Biology subjects

Milton, M.

Publications and source records attributed to Milton, M..

6 recordsLinked to original sources

bioRxiv2026

cellNexus: Quality control, annotation, aggregation and analytical layers for the Human Cell Atlas data

Large-scale single-cell atlases such as the Human Cell Atlas have transformed our understanding of human biology. Yet, the lack of a robust framework that standardises quality control, expands cellular annotation, and adds normalisation and analytical layers, limits multi-study analyses and the usefulness of this resource. Here we present cellNexus, a comprehensive resource that enhances the Human Cell Atlas collection into analysis-ready data by linking quality control layers, metadata enrichment, expression normalisation, analysis and data aggregation. These enhancements enable robust large-scale statistical modelling across studies, exemplified here by a multi-tissue map of immune cell communication during ageing. All harmonised layers are accessible via a public web interface and with R and Python APIs. By providing continuous integration with CELLxGENE releases, cellNexus transforms large cell atlas corpora into an accessible, reproducible, interoperable foundation for large-scale biological discovery and the next generation of single-cell foundation models.

bioinformatics↗

bioRxiv2026

Fast, accurate and scalable normalization for RNA sequencing data with the RUVprps software package

Unwanted variation refers to any source of variability in the data that can compromise down-stream analysis. Effective removal of such variation from gene expression data is essential to derive accurate and meaningful biological results. We refer to this process as normalization. Data may come from a single study or from multiple studies with different sources of unwanted variation. We have previously developed the RUV-III method for normalizing omics data with a strong focus on transcriptomics. Initially, we introduced RUV-III for the normalization of Nanostring nCounter gene expression data, utilizing genuine technical replicates and pseudo-replicates as control samples. Subsequently, we proposed RUV-III with pseudo-replicates of pseudo-samples (PRPS), and which demonstrated its potential in mitigating the effects of different sources of unwanted variation in large and complex RNA-seq studies. To enhance accessibility and performance of this method, we present a new comprehensive R package named RUVprps. The package offers over 100 functions including ones for assessing variation in both biological and unwanted variables, an automated RUV-III normalization process, and metrics for evaluating the effectiveness of the resulting normalizations. Further, it introduces several new features such as ways of identifying unknown sources of unwanted variation, strategies to identify suitable negative control genes, and methods for generating PRPS when information on the biological and unwanted variation is unavailable. The package also implements a faster approach to RUV-III normalization, streamlining its application to large RNA-seq datasets. Our freely available R package and normalization assessment pipeline can help find effective data normalization methods for new data and help benchmark new methods.

bioinformatics↗

bioRxiv2026

Human CD1c-autoreactive T cells recognise Mycobacterium tuberculosis-infected antigen-presenting cells and display cytotoxic effector programmes

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), remains the leading cause of death from infection globally, yet the contribution of non-classical T-cell pathways to human immunity remains poorly defined. CD1c-autoreactive T-cells, which recognise self-lipids presented by the antigen-presenting molecule CD1c, are frequent in human blood, but their role during infection is unclear. Here, we investigate how CD1c-expressing antigen-presenting cells (APCs) and Mtb infection shape CD1c-autoreactive T-cell responses using engineered human APC systems, complemented by single-cell transcriptomic profiling to define the ex vivo phenotypic landscape of these T-cells. CD1c is present within human TB granulomas, whereas Mtb down-modulates CD1c expression on infected APCs, consistent with an immune evasion strategy. CD1c-autoreactive T-cells respond more strongly to Mtb-infected CD1c+ APCs than to uninfected cells, exhibiting enhanced activation, cytotoxicity, and diverse cytokine secretion via CD1c-dependent recognition. Under in vitro conditions, these T-cells reduce relative Mtb burden in infected phagocytes. Single-cell RNA-sequencing reveals cytotoxic effector-memory programmes and expression of antimicrobial molecules, providing a mechanistic basis for these responses. Together, these findings define a human CD1c-restricted T-cell response to Mtb-infected APCs and identify autoreactive CD1c-restricted T-cells as a candidate cellular axis for lipid-directed immunity in TB.

immunology↗

bioRxiv2023

Whole body cell map tracks tissue-specific immune cell accumulation and plasticity loss through ageing

Understanding tissue biologys heterogeneity is crucial for advancing precision medicine. Despite the centrality of the immune system in tissue homeostasis, a detailed and comprehensive map of immune cell distribution and interactions across human tissues and demographics remains elusive. To fill this gap, we harmonised data from 12,981 single-cell RNA sequencing samples and curated 29 million cells from 45 anatomical sites to create a comprehensive compositional and transcriptional healthy map of the healthy immune system. We used this resource and a novel multilevel modelling approach to track immune ageing and test differences across sex and ethnicity. We uncovered conserved and tissue-specific immune-ageing programs, resolved sex-dependent differential ageing and identified ethnic diversity in clinically critical immune checkpoints. This study provides a quantitative baseline of the immune system, facilitating advances in precision medicine. By sharing our immune map, we hope to catalyse further breakthroughs in cancer, infectious disease, immunology and precision medicine.

immunology↗

bioRxiv2022

Atmospheric hydrogen oxidation extends to the domain archaea

Diverse aerobic bacteria use atmospheric hydrogen (H2) and carbon monoxide (CO) as energy sources to support growth and survival. Though recently discovered, trace gas oxidation is now recognised as a globally significant process that serves as the main sink in the biogeochemical H2 cycle and sustains microbial biodiversity in oligotrophic ecosystems. While trace gas oxidation has been reported in nine phyla of bacteria, it was not known whether archaea also use atmospheric H2. Here we show that a thermoacidophilic archaeon, Acidianus brierleyi (Thermoproteota), constitutively consumes H2 and CO to sub-atmospheric levels. Oxidation occurred during both growth and survival across a wide range of temperatures (10 to 70{degrees}C). Genomic analysis demonstrated that A. brierleyi encodes a canonical carbon monoxide dehydrogenase and, unexpectedly, four distinct [NiFe]-hydrogenases from subgroups not known to mediate aerobic H2 uptake. Quantitative proteomic analyses showed that A. brierleyi differentially produced these enzymes in response to electron donor and acceptor availability. A previously unidentified group 1 [NiFe]-hydrogenase, with a unique genetic arrangement, is constitutively expressed and upregulated during stationary phase and aerobic hydrogenotrophic growth. Another archaeon, Metallosphaera sedula, was also found to oxidize atmospheric H2. These results suggest that trace gas oxidation is a common trait of aerobic archaea, which likely plays a role in their survival and niche expansion, including during dispersal through temperate environments. These findings also demonstrate that atmospheric H2 consumption is a cross-domain phenomenon, suggesting an ancient origin of this trait, and identify previously unknown microbial and enzymatic sinks of atmospheric H2 and CO.

microbiology↗

bioRxiv2021

Message in a Bottle, Metabarcoding Enables Biodiversity Comparisons Across Ecoregions

BackgroundTraditional biomonitoring approaches have delivered a basic understanding of biodiversity, but they cannot support the large-scale assessments required to manage and protect entire ecosystems. This study employed DNA metabarcoding to assess spatial and temporal variation in species richness and diversity in arthropod communities from 52 protected areas spanning three Canadian ecoregions. ResultsThis study revealed the presence of 26,263 arthropod species in the three ecoregions and indicated that at least another 3,000-5,000 await detection. Results further demonstrate that communities are more similar within than between ecoregions, even after controlling for geographical distance. Overall -diversity declined from east to west, reflecting a gradient in habitat disturbance. Shifts in species composition were high at every site with turnover greater than nestedness, suggesting the presence of many transient species. ConclusionsDifferences in species composition among their arthropod communities confirm that ecoregions are a useful synoptic for biogeographic patterns and for structuring conservation efforts. The present results also demonstrate that metabarcoding enables large-scale monitoring of shifts in species composition, making it possible to move beyond the biomass measurements that have been the key metric employed in prior efforts to track change in arthropod communities.

ecology↗