Biofilm formation and manipulation with optical tweezers.

Some bacterial species form biofilms in suboptimal growth and environmental conditions. Biofilm structures allow the cells not only to optimize growth with nutrient availability but also to defend each other against external stress, such as antibiotics. Medical and bioengineering implications of biofilms have led to an increased interest in the regulation of bacterial biofilm formation. Prior research has primarily focused on mechanical and chemical approaches for stimulating and controlling biofilm formation, yet optical techniques are still largely unexplored. In this paper, we investigate the biofilm formation of Bacillus subtilis in a minimum biofilm-promoting medium (MSgg media) and explore the potential of optical trapping in regulating bacterial aggregation and biofilm development. Specifically, we determine the most advantageous stage of bacterial biofilm formation for optical manipulation and investigate the impact of optical trapping at different wavelengths on the aggregation of bacterial cells and the formation of biofilm. The investigation of optically regulated biofilm formation with optical tweezers presents innovative methodologies for the stimulation and suppression of biofilm growth through the application of lasers.

Modeling selectivity of antimicrobial peptides: how it depends on the presence of host cells and cell density.

Antimicrobial peptides (AMPs), naturally-occurring peptide antibiotics, are known to attack bacteria selectively over the host cells. The emergence of drug-resistant bacteria has spurred much effort in utilizing optimized (more selective) AMPs as new peptide antibiotics. Cell selectivity of these peptides depends on various factors or parameters such as their binding affinity for cell membranes, peptide trapping in cells, peptide coverages on cell membranes required for membrane rupture, and cell densities. In this work, using a biophysical model of peptide selectivity, we show this dependence quantitatively especially for a mixture of bacteria and host cells. The model suggests a rather nontrivial dependence of the selectivity on the presence of host cells, cell density, and peptide trapping. In a typical biological setting, peptide trapping works in favor of host cells; the selectivity increases with increasing host-cell density but decreases with bacterial cell density. Because of the cell-density dependence of peptide activity, the selectivity can be overestimated by two or three orders of magnitude. The model also clarifies how the cell selectivity of AMPs differs from their membrane selectivity.

Modeling Cell Selectivity of Antimicrobial Peptides: How Is the Selectivity Influenced by Intracellular Peptide Uptake and Cell Density.

Antimicrobial peptides (AMPs) are known to attack bacteria selectively over their host cells. Many attempts have been made to use them as a template for designing peptide antibiotics for fighting drug-resistant bacteria. A central concept in this endeavor is "peptide selectivity," which measures the "quality" of peptides. However, the relevance of selectivity measurements has often been obscured by the cell-density dependence of the selectivity. For instance, the selectivity can be overestimated if the cell density is larger for the host cell. Furthermore, recent experimental studies suggest that peptide trapping in target bacteria magnifies the cell-density dependence of peptide activity. Here, we propose a biophysical model for peptide activity and selectivity, which assists with the correct interpretation of selectivity measurements. The resulting model shows how cell density and peptide trapping in cells influence peptide activity and selectivity: while these effects can alter the selectivity by more than an order of magnitude, peptide trapping works in favor of host cells at high host-cell densities. It can be used to correct selectivity overestimates.

Toward building a physical model for membrane selectivity of antimicrobial peptides: making a quantitative sense of the selectivity.

Antimicrobial peptides (AMPs) are naturally-occurring peptide antibiotics. AMPs are typically cationic and utilize their electrostatic interactions with the bacterial membrane to selectively attack bacteria. The way they work has inspired a vigorous search for optimized peptides for fighting resistant bacteria. Here, we present a physical model of membrane selectivity of AMPs. The challenge for theoretical modeling of membrane-peptide systems arises from the simultaneous presence of several competing effects, including lipid demixing and peptide-peptide interactions on the membrane surface. We first examine critically a number of models of peptide-membrane interactions and map out one, which incorporates adequately these competing effects as well as the geometry of various regions in membranes, occupied by bound peptides, anionic lipids within the interaction range of each peptide, and those outside this range. This effort leads to a systematically-improved model for peptide selectivity. Using the model, we relate peptide's intrinsic (Ccell-independent) selectivity to an apparent, Ccell-dependent one, and clarify the relative roles of peptide parameters and cell densities in determining their selectivity. This relationship suggests that the selectivity is more sensitive to peptide parameters at low cell densities; as a result, the optimal peptide charge, at which the selectivity is maximized, increases with the cell density in such a manner that this notion becomes less meaningful at high cell densities.

One is Nothing without the Other: Theoretical and Empirical Analysis of Cell Growth and Cell Cycle Progression.

Small, fast-growing bacteria make ideal subjects for genetic and quantitative analysis alike. Long the darling of theoreticians, efforts to understand the relationship between cell growth and cell cycle progression in bacterial systems have been propelled by modelers and empiricist in equal measure. Taking a historical approach, here we break down early work in this area, the impact it had on how the bacterial cell cycle is understood and interrogated, and changes brought by the advent of high-throughput techniques for the analysis of individual bacterial cells in culture.

Tuning optimum transfection of gemini surfactant-phospholipid-DNA nanoparticles by validated theoretical modeling.

Gemini nanoparticles (NPs) are a family of non-viral gene delivery systems with potential for applications in non-invasive gene therapy. Translation of these non-viral gene delivery systems requires improvement of transfection efficiency (TE) through fine-tuning of their physicochemical properties such as electric charge and exact ratios of their components. Since high-throughput experimental screening of minute differences in NP compositions is not routinely feasible, we have developed a coarse-grained model to quantitatively study the energetics of the formation of gene delivery complexes with cationic gemini surfactants (G) (m-s-m type) and helper lipids (H) (1,2-dioleoyl-sn-glycero-3-phosphoethanolamine (DOPE) and DOPE/1,2-dipalmitoyl-sn-glycerol-3-phosphocholine (DPPC)), in order to use it as a tool to predict effective compositions. The model is based on the polymorphic structural conformational flip of NPs and incorporates the electrostatic, entropic and elastic energies, to predict the formation energy and stability of different polymorphic structures as a function of the electric charge of cationic surfactants and concentration of constituent helper lipids. Our results show that these two factors are intertwined in determining the behavior of gene delivery vectors. Specifically, we show that increasing H/G lowers free energy per DNA base pair and increases the stability of the complex. At pH 7, low H/G and charge ratio (ρ±), where the lamellar structure is favored, the formation free energy per DNA base pair is between 0 and -14kBT. At higher values of H/G (2-3) and ρ±, where HII and cubic structures are formed, the formation free energy drops down to values ≈-50kBT, indicating the stable existence of these polymorphic structures in the NPs. At pH 5, the structural transformation of NPs in the endosomes to the lamellar/HII structure with free energy values of about -40kBT is beneficial for endosomal escape, and correlates with increased transfection efficiency. The theoretical model is supported by transfection data in A7 astrocytes with a panel of 16-3-16 gemini NPs, which validates the mathematical model and supports the hypothesis that the NP polymorphic phase transition increases transfection efficiency.

Heterogeneous absorption of antimicrobial peptide LL37 in Escherichia coli cells enhances population survivability.

Antimicrobial peptides (AMPs) are broad spectrum antibiotics that selectively target bacteria. Here we investigate the activity of human AMP LL37 against Escherichia coli by integrating quantitative, population and single-cell level experiments with theoretical modeling. We observe an unexpected, rapid absorption and retention of a large number of LL37 peptides by E. coli cells upon the inhibition of their growth, which increases population survivability. This transition occurs more likely in the late stage of cell division cycles. Cultures with high cell density exhibit two distinct subpopulations: a non-growing population that absorb peptides and a growing population that survive owing to the sequestration of the AMPs by others. A mathematical model based on this binary picture reproduces the rather surprising observations, including the increase of the minimum inhibitory concentration with cell density (even in dilute cultures) and the extensive lag in growth introduced by sub-lethal dosages of LL37 peptides.

Self-Consistent Examination of Donachie's Constant Initiation Size at the Single-Cell Level.

How growth, the cell cycle, and cell size are coordinated is a fundamental question in biology. Recently, we and others have shown that bacterial cells grow by a constant added size per generation, irrespective of the birth size, to maintain size homeostasis. This "adder" principle raises a question as to when during the cell cycle size control is imposed. Inspired by this question, we examined our single-cell data for initiation size by employing a self-consistency approach originally used by Donachie. Specifically, we assumed that individual cells divide after constant C + D minutes have elapsed since initiation, independent of the growth rate. By applying this assumption to the cell length vs. time trajectories from individual cells, we were able to extract theoretical probability distribution functions for initiation size for all growth conditions. We found that the probability of replication initiation shows peaks whenever the cell size is a multiple of a constant unit size, consistent with the Donachie's original analysis at the population level. Our self-consistent examination of the single-cell data made experimentally testable predictions, e.g., two consecutive replication cycles can be initiated during a single cell-division cycle.

How Cell Concentrations Are Implicated in Cell Selectivity of Antimicrobial Peptides.

Antimicrobial peptides (AMPs) are known to selectively bind to and kill microbes over host cells. Contrary to a conventional view, there is now evidence that AMP's cell selectivity varies with cell densities and is not uniquely determined. Using a coarse-grained model, we study how the cell selectivity of membrane-lytic AMPs, defined as the ratio between their minimum hemolytic (MHC) and minimum inhibitory concentrations (MIC), depends on cell densities or on the way it is measured. A general picture emerging from our study is that the selectivity better captures peptide's intrinsic properties at low cell densities. The selectivity, however, decreases and becomes less intrinsic as the cell density increases, as long as it is chosen to be the same for both types of cells. Importantly, our results show that the selectivity can be excessively overestimated if higher host cell concentrations are used; in contrast, it becomes mistakenly small if measured for a mixture of both types of cells, even with similar choices of cell densities (i.e., higher host cell densities). Our approach can be used as a fitting model for relating the intrinsic selectivity to the apparent (cell-density-dependent) one.

Single-Cell Physiology.

Single-cell techniques have a long history of unveiling fundamental paradigms in biology. Recent improvements in the throughput, resolution, and availability of microfluidics, computational power, and genetically encoded fluorescence have led to a modern renaissance in microbial physiology. This resurgence in research activity has offered new perspectives on physiological processes such as growth, cell cycle, and cell size of model organisms such as Escherichia coli. We expect these single-cell techniques, coupled with the molecular revolution of biology's recent half-century, to continue illuminating unforeseen processes and patterns in microorganisms, the bedrock of biological science. In this article we review major open questions in single-cell physiology, provide a brief introduction to the techniques for scientists of diverse backgrounds, and highlight some pervasive issues and their solutions.

Cell-size control and homeostasis in bacteria.

How cells control their size and maintain size homeostasis is a fundamental open question. Cell-size homeostasis has been discussed in the context of two major paradigms: "sizer," in which the cell actively monitors its size and triggers the cell cycle once it reaches a critical size, and "timer," in which the cell attempts to grow for a specific amount of time before division. These paradigms, in conjunction with the "growth law" [1] and the quantitative bacterial cell-cycle model [2], inspired numerous theoretical models [3-9] and experimental investigations, from growth [10, 11] to cell cycle and size control [12-15]. However, experimental evidence involved difficult-to-verify assumptions or population-averaged data, which allowed different interpretations [1-5, 16-20] or limited conclusions [4-9]. In particular, population-averaged data and correlations are inconclusive as the averaging process masks causal effects at the cellular level. In this work, we extended a microfluidic "mother machine" [21] and monitored hundreds of thousands of Gram-negative Escherichia coli and Gram-positive Bacillus subtilis cells under a wide range of steady-state growth conditions. Our combined experimental results and quantitative analysis demonstrate that cells add a constant volume each generation, irrespective of their newborn sizes, conclusively supporting the so-called constant Δ model. This model was introduced for E. coli [6, 7] and recently revisited [9], but experimental evidence was limited to correlations. This "adder" principle quantitatively explains experimental data at both the population and single-cell levels, including the origin and the hierarchy of variability in the size-control mechanisms and how cells maintain size homeostasis.

Cell-size maintenance: universal strategy revealed.

How cells maintain a stable size has fascinated scientists since the beginning of modern biology, but has remained largely mysterious. Recently, however, the ability to analyze single bacteria in real time has provided new, important quantitative insights into this long-standing question in cell biology.

Electrostatic bending of lipid membranes: how are lipid and electrostatic properties interrelated?

Electrostatic modification of lipid headgroups and its effect on membrane curvature are not only relevant in a variety of contexts such as cell shape transformation and membrane tubulation but also are intriguingly implicated in membrane functions. For instance, the gating (open vs closed) properties of mechanosensitive channels can be influenced by membrane curvature and ion valence. However, a full theoretical description of membrane electrostatics is still lacking; in the past, membrane bending has often been considered under a few assumptions about how bending modifies lipid arrangements and surface charges. Here, we present a unified theoretical approach to spontaneous membrane curvature, C(0), in which lipid properties (e.g., packing shape) and electrostatic effects are self-consistently integrated. For the description of electrostatic interactions, especially between a lipid charge and a divalent counterion, we implement the Poisson-Boltzmann (PB) approach by incorporation of finite ionic sizes, so as to capture both lateral and transverse charge correlations on the membrane surface. Our results show that C(0) is sensitive to the way lipid rearrangements and divalent counterions are modeled. Interestingly, it can change its sign in the presence of divalent counterions, thus stabilizing reverse hexagonal (H(II)) phases. Our results show how electrostatic modification of headgroups influences the preferred structure of lipid aggregates (inverted micelles vs bilayers).

Physical basis for membrane-charge selectivity of cationic antimicrobial peptides.

Antimicrobial peptides are known to selectively disrupt (highly charged) microbial membranes by asymmetrical incorporation into the outer layers. We present a physical basis for membrane-charge selectivity of cationic antimicrobial peptides. In particular, we provide a clear picture of how peptide-charge Q influences the asymmetrical insertion--one salient feature is the existence of an optimal peptide charge, at which selective insertion is optimized. Our results suggest that large Q is required for antimicrobial selectivity, consistent with experiments.

Charge renormalization and inversion of a highly charged lipid bilayer: effects of dielectric discontinuities and charge correlations.

We reexamine the problem of charge renormalization and inversion of a highly charged surface of a low dielectric constant immersed in ionic solutions. To be specific, we consider an asymmetrically charged lipid bilayer, in which only one layer is negatively charged. In particular, we study how dielectric discontinuities and charge correlations (among lipid charges and condensed counterions) influence the effective charge of the surface. When counterions are monovalent (e.g., Na+), our mean-field approach implies that dielectric discontinuities can enhance counterion condensation. A simple scaling picture shows how the effects of dielectric discontinuities and surface-charge distributions are intertwined: Dielectric discontinuities diminish condensation if the backbone charge is uniformly smeared out while counterions are localized in space; they can, however, enhance condensation when the backbone charge is discrete. In the presence of asymmetric salts such as CaCl2 , we find that the correlation effect, treated at the Gaussian level, is more pronounced when the surface has a lower dielectric constant, inverting the sign of the charge at a smaller value of Ca2+ concentration.