Synthetic biology—putting engineering into biology

Synthetic biology is interpreted as the engineering-driven building of increasingly complex biological entities for novel applications. Encouraged by progress in the design of artificial gene networks, de novo DNA synthesis and protein engineering, we review the case for this emerging discipline. Key aspects of an engineering approach are purpose-orientation, deep insight into the underlying scientific principles, a hierarchy of abstraction including suitable interfaces between and within the levels of the hierarchy, standardization and the separation of design and fabrication. Synthetic biology investigates possibilities to implement these requirements into the process of engineering biological systems. This is illustrated on the DNA level by the implementation of engineering-inspired artificial operations such as toggle switching, oscillating or production of spatial patterns. On the protein level, the functionally self-contained domain structure of a number of proteins suggests possibilities for essentially Lego-like recombination which can be exploited for reprogramming DNA binding domain specificities or signaling pathways. Alternatively, computational design emerges to rationally reprogram enzyme function. Finally, the increasing facility of de novo DNA synthesis—synthetic biology’s system fabrication process—supplies the possibility to implement novel designs for ever more complex systems. Some of these elements have merged to realize the first tangible synthetic biology applications in the area of manufacturing of pharmaceutical compounds.

Rates of agonism among female primates: a cross-taxon perspective

Agonism is common in group-living animals, shaping dominance relationships and ultimately impacting individual tness. Rates of agonism vary considerably among taxa, however, and explaining this variation has been central in ecological models of female social relationships in primates. Early iterations of these models posited a link to diet, with more frequent agonism predicted in frugivorous species due to the presumed greater contestability of fruits relative to other food types. Although some more recent studies have suggested that dietary categories may be poor predictors of contest competition among primates, to date there have been no broad, cross-taxa comparisons of rates of female–female agonism in relation to diet. This study tests whether dietary variables do indeed pre- dict rates of female agonism and further investigates the role of group size (i.e., number of competitors) and substrate use (i.e., degree of arboreality) on the frequency of agonism. Data from 44 wild, unprovisioned groups, including 3 strepsirhine species, 3 platyrrhines, 5 colobines, 10 cercopithecines, and 2 hominoids were analyzed using phylogenetically controlled and uncontrolled methods. Results indicate that diet does not predict agonistic rates, with trends actually being in the opposite direction than predicted for all taxa except cercopithecines. In contrast, agonistic rates are positively associated with group size and possibly degree of terrestriality. Competitor density and perhaps the risk of ghting, thus, appear more important than general diet in predicting agonism among female primates. We discuss the implications of these results for socio-ecological hypotheses

Language and action in Broca’s area: Computational differentiation and cortical segregation

Actions have been proposed to follow hierarchical principles similar to those hypothesized for language syntax. These structural similarities are claimed to be reflected in the common involvement of certain neural populations of Broca’s area, in the Inferior Frontal Gyrus (IFG). In this position paper, we follow an influential hypothesis in linguistic theory to introduce the syntactic operation Merge and the corresponding motor/conceptual interfaces. We argue that actions hierarchies do not follow the same principles ruling language syntax. We propose that hierarchy in the action domain lies in predictive processing mechanisms mapping sensory inputs and statistical regularities of action-goal relationships. At the cortical level, distinct Broca’s subregions appear to support different types of computations across the two domains. We argue that anterior BA44 is a major hub for the implementation of the syntactic operation Merge. On the other hand, posterior BA44 is recruited in selecting premotor mental representations based on the information provided by contextual signals. This functional distinction is corroborated by a recent meta-analysis (Papitto, Friederici, & Zaccarella, 2020). We conclude by suggesting that action and language can meet only where the interfaces transfer abstract computations either to the external world or to the internal mental world

Analysis of Three-Dimensional Protein Images

A fundamental goal of research in molecular biology is to understand protein structure. Protein crystallography is currently the most successful method for determining the three-dimensional (3D) conformation of a protein, yet it remains labor intensive and relies on an expert's ability to derive and evaluate a protein scene model. In this paper, the problem of protein structure determination is formulated as an exercise in scene analysis. A computational methodology is presented in which a 3D image of a protein is segmented into a graph of critical points. Bayesian and certainty factor approaches are described and used to analyze critical point graphs and identify meaningful substructures, such as alpha-helices and beta-sheets. Results of applying the methodologies to protein images at low and medium resolution are reported. The research is related to approaches to representation, segmentation and classification in vision, as well as to top-down approaches to protein structure prediction.Comment: See http://www.jair.org/ for any accompanying file

A Positive Theory of Network Connectivity

This paper develops a positive theory of network connectivity, seeking to explain the micro-foundations of alternative network topologies as the result of self-interested actors. By building roads, landowners hope to increase their parcelsÕ accessibility and economic value. A simulation model is performed on a grid-like land use layer with a downtown in the center, whose structure resembles the early form of many Midwest- ern and Western (US) cities. The topological attributes for the networks are evaluated. This research posits that road networks experience an evolutionary process where a tree-like structure first emerges around the centered parcel before the network pushes outward to the periphery. In addition, road network topology undergoes clear phase changes as the economic values of parcels vary. The results demonstrate that even without a centralized authority, road networks have the property of self-organization and evolution, and, that in the absence of intervention, the tree-like or web-like nature of networks is a result of the underlying economics.road network, land parcel, network evolution, network growth, phase change, centrality measures, degree centrality, closeness centrality, betweenness centrality, network structure, treeness, circuitness, topology

Phylogeny reconciliation under gene tree parsimony

The growing genomic and phylogenetic data sets represent a unique opportunity to analytically and computationally study the relationship among diversifying species. Unfortunately, such data often result in contradictory gene phylogenies due to common yet unobserved evolutionary events, e.g., gene duplication or deep coalescence. Gene tree parsimony (GTP) methods address such issue by reconciling gene phylogenies into one consistent species evolutionary history as well as identifying the underlying events. In this study, we solve not only the GTP problem but also propose a new method to select gene trees in order to assist biologists in gaining insight from phylogenetic analysis. First, we introduce exact solutions for the intrinsically complex GTP problem. Exact solutions for NP-hard problems, like GTP, have a long and extensive history of improvements for classic problems such as traveling salesman and knapsack. Our solutions presented here are designed via integer linear programming (ILP) and dynamic programming (DP), which are techniques widely used in solving problems of similar complexity. We also demonstrate the effectiveness of our solutions through simulation analysis and empirical datasets. To ensure input data coherence for GTP analysis, as a method to strengthen species represented in a gene tree, we introduce the quasi-biclique (QBC) approach to analyze and condense input datasets. In order to take advantage of emerging techniques that further describe the sequence-host and gene-taxon relations, quasi-bicliques are optimized via weighted edge connectivities and distribution of missing information. Our study showed these QBC mining problems are NP-hard. We describe an ILP formulation that is capable of finding optimal QBCs in an effort to support GTP analysis. We also investigate the applicability of QBC to other applications such as mining genetic interaction networks to encouraging results