Biology subjects

Amann-Zalcenstein, D.

Publications and source records attributed to Amann-Zalcenstein, D..

13 recordsLinked to original sources

bioRxiv2026

SpatialBench: Comparative cross-platform benchmarking of high-resolution spatial transcriptomics using matched mouse lymphoid tissue

Spatial transcriptomics (ST) has rapidly expanded with the introduction of multiple high-resolution platforms, yet cross-platform benchmarking remains limited and largely focused on technical performance. Here we present SpatialBench, a matched multi-platform resource comprising Visium HD, Xenium and MERSCOPE data together with single-cell and single-nucleus references from a malaria-challenged wild-type and B cell-specific Tbx21 knockout mouse spleen model. In this system, loss of T-bet in B cells disrupts germinal center (GC) polarization and antibody maturation, providing a biologically grounded benchmark for technology comparison. We leveraged this system to systematically evaluate ST platform performance using technical and biological readouts. Across platforms, immune organization and Tbx21-associated programs were consistently recovered, indicating robustness of major biological signals. Platforms instead differed in the level of biological resolution accessible. Visium HD enabled transcriptome-scale GC characterization and, together with Xenium, resolved dark and light zone organization, whereas GC zonation was not resolved in MERSCOPE, consistent with differences in transcript detection sensitivity. SpatialBench provides a biologically defined reference dataset for evaluation of ST technologies, method development, computational benchmarking, and studies of GC spatial organization in lymphoid tissue.

bioinformatics↗

bioRxiv2025

Host iron deficiency protects against Plasmodium infection and drives parasite molecular reprofiling.

Iron deficiency, anemia and Plasmodium infection represent significant global health challenges with overlapping geographical distributions, particularly affecting pregnant women in Africa, yet the mechanisms underlying their interactions remain poorly understood. We employed a multilayered approach combining clinical data from Malawian pregnant women (n=711) in the REVAMP trial, a genetic mouse model (Tmprss6-knockout), and in vitro P. falciparum cultures to clarify associations between iron status and malaria susceptibility. Iron deficiency was associated with 50% reduced P. falciparum parasitemia in pregnant women (95% CI [30%-64%], p<0.0001), while iron-deficient mice exhibited significantly improved survival against P. berghei (median 15.5 days vs. 7.0 days for WT mice) and protection from cerebral malaria (83% vs 17% survival). Iron chelation induced substantial transcriptomic and proteomic changes in cultured parasites, affecting host cell invasion and nutrient acquisition processes. Importantly, intravenous iron supplementation did not increase subsequent parasitemia when coupled with malaria prevention. These findings demonstrate that iron deficiency protects against Plasmodium infection and support WHO recommendations for iron supplementation in malaria-endemic regions when combined with adequate malaria prevention strategies.

cell biology↗

bioRxiv2024

TIRE-seq: an Integrated Sample Extraction and Transcriptomics Workflow for High Throughput Perturbation Studies

RNA sequencing (RNA-seq) is widely used in biomedical research, advancing our understanding of gene expression across biological systems. Traditional methods require upstream RNA extraction from biological inputs, adding time and expense to workflows. We developed TIRE-seq (Turbocapture Integrated RNA Expression Sequencing) to address these challenges. TIRE-seq integrates mRNA purification directly into library preparation, eliminating the need for a separate extraction step. This streamlined approach reduces turnaround time, minimizes sample loss, and improves data quality. A comparative study with the widely used Prime-seq protocol demonstrates TIRE-seqs superior sequencing efficiency with crude cell lysates as inputs. TIRE-seqs utility was demonstrated across three biological applications. It captured transcriptional changes in stimulated human T cells, revealing activation-associated gene expression profiles. It also identified key genes driving murine dendritic cell differentiation, providing insights into lineage commitment. Lastly, TIRE-seq analyzed the dose-response and time-course effects of temozolomide on patient-derived neurospheres, identifying differentially expressed genes and enriched pathways linked to the drugs mechanism of action. With its simplified workflow and high sequencing efficiency, TIRE-seq offers a cost-effective solution for large-scale gene expression studies across diverse biological systems.

genomics↗

bioRxiv2024

More cells, more doublets in highly multiplexed single-cell data

Withdrawal statementThe authors have withdrawn this manuscript. In our initial submission of this paper, we proposed a combinatoric model for the probability of finding doublets in sample-barcoded single-cell RNA-sequencing data. This model predicts a doublet rate higher than the rate included in the documentation for the 10X Flex protocol. This was motivated by our use of doublet-finding software, scDblFinder, on experimental data using the Flex protocol, which identified several times more doublets than we expected based on the documentation. Our original model produced better agreement with the results of scDblFinder in 9 of our own data sets as well as one public dataset made available by 10X. During revisions, however, we performed Monte Carlo simulations of doublet formation that were inconsistent with the results of our model, and much closer to the predictions from the documentation. This prompted us to reanalyse the assumptions of our model. A longer version of this withdrawal statement that explains in detail the errors in the model and includes updated figures is available at https://github.com/Oshlack/flex-doublets, but in brief, our initial assumptions over-predicted the doublet fraction, and our revised model is now consistent with both the Monte Carlo simulations and the predictions from the Flex documentation. We therefore speculate that the unexpectedly high doublet fractions observed in the experimental data might be due to some combination of experimental conditions and software performance. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please ontact the corresponding author.

bioinformatics↗

bioRxiv2024

Spotlight on 10x Visium: a multi-sample protocol comparison of spatial technologies

BackgroundSpatial transcriptomics allows gene expression to be measured within complex tissue contexts. Among the array of spatial capture technologies available is 10x Genomics Visium platform, a popular method which enables transcriptomewide profiling of tissue sections. Visium offers a range of sample handling and library construction methods which introduces a need for benchmarking to compare data quality and assess how well the technology can recover expected tissue features and biological signatures. ResultsHere we present SpatialBench, a unique reference dataset generated from spleen tissue of mice responding to malaria infection spanning several tissue preparation protocols (both fresh frozen and FFPE samples, with and without CytAssist tissue placement). We noted better quality control metrics in reference samples prepared using probe-based capture methods, particularly those processed with CytAssist, validating the improvement in data quality produced with the platform. Our analysis of replicate samples extends to explore spatially variable gene detection, the outcomes of clustering and cell deconvolution using matched single-cell RNA-sequencing data and publicly available reference data to identify cell types and tissue regions expected in the spleen. Multi-sample differential expression analysis recovered known gene signatures related to biological sex or gene knockout. ConclusionsWe framed a comprehensive multi-sample analysis workflow that allowed us to generate consistent results both within and between different subsets of replicate samples, enabling broader comparisons and interpretations to be made at the group-level. Our SpatialBench dataset, analysis, and workflow can serve as a practical guide for Visium users and may prove valuable in other benchmarking studies.

genomics↗

bioRxiv2023

Spatial analysis of Hofbauer cell transcriptome, distribution and morphology in placentas exposed to Plasmodium falciparum

Placental infection remains a significant health burden for mothers and their babies in low-income countries, especially in sub-Saharan Africa, where malaria transmission is intense. An increase in inflammatory biomarkers and poor vascularisation are characteristics of placentas infected with malaria. Hofbauer cells (HBCs) - placental villous macrophages of fetal origin - are one of the most abundant immune cells in the placenta. HBCs are thought to have roles in angiogenic processes and have been linked with the pathophysiology of several infections and inflammatory conditions during pregnancy, including malaria (caused by Plasmodium falciparum). However, there is limited in situ data on the transcriptional, proteomic or morphologic profile of these cells either during or following clearance of P. falciparum infection. We leveraged placental samples prospectively collected at delivery from 610 Malawian women enduring a high burden of malaria and other infections and nutritional deficiencies. We profiled placentas through spatial transcriptomic and proteomic platforms to discern in situ HBC features that could distinguish placentas with or without evidence of past malaria. In this cohort, past placental infection was common and was associated with lower birth weight babies (adjusted effect [95% confidence interval], -80.9 [-165.9, -3.7] g, P= 0.040). However, at term, HBC numbers, abundance, and transcriptional profiles from placentas with evidence of past infection were similar to those of placentas without malaria. HBCs may recover post-infection back to a basal state or may be replaced in the tissue over the course of pregnancy. Placentas with evidence of past malaria did show evidence of reduced fetal vessel development (mean area difference: -22.8% [-37.6, -7.9], P=0.003). Reduced vascular development following infection early in pregnancy may reflect disturbances to the normal vasculogenic and angiogenic processes, of which HBCs are an integral part.

immunology↗

bioRxiv2023

A Risk-reward Examination of Sample Multiplexing Reagents for Single Cell RNA-Seq

Single-cell RNA sequencing (scRNA-Seq) has emerged as a powerful tool for understanding cellular heterogeneity and function. However the choice of sample multiplexing reagents can impact data quality and experimental outcomes. In this study, we compared various multiplexing reagents, including MULTI-Seq, Hashtag antibody, and CellPlex, across diverse sample types such as human peripheral blood mononuclear cells (PBMCs), mouse embryonic brain and patient-derived xenografts (PDXs). We found that all multiplexing reagents worked well in cell types robust to ex vivo manipulation but suffered from signal-to-noise issues in more delicate sample types. We compared multiple demultiplexing algorithms which differed in performance depending on data quality. We find that minor improvements to laboratory workflows such as titration and rapid processing are critical to optimal performance. We also compared the performance of fixed scRNA-Seq kits and highlight the advantages of the Parse Biosciences kit for fragile samples. Highly multiplexed scRNA-Seq experiments require more sequencing resources, therefore we evaluated CRISPR-based destruction of non-informative genes to enhance sequencing value. Our comprehensive analysis provides insights into the selection of appropriate sample multiplexing reagents and protocols for scRNASeq experiments, facilitating more accurate and cost-effective studies.

genomics↗

bioRxiv2022

Multimodal single cell analysis of the paediatric lower airway reveals novel immune cell phenotypes in early life health and disease

Inflammation is a key driver of cystic fibrosis (CF) lung disease, not addressed by current standard care. Improved understanding of the mechanisms leading to aberrant inflammation may assist the development of effective anti-inflammatory therapy. Single-cell RNA sequencing (scRNA-seq) allows profiling of cell composition and function at previously unprecedented resolution. Herein, we seek to use multimodal single-cell analysis to comprehensively define immune cell phenotypes, proportions and functional characteristics in preschool children with CF. We analyzed 42,658 cells from bronchoalveolar lavage of 11 preschool children with CF and a healthy control using scRNA-seq and parallel assessment of 154 cell surface proteins. Validation of cell types identified by scRNA-seq was achieved by assessment of samples by spectral flow cytometry. Analysis of transcriptome expression and cell surface protein expression, combined with functional pathway analysis, revealed 41 immune and epithelial cell populations in BAL. Spectral flow cytometry analysis of over 256,000 cells from a subset of the same patients revealed high correlation in major cell type proportions across the two technologies. Macrophages consisted of 13 functionally distinct sub populations, including previously undescribed populations enriched for markers of vesicle production and regulatory/repair functions. Other novel cell populations included CD4 T cells expressing inflammatory IFN/{beta} and NF{kappa}B signalling genes. Our work provides a comprehensive cellular analysis of the pediatric lower airway in preschool children with CF, reveals novel cell types and provides a reference for investigation of inflammation in early life CF.

systems biology↗

bioRxiv2020

The clonal and molecular aetiology of emergency dendritic cell development

Extrinsic regulation of single haematopoietic stem and progenitor cell (HSPC) fate is crucial for immune cell development. Here, we examine the aetiology of Flt3 ligand (Flt3L)-mediated emergency development of type 1 conventional dendritic cells (cDC1s), which results in enhanced immunity against infections and cancer. Using cellular barcoding, we demonstrate a predominant role of enhanced clonal expansion and moderate contribution via recruitment of additional cDC1-generating HSPCs. The selective cDC1 expansion occurs primarily via multi-/oligo-potent clones, without compromising output to other lineages. To understand the molecular hallmarks early during a Flt3L response, we develop Divi-Seq to simultaneously profile cell division history, surface phenotype and transcriptional state of single HSPCs. We discover that Flt3L-responsive HSPCs maintain a proliferative early progenitor-like state, which leads to selective emergence of CD11c+cKit+ transitional precursors with high cellular output to cDC1s. These findings inform the mechanistic action of Flt3L in natural immunity and immunotherapy at a clonal level.

immunology↗

bioRxiv2019

Evolving Transcriptomic Signature of Human Pluripotent Stem Cell-Derived Retinal Pigment Epithelium Cells With Age

Human pluripotent stem cell (hPSC)-derived progenies are immature versions of cells, presenting a potential limitation to the accurate modelling of disease associated with maturity or age. Hence, it is important to characterise how closely cells used in culture resemble their native counterparts. In order to select appropriate points in time for RPE cultures to reflect native counterparts, we characterised the transcriptomic profiles of hPSC-derived retinal pigment epithelium (RPE) cells from 1- and 12-month cultures. We differentiated the human embryonic stem cell line H9 into RPE cells, performed single cell RNA-sequencing of a total of 16,576 cells, and analysed the resulting data to assess the molecular changes of RPE cells across these two culture time points. Our results indicate the stability of the RPE transcriptomic signature, with no evidence of an epithelial - mesenchymal transition, and with maturing populations of RPE observed with time in culture. Assessment of gene ontology pathways revealed that as cultures age, RPE cells upregulate expression of genes involved in metal binding and antioxidant functions. This might reflect an increased ability to handle oxidative stress as cells mature. Comparison with native human RPE data confirmed a maturing transcriptional profile of RPE cells in culture. These results suggest that in vitro long-term culture of RPE cells allow the modelling of specific phenotypes observed in native mature tissue. Our work highlights the transcriptional landscape of hPSC-derived RPE as they age in culture, which provides a reference for native and patient-samples to be benchmarked against.

cell biology↗

bioRxiv2018

scRNA-seq mixology: towards better benchmarking of single cell RNA-seq protocols and analysis methods

Single cell RNA sequencing (scRNA-seq) technology has undergone rapid development in recent years, bringing with it new challenges in data processing and analysis. This has led to an explosion of tailored analysis methods for scRNA-seq to address various biological questions. However, the current lack of gold-standard benchmarking datasets makes it difficult for researchers to evaluate the performance of the many methods. Here, we designed and carried out a realistic benchmark experiment that included mixtures of single cells or pseudo-cells created by sampling admixtures of cells or RNA from 3 distinct cancer cell lines. Altogether we generated 10 datasets using a combination of droplet and plate-based scRNA-seq protocols, with varying data quality, population heterogeneity and noise levels. Using these benchmark datasets, we compared different protocols, evaluated the spike-in standard and multiple data analysis methods for tasks ranging from normalization and imputation, to clustering, trajectory analysis and data integration. Evaluation of methods across multiple datasets revealed some that performed well in general and others that suited specific situations. Our dataset and analysis provide a comprehensive comparison framework for benchmarking most popular scRNA-seq analysis tasks.

bioinformatics↗

bioRxiv2018

SIS-seq, a molecular ‘time machine’, connects single cell fate with gene programs

Conventional single cell RNA-seq methods are destructive, such that a given cell cannot also then be tested for fate and function, without a time machine. Here, we develop a clonal method SIS-seq, whereby single cells are allowed to divide, and progeny cells are assayed separately in SISter conditions; some for fate, others by RNA-seq. By cross-correlating progenitor gene expression with mature cell fate within a clone, and doing this for many clones, we can identify the earliest gene expression signatures of dendritic cell subset development. SIS-seq could be used to study other populations harboring clonal heterogeneity, including stem, reprogrammed and cancer cells to reveal the transcriptional origins of fate decisions.

systems biology↗

bioRxiv2017

scPipe: a flexible data preprocessing pipeline for single-cell RNA-sequencing data

Single-cell RNA sequencing (scRNA-seq) technology allows researchers to profile the transcriptomes of thousands of cells simultaneously. Protocols that incorpo-rate both designed and random barcodes have greatly increased the throughput of scRNA-seq, but give rise to a more complex data structure. There is a need for new tools that can handle the various barcoding strategies used by different protocols and exploit this information for quality assessment at the sample-level and provide effective visualization of these results in preparation for higher-level analyses.\n\nTo this end, we developed scPipe, a R/Bioconductor package that integrates barcode demultiplexing, read alignment, UMI-aware gene-level quantification and quality control of raw sequencing data generated by multiple 3-prime-end sequencing protocols that include CEL-seq, MARS-seq, Chromium 10X and Drop-seq. scPipe produces a count matrix that is essential for downstream analysis along with an HTML report that summarises data quality. These results can be used as input for downstream analyses including normalization, visualization and statistical testing. scPipe performs this processing in a few simple R commands, promoting reproducible analysis of single-cell data that is compatible with the emerging suite of scRNA-seq analysis tools available in R/Bioconductor. The scPipe R package is available for download from https://www.bioconductor.org/packages/scPipe.

bioinformatics↗