Public viral genome resources such as the National Center for Biotechnology Information (NCBI) Virus database are central to outbreak response, evolutionary analysis, vaccine design, and genomic surveillance. Yet many high-value retrieval workflows remain optimized for interactive use rather than deterministic, reproducible programmatic interfaces. This creates a challenge for Large Language Model (LLM)-based scientific agents, where errors in metadata interpretation, filtering logic, or retrieval can propagate into incorrect datasets. To evaluate agentic viral data retrieval, we built VirBench, a manually curated benchmark of 120 queries spanning diverse pathogens, taxonomic levels, and metadata filters. When autonomous AI systems, including Biomni, Claude, GPT, and Edison Analysis, were tasked with these queries without a dedicated retrieval layer, performance varied widely: mean accuracy ranged from 16.9

Mpox is a re-emerging zoonotic disease caused by MPXV, which has led to outbreaks across multiple countries in recent years. Sierra Leone reported its first mpox case in 8 years in January 2025, rapidly becoming the epicenter of a continental outbreak with more than 5,000 confirmed cases by August, a surge with unknown origins, timings and drivers. Phylodynamic analyses using 338 genomes generated from 14 districts suggests that the outbreak was caused by lineage G.1 (A.2.2.1) which descended from lineages circulating in Nigeria. Here we observed a strong APOBEC3 mutational enrichment, consistent with sustained human transmission that circulated undetected for ~3 months before the first confirmed case in January 2025. The Western Area Urban district served as the primary hub for nationwide spread and persistence, as well as multiple international export events. We further estimated that the true epidemic size was nearly double official case counts, highlighting substantial surveillance gaps. These findings underscore the urgent need for strengthened genomic and diagnostic surveillance systems across West Africa to pre-empt epidemics.

In January 2025, Sierra Leone reported its first mpox case in eight years, followed by a rapid nationwide surge that made it the epicenter of the continental mpox virus (MPXV) Clade IIb A.2.2 outbreak, with more than 5,000 confirmed cases reported by August. To investigate the origin, timing, and spread of this epidemic, we generated 338 high-quality MPXV genomes from cases across 14 districts and conducted Bayesian phylogeographic analyses. We found that transmission was driven by a newly emerging Clade IIb lineage, G.1, descended from lineages circulating in the ongoing Nigerian epidemic. Phylogeographic reconstructions indicate that G.1 arose in late September 2024 and circulated undetected for approximately three months before establishing sustained transmission in the densely populated Western Area Urban and Rural districts, which became the principal source of repeated viral introductions that drove epidemics in other regions. Together, these findings reveal the origins and dispersal dynamics of the 2025 mpox outbreak in Sierra Leone and underscore that effective control remains achievable through targeted vaccination, strengthened early warning systems, and improved access to genomic and diagnostic surveillance.

Transmission reconstruction-the inference of who infects whom in disease outbreaks-offers critical insights into how pathogens spread and provides opportunities for targeted control measures. We developed JUNIPER (Joint Underlying Network Inference for Phylogenetic and Epidemiological Reconstructions), a highly-scalable pathogen outbreak reconstruction tool that incorporates intrahost variation, incomplete sampling, and algorithmic parallelization. Central to JUNIPER is a statistical model for within-host variant frequencies observed by next generation sequencing, which we validated on a dataset of over 160,000 deep-sequenced SARS-CoV-2 genomes. Combining this within-host variation model with population-level evolutionary and transmission models, we developed a method for inferring phylogenies and transmission trees simultaneously. We benchmarked JUNIPER on computer-generated and real outbreaks in which transmission links were known or epidemiologically confirmed. We demonstrated JUNIPER's real-world utility on two large-scale datasets: over 1,500 bovine H5N1 cases and over 13,000 human COVID-19 cases. Based on these analyses, we quantified the elevated H5N1 transmission rates in California and identified high-confidence transmission events, and demonstrated the efficacy of vaccination for reducing SARS-CoV-2 transmission. By overcoming computational and methodological limitations in existing outbreak reconstruction tools, JUNIPER provides a robust framework for studying pathogen spread at scale.

Pathogen genomic analysis is central to tracking, understanding, and containing outbreaks, but complexity and high costs of state-of-the-art (SOTA) phylogenetic tools limit global access and impact. We introduce Delphy, an exact reformulation of Bayesian phylogenetics designed to transform its speed, scalability and accessibility while retaining SOTA accuracy. Delphy's central data structure, an Explicit Mutation Annotated Tree, exploits the high sequence similarity in large-scale epidemic datasets for efficient tree exploration and convergence. By reproducing key analyses from recent major epidemics (Ebola, Zika, SARS-CoV-2, mpox, and H5N1), we demonstrate SOTA accuracy with up to 1,000x speedups. Assessing Delphy's scalability, we show that a simulated dataset of 100,000 sequences can be analyzed in under a day—the largest such computation to date. We distribute Delphy as a client-side web application, enabling users worldwide to turn raw data into interactive results within minutes, without the data ever leaving the user's machine. Delphy automatically identifies key viral lineages and mutations, as well as their emergence and prevalence through time, all with quantified uncertainties derived from a solid theoretical foundation. Delphy shows the power of Bayesian phylogenetics as a fast, accessible frontline tool for tackling future outbreaks. ### Competing Interest Statement P.V., B.F., M.S., K.Y., I.S., M.D.M. and P.C.S. are inventors on Patent Application No. PCT/US2024/050993 filed for this work; Delphy is free for all academic use. P.C.S. is a co-founder of, shareholder in Delve Bio; she was formerly a co-founder of and shareholder in Sherlock Biosciences, Inc and a Board member of and shareholder in Danaher Corporation. B.F. is the Founder of Fathom Information Design, a design and software development firm in Boston.

Five years before the 2022 multi-country mpox outbreak, Nigeria and Cameroon reported their first cases in more than three decades1,2. Whereas the outbreak in Nigeria is recognized as an ongoing human epidemic, the drivers of the resurgence in Cameroon remain unclear3,4. The rate of zoonoses remains uncertain in both countries, and gaps in genomic data obscure the timing and zoonotic and geographic origin of monkeypox virus (MPXV) emergence in humans. Here, to address these uncertainties, we sequenced 118 MPXV genomes isolated from cases in Nigeria and Cameroon between 2018 and 2023. We show that in contrast to cases in Nigeria, cases in Cameroon are the result of repeated zoonoses, with two distinct zoonotic lineages circulating across the Nigeria-Cameroon border. Our findings suggest that shared animal populations in the cross-border forest ecosystems drive the emergence and spread of the virus. Accordingly, we identify the closest zoonotic outgroup to the Nigerian human epidemic lineage (hMPXV-1) in a southern Nigerian border state. We estimate that the shared ancestor of the zoonotic outgroup and hMPXV-1 circulated in animals in southern Nigeria in late 2013. We find that hMPXV-1 emerged in humans in August 2014 in the southern Rivers State and circulated undetected for three years. Rivers State was the main source of viral spread during the human epidemic. Our study sheds light on the recent establishment of MPXV in the human population and highlights the risk of persistent zoonotic emergence of MPXV in the complex border regions of Cameroon and Nigeria.

Nigeria and Cameroon reported their first mpox cases in over three decades in 2017 and 2018 respectively. The outbreak in Nigeria is recognised as an ongoing human epidemic. However, owing to sparse surveillance and genomic data, it is not known whether the increase in cases in Cameroon is driven by zoonotic or sustained human transmission. Notably, the frequency of zoonotic transmission remains unknown in both Cameroon and Nigeria. To address these uncertainties, we investigated the zoonotic transmission dynamics of the mpox virus (MPXV) in Cameroon and Nigeria, with a particular focus on the border regions. We show that in these regions mpox cases are still driven by zoonotic transmission of a newly identified Clade IIb.1. We identify two distinct zoonotic lineages that circulate across the Nigeria-Cameroon border, with evidence of recent and historic cross border dissemination. Our findings support that the complex cross-border forest ecosystems likely hosts shared animal populations that drive cross-border viral spread, which is likely where extant Clade IIb originated. We identify that the closest zoonotic outgroup to the human epidemic circulated in southern Nigeria in October 2013. We also show that the zoonotic precursor lineage circulated in an animal population in southern Nigeria for more than 45 years. This supports findings that southern Nigeria was the origin of the human epidemic. Our study highlights the ongoing MPXV zoonotic transmission in Cameroon and Nigeria, underscoring the continuous risk of MPXV (re)emergence.

Five years before the 2022-2023 global mpox outbreak Nigeria reported its first cases in nearly 40 years, with the ongoing epidemic since driven by sustained human-to-human transmission. However, limited genomic data has left questions about the timing and origin of the mpox virus' (MPXV) emergence. Here we generated 112 MPXV genomes from Nigeria from 2021-2023. We identify the closest zoonotic outgroup to the human epidemic in southern Nigeria, and estimate that the lineage transmitting from human-to-human emerged around July 2014, circulating cryptically until detected in September 2017. The epidemic originated in Southern Nigeria, particularly Rivers State, which also acted as a persistent and dominant source of viral dissemination to other states. We show that APOBEC3 activity increased MPXV's evolutionary rate twenty-fold during human-to-human transmission. We also show how Delphy, a tool for near-real-time Bayesian phylogenetics, can aid rapid outbreak analytics. Our study sheds light on MPXV's establishment in West Africa before the 2022-2023 global outbreak and highlights the need for improved pathogen surveillance and response.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Recently, Rogers and Crocker (1) proposed a method to predict the interaction between colloids coated with two kinds of ssDNA, A and B. A key step in ref. 1 was to estimate the average number of DNA bonds, 〈N〉, assuming local chemical equilibrium (LCE) between hybridized and unhybridized sticky end concentrations:

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Author(s): Varilly, Patrick Stephen | Advisor(s): Chandler, David; Liphardt, Jan T | Abstract: The hydrophobic effect, or the tendency for oil and water not to mix, is a fundamental force that strongly influences the shape, behavior and assembly of solutes in solution. Hydrophobicity emerges from the collective behavior of large numbers of solvent molecules, so its accurate treatment is challenging. A decade ago, Lum, Chandler and Weeks (LCW) addressed this challenge indirectly by modeling how solvent density fluctuations couple to external solutes and constraints, and then inferring hydrophobic behavior from the resulting mean solvent density. LCW theory is successful because it distinguishes between, and separately models, small-length-scale and large-length-scale density fluctuations. In this thesis, we develop methods for probing the statistics of large-length-scale density fluctuations in computer simulations of water. We use these tools to study solvation phenomena in model systems and in proteins, in bulk water and near surfaces, and we rationalize these phenomena in terms of LCW ideas. Building on these ideas and on past efforts by others, we construct a tractable, efficient and accurate theory of solvation on a coarse-grained lattice. The final theory allows us to model the solvation behavior of uncharged, static solutes of arbitrary shape, and we outline the steps necessary to model charged, dynamic solutes in the future. A unifying thread in our solvation studies is the importance of fluctuations of liquid-vapor interfaces. At the end of this thesis, we describe how these fluctuations may play a role in water evaporation.