The advent of stem cell based therapies has brought regenerative medicine into an increased focus as a part of the modern medicine practice, with a potential to treat a myriad of intractable diseases in the future. Stem cells reside in a complex microenvironment presenting them with a multitude of potential cues that are chemical, physical, and mechanical in nature. Conventional techniques used for experiments involving stem cells can only poorly mimic the physiological context, and suffer from imprecise spatial and temporal control, low throughput, lack of scalability and reproducibility, and poor representation of the mechanical and physical cell microenvironment. Novel lab-on-a-chip platforms, on the other hand, can much better mimic the complexity of in vivo tissue milieu and provide a greater control of the parameter variation in a high throughput and scalable manner. This capability may be especially important for understanding the biology and cementing the clinical potential of stem cell based therapies. Here we review microfabrication- and microfluidics-based approaches to investigating the complex biology of stem cell responses to changes in the local microenvironment. In particular, we categorize each method based on the types of controlled inputs it can have on stem cells, including soluble biochemical factors, extracellular matrix interactions, homotypic and heterotypic cell-cell signaling, physical cues (e.g. oxygen tension, pH, temperature), and mechanical forces (e.g. shear, topography, rigidity). Finally, we outline the methods to perform large scale observations of stem cell phenotypes and high-throughput screening of cellular responses to a combination of stimuli, and many new emerging technologies that are becoming available specifically for stem cell applications.

Collective cell responses to exogenous cues depend on cell-cell interactions. In principle, these can result in enhanced sensitivity to weak and noisy stimuli. However, this has not yet been shown experimentally, and, little is known about how multicellular signal processing modulates single cell sensitivity to extracellular signaling inputs, including those guiding complex changes in the tissue form and function. Here we explored if cell-cell communication can enhance the ability of cell ensembles to sense and respond to weak gradients of chemotactic cues. Using a combination of experiments with mammary epithelial cells and mathematical modeling, we find that multicellular sensing enables detection of and response to shallow Epidermal Growth Factor (EGF) gradients that are undetectable by single cells. However, the advantage of this type of gradient sensing is limited by the noisiness of the signaling relay, necessary to integrate spatially distributed ligand concentration information. We calculate the fundamental sensory limits imposed by this communication noise and combine them with the experimental data to estimate the effective size of multicellular sensory groups involved in gradient sensing. Functional experiments strongly implicated intercellular communication through gap junctions and calcium release from intracellular stores as mediators of collective gradient sensing. The resulting integrative analysis provides a framework for understanding the advantages and limitations of sensory information processing by relays of chemically coupled cells. Significance StatementWhat new properties may result from collective cell behavior, and how these emerging capabilities may influence shaping and function of tissues, in health and disease? Here, we explored these questions in the context of epithelial branching morphogenesis. We show experimentally that, while individual mammary epithelial cells are incapable of sensing extremely weak gradients of a growth factor, cellular collectives in organotypic cultures exhibit reliable, gradient driven, directional growth. This underscores a critical importance of collective cell-cell communication and computation in gradient sensing. We develop and verify a biophysical theory of such communication, and identify the mechanisms by which it is implemented in the mammary epithelium, quantitatively analyzing both advantages and limitations of biochemical cellular communication in collective decision making.All rights reserved. No reuse allowed without permission.(which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.

Collective cell responses to exogenous cues depend on cell-cell interactions. In principle, these can result in enhanced sensitivity to weak and noisy stimuli. However, this has not yet been shown experimentally, and little is known about how multicellular signal processing modulates single-cell sensitivity to extracellular signaling inputs, including those guiding complex changes in the tissue form and function. Here we explored whether cell-cell communication can enhance the ability of cell ensembles to sense and respond to weak gradients of chemotactic cues. Using a combination of experiments with mammary epithelial cells and mathematical modeling, we find that multicellular sensing enables detection of and response to shallow epidermal growth factor (EGF) gradients that are undetectable by single cells. However, the advantage of this type of gradient sensing is limited by the noisiness of the signaling relay, necessary to integrate spatially distributed ligand concentration information. We calculate the fundamental sensory limits imposed by this communication noise and combine them with the experimental data to estimate the effective size of multicellular sensory groups involved in gradient sensing. Functional experiments strongly implicated intercellular communication through gap junctions and calcium release from intracellular stores as mediators of collective gradient sensing. The resulting integrative analysis provides a framework for understanding the advantages and limitations of sensory information processing by relays of chemically coupled cells. gradient sensing | development | collective cellular phenomena | linear response theory | chemotaxis

No abstract

No abstract

Abstract-The TreeSAAP software has been successfully used in a variety of protein studies for identifying and characterizing adaptation in terms of shifts in the physicochemical properties of amino acid replacements. It differentiates adaptive replacements from those that may have resulted from random mutation. The accuracy of TreeSAAP was tested using simulated protein-coding DNA data that was randomly generated using a bifurcating phylogeny to reflect a random pattern of mutation constrained only by the structure of the genetic code. A sampling of 1402 simulated amino acid replacements resulted in a default accuracy of 80.6%. More than 50% of the false-positive results were traced to just 11 of the possible single-step amino acid exchanges, each of which exhibited less than 50% accuracy. When these 11 exchanges are eliminated from the subsequent analysis, the accuracy of TreeSAAP is increased to nearly 90%. Further testing of this modified approach for adverse implications with empirical data is warranted.

No abstract

Autocrine and paracrine signaling mechanisms are traditionally difficult to study due to the recursive nature of the process and the sub-micromolar concentrations involved. This has proven to be especially limiting in the study of embryonic stem cells that might rely on such signaling for viability, self-renewal, and proliferation. To better characterize possible effects of autocrine and paracrine signaling in the setting of expanding stem cells, we developed a computational model assuming a critical need for cell-secreted survival factors. This model suggested that the precise way in which the removal of putative survival factors could affect stem cell survival in culture. We experimentally tested the predictions in mouse embryonic stem cells by taking advantage of a novel microfluidic device allowing removal of the cell-conditioned medium at defined time intervals. Experimental results in both serum-containing and defined N2B27 media confirmed computational model predictions, suggested existence of unknown survival factors with distinct rates of diffusion, and revealed an adaptive/selective phase in mouse embryonic stem cell response to a lack of paracrine signaling. We suggest that the described computational/experimental platform can be used to identify and study specific factors and pathways involved in a wide variety of paracrine signaling systems.