Minimal Developmental Computation: A Causal Network Approach to Understand Morphogenetic Pattern Formation

What information-processing strategies and general principles are sufficient to enable self-organized morphogenesis in embryogenesis and regeneration? We designed and analyzed a minimal model of self-scaling axial patterning consisting of a cellular network that develops activity patterns within implicitly set bounds. The properties of the cells are determined by internal ‘genetic’ networks with an architecture shared across all cells. We used machine-learning to identify models that enable this virtual mini-embryo to pattern a typical axial gradient while simultaneously sensing the set boundaries within which to develop it from homogeneous conditions—a setting that captures the essence of early embryogenesis. Interestingly, the model revealed several features (such as planar polarity and regenerative re-scaling capacity) for which it was not directly selected, showing how these common biological design principles can emerge as a consequence of simple patterning modes. A novel “causal network” analysis of the best model furthermore revealed that the originally symmetric model dynamically integrates into intercellular causal networks characterized by broken-symmetry, long-range influence and modularity, offering an interpretable macroscale-circuit-based explanation for phenotypic patterning. This work shows how computation could occur in biological development and how machine learning approaches can generate hypotheses and deepen our understanding of how featureless tissues might develop sophisticated patterns—an essential step towards predictive control of morphogenesis in regenerative medicine or synthetic bioengineering contexts. The tools developed here also have the potential to benefit machine learning via new forms of backpropagation and by leveraging the novel distributed self-representation mechanisms to improve robustness and generalization.

Maximization of information transmission influences selection of native phosphorelay architectures

Phosphorelays are signal transduction circuits that sense environmental changes and adjust cellular metabolism. Five different circuit architectures account for 99% of all phosphorelay operons annotated in over 9,000 fully sequenced genomes. Here we asked what biological design principles, if any, could explain selection among those architectures in nature. We began by studying kinetically well characterized phosphorelays (Spo0 of Bacillus subtilis and Sln1 of Saccharomyces cerevisiae). We find that natural circuit architecture maximizes information transmission in both cases. We use mathematical models to compare information transmission among the architectures for a realistic range of concentration and parameter values. Mapping experimentally determined phosphorelay protein concentrations onto that range reveals that the native architecture maximizes information transmission in sixteen out of seventeen analyzed phosphorelays. These results suggest that maximization of information transmission is important in the selection of native phosphorelay architectures, parameter values and protein concentrations.

Thomas Aquinas on Sexual Difference: The Metaphysical Biology and Moral Significance of Human Sexuality

Thomas Aquinas offers for his time a novel take on human sexual difference, in that he grounds human sexuality in what we might term a metaphysical biology and accords it a privileged role in the moral life. Though his biology is drawn from Aristotle, which leads Aquinas to make problematic statements on sexual difference, he nonetheless offers a perspective that remains deeply relevant and significant for today. His method or approach of tethering sexual difference first and foremost to our animal-like biological design remains perennial, particularly at a time when many seek to dismiss biology as irrelevant to sexual identity and gender difference. The latest findings of the emerging field of neurobiology, which have uncovered structural differences between the male and female brains, offer key support to Aquinas’s approach. Even more important, he holds, in an unprecedented move, that sexual design and inclination provide a veritable source of moral excellence. He goes so far as to locate the mean of virtue in our sexual design and appetites.

The Expanding Computational Toolbox for Engineering Microbial Phenotypes at the Genome Scale

Microbial strains are being engineered for an increasingly diverse array of applications, from chemical production to human health. While traditional engineering disciplines are driven by predictive design tools, these tools have been difficult to build for biological design due to the complexity of biological systems and many unknowns of their quantitative behavior. However, due to many recent advances, the gap between design in biology and other engineering fields is closing. In this work, we discuss promising areas of development of computational tools for engineering microbial strains. We define five frontiers of active research: (1) Constraint-based modeling and metabolic network reconstruction, (2) Kinetics and thermodynamic modeling, (3) Protein structure analysis, (4) Genome sequence analysis, and (5) Regulatory network analysis. Experimental and machine learning drivers have enabled these methods to improve by leaps and bounds in both scope and accuracy. Modern strain design projects will require these tools to be comprehensively applied to the entire cell and efficiently integrated within a single workflow. We expect that these frontiers, enabled by the ongoing revolution of big data science, will drive forward more advanced and powerful strain engineering strategies.

Recent Developments in Biomimetic Antifouling Materials: A Review

The term ‘biomimetic’ might be applied to any material or process that in some way reproduces, mimics, or is otherwise inspired by nature. Also variously termed bionic, bioinspired, biological design, or even green design, the idea of adapting or taking inspiration from a natural solution to solve a modern engineering problem has been of scientific interest since it was first proposed in the 1960s. Since then, the concept that natural materials and nature can provide inspiration for incredible breakthroughs and developments in terms of new technologies and entirely new approaches to solving technological problems has become widely accepted. This is very much evident in the fields of materials science, surface science, and coatings. In this review, we survey recent developments (primarily those within the last decade) in biomimetic approaches to antifouling, self-cleaning, or anti-biofilm technologies. We find that this field continues to mature, and emerging novel, biomimetic technologies are present at multiple stages in the development pipeline, with some becoming commercially available. However, we also note that the rate of commercialization of these technologies appears slow compared to the significant research output within the field.