Long-term ecological and evolutionary dynamics in the gut microbiomes of carbapenemase-producing Enterobacteriaceae colonized subjects.

Long-term colonization of the gut microbiome by carbapenemase-producing Enterobacteriaceae (CPE) is a growing area of public health concern as it can lead to community transmission and rapid increase in cases of life-threatening CPE infections. Here, leveraging the observation that many subjects are decolonized without interventions within a year, we used longitudinal shotgun metagenomics (up to 12 timepoints) for detailed characterization of ecological and evolutionary dynamics in the gut microbiome of a cohort of CPE-colonized subjects and family members (n = 46; 361 samples). Subjects who underwent decolonization exhibited a distinct ecological shift marked by recovery of microbial diversity, key commensals and anti-inflammatory pathways. In addition, colonization was marked by elevated but unstable Enterobacteriaceae abundances, which exhibited distinct strain-level dynamics for different species (Escherichia coli and Klebsiella pneumoniae). Finally, comparative analysis with whole-genome sequencing data from CPE isolates (n = 159) helped identify substrain variation in key functional genes and the presence of highly similar E. coli and K. pneumoniae strains with variable resistance profiles and plasmid sharing. These results provide an enhanced view into how colonization by multi-drug-resistant bacteria associates with altered gut ecology and can enable transfer of resistance genes, even in the absence of overt infection and antibiotic usage.

The Merging of Biological and Electronic Circuits.

Biological circuits and systems within even a single cell need to be represented by large-scale feedback networks of nonlinear, stochastic, stiff, asynchronous, non-modular coupled differential equations governing complex molecular interactions. Thus, rational drug discovery and synthetic biological design is difficult. We suggest that a four-pronged interdisciplinary approach merging biology and electronics can help: (1) The mapping of biological circuits to electronic circuits via quantitatively exact schematics; (2) The use of existing electronic circuit software for hierarchical modeling, design, and analysis with such schematics; (3) The use of cytomorphic electronic hardware for rapid stochastic simulation of circuit schematics and associated parameter discovery to fit measured biological data; (4) The use of bio-electronic reporting circuits rather than bio-optical circuits for measurement. We suggest how these approaches can be combined to automate design, modeling, analysis, simulation, and quantitative fitting of measured data from a synthetic biological operational amplifier circuit in living microbial cells.

An Artificial Tissue Homeostasis Circuit Designed via Analog Circuit Techniques.

Tissue homeostasis (feedback control) is an important mechanism that regulates the population of different cell types within a tissue. In type-1 diabetes, auto-immune attack and consequent death of pancreatic ß cells result in the failure of homeostasis and loss of organ function. Synthetically engineered adult stem cells with homeostatic control based on digital logic have been proposed as a solution for regenerating ß cells. Such previously proposed homeostatic control circuits have thus far been unable to reliably control both stem-cell proliferation and stem-cell differentiation. Using analog circuits and feedback systems analysis, we have designed an in silico circuit that performs homeostatic control by utilizing a novel scheme with both symmetric and asymmetric division of stem cells. The use of a variety of feedback systems analysis techniques, which is common in analog circuit design, including root-locus techniques, Bode plots of feedback-loop frequency response, compensation techniques for improving stability, and robustness analysis help us choose design parameters to meet desirable specifications. For example, we show that lead compensation in analog circuits instantiated as an incoherent feed-forward loop in the biological circuit improves stability, whereas simultaneously reducing steady-state tracking error. Our symmetric and asymmetric division scheme also improves phase margin in the feedback loop, and thus improves robustness. This paper could be useful in porting an analog-circuit design framework to synthetic biological applications of the future.

Synthetic Biology: A Unifying View and Review Using Analog Circuits.

We review the field of synthetic biology from an analog circuits and analog computation perspective, focusing on circuits that have been built in living cells. This perspective is well suited to pictorially, symbolically, and quantitatively representing the nonlinear, dynamic, and stochastic (noisy) ordinary and partial differential equations that rigorously describe the molecular circuits of synthetic biology. This perspective enables us to construct a canonical analog circuit schematic that helps unify and review the operation of many fundamental circuits that have been built in synthetic biology at the DNA, RNA, protein, and small-molecule levels over nearly two decades. We review 17 circuits in the literature as particular examples of feedforward and feedback analog circuits that arise from special topological cases of the canonical analog circuit schematic. Digital circuit operation of these circuits represents a special case of saturated analog circuit behavior and is automatically incorporated as well. Many issues that have prevented synthetic biology from scaling are naturally represented in analog circuit schematics. Furthermore, the deep similarity between the Boltzmann thermodynamic equations that describe noisy electronic current flow in subthreshold transistors and noisy molecular flux in biochemical reactions has helped map analog circuit motifs in electronics to analog circuit motifs in cells and vice versa via a `cytomorphic' approach. Thus, a body of knowledge in analog electronic circuit design, analysis, simulation, and implementation may also be useful in the robust and efficient design of molecular circuits in synthetic biology, helping it to scale to more complex circuits in the future.