Designing Spatially Distributed Gene Regulatory Networks To Elicit Contrasting Patterns.

Pattern formation and differential interactions are important for microbial consortia to divide labor and perform complex functions. To obtain further insight into such interactions, we present a computational method for simulating physically separated microbial colonies, each implementing different gene regulatory networks. We validate our theory by experimentally demonstrating control over gene expression patterns in a diffusion-mediated lateral inhibition circuit. We highlight the importance of spatial arrangement as a control knob for modulating system behavior. Our systematic approach provides a foundation for future applications that require understanding and engineering of multistrain microbial communities for sophisticated, synergistic functions.

Evaluation of 244,000 synthetic sequences reveals design principles to optimize translation in Escherichia coli.

Comparative analyses of natural and mutated sequences have been used to probe mechanisms of gene expression, but small sample sizes may produce biased outcomes. We applied an unbiased design-of-experiments approach to disentangle factors suspected to affect translation efficiency in E. coli. We precisely designed 244,000 DNA sequences implementing 56 replicates of a full factorial design to evaluate nucleotide, secondary structure, codon and amino acid properties in combination. For each sequence, we measured reporter transcript abundance and decay, polysome profiles, protein production and growth rates. Associations between designed sequences properties and these consequent phenotypes were dominated by secondary structures and their interactions within transcripts. We confirmed that transcript structure generally limits translation initiation and demonstrated its physiological cost using an epigenetic assay. Codon composition has a sizable impact on translatability, but only in comparatively rare elongation-limited transcripts. We propose a set of design principles to improve translation efficiency that would benefit from more accurate prediction of secondary structures in vivo.

A wise consistency: engineering biology for conformity, reliability, predictability.

The next generation of synthetic biology applications will increasingly involve engineered organisms that exist in intimate contact with humans, animals and the rest of the environment. Examples include cellular and viral approaches for maintaining and improving health in humans and animals. The need for reliable and specific function in these environments may require more complex system designs than previously. In these cases the uncertainties in the behavior of biological building blocks, their hosts and their environments present a challenge for design of predictable and safe systems. Here, we review systematic methods for the effective characterization of these uncertainties that are lowering the barriers to predictive design of reliable complex biological systems.

Effects of genetic variation on the E. coli host-circuit interface.

Predictable operation of engineered biological circuitry requires the knowledge of host factors that compete or interfere with designed function. Here, we perform a detailed analysis of the interaction between constitutive expression from a test circuit and cell-growth properties in a subset of genetic variants of the bacterium Escherichia coli. Differences in generic cellular parameters such as ribosome availability and growth rate are the main determinants (89%) of strain-specific differences of circuit performance in laboratory-adapted strains but are responsible for only 35% of expression variation across 88 mutants of E. coli BW25113. In the latter strains, we identify specific cell functions, such as nitrogen metabolism, that directly modulate circuit behavior. Finally, we expose aspects of carbon metabolism that act in a strain- and sequence-specific manner. This method of dissecting interactions between host factors and heterologous circuits enables the discovery of mechanisms of interference necessary for the development of design principles for predictable cellular engineering.

Contextualizing context for synthetic biology--identifying causes of failure of synthetic biological systems.

Despite the efforts that bioengineers have exerted in designing and constructing biological processes that function according to a predetermined set of rules, their operation remains fundamentally circumstantial. The contextual situation in which molecules and single-celled or multi-cellular organisms find themselves shapes the way they interact, respond to the environment and process external information. Since the birth of the field, synthetic biologists have had to grapple with contextual issues, particularly when the molecular and genetic devices inexplicably fail to function as designed when tested in vivo. In this review, we set out to identify and classify the sources of the unexpected divergences between design and actual function of synthetic systems and analyze possible methodologies aimed at controlling, if not preventing, unwanted contextual issues.

Comparative genomics of regulation of fatty acid and branched-chain amino acid utilization in proteobacteria.

Bacteria can use branched-chain amino acids (ILV, i.e., isoleucine, leucine, valine) and fatty acids (FAs) as sole carbon and energy sources converting ILV into acetyl-coenzyme A (CoA), propanoyl-CoA, and propionyl-CoA, respectively. In this work, we used the comparative genomic approach to identify candidate transcriptional factors and DNA motifs that control ILV and FA utilization pathways in proteobacteria. The metabolic regulons were characterized based on the identification and comparison of candidate transcription factor binding sites in groups of phylogenetically related genomes. The reconstructed ILV/FA regulatory network demonstrates considerable variability and involves six transcriptional factors from the MerR, TetR, and GntR families binding to 11 distinct DNA motifs. The ILV degradation genes in gamma- and betaproteobacteria are regulated mainly by a novel regulator from the MerR family (e.g., LiuR in Pseudomonas aeruginosa) (40 species); in addition, the TetR-type regulator LiuQ was identified in some betaproteobacteria (eight species). Besides the core set of ILV utilization genes, the LiuR regulon in some lineages is expanded to include genes from other metabolic pathways, such as the glyoxylate shunt and glutamate synthase in Shewanella species. The FA degradation genes are controlled by four regulators including FadR in gammaproteobacteria (34 species), PsrA in gamma- and betaproteobacteria (45 species), FadP in betaproteobacteria (14 species), and LiuR orthologs in alphaproteobacteria (22 species). The remarkable variability of the regulatory systems associated with the FA degradation pathway is discussed from functional and evolutionary points of view.

Morphology matters in immune cell chemotaxis: membrane asymmetry affects amplification.

A key mediator of eukaryotic chemotaxis is the asymmetric accumulation of phosphatidylinositol-3,4,5-triphosphate (PIP3) on the cell membrane. Recent work has focused on understanding how a shallow external gradient of chemoattractant leads to an amplified internal gradient of PIP3. In this paper we dissect what fraction of this amplification is derived biochemically by the signal transduction network and how much arises entirely from the effects of cell morphology. Here we identify and formalize the role of morphology in signal detection and demonstrate its effects through simulation and experiments. Our key result is that an asymmetric distribution of membrane accounts for approximately one-half of the measured amplification from ligand concentration to PIP3 production. We also show that the underlying biochemical network behaves as a linear amplifier in the micropipette assay.

Numerical computation of diffusion on a surface.

We present a numerical method for computing diffusive transport on a surface derived from image data. Our underlying discretization method uses a Cartesian grid embedded boundary method for computing the volume transport in a region consisting of all points a small distance from the surface. We obtain a representation of this region from image data by using a front propagation computation based on level set methods for solving the Hamilton-Jacobi and eikonal equations. We demonstrate that the method is second-order accurate in space and time and is capable of computing solutions on complex surface geometries obtained from image data of cells.