Mechanical Fluidity of Fully Suspended Biological Cells

Mechanical characteristics of single biological cells are used to identify and possibly leverage interesting differences among cells or cell populations. Fluidity—hysteresivity normalized to the extremes of an elastic solid or a viscous liquid—can be extracted from, and compared among, multiple rheological measurements of cells: creep compliance versus time, complex modulus versus frequency, and phase lag versus frequency. With multiple strategies available for acquisition of this nondimensional property, fluidity may serve as a useful and robust parameter for distinguishing cell populations, and for understanding the physical origins of deformability in soft matter. Here, for three disparate eukaryotic cell types deformed in the suspended state via optical stretching, we examine the dependence of fluidity on chemical and environmental influences at a timescale of ∼1 s. We find that fluidity estimates are consistent in the time and frequency domains under a structural damping (power-law or fractional-derivative) model, but not under an equivalent-complexity, lumped-component (spring-dashpot) model; the latter predicts spurious time constants. Although fluidity is suppressed by chemical cross-linking, we find that ATP depletion in the cell does not measurably alter the parameter, and we thus conclude that active ATP-driven events are not a crucial enabler of fluidity during linear viscoelastic deformation of a suspended cell. Finally, by using the capacity of optical stretching to produce near-instantaneous increases in cell temperature, we establish that fluidity increases with temperature—now measured in a fully suspended, sortable cell without the complicating factor of cell-substratum adhesion.     

Mesenchymal stem cell mechanics from the attached to the suspended state

Human mesenchymal stem cells (hMSCs) are therapeutically useful cells that are typically expanded in vitro on stiff substrata before reimplantation. Here we explore MSC mechanical and structural changes via atomic force microscopy and optical stretching during extended passaging, and we demonstrate that cytoskeletal organization and mechanical stiffness of attached MSC populations are strongly modulated over >15 population doublings in vitro. Cytoskeletal actin networks exhibit significant coarsening, attendant with decreasing average mechanical compliance and differentiation potential of these cells, although expression of molecular surface markers does not significantly decline. These mechanical changes are not observed in the suspended state, indicating that the changes manifest themselves as alterations in stress fiber arrangement rather than cortical cytoskeleton arrangement. Additionally, optical stretching is capable of investigating a previously unquantified structural transition: remodeling-induced stiffening over tens of minutes after adherent cells are suspended. Finally, we find that optically stretched hMSCs exhibit power-law rheology during both loading and recovery; this evidence appears to be the first to originate from a biophysical measurement technique not involving cell-probe or cell-substratum contact. Together, these quantitative assessments of attached and suspended MSCs define the extremes of the extracellular environment while probing intracellular mechanisms that contribute to cell mechanical response.     

Effect of cellular rearrangement time delays on the rheology of vertex models for confluent tissues

Large-scale tissue deformation during biological processes such as morphogenesis requires cellular rearrangements. The simplest rearrangement in confluent cellular monolayers involves neighbor exchanges among four cells, called a T1 transition, in analogy to foams. But unlike foams, cells must execute a sequence of molecular processes, such as endocytosis of adhesion molecules, to complete a T1 transition. Such processes could take a long time compared to other timescales in the tissue. In this work, we incorporate this idea by augmenting vertex models to require a fixed, finite time for T1 transitions, which we call the “T1 delay time”. We study how variations in T1 delay time affect tissue mechanics, by quantifying the relaxation time of tissues in the presence of T1 delays and comparing that to the cell-shape based timescale that characterizes fluidity in the absence of any T1 delays. We show that the molecular-scale T1 delay timescale dominates over the cell shape-scale collective response timescale when the T1 delay time is the larger of the two. We extend this analysis to tissues that become anisotropic under convergent extension, finding similar results. Moreover, we find that increasing the T1 delay time increases the percentage of higher-fold coordinated vertices and rosettes, and decreases the overall number of successful T1s, contributing to a more elastic-like—and less fluid-like—tissue response. Our work suggests that molecular mechanisms that act as a brake on T1 transitions could stiffen global tissue mechanics and enhance rosette formation during morphogenesis.     

Reconstructing Local Population Dynamics in Noisy Metapopulations—The Role of Random Catastrophes and Allee Effects

Reconstructing the dynamics of populations is complicated by the different types of stochasticity experienced by populations, in particular if some forms of stochasticity introduce bias in parameter estimation in addition to error. Identification of systematic biases is critical when determining whether the intrinsic dynamics of populations are stable or unstable and whether or not populations exhibit an Allee effect, i.e., a minimum size below which deterministic extinction should follow. Using a simulation model that allows for Allee effects and a range of intrinsic dynamics, we investigated how three types of stochasticity—demographic, environmental, and random catastrophes— affect our ability to reconstruct the intrinsic dynamics of populations. Demographic stochasticity aside, which is only problematic in small populations, we find that environmental stochasticity—positive and negative environmental fluctuations—caused increased error in parameter estimation, but bias was rarely problematic, except at the highest levels of noise. Random catastrophes, events causing large-scale mortality and likely to be more common than usually recognized, caused immediate bias in parameter estimates, in particular when Allee effects were large. In the latter case, population stability was predicted when endogenous dynamics were actually unstable and the minimum viable population size was overestimated in populations with small or non-existent Allee effects. Catastrophes also generally increased extinction risk, in particular when endogenous Allee effects were large. We propose a method for identifying data points likely resulting from catastrophic events when such events have not been recorded. Using social spider colonies (Anelosimus spp.) as models for populations, we show that after known or suspected catastrophes are accounted for, reconstructed growth parameters are consistent with intrinsic dynamical instability and substantial Allee effects. Our results are applicable to metapopulation or time series data and are relevant for predicting extinction in conservation applications or the management of invasive species.     

Single-cell variation leads to population invariance in NF-κB signaling dynamics

The activation dynamics of nuclear factor (NF)-κB have been shown to affect downstream gene expression. On activation, NF-κB shuttles back and forth across the nuclear envelope. Many dynamic features of this shuttling have been characterized, and most features vary significantly with respect to ligand type and concentration. Here, we report an invariant feature with regard to NF-κB dynamics in cellular populations: the distribution—the average, as well as the variance—of the time between two nuclear entries (the period). We find that this period is conserved, regardless of concentration and across several different ligands. Intriguingly, the distributions observed at the population level are not observed in individual cells over 20-h time courses. Instead, the average period of NF-κB nuclear translocation varies considerably among single cells, and the variance is much smaller within a cell than that of the population. Finally, analysis of daughter-cell pairs and isogenic populations indicates that the dynamics of the NF-κB response is heritable but diverges over multiple divisions, on the time scale of weeks to months. These observations are contrary to the existing theory of NF-κB dynamics and suggest an additional level of control that regulates the overall distribution of translocation timing at the population level.     

A Population Genomic Assessment of Three Decades of Evolution in a Natural Drosophila Population

Population genetics seeks to illuminate the forces shaping genetic variation, often based on a single snapshot of genomic variation. However, utilizing multiple sampling times to study changes in allele frequencies can help clarify the relative roles of neutral and non-neutral forces on short time scales. This study compares whole-genome sequence variation of recently collected natural population samples of Drosophila melanogaster against a collection made approximately 35 years prior from the same locality—encompassing roughly 500 generations of evolution. The allele frequency changes between these time points would suggest a relatively small local effective population size on the order of 10,000, significantly smaller than the global effective population size of the species. Some loci display stronger allele frequency changes than would be expected anywhere in the genome under neutrality—most notably the tandem paralogs Cyp6a17 and Cyp6a23, which are impacted by structural variation associated with resistance to pyrethroid insecticides. We find a genome-wide excess of outliers for high genetic differentiation between old and new samples, but a larger number of adaptation targets may have affected SNP-level differentiation versus window differentiation. We also find evidence for strengthening latitudinal allele frequency clines: northern-associated alleles have increased in frequency by an average of nearly 2.5% at SNPs previously identified as clinal outliers, but no such pattern is observed at random SNPs. This project underscores the scientific potential of using multiple sampling time points to investigate how evolution operates in natural populations, by quantifying how genetic variation has changed over ecologically relevant timescales.     

Allele frequency divergence reveals ubiquitous influence of positive selection in Drosophila

Resolving the role of natural selection is a basic objective of evolutionary biology. It is generally difficult to detect the influence of selection because ubiquitous non-selective stochastic change in allele frequencies (genetic drift) degrades evidence of selection. As a result, selection scans typically only identify genomic regions that have undergone episodes of intense selection. Yet it seems likely such episodes are the exception; the norm is more likely to involve subtle, concurrent selective changes at a large number of loci. We develop a new theoretical approach that uncovers a previously undocumented genome-wide signature of selection in the collective divergence of allele frequencies over time. Applying our approach to temporally resolved allele frequency measurements from laboratory and wild Drosophila populations, we quantify the selective contribution to allele frequency divergence and find that selection has substantial effects on much of the genome. We further quantify the magnitude of the total selection coefficient (a measure of the combined effects of direct and linked selection) at a typical polymorphic locus, and find this to be large (of order 1%) even though most mutations are not directly under selection. We find that selective allele frequency divergence is substantially elevated at intermediate allele frequencies, which we argue is most parsimoniously explained by positive—not negative—selection. Thus, in these populations most mutations are far from evolving neutrally in the short term (tens of generations), including mutations with neutral fitness effects, and the result cannot be explained simply as an ongoing purging of deleterious mutations.     

Derivation of the frequency distributions of cycle durations from continuous labeling curves

In cell populations that are continuously exposed to radioactive thymidine over a long period, all proliferating cells become labeled as they pass through their DNA-replicating phase. The continuous labeling curve (CLC) shows the percentage of labeled cells versus time. Expected CLCs are calculated for cell populations with arbitrary frequency distributions of cycle durations. By optimizing the parameter values of a general probability function in the formula for CLC, frequency distributions of cycle durations are estimated from experimental CLCs. The analysis of several fetal rat tissues shows that the cycle durations vary over quite a wide range within the same tissue.     

Optogenetic versus Electrical Stimulation of Human Cardiomyocytes: Modeling Insights

Optogenetics provides an alternative to electrical stimulation to manipulate membrane voltage, and trigger or modify action potentials (APs) in excitable cells. We compare biophysically and energetically the cellular responses to direct electrical current injection versus optical stimulation mediated by genetically expressed light-sensitive ion channels, e.g., Channelrhodopsin-2 (ChR2). Using a computational model of ChR2(H134R mutant), we show that both stimulation modalities produce similar-in-morphology APs in human cardiomyocytes, and that electrical and optical excitability vary with cell type in a similar fashion. However, whereas the strength-duration curves for electrical excitation in ventricular and atrial cardiomyocytes closely follow the theoretical exponential relationship for an equivalent RC circuit, the respective optical strength-duration curves significantly deviate, exhibiting higher nonlinearity. We trace the origin of this deviation to the waveform of the excitatory current—a nonrectangular self-terminating inward current produced in optical stimulation due to ChR2 kinetics and voltage-dependent rectification. Using a unifying charge measure to compare energy needed for electrical and optical stimulation, we reveal that direct electrical current injection (rectangular pulse) is more efficient at short pulses, whereas voltage-mediated negative feedback leads to self-termination of ChR2 current and renders optical stimulation more efficient for long low-intensity pulses. This applies to cardiomyocytes but not to neuronal cells (with much shorter APs). Furthermore, we demonstrate the cell-specific use of ChR2 current as a unique modulator of intrinsic activity, allowing for optical control of AP duration in atrial and, to a lesser degree, in ventricular myocytes. For self-oscillatory cells, such as Purkinje, constant light at extremely low irradiance can be used for fine control of oscillatory frequency, whereas constant electrical stimulation is not feasible due to electrochemical limitations. Our analysis offers insights for designing future new energy-efficient stimulation strategies in heart or brain.     

Sublethal Supraphysiological Shear Stress Alters Erythrocyte Dynamics in Subsequent Low-Shear Flows

Blood is a non-Newtonian, shear-thinning fluid owing to the physical properties and behaviors of red blood cells (RBCs). Under increased shear flow, pre-existing clusters of cells disaggregate, orientate with flow, and deform. These essential processes enhance fluidity of blood, although accumulating evidence suggests that sublethal blood trauma—induced by supraphysiological shear exposure—paradoxically increases the deformability of RBCs when examined under low-shear conditions, despite obvious decrement of cellular deformation at moderate-to-higher shear stresses. Some propose that rather than actual enhancement of cell mechanics, these observations are “pseudoimprovements” and possibly reflect altered flow and/or cell orientation, leading to methodological artifacts, although direct evidence is lacking. This study thus sought to explore RBC mechanical responses in shear flow using purpose-built laser diffractometry in tandem with direct optical visualization to address this problem. Freshly collected RBCs were exposed to a mechanical stimulus known to drastically alter cell deformability (i.e., prior shear exposure (PSE) to 100 Pa × 300 s). Samples were subsequently transferred to a custom-built slit-flow chamber that combined laser diffractometry with direct cell visualization. Cell suspensions were sheared in a stepwise manner (between 0.3 and 5.0 Pa), with each step being maintained for 15 s. Deformability and cell orientation indices were recorded for small-scatter Fraunhofer diffraction patterns and also visualized RBCs. PSE RBCs had significantly decreased visualized and laser-derived deformability at any given shear stress ≥1 Pa. Novel, to our knowledge, observations demonstrated that PSE RBCs had increased heterogeneity of direct visualized orientation with flow vector at any shear, which may be due to greater vorticity and thus instability in 5-Pa flow compared with unsheared control. These findings indicate that shear exposure and stress-strain history can alter subsequent RBC behavior in physiologically relevant low-shear flows. These findings may yield insight into microvascular disorders in recipients of mechanical circulatory support and individuals with hematological diseases that alter physical properties of blood.     

Segregational Drift Constrains the Evolutionary Rate of Prokaryotic Plasmids

Plasmids are extrachromosomal genetic elements in prokaryotes that have been recognized as important drivers of microbial ecology and evolution. Plasmids are found in multiple copies inside their host cell where independent emergence of mutations may lead to intracellular genetic heterogeneity. The intracellular plasmid diversity is thus subject to changes upon cell division. However, the effect of plasmid segregation on plasmid evolution remains understudied. Here, we show that genetic drift during cell division—segregational drift—leads to the rapid extinction of novel plasmid alleles. We established a novel experimental approach to control plasmid allele frequency at the levels of a single cell and the whole population. Following the dynamics of plasmid alleles in an evolution experiment, we find that the mode of plasmid inheritance—random or clustered—is an important determinant of plasmid allele dynamics. Phylogenetic reconstruction of our model plasmid in clinical isolates furthermore reveals a slow evolutionary rate of plasmid-encoded genes in comparison to chromosomal genes. Our study provides empirical evidence that genetic drift in plasmid evolution occurs at multiple levels: the host cell and the population of hosts. Segregational drift has implications for the evolutionary rate heterogeneity of extrachromosomal genetic elements.     

Tunable Chemokine Production by Antigen Presenting Dendritic Cells in Response to Changes in Regulatory T Cell Frequency in Mouse Reactive Lymph Nodes

Background

Although evidence exists that regulatory T cells (Tregs) can suppress the effector phase of immune responses, it is clear that their major role is in suppressing T cell priming in secondary lymphoid organs. Recent experiments using two photon laser microscopy indicate that dendritic cells (DCs) are central to Treg cell function and that the in vivo mechanisms of T cell regulation are more complex than those described in vitro.

Principal Findings

Here we have sought to determine whether and how modulation of Treg numbers modifies the lymph node (LN) microenvironment. We found that pro-inflammatory chemokines—CCL2 (MCP-1) and CCL3 (MIP-la)—are secreted in the LN early (24 h) after T cell activation, that this secretion is dependent on antigen-specific DC–T cell interactions, and that it was inversely related to the frequency of Tregs specific for the same antigen. Furthermore, we demonstrate that Tregs modify the chemoattractant properties of antigen-presenting DCs, which, as the frequency of Tregs increases, fail to produce CCL2 and CCL3 and to attract antigen-specific T cells.

Conclusions

These results substantiate a major role of Tregs in LN patterning during antigen-specific immune responses.     

Coupling the cell cycle to cell growth

In order to multiply, both prokaryotic and eukaryotic cells go through a series of events that are collectively called the cell cycle. However, DNA replication, mitosis and cell division may also be viewed as having their own, in principle independent, cycles, which are tied together by mechanisms extrinsic to the cell cycle—the checkpoints—that maintain the order of events. We propose that our understanding of cell-cycle regulation is enhanced by viewing each event individually, as an independently regulated process. The nature of the parameters that regulate cell-cycle events is discussed and, in particular, we argue that cell mass is not such a parameter.     

The frustrated brain: from dynamics on motifs to communities and networks

Cognitive function depends on an adaptive balance between flexible dynamics and integrative processes in distributed cortical networks. Patterns of zero-lag synchrony likely underpin numerous perceptual and cognitive functions. Synchronization fulfils integration by reducing entropy, while adaptive function mandates that a broad variety of stable states be readily accessible. Here, we elucidate two complementary influences on patterns of zero-lag synchrony that derive from basic properties of brain networks. First, mutually coupled pairs of neuronal subsystems—resonance pairs—promote stable zero-lag synchrony among the small motifs in which they are embedded, and whose effects can propagate along connected chains. Second, frustrated closed-loop motifs disrupt synchronous dynamics, enabling metastable configurations of zero-lag synchrony to coexist. We document these two complementary influences in small motifs and illustrate how these effects underpin stable versus metastable phase-synchronization patterns in prototypical modular networks and in large-scale cortical networks of the macaque (CoCoMac). We find that the variability of synchronization patterns depends on the inter-node time delay, increases with the network size and is maximized for intermediate coupling strengths. We hypothesize that the dialectic influences of resonance versus frustration may form a dynamic substrate for flexible neuronal integration, an essential platform across diverse cognitive processes.     

Novel Applications of Magnetic Cell Sorting to Analyze Cell-Type Specific Gene and Protein Expression in the Central Nervous System

The isolation and study of cell-specific populations in the central nervous system (CNS) has gained significant interest in the neuroscience community. The ability to examine cell-specific gene and protein expression patterns in healthy and pathological tissue is critical for our understanding of CNS function. Several techniques currently exist to isolate cell-specific populations, each having their own inherent advantages and shortcomings. Isolation of distinct cell populations using magnetic sorting is a technique which has been available for nearly 3 decades, although rarely used in adult whole CNS tissue homogenate. In the current study we demonstrate that distinct cell populations can be isolated in rodents from early postnatal development through adulthood. We found this technique to be amendable to customization using commercially available membrane-targeted antibodies, allowing for cell-specific isolation across development and animal species. This technique yields RNA which can be utilized for downstream applications—including quantitative PCR and RNA sequencing—at relatively low cost and without the need for specialized equipment or fluorescently labeled cells. Adding to its utility, we demonstrate that cells can be isolated largely intact, retaining their processes, enabling analysis of extrasomatic proteins. We propose that magnetic cell sorting will prove to be a highly useful technique for the examination of cell specific CNS populations.     

STUDIES ON CELL ADHESION : III. Adhesion of Baby Hamster Kidney Cells

Normal and transformed baby hamster kidney (BHK) cells attach to Falcon polystyrene with the same first order rate constant. The longer the cells are attached to the bottles, the more difficult they are to remove. Sulfhydryl (—SH) binding reagents inhibit both the attachment of BHK cells and the increase in adhesive strength of attached cells. Attached BHK cells bind fewer molecules of [1-¹⁴C]N-ethylamleimide (an —SH binding reagent) than do suspended cells. Incubation of cells with high concentrations of trypsin results in a reversible loss of cell adhesiveness. The recovery of adhesiveness of trypsin-treated cells is inhibited by cycloheximide.     

Laurdan Fluorescence Lifetime Discriminates Cholesterol Content from?Changes in Fluidity in Living Cell Membranes

Detection of the fluorescent properties of Laurdan has been proven to be an efficient tool to investigate membrane packing and ordered lipid phases in model membranes and living cells. Traditionally the spectral shift of Laurdan’s emission from blue in the ordered lipid phase of the membrane (more rigid) toward green in the disordered lipid phase (more fluid) is quantified by the generalized polarization function. Here, we investigate the fluorescence lifetime of Laurdan at two different emission wavelengths and find that when the dipolar relaxation of Laurdan’s emission is spectrally isolated, analysis of the fluorescence decay can distinguish changes in membrane fluidity from changes in cholesterol content. Using the phasor representation to analyze changes in Laurdan’s fluorescence lifetime we obtain two different phasor trajectories for changes in polarity versus changes in cholesterol content. This gives us the ability to resolve in vivo membranes with different properties such as water content and cholesterol content and thus perform a more comprehensive analysis of cell membrane heterogeneity. We demonstrate this analysis in NIH3T3 cells using Laurdan as a biosensor to monitor changes in the membrane water content during cell migration.     

Detecting Selection on Temporal and Spatial Scales: A Genomic Time-Series Assessment of Selective Responses to Devil Facial Tumor Disease

Detecting loci under selection is an important task in evolutionary biology. In conservation genetics detecting selection is key to investigating adaptation to the spread of infectious disease. Loci under selection can be detected on a spatial scale, accounting for differences in demographic history among populations, or on a temporal scale, tracing changes in allele frequencies over time. Here we use these two approaches to investigate selective responses to the spread of an infectious cancer—devil facial tumor disease (DFTD)—that since 1996 has ravaged the Tasmanian devil (Sarcophilus harrisii). Using time-series ‘restriction site associated DNA’ (RAD) markers from populations pre- and post DFTD arrival, and DFTD free populations, we infer loci under selection due to DFTD and investigate signatures of selection that are incongruent among methods, populations, and times. The lack of congruence among populations influenced by DFTD with respect to inferred loci under selection, and the direction of that selection, fail to implicate a consistent selective role for DFTD. Instead genetic drift is more likely driving the observed allele frequency changes over time. Our study illustrates the importance of applying methods with different performance optima e.g. accounting for population structure and background selection, and assessing congruence of the results.