Biology subjects

Hickey, P. F.

Publications and source records attributed to Hickey, P. F..

15 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

γδ T cells modulate anti-tumor immunity in small cell lung cancer

Small cell lung cancer (SCLC) is a highly aggressive neoplasm with limited sensitivity to anti-PD-(L)1 blockade, likely due to the epigenetic silencing of MHC-I. Elucidating MHC-I-independent immune recognition mechanisms is therefore crucial for enhancing treatment responses and improving clinical outcomes in a greater number of patients. Leveraging single cell approaches, we discovered {gamma}{delta} T cell infiltration in biospecimens from patients with SCLC. Despite PD-1 expression, {gamma}{delta} T cells maintained a cytotoxic transcriptional profile, suggestive of an anti-tumor role. Indeed, high {gamma}{delta} T cell infiltration predicted improved response to anti-PD-L1 immunotherapy in patients with SCLC. Moreover, using pre-clinical models, we demonstrated that {gamma}{delta} T cells are effective at tarlatamab (DLL3-CD3 BiTE) redirected SCLC killing and that zoledronate, an FDA-approved compound, can sensitize SCLC cells to {gamma}{delta} T cell-mediated killing. Thus, our findings suggest that engaged {gamma}{delta} T cells are potentially valuable targets for SCLC therapy.

cancer biology↗

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

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

Modelling group heteroscedasticity in single-cellRNA-seq pseudo-bulk data

Group heteroscedasticity is commonly observed in pseudo-bulk single-cell RNA-seq datasets and when not modelled appro-priately, its presence can hamper the detection of differentially expressed genes. Most bulk RNA-seq methods assume equal group variances which will under- and/or over-estimate the true variability in such datasets. We present two methods that account for heteroscedastic groups, namely voomByGroup and voomWithQualityWeights using a blocked design (voomQWB). Compared to current gold standard methods that do not account for heteroscedasticity, we show results from simulation studies and various experiments that demonstrate the superior performance of both voomByGroup and voomQWB in error control and power when group variances in pseudo-bulk scRNA-seq data are unequal. We recommend the use of either of these methods over established approaches, with voomByGroup having the advantage of accurate variance estimation since group variance trends can take on different "shapes", whilst voomQWB has the advantage of catering to complex study designs.

bioinformatics↗

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↗

bioRxiv2022

A method for stabilising the XX karyotype in female mESC cultures

Female mouse embryonic stem cells (mESCs) present differently to male mESCs in several fundamental ways, however complications with their in vitro culture have resulted in an underrepresentation of female mESCs in the literature. Recent studies show that the second X chromosome in female, and more specifically the transcriptional activity from both of these chromosomes due to absent X chromosome inactivation, sets female mESCs apart from males. To avoid this undesirable state, female mESCs in culture preferentially adopt an XO karyotype, with this adaption leading to loss of their unique properties in favour of a state near indistinguishable from male. If female pluripotency is to be studied effectively in this system, it is critical that high quality cultures of XX mESCs are available. Here we report a method for better maintaining XX female mESCs in culture, which also stabilises the male karyotype, and makes study of female specific pluripotency more feasible.

cell biology↗

bioRxiv2021

Benchmarking UMI-based single cell RNA-sequencing preprocessing workflows

Single-cell RNA sequencing (scRNA-seq) technologies and associated analysis methods have undergone rapid development in recent years. This includes methods for data preprocessing, which assign sequencing reads to genes to create count matrices for downstream analysis. Several packaged preprocessing workflows have been developed that aim to provide users with convenient tools for handling this process. How different preprocessing workflows compare to one another and influence downstream analysis has been less well studied. Here, we systematically benchmark the performance of 9 end-to-end preprocessing workflows (Cell Ranger, Optimus, salmon alevin, kallisto bustools, dropSeqPipe, scPipe, zUMIs, celseq2 and scruff) using datasets with varying levels of biological complexity generated on the CEL-Seq2 and 10x Chromium platforms. We compare these workflows in terms of their quantification properties directly and their impact on normalization and clustering by evaluating the performance of different method combinations. We find that lowly expressed genes are discordant between workflows and observe that some workflows have systematic biases towards particular classes of genomics features. While the scRNA-seq preprocessing workflows compared varied in their detection and quantification of genes across datasets, after downstream analysis with performant normalization and clustering methods, almost all combinations produced clustering results that agreed well with the known cell type labels that provided the ground truth in our analysis. In summary, the choice of preprocessing method was found to be less influential than other steps in the scRNA-seq analysis process. Our study comprehensively compares common scRNA-seq preprocessing workflows and summarizes their characteristics to guide workflow users.

bioinformatics↗

bioRxiv2021

Human brain region-specific variably methylated regions (VMRs) are enriched for heritability of distinct neuropsychiatric traits

BACKGROUNDDNA methylation dynamics in the brain are associated with normal development and neuropsychiatric disease and differ across functionally distinct brain regions. Previous studies of genome-wide methylation differences among human brain regions focused on limited numbers of individuals and one to two brain regions. RESULTSUsing GTEx samples, we have generated a resource of DNA methylation in purified neuronal nuclei from 8 brain regions as well as lung and thyroid tissues from 12-23 donors. We identified differentially methylated regions between brain regions (DMRs) among neuronal nuclei in both CpG (181,146) and non-CpG (264,868) contexts, few of which were unique to a single pair-wise comparison. This significantly expands the knowledge of differential methylation across the brain by 10-fold. In addition, we present the first differential methylation analysis among neuronal nuclei from basal ganglia tissues and identified 2,295 unique CpG DMRs, many associated with ion transport. Consistent with prior studies, CpG DMRs were enriched in regulatory regions while non-CpG DMRs were enriched in intergenic regions. We also identified 81,130 regions of variably CpG methylated regions (VMRs), i.e. variable methylation among individuals in the same brain region, which were enriched in regulatory regions and in CpG DMRs. Many VMRs were unique to a specific brain region, with only 202 common across all brain regions, as well as lung and thyroid. VMRs identified in the amygdala, anterior cingulate cortex, and hippocampus were enriched for heritability of schizophrenia. CONCLUSIONSThese data suggest that epigenetic variation in these particular human brain regions could be associated with the risk for this neuropsychiatric disorder.

genomics↗

bioRxiv2020

Genetic demultiplexing of pooled single-cell RNA-sequencing samples in cancer facilitates effective experimental design

BackgroundPooling cells from multiple biological samples prior to library preparation within the same single-cell RNA sequencing experiment provides several advantages, including lower library preparation costs and reduced unwanted technological variation, such as batch effects. Computational demultiplexing tools based on natural genetic variation between individuals provide a simple approach to demultiplex samples, which does not require complex additional experimental procedures. However, these tools have not been evaluated in cancer, where somatic variants, which could differ between cells from the same sample, may obscure the signal in natural genetic variation. ResultsHere, we performed in silico benchmark evaluations by combining raw sequencing reads from multiple single-cell samples in high-grade serous ovarian cancer, which has a high copy number burden, and lung adenocarcinoma, which has a high tumor mutational burden. Our results confirm that genetic demultiplexing tools can be effectively deployed on cancer tissue using a pooled experimental design, although high proportions of ambient RNA from cell debris reduce performance. ConclusionsThis strategy provides significant cost savings through pooled library preparation. To facilitate similar analyses at the experimental design phase, we provide freely accessible code and a reproducible Snakemake workflow built around the best-performing tools found in our in silico benchmark evaluations, available at https://github.com/lmweber/snp-dmx-cancer.

bioinformatics↗

bioRxiv2019

Tximeta: reference sequence checksums for provenance identification in RNA-seq

Correct annotation metadata is critical for reproducible and accurate RNA-seq analysis. When files are shared publicly or among collaborators with incorrect or missing annotation metadata, it becomes difficult or impossible to reproduce bioinformatic analyses from raw data. It also makes it more difficult to locate the transcriptomic features, such as transcripts or genes, in their proper genomic context, which is necessary for overlapping expression data with other datasets. We provide a solution in the form of an R/Bioconductor package tximeta that performs numerous annotation and metadata gathering tasks automatically on behalf of users during the import of transcript quantification files. The correct reference transcriptome is identified via a hashed checksum stored in the quantification output, and key transcript databases are downloaded and cached locally. The computational paradigm of automatically adding annotation metadata based on reference sequence checksums can greatly facilitate genomic workflows, by helping to reduce overhead during bioinformatic analyses, preventing costly bioinformatic mistakes, and promoting computational reproducibility. The tximeta package is available at https://bioconductor.org/packages/tximeta.

bioinformatics↗

bioRxiv2019

Xmas ESC: A new female embryonic stem cell system that reveals the BAF complex as a key regulator of the establishment of X chromosome inactivation

Although female pluripotency significantly differs to male, complications with in vitro culture of female embryonic stem cells (ESC) have severely limited the use and study of these cells. We report a replenishable female ESC system, Xmas, that has enabled us to optimise a protocol for preserving the XX karyotype. Our protocol also improves male ESC fitness. We utilised our Xmas ESC system to screen for regulators of the female-specific process of X chromosome inactivation, revealing chromatin remodellers Smarcc1 and Smarca4 as key regulators of establishment of X inactivation. The remodellers create a nucleosome depleted region at gene promotors on the inactive X during exit from pluripotency, without which gene silencing fails. Our female ESC system provides a tractable model for XX ESC culture that will expedite study of female pluripotency and has enabled us to discover new features of the female-specific process of X inactivation.

cell biology↗