Biology subjects

Mead, B. E.

Publications and source records attributed to Mead, B. E..

5 recordsLinked to original sources

bioRxiv2023

Chronic metabolic stress drives developmental programs and loss of tissue functions in non-transformed liver that mirror tumor states and stratify survival

Under chronic stress, cells must balance competing demands between cellular survival and tissue function. In metabolic dysfunction-associated steatotic liver disease (MASLD, formerly NAFLD/NASH), hepatocytes cooperate with structural and immune cells to perform crucial metabolic, synthetic, and detoxification functions despite nutrient imbalances. While prior work has emphasized stress-induced drivers of cell death, the dynamic adaptations of surviving cells and their functional repercussions remain unclear. Namely, we do not know which pathways and programs define cellular responses, what regulatory factors mediate (mal)adaptations, and how this aberrant activity connects to tissue-scale dysfunction and long-term disease outcomes. Here, by applying longitudinal single-cell multi-omics to a mouse model of chronic metabolic stress and extending to human cohorts, we show that stress drives survival-linked tradeoffs and metabolic rewiring, manifesting as shifts towards development-associated states in non-transformed hepatocytes with accompanying decreases in their professional functionality. Diet-induced adaptations occur significantly prior to tumorigenesis but parallel tumorigenesis-induced phenotypes and predict worsened human cancer survival. Through the development of a multi-omic computational gene regulatory inference framework and human in vitro and mouse in vivo genetic perturbations, we validate transcriptional (RELB, SOX4) and metabolic (HMGCS2) mediators that co-regulate and couple the balance between developmental state and hepatocyte functional identity programming. Our work defines cellular features of liver adaptation to chronic stress as well as their links to long-term disease outcomes and cancer hallmarks, unifying diverse axes of cellular dysfunction around core causal mechanisms.

systems biology↗

bioRxiv2023

Compressed phenotypic screens for complex multicellular models and high-content assays

High-throughput phenotypic screens leveraging biochemical perturbations, high-content readouts, and complex multicellular models could advance therapeutic discovery yet remain constrained by limitations of scale. To address this, we establish a method for compressing screens by pooling perturbations followed by computational deconvolution. Conducting controlled benchmarks with a highly bioactive small molecule library and a high-content imaging readout, we demonstrate increased efficiency for compressed experimental designs compared to conventional approaches. To prove generalizability, we apply compressed screening to examine transcriptional responses of patient-derived pancreatic cancer organoids to a library of tumor-microenvironment (TME)-nominated recombinant protein ligands. Using single-cell RNA-seq as a readout, we uncover reproducible phenotypic shifts induced by ligands that correlate with clinical features in larger datasets and are distinct from reference signatures available in public databases. In sum, our approach enables phenotypic screens that interrogate complex multicellular models with rich phenotypic readouts to advance translatable drug discovery as well as basic biology.

systems biology↗

bioRxiv2021

Cellular and transcriptional diversity over the course of human lactation

Human breast milk is a dynamic fluid that contains millions of cells, but their identities and phenotypic properties are poorly understood. We used single-cell RNA-seq (scRNA-seq) to characterize the transcriptomes of cells from human breast milk (hBM) across lactational time from 3 to 632 days postpartum in 15 donors. We find that the majority of cells in human breast milk are lactocytes, a specialized epithelial subset, and cell type frequencies shift over the course of lactation yielding greater epithelial diversity at later points. Analysis of lactocytes reveals a continuum of cell states characterized by transcriptional changes in hormone, growth factor, and milk production related pathways. Generalized additive models suggest that one sub-cluster, LALBAlow epithelial cells, increase as a function of time postpartum, daycare attendance, and the use of hormonal birth control. We identify several sub-clusters of macrophages in hBM that are enriched for tolerogenic functions, possibly playing a role in protecting the mammary gland during lactation. Our description of the cellular components of breast milk, their association with maternal-infant dyad metadata and quantification of alterations at the gene and pathways levels provides the first detailed longitudinal picture of human breast milk cells across lactational time. This work paves the way for future investigations of how a potential division of cellular labor and differential hormone regulation might be leveraged therapeutically to support healthy lactation and potentially aid in milk production.

genomics↗

bioRxiv2020

High-throughput organoid screening enables engineering of intestinal epithelial composition

Barrier tissue epithelia play an essential role in maintaining organismal homeostasis, and changes in their cellular composition have been observed in multiple human diseases. Within the small intestinal epithelium, adult stem cells integrate diverse signals to regulate regeneration and differentiation, thereby establishing overall cellularity. Accordingly, directing stem cell differentiation could provide a tractable approach to alter the abundance or quality of specialized cells of the small intestinal epithelium, including the secretory Paneth, goblet, and enteroendocrine populations. Yet, to date, there has been a lack of suitable tools and rigorous approaches to identify biological targets and pharmacological agents that can modify epithelial composition to enable causal testing of disease-associated changes with novel therapeutic candidates. To empower the search for epithelia-modifying agents, we establish a first-of-its-kind high-throughput phenotypic organoid screen. We demonstrate the ability to screen thousands of samples and uncover biological targets and associated small molecule inhibitors which translate to in vivo. This approach is enabled by employing a functional, cell-type specific, scalable assay on an organoid model designed to represent the physiological cues of in vivo Paneth cell differentiation from adult intestinal stem cells. Further, we miniaturize and adapt the organoid culture system to enable automated plating and screening, thereby providing the ability to test thousands of samples. Strikingly, in our screen we identify inhibitors of the nuclear exporter Xpo1 modulate stem cell fate commitment by inducing a pan-epithelial stress response combined with an interruption of mitogen signaling in cycling intestinal progenitors, thereby significantly increasing the abundance of Paneth cells independent of known WNT and Notch differentiation cues. We extend our observation in vivo, demonstrating that oral administration of Xpo1 inhibitor KPT-330 at doses 1,000-fold lower than conventionally used in hematologic malignancies increases Paneth cell abundance. In total, we provide a framework to identify novel biological cues and therapeutic leads to rebalance intestinal stem cell differentiation and modulate epithelial tissue composition via high-throughput phenotypic screening in rationally-designed organoid model of differentiation.

bioengineering↗

bioRxiv2020

Spatially-Resolved Live Cell Tagging and Isolation Using Protected Photoactivatable Cell Dyes

Whether cultured in vitro or part of a complex tissue in vivo, a cells phenotype and function are significantly influenced by dynamic interactions with its microenvironment. To explicitly examine how a cells spatiotemporal activity impacts its behavior, we developed and validated a strategy termed SPACECAT--Spatially PhotoActivatable Color Encoded Cell Address Tags--to annotate, track, and isolate specific cells in a non-destructive, viability-preserving manner. In SPACECAT, a biological sample is immersed in a photocaged fluorescent molecule, and cells within a location of interest are labeled for further study by uncaging that molecule with user-patterned near-UV light. SPACECAT offers high spatial precision and temporal stability across diverse cell and tissue types, and is compatible with common downstream assays, including flow cytometry and single-cell RNA-Seq. Illustratively, we leveraged this approach in patient-derived intestinal organoids, a spatially complex system less amenable to genetic manipulations, to select for crypt-like regions enriched in stem-like and actively mitotic cells. Moreover, we demonstrate its applicability and utility on ex vivo tissue sections from four healthy organs and an autochthonous lung tumor model, uncovering spatially-biased gene expression patterns among immune cell subsets and identifying rare myeloid phenotypes enriched around tumor/healthy border regions. In sum, our method provides a minimally invasive and broadly applicable approach to link cellular spatiotemporal features and/or behavioral phenotypes with diverse downstream assays, enabling fundamental insights into the connections between tissue microenvironments and biological (dys)function.

systems biology↗