 epithelium showed loss of mature absorptive cell states and expansion of stress-associated, immune-interacting and regenerative programmes. Transit-amplifying cells acquired differentiation and tissue-remodelling signatures, while enteroendocrine cells expanded and developed a sensory-neurosecretory programme involving TRPA1, TRPV1, vesicle trafficking and NEUROD1 regulon activity. Spatial transcriptomics localised regenerative and enteroendocrine-associated epithelial programmes adjacent to immune-visible epithelial regions and KLRK1/GZMK-expressing IEL-rich niches in refractory tissue. Conclusion RCD1 represents a distinct mucosal state characterised by coordinated clonal IEL adaptation and epithelial remodelling, rather than simple amplification of ACD, providing a cellular framework for persistent tissue injury and disease stratification.

immunology↗

bioRxiv2025

Detecting Somatic Mutations in Rare Clones using Single Cell Multi-Omics

BackgroundSomatic mutations are increasingly recognised as drivers of diseases beyond cancer, including autoimmune disorders. However, identifying rare, cell type-specific causal mutations remains challenging due to their low frequency within heterogeneous cell populations. Traditional bulk sequencing approaches lack the resolution to detect rare variants, underscoring the need for novel methods specifically designed for single-cell data of heterogeneous cell populations. MethodsWe present an integrated single-cell multi-omics computational framework, SCARCE (Single-Cell Analysis of Rare Clonal Events), tailored for single-cell DNA sequencing (scDNA-seq) to statistically prioritise rare somatic mutations within defined cell subpopulations. By comparing variant frequencies across subpopulations, identified through either variant-based clustering or cell type annotation from surface marker expression, we identify variants enriched in specific cell populations. Our method applies multiple user-adjustable filters and statistical enrichment tests to distinguish true somatic variants from technical artifacts. ResultsSCARCE successfully identifies rare somatic mutations across three distinct datasets using technologies including MissionBio Tapestri and clonally-amplified whole-genome sequencing of single cells. We demonstrate that SCARCE correctly isolates and identifies true variants in a cell population comprising just 10 of 16,316 cells (0.06% of the total population). Furthermore, in an extensively characterised sample with known causal variants, SCARCE correctly identifies all known pathogenic variants among its top-ranked candidates. ConclusionsSCARCE offers several advantages over existing tools in the field. By integrating genetic and phenotypic information at single-cell resolution, our approach opens new avenues for understanding the clonal origins of diseases driven by somatic mutations in small cell populations.

bioinformatics↗

bioRxiv2025

Scaffolded hiPSC liver organoids recapitulating bile duct tubulogenesis and periportal architecture.

Recapitulating the liver periportal area in vitro remains a major challenge due to its complex cellular composition and the coordinated development of both ductal and endothelial networks. Most existing bile duct organoid models fail to reproduce tubular extension and multicellular organization. We present a 3D ECM micro-rods system biofunctionalized with grafted growth factors mimicking fetal liver paracrine signaling to initiate and to coordinate the development of bile ducts, parenchymal cells, and vascular structures. Our system recapitulates key developmental stages, from the formation of the ductal plate to the emergence of elongated tubular ducts. The ECM rod alone provides the biophysical cues initiating the elongation of the bile ducts and the spatial structuration of the cellular organization, while the biofunctionalization with growth factors enhance the organization and maturation of the biliary and vascular systems. We further demonstrate that this approach is scalable and amenable to quantitative analysis through label-free Optical Coherence Tomography combined with AI-driven 3D segmentation.

cell biology↗

bioRxiv2025

Identifying the Minimal Number of Protein Markers for Cell Type Annotation Using MiniMarS

Over the past decade, there has been an explosion in the characterisation and discovery of cell populations using single-cell technologies. Single-cell multi-omics data, particularly those incorporating gene and protein expression, are increasingly commonplace and can lead to more refined characterisation of cell types. A common challenge for biologists is to isolate cells of interest using a minimal number of markers for cytometry experiments. Although several methods exist for marker selection, there is limited guidance on the relative performance of these methods, and a wrapper package that combines multiple methods is lacking. The method that performs best can vary depending on the dataset and it can be challenging for researchers to test multiple methods for a given dataset. To address these issues, we present MiniMarS (Minimal Marker Selection), an R package that serves as a wrapper for 10 different algorithms. It allows users to determine the best-performing algorithm for identifying the optimal number of markers that will delineate cell populations in their dataset. MiniMarS uses pre-annotated cells with protein features from CyTOF or sequencing-based assays such as CITE-seq and Abseq as input. Outputs include 1) the minimum number of protein markers required to identify the annotated cell populations using a range of marker selection algorithms, and 2) a range of metrics to evaluate the performance of each algorithm. MiniMarS effectively differentiated populations across various datasets, including those from human blood, bone marrow, thymus, mouse spleen, and lymph nodes, even after subsampling over 41,000 cells to 2,500 cells. MiniMarS also identified 15 markers from CITE-seq data, which were then used to successfully identify the same 11 cell subsets in a CyTOF dataset (F1 score>0.9). Additionally, we showed that by appropriately combining clusters, MiniMarS improves the F1 score of a rare population identification (<1% of total cells) by 28.7%. Together, these findings highlight the broad applicability of MiniMarS in identifying appropriate markers for distinguishing cell populations.

bioinformatics↗

bioRxiv2025

Extracellular matrix deposition controls early differentiation patterns in human cardiac gastruloids

Amongst the various factors that affect differentiation and tissue organization, the autonomous deposition of extracellular matrix (ECM) has hardly been considered in the context of gastruloids. Using biofunctionalized colloidal particles as artificial organizing centers (aOCs), we patterned differentiation loci within 3D embryonic bodies. Our findings reveal that the spatial distribution of the aOCs induces various pattern organizations, mediated by endogenous deposition of ECM. We investigated how the interplay between meso-endoderm cell epithelial-to-mesenchymal transition, migration into germ layers, and the prolonged maintenance of local stem-cell niches orchestrates gastruloid structure and composition. These factors collectively regulate the complexity of emergent cardiac structures observed at later time points. This work uncovers a critical feedback loop between cell differentiation rates and endogenous ECM deposition patterns, which governs the differentiation paths in scaffolded cardiac gastruloids.

cell biology↗

bioRxiv2024

Temporal dynamics of viral fitness and the adaptive immune response in HCV infection

Numerous studies have shown that viral variants that elude the host immune response may incur a fitness expense, diminishing the survival of the viral strain within the host, and the capacity of the variant to survive future transmission events. However, this generic definition can be further divided into two categories where intrinsic fitness describes the viral fitness without the influence of any immune pressure and effective fitness considers both intrinsic fitness with the influence of host immune pressure. Furthermore, co-occurring mutations outside the epitope regions targeted by the immune response may increase or decrease the likelihood of survival of the variant (known as epistasis). Analysis of viral fitness and epistasis over the non-structural protein regions is lacking for hepatitis C virus (HCV). Here, using a rare cohort of subjects very recently infected with HCV, we build upon our prior investigations by integrating mathematical modelling and experimental data to examine the interplay between the evolving transmitted/founder (T/F) viruses, the adaptive immune response, viral fitness, and co-occurring mutations. We show that viral fitness decreases during the first 90 days post-infection (DPI) associated with the magnitude of CD8+ T-cell responses and the initial level of diversification. Thereafter, viral fitness rebounds in a complex pattern of evolution characterized by multiple sets of co-occurring mutations. Finally, we show that an early and strong CD8+ T-cell response in the absence of neutralizing antibodies (nAbs) imposes a strong selective force on the T/F virus population, enabling the virus to escape and establish chronic infection. Understanding these dynamics is highly relevant for HCV vaccine design and supports a vaccine strategy that induces broad immunity targeting both T and B cell responses.

immunology↗

bioRxiv2024

Self-reactive B cells traverse a perfect storm of somatic mutagenesis to cause a virus-induced autoimmune disease

The unexplained association between infection and autoimmune disease is strongest for hepatitis C virus-induced cryoglobulinemic vasculitis (HCV-CV). We traced the evolution of the pathogenic rheumatoid factor (RhF) autoantibodies in four HCV-CV patients by deep single cell multi-omic analysis, revealing three sources of B cell somatic mutation converged to drive accumulation of a large disease causing clone. A sensitive method for quantifying low affinity binding revealed three recurring heavy/light chain combinations created by V(D)J recombination bound self IgG but not viral E2 antigen. Whole genome sequencing revealed accumulation of thousands of somatic mutations, at levels comparable to CLL and normal memory B cells, but with 1-2 corresponding to driver mutations found recurrently in B cell leukemia/lymphoma. V(D)J hypermutation created autoantibodies with compromised solubility. In this virus-induced autoimmune disease, infection promotes a perfect storm of somatic mutagenesis in the descendants of a single B cell.

immunology↗

bioRxiv2022

Global and cell type-specific immunological hallmarks of severe dengue progression

Severe dengue (SD) is a major cause of morbidity and mortality impacting approximately 5 million of the 400 million people infected with dengue virus (DENV) annually. To define DENV target cells and immunological hallmarks of SD progression in childrens blood, we integrated virus-inclusive single cell RNA-Seq 2 (viscRNA-Seq 2) with functional assays. Beyond myeloid cells, in natural infection, B cells harbor replicating DENV capable of infecting permissive cells. Alterations in cell type abundance, gene and protein expression and secretion, and cell-cell communications point towards increased migration and inflammation in SD progressors (SDp). Concurrently, antigen presenting cells from SDp demonstrate intact uptake, yet impaired interferon responses and antigen presentation, in part DENV-modulated. Increased activation, regulation, and exhaustion of effector responses and expansion of HLA-DR-expressing, possibly compensatory, adaptive-like NK cells also characterize SDp. These findings reveal DENV target cells in the human blood and provide insight into SD pathogenesis beyond antibody-mediated enhancement.

immunology↗

bioRxiv2022

The E-cadherin-ESR1-GRPR axis defines a sex-specific metastatic pathway in melanoma

Although tremendous progress has been made in understanding the mechanisms leading to cancer, those governing metastases are still poorly understood. E-cadherin (Ecad) is a cell-cell adhesion molecule essential for tissue homeostasis, and its loss often correlates with the dissemination of human cancers. However, whether and how the loss of Ecad triggers the full metastatic program is largely unknown. Here, we show that the loss of Ecad promotes melanoma lung metastases in females. The loss of Ecad, after the induction of estrogen receptor (ER) expression, activates gastrin-releasing peptide receptor (GRPR) expression. GRPR promotes cellular processes essential for metastasis formation through G{square}q and YAP1 signaling and its pharmacological inhibition reduces metastasis in vivo. This study reveals an Ecad-ER-GRPR metastatic sex dimorphism axis in melanoma that is conserved in human breast cancer and provides proof of concept that the G-coupled receptor GRPR is a therapeutic target for metastasis.

cancer biology↗

bioRxiv2021

Single cell multi-omics reveals early elevated function and multiple fates within human progenitor exhausted CD8+ T cells

T-cell exhaustion is a hallmark of hepatitis C virus (HCV) infection and limits protective immunity in chronic viral infections and cancer. Limited knowledge exists of the initial viral and immune dynamics that characterise exhaustion in humans. We studied longitudinal blood samples from a unique cohort of subjects with primary infection using single cell multi-omics to identify the functions and phenotypes of HCV-specific CD8+ T cells. Early elevated IFN-{gamma} response against the transmitted virus was associated with the rate of immune escape, larger clonal expansion, and early onset of exhaustion. Irrespective of disease outcome we discovered progenitors of early-exhaustion with intermediate expression of PD-1. Intra clonal analysis revealed distinct trajectories with multiple fates suggesting evolutionary plasticity of precursor cells. These findings challenge current paradigm on the contribution of CD8+ T cells to HCV disease outcome and provide data for future studies on T-cell differentiation in human infections. One sentence summaryProgenitors of T-cell exhaustion in acute HCV infection

immunology↗

bioRxiv2021

A distinct CD115- erythro-myeloid precursor present at the maternal-embryonic interface and in the bone marrow of adult mice

During ontogeny, macrophages develop from CD115+ precursors, including erythro-myeloid progenitors (EMP). EMP arise in the embryonic yolk sac, the primary site of early haematopoiesis. In adults, CD115+ bone marrow-derived monocytes represent essential macrophage precursors. Herein, we identify a CD115- macrophage precursor within the adult bone marrow that is unrelated to the classical monocyte lineage but rather shares transcriptomic and functional characteristics of embryonic EMP. These EMPROR (for Erythro Myeloid Precursor) cells are capable of efficiently generating macrophages in disease settings. During early development, EMPROR cells were largely absent from the yolk sac but were instead found at the embryonic-maternal interface in the uterine wall. Unexpectedly, the latter site contains robust haematopoietic activity and harbours defined embryonic haematopoietic progenitor cells, including classical CD115+ EMP. Our data suggest the existence of an alternative pathway of macrophage generation in the adult. Further, we uncover a hitherto unknown site of earliest blood cell development.

immunology↗

bioRxiv2020

Analytical validity of nanopore sequencing for rapid SARS-CoV-2 genome analysis

Viral whole-genome sequencing (WGS) provides critical insight into the transmission and evolution of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Long-read sequencing devices from Oxford Nanopore Technologies (ONT) promise significant improvements in turnaround time, portability and cost, compared to established short-read sequencing platforms for viral WGS (e.g., Illumina). However, adoption of ONT sequencing for SARS-CoV-2 surveillance has been limited due to common concerns around sequencing accuracy. To address this, we performed viral WGS with ONT and Illumina platforms on 157 matched SARS-CoV-2-positive patient specimens and synthetic RNA controls, enabling rigorous evaluation of analytical performance. Despite the elevated error rates observed in ONT sequencing reads, highly accurate consensus-level sequence determination was achieved, with single nucleotide variants (SNVs) detected at >99% sensitivity and >99% precision above a minimum ~60-fold coverage depth, thereby ensuring suitability for SARS-CoV-2 genome analysis. ONT sequencing also identified a surprising diversity of structural variation within SARS-CoV-2 specimens that were supported by evidence from short-read sequencing on matched samples. However, ONT sequencing failed to accurately detect short indels and variants at low read-count frequencies. This systematic evaluation of analytical performance for SARS-CoV-2 WGS will facilitate widespread adoption of ONT sequencing within local, national and international COVID-19 public health initiatives.

genomics↗

bioRxiv2020

Atypical B cells are a normal component of immune responses to vaccination and infection in humans

The full diversity of the circulating human B cell compartment is unknown. Flow cytometry analysis suggests that in addition to naive and memory B cells, there exists a population of CD11c+, CD27- CD21- "atypical" B cells, that are associated with chronic or recurrent infection and autoimmunity. We used single cell RNA-seq approaches to examine the diversity of both antigen-specific B cells and total B cells in healthy subjects and individuals naturally-exposed to recurrent malaria infections. This analysis revealed two B cell lineages: a classical lineage of activated and resting memory B cells, and an atypical-like lineage. Surprisingly, the atypical lineage was common in both malaria exposed individuals and non-exposed healthy controls. Using barcoded antibodies in conjunction with our transcriptomic data, we found that atypical lineage cells in healthy individuals lack many atypical B markers and thus represent an undercounted cryptic population. We further determined using antigen specific probes that atypical cells can be induced by primary vaccination in humans and can be recalled upon boosting. Collectively these data suggest that atypical cells are not necessarily pathogenic but can be a normal component of B responses to antigen.

immunology↗

bioRxiv2019

Single cell multi-modal analysis with VDJPuzzle identifies clonality and gene expression profiles of T and B cells

BackgroundSingle cell RNA sequencing provides unprecedented opportunity to simultaneously explore the transcriptomic and immune receptor diversity of T and B cells. However, there are limited tools available that simultaneously analyse large multi-omics datasets integrated with metadata such as patient and clinical information.\n\nResultsWe developed VDJView, which permits the simultaneous or independent analysis and visualisation of gene expression, immune receptors, and clinical metadata of both T and B cells. This tool is implemented as an easy-to-use R shiny web-application, which integrates numerous gene expression and TCR analysis tools, and accepts data from plate-based sorted or high-throughput single cell platforms. We utilised VDJView to analyse several 10X scRNA-seq datasets, including a recent dataset of 150,000 CD8+ T cells with available gene expression, TCR sequences, quantification of 15 surface proteins, and 44 antigen specificities (across viruses, cancer, and self-antigens). We performed quality control, filtering of tetramer non-specific cells, clustering, random sampling and hypothesis testing to discover antigen specific gene signatures which were associated with immune cell differentiation states and clonal expansion across the pathogen specific T cells. We also analysed 563 single cells (plate-based sorted) obtained from 11 subjects, revealing clonally expanded T and B cells across primary cancer tissues and metastatic lymph-node. These immune cells clustered with distinct gene signatures according to the breast cancer molecular subtype. VDJView has been tested in lab meetings and peer-to-peer discussions, showing effective data generation and discussion without the need to consult bioinformaticians.\n\nConclusionsVDJView enables researchers without profound bioinformatics skills to analyse immune scRNA-seq data, integrating and visualising this with clonality and metadata profiles, thus accelerating the process of hypothesis testing, data interpretation and discovery of cellular heterogeneity. VDJView is freely available at https://bitbucket.org/kirbyvisp/vdjview.

bioinformatics↗

bioRxiv2018

High-throughput targeted long-read single cell sequencing reveals the clonal and transcriptional landscape of lymphocytes

High-throughput single-cell RNA-Sequencing is a powerful technique for gene expression profiling of complex and heterogeneous cellular populations such as the immune system. However, these methods only provide short-read sequence from one end of a cDNA template, making them poorly suited to the investigation of gene-regulatory events such as mRNA splicing, adaptive immune responses or somatic genome evolution. To address this challenge, we have developed a method that combines targeted long-read sequencing with short-read based transcriptome profiling of barcoded single cell libraries generated by droplet-based partitioning. We use Repertoire And Gene Expression sequencing (RAGE-seq) to accurately characterize full-length T cell (TCR) and B cell (BCR) receptor sequences and transcriptional profiles of more than 7,138 lymphocytes sampled from the primary tumour and draining lymph node of a breast cancer patient. With this method we show that somatic mutation, alternate splicing and clonal evolution of T and B lymphocytes can be tracked across these tissue compartments. Our results demonstrate that RAGE-Seq is an accessible and cost-effective method for high-throughput deep single cell profiling, applicable to a wide range of biological challenges.

genomics↗

bioRxiv2017

B-cell receptor reconstruction from single-cell RNA-seq with VDJPuzzle

The B-cell receptor (BCR) performs essential functions for the adaptive immune system including recognition of pathogen-derived antigens. Cell-to-cell variability of BCR sequences due to V(D)J recombination and somatic hypermutation (SHM) necessitates single-cell characterization of BCR sequences. Single-cell RNA sequencing (scRNA-seq) presents the opportunity for simultaneous capture of the BCR sequence and transcriptomic signature for a detailed understanding of the dynamics of an immune response.\n\nWe developed VDJPuzzle 2.0, a bioinformatic tool that reconstructs productive, full-length B-cell receptor sequences of both heavy and light chains. VDJPuzzle successfully reconstructs BCRs from 98.3% (n=117) of human and 96.5% (n=200) from murine B cells. 92.0% of clonotypes and 90.3% of mutations were concordant with single-cell Sanger sequencing of the immunoglobulin chains. VDJPuzzle is available at https://bitbucket.org/kirbyvisp/vdjpuzzle2

bioinformatics↗

bioRxiv2017

Impact Of Sequencing Depth And Read Length On Single Cell RNA Sequencing Data: Lessons From T Cells

Single cell RNA sequencing (scRNA-seq) has shown great potential in measuring the gene expression profiles of heterogeneous cell populations. In immunology, scRNA-seq allowed the characterisation of transcript sequence diversity of functionally relevant sub-populations of T cells, and notably the identification of the full length T cell receptor (TCR{beta}), which defines the specificity against cognate antigens. Several factors, such as RNA library capture, cell quality, and sequencing output have been suggested to affect the quality of scRNA-seq data, but these factors have not been systematically examined.\n\nWe studied the effect of read length and sequencing depth on the quality of gene expression profiles, cell type identification, and TCR{beta} reconstruction, utilising 1,305 publically available scRNA-seq datasets, and simulation-based analyses. Gene expression was characterised by an increased number of unique genes identified with short read lengths (<50 bp), but these featured higher technical variability compared to profiles from longer reads. TCR{beta} were detected in 1,027 cells (79%), with a success rate between 81% and 100% for datasets with at least 250,000 (PE) reads of length >50 bp.\n\nSufficient read length and sequencing depth can control technical noise to enable accurate identification of TCR{beta} and gene expression profiles from scRNA-seq data of T cells.

bioinformatics↗