Heterogeneous recruitment abilities to RNA polymerases generate nonlinear scaling of gene expression with cell volume

While most genes’ expression levels are proportional to cell volumes, some genes exhibit nonlinear scaling between their expression levels and cell volume. Therefore, their mRNA and protein concentrations change as the cell volume increases, which often have crucial biological functions such as cell-cycle regulation. However, the biophysical mechanism underlying the nonlinear scaling between gene expression and cell volume is still unclear. In this work, we show that the nonlinear scaling is a direct consequence of the heterogeneous recruitment abilities of promoters to RNA polymerases based on a gene expression model at the whole-cell level. Those genes with weaker (stronger) recruitment abilities than the average ability spontaneously exhibit superlinear (sublinear) scaling with cell volume. Analysis of the promoter sequences and the nonlinear scaling of Saccharomyces cerevisiae’s mRNA levels shows that motifs associated with transcription regulation are indeed enriched in genes exhibiting nonlinear scaling, in concert with our model.

Network Model With Reduced Metabolic Rate Predicts Spatial Synchrony of Neuronal Activity

In a cerebral hypometabolic state, cortical neurons exhibit slow synchronous oscillatory activity with sparse firing. How such a synchronization spatially organizes as the cerebral metabolic rate decreases have not been systemically investigated. We developed a network model of leaky integrate-and-fire neurons with an additional dependency on ATP dynamics. Neurons were scattered in a 2D space, and their population activity patterns at varying ATP levels were simulated. The model predicted a decrease in firing activity as the ATP production rate was lowered. Under hypometabolic conditions, an oscillatory firing pattern, that is, an ON-OFF cycle arose through a failure of sustainable firing due to reduced excitatory positive feedback and rebound firing after the slow recovery of ATP concentration. The firing rate oscillation of distant neurons developed at first asynchronously that changed into burst suppression and global synchronization as ATP production further decreased. These changes resembled the experimental data obtained from anesthetized rats, as an example of a metabolically suppressed brain. Together, this study substantiates a novel biophysical mechanism of neuronal network synchronization under limited energy supply conditions.

Energy-induced resonance synchronization in neural circuits

Biological neurons can be approached by using some functional neural circuits, and the biophysical mechanism for signal processing can be explained. Chemical stimulus can adjust the intracellular and extracellular ions concentration, and thus the channel current can be regulated to trigger appropriate firing modes in the neural activities. A physical stimulus often injects kinds of energy, and the energy can be encoded in the components for generating a certain channel current. The energy driving on the cell can be effective to enhance the pumping of ions and mode transition is induced. Based on a simple neural circuit exposed to the external magnetic field, the mode selection is investigated to explore the biophysical mechanism of energy absorption by applying periodic, and stochastic magnetic fields, respectively. The external field energy is encoded in the induction coil of the neural circuit, and the channel current is induced. Two identical neural circuits are exposed to the same magnetic field and the synchronization approach is investigated without synapse coupling. It is found that two neurons in periodic firings can be synchronized under the same periodic or noise-like magnetic field even applying different initials, while intermittent phase lock is induced between two chaotic neurons. Stochastic variation in the external magnetic field can induce noisy induced electromotive force (IEF) and the firing mode is regulated effectively. When both noisy IEF and periodic stimulus are applied, synchronization stability between periodic neurons with initials diversity is enhanced while synchronization approach between chaotic neurons becomes difficult. In addition, the Hamilton energy in each neuron can keep pace with another neuron when complete synchronization is stabilized within a finite transient period. These results provide new insights to know the energy encoding mechanism in neural circuits and neurons exposed to external magnetic field.

A Physiology-Guided Classification of Active-Stress and Active-Strain Approaches for Continuum-Mechanical Modeling of Skeletal Muscle Tissue

The well-established sliding filament and cross-bridge theory explain the major biophysical mechanism responsible for a skeletal muscle's active behavior on a cellular level. However, the biomechanical function of skeletal muscles on the tissue scale, which is caused by the complex interplay of muscle fibers and extracellular connective tissue, is much less understood. Mathematical models provide one possibility to investigate physiological hypotheses. Continuum-mechanical models have hereby proven themselves to be very suitable to study the biomechanical behavior of whole muscles or entire limbs. Existing continuum-mechanical skeletal muscle models use either an active-stress or an active-strain approach to phenomenologically describe the mechanical behavior of active contractions. While any macroscopic constitutive model can be judged by it's ability to accurately replicate experimental data, the evaluation of muscle-specific material descriptions is difficult as suitable data is, unfortunately, currently not available. Thus, the discussions become more philosophical rather than following rigid methodological criteria. Within this work, we provide a extensive discussion on the underlying modeling assumptions of both the active-stress and the active-strain approach in the context of existing hypotheses of skeletal muscle physiology. We conclude that the active-stress approach resolves an idealized tissue transmitting active stresses through an independent pathway. In contrast, the active-strain approach reflects an idealized tissue employing an indirect, coupled pathway for active stress transmission. Finally the physiological hypothesis that skeletal muscles exhibit redundant pathways of intramuscular stress transmission represents the basis for considering a mixed-active-stress-active-strain constitutive framework.

Redefining Molecular Chaperones as Chaotropes

Molecular chaperones are the key instruments of bacterial protein homeostasis. Chaperones not only facilitate folding of client proteins, but also transport them, prevent their aggregation, dissolve aggregates and resolve misfolded states. Despite this seemingly large variety, single chaperones can perform several of these functions even on multiple different clients, thus suggesting a single biophysical mechanism underlying. Numerous recently elucidated structures of bacterial chaperone–client complexes show that dynamic interactions between chaperones and their client proteins stabilize conformationally flexible non-native client states, which results in client protein denaturation. Based on these findings, we propose chaotropicity as a suitable biophysical concept to rationalize the generic activity of chaperones. We discuss the consequences of applying this concept in the context of ATP-dependent and -independent chaperones and their functional regulation.

Swarming bacteria undergo localized dynamic phase transition to form stress-induced biofilms

Self-organized multicellular behaviors enable cells to adapt and tolerate stressors to a greater degree than isolated cells. However, whether and how cellular communities alter their collective behaviors adaptively upon exposure to stress is largely unclear. Here, we investigate this question using Bacillus subtilis, a model system for bacterial multicellularity. We discover that, upon exposure to a spatial gradient of kanamycin, swarming bacteria activate matrix genes and transit to biofilms. The initial stage of this transition is underpinned by a stress-induced multilayer formation, emerging from a biophysical mechanism reminiscent of motility-induced phase separation (MIPS). The physical nature of the process suggests that stressors which suppress the expansion of swarms would induce biofilm formation. Indeed, a simple physical barrier also induces a swarm-to-biofilm transition. Based on the gained insight, we propose a strategy of antibiotic treatment to inhibit the transition from swarms to biofilms by targeting the localized phase transition.

SWI/SNF senses carbon starvation with a pH-sensitive low complexity sequence

It is increasingly appreciated that intracellular pH changes are important biological signals. This motivates the elucidation of molecular mechanisms of pH-sensing. We determined that a nucleocytoplasmic pH oscillation was required for the transcriptional response to carbon starvation in S. cerevisiae. The SWI/SNF chromatin remodeling complex is a key mediator of this transcriptional response. We found that a glutamine-rich low complexity sequence (QLC) in the SNF5 subunit of this complex, and histidines within this sequence, were required for efficient transcriptional reprogramming during carbon starvation. Furthermore, the SNF5 QLC mediated pH-dependent recruitment of SWI/SNF to a model promoter in vitro. Simulations showed that protonation of histidines within the SNF5 QLC lead to conformational expansion, providing a potential biophysical mechanism for regulation of these interactions. Together, our results indicate that that pH changes are a second messenger for transcriptional reprogramming during carbon starvation, and that the SNF5 QLC acts as a pH-sensor.

Cholinergic neuromodulation of inhibitory interneurons facilitates functional integration in whole-brain models

Segregation and integration are two fundamental principles of brain structural and functional organization. Neuroimaging studies have shown that the brain transits between different functionally segregated and integrated states, and neuromodulatory systems have been proposed as key to facilitate these transitions. Although whole-brain computational models have reproduced this neuromodulatory effect, the role of local inhibitory circuits and their cholinergic modulation has not been studied. In this article, we consider a Jansen & Rit whole-brain model in a network interconnected using a human connectome, and study the influence of the cholinergic and noradrenergic neuromodulatory systems on the segregation/integration balance. In our model, we introduce a local inhibitory feedback as a plausible biophysical mechanism that enables the integration of whole-brain activity, and that interacts with the other neuromodulatory influences to facilitate the transition between different functional segregation/integration regimes in the brain.