First Study of the ^{139}Ba(n,γ)^{140}Ba Reaction to Constrain the Conditions for the Astrophysical i Process

New astronomical observations point to a nucleosynthesis picture that goes beyond what was accepted until recently. The intermediate "i" process was proposed as a plausible scenario to explain some of the unusual abundance patterns observed in metal-poor stars. The most important nuclear physics properties entering i-process calculations are the neutron-capture cross sections and they are almost exclusively not known experimentally. Here we provide the first experimental constraints on the ^{139}Ba(n,γ)^{140}Ba reaction rate, which is the dominant source of uncertainty for the production of lanthanum, a key indicator of i-process conditions. This is an important step towards identifying the exact astrophysical site of stars carrying the i-process signature.

Proton Shell Gaps in N=28 Nuclei from the First Complete Spectroscopy Study with FRIB Decay Station Initiator

The first complete measurement of the β-decay strength distribution of _{17}^{45}Cl_{28} was performed at the Facility for Rare Isotope Beams (FRIB) with the FRIB Decay Station Initiator during the second FRIB experiment. The measurement involved the detection of neutrons and γ rays in two focal planes of the FRIB Decay Station Initiator in a single experiment for the first time. This enabled an analytical consistency in extracting the β-decay strength distribution over the large range of excitation energies, including neutron unbound states. We observe a rapid increase in the β-decay strength distribution above the neutron separation energy in _{18}^{45}Ar_{27}. This was interpreted to be caused by the transitioning of neutrons into protons excited across the Z=20 shell gap. The SDPF-MU interaction with reduced shell gap best reproduced the data. The measurement demonstrates a new approach that is sensitive to the proton shell gap in neutron rich nuclei according to SDPF-MU calculations.

Synchronized strobed phase contrast and fluorescence microscopy: the interlaced standard reimagined

We propose a simple, cost-effective method for synchronized phase contrast and fluorescence video acquisition in live samples. Counter-phased pulses of phase contrast illumination and fluorescence excitation light are synchronized with the exposure of the two fields of an interlaced camera sensor. This results in a video sequence in which each frame contains both exposure modes, each in half of its pixels. The method allows real-time acquisition and display of synchronized and spatially aligned phase contrast and fluorescence image sequences that can be separated by de-interlacing in two independent videos. The method can be implemented on any fluorescence microscope with a camera port without needing to modify the optical path.

Comprehensive Test of the Brink-Axel Hypothesis in the Energy Region of the Pygmy Dipole Resonance

The validity of the Brink-Axel hypothesis, which is especially important for numerous astrophysical calculations, is addressed for ^{116,120,124}Sn below the neutron separation energy by means of three independent experimental methods. The γ-ray strength functions (GSFs) extracted from primary γ-decay spectra following charged-particle reactions with the Oslo method and with the shape method demonstrate excellent agreement with those deduced from forward-angle inelastic proton scattering at relativistic beam energies. In addition, the GSFs are shown to be independent of excitation energies and spins of the initial and final states. The results provide a critical test of the generalized Brink-Axel hypothesis in heavy nuclei, demonstrating its applicability in the energy region of the pygmy dipole resonance.

Structural basis of torque generation in the bi-directional bacterial flagellar motor

The flagellar stator unit is an oligomeric complex of two membrane proteins (MotA₅B₂) that powers bi-directional rotation of the bacterial flagellum. Harnessing the ion motive force across the cytoplasmic membrane, the stator unit operates as a miniature rotary motor itself to provide torque for rotation of the flagellum. Recent cryo-electron microscopic (cryo-EM) structures of the stator unit provided novel insights into its assembly, function, and subunit stoichiometry, revealing the ion flux pathway and the torque generation mechanism. Furthermore, in situ cryo-electron tomography (cryo-ET) studies revealed unprecedented details of the interactions between stator unit and rotor. In this review, we summarize recent advances in our understanding of the structure and function of the flagellar stator unit, torque generation, and directional switching of the motor.

Mechanosensitive remodeling of the bacterial flagellar motor is independent of direction of rotation

Motility is important for the survival and dispersal of many bacteria, and it often plays a role during infections. Regulation of bacterial motility by chemical stimuli is well studied, but recent work has added a new dimension to the problem of motility control. The bidirectional flagellar motor of the bacterium Escherichia coli recruits or releases torque-generating units (stator units) in response to changes in load. Here, we show that this mechanosensitive remodeling of the flagellar motor is independent of direction of rotation. Remodeling rate constants in clockwise rotating motors and in counterclockwise rotating motors, measured previously, fall on the same curve if plotted against torque. Increased torque decreases the off rate of stator units from the motor, thereby increasing the number of active stator units at steady state. A simple mathematical model based on observed dynamics provides quantitative insight into the underlying molecular interactions. The torque-dependent remodeling mechanism represents a robust strategy to quickly regulate output (torque) in response to changes in demand (load).

A molecular rack and pinion actuates a cell-surface adhesin and enables bacterial gliding motility

The gliding bacterium Flavobacterium johnsoniae is known to have an adhesin, SprB, that moves along the cell surface on a spiral track. Following viscous shear, cells can be tethered by the addition of an anti-SprB antibody, causing spinning at 3 Hz. Labeling the type 9 secretion system (T9SS) with a YFP fusion of GldL showed a yellow fluorescent spot near the rotation axis, indicating that the motor driving the motion is associated with the T9SS. The distance between the rotation axis and the track (90 nm) was determined after adding a Cy3 label for SprB. A rotary motor spinning a pinion of radius 90 nm at 3 Hz would cause a spot on its periphery to move at 1.5 μm/s, the gliding speed. We suggest the pinion drives a flexible tread that carries SprB along a track fixed to the cell surface. Cells glide when this adhesin adheres to the solid substratum.

CW and CCW Conformations of the E. coli Flagellar Motor C-Ring Evaluated by Fluorescence Anisotropy

The molecular cascade that controls switching of the direction of rotation of Escherichia coli flagellar motors is well known, but the conformational changes that allow the rotor to switch are still unclear. The signaling molecule CheY, when phosphorylated, binds to the C-ring at the base of the rotor, raising the probability that the motor spins clockwise. When the concentration of CheY-P is so low that the motor rotates exclusively counterclockwise (CCW), the C-ring recruits more monomers of FliM and tetramers of FliN, the proteins to which CheY-P binds, thus increasing the motor's sensitivity to CheY-P and allowing it to switch once again. Motors that rotate exclusively CCW have more FliM and FliN subunits in their C-rings than motors that rotate exclusively clockwise. How are the new subunits accommodated? Does the diameter of the C-ring increase, or do FliM and FliN get packed in a different pattern, keeping the overall diameter of the C-ring constant? Here, by measuring fluorescence anisotropy of yellow fluorescent protein-labeled motors, we show that the CCW C-rings accommodate more FliM monomers without changing the spacing between them, and more FliN monomers at the same time as increasing their effective spacing and/or changing their orientation within the tetrameric structure.

The bacterium has landed

Mechanosensing mechanisms for surface recognition by bacteria allow biofilm formation

The Screw-Like Movement of a Gliding Bacterium Is Powered by Spiral Motion of Cell-Surface Adhesins

Flavobacterium johnsoniae, a rod-shaped bacterium, glides over surfaces at speeds of ∼2 μm/s. The propulsion of a cell-surface adhesin, SprB, is known to enable gliding. We used cephalexin to generate elongated cells with irregular shapes and followed their displacement in three dimensions. These cells rolled about their long axes as they moved forward, following a right-handed trajectory. We coated gold nanoparticles with an SprB antibody and tracked them in three dimensions in an evanescent field where the nanoparticles appeared brighter when they were closer to the glass. The nanoparticles followed a right-handed spiral trajectory on the surface of the cell. Thus, if SprB were to adhere to the glass rather than to a nanoparticle, the cell would move forward along a right-handed trajectory, as observed, but in a direction opposite to that of the nanoparticle.

Modeling polymorphic transformation of rotating bacterial flagella in a viscous fluid

The helical flagella that are attached to the cell body of bacteria such as Escherichia coli and Salmonella typhimurium allow the cell to swim in a fluid environment. These flagella are capable of polymorphic transformation in that they take on various helical shapes that differ in helical pitch, radius, and chirality. We present a mathematical model of a single flagellum described by Kirchhoff rod theory that is immersed in a fluid governed by Stokes equations. We perform numerical simulations to demonstrate two mechanisms by which polymorphic transformation can occur, as observed in experiments. First, we consider a flagellar filament attached to a rotary motor in which transformations are triggered by a reversal of the direction of motor rotation [L. Turner et al., J. Bacteriol. 182, 2793 (2000)10.1128/JB.182.10.2793-2801.2000]. We then consider a filament that is fixed on one end and immersed in an external fluid flow [H. Hotani, J. Mol. Biol. 156, 791 (1982)10.1016/0022-2836(82)90142-5]. The detailed dynamics of the helical flagellum interacting with a viscous fluid is discussed and comparisons with experimental and theoretical results are provided.

The flagellar motor adapts, optimizing bacterial behavior

A short review is given of recent work showing that the flagellar rotary motor of the bacterium Escherichia coli remodels to match its operating point (the fraction of time that it spins clockwise) to the requirements of the chemotaxis signaling network, and to provide the torque necessary to operate at different viscous loads.

The flagellar motor of Caulobacter crescentus generates more torque when a cell swims backward

Caulobacter crescentus, a monotrichous bacterium, swims by rotating a single right-handed helical filament. CW motor rotation thrusts the cell forward ¹, a mode of motility known as the pusher mode; CCW motor rotation pulls the cell backward, a mode of motility referred to as the puller mode ². The situation is opposite in E. coli, a peritrichous bacterium, where CCW rotation of multiple left-handed filaments drives the cell forward. The flagellar motor in E. coli generates more torque in the CCW direction than the CW direction in swimming cells ^3,4. However, monotrichous bacteria including C. crescentus swim forward and backward at similar speeds, prompting the assumption that motor torques in the two modes are the same ^5,6. Here, we present evidence that motors in C. crescentus develop higher torques in the puller mode than in the pusher mode, and suggest that the anisotropy in torque-generation is similar in two species, despite the differences in filament handedness and motor bias (probability of CW rotation).

Response thresholds in bacterial chemotaxis

Stimulation of Escherichia coli by exponential ramps of chemoattractants generates step changes in the concentration of the response regulator, CheY-P. Because flagellar motors are ultrasensitive, this should change the fraction of time that motors spin clockwise, the CWbias. However, early work failed to show changes in CWbias when ramps were shallow. This was explained by a model for motor remodeling that predicted plateaus in plots of CWbias versus [CheY-P]. We looked for these plateaus by examining distributions of CWbias in populations of cells with different mean [CheY-P]. We did not find such plateaus. Hence, we repeated the work on shallow ramps and found that motors did indeed respond. These responses were quantitatively described by combining motor remodeling with ultrasensitivity in a model that exhibited high sensitivities over a wide dynamic range.

Osmotic pressure in a bacterial swarm

Using Escherichia coli as a model organism, we studied how water is recruited by a bacterial swarm. A previous analysis of trajectories of small air bubbles revealed a stream of fluid flowing in a clockwise direction ahead of the swarm. A companion study suggested that water moves out of the agar into the swarm in a narrow region centered ∼ 30 μm from the leading edge of the swarm and then back into the agar (at a smaller rate) in a region centered ∼ 120 μm back from the leading edge. Presumably, these flows are driven by changes in osmolarity. Here, we utilized green/red fluorescent liposomes as reporters of osmolarity to verify this hypothesis. The stream of fluid that flows in front of the swarm contains osmolytes. Two distinct regions are observed inside the swarm near its leading edge: an outer high-osmolarity band (∼ 30 mOsm higher than the agar baseline) and an inner low-osmolarity band (isotonic or slightly hypotonic to the agar baseline). This profile supports the fluid-flow model derived from the drift of air bubbles and provides new (to our knowledge) insights into water maintenance in bacterial swarms. High osmotic pressure at the leading edge of the swarm extracts water from the underlying agar and promotes motility. The osmolyte is of high molecular weight and probably is lipopolysaccharide.

A rotary motor drives Flavobacterium gliding

Cells of Flavobacterium johnsoniae, a rod-shaped bacterium devoid of pili or flagella, glide over glass at speeds of 2-4 μm/s [1]. Gliding is powered by a protonmotive force [2], but the machinery required for this motion is not known. Usually, cells move along straight paths, but sometimes they exhibit a reciprocal motion, attach near one pole and flip end over end, or rotate. This behavior is similar to that of a Cytophaga species described earlier [3]. Development of genetic tools for F. johnsoniae led to discovery of proteins involved in gliding [4]. These include the surface adhesin SprB that forms filaments about 160 nm long by 6 nm in diameter, which, when labeled with a fluorescent antibody [2] or a latex bead [5], are seen to move longitudinally down the length of a cell, occasionally shifting positions to the right or the left. Evidently, interaction of these filaments with a surface produces gliding. To learn more about the gliding motor, we sheared cells to reduce the number and size of SprB filaments and tethered cells to glass by adding anti-SprB antibody. Cells spun about fixed points, mostly counterclockwise, rotating at speeds of 1 Hz or more. The torques required to sustain such speeds were large, comparable to those generated by the flagellar rotary motor. However, we found that a gliding motor runs at constant speed rather than at constant torque. Now, there are three rotary motors powered by protonmotive force: the bacterial flagellar motor, the Fo ATP synthase, and the gliding motor.

Adaptive remodelling by FliN in the bacterial rotary motor

Sensory adaptation in the Escherichia coli chemosensory pathway has been the subject of interest for decades, with investigation focusing on the receptors that process extracellular inputs. Recent studies demonstrate that the flagellar motors responsible for cell locomotion also play a role, adding or subtracting FliM subunits to maximise sensitivity to pathway signals. It is difficult to reconcile this FliM remodelling with the observation that partner FliN subunits are relatively static fixtures in the motor. By fusing a fluorescent protein internally to FliN, we show that there is in fact significant FliN remodelling. The kinetics and stoichiometry of FliN in steady state and in adapting motors are investigated and found to match the behaviour of FliM in all respects except for timescale where FliN rates are about 4 times slower. We notice that motor adaptation is slower in the presence of the fluorescent protein, indicating a possible source for the difference. The behaviour of FliM and FliN is consistent with a kinetic and stoichiometric model that contradicts the traditional view of a packed, rigid motor architecture.

Ultrasensitivity of an adaptive bacterial motor

The flagellar motor of Escherichia coli adapts to changes in the steady-state level of the chemotaxis response regulator, CheY-P, by adjusting the number of FliM molecules to which CheY-P binds. Previous measurements of motor ultrasensitivity have been made on cells containing different amounts of CheY-P and, thus, different amounts of FliM in flagellar motors. Here, we designed an experiment to measure the sensitivity of motors containing fixed amounts of FliM, finding Hill coefficients about twice as large as those observed before. This ultrasensitivity provides further insights into the motor switching mechanism and plays important roles in chemotaxis signal amplification and coordination of multiple motors. The Hill coefficients observed here appear to be the highest known for allosteric protein complexes, either biological or synthetic. Extreme motor ultrasensitivity broadens our understanding of mechanisms of allostery and serves as an inspiration for future design of synthetic protein switches.

Tandem adaptation with a common design in Escherichia coli chemotaxis

We analyze a model for motor-level adaptation in Escherichia coli based upon the premise that clockwise (CW) and counter-clockwise (CCW) states have different preferred numbers of FliM subunits. We show that this model provides a simple mechanism for the recently observed motor-level adaptation, and it also explains the long-lasting puzzle on the thresholds observed when tethered cells are used to monitor responses to temporal ramps. We note that the motor-level adaptation has the same negative-feedback network design as the upstream receptor-level adaptation, and the tandem architecture of one control circuit followed by the other mitigates the effects of cell-to-cell variation and broadens the range of stimuli over which cells optimally respond.

Adaptation at the output of the chemotaxis signalling pathway

In the bacterial chemotaxis network, receptor clusters process input^1–3, and flagellar motors generate output⁴. Receptor and motor complexes are coupled by the diffusible protein CheY-P. Receptor output (the steady-state concentration of CheY-P) varies from cell to cell⁵. However, the motor is ultrasensitive, with a narrow [CheY-P] operating range⁶. How might the match between receptor output and motor input be optimized? Here we show that the motor can shift its operating range by changing its composition. The number of FliM subunits in the C-ring increases in response to a decrement in the concentration of CheY-P, increasing motor sensitivity. This shift in sensitivity explains the slow partial adaptation observed in mutants that lack the receptor methyltransferase and methylesterase^7–8 and why motors exhibit signal-dependent FliM turnover⁹. Adaptive remodelling is likely to be a common feature in the operation of many molecular machines.

A modular gradient-sensing network for chemotaxis in Escherichia coli revealed by responses to time-varying stimuli

Combining in vivo FRET with time-varying stimuli, such as steps, ramps, and sinusoids allowed deduction of the molecular mechanisms underlying cellular signal processing.

The bacterial chemotaxis pathway can be described as a two-module feedback circuit, the transfer functions of which we have characterized quantitatively by experiment. Model-driven experimental design allowed the use of a single FRET pair for measurements of both transfer functions of the pathway.

The adaptation module's transfer function revealed that feedback near steady state is weak, consistent with high sensitivity to shallow gradients, but also strong steady-state fluctuations in pathway output.

The measured response to oscillatory stimuli defines the frequency band over which the chemotaxis system can compute time derivatives.

In searching for better environments, bacteria sample their surroundings by random motility, and make temporal comparisons of experienced sensory cues to bias their movement toward favorable directions (Berg and Brown, 1972). Thus, the problem of sensing spatial gradients is reduced to time-derivative computations, carried out by a signaling pathway that is well characterized at the molecular level in Escherichia coli. Here, we study the physiology of this signal processing system in vivo by fluorescence resonance energy transfer (FRET) experiments in which live cells are stimulated by time-varying chemoeffector signals. By measuring FRET between the active response regulator of the pathway CheY-P and its phosphatase CheZ, each labeled with GFP variants, we obtain a readout that is directly proportional to pathway activity (Sourjik et al, 2007). We analyze the measured response functions in terms of mechanistic models of signaling, and discuss functional consequences of the observed quantitative characteristics.

Experiments are guided by a coarse-grained modular model (Tu et al, 2008) of the sensory network (Figure 1), in which we identify two important ‘transfer functions': one corresponding to the receptor–kinase complex, which responds to changes in input ligand concentration on a fast time scale, and another corresponding to the adaptation system, which provides negative feedback, opposing the effect of ligand on a slower time scale. For the receptor module, we calibrate an allosteric MWC-type model of the receptor–kinase complex by FRET measurements of the ‘open-loop' transfer function G([L],m) using step stimuli. This calibration provides a basis for using the same FRET readout (between CheY-P and CheZ) to further study properties of the adaptation module.

It is well known that adaptation in E. coli's chemotaxis system uses integral feedback, which guarantees exact restoration of the baseline activity after transient responses to step stimuli (Barkai and Leibler, 1997; Yi et al, 2000). However, the output of time-derivative computations during smoothly varying stimuli depends not only on the presence of integral feedback, but also on what is being integrated. As this integrand can in general be any function of the output, we represent it by a black-box function F(a) in our model, and set out to determine its shape by experiments with time-varying stimuli.

We first apply exponential ramp stimuli—waveforms in which the logarithm of the stimulus level varies linearly with time, at a fixed rate r. It was shown many years ago that during such a stimulus, the kinase output of the pathway changes to a new constant value, a_c that is dependent on the applied ramp rate, r (Block et al, 1983). A plot of a_c versus r (Figure 5A) can thus be considered as an output of time-derivative computations by the network, and could also be used to study the ‘gradient sensitivity' of bacteria traveling at constant speeds.

To obtain the feedback transfer function, F(a), we apply a simple coordinate transformation, identified using our model, to the same ramp-response data (Figure 5B). This function reveals how the temporal rate of change of the feedback signal m depends on the current output signal a. The shape of this function is analyzed using a biochemical reaction scheme, from which in vivo kinetic parameters of the feedback enzymes, CheR and CheB, are extracted. The fitted Michaelis constants for these enzymatic reactions are small compared with the steady-state abundance of their substrates, thus indicating that these enzymes operate close to saturation in vivo. The slope of the function near steady state can be used to assess the strength of feedback, and to compute the relaxation time of the system, τ_m. Relaxation is found to be slow (i.e. large τ_m), consistent with large fluctuations about the steady-state activity caused by the near-saturation kinetics of the feedback enzymes (Emonet and Cluzel, 2008).

Finally, exponential sine-wave stimuli are used to map out the system's frequency response (Figure 5C). The measured data points for both the amplitude and phase of the response are found to be in excellent agreement with model predictions based on parameters from the independently measured step and ramp responses. No curve fitting was required to obtain this agreement. Although the amplitude response as a function of frequency resembles a first-order high-pass filter with a well-defined cutoff frequency, ν_m, we point out that the chemotaxis pathway is actually a low-pass filter if the time derivative of the input is viewed as the input signal. In this latter perspective, ν_m defines an upper bound for the frequency band over which time-derivative computations can be carried out.

The two types of measurements yield complementary information regarding time-derivative computations by E. coli. The ramp-responses characterize the asymptotically constant output when a temporal gradient is held fixed over extended periods. Interestingly, the ramp responses do not depend on receptor cooperativity, but only on properties of the adaptation system, and thus can be used to reveal the in vivo adaptation kinetics, even outside the linear regime of the kinase response. The frequency response is highly relevant in considering spatial searches in the real world, in which experienced gradients are not held fixed in time. The characteristic cutoff frequency ν_m is found by working within the linear regime of the kinase response, and depends on parameters from both modules (it increases with both cooperativity in the receptor module, and the strength of feedback in the adaptation module).

Both ramp responses and sine-wave responses were measured at two different temperatures (22 and 32°C), and found to differ significantly. Both the slope of F(a) near steady state, from ramp experiments, and the characteristic cutoff frequency, from sine-wave experiments, were higher by a factor of ∼3 at 32°C. Fits of the enzymatic model to F(a) suggest that temperature affects the maximal velocity (V_max) more strongly than the Michaelis constants (K_m) for CheR and CheB.

Successful application of inter-molecular FRET in live cells using GFP variants always requires some degree of serendipity. Genetic fusions to these bulky fluorophores can impair the function of the original proteins, and even when fusions are functional, efficient FRET still requires the fused fluorophores to come within the small (<10 nm) Förster radius on interactions between the labeled proteins. Thus, when a successful FRET pair is identified, it is desirable to make the most of it. We have shown here that combined with careful temporal control of input stimuli, and appropriately calibrated models, a single FRET pair can be used to study the structure of multiple transfer functions within a signaling network.

The Escherichia coli chemotaxis-signaling pathway computes time derivatives of chemoeffector concentrations. This network features modules for signal reception/amplification and robust adaptation, with sensing of chemoeffector gradients determined by the way in which these modules are coupled in vivo. We characterized these modules and their coupling by using fluorescence resonance energy transfer to measure intracellular responses to time-varying stimuli. Receptor sensitivity was characterized by step stimuli, the gradient sensitivity by exponential ramp stimuli, and the frequency response by exponential sine-wave stimuli. Analysis of these data revealed the structure of the feedback transfer function linking the amplification and adaptation modules. Feedback near steady state was found to be weak, consistent with strong fluctuations and slow recovery from small perturbations. Gradient sensitivity and frequency response both depended strongly on temperature. We found that time derivatives can be computed by the chemotaxis system for input frequencies below 0.006 Hz at 22°C and below 0.018 Hz at 32°C. Our results show how dynamic input–output measurements, time honored in physiology, can serve as powerful tools in deciphering cell-signaling mechanisms.