Biology subjects

Milner, J.

Publications and source records attributed to Milner, J..

5 recordsLinked to original sources

bioRxiv2023

Balancing the scales: Impact of irrigation and pathogen burden on potato blackleg disease and soil microbial communities

Understanding the interaction between environmental conditions, crop yields, and soil health is crucial for sustainable agriculture in a changing climate. Management practices to limit disease are a balancing act. For example, in potato production, dry conditions favour common scab (Streptomyces spp.) and wet conditions favour blackleg disease (Pectobacterium spp.). The exact mechanisms involved and how these link to changes in the soil microbiome is unclear. Our objectives were to test how irrigation management and bacterial pathogen load in potato seed stocks impact: i) crop yields; ii) disease development (blackleg/common scab); and iii) soil microbial community dynamics. We used stocks of seed potatoes with varying Pectobacterium levels (Jelly [high load], Jelly [low load], and Estima [Zero - no Pectobacterium]). Stocks were grown under four irrigation regimes that differed in the timing and level of watering. The soil microbial communities were profiled using amplicon sequencing at 50% plant emergence and harvest and advanced bioinformatic analyses were used to correlate microbes to treatments and disease symptoms. Irrigation increased blackleg symptoms in the plots planted with stocks with low and high levels of Pectobacterium (22-34%) but not in the zero stock (2-6%). Not irrigating increased common scab symptoms (2-5%) and reduced crop yields. Irrigation did not impact the composition of the soil microbiome, but planting stock with a high Pectobacterium burden resulted in an increased abundance of Planctomycetota, Anaerolinea, and Acidobacteria species within the microbiome. Ensemble quotient analysis highlighted Anaerolinea as highly associated with blackleg symptoms in the field. We conclude that Pectobacterium pathogen load within seed stocks could have more substantial effects on soil communities than irrigation regimes.

microbiology↗

bioRxiv2023

Feature selection for preserving biological trajectories in single-cell data

Single-cell technologies can readily measure the expression of thousands of molecular features from individual cells undergoing dynamic biological processes, such as cellular differentiation, immune response, and disease progression. While examining cells along a computationally ordered pseudotime offers the potential to study how subtle changes in gene or protein expression impact cell fate decision-making, identifying characteristic features that drive continuous biological processes remains difficult to detect from unenriched and noisy single-cell data. Given that all profiled sources of feature variation contribute to the cell-to-cell distances that define an inferred cellular trajectory, including confounding sources of biological variation (e.g. cell cycle or metabolic state) or noisy and irrelevant features (e.g. measurements with low signal-to-noise ratio) can mask the underlying trajectory of study and hinder inference. Here, we present DELVE (dynamic selection of locally covarying features), an unsupervised feature selection method for identifying a representative subset of dynamically-expressed molecular features that recapitulates cellular trajectories. In contrast to previous work, DELVE uses a bottom-up approach to mitigate the effect of unwanted sources of variation confounding inference, and instead models cell states from dynamic feature modules that constitute core regulatory complexes. Using simulations, single-cell RNA sequencing data, and iterative immunofluorescence imaging data in the context of the cell cycle and cellular differentiation, we demonstrate that DELVE selects features that more accurately characterize cell populations and improve the recovery of cell type transitions. This feature selection framework provides an alternative approach for improving trajectory inference and uncovering co-variation amongst features along a biological trajectory. DELVE is implemented as an open-source python package and is publicly available at: https://github.com/jranek/delve.

bioinformatics↗

bioRxiv2021

Single-cell lineage trajectories and chromatin regulators that initialize antiviral CD8 T cell ontogeny

Individual naive CD8 T cells activated in lymphoid organs differentiate into functionally diverse and anatomically distributed T cell phylogenies in response to intracellular microbes. During infections that resolve rapidly, including live viral vaccines1, distinct effector (TEFF) and memory (TMEM) cell populations develop that ensure long term immunity2. During chronic infections, responding cells progressively become dysfunctional and "exhaust"3. A diverse taxonomy of TEFF, TMEM and exhausted (TEX) CD8 T cell populations is known, but the initial developmental basis of this phenotypic variation remains unclear4-10. Here, we defined single-cell trajectories and identified chromatin regulators that establish antiviral CD8 T cell heterogeneity using unsupervised analyses of single-cell RNA dynamics11-13 and an in vivo RNAi screen14. Activated naive cells differentiate linearly into uncommitted effector-memory progenitor (EMP) cells, which initially branch into an analogous manifold during either acute or chronic infection. Disparate RNA velocities in single EMP cells initiate divergence into stem, circulating, and tissue-resident memory lineages that generate diverse TMEM and TEX precursor states in specific developmental orders. Interleukin-2 receptor (IL-2R) signals are essential for formation and transcriptional heterogeneity of EMP cells, and promote trajectories toward TEFF rather than TEX states. Nucleosome remodelers Smarca4 and Chd7 differentially promote transcription that delineates divergent TMEM lineages before cooperatively driving terminal TEFF cell differentiation. Thus, the lineage architecture is established by specific chromatin regulators that stabilize diverging transcription in uncommitted progenitors.

immunology↗

bioRxiv2020

Delineation of a molecularly distinct terminally differentiated memory CD8 T cell population

Memory CD8 T cells provide durable protection against diverse intracellular pathogens and can be broadly segregated into distinct circulating and tissue-resident populations. Paradigmatic studies have demonstrated circulating memory cells can be further divided into effector memory (TO_SCPLOWEMC_SCPLOW) and central memory (TO_SCPLOWCMC_SCPLOW) populations based on discrete functional characteristics. Following resolution of infection, we identified a persisting antigen-specific CD8 T cell population that was simultaneously terminally-fated with potent effector function but maintained memory T cell qualities and conferred robust protection against reinfection. Notably, this terminally-differentiated effector memory CD8 T cell population (terminal-TO_SCPLOWEMC_SCPLOW) was conflated within the conventional TO_SCPLOWEMC_SCPLOW population, prompting redefinition of the classical characteristics of TO_SCPLOWEMC_SCPLOW cells. Murine terminal-TO_SCPLOWEMC_SCPLOW were transcriptionally, functionally, and developmentally unique compared to TO_SCPLOWEMC_SCPLOW cells. Through mass cytometry and single-cell RNAseq analyses of human peripheral blood from healthy individuals, we also identified an analogous terminal-TO_SCPLOWEMC_SCPLOW population of CD8 T cells that was transcriptionally distinct from TO_SCPLOWEMC_SCPLOW and TO_SCPLOWCMC_SCPLOW. A key finding of this study was that parsing of terminal-TO_SCPLOWEMC_SCPLOW from conventionally defined TO_SCPLOWEMC_SCPLOW challenges classical characteristics of TO_SCPLOWEMC_SCPLOW biology, including enhanced presence in lymphoid tissues, robust IL-2 production and recall potential, greater than expected homeostatic fitness, refined transcription factor dependencies, and a distinct molecular phenotype. Classification of terminal-TO_SCPLOWEMC_SCPLOW and clarification of TO_SCPLOWEMC_SCPLOW biology hold broad implications for understanding the molecular regulation of memory cell states and harnessing immunological memory to improve immunotherapies.

immunology↗

bioRxiv2020

Molecular determinants and heterogeneity of tissue-resident memory CD8+ T lymphocytes revealed by single-cell RNA sequencing

During an immune response to microbial infection, CD8+ T cells give rise to distinct classes of cellular progeny that coordinately mediate clearance of the pathogen and provide long-lasting protection against reinfection, including a subset of non-circulating tissue-resident memory (TRM) cells that mediate potent protection within non-lymphoid tissues. Here, we utilized single-cell RNA-sequencing to examine the gene expression patterns of individual CD8+ T cells in the spleen and small intestine intraepithelial lymphocyte (siIEL) compartment throughout the course of their differentiation in response to viral infection. These analyses revealed previously unknown transcriptional heterogeneity within the siIEL CD8+ T cell population at several states of differentiation, representing functionally distinct TRM cell subsets as well as a subset of TRM cell precursors within the tissue early in infection. Taken together, these findings may inform strategies to optimize CD8+ T cell responses to protect against microbial infection and cancer. One sentence summaryHere, we applied single-cell RNA-sequencing to elucidate the gene expression patterns of individual CD8+ T cells differentiating throughout the course of infection in the spleen and small intestinal epithelium, which revealed previously unidentified molecular determinants of tissue-resident T cell differentiation as well as functional heterogeneity within the tissue-resident CD8+ T cell population.

immunology↗