Pattern Engineering of Living Bacterial Colonies Using Meniscus-Driven Fluidic Channels

Making use of noise in biological systems

Disorder and noise are inherent in biological systems. They are required to provide systems with the advantages required for proper functioning. Noise is a part of the flexibility and plasticity of biological systems. It provides systems with increased routes, improves information transfer, and assists in response triggers. This paper reviews recent studies on noise at the genome, cellular, and whole organ levels. We focus on the need to use noise in system engineering. We present some of the challenges faced in studying noise. Optimizing the efficiency of complex systems requires a degree of variability in their functions within certain limits. Constrained noise can be considered a method for improving system robustness by regulating noise levels in continuously dynamic settings. The digital pill-based artificial intelligence (AI)-based platform is the first to implement second-generation AI comprising variability-based signatures. This platform enhances the efficacy of the therapeutic regimens. Systems requiring variability and mechanisms regulating noise are mandatory for understanding biological functions.

Protein Patterning on Microtextured Polymeric Nano-brush Templates Obtained By Nanosecond Fibre Laser

Micropatterned polymer brushes have attracted attention in several biomedical areas, i.e., tissue engineering, protein microarray, biosensors etc., for precise arrangement of biomolecules. Herein, we report a facile and scalable approach to create microtextured polymer brushes with the ability to generate different type of protein patterns. Nanosecond fibre laser was exploited to generate micropatterns on polyPEGMA (poly(ethylene glycol) methacrylate) brush modified Ti alloy substrate. Surface initiated atom transfer radical polymerisation was employed to grow PolyPEGMA brush (11-87 nm thick) on Ti alloy surface immobilized with initiator having an initiator density (σ*) of 1.5 initiators/nm² . Polymer brushes were then selectively laser ablated and their presence on non-textured area was confirmed by atomic force microscopy, fluorescence microscopy and X-ray photoelectron spectroscopy. Spatial orientation of biomolecules was first achieved by non-specific protein adsorption on areas ablated by the laser, via physisorption. Further, patterned brushes of polyPEGMA were modified to activated ester that gave rise to protein conjugation specifically on non-laser ablated brush areas. Moreover, the laser ablated brush modified patterned template was also successfully utilized for generating alternate patterns of bacteria. This promising technique can be further extended to create interesting patterns of several biomolecules which are of great interest to biomedical research community. This article is protected by copyright. All rights reserved.

Biofabrication and characterization of multispecies electroactive biofilms in stratified paper-based scaffolds

This work develops novel biofabrication and analysis platforms by creating innovative, paper-based 3-D systems that accurately recapitulate the structure, function, and physiology of living multispecies biofilms.

Bringing cells to the edge

A network of open channels allows cells and molecular cargo to travel from the center to the periphery of lab-grown colonies of Pseudomonas aeruginosa, helping to eradicate competing species.

Swarming bacteria undergo localized dynamic phase transition to form stress-induced biofilms

Self-organized multicellular behaviors enable cells to adapt and tolerate stressors to a greater degree than isolated cells. However, whether and how cellular communities alter their collective behaviors adaptively upon exposure to stress is largely unclear. Here, we investigate this question using Bacillus subtilis, a model system for bacterial multicellularity. We discover that, upon exposure to a spatial gradient of kanamycin, swarming bacteria activate matrix genes and transit to biofilms. The initial stage of this transition is underpinned by a stress-induced multilayer formation, emerging from a biophysical mechanism reminiscent of motility-induced phase separation (MIPS). The physical nature of the process suggests that stressors which suppress the expansion of swarms would induce biofilm formation. Indeed, a simple physical barrier also induces a swarm-to-biofilm transition. Based on the gained insight, we propose a strategy of antibiotic treatment to inhibit the transition from swarms to biofilms by targeting the localized phase transition.

Biofilm and swarming emergent behaviours controlled through the aid of biophysical understanding and tools

Bacteria can organise themselves into communities in the forms of biofilms and swarms. Through chemical and physical interactions between cells, these communities exhibit emergent properties that individual cells alone do not have. While bacterial communities have been mainly studied in the context of biochemistry and molecular biology, recent years have seen rapid advancements in the biophysical understanding of emergent phenomena through physical interactions in biofilms and swarms. Moreover, new technologies to control bacterial emergent behaviours by physical means are emerging in synthetic biology. Such technologies are particularly promising for developing engineered living materials (ELM) and devices and controlling contamination and biofouling. In this minireview, we overview recent studies unveiling physical and mechanical cues that trigger and affect swarming and biofilm development. In particular, we focus on cell shape, motion and density as the key parameters for mechanical cell-cell interactions within a community. We then showcase recent studies that use physical stimuli for patterning bacterial communities, altering collective behaviours and preventing biofilm formation. Finally, we discuss the future potential extension of biophysical and bioengineering research on microbial communities through computational modelling and deeper investigation of mechano-electrophysiological coupling.

Novel Tunable Spatio-Temporal Patterns From a Simple Genetic Oscillator Circuit

Multicellularity, the coordinated collective behavior of cell populations, gives rise to the emergence of self-organized phenomena at many different spatio-temporal scales. At the genetic scale, oscillators are ubiquitous in regulation of multicellular systems, including during their development and regeneration. Synthetic biologists have successfully created simple synthetic genetic circuits that produce oscillations in single cells. Studying and engineering synthetic oscillators in a multicellular chassis can therefore give us valuable insights into how simple genetic circuits can encode complex multicellular behaviors at different scales. Here we develop a study of the coupling between the repressilator synthetic genetic ring oscillator and constraints on cell growth in colonies. We show in silico how mechanical constraints generate characteristic patterns of growth rate inhomogeneity in growing cell colonies. Next, we develop a simple one-dimensional model which predicts that coupling the repressilator to this pattern of growth rate via protein dilution generates traveling waves of gene expression. We show that the dynamics of these spatio-temporal patterns are determined by two parameters; the protein degradation and maximum expression rates of the repressors. We derive simple relations between these parameters and the key characteristics of the traveling wave patterns: firstly, wave speed is determined by protein degradation and secondly, wavelength is determined by maximum gene expression rate. Our analytical predictions and numerical results were in close quantitative agreement with detailed individual based simulations of growing cell colonies. Confirming published experimental results we also found that static ring patterns occur when protein stability is high. Our results show that this pattern can be induced simply by growth rate dilution and does not require transition to stationary phase as previously suggested. Our method generalizes easily to other genetic circuit architectures thus providing a framework for multi-scale rational design of spatio-temporal patterns from genetic circuits. We use this method to generate testable predictions for the synthetic biology design-build-test-learn cycle.