Bacteria Swarm Research Articles

Out-of-equilibrium interactions and collective locomotion of colloidal spheres with squirming of nematoelastic multipoles

Many living and artificial systems show similar emergent behavior and collective motions on different scales, starting from swarms of bacteria to synthetic active particles, herds of mammals, and crowds of people. What all these systems often have in common is that new collective properties like flocking emerge from interactions between individual self-propelled or driven units. Such systems are naturally out-of-equilibrium and propel at the expense of consumed energy. Mimicking nature by making self-propelled or externally driven particles and studying their individual and collective motility may allow for deeper understanding of physical underpinnings behind collective motion of large groups of interacting objects or beings. Here, using a soft matter system of colloids immersed into a liquid crystal, we show that resulting so-called nematoelastic multipoles can be set into a bidirectional locomotion by external oscillating electric fields. Out-of-equilibrium elastic interactions between such colloidal objects lead to collective flock-like behaviors emerging from time-varying elasticity-mediated interactions between externally driven propelling particles. Repulsive elastic interactions in the equilibrium state can be turned into attractive interactions in the out-of-equilibrium state under applied external electric fields. We probe this behavior at different number densities of colloidal particles and show that particles in dense dispersions collectively select the same direction of a coherent motion due to elastic interactions between near neighbors. In our experimentally implemented design, their motion is highly ordered and without clustering or jamming often present in other colloidal transport systems, which is promising for technological and fundamental-science applications, like nano-cargo transport, out-of-equilibrium assembly, and microrobotics.

Undergraduate Tutorial for Simulating Flocking with the Vicsek Model

ABSTRACT There are many instances of collective behaviors in the natural world. For example, eukaryotic cells coordinate their motion to heal wounds; bacteria swarm during colony expansion; defects in alignment in growing bacterial populations lead to biofilm growth; and birds move within dynamic flocks. Although the details of how these groups behave vary across animals and species, they share the same qualitative feature: they exhibit collective behaviors that are not simple extensions of details associated with the motion of an individual. To learn more about these biological systems, we propose studying these systems through the lens of the foundational Vicsek model. Here, we present the process of building this computational model from scratch in a tutorial format that focuses on building the appropriate skills of an undergraduate student. In doing so, an undergraduate student should be able to work alongside this article, the corresponding tutorial, and the original manuscript of the Vicsek model to build their own model. We conclude by summarizing some of the current work involving computational modeling of flocking with Vicsek-type models.

Discrete bacterial foraging optimization for community detection in networks

An essential mesoscopic concept in network analysis is that of community structure. However, conventional nature-inspired optimization algorithms encounter serious challenges and difficulties when used directly to seek communities in networks, due to the large amount of data and the NP-hard combinatorial nature of the problem. Thus in this paper, we introduce a novel bacterial foraging optimization approach to uncovering community structure in networks. Instead of using the original bacterial foraging designed traditionally for continuous optimization, the problem of community detection is exquisitely embedded into a redefined discrete framework. The evolutionary principles for the bacterial foraging are developed from a topological perspective. Furthermore, two specific local updating rules, namely the greedy strategy and the stochastic strategy, are designed to steer the swarm of bacteria to the favored regions. The extensive experimental results on both synthetic and real-world networks indicate that the proposed approach outperforms the baseline algorithms and can achieve a high accuracy on the uncovered community structure. The integration of the proposed approach into the analysis of power grids and its explicit utility are also discussed in detail, showing that our method has high accuracy and practicability.

Bacterial motility: machinery and mechanisms.

Bacteria have developed a large array of motility mechanisms to exploit available resources and environments. These mechanisms can be broadly classified into swimming in aqueous media and movement over solid surfaces. Swimming motility involves either the rotation of rigid helical filaments through the external medium or gyration of the cell body in response to the rotation of internal filaments. On surfaces, bacteria swarm collectively in a thin layer of fluid powered by the rotation of rigid helical filaments, they twitch by assembling and disassembling type IV pili, they glide by driving adhesins along tracks fixed to the cell surface and, finally, non-motile cells slide over surfaces in response to outward forces due to colony growth. Recent technological advances, especially in cryo-electron microscopy, have greatly improved our knowledge of the molecular machinery that powers the various forms of bacterial motility. In this Review, we describe the current understanding of the physical and molecular mechanisms that allow bacteria to move around.

Assessing Swarming of Aerobic Bacteria from Human Fecal Matter.

Swarming - swift movement across a surface via flagella propulsion - is a unique property of many bacteria. The role of swarming, particularly among bacterial populations of the human gut microbiome, is not yet fully understood; although, it is becoming an area of increased scientific and clinical inquiry. To further characterize bacterial swarming in human health, an effective assay for swarming that utilizes complex material, such as fecal matter, is necessary. Until now, the vast majority of swarming assays have only been able to accommodate bacteria grown in culture, most often Pseudomonas. These assays tend to use a standard lysogenic broth (LB) agar medium; however, the reagents involved have not been tailored to the inoculation of complex material. In this paper, we offer a specialized protocol for eliciting the swarming of bacteria from frozen human fecal samples. We describe the simple, yet reproducible steps required to perform the assay, identifying an ideal volume of 7.5 μl for inoculation of material, as well as an ideal agar concentration of 0.4%. This protocol typically allows researchers to identify swarming within 24 h after incubation in a standard incubator.

Enumeration and Identification of Bacterial Spores in Cocoa Powders

The presence of bacterial spores in cocoa powders is inevitable due to the cocoa bean fermentation process, during which members of the genera Bacillus and Geobacillus are typically present. Spores are a concern in heat-treated foods when they survive heat treatments and the finished product supports germination, growth, and potentially toxin production. In this study, available methods for the enumeration of total mesophilic and thermophilic spores (TMS and TTS, respectively) were evaluated, leading to the recommendation of one global method specifically for cocoa powders. The proposed method was validated during a ring test on seven selected cocoa powders and applied during routine analyses on commercial powders. The method includes dilution of cocoa powder using buffered peptone water, heating at 80°C for 10 min for TMS and TTS counts, and heating at 100°C for 30 min for a heat-resistant (HR) spore count. Tryptic soy agar is used as a recovery medium with a maximal concentration of cocoa powder of 2.5 mg/mL (to prevent growth inhibition) and a nonnutrient agar overlay to prevent swarming of bacteria. Plates are incubated for at least 72 h at 30°C for recovery of mesophilic bacteria and 55°C for thermophilic bacteria. Suitable alternatives to specific method parameters are provided. Median values of total spore concentrations are low (<400 CFU/g for TMS and <75 CFU/g for TTS), and concentrations of HR spores are very low (<5 CFU/g). Importantly, the relation between concentrations of HR spores in cocoa powder and incidence of spoilage of heat-treated beverages containing cocoa is currently unclear. In the powders included in this study, Bacillus subtilis and Bacillus licheniformis were the predominant spore-forming species identified (49 and 39%, respectively). Both species are known for high variability in spore heat resistance. The development of reliable and sensitive molecular methods is therefore required to assess the risk of spoilage caused by spores present in cocoa powders.

An Evolutionary Algorithm for Optimal Multi-Direction Search Route in Search and Rescue Operation

Enhancing the effectiveness of search and rescue operation at sea is the utmost importance. Once the search area has been identified, the success of search and rescue operations depends on search and rescue vessel swept the probability area of the distress object with the minimum search time, this is an important element to the success of search and rescue operation as it minimizes the risk and the cost for search and rescue team. However, determining the optimal search route to find the distress object is extremely complex because weather conditions, winds, waves, and currents always change constantly, whereas the condition of the search and rescue vessel also changes. The present article proposes the use of a bacterial foraging optimization algorithm and applies it to finding the optimal multi-direction search route for search and rescue vessel. The cost function takes into the consideration of the total search time as well as the probability of quick find of the object in distress. In this paper, the Monte Carlo simulation method is used to predict the most probable drift area of the distress object, and then a swarm of 10 bacteria is deployed for searching the optimal SAR route. It can be seen from the calculation result that the bacteria swarm has concentrated rather well after just several generations. The optimal search path is reasonable for the dominant weather conditions and is accordance with the popular code of practice.

Active particles bound by information flows

Self-organization is the generation of order out of local interactions. It is deeply connected to many fields of science from physics, chemistry to biology, all based on physical interactions. The emergence of collective animal behavior is the result of self-organization processes as well, though they involve abstract interactions arising from sensory inputs, information processing, storage, and feedback. Resulting collective behaviors are found, for example, in crowds of people, flocks of birds, and swarms of bacteria. Here we introduce interactions between active microparticles which are based on the information about other particle positions. A real-time feedback of multiple active particle positions is the information source for the propulsion direction of these particles. The emerging structures require continuous information flows. They reveal frustrated geometries due to confinement to two dimensions and internal dynamical degrees of freedom that are reminiscent of physically bound systems, though they exist only as nonequilibrium structures.

Bacillus subtilis biofilm development in the presence of soil clay minerals and iron oxides

Clay minerals and metal oxides, as important parts of the soil matrix, play crucial roles in the development of microbial communities. However, the mechanism underlying such a process, particularly on the formation of soil biofilm, remains poorly understood. Here, we investigated the effects of montmorillonite, kaolinite, and goethite on the biofilm formation of the representative soil bacteria Bacillus subtilis. The bacterial biofilm formation in goethite was found to be impaired in the initial 24 h but burst at 48 h in the liquid–air interface. Confocal laser scanning microscopy showed that the biofilm biomass in goethite was 3–16 times that of the control, montmorillonite, and kaolinite at 48 h. Live/Dead staining showed that cells had the highest death rate of 60% after 4 h of contact with goethite, followed by kaolinite and montmorillonite. Atomic force microscopy showed that the interaction between goethite and bacteria may injure bacterial cells by puncturing cell wall, leading to the swarming of bacteria toward the liquid–air interface. Additionally, the expressions of abrB and sinR, key players in regulating the biofilm formation, were upregulated at 24 h and downregulated at 48 h in goethite, indicating the initial adaptation of the cells to minerals. A model was proposed to describe the effects of goethite on the biofilm formation. Our findings may facilitate a better understanding of the roles of soil clays in biofilm development and the manipulation of bacterial compositions through controlling the biofilm in soils.

Water surface tension modulates the swarming mechanics of Bacillus subtilis.

Many Bacillus subtilis strains swarm, often forming colonies with tendrils on agar medium. It is known that B. subtilis swarming requires flagella and a biosurfactant, surfactin. In this study, we find that water surface tension plays a role in swarming dynamics. B. subtilis colonies were found to contain water, and when a low amount of surfactin is produced, the water surface tension of the colony restricts expansion, causing bacterial density to rise. The increased density induces a quorum sensing response that leads to heightened production of surfactin, which then weakens water surface tension to allow colony expansion. When the barrier formed by water surface tension is breached at a specific location, a stream of bacteria swarms out of the colony to form a tendril. If a B. subtilis strain produces surfactin at levels that can substantially weaken the overall water surface tension of the colony, water floods the agar surface in a thin layer, within which bacteria swarm and migrate rapidly. This study sheds light on the role of water surface tension in regulating B. subtilis swarming, and provides insight into the mechanisms underlying swarming initiation and tendril formation.

Collective dynamics of soft active particles.

We present a model of soft active particles that leads to a rich array of collective behavior found also in dense biological swarms of bacteria and other unicellular organisms. Our model uses only local interactions, such as Vicsek-type nearest-neighbor alignment, short-range repulsion, and a local boundary term. Changing the relative strength of these interactions leads to migrating swarms, rotating swarms, and jammed swarms, as well as swarms that exhibit run-and-tumble motion, alternating between migration and either rotating or jammed states. Interestingly, although a migrating swarm moves slower than an individual particle, the diffusion constant can be up to three orders of magnitude larger, suggesting that collective motion can be highly advantageous, for example, when searching for food.

English

Proteus mirabilis colonies exhibit striking geometric regularity, and swarm colony terraces correspond to one swarming-plus-consolidation cycle. Basic microbiological methods and imaging techniques were used to measure periodic macroscopic events in swarm colony morphogenesis. Here, adding a respiratory enzyme indicator, 2,3,5-triphenyltetra-zolium chloride (TTC) into the culture medium, the bacteria on the rings gradually changed into red and the change was not synchronous with the formation of ring. According to this phenomenon, we distinguished five phases as P. mirabilis colonize agar surfaces during swarming to investigate the bacteria swarm colony development mechanism by the methods of matrix assisted laser desorption/ionization (MALDI) mass spectrometry and real time fluorescence quantitative-polymerase chain reaction (RTFQ-PCR). Through these observations, we found that P. mirabilis swarm colony development was closely related to the gene fusA, fliC1, tufB, ahpC, icd and flaB. The research indicates that the functions of the genes fusA, filC1 and tufB in swarming phase significantly influence the P. mirabilis swarming behavior. In consolidation phase, expression of ahpC connected to oxidative stress decreased as compared to other phases. The gene icd which affected the metabolism had high expression in consolidation phase I and there were more expression from the bacteria on the ring than that from the bacteria between two rings. The increase of flaB was concomitant with the development of cell growth from swarming phase to turn red phase II. The morphology of P. mirabilis was obviously distinct in different growth phase, and periodically changed. The movement and metabolize way of P. mirabilis were diverse in different growth phase. In swarming phase, the swarm colony and antioxidant ability was enhanced, but the functions of respiratory and metabolism was down-regulated. In conclusion, the bacteria fertility ability and respiratory function were enhanced in consolidation phase. These genes related with motion and metabolism played a key role in regulating P. mirabilis swarm colony development. Key words: Proteus mirabilis, real time fluorescence quantitative-polymerase chain reaction (RTFQ-PCR), matrix assisted laser desorption/ionization (MALDI)-TOF, swarm.

A Chimeric Siderophore Halts Swarming Vibrio

Some bacteria swarm under some circumstances; they move rapidly and collectively over a surface. In an effort to understand the molecular signals controlling swarming, we isolated two bacterial strains from the same red seaweed, Vibrio alginolyticus B522, a vigorous swarmer, and Shewanella algae B516, which inhibits V. alginolyticus swarming in its vicinity. Plate assays combined with NMR, MS, and X-ray diffraction analyses identified a small molecule, which was named avaroferrin, as a potent swarming inhibitor. Avaroferrin, a previously unreported cyclic dihydroxamate siderophore, is a chimera of two well-known siderophores: putrebactin and bisucaberin. The sequenced genome of S. algae revealed avaroferrin's biosynthetic gene cluster to be a mashup of putrebactin and bisucaberin biosynthetic genes. Avaroferrin blocks swarming through its ability to bind iron in a form that cannot be pirated by V. alginolyticus, thereby securing this essential resource for its producer.

Binarization based Image Edge Detection using Bacterial Foraging Algorithm

Bacterial Foraging Algorithm (BFA) is one of the powerful bio-inspired optimization algorithms which attempt to imitate the single and groups of E. Coli bacteria. In BFA algorithm, a set of bacteria try to forage towards a nutrient rich medium to get more nutrients. In this scheme, an objective function is posed as the effort or a cost incurred by the bacteria in search of food. In the present, an approach is presented for edge detection in a binarized image using bacterial foraging algorithm. .First binarization is applied to the input image to get an image matrix consisting of only the intensity values 0 and 255 of 8-bit image and then a swarm of bacteria are enthrusted on the binary image for extraction of edge information. Edges are detected by calculating the difference between intensity values of the present pixel with each of the neighboring eight pixels. Whenever the bacteria finds this intensity difference of 255 it will treat that pixel as its food and mark it as an edge pixel.

Self-organization in bacterial swarming: lessons from myxobacteria

When colonizing surfaces, many bacteria are able to self-organize into an actively expanding biofilm, in which millions of cells move smoothly and orderly at high densities. This phenomenon is known as bacterial swarming. Despite the apparent resemblance to patterns seen in liquid crystals, the dynamics of bacterial swarming cannot be explained by theories derived from equilibrium statistical mechanics. To understand how bacteria swarm, a central question is how order emerges in dense and initially disorganized populations of bacterial cells. Here we briefly review recent efforts, with integrated computational and experimental approaches, in addressing this question.

Lipid imaging with cluster time-of-flight secondary ion mass spectrometry

This brief article provides an overview of the current state of the art in biological imaging mass spectrometry using cluster time-of-flight secondary ion mass spectrometry (TOF-SIMS). Recent and spectacular improvements in terms of sensitivity of TOF-SIMS imaging methods have allowed many biological applications to recently be successfully tested, such as mapping of lipid disorders in human muscles of a patient suffering from dystrophy, localization of surfactins after the swarming of bacteria on a surface, or lipid mapping over whole-body animal sections.

Rewiring Bacteria, Two Components at a Time

In this issue, Skerker et al. (2008) present a rational method for rewiring the protein-protein interactions and output responses of prokaryotic two-component signal transduction systems. This work has important implications for understanding the specificity of protein interactions and for designing protein-based synthetic signaling cascades.

Enhanced swarming of bacteria on agar plates containing the surfactant Tween 80

A widely used method for quantifying swarming motility is the swarm plate assay. A significant increase in the motility halo size formed by Escherichia coli or Azospirillum brasilense was measured on Tween 80-containing agar relative to untreated agar. This improvement could benefit the identification of mutants in swarming motility.

Bacterial swarming: a biochemical time-resolved FTIR-ATR study of Proteus mirabilis swarm-cell differentiation.

Fourier transform infrared spectroscopy was applied to the study of the differentiation process undergone by Proteus mirabilis. This bacterium exhibits a remarkable dimorphism, allowing the cells to migrate on a solid substratum in a concerted manner yielding characteristic ring patterns. We performed an in situ noninvasive analysis of biochemical events occurring as vegetative cells differentiate into elongated, multinucleate, nonseptate, and hyperflagellated swarm cells. The major findings arising from this study are (i) the real-time monitoring of flagellar filament assembly, (ii) the evidence for de novo synthesis of qualitatively different lipopolysaccharides (LPS) and/or exopolysaccharides (EPS) constituting the slime into which bacteria swarm, and (iii) the alteration in the membrane fatty acid composition with a concomitant 10 degrees C decrease in the gel/liquid crystal phase transition resulting in an elevated membrane fluidity in swarm cells at the growth temperature. The time course of events shows that the EPS-LPS syntheses are synchronous with membrane fatty acid alterations and occur about 1 h before massive flagellar filament assembly is detected. This study not only provided a time sketch of biochemical events involved in the differentiation process but also led to the identification of the major spectral markers of both vegetative and swarm cells. This identification will allow to resolve the time-space structure of P. mirabilis colonies by using infrared microscopy.

Influence of bacteria, diffusion and shear on micro-scale nutrient patches, and implications for bacterial chemotaxis

Micro-scale nutrient patches were observed in mixtures of isolates consisting of a protozoan, its prey, and chemotactic bacteria. The patches were shown by swarms of bacteria and the events leading to patches were associated with cell lysis and predation events. In such a form, nutrients are experienced by bacteria as pulses. Simulations showed that patches can be consumed by the bacterial community before being dispersed. As a result, even non-motile bacteria may only ever encounter diffuse patches within a sphere of 2 mm radius. If patches are generated randomly in time and space, it can be advantageous for a bacterium to swim, if only to break this 2 mm barrier. Simulations suggested that chemotaxis can increase a bacterium's exposure to nutrients within a patch, but that the enhancement depends on the size of the patch, due to limitations in sensitivity. The patch size limit for achieving enhancement is ∼0. 1 pmol. Swimming speed is the most important motility parameter influencing efficiency of chemotactic foraging on diffuse patches, with an optimum speed as a function of patch size. Simulations illustrated that shear stretches patches, but that moderate shear does not significantly alter patch volumes within time scales of several minutes. A large proportion of the nutrients within a patch can be encountered by bacteria within that time.