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Cell–cell communication governs the biological behaviors of multicellular populations such as developmental and immunological systems. Thanks to intense genetic analytical studies, the molecular components of cell–cell communication pathways have been well identified. We also have been developing synthetic biology tools to control cellular sensing and response systems that enable engineering of new cell–cell communication with design-based regulatory features. Recently, using these molecular backgrounds, synthetic cellular networks have been built and tested to understand the basic principles of multicellular biological behaviors. These approaches will provide new capabilities to control and program desired biological behaviors with engineered cell–cell communication to apply them toward cell-based therapeutics. [ABSTRACT FROM AUTHOR]

Living cells detect and process external signals using signaling pathways that are affected by random fluctuations. These variations cause the behavior of individual cells to fluctuate over time (behavioral variability) and generate phenotypic differences between genetically identical individuals (phenotypic diversity). These two noise sources reduce our ability to predict biological behavior because they diversify cellular responses to identical signals. Here, we review recent experimental and theoretical advances in understanding the mechanistic origin and functional consequences of such variation in Escherichia coli chemotaxis-a well-understood model of signal transduction and behavior. After briefly summarizing the architecture and logic of the chemotaxis system, we discuss determinants of behavior and chemotactic performance of individual cells. Then, we review how cell-to-cell differences in protein abundance map onto differences in individual chemotactic abilities and how phenotypic variability affects the performance of the population. We conclude with open questions to be addressed by future research. [ABSTRACT FROM AUTHOR]

Biological functions are typically performed by groups of cells that express predominantly the same genes, yet display a continuum of phenotypes. While it is known how one genotype can generate such non-genetic diversity, it remains unclear how different phenotypes contribute to the performance of biological function at the population level. We developed a microfluidic device to simultaneously measure the phenotype and chemotactic performance of tens of thousands of individual, freely swimming Escherichia coli as they climbed a gradient of attractant. We discovered that spatial structure spontaneously emerged from initially well-mixed wild-type populations due to non-genetic diversity. By manipulating the expression of key chemotaxis proteins, we established a causal relationship between protein expression, non-genetic diversity, and performance that was theoretically predicted. This approach generated a complete phenotype-to-performance map, in which we found a nonlinear regime. We used this map to demonstrate how changing the shape of a phenotypic distribution can have as large of an effect on collective performance as changing the mean phenotype, suggesting that selection could act on both during the process of adaptation. [ABSTRACT FROM AUTHOR]

The article presents a study which engineer therapeutic T cells bearing synthetic cytokine circuits in which a tumor-specific synthetic Notch (synNotch) receptor drives IL-2 production. It mentions that tumor-targeted IL-2 delivery circuits offer a potential way to locally overcome tumor suppression while minimizing systemic IL-2 toxicity.

Many processes controlling cell growth and death are well characterized for individual cell lineages, but how ensembles of different cell types in a tissue regulate collective size and composition remains unclear. In this issue of Cell , Zhou et al. employ experiments and theory to uncover design principles of tissue homeostasis arising from cross-talk between fibroblasts and macrophages. [ABSTRACT FROM AUTHOR]

A correction is presented to the article "Non-genetic diversity modulates population performance" which was published in the perodical.

Understanding how stochastic molecular fluctuations affect cell behavior requires the quantification of both behavior and protein numbers in the same cells. Here, we combine automated microscopy with in situ hydrogel polymerization to measure single-cell protein expression after tracking swimming behavior. We characterized the distribution of non-genetic phenotypic diversity in Escherichia coli motility, which affects single-cell exploration. By expressing fluorescently tagged chemotaxis proteins (CheR and CheB) at different levels, we quantitatively mapped motile phenotype (tumble bias) to protein numbers using thousands of single-cell measurements. Our results disagreed with established models until we incorporated the role of CheB in receptor deamidation and the slow fluctuations in receptor methylation. Beyond refining models, our central finding is that changes in numbers of CheR and CheB affect the population mean tumble bias and its variance independently. Therefore, it is possible to adjust the degree of phenotypic diversity of a population by adjusting the global level of expression of CheR and CheB while keeping their ratio constant, which, as shown in previous studies, confers functional robustness to the system. Since genetic control of protein expression is heritable, our results suggest that non-genetic diversity in motile behavior is selectable, supporting earlier hypotheses that such diversity confers a selective advantage. [ABSTRACT FROM AUTHOR]