Spontaneous modulation of a dynamic balance between bacterial genomic stability and mutability: roles and molecular mechanisms of the genetic switch

Interface-Mediated Neurogenic Signaling: The Impact of Surface Geometry and Chemistry on Neural Cell Behavior for Regenerative and Brain-Machine Interfacing Applications

Nanomaterial advancements have driven progress in central and peripheral nervous system applications such as tissue regeneration and brain-machine interfacing. Ideally, neural interfaces with native tissue shall seamlessly integrate, a process that is often mediated by the interfacial material properties. Surface topography and material chemistry are significant extracellular stimuli that can influence neural cell behavior to facilitate tissue integration and augment therapeutic outcomes. This review characterizes topographical modifications, including micropillars, microchannels, surface roughness, and porosity, implemented on regenerative scaffolding and brain-machine interfaces. Their impact on neural cell response is summarized through neurogenic outcome and mechanistic analysis. The effects of surface chemistry on neural cell signaling with common interfacing compounds like carbon-based nanomaterials, conductive polymers, and biologically inspired matrices are also reviewed. Finally, the impact of these extracellular mediated neural cues on intracellular signaling cascades is discussed to provide perspective on the manipulation of neuron and neuroglia cell microenvironments to drive therapeutic outcomes.

E. coli diversity: low in colorectal cancer

BACKGROUND

Escherichia coli are mostly commensals but also contain pathogenic lineages. It is largely unclear whether the commensal E. coli as the potential origins of pathogenic lineages may consist of monophyletic or polyphyletic populations, elucidation of which is expected to lead to novel insights into the associations of E. coli diversity with human health and diseases.

METHODS

Using genomic sequencing and pulsed field gel electrophoresis (PFGE) techniques, we analyzed E. coli from the intestinal microbiota of three groups of healthy individuals, including preschool children, university students, and seniors of a longevity village, as well as colorectal cancer (CRC) patients, to probe the commensal E. coli populations for their diversity.

RESULTS

We delineated the 2280 fresh E. coli isolates from 185 subjects into distinct genome types (genotypes) by PFGE. The genomic diversity of the sampled E. coli populations was so high that a given subject may have multiple genotypes of E. coli, with the general diversity within a host going up from preschool children through university students to seniors. Compared to the healthy subjects, the CRC patients had the lowest diversity level among their E. coli isolates. Notably, E. coli isolates from CRC patients could suppress the growth of E. coli bacteria isolated from healthy controls under nutrient-limited culture conditions.

CONCLUSIONS

The coexistence of multiple E. coli lineages in a host may help create and maintain a microbial environment that is beneficial to the host. As such, the low diversity of E. coli bacteria may be associated with unhealthy microenvironment in the intestine and hence facilitate the pathogenesis of diseases such as CRC.

Intracellular Noise Level Determines Ratio Control Strategy Confined by Speed-Accuracy Trade-off

Robust and precise ratio control of heterogeneous phenotypes within an isogenic population is an essential task, especially in the development and differentiation of a large number of cells such as bacteria, sensory receptors, and blood cells. However, the mechanisms of such ratio control are poorly understood. Here, we employ experimental and mathematical techniques to understand the combined effects of signal induction and gene expression stochasticity on phenotypic multimodality. We identify two strategies to control phenotypic ratios from an initially homogeneous population, suitable roughly to high-noise and low-noise intracellular environments, and we show that both can be used to generate precise fractional differentiation. In noisy gene expression contexts, such as those found in bacteria, induction within the circuit's bistable region is enough to cause noise-induced bimodality within a feasible time frame. However, in less noisy contexts, such as tightly controlled eukaryotic systems, spontaneous state transitions are rare and hence bimodality needs to be induced with a controlled pulse of induction that falls outside the bistable region. Finally, we show that noise levels, system response time, and ratio tuning accuracy impose trade-offs and limitations on both ratio control strategies, which guide the selection of strategy alternatives.