Improving Bacteria Controller Efficiency

We present a novel approach that would enable the placement of dynamic sensor platforms in the most optimal areas for data collection in an environment of any size. Our approach would ensure that more sensors are placed in areas that contain interesting data and less in areas with little or no data. In this paper, we use a bacteria controller to navigate the environment in the search of interesting data and show that the addition of a flocking algorithm improves the chances of finding data

Networking strategies in streptomyces coelicolor

We are interested the soil dwelling bacteria Streptomyces coelicolor because its cells grow end to end in a line. New branches have the potential to extend from any point along this line and the result is a network of branches and connections. This is a novel form of colonisation in the bacterial world and it is advantageous for spreading through an environment resourcefully. Networking protocols for communication technologies have similar pressures to be resourceful in terms of time, computing power, and energy. In this preliminary investigation we design a computer model of the biological system to understand its limitations and strategies for survival. The decentralised capacity for organisation of both the bacterial system and the model reflects well on the now-popular conventions for path finding and ad hoc network building in human technologies. The project will ultimately become a comparison of strategies between nature and the man-made

Mathematical models for chemotaxis and their applications in self-organisation phenomena

Chemotaxis is a fundamental guidance mechanism of cells and organisms, responsible for attracting microbes to food, embryonic cells into developing tissues, immune cells to infection sites, animals towards potential mates, and mathematicians into biology. The Patlak-Keller-Segel (PKS) system forms part of the bedrock of mathematical biology, a go-to-choice for modellers and analysts alike. For the former it is simple yet recapitulates numerous phenomena; the latter are attracted to these rich dynamics. Here I review the adoption of PKS systems when explaining self-organisation processes. I consider their foundation, returning to the initial efforts of Patlak and Keller and Segel, and briefly describe their patterning properties. Applications of PKS systems are considered in their diverse areas, including microbiology, development, immunology, cancer, ecology and crime. In each case a historical perspective is provided on the evidence for chemotactic behaviour, followed by a review of modelling efforts; a compendium of the models is included as an Appendix. Finally, a half-serious/half-tongue-in-cheek model is developed to explain how cliques form in academia. Assumptions in which scholars alter their research line according to available problems leads to clustering of academics and the formation of "hot" research topics.Comment: 35 pages, 8 figures, Submitted to Journal of Theoretical Biolog

PATTERNED BIOFILM FORMATION TO INVESTIGATE BACTERIA-SURFACE INTERACTIONS

Bacterial adhesion to surfaces and subsequent formation of microcolonies play important roles in biofilm formation, which is a major cause of chronic infections and persistent biofouling. Despite the significance, mechanistic understanding of biofilm formation is still hindered by the structural heterogeneity in biofilms; and effective control of biofilm formation remains challenging. Biofilm formation is a dynamic process that involves numerous changes in bacterial gene and protein expression. These changes are highly sensitive to environmental factors such as surface chemistry, topography, charge, and hydrophobicity. To better control biofilm morphology and specifically investigate the effects of these factors, a platform was developed in this study to obtain patterned biofilm formation using surfaces with well-defined patterns of chemistry and topography. By modifying surfaces with systematically varied square patterns of self-assembled monolayers (SAMs) of functional alkanthiols, the size of cell clusters and inter-cluster distance were well controlled. By following biofilm formation of Escherichia coli on these surfaces, it was found that multicellular connections were formed between adjacent cell clusters when the clusters were within a threshold distance (10 µm); and such connections were influenced by the size of interacting cell clusters. It was also found that the connections were formed by active interactions of cell clusters, rather than nonspecific binding of planktonic cells on the bioinert background. Interestingly, the mutants of luxS and motB exhibited major defects in interaction between cell clusters. The phenotype of the luxS mutant was successfully restored by both complementing the luxS gene on a plasmid and by adding the precursor of autoinducer-2 (AI-2) signal in the culture. These results suggest that AI-2 mediated quorum sensing and motility are involved in the interaction among cell clusters. Based on these findings, a model was proposed to explain the intrinsic heterogeneity in biofilm structures. Consistently, cells attached between interacting clusters were found to be more sensitive to the antibiotic ampicillin. Besides surfaces with patterns of surface chemistry, poly(dimethylsiloxane) (PDMS) surfaces with microtopographic patterns of different shapes, dimensions and inter-pattern distances were used to understand the effects of surface topography on bacteria-surface interactions and biofilm formation. E. coli was found to preferentially attach and form biofilms in the valleys between square shaped plateaus. In addition, there appeared to be a threshold dimension of a plateau to allow bacterial attachment and biofilm formation on top of the plateaus. The threshold was found to be 40 µm × 40 µm for inverted patterns used in this study. Inspired by this finding, we created PDMS surfaces with hexagon shaped patterns and found that the ones with 15 µm side width and 2 µm inter-pattern distance can reduce biofilm formation by 7-fold compared to flat PDMS surfaces. These results were integrated with additional tests to better understand the resistance of biofilm cells to antibiotics. Specifically, the biofilm formation of fluorescently labeled donors and recipients on PDMS surfaces with square shaped microtopographic patterns was followed to investigate the effects of cell density on bacterial conjugation. PDMS surfaces with microtopogrpahic patterns were found to promote both biofilm formation and bacterial conjugation. This result was found to be due to the aggregation of biofilm cells on the side of plateaus, providing hot spots for bacterial conjugation. Bacterial motility was also found to play an important role in biofilm formation and bacterial conjugation. Collectively, these results are helpful for understanding the mechanism of biofilm formation and associated drug resistance, as well as the design of nonfouling surfaces

Interacting particles with L\'{e}vy strategies: limits of transport equations for swarm robotic systems

L\'{e}vy robotic systems combine superdiffusive random movement with emergent collective behaviour from local communication and alignment in order to find rare targets or track objects. In this article we derive macroscopic fractional PDE descriptions from the movement strategies of the individual robots. Starting from a kinetic equation which describes the movement of robots based on alignment, collisions and occasional long distance runs according to a L\'{e}vy distribution, we obtain a system of evolution equations for the fractional diffusion for long times. We show that the system allows efficient parameter studies for a search problem, addressing basic questions like the optimal number of robots needed to cover an area in a certain time. For shorter times, in the hyperbolic limit of the kinetic equation, the PDE model is dominated by alignment, irrespective of the long range movement. This is in agreement with previous results in swarming of self-propelled particles. The article indicates the novel and quantitative modeling opportunities which swarm robotic systems provide for the study of both emergent collective behaviour and anomalous diffusion, on the respective time scales.Comment: 23 pages, 3 figures, to appear in SIAM Journal on Applied Mathematic

Tiling solutions for optimal biological sensing

Biological systems, from cells to organisms, must respond to the ever changing environment in order to survive and function. This is not a simple task given the often random nature of the signals they receive, as well as the intrinsically stochastic, many body and often self-organized nature of the processes that control their sensing and response and limited resources. Despite a wide range of scales and functions that can be observed in the living world, some common principles that govern the behavior of biological systems emerge. Here I review two examples of very different biological problems: information transmission in gene regulatory networks and diversity of adaptive immune receptor repertoires that protect us from pathogens. I discuss the trade-offs that physical laws impose on these systems and show that the optimal designs of both immune repertoires and gene regulatory networks display similar discrete tiling structures. These solutions rely on locally non-overlapping placements of the responding elements (genes and receptors) that, overall, cover space nearly uniformly.Comment: 11 page

Frontiers in microfluidics, a teaching resource review

This is a literature teaching resource review for biologically inspired microfluidics courses or exploring the diverse applications of microfluidics. The structure is around key papers and model organisms. While courses gradually change over time, a focus remains on understanding how microfluidics has developed as well as what it can and cannot do for researchers. As a primary starting point, we cover micro-fluid mechanics principles and microfabrication of devices. A variety of applications are discussed using model prokaryotic and eukaryotic organisms from the set of bacteria (Escherichia coli), trypanosomes (Trypanosoma brucei), yeast (Saccharomyces cerevisiae), slime molds (Physarum polycephalum), worms (Caenorhabditis elegans), flies (Drosophila melangoster), plants (Arabidopsis thaliana), and mouse immune cells (Mus musculus). Other engineering and biochemical methods discussed include biomimetics, organ on a chip, inkjet, droplet microfluidics, biotic games, and diagnostics. While we have not yet reached the end-all lab on a chip, microfluidics can still be used effectively for specific applications

Advances in cellular and molecular predatory biology of Bdellovibrio bacteriovorus six decades after discovery

Since its discovery six decades ago, the predatory bacterium Bdellovibrio bacteriovorus has sparked recent interest as a potential remedy to the antibiotic resistance crisis. Here we give a comprehensive historical overview from discovery to progressive developments in microscopy and molecular mechanisms. Research on B. bacteriovorus has moved from curiosity to a new model organism, revealing over time more details on its physiology and fascinating predatory life cycle with the help of a variety of methods. Based on recent findings in cryo-electron tomography, we recapitulate on the intricate molecular details known in the predatory life cycle including how this predator searches for its prey bacterium, to how it attaches, grows, and divides all from within the prey cell. Finally, the newly developed B. bacteriovorus progeny leave the prey cell remnants in the exit phase. While we end with some unanswered questions remaining in the field, new imaging technologies and quantitative, systematic advances will likely help to unravel them in the next decades