Physical biology最新文献

The network-shaped body plan distinguishes the unicellular slime mouldPhysarum polycephalumin body architecture from other unicellular organisms. Yet, network-shaped body plans dominate branches of multi-cellular life such as in fungi. What survival advantage does a network structure provide when facing a dynamic environment with adverse conditions? Here, we probe how network topology impactsP. polycephalum's avoidance response to an adverse blue light. We stimulate either an elongated, I-shaped amoeboid or a Y-shaped networked specimen and subsequently quantify the evacuation process of the light-exposed body part. The result shows that Y-shaped specimen complete the avoidance retraction in a comparable time frame, even slightly faster than I-shaped organisms, yet, at a lower almost negligible increase in migration velocity. Contraction amplitude driving mass motion is further only locally increased in Y-shaped specimen compared to I-shaped-providing further evidence that Y-shaped's avoidance reaction is energetically more efficient than in I-shaped amoeboid organisms. The difference in the retraction behaviour suggests that the complexity of network topology provides a key advantage when encountering adverse environments. Our findings could lead to a better understanding of the transition from unicellular to multicellularity.

The output of the bacterial chemotaxis signaling pathway, the level of the intracellular regulator CheY-P, modulates the rotation direction of the flagellar motor, thereby regulating bacterial run-and-tumble behavior. The multiple flagellar motors on anE. colicell are controlled by a common cytoplasmic pool of CheY-P. Fluctuation of the CheY-P level was thought to be able to coordinate the switching of multiple motors. Here, we measured the correlation of rotation directions between two motors on a cell, finding that it surprisingly exhibits two well separated timescales. We found that the slow timescale (∼6 s) can be explained by the slow fluctuation of the CheY-P level due to stochastic activity of the chemotactic adaptation enzymes, whereas the fast timescale (∼0.3 s) can be explained by the random pulse-like fluctuation of the CheY-P level, due probably to the activity of the chemoreceptor clusters. We extracted information on the properties of the fast CheY-P pulses based on the correlation measurements. The two well-separated timescales in the fluctuation of CheY-P level help to coordinate multiple motors on a cell and to enhance bacterial chemotactic performance.

Conventionally, only the normal cell membrane fluctuations have been studied and used to ascertain membrane properties like the bending rigidity. A new concept, the membrane local slope fluctuations was introduced recently (Vaippullyet al2020Soft Matter167606), which can be modelled as a gradient of the normal fluctuations. It has been found that the power spectral density (PSD) of slope fluctuations behave as (frequency)^-1while the normal fluctuations yields (frequency)-5/3even on the apical cell membrane in the high frequency region. In this manuscript, we explore a different situation where the cell is applied with the drug Latrunculin-B which inhibits actin polymerization and find the effect on membrane fluctuations. We find that even as the normal fluctuations show a power law (frequency)-5/3as is the case for a free membrane, the slope fluctuations PSD remains (frequency)^-1, with exactly the same coefficient as the case when the drug was not applied. Moreover, while sometimes, when the normal fluctuations at high frequency yield a power law of (frequency)-4/3, the pitch PSD still yields (frequency)^-1. Thus, this presents a convenient opportunity to study membrane parameters like bending rigidity as a function of time after application of the drug, while the membrane softens. We also investigate the active athermal fluctuations of the membrane appearing in the PSD at low frequencies and find active timescales of slower than 1 s.

This paper concerns the identification of gene co-expression modules in transcriptomics data, i.e. collections of genes which are highly co-expressed and potentially linked to a biological mechanism. Weighted gene co-expression network analysis (WGCNA) is a widely used method for module detection based on the computation of eigengenes, the weights of the first principal component for the module gene expression matrix. This eigengene has been used as a centroid in ak-means algorithm to improve module memberships. In this paper, we present four new module representatives: the eigengene subspace, flag mean, flag median and module expression vector. The eigengene subspace, flag mean and flag median are subspace module representatives which capture more variance of the gene expression within a module. The module expression vector is a weighted centroid of the module which leverages the structure of the module gene co-expression network. We use these module representatives in Linde-Buzo-Gray clustering algorithms to refine WGCNA module membership. We evaluate these methodologies on two transcriptomics data sets. We find that most of our module refinement techniques improve upon the WGCNA modules by two statistics: (1) module classification between phenotype and (2) module biological significance according to Gene Ontology terms.

Evolution is the main feature of all biological systems that allows populations to change their characteristics over successive generations. A powerful approach to understand evolutionary dynamics is to investigate fixation probabilities and fixation times of novel mutations on networks that mimic biological populations. It is now well established that the structure of such networks can have dramatic effects on evolutionary dynamics. In particular, there are population structures that might amplify the fixation probabilities while simultaneously delaying the fixation events. However, the microscopic origins of such complex evolutionary dynamics remain not well understood. We present here a theoretical investigation of the microscopic mechanisms of mutation fixation processes on inhomogeneous networks. It views evolutionary dynamics as a set of stochastic transitions between discrete states specified by different numbers of mutated cells. By specifically considering star networks, we obtain a comprehensive description of evolutionary dynamics. Our approach allows us to employ physics-inspired free-energy landscape arguments to explain the observed trends in fixation times and fixation probabilities, providing a better microscopic understanding of evolutionary dynamics in complex systems.

Living groups move in complex environments and are constantly subject to external stimuli, predatory attacks and disturbances. An efficient response to such perturbations is vital to maintain the group's coherence and cohesion. Perturbations are often local, i.e. they are initially perceived only by few individuals in the group, but can elicit a global response. This is the case of starling flocks, that can turn very quickly to evade predators. In this paper, we investigate the conditions under which a global change of direction can occur upon local perturbations. Using minimal models of self-propelled particles, we show that a collective directional response occurs on timescales that grow with the system size and it is, therefore, a finite-size effect. The larger the group is, the longer it will take to turn. We also show that global coherent turns can only take place if i) the mechanism for information propagation is efficient enough to transmit the local reaction undamped through the whole group; and if ii) motility is not too strong, to avoid that the perturbed individual leaves the group before the turn is complete. No compliance with such conditions results in the group's fragmentation or in a non-efficient response.

Microtubule (MT) severing enzymes Katanin and Spastin cut the MT into smaller fragments and are being studied extensively usingin-vitroexperiments due to their crucial role in different cancers and neurodevelopmental disorders. It has been reported that the severing enzymes are either involved in increasing or decreasing the tubulin mass. Currently, there are a few analytical and computational models for MT amplification and severing. However, these models do not capture the action of MT severing explicitly, as these are based on partial differential equations in one dimension. On the other hand, a few discrete lattice-based models were used earlier to understand the activity of severing enzymes only on stabilized MTs. Hence, in this study, discrete lattice-based Monte Carlo models that included MT dynamics and severing enzyme activity have been developed to understand the effect of severing enzymes on tubulin mass, MT number, and MT length. It was found that the action of severing enzyme reduces average MT length while increasing their number; however, the total tubulin mass can decrease or increase depending on the concentration of GMPCPP (Guanylyl-(α,β)-methylene-diphosphonate)-which is a slowly hydrolyzable analogue of GTP (Guanosine triphosphate). Further, relative tubulin mass also depends on the detachment ratio of GTP/GMPCPP and Guanosine diphosphate tubulin dimers and the binding energies of tubulin dimers covered by the severing enzyme.