Spin controlled atom-ion inelastic collisions

The control of the ultracold collisions between neutral atoms is an extensive and successful field of study. The tools developed allow for ultracold chemical reactions to be managed using magnetic fields, light fields and spin-state manipulation of the colliding particles among other methods. The control of chemical reactions in ultracold atom-ion collisions is a young and growing field of research. Recently, the collision energy and the ion electronic state were used to control atom-ion interactions. Here, we demonstrate spin-controlled atom-ion inelastic processes. In our experiment, both spin-exchange and charge-exchange reactions are controlled in an ultracold Rb-Sr$^+$ mixture by the atomic spin state. We prepare a cloud of atoms in a single hyperfine spin-state. Spin-exchange collisions between atoms and ion subsequently polarize the ion spin. Electron transfer is only allowed for (RbSr)$^+$ colliding in the singlet manifold. Initializing the atoms in various spin states affects the overlap of the collision wavefunction with the singlet molecular manifold and therefore also the reaction rate. We experimentally show that by preparing the atoms in different spin states one can vary the charge-exchange rate in agreement with theoretical predictions

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

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

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

Comparison of the model and data.

<p>Red curves show the simulation results, which are compared to to the experimental data points. Error bars are showing the standard error of mean. The initial conditions for simulations are taken from an experiment with 1291 particles, with 495 “active” and <i>m</i>_<i>p</i> = 796 “passive” particles. Diffusion constant as a function of cluster size is given in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0137661#pone.0137661.g004" target="_blank">Fig 4</a><i>D</i>₀ = 0.6 <i>μ</i>m² s⁻¹, with minimal and cut off cluster sizes set to <i>a</i>_<i>s</i> = 0.8<i>μm</i>, and <i>a</i>_cut = 3.5<i>μm</i>. The pili length <i>l</i>₀ = 1.6 <i>μ</i>m, growth rate <i>λ</i> = 4.2 × 10⁻⁵ s⁻¹, and a delay time for the establishment of pili-pili contact <i>T</i>_<i>w</i> = 18.3min.</p

Merging of two clusters.

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

Model for the merging of bacterial clusters.

<p>Each spherical cluster consists of a certain number of gonococci and is characterized by its radius <i>a</i> and volume <math><mrow><mi>V</mi><mo>=</mo><mn>4</mn><mn>3</mn><mi>π</mi><mi>a</mi><mn>3</mn></mrow></math>. The two sketched aggregates merge after an exponentially distributed waiting time, if the corresponding pili shells of the width <i>l</i>₀ overlap. After aggregation, the total volume of cells is conserved (see also the explanation in the text). Note that the extent of the actual mixing of cells from two different clusters is not known and here should be only considered as an illustration.</p

Probability density for the cluster size distribution.

<p>The distribution is obtained at the end of the clustering process (at the maximal time 147 min) from the same experiment, which provided the data for <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0137661#pone.0137661.g002" target="_blank">Fig 2</a>. For a typical distribution of aggregates in space, we refer to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0137661#pone.0137661.g001" target="_blank">Fig 1</a>.</p