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Biology subjects

MacLean, A. L.

Publications and source records attributed to MacLean, A. L..

22 records · Page 2Linked to original sources

Defining epidermal basal cell states during skin homeostasis and wound healing using single-cell transcriptomics

Our knowledge of transcriptional heterogeneities in epithelial stem/progenitor cell compartments is limited. Epidermal basal cells sustain cutaneous tissue maintenance and drive wound healing. Previous studies have probed basal cell heterogeneity in stem/progenitor potential, but a non-biased dissection of basal cell dynamics during differentiation is lacking. Using single-cell RNA-sequencing coupled with RNAScope and fluorescence lifetime imaging, we identify three non-proliferative and one proliferative basal cell transcriptional states in homeostatic skin that differ in metabolic preference and become spatially partitioned during wound re-epithelialization. Pseudotemporal trajectory and RNA velocity analyses produce a quasi-linear differentiation hierarchy where basal cells progress from Col17a1high/Trp63high state to early response state, proliferate at the juncture of these two states, or become growth arrested before differentiating into spinous cells. Wound healing induces plasticity manifested by dynamic basal-spinous interconversions at multiple basal states. Our study provides a systematic view of epidermal cellular dynamics supporting a revised \"hierarchical-lineage\" model of homeostasis.

developmental biology↗

Single cell transcriptomics of human epidermis reveals basal stem cell transition states

How stem cells give rise to human interfollicular epidermis is unclear despite the crucial role the epidermis plays in barrier and appendage formation. Here we use single cell-RNA sequencing to interrogate basal stem cell heterogeneity of human interfollicular epidermis and find at least four spatially distinct stem cell populations that decorate the top and bottom of rete ridge architecture and hold transitional positions between the basal and suprabasal epidermal layers. Cell-cell communication modeling through co-variance of cognate ligand-receptor pairs indicate that the basal cell populations distinctly serve as critical signaling hubs that maintain epidermal communication. Combining pseudotime, RNA velocity, and cellular entropy analyses point to a hierarchical differentiation lineage supporting multi-stem cell interfollicular epidermal homeostasis models and suggest the \"transitional\" basal stem cells are stable states essential for proper stratification. Finally, alterations in differentially expressed \"transitional\" basal stem cell genes result in severe thinning of human skin equivalents, validating their essential role in epidermal homeostasis and reinforcing the critical nature of basal stem cell heterogeneity.

systems biology↗

Modeling the competing effects of the immune system and EMT on tumor development

During progression from carcinoma in situ to an invasive tumor, the immune system is engaged in complex sets of interactions with various tumor cells. Tumor cell plasticity also alters disease trajectories via epithelial-to-mesenchymal transition (EMT). Several of the same pathways that regulate EMT are involved in tumor-immune interactions, yet little is known about the mechanisms and consequences of crosstalk between these regulatory processes. Here we introduce a multiscale evolutionary model to describe tumor-immune-EMT interactions and their impact on epithelial cancer progression from in situ to invasive disease. Through in silico analyses of large patient cohorts, we find controllable regions that maximize invasion-free survival. We identify that delaying tumor progression depends crucially on properties of the mesenchymal tumor cell phenotype: its growth rate and its immune-evasiveness. Through analysis of EMT-inflammation-associated data from The Cancer Genome Atlas, we find that association with EMT significantly worsens invasion-free survival probabilities in support of our model, and we predict new genes influencing outcomes in bladder and uterine cancer, including FGF pathway members. These results offer novel means to delay disease progression by regulating properties of EMT through specific gene interactions, and demonstrate the importance of studying cancer-immune interactions in light of EMT.

systems biology↗

Bayesian inference of agent-based models: a tool for studying kidney branching morphogenesis

The adult mammalian kidney has a complex, highly-branched collecting duct epithelium that arises as a ureteric bud sidebranch from an epithelial tube known as the nephric duct. Subsequent branching of the ureteric bud to form the collecting duct tree is regulated by subcellular interactions between the epithelium and a population of mesenchymal cells that surround the tips of outgrowing branches. The mesenchymal cells produce glial cell-line derived neurotrophic factor (GDNF), that binds with RET receptors on the surface of the epithelial cells to stimulate several subcellular pathways in the epithelium. Such interactions are known to be a prerequisite for normal branching development, although competing theories exist for their role in morphogenesis. Here we introduce the first agent-based model of ex vivo kidney uretic branching. Through comparison with experimental data, we show that growth factor-regulated growth mechanisms can explain early epithelial cell branching, but only if epithelial cell division depends in a switch-like way on the local growth factor concentration; cell division occurring only if the driving growth factor level exceeds a threshold. We also show how a recently-developed method, \"Approximate Approximate Bayesian Computation\", can be used to infer key model parameters, and reveal the dependency between the parameters controlling a growth factor-dependent growth switch. These results are consistent with a requirement for signals controlling proliferation and chemotaxis, both of which are previously identified roles for GDNF.\n\nAuthor SummaryA number of important congenital disorders arise due to incomplete development of the mammalian kidney. Elucidating the cause of these conditions requires an understanding of the mechanisms that contribute to kidney morphogenesis. Whilst experimental work has suggested several candidate mechanisms, their importance is still not well understood. Here we develop a computational model of kidney morphogenesis at the individual cell level to compare these different hypotheses. Guided by existing experimental evidence we propose that a generic growth factor, that we term \"GDNF\", produced from the mesenchyme surrounding the epithelium, can drive a number of cellular responses. Simulations of our agent-based model reveal that diffusion of GDNF, coupled with GDNF-stimulated epithelial cell division, can generate the branching patterns seen in ex vivo kidney explant experiments. We also find that branching depends on the sensitivity of cell proliferation to changes in GDNF levels. In particular our model only generates realistic branching when there is significant variation in GDNF levels along the boundary of the epithelium, and most cells divide only if the local concentration of GDNF exceeds a threshold value. We conclude that feedback between mesenchymal cells that produce GDNF, and epithelial cells that consume it, is vital for normal kidney organogenesis.

developmental biology↗