Biology subjects

Atwood, S.

Publications and source records attributed to Atwood, S..

9 recordsLinked to original sources

bioRxiv2026

Robust identification of cell-cell communication heterogeneity in single cells

Communication between cells modulates cell fate decisions by relaying information across tissues and inducing intracellular responses mediated by gene regulatory networks. Inference of cell-cell communication from high throughput data such as single cell transcriptomics is gaining popularity due to the high data availability and ease to automate modeling over hundreds of signaling pathways. Studying how cell-cell communication operates across biological scales and influences cell fate decisions, however, remain a major open question. Here, we present scRICH, a framework and package that integrates mechanism-based, multiscale mathematical modeling with learning strategies to capture the complexity of cell-cell communication from single-cell and spatial transcriptomics data. scRICH unravels the heterogeneity of communication behavior within cell types, links cell-cell communication to cell fate decisions by incorporating dynamical information of RNA splicing, and connects the scales of cell-cell interactions and intracellular response by constructing multilayer regulatory networks. We validate scRICH with new experiments on EGF ligand/receptor co-expression in keratinocytes from skin-equivalent organoid, and compare these computational predictions against existing CCC inference methods. Applying scRICH to multiple biological scenarios demonstrate its ability to capture emerging relations between distinct cell-cell communication pathways, interactions at the onset of cell fate decision, and emerging trends in cell-cell communications along cell lineages and in space.

bioinformatics↗

bioRxiv2025

Enhanced Differentiation Potential of Pigmented Human Epidermal Equivalents

Melanocyte-keratinocyte interactions are vital for regulating melanogenesis and maintaining epidermal homeostasis. However, most 3D human skin equivalents lack melanocytes, limiting their relevance for pigmentation studies. To address this, we utilized a pigmented human epidermal equivalent (PmtHEE) that incorporates melanocytes into the epidermis. Using single-cell RNA sequencing (scRNA-seq), we characterized PmtHEE and compared it with neonatal foreskin epidermis (FsEpi) and a fibroblast-containing human skin equivalent model (FibHSE). PmtHEE showed a higher proportion of differentiated cells and model-specific cell state transition paths that reflect in vivo trajectories. We further uncovered a shared L1CAM-EZR-driven external signaling network using exSigNet in FsEpi and PmtHEE that mediates melanocyte-to-keratinocyte communication and supports epidermal differentiation. Altogether, PmtHEE provides a distinct and physiologically relevant model of pigmented skin, with enhanced differentiation potential compared to conventional in vitro systems.

cell biology↗

bioRxiv2024

Statistically principled feature selection for single cell transcriptomics

The high dimensionality of data in single cell transcriptomics (scRNAseq) requires investigators to choose subsets of genes (feature selection) for downstream analysis (e.g., unsupervised cell clustering). The evaluation of different approaches to feature selection is hampered by the fact that, as we show here, the performance of feature selection methods varies greatly with the task being performed. For routine cell type identification, even randomly chosen features can perform well, but for cell type differences that are subtle, both number of features and selection strategy can matter strongly. Here we present a simple feature selection method grounded in an analytical model that, without resorting to arbitrary thresholds or user-defined parameters, allows for interpretable delineation of both how many and which features to choose, facilitating identification of biologically meaningful rare cell types. We compare this method to default methods in scanpy and Seurat, as well as SCTransform, showing how greater accuracy can often be achieved with surprisingly few, well-chosen features.

bioinformatics↗

bioRxiv2024

ESPRESSO: Spatiotemporal omics based on organelle phenotyping

Omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, have been instrumental to improving our understanding of complex biological systems. Despite fast-pace advancements, a crucial dimension is still left to explore: time. To capture this key parameter, we introduce ESPRESSO (Environmental Sensor Phenotyping RElayed by Subcellular Structures and Organelles), a pioneering technique that provides high-dimensional phenotyping resolved in space and time. Through a novel paradigm, ESPRESSO combines fluorescent labeling, advanced microscopy and bioimage and data analysis to extract morphological and functional information of the organelle network unveiling phenotypic changes over time at the single-cell level. In this work, we present ESPRESSOs methodology and its application across numerous cellular systems, showcasing its ability to discern cell types, stress response, differentiation and immune cells polarization. We then correlate ESPRESSO phenotypic changes with gene expression and demonstrate its applicability to 3D cultures, offering a path to revolutionizing biological exploration, providing invaluable insights into cellular states in both space and time.

bioengineering↗

bioRxiv2023

Leveraging gene correlations in single cell transcriptomic data

BACKGROUNDMany approaches have been developed to overcome technical noise in single cell RNA-sequencing (scRNAseq). As researchers dig deeper into data--looking for rare cell types, subtleties of cell states, and details of gene regulatory networks--there is a growing need for algorithms with controllable accuracy and fewer ad hoc parameters and thresholds. Impeding this goal is the fact that an appropriate null distribution for scRNAseq cannot simply be extracted from data when ground truth about biological variation is unknown (i.e., usually). RESULTSWe approach this problem analytically, assuming that scRNAseq data reflect only cell heterogeneity (what we seek to characterize), transcriptional noise (temporal fluctuations randomly distributed across cells), and sampling error (i.e., Poisson noise). We analyze scRNAseq data without normalization--a step that skews distributions, particularly for sparse data--and calculate p-values associated with key statistics. We develop an improved method for selecting features for cell clustering and identifying gene-gene correlations, both positive and negative. Using simulated data, we show that this method, which we call BigSur (Basic Informatics and Gene Statistics from Unnormalized Reads), captures even weak yet significant correlation structures in scRNAseq data. Applying BigSur to data from a clonal human melanoma cell line, we identify thousands of correlations that, when clustered without supervision into gene communities, align with known cellular components and biological processes, and highlight potentially novel cell biological relationships. CONCLUSIONSNew insights into functionally relevant gene regulatory networks can be obtained using a statistically grounded approach to the identification of gene-gene correlations.

systems biology↗

bioRxiv2022

Single cell transcriptomics of human skin equivalent organoids

Several methods for generating human skin equivalent (HSE) organoid cultures are regularly used to study skin biology and test pharmaceuticals, however few studies have thoroughly characterized these systems. To fill this gap, we used single cell-RNA sequencing to compare the cellular states of in vitro HSEs generated from distinct culture methods, HSEs xenografted onto mice, and in vivo epidermis. By combining differential gene expression, pseudotime analyses, splicing kinetics, and spatial localization, we reconstructed HSE keratinocyte differentiation trajectories that recapitulated known in vivo epidermal differentiation pathways and show that HSEs contain many of the major in vivo cellular states. However, HSEs also develop several unique keratinocyte states, an expanded basal stem cell program, and disrupted terminal differentiation. In addition, cell-cell communication modeling showed the presence of EMT-associated signaling pathways not normally active in homeostatic skin and we show that EGF supplementation influences the EMT signature. Lastly, xenografted HSEs at early timepoints post-transplantation significantly rescued many of the observed in vitro deficits, while undergoing a hypoxic response that drove an alternative differentiation lineage. This study highlights the strengths and limitations of organoid cultures and identifies areas for potential innovation.

systems biology↗

bioRxiv2020

Divergent resistance mechanisms to immunotherapy explains response in different skin cancers.

The advent of immune checkpoint therapy for metastatic skin cancer has greatly improved patient survival. However, most skin cancer patients are refractory to checkpoint therapy, and furthermore the differential intra-immune signaling between cancers driving the response to checkpoint therapy remains uncharacterized. When comparing the immune transcriptome in the tumor microenvironment of melanoma and basal cell carcinoma (BCC), we found that the presence of memory B cells and macrophages negatively correlate when stratifying patients by response, with memory B cells more present in responders. Inhibitory immune signaling is reduced in melanoma responders and is increased in BCC responders. We further explored the relationships between macrophages, B cells and response to checkpoint therapy by developing a stochastic differential equation model which qualitatively agrees with the data analysis. Our model predicts BCC to be more refractory to checkpoint therapy than melanoma. We show differences in tumor progression and regression that could serve as a diagnostic and predict the optimal ratio of macrophages and memory B cells for successful treatment.

cancer biology↗

bioRxiv2020

Acoustic regularities in infant-directed vocalizations across cultures

The forms of many species vocal signals are shaped by their functions1-15. In humans, a salient context of vocal signaling is infant care, as human infants are altricial16, 17. Humans often alter their vocalizations to produce "parentese", speech and song produced for infants that differ acoustically from ordinary speech and song18-35 in fashions that have been proposed to support parent-infant communication and infant language learning36-39; modulate infant affect33, 40-45; and/or coordinate communicative interactions with infants46-48. These theories predict a form-function link in infant-directed vocalizations, with consistent acoustic differences between infant-directed and adult-directed vocalizations across cultures. Some evidence supports this prediction23, 27, 28, 32, 49-52, but the limited generalizability of individual ethnographic reports and laboratory experiments53 and small stimulus sets54, along with intriguing reports of counterexamples55-62, leave the question open. Here, we show that people alter the acoustic forms of their vocalizations in a consistent fashion across cultures when speaking or singing to infants. We collected 1,615 recordings of infant- and adult-directed singing and speech produced by 410 people living in 21 urban, rural, and small-scale societies, and analyzed their acoustic forms. We found cross-culturally robust regularities in the acoustics of infant-directed vocalizations, such that infant-directed speech and song were reliably classified from acoustic features found across the 21 societies studied. The acoustic profiles of infant-directedness differed across language and music, but in a consistent fashion worldwide. In a secondary analysis, we studied whether listeners are sensitive to these acoustic features, playing the recordings to 51,065 people recruited online, from many countries, who guessed whether each vocalization was infant-directed. Their intuitions were largely accurate, predictable in part by acoustic features of the recordings, and robust to the effects of linguistic relatedness between vocalizer and listener. By uniting rich cross-cultural data with computational methods, we show links between the production of vocalizations and cross-species principles of bioacoustics, informing hypotheses of the psychological functions and evolution of human communication.

animal behavior and cognition↗

bioRxiv2017

Catching up to a fast-moving target: Evaluation of a health system strengthening intervention in rural Rwanda 2005-2010 using data from repeated cross-sectional surveys

IntroductionAlthough Rwandas health system underwent major reforms and improvements after the 1994 Genocide, the health system and population health in the southeast lagged behind other areas. In 2005 Partners In Health and the Rwandan Ministry of Health began a health system strengthening intervention in this region.\n\nMethodsCombining results from the 2005 and 2010 Demographic and Health Surveys with those from a supplemental 2010 survey, we compared changes in health system output indicators and population health outcomes between 2005 and 2010 as reported by 21,338 women living in the intervention area and similar rural areas, controlling for potential confounding by economic and demographic variables.\n\nResultsOverall health system coverage improved similarly in both regions between 2005 and 2010, with an indicator of composite coverage of child health interventions increasing from 57.9% to 75.0% in the intervention area and from 58.7% to 73.8% in other rural areas. Despite experiencing poorer health outcomes in 2005, the intervention area caught up to or exceeded other rural areas on 23 of 25 indicators. Most notably, under-five mortality declined by an annual rate of 12.8% in the intervention area, from 229.8 to 83.2 deaths per 1000 live births, and by 8.9% in other rural areas, from 157.7 to 75.8 deaths per 1000 live births. Improvements were most dramatic among the poorest households.\n\nConclusionWe observed dramatic improvements in population health outcomes including under-five mortality between 2005 and 2010 in rural Rwanda generally, and in the intervention area specifically.\n\nSUMMARY BOXO_ST_ABSWhat is already known about this topic?C_ST_ABSO_LIMuch of the evidence that health system strengthening in rural Africa has improved health outcomes comes from studies of targeted regional interventions such as performance based financing or community health worker programs, rather than integrated interventions that encompass multiple components including infrastructure and supply chain investments, health management information system, workforce training and incentives at all levels, community health workers, and free services for poor patients.\nC_LIO_LIIn addition to these experimental or quasi-experimental studies, a series of case studies have documented individual nations, pathways to achieving millennium development goal 4 target, the reduction of under-five mortality by two thirds between 1990 and 2015.\nC_LIO_LIThese reports suggest that improvements in coverage of reproductive, maternal and child health indicators explain some, but not all, of the decline in child mortality and that these successes occurred in the context of national gains in health, nutrition and food security, sanitation, poverty reduction, and access to clean water.\nC_LI\n\nWhat are the new findings?O_LICoverage of most maternal and child health care interventions improved at a similar pace in our rural intervention area and other rural areas.\nC_LIO_LIDespite experiencing poorer health outcomes in 2005, our rural intervention area caught up to or exceeded other rural areas on 23 of 25 population health indicators by 2010.\nC_LIO_LIInfant and under-5 mortality declined in our rural intervention area even more precipitously than in other rural areas of Rwanda between 2005 and 2010.\nC_LI\n\nHow might this influence practice?O_LIThe process of strengthening national health systems often involves trade-offs between a focus on first testing individual programs that distributed widely, as is often practiced by pilot programs with multilateral institutions, or implementing multiple simultaneous programs locally. Our results show that integrated health system strengthening interventions can be locally adapted to enable the rapid expansion of health care coverage as well as dramatic improvements in population health outcomes.\nC_LIO_LIIntegrated multi-level interventions can also help narrow the health care coverage and outcome gap between richer and poorer members of a society.\nC_LIO_LINational governments can leverage nongovernmental partners to achieve the health related sustainable development goals through joint implementation of national health policy.\nC_LI

epidemiology↗