How the Motility Pattern of Bacteria Affects Their Dispersal and Chemotaxis

Most bacteria at certain stages of their life cycle are able to move actively; they can swim in a liquid or crawl on various surfaces. A typical path of the moving cell often resembles the trajectory of a random walk. However, bacteria are capable of modifying their apparently random motion in response to changing environmental conditions. As a result, bacteria can migrate towards the source of nutrients or away from harmful chemicals. Surprisingly, many bacterial species that were studied have several distinct motility patterns, which can be theoretically modeled by a unifying random walk approach. We use this approach to quantify the process of cell dispersal in a homogeneous environment and show how the bacterial drift velocity towards the source of attracting chemicals is affected by the motility pattern of the bacteria. Our results open up the possibility of accessing additional information about the intrinsic response of the cells using macroscopic observations of bacteria moving in inhomogeneous environments

Dry and wet interfaces: Influence of solvent particles on molecular recognition

We present a coarse-grained lattice model to study the influence of water on the recognition process of two rigid proteins. The basic model is formulated in terms of the hydrophobic effect. We then investigate several modifications of our basic model showing that the selectivity of the recognition process can be enhanced by considering the explicit influence of single solvent particles. When the number of cavities at the interface of a protein-protein complex is fixed as an intrinsic geometric constraint, there typically exists a characteristic fraction that should be filled with water molecules such that the selectivity exhibits a maximum. In addition the optimum fraction depends on the hydrophobicity of the interface so that one has to distinguish between dry and wet interfaces.Comment: 11 pages, 7 figure

Pili-Induced Clustering of N. gonorrhoeae Bacteria

Type IV pili (Tfp) are prokaryotic retractable appendages known to mediate surface attachment, motility, and subsequent clustering of cells. Tfp are the main means of motility for Neisseria gonorrhoeae, the causative agent of gonorrhea. Tfp are also involved in formation of the microcolonies, which play a crucial role in the progression of the disease. While motility of individual cells is relatively well understood, little is known about the dynamics of N. gonorrhoeae aggregation. We investigate how individual N. gonorrhoeae cells, initially uniformly dispersed on flat plastic or glass surfaces, agglomerate into spherical microcolonies within hours. We quantify the clustering process by measuring the area fraction covered by the cells, number of cell aggregates, and their average size as a function of time. We observe that the microcolonies are also able to move but their mobility rapidly vanishes as the size of the colony increases. After a certain critical size they become immobile. We propose a simple theoretical model which assumes a pili-pili interaction of cells as the main clustering mechanism. Numerical simulations of the model quantitatively reproduce the experimental data on clustering and thus suggest that the agglomeration process can be entirely explained by the Tfp-mediated interactions. In agreement with this hypothesis mutants lacking pili are not able to form colonies. Moreover, cells with deficient quorum sensing mechanism show similar aggregation as the wild-type bacteria. Therefore, our results demonstrate that pili provide an essential mechanism for colony formation, while additional chemical cues, for example quorum sensing, might be of secondary importance

Modelle für Zufallsbewegungen und Chemotaxis von Bakterien – Aspekte der Biofilmentstehung

Ansammlungen von Bakterien auf Oberflächen werden als Biofilme bezeichnet, deren Entstehung durch zahlreiche biologische, chemische und physikalische Prozesse beeinflusst wird. In dieser Arbeit untersuchen wir mit Methoden der Statistischen Physik Aspekte, die im frühen Entwicklungsstadium von Biofilmen relevant sind. Die Fortbewegungsstrategien von Bakterien lassen sich als Zufallsbewegungen charakterisieren: "Run-and-tumble" für das Darmbakterium E. coli, "Run-reverse" für den Krankheitserreger P. aeruginosa oder "Run-reverse-flick" für das Meeresbakterium V. alginolyticus. Zum quantitativen Vergleich dieser unterschiedlichen Bewegungsmuster entwickeln wir eine verallgemeinerte Zufallsbewegung, für die wir analytisch den Diffusionskoeffizienten als Maß der Zellmotilität bestimmen. In inhomogener Umgebung können Mikroorganismen ihre Bewegung entlang eines chemischen Gradienten ausrichten, was als Chemotaxis bezeichnet wird. Um die chemotaktische Effizienz zu vergleichen, berechnen wir die chemotaktische Driftgeschwindigkeit, mit der sich ein "Run-tumble-flick"-Bakterium einer Nahrungsquelle nähert. Sobald Mikroorganismen sich auf einer Oberfläche anlagern, aktiviert "Kommunikation" zwischen einzelnen Zellen die Bildung von Mikrokolonien und damit die Entstehung eines Biofilms. Coli-Bakterien, Salmonellen oder Amöben können selbst chemische Stoffe produzieren, auf die die jeweilige Zellpopulation chemotaktisch reagiert. Diese Mikroorganismen inspirieren unser Modell für aktive, "autochemotaktische" Teilchen. Wir zeigen, dass die chemotaktische Wechselwirkung bei unseren Modellorganismen die Bildung von Zellaggregaten bewirkt, was im Einklang mit zahlreichen Experimenten steht. Für die diffusive Langzeitdynamik eines isolierten Modellteilchens geben wir den Diffusionskoeffizienten analytisch an. Physikalische Wechselwirkungen zwischen Zellen können ebenfalls die Bildung von Mikrokolonien verursachen. Gonokokken-Bakterien (N. gonorrhoeae), Erreger der sexuell übertragbaren Krankheit Gonorrhoe, weisen Zellfortsätze auf, sogenannte Typ-IV-Pili, die den Zellen Oberflächenhaftung und "Twitching Motility" als Art der Fortbewegung ermöglichen. Unserer Hypothese nach erfolgt die Bildung von Mikrokolonien von N. gonorrhoeae ausschließlich über die Wechselwirkung der Pili, wofür insbesondere keine Chemotaxis notwendig ist. Ein von uns durchgeführtes Experiment demonstriert, wie anfänglich auf einer Oberfläche verteilte Zellen binnen Stunden aggregieren. Für die Dynamik der Zellaggregation entwickeln wir ein auf der Pili-Wechselwirkung basierendes Modell, das die experimentellen Beobachtungen gut reproduziert.A biofilm is an aggregation of bacteria living on a surface within a matrix of self-produced biopolymers. The formation of a biofilm is governed by numerous biological, chemical, and physical processes. In this thesis, we apply methods of statistical physics to investigate aspects relevant to the early stages of biofilm formation. Swimming strategies of bacteria can be characterized as random walks: "Run-and-tumble" of the intestinal bacterium E. coli, "Run-reverse" of the pathogen P. aeruginosa, or "Run-reverse-flick" of the marine bacterium V. alginolyticus. To compare these different patterns of motion, we develop a generalized random walk model and analytically calculate the diffusion coefficient to quantify each motility pattern. In an inhomogeneous environment, microorganisms perform chemotaxis and align their motion along a chemical gradient. To measure the chemotactic efficiency, we determine the chemotactic drift speeds of bacteria towards a food source and compare them for different strategies. Once microorganisms have attached to a surface, communication among the cells initiates the formation of microcolonies and biofilms. Coli bacteria, salmonellae, or amoebae can produce chemical substances themselves, to which they respond chemotactically. These microorganisms inspired our model for active, autochemotactic walkers. We show that the chemotactic interaction results in the formation of cell aggregates, as observed in various experiments. The long-time dynamics of an isolated model particle is diffusive and we determine its diffusion coefficient analytically. Physical interactions between cells also cause the formation of microcolonies. Cell appendages, called type IV pili, are attached on the cell body of the bacterium N. gonorrhoeae, the causative agent of the disease gonorrhea. These pili enable the cells to attach to surfaces and provide "twitching motility" as a means of bacterial locomotion. We hypothesize that the formation of microcolonies of N. gonorrhoeae is solely explained by a pili-mediated interaction, and chemotaxis is not required. Our experiments demonstrate how cells, initially dispersed over a surface, form aggregates within hours. Our model for the dynamics of cell aggregation is based on a pili-mediated attraction between the bacteria and reproduces our experimental observations

Chemotactic drift speed as a function of for <i>E. coli</i> and <i>V. alginolyticus</i>.

<p>The plot on the left shows ; on the right, the chemotactic drift is normalized by the swimming speed as and coincides with the chemotactic index.</p

Comparison of the chemotactic drift speed versus persistence parameter between run-tumble-flick [Eq. (28)] and run-tumble [Eq. (27)].

<p>All parameters are adjusted to <i>E. coli</i> in the gradient with , , , and .</p

Sketch of the predominant motility patterns.

<p>a) Run-and-tumble, b) Run-reverse, and c) Run-reverse-flick. During a “run” event, a cell moves with high persistence. Runs are interrupted by reorientation events like tumbling or reversal. The time steps indicate the sequence of these events. An average turning angle after tumbling in <i>E. coli</i> bacteria is (a), whereas it is an almost perfect reversal of for many marine bacteria, or cells with twitching motility due to cell appendages, called pili (b). <i>V. alginolyticus</i> (c) alternates reversals (at ) with randomizing flicks (at ) with an average turning angle of .</p

Velocity correlation function.

<p>The normalized velocity correlation function is plotted as a function of dimensionless time . The curves are shown for run-and-tumble of <i>E. coli</i> with persistence parameter (red), run-reverse with (green), and run-reverse-flick with alternating and (blue). The analytical expressions are given in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0081936#pone.0081936.e103" target="_blank">Eqs. (12)</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0081936#pone.0081936.e160" target="_blank">(21)</a>, respectively.</p

Pili-Induced Clustering of <i>N. gonorrhoeae</i> Bacteria

<div><p>Type IV pili (Tfp) are prokaryotic retractable appendages known to mediate surface attachment, motility, and subsequent clustering of cells. Tfp are the main means of motility for <i>Neisseria gonorrhoeae</i>, the causative agent of gonorrhea. Tfp are also involved in formation of the microcolonies, which play a crucial role in the progression of the disease. While motility of individual cells is relatively well understood, little is known about the dynamics of <i>N. gonorrhoeae</i> aggregation. We investigate how individual <i>N. gonorrhoeae</i> cells, initially uniformly dispersed on flat plastic or glass surfaces, agglomerate into spherical microcolonies within hours. We quantify the clustering process by measuring the area fraction covered by the cells, number of cell aggregates, and their average size as a function of time. We observe that the microcolonies are also able to move but their mobility rapidly vanishes as the size of the colony increases. After a certain critical size they become immobile. We propose a simple theoretical model which assumes a pili-pili interaction of cells as the main clustering mechanism. Numerical simulations of the model quantitatively reproduce the experimental data on clustering and thus suggest that the agglomeration process can be entirely explained by the Tfp-mediated interactions. In agreement with this hypothesis mutants lacking pili are not able to form colonies. Moreover, cells with deficient quorum sensing mechanism show similar aggregation as the wild-type bacteria. Therefore, our results demonstrate that pili provide an essential mechanism for colony formation, while additional chemical cues, for example quorum sensing, might be of secondary importance.</p></div

Merging of two clusters.

<p>Two large microcolonies merge into an aggregate that finally tends to an almost spherical shape.</p