Inferring Viral Transmission Pathways from Within-Host Variation.

Genome sequencing can offer critical insight into pathogen spread in viral outbreaks, but existing transmission inference methods use simplistic evolutionary models and only incorporate a portion of available genetic data. Here, we develop a robust evolutionary model for transmission reconstruction that tracks the genetic composition of within-host viral populations over time and the lineages transmitted between hosts. We confirm that our model reliably describes within-host variant frequencies in a dataset of 134,682 SARS-CoV-2 deep-sequenced genomes from Massachusetts, USA. We then demonstrate that our reconstruction approach infers transmissions more accurately than two leading methods on synthetic data, as well as in a controlled outbreak of bovine respiratory syncytial virus and an epidemiologically-investigated SARS-CoV-2 outbreak in South Africa. Finally, we apply our transmission reconstruction tool to 5,692 outbreaks among the 134,682 Massachusetts genomes. Our methods and results demonstrate the utility of within-host variation for transmission inference of SARS-CoV-2 and other pathogens, and provide an adaptable mathematical framework for tracking within-host evolution.

Intra-chain organisation of hydrophobic residues controls inter-chain aggregation rates of amphiphilic polymers.

Aggregation of amphiphiles through the action of hydrophobic interactions is a common feature in soft condensed matter systems and is of particular importance in the context of biophysics as it underlies both the generation of functional biological machinery as well as the formation of pathological misassembled states of proteins. Here we explore the aggregation behaviour of amphiphilic polymers using lattice Monte Carlo calculations and show that the distribution of hydrophobic residues within the polymer sequence determines the facility with which dry/wet interfaces can be created and that such interfaces drive the aggregation process.

Consistent Treatment of Hydrophobicity in Protein Lattice Models Accounts for Cold Denaturation.

The hydrophobic effect stabilizes the native structure of proteins by minimizing the unfavorable interactions between hydrophobic residues and water through the formation of a hydrophobic core. Here, we include the entropic and enthalpic contributions of the hydrophobic effect explicitly in an implicit solvent model. This allows us to capture two important effects: a length-scale dependence and a temperature dependence for the solvation of a hydrophobic particle. This consistent treatment of the hydrophobic effect explains cold denaturation and heat capacity measurements of solvated proteins.

Mobile linkers on DNA-coated colloids: valency without patches.

Colloids coated with single-stranded DNA (ssDNA) can bind selectively to other colloids coated with complementary ssDNA. The fact that DNA-coated colloids (DNACCs) can bind to specific partners opens the prospect of making colloidal "molecules." However, in order to design DNACC-based molecules, we must be able to control the valency of the colloids, i.e., the number of partners to which a given DNACC can bind. One obvious, but not very simple approach is to decorate the colloidal surface with patches of single-stranded DNA that selectively bind those on other colloids. Here we propose a design principle that exploits many-body effects to control the valency of otherwise isotropic colloids. Using a combination of theory and simulation, we show that we can tune the valency of colloids coated with mobile ssDNA, simply by tuning the nonspecific repulsion between the particles. Our simulations show that the resulting effective interactions lead to low-valency colloids self-assembling in peculiar open structures, very different from those observed in DNACCs with immobile DNA linkers.

Effect of inert tails on the thermodynamics of DNA hybridization.

The selective hybridization of DNA is of key importance for many practical applications such as gene detection and DNA-mediated self-assembly. These applications require a quantitative prediction of the hybridization free energy. Existing methods ignore the effects of non-complementary ssDNA tails beyond the first unpaired base. We use experiments and simulations to show that the binding strength of complementary ssDNA oligomers is altered by these sequences of non-complementary nucleotides. Even a small number of non-binding bases are enough to raise the hybridization free energy by approximately 1 kcal/mol at physiological salt concentrations. We propose a simple analytical expression that accounts quantitatively for this variation as a function of tail length and salt concentration.

Designing stimulus-sensitive colloidal walkers.

Colloidal particles with DNA "legs" that can bind reversibly to receptors on a surface can be made to 'walk' if there is a gradient in receptor concentration. We use a combination of theory and Monte Carlo simulations to explore how controllable parameters, e.g. coating density and binding strength, affect the dynamics of such colloids. We find that competition between thermodynamic and kinetic trends imply that there is an optimal value for both the binding strength and the number of "legs" for which transport is the fastest. Using available thermodynamic data on DNA binding, we indicate how directionally reversible, temperature-controlled transport of colloidal walkers can be achieved. In particular, the present results should make it possible to design a chromatographic technique that can be used to separate colloids with different DNA functionalizations.

Water evaporation: a transition path sampling study.

We use transition path sampling to study evaporation in the SPC/E model of liquid water. On the basis of thousands of evaporation trajectories, we characterize the members of the transition state ensemble (TSE), which exhibit a liquid-vapor interface with predominantly negative mean curvature at the site of evaporation. We also find that after evaporation is complete, the distributions of translational and angular momenta of the evaporated water are Maxwellian with a temperature equal to that of the liquid. To characterize the evaporation trajectories in their entirety, we find that it suffices to project them onto just two coordinates: the distance of the evaporating molecule to the instantaneous liquid-vapor interface and the velocity of the water along the average interface normal. In this projected space, we find that the TSE is well-captured by a simple model of ballistic escape from a deep potential well, with no additional barrier to evaporation beyond the cohesive strength of the liquid. Equivalently, they are consistent with a near-unity probability for a water molecule impinging upon a liquid droplet to condense. These results agree with previous simulations and with some, but not all, recent experiments.

Communication: a simple analytical formula for the free energy of ligand-receptor-mediated interactions.

Recently [P. Varilly, S. Angioletti-Uberti, B. M. Mognetti, and D. Frenkel, "A general theory of DNA-mediated and other valence-limited colloidal interactions," J. Chem. Phys. 137, 094108 (2012)], we presented a general theory for calculating the strength and properties of colloidal interactions mediated by ligand-receptor bonds (such as those that bind DNA-coated colloids). In this Communication, we derive a surprisingly simple analytical form for the interaction free energy, which was previously obtainable only via a costly numerical thermodynamic integration. As a result, the computational effort to obtain potentials of interaction is significantly reduced. Moreover, we can gain insight from this analytic expression for the free energy in limiting cases. In particular, the connection of our general theory to other previous specialised approaches is now made transparent. This important simplification will significantly broaden the scope of our theory.

A general theory of DNA-mediated and other valence-limited colloidal interactions.

We present a general theory for predicting the interaction potentials between DNA-coated colloids, and more broadly, any particles that interact via valence-limited ligand-receptor binding. Our theory correctly incorporates the configurational and combinatorial entropic factors that play a key role in valence-limited interactions. By rigorously enforcing self-consistency, it achieves near-quantitative accuracy with respect to detailed Monte Carlo calculations. With suitable approximations and in particular geometries, our theory reduces to previous successful treatments, which are now united in a common and extensible framework. We expect our tools to be useful to other researchers investigating ligand-mediated interactions. A complete and well-documented Python implementation is freely available at http://github.com/patvarilly/DNACC.

Sitting at the edge: how biomolecules use hydrophobicity to tune their interactions and function.

Water near extended hydrophobic surfaces is like that at a liquid-vapor interface, where fluctuations in water density are substantially enhanced compared to those in bulk water. Here we use molecular simulations with specialized sampling techniques to show that water density fluctuations are similarly enhanced, even near hydrophobic surfaces of complex biomolecules, situating them at the edge of a dewetting transition. Consequently, water near these surfaces is sensitive to subtle changes in surface conformation, topology, and chemistry, any of which can tip the balance toward or away from the wet state and thus significantly alter biomolecular interactions and function. Our work also resolves the long-standing puzzle of why some biological surfaces dewet and other seemingly similar surfaces do not.

Quantifying density fluctuations in volumes of all shapes and sizes using indirect umbrella sampling.

Water density fluctuations are an important statistical mechanical observable that is related to many-body correlations, as well as hydrophobic hydration and interactions. Local water density fluctuations at a solid-water surface have also been proposed as a measure of it's hydrophobicity. These fluctuations can be quantified by calculating the probability, P(v)(N), of observing N waters in a probe volume of interest v. When v is large, calculating P(v)(N) using molecular dynamics simulations is challenging, as the probability of observing very few waters is exponentially small, and the standard procedure for overcoming this problem (umbrella sampling in N) leads to undesirable impulsive forces. Patel et al. [J. Phys. Chem. B, 114, 1632 (2010)] have recently developed an indirect umbrella sampling (INDUS) method, that samples a coarse-grained particle number to obtain P(v)(N) in cuboidal volumes. Here, we present and demonstrate an extension of that approach to volumes of other basic shapes, like spheres and cylinders, as well as to collections of such volumes. We further describe the implementation of INDUS in the NPT ensemble and calculate P(v)(N) distributions over a broad range of pressures. Our method may be of particular interest in characterizing the hydrophobicity of interfaces of proteins, nanotubes and related systems.

Extended surfaces modulate hydrophobic interactions of neighboring solutes.

Interfaces are a most common motif in complex systems. To understand how the presence of interfaces affects hydrophobic phenomena, we use molecular simulations and theory to study hydration of solutes at interfaces. The solutes range in size from subnanometer to a few nanometers. The interfaces are self-assembled monolayers with a range of chemistries, from hydrophilic to hydrophobic. We show that the driving force for assembly in the vicinity of a hydrophobic surface is weaker than that in bulk water and decreases with increasing temperature, in contrast to that in the bulk. We explain these distinct features in terms of an interplay between interfacial fluctuations and excluded volume effects--the physics encoded in Lum-Chandler-Weeks theory [Lum K, Chandler D, Weeks JD (1999) J Phys Chem B 103:4570-4577]. Our results suggest a catalytic role for hydrophobic interfaces in the unfolding of proteins, for example, in the interior of chaperonins and in amyloid formation.

An improved coarse-grained model of solvation and the hydrophobic effect.

We present a coarse-grained lattice model of solvation thermodynamics and the hydrophobic effect that implements the ideas of Lum-Chandler-Weeks theory [J. Phys. Chem. B 134, 4570 (1999)] and improves upon previous lattice models based on it. Through comparison with molecular simulation, we show that our model captures the length-scale and curvature dependence of solvation free energies with near-quantitative accuracy and 2-3 orders of magnitude less computational effort, and further, correctly describes the large but rare solvent fluctuations that are involved in dewetting, vapor tube formation, and hydrophobic assembly. Our model is intermediate in detail and complexity between implicit-solvent models and explicit-water simulations.

Fluctuations of water near extended hydrophobic and hydrophilic surfaces.

We use molecular dynamics simulations of the SPC-E model of liquid water to derive probability distributions for water density fluctuations in probe volumes of different shapes and sizes, both in the bulk as well as near hydrophobic and hydrophilic surfaces. Our results are obtained with a biased sampling of coarse-grained densities that is easily combined with molecular dynamics integration algorithms. Our principal result is that the probability for density fluctuations of water near a hydrophobic surface, with or without surface water attractions, is akin to density fluctuations at the water-vapor interface. Specifically, the probability of density depletion near the surface is significantly larger than that in the bulk, and this enhanced probability is responsible for hydrophobic forces of assembly. In contrast, we find that the statistics of water density fluctuations near a model hydrophilic surface are similar to that in the bulk.

Genome-wide detection and characterization of positive selection in human populations.

With the advent of dense maps of human genetic variation, it is now possible to detect positive natural selection across the human genome. Here we report an analysis of over 3 million polymorphisms from the International HapMap Project Phase 2 (HapMap2). We used 'long-range haplotype' methods, which were developed to identify alleles segregating in a population that have undergone recent selection, and we also developed new methods that are based on cross-population comparisons to discover alleles that have swept to near-fixation within a population. The analysis reveals more than 300 strong candidate regions. Focusing on the strongest 22 regions, we develop a heuristic for scrutinizing these regions to identify candidate targets of selection. In a complementary analysis, we identify 26 non-synonymous, coding, single nucleotide polymorphisms showing regional evidence of positive selection. Examination of these candidates highlights three cases in which two genes in a common biological process have apparently undergone positive selection in the same population:LARGE and DMD, both related to infection by the Lassa virus, in West Africa;SLC24A5 and SLC45A2, both involved in skin pigmentation, in Europe; and EDAR and EDA2R, both involved in development of hair follicles, in Asia.

Searching for signals of evolutionary selection in 168 genes related to immune function.

Pathogens have played a substantial role in human evolution, with past infections shaping genetic variation at loci influencing immune function. We selected 168 genes known to be involved in the immune response, genotyped common single nucleotide polymorphisms across each gene in three population samples (CEPH Europeans from Utah, Han Chinese from Guangxi, and Yoruba Nigerians from Southwest Nigeria) and searched for evidence of selection based on four tests for non-neutral evolution: minor allele frequency (MAF), derived allele frequency (DAF), Fst versus heterozygosity and extended haplotype homozygosity (EHH). Six of the 168 genes show some evidence for non-neutral evolution in this initial screen, with two showing similar signals in independent data from the International HapMap Project. These analyses identify two loci involved in immune function that are candidates for having been subject to evolutionary selection, and highlight a number of analytical challenges in searching for selection in genome-wide polymorphism data.

The case for selection at CCR5-Delta32.

The C-C chemokine receptor 5, 32 base-pair deletion (CCR5-Delta32) allele confers strong resistance to infection by the AIDS virus HIV. Previous studies have suggested that CCR5-Delta32 arose within the past 1,000 y and rose to its present high frequency (5%-14%) in Europe as a result of strong positive selection, perhaps by such selective agents as the bubonic plague or smallpox during the Middle Ages. This hypothesis was based on several lines of evidence, including the absence of the allele outside of Europe and long-range linkage disequilibrium at the locus. We reevaluated this evidence with the benefit of much denser genetic maps and extensive control data. We find that the pattern of genetic variation at CCR5-Delta32 does not stand out as exceptional relative to other loci across the genome. Moreover using newer genetic maps, we estimated that the CCR5-Delta32 allele is likely to have arisen more than 5,000 y ago. While such results can not rule out the possibility that some selection may have occurred at C-C chemokine receptor 5 (CCR5), they imply that the pattern of genetic variation seen at CCR5-Delta32 is consistent with neutral evolution. More broadly, the results have general implications for the design of future studies to detect the signs of positive selection in the human genome.