Biology subjects

Hickey, J.

Publications and source records attributed to Hickey, J..

9 recordsLinked to original sources

bioRxiv2025

A spatial atlas of colorectal cancer reveals the influence of stromal niches on tumour differentiation

Colorectal cancer is the third most common cancer worldwide and the second leading cause of cancer-related mortality. Tumour architecture is spatially heterogeneous, ranging from the necrotic core to the invasive front, accompanied by diverse stromal and immune responses that influence tumour progression and treatment outcomes. To explore the spatial organisation of the tumour microenvironment, we profiled 1000 genes in 846,469 cells in 23 normal and late-stage colorectal tumour samples. We identified nine distinct spatial niches based on their cellular composition. We show that lymphoid aggregates enriched for CCR7/SELL+ CD4 T cells displayed heightened interferon signalling, more proliferating B cells and gene expression changes indicative of an adaptive immune response. We defined granulocyte-rich regions are concomitant with inflammation-mediated stromal reprogramming and increased tumour stemness. Finally, we uncovered the impact of the tumour microenvironment by distinguishing gene expression programs that were intrinsic to cancerous epithelial cells from those mediated by niche-specific changes. Key pointsO_LIWe present a spatial atlas of colorectal cancer and normal colon alongside an R/shiny interface to interactively explore this data: https://abud-apps.abud-lab-spatial.cloud.edu.au/shiny/cosmxos/. We analysed nine CosMx slides and provide QC metrics, identify strengths and weaknesses and provide suggestions for analysis of imaging-based spatial data. C_LIO_LIWe identify and characterise nine distinct spatial niches, each with their unique gene expression profile. C_LIO_LIWe observe granulocyte infiltration associated with spatially controlled TNF and IL1 signalling from granulocytes and myeloid cells. This signalling associates with a reduction in pro-differentiation CXCL14 fibroblasts and an increase in MMP tissue-remodelling fibroblasts, ultimately reprogramming tumours toward a more foetal/stem-like (progenitor) state. We suggest IL24 as a potential regulatory factor of this response. C_LIO_LIGranulocyte chemoattractants were consistently expressed at higher levels by both cancerous epithelial cells and the tumour microenvironment (TME) relative to normal colon. C_LIO_LIWe identify colonic LAs associated with T cell infiltration, including a population of CCR7/SELL+ CD4 T cells linked to significant reprogramming of B cells. Furthermore, we show that granulocyte-driven fibroblast and myeloid reprogramming is reversed within LAs. C_LIO_LIWe show that mutated epithelial cells within tumours are uniquely marked by an FXYD5+ PIGRlow expression profile, allowing for tumour vs normal epithelial cell differential gene expression analysis. This distinction clarifies cancerous tumour-intrinsic expression changes versus those promoted by the TME. C_LI

cancer biology↗

bioRxiv2023

Formulation development and comparability studies with an aluminum-salt adjuvanted SARS-CoV-2 Spike ferritin nanoparticle vaccine antigen produced from two different cell lines

The development of safe and effective second-generation COVID-19 vaccines to improve affordability and storage stability requirements remains a high priority to expand global coverage. In this report, we describe formulation development and comparability studies with a self-assembled SARS-CoV-2 spike ferritin nanoparticle vaccine antigen (called DCFHP), when produced in two different cell lines and formulated with an aluminum-salt adjuvant (Alhydrogel, AH). Varying levels of phosphate buffer altered the extent and strength of antigen-adjuvant interactions, and these formulations were evaluated for their (1) in vivo performance in mice and (2) in vitro stability profiles. Unadjuvanted DCFHP produced minimal immune responses while AH-adjuvanted formulations elicited greatly enhanced pseudovirus neutralization titers independent of [~]100%, [~]40% or [~]10% of the DCFHP antigen adsorbed to AH. These formulations differed, however, in their in vitro stability properties as determined by biophysical studies and a competitive ELISA for measuring ACE2 receptor binding of AH-bound antigen. Interestingly, after one month of 4{degrees}C storage, small increases in antigenicity with concomitant decreases in the ability to desorb the antigen from the AH were observed. Finally, we performed a comparability assessment of DCFHP antigen produced in Expi293 and CHO cells, which displayed expected differences in their N-linked oligosaccharide profiles. Despite consisting of different DCFHP glycoforms, these two preparations were highly similar in their key quality attributes including molecular size, structural integrity, conformational stability, binding to ACE2 receptor and mouse immunogenicity profiles. Taken together, these studies support future preclinical and clinical development of an AH-adjuvanted DCFHP vaccine candidate produced in CHO cells.

immunology↗

bioRxiv2023

Correlating physicochemical and biological properties to define critical quality attributes of a recombinant AAV vaccine candidate

Recombinant adeno-associated viruses (rAAVs) are a preferred vector system in clinical gene transfer. A fundamental challenge to formulate and deliver rAAVs as stable and efficacious vaccines is to elucidate interrelationships between the vectors physicochemical properties and biological potency. To this end, we evaluated an rAAV-based COVID-19 vaccine candidate which encodes the Spike antigen (AC3) and is produced by an industrially-compatible process. First, state-of-the-art analytical techniques were employed to determine key structural attributes of AC3 including primary and higher-order structures, particle size, empty/full capsid ratios, aggregates and multi-step thermal degradation pathway analysis. Next, several quantitative potency measures for AC3 were implemented and data were correlated with the physicochemical analyses on thermal-stressed and control samples. Results demonstrate links between decreasing AC3 physical stability profiles, in vitro transduction efficiency in a cell-based assay, and importantly, in vivo immunogenicity in a mouse model. These findings are discussed in the general context of future development of rAAV-based vaccines candidates as well as specifically for the rAAV vaccine application under study.

immunology↗

bioRxiv2023

Integration of spatial and single-cell data across modalities with weak linkage

single-cell sequencing methods have enabled the profiling of multiple types of molecular readouts at cellular resolution, and recent developments in spatial barcoding, in situ hybridization, and in situ sequencing allow such molecular readouts to retain their spatial context. Since no technology can provide complete characterization across all layers of biological modalities within the same cell, there is pervasive need for computational cross-modal integration (also called diagonal integration) of single-cell and spatial omics data. For current methods, the feasibility of cross-modal integration relies on the existence of highly correlated, a priori "linked" features. When such linked features are few or uninformative, a scenario that we call "weak linkage", existing methods fail. We developed MaxFuse, a cross-modal data integration method that, through iterative co-embedding, data smoothing, and cell matching, leverages all information in each modality to obtain high-quality integration. MaxFuse is modality-agnostic and, through comprehensive benchmarks on single-cell and spatial ground-truth multiome datasets, demonstrates high robustness and accuracy in the weak linkage scenario. A prototypical example of weak linkage is the integration of spatial proteomic data with single-cell sequencing data. On two example analyses of this type, we demonstrate how MaxFuse enables the spatial consolidation of proteomic, transcriptomic and epigenomic information at single-cell resolution on the same tissue section.

bioinformatics↗

bioRxiv2021

Anatomical Structures, Cell Types, and Biomarkers Tables Plus 3D Reference Organs in Support of a Human Reference Atlas

1.This paper reviews efforts across 16 international consortia to construct human anatomical structures, cell types, and biomarkers (ASCT+B) tables and three-dimensional reference organs in support of a Human Reference Atlas. We detail the ontological descriptions and spatial three-dimensional anatomical representations together with user interfaces that support the registration and exploration of human tissue data. Four use cases are presented to demonstrate the utility of ASCT+B tables for advancing biomedical research and improving health.

cell biology↗

bioRxiv2018

Extending long-range phasing and haplotype library imputation algorithms to very large and heterogeneous datasets

BackgroundThis paper describes the latest improvements to the long-range phasing and haplotype library imputation algorithms that enable them to successfully phase both datasets with one million individuals and datasets genotyped using different sets of single nucleotide polymorphisms (SNPs). Previous publicly available implementations of long-range phasing could not phase large datasets due to the computational cost of defining surrogate parents by exhaustive all-against-all searches. Further, both long-range phasing and haplotype library imputation were not designed to deal with large amounts of missing data, which is inherent when using multiple SNP arrays.\n\nMethodsHere, we developed methods which avoid the need for all-against-all searches by performing long-range phasing on subsets of individuals and then combing results. We also extended long-range phasing and haplotype library imputation algorithms to enable them to use different sets of markers, including missing values, when determining surrogate parents and identifying haplotypes. We implemented and tested these extensions in an updated version of our phasing software AlphaPhase.\n\nResultsA simulated dataset with one million individuals genotyped with the same set of 6,711 SNP for a single chromosome took two days to phase. A larger dataset with one million individuals genotyped with 49,579 SNP for a single chromosome took 14 days to phase. The percentage of correctly phased alleles at heterozygous loci was respectively 90.5% and 90.0% for the two datasets, which is comparable to the accuracy achieved with previous versions of AlphaPhase on smaller datasets.\n\nThe phasing accuracy for datasets with different sets of markers was generally lower than that for datasets with one set of markers. For a simulated dataset with three sets of markers 2.8% of alleles at heterozygous positions were phased incorrectly whereas the equivalent figure with one set of markers was 0.6%.\n\nConclusionsThe improved long-range phasing and haplotype library imputation algorithms enable AlphaPhase to quickly and accurately phase very large and heterogeneous datasets. This will enable more powerful breeding and genetics research and application.

bioinformatics↗

bioRxiv2018

Impact of index hopping and bias towards the reference allele on accuracy of genotype calls from low-coverage sequencing

BackgroundInherent sources of error and bias that affect the quality of the sequence data include index hopping and bias towards the reference allele. The impact of these artefacts is likely greater for low-coverage data than for high-coverage data because low-coverage data has scant information and standard tools for processing sequence data were designed for high-coverage data. With the proliferation of cost-effective low-coverage sequencing there is a need to understand the impact of these errors and bias on resulting genotype calls.\n\nResultsWe used a dataset of 26 pigs sequenced both at 2x with multiplexing and at 30x without multiplexing to show that index hopping and bias towards the reference allele due to alignment had little impact on genotype calls. However, pruning of alternative haplotypes supported by a number of reads below a predefined threshold, a default and desired step for removing potential sequencing errors in high-coverage data, introduced an unexpected bias towards the reference allele when applied to low-coverage data. This bias reduced best-guess genotype concordance of low-coverage sequence data by 19.0 absolute percentage points.\n\nConclusionsWe propose a simple pipeline to correct this bias and we recommend that users of low-coverage sequencing be wary of unexpected biases produced by tools designed for high-coverage sequencing.

bioinformatics↗

bioRxiv2018

Parentage assignment with low density array data and low coverage sequence data

In this paper we evaluate using genotype-by-sequencing (GBS) data to perform parentage assignment in lieu of traditional array data. The use of GBS data raises two issues: First, for low-coverage GBS data, it may not be possible to call the genotype at many loci, a critical first step for detecting opposing homozygous markers. Second, the amount of sequencing coverage may vary across individuals, making it challenging to directly compare the likelihood scores between putative parents. To address these issues we extend the probabilistic framework of Huisman (2017) and evaluate putative parents by comparing their (potentially noisy) genotypes to a series of proposal distributions. These distributions describe the expected genotype probabilities for the relatives of an individual. We assign putative parents as a parent if they are classified as a parent (as opposed to e.g., an unrelated individual), and if the assignment score passes a threshold. We evaluated this method on simulated data and found that (1) high-coverage GBS data performs similarly to array data and requires only a small number of markers to correctly assign parents and (2) low-coverage GBS data (as low as 0.1x) can also be used, provided that it is obtained across a large number of markers. When analysing the low-coverage GBS data, we also found a high number of false positives if the true parent is not contained within the list of candidate parents, but that this false positive rate can be greatly reduced by hand tuning the assignment threshold. We provide this parentage assignment method as a standalone program called AlphaAssign.

genetics↗

bioRxiv2017

A strategy to exploit surrogate sire technology in livestock breeding programs

In this work, we performed simulations to develop and test a strategy for exploiting surrogate sire technology in animal breeding programs. Surrogate sire technology allows the creation of males that lack their own germline cells, but have transplanted spermatogonial stem cells from donor males. With this technology, a single elite male donor could give rise to huge numbers of progeny, potentially as much as all the production animals in a particular time period.\n\nOne hundred replicates of various scenarios were performed. Scenarios followed a common overall structure but differed in the strategy used to identify elite donors and how these donors were used in the product development part.\n\nThe results of this study showed that using surrogate sire technology would significantly increase the genetic merit of commercial sires, by as much as 6.5 to 9.2 years worth of genetic gain compared to a conventional breeding program. The simulations suggested that a strategy involving three stages (an initial genomic test followed by two subsequent progeny tests) was the most effective of all the strategies tested.\n\nThe use of one or a handful of elite donors to generate the production animals would be very different to current practice. While the results demonstrate the great potential of surrogate sire technology there are considerable risks but also other opportunities. Practical implementation of surrogate sire technology would need to account for these.

genetics↗