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Many replicative DNA polymerases couple DNA replication and unwinding activities to perform strand displacement DNA synthesis, a critical ability for DNA metabolism. Strand displacement is tightly regulated by partner proteins, such as single-stranded DNA (ssDNA) binding proteins (SSBs) by a poorly understood mechanism. Here, we use single-molecule optical tweezers and biochemical assays to elucidate the molecular mechanism of strand displacement DNA synthesis by the human mitochondrial DNA polymerase, Polγ, and its modulation by cognate and noncognate SSBs. We show that Polγ exhibits a robust DNA unwinding mechanism, which entails lowering the energy barrier for unwinding of the first base pair of the DNA fork junction, by ∼55%. However, the polymerase cannot prevent the reannealing of the parental strands efficiently, which limits by ∼30-fold its strand displacement activity. We demonstrate that SSBs stimulate the Polγ strand displacement activity through several mechanisms. SSB binding energy to ssDNA additionally increases the destabilization energy at the DNA junction, by ∼25%. Furthermore, SSB interactions with the displaced ssDNA reduce the DNA fork reannealing pressure on Polγ, in turn promoting the productive polymerization state by ∼3-fold. These stimulatory effects are enhanced by species-specific functional interactions and have significant implications in the replication of the human mitochondrial DNA.

Population dynamics is affected by environmental fluctuations (such as climate variations), which have a characteristic correlation time. Strikingly, the time scale of predictability can be larger for the population dynamics than for the underlying environmental fluctuations. Here, we present a general mechanism leading to this increase in predictability. We considered colored environmental fluctuation acting on a population close to equilibrium. In this framework, we derived the temporal auto and cross-correlation functions for the environmental and population fluctuations. We found a general correlation time hierarchy led by the environmental-population correlation time, closely followed by the population autocorrelation time. The increased predictability of the population fluctuations arises as an increase in its autocorrelation and cross-correlation times. These increases are enhanced by the slow damping of the population fluctuations, which has an integrative effect on the impact of correlated environmental fluctuations. Therefore, population fluctuation predictability is enhanced when the damping time of the population fluctuation is larger than the environmental fluctuations. This general mechanism can be quite frequent in nature, and it largely increases the perspectives of making reliable predictions of population fluctuations.

Environmental fluctuations can create population-depleted areas and even extinct areas for the population. This effect is more severe in the presence of the Allee effect (decreasing growth rate at low population densities). Dispersal inside the habitat provides a rescue effect on population-depleted areas, enhancing the population resilience to environmental fluctuations. Habitat reduction decreases the effectiveness of the dispersal rescue mechanism. We report here how the population resilience to environmental fluctuations decreases when the dispersal length or the habitat size are reduced. The resilience reduction is characterized by a decrease of the extinction threshold for environmental fluctuations. The extinction threshold is shown to scale with the ratio between the dispersal length and the scale of environmental synchrony, i.e., it is the dispersal connection between non-environmentally-correlated regions that provides resilience to environmental fluctuations. Habitat reduction also decreases the resilience to environmental fluctuations, when the habitat size is similar to or smaller than the characteristic dispersal distances. The power laws of these scaling behaviors are characterized here. Alternative scaling functions with spatial scales of population synchrony are found to fit the simulations worse. These results support the dispersal length as the critical scale for extinction induced by habitat reduction., Comment: 24 pages

Achieving sustainable harvesting of natural populations depends on our ability to predict population responses to the combined effects of harvesting and environmental fluctuations while accounting for other internal and external factors that influence population dynamics in time and space. Here, we review recent research showing how spatial patterns and interspecific interactions can influence population responses to harvesting in fluctuating environments. We highlight several pathways through which harvesting can, often inadvertently, influence the dynamics and resilience to environmental fluctuations of both harvested and surrounding non-harvested populations and species. For instance, spatial models have shown that harvesting is expected to influence the spatial synchrony of population fluctuations, both of the harvested species and its competitors, predators and prey, with implications for population extinction risk. Dispersal and interspecific interactions can cause responses to harvesting in areas and species that are not themselves harvested. Harvesting that selectively targets certain groups of individuals, either intentionally or through for example spatially biased harvesting, can amplify environmentally induced population fluctuations by biasing the population structure towards individuals that are more sensitive to environmental variation. On the other hand, harvesting can in some cases buffer populations against the density-dependent effects of harsh climatic conditions, which are probably more common than previously acknowledged. Recent advances in modeling are providing new predictions that are highly relevant under global warming and now need to be tested empirically. We discuss how knowledge of these pathways can be used to increase the sustainability of harvesting.

Optical tweezers enable the isolation and mechanical manipulation of individual nucleoprotein complexes. Here, we describe how to use this technique to interrogate the mechanical properties of individual protein-DNA complexes and extract information about their overall structural organization.

Graphical abstract, Highlights • Data analysis allows to extract information from the noisy single-molecule data. • Models provide insight in the underlying biochemical processes. • Ligands can activate or inhibit DNA replication and DNA unwinding., DNA replication is a key biochemical process of the cell cycle. In the last years, analysis of in vitro single-molecule DNA replication events has provided new information that cannot be obtained with ensembles studies. Here, we introduce crucial techniques for the proper analysis and modelling of DNA replication in vitro single-molecule manipulation data. Specifically, we review some of the main methods to analyze and model the real-time kinetics of the two main molecular motors of the replisome: DNA polymerase and DNA helicase. Our goal is to facilitate access to and understanding of these techniques to promotetheir use in the study of DNA replication at the single-molecule level. A proper analysis of single-molecule data is crucial to obtain a detailed picture of, among others, the kinetics rates, equilibrium contants and conformational changes of the system under study. The techniques presented here have been used or can be adapted to study the operation of other proteins involved in nucleic acids metabolism.

Optical tweezers enable the isolation and mechanical manipulation of individual nucleoprotein complexes. Here, we describe how to use this technique to interrogate the mechanical properties of individual protein-DNA complexes and extract information about their overall structural organization.

Ligand binding to polymers modifies the physical and chemical properties of the polymers, leading to physical, chemical, and biological implications. McGhee and von Hippel obtained the equilibrium coverage as a function of the ligand affinity, through the computation of the possible binding sites for the ligand. Here, we complete this theory deriving the kinetic model for the ligand-binding dynamics and the associated equilibrium chemical potential, which turns out to be of the Tonks gas model type. At low coverage, the Tonks chemical potential becomes the Fermi chemical potential and even the ideal gas chemical potential. We also discuss kinetic models associated with these chemical potentials. These results clarify the kinetic models of ligand binding, their relations with the chemical potentials, and their range of validity. Our results highlight the inaccuracy of ideal and simplified kinetic approaches for medium and high coverages.

Many species show synchronous fluctuations in population size over large geographical areas, which are likely to increase their regional extinction risk. Here we examine how the degree of spatial synchrony in population dynamics is affected by trophic interactions using a two-species predator-prey model with spatially correlated environmental noise. We show that the predator has a larger spatial scale of population synchrony than the prey if the population fluctuations of both species are mainly determined by the direct effect of stochastic environmental variations in the prey. This result implies that in ecosystems regulated from the bottom up, the spatial scale of synchrony of the predator population increases beyond the scale of the spatial autocorrelation in the environmental noise and in the prey fluctuations. Harvesting the prey increases the spatial scale of population synchrony of the predator, while harvesting the predator reduces the spatial scale of the population fluctuations of its prey. Hence, the development of sustainable harvesting strategies should also consider the impact on unharvested species at other trophic levels as well as human perturbations of ecosystems, whether the result of exploitation or an effect on dispersal processes, as they can affect food web structures and trophic interactions over large geographical areas.

16 pags., 9 figs., Cell constriction is a decisive step for division in many cells. However, its physical pathway remains poorly understood, calling for a quantitative analysis of the forces required in different cytokinetic scenarios. Using a model cell composed by a flexible membrane (actin cortex and cell membrane) that encloses the cytoplasm, we study the mechanical conditions necessary for stable symmetric constriction under radial equatorial forces using analytical and numerical methods. We deduce that stable symmetric constriction requires positive effective spontaneous curvature, while spontaneous constriction requires a spontaneous curvature higher than the characteristic inverse cell size. Surface tension reduction (for example by actin cortex growth and membrane trafficking) increases the stability and spontaneity of cellular constriction. A reduction of external pressure also increases stability and spontaneity. Cells with prolate lobes (elongated cells) require lower stabilization forces than oblate-shaped cells (discocytes). We also show that the stability and spontaneity of symmetric constriction increase as constriction progresses. Our quantitative results settle the physical requirements for stable cytokinesis, defining a quantitative framework to analyze the mechanical role of the different constriction machinery and cytokinetic pathways found in real cells, so contributing to a deeper quantitative understanding of the physical mechanism of the cell division process., E.B.H. acknowledges financial support from Ministerio de Educación, Cultura, y Deporte (MECD, Spain) under FPU Grant No. 13/02826. F.M. acknowledges financial support from Ministerio de Economía y Competitividad (MINECO, Spain) and European Regional Development Fund (ERDF) under Grant No. FIS201570339-C2-1-R, and from Comunidad de Madrid (CAM, Spain) under Grant No. S2013/MIT-2807. F.J.C.G. acknowledges financial support from Ministerio de Economía y Competitividad (MINECO, Spain) and from European Regional Development Fund (ERDF) under Grant No. FIS2015-67745-R. .

Many species are unsustainable at small population densities (Allee Effect), i.e., below a threshold named Allee threshold, the population decreases instead of growing. In a closed local population, environmental fluctuations always lead to extinction. Here, we show how, in spatially extended habitats, dispersal can lead to a sustainable population in a region, provided the amplitude of environmental fluctuations is below an extinction threshold. We have identified two types of sustainable populations: high-density and low-density populations (through a mean-field approximation, valid in the limit of large dispersal length). Our results show that patches where population is high, low or extinct, coexist when the population is close to global extinction (even for homogeneous habitats). The extinction threshold is maximum for characteristic dispersal distances much larger than the spatial scale of synchrony of environmental fluctuations. The extinction threshold increases proportionally to the square root of the dispersal rate and decreases with the Allee threshold. The low-density population solution can allow understanding difficulties in recovery after harvesting. This theoretical framework provides a novel approach to address other factors, such as habitat fragmentation or harvesting, impacting population resilience to environmental fluctuations., 32 pages, 9 figures, 1 table