Physical Model of the Genotype-to-Phenotype Map of Proteins

How DNA is mapped to functional proteins is a basic question of living matter. We introduce and study a physical model of protein evolution which suggests a mechanical basis for this map. Many proteins rely on large-scale motion to function. We therefore treat protein as learning amorphous matter that evolves towards such a mechanical function: Genes are binary sequences that encode the connectivity of the amino acid network that makes a protein. The gene is evolved until the network forms a shear band across the protein, which allows for long-range, soft modes required for protein function. The evolution reduces the high-dimensional sequence space to a low-dimensional space of mechanical modes, in accord with the observed dimensional reduction between genotype and phenotype of proteins. Spectral analysis of the space of 10(6) solutions shows a strong correspondence between localization around the shear band of both mechanical modes and the sequence structure. Specifically, our model shows how mutations are correlated among amino acids whose interactions determine the functional mode

Universal protein fluctuations in populations of microorganisms

The copy number of any protein fluctuates among cells in a population; characterizing and understanding these fluctuations is a fundamental problem in biophysics. We show here that protein distributions measured under a broad range of biological realizations collapse to a single non-Gaussian curve under scaling by the first two moments. Moreover in all experiments the variance is found to depend quadratically on the mean, showing that a single degree of freedom determines the entire distribution. Our results imply that protein fluctuations do not reflect any specific molecular or cellular mechanism, and suggest that some buffering process masks these details and induces universality

Green function of correlated genes in a minimal mechanical model of protein evolution

The function of proteins arises from cooperative interactions and rearrangements of their amino acids, which exhibit large-scale dynamical modes. Long-range correlations have also been revealed in protein sequences, and this has motivated the search for physical links between the observed genetic and dynamic cooperativity. We outline here a simplified theory of protein, which relates sequence correlations to physical interactions and to the emergence of mechanical function. Our protein is modeled as a strongly coupled amino acid network with interactions and motions that are captured by the mechanical propagator, the Green function. The propagator describes how the gene determines the connectivity of the amino acids and thereby, the transmission of forces. Mutations introduce localized perturbations to the propagator that scatter the force field. The emergence of function is manifested by a topological transition when a band of such perturbations divides the protein into subdomains. We find that epistasis-the interaction among mutations in the gene-is related to the nonlinearity of the Green function, which can be interpreted as a sum over multiple scattering paths. We apply this mechanical framework to simulations of protein evolution and observe long-range epistasis, which facilitates collective functional modes

Biophysical basis for convergent evolution of two veil-forming microbes

Microbes living in stagnant water typically rely on chemical diffusion to draw nutrients from their environment. The sulfur-oxidizing bacterium Thiovulum majus and the ciliate Uronemella have independently evolved the ability to form a ‘veil’, a centimetre-scale mucous sheet on which cells organize to produce a macroscopic flow. This flow pulls nutrients through the community an order of magnitude faster than diffusion. To understand how natural selection led these microbes to evolve this collective behaviour, we connect the physical limitations acting on individual cells to the cell traits. We show how diffusion limitation and viscous dissipation have led individual T. majus and Uronemella cells to display two similar characteristics. Both of these cells exert a force of approximately 40 pN on the water and attach to boundaries by means of a mucous stalk. We show how the diffusion coefficient of oxygen in water and the viscosity of water define the force the cells must exert. We then show how the hydrodynamics of filter-feeding orient a microbe normal to the surface to which it attaches. Finally, we combine these results with new observations of veil formation and a review of veil dynamics to compare the collective dynamics of these microbes. We conclude that this convergent evolution is a reflection of similar physical limitations imposed by diffusion and viscosity acting on individual cells

On growth and form of Bacillus subtilis biofilms

International audienceA general feature of mature biofilms is their highly heterogeneous architecture that partitions the microbial city into sectors with specific micro-environments. To understand how this heterogeneity arises, we have investigated the for- mation of a microbial community of the model organism Bacillus subtilis. We first show that the growth of macroscopic colonies is inhibited by the accumulation of ammoniacal by-products. By constraining biofilms to grow approximately as two-dimensional layers, we then find that the bacteria which differentiate to produce extracellular polymeric substances form tightly packed bacterial chains. In addition to the process of cellular chaining, the bio- mass stickiness also strongly hinders the reorganization of cells within the biofilm. Based on these observations, we then write a biomechanical model for the growth of the biofilm where the cell density is constant and the physical mechanism responsible for the spreading of the biomass is the pressure gener- ated by the division of the bacteria. Besides reproducing the velocity field of the biomass across the biofilm, the model predicts that, although bacteria divide everywhere in the biofilm, fluctuations in the growth rates of the bacteria lead to a coarsening of the growing bacterial layer. This process of kin- etic roughening ultimately leads to the formation of a rough biofilm surface exhibiting self-similar properties. Experimental measurements of the biofilm texture confirm these predictions

Signal and noise in bridging PCR

BACKGROUND: In a variant of the standard PCR reaction termed bridging, or jumping, PCR the primer-bound sequences are originally on separate template molecules. Bridging can occur if, and only if, the templates contain a region of sequence similarity. A 3' end of synthesis in one round of synthesis that terminates in this region of similarity can prime on the other. In principle, Bridging PCR (BPCR) can detect a subpopulation of one template that terminates synthesis in the region of sequence shared by the other template. This study considers the sensitivity and noise of BPCR as a quantitative assay for backbone interruptions. Bridging synthesis is also important to some methods for computing with DNA. RESULTS: In this study, BPCR was tested over a 328 base pair segment of the E. coli lac operon and a signal to noise ratio (S/N) of approximately 10 was obtained under normal PCR conditions with Taq polymerase. With special precautions in the case of Taq or by using the Stoffel fragment the S/N was improved to 100, i.e. 1 part of cut input DNA yielded the same output as 100 parts of intact input DNA. CONCLUSIONS: In the E. coli lac operator region studied here, depending on details of protocol, between 3 and 30% per kilobase of final PCR product resulted from bridging. Other systems are expected to differ in the proportion of product that is bridged consequent to PCR protocol and the sequence analyzed. In many cases physical bridging during PCR will have no informational consequence because the bridged templates are of identical sequence, but in a number of special cases bridging creates, or, destroys, information

High-Fidelity DNA Sensing by Protein Binding Fluctuations

One of the major functions of RecA protein in the cell is to bind single-stranded DNA exposed upon damage, thereby triggering the SOS repair response.We present fluorescence anisotropy measurements at the binding onset, showing enhanced DNA length discrimination induced by adenosine triphosphate consumption. Our model explains the observed DNA length sensing as an outcome of out-of equilibrium binding fluctuations, reminiscent of microtubule dynamic instability. The cascade architecture of the binding fluctuations is a generalization of the kinetic proofreading mechanism. Enhancement of precision by an irreversible multistage pathway is a possible design principle in the noisy biological environment.Comment: PACS numbers: 87.15.Ya, 87.14.Ee, 87.14.Gg http://www.ncbi.nlm.nih.gov/pubmed/1569795

Walking droplets, swimming microbes: on memory in physics and life

Whirling and swerving, a bacterium is swimming in a test tube, foraging for food. On the surface of a vibrating bath, a droplet starts walking. A certain similarity, but mostly dissimilarity, between the physical memory that emerges in Couder's droplet experiments and the biological memory of the bacterium is noted. It serves as a starting point for a short perspective and speculation on the multilevel, loopy memory of living matter