Biology subjects

Weaver, S.

Publications and source records attributed to Weaver, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Verifiable Agentic Science on Public Infrastructure

Autonomous artificial intelligence agents are transforming the practice of science. Across every discipline, researchers are handing data analysis to coding agents that can design and execute complex studies from a single prompt. Yet this revolution carries a threat. When agents improvise in local environments, they leave no verifiable record, ultimately risking a wave of irreproducible science. Solving this crisis requires moving agentic science onto public infrastructure where every action leaves an examinable trail. Here we connect autonomous coding agents to shared computing resources, turning ephemeral prompts into auditable scientific records. After showing that 30 unguided local agents splinter into 18 incompatible pipelines on the same dataset, we conduct an agentic reproduction and discovery study on a large scale---reproducing a large, diverse array of studies with every workflow, history, and intermediate dataset publicly accessible. This complete provenance trail exposes unstated modeling choices, reference mismatches, and subsampled tutorial inputs in published studies, and establishes a new foundation where human scientists can understand, steer, and trust AI-driven discovery.

bioinformatics↗

bioRxiv2026

Clean Breaks: Attention Force Field Deconvolution of Recombination Across Sequence Manifolds

Homologous recombination and horizontal gene transfer assemble mosaic chromosomes across divergent lineages. Reticulate evolution violates bifurcating trees, yet existing detectors enforce a stark trade-off: phylogenetic changepoint models optimize partitioned topologies at exponential computational cost, whereas sequence triplet heuristics evaluate rapidly but suffer from severe combinatorial event overcounting. We introduce RhizAeon, an open-source platform that deconvolves reticulate evolution through continuous trajectory mechanics across metric embeddings in linear time (O(N K L)). Projecting aligned sequences into canonical metric coordinates and routing lineage-specific rate variation into an unpolarized root sink, the engine iteratively scrubs mosaic tracts and verifies breakpoints through Brownian-bridge statistics, dyadic matched filters, and maximum-likelihood polishing. Across canonical coalescent benchmarks and a continuous parameter sweep of 1,000,000 whole genomes, RhizAeon bounds false-positive rates well below the 5.0% nominal ceiling (0.58% on 1,200 rate-variation nulls and 1.01% across 333,334 continuous sweep nulls). Leave-one-in verification and bidirectional overlap clustering collapse co-recombinant clades into single ancestral reticulations. Empirical analyses across wildlife sarbecovirus Spike chimeras, multidrug-resistant Streptococcus pneumoniae chromosomes (2.22 Mb), and 379 primate HLA Class I alleles reconstruct complex whole-genome mosaicism, cassette exchanges, and micro-conversions in seconds. The core engine compiles to WebAssembly for interactive execution within standard web browsers.

evolutionary biology↗

bioRxiv2026

HyphAeon: Attention on Evolution Across Deep Time Transforms Comparative Genomics

Detecting Darwinian natural selection is fundamental to evolutionary biology and functional genomics, yet standard methods based on phylogenetic models that estimate the ratio of non-synonymous to synonymous substitution rates (dN/dS) fail to scale with modern genomic volumes. Fitting continuous-time Markov substitution matrices across dense trees with hundreds of species requires extensive compute, forcing comparative genomics to rely on aggressive taxon subsampling or static whole-tree summaries that dilute transient adaptive bursts. Here we present HyphAeon, a lightweight (~1.91M parameter backbone, 2.46M across the full multi-task suite) phylogeny-informed foundation transformer trained to amortize the detection of episodic diversifying selection across 742-species mammalian coding alignments (17,186 genes, 9.77 x 10^6 codons). HyphAeon approaches the discriminative accuracy of numerical maximum-likelihood selection tests (MEME) across episodic burst regimes (ROC-AUC up to 0.942, mean 0.659; empirical Precision-Recall lift up to 25.8x, mean 7.7x; rank concordance up to rho = 0.983) while executing >1,000x faster per locus (averaging <1 ms per site across genome-wide scans) and >10,000x faster at proteome scale, generalizing outside its mammalian training distribution without retraining. Beyond accelerating classical tests, embedding molecular evolution into a differentiable geometric latent space enables analytical capabilities inaccessible to static dN/dS models: (1) targeted alignment artifact correction via counterfactual attribution; (2) macromolecular contact recovery and multi-site epistatic sectors (CESI); (3) directional phenotype-to-genotype attribution in lineage space (PARS); and (4) continuous temporal surveillance regression that tracks positive sweep velocities across longitudinal cohorts (evaluated across 12,167 timestamped genomes and benchmarked against external frequencies from >9.34 million genomes), rescuing adaptive substitutions obscured by post-fixation dilution. By bridging statistical phylogenetics with geometric representation learning, HyphAeon establishes comparative genomics as an interactive, high-throughput computational framework for evolutionary discovery.

bioinformatics↗

bioRxiv2026

Whole mitochondrial genome sequencing identifies unique haplotype diversity and a lack of fine-scale genetic structure: a case study in the vulnerable estuarine turtle Malaclemys terrapin

A central goal when assessing patterns of population structure for conservation is to identify populations with unique genetic compositions. The use of genomic sequencing to identify distinct populations has become an increasingly popular method of delineating conservation units. Reduced costs associated with sequencing make it possible to generate larger, more informative datasets to assess genetic diversity within and among populations. In species that exhibit nest-site philopatry, genetic population structure can emerge on much finer scales, particularly in maternally inherited mitochondrial genomes. We demonstrate the feasibility and insight gained by using whole mitochondrial genome sequencing for evaluating population genetic structure and comparing to previous single marker studies in a vulnerable turtle. We used whole mitochondrial genome sequences from diamond-backed terrapin (Malaclemys terrapin) to evaluate whether nest-site philopatry generates fine-scale genetic structure among M. terrapin nesting beaches in western Mobile Bay (Alabama, USA). We then compared haplotype diversity between the Alabama population and M. terrapin populations from the Atlantic and Gulf coasts and evaluated the utility of using whole mitochondrial genomes rather than a subset of loci to characterize unique haplotypic diversity. We found no genetic structure associated with nest-site philopatry within Alabama, but none of the haplotypes in this region were shared with other Gulf Coast sites. This genetic structure is consistent with strong female natal philopatry within western Mobile Bay relative to the Gulf of Mexico and suggests that the Mobile Bay population is genetically unique relative to other M. terrapin populations and merits a unique conservation and management plan.

ecology↗

bioRxiv2026

Beyond Invariable Sites: Using Evolutionary Stasis to Map Multi-Layered Constraints on the Evolution of Viral and Mammalian Genomes

The quantification of genomic conservation has progressed from foundational statistical modeling of evolutionary rates to state-of-the-art phylogeny-aware deep learning architectures. Yet, a fundamental resolution gap remains whenever evolutionary rates closely approach the "zero-rate origin," where standard selection inference tools will essentially ignore signals of extreme purifying section at invariant genome sites. We present B-STILL (Bayesian Significance Test of Invariant Low Likelihoods), a hierarchical Bayesian framework designed to resolve the selective landscape of protein-coding data by leveraging gene-level calibration and codon-site specific evolutionary opportunity. This framework is based on computationally efficient approximations using codon-substitution models which are scalable to alignments with thousands of sequences. By explicitly tuning the stasis radius around the near-zero evolutionary-rate regime, B-STILL distinguishes between stochastic invariance and functional constraint, identifying Evolutionary Stasis Anchors (ESAs) where the upper bound on permitted evolutionary change is statistically anomalous relative to the background of the gene. This hierarchical approach provides a signature of functional or structural constraint that is often difficult to detect using other tools. Validation against extensive pathogen and clinical databases confirms that ESAs are predictors of biological fitness and disease potential. Collectively, we identified thousands of significantly clustered ESAs that precisely footprint both known functional domains and currently uncharacterized structural motifs in mammalian and viral genomes. These findings establish B-STILL as a scalable statistical framework for high-resolution genomic annotation, transforming formerly ignored invariant genome and protein sites into informative markers of extreme purifying selection across both well-characterized and uncharacterized protein-coding genes from different domains of life.

evolutionary biology↗

bioRxiv2026

Characterizing Physicochemical Selection in Protein Evolution with Property-Informed Models (PRIME)

AbstractStandard probabilistic models of coding sequence evolution effectively identify where and when selection acts but remain agnostic to the mechanistic realization of these forces. We introduce PRIME (PRoperty Informed Models of Evolution), a framework of codon-level maximum likelihood methods--including global (G-PRIME), episodic (E-PRIME), and site-specific (S-PRIME) implementations--that explicitly model amino acid exchange-ability as a function of physicochemical properties. By parameterizing attributes such as molecular volume, hydropathy, and secondary structure propensities, PRIME resolves the biophysical basis of selective constraint across both the sequence and the phylogeny. At the site level, S-PRIME leverages an explicit biophysical taxon-omy to precisely categorize residues as conserved, neutral, or changing for specific properties, resolving selective signals that remain invisible to traditional rate-based metrics. Our analysis of a benchmark of 24 diverse datasets and a genome-wide screen of 18,944 mammalian genes demonstrates that biophysical realism yields substantial improvements in model fit, acting synergistically with rate variation to explain complex evolutionary patterns. We find that power to detect physicochemical constraints at individual sites is fundamentally governed by simple informational redundancy (substitutions per unique amino acid; AUC = 0.91), with sensitivity exceeding 90% in data-rich alignments. E-PRIME reveals a distinct biophysical hierarchy: while core packing and beta-sheet scaffolds are rigidly conserved, alpha-helix propensity and surface electrostatics serve as the primary substrates for adaptive tuning. Furthermore, PRIME importance weights align with aspects of the primary semantic axes of deep learning representations (ESM-2) and capture key features of experimental fitness landscapes. By trans-forming abstract evolutionary rates into interpretable biophysical rules, PRIME provides a useful framework for characterizing the mechanistic drivers of protein diversity.

evolutionary biology↗

bioRxiv2025

Segmentally duplicated regulatory elements undergo human-specific rewiring

Gene regulatory innovation underlies many phenotypic transitions. Transposable elements are an established mechanism for creating families of cis-acting elements with shared sequence features and the potential to establish co-regulatory networks. To understand additional mechanisms by which co-regulatory networks form, we define families of noncoding elements based on sequence similarity and cell type-specific activity. We apply this analysis framework to the human telomere-to-telomere genome assembly and embryonic stem cell chromatin accessibility data. We identify segmental duplications as the major mechanism establishing these families, creating over one thousand networks of elements with open chromatin in embryonic stem cells. We functionally validate a subset of these networks as families of regulatory elements with STARR-seq and identify their target genes with CRISPRi in embryonic stem cells. Following segmental duplication, we find that regulatory elements at times maintain their relationship to target genes, and at times rewire to form novel connections. During this rewiring, we observe proximal-acting elements gaining the ability to regulate distally-located genes and observe transcriptional enhancers rewiring to regulate genes present at the locus outside the segmental duplication. Many of these rewiring events are human specific. Finally, we find that segmental duplications have made outsized contributions to expanding regulatory element families functioning in immune cell types and specific brain regions, including the posterior cingulate gyrus. We speculate that placing regulatory elements in new genomic contexts primes regulatory elements for neofunctionalization, and that regulatory rewiring after segmental duplication was a common mechanism underlying gene regulatory change during human evolution.

genomics↗

bioRxiv2025

Interrogating the Regulatory Function of HAQERs during Human Cortical Development

BackgroundSequence divergence within gene regulatory elements has been proposed to play an important role in the evolution of human-specific traits, including cortical expansion. However, the mutational processes that efficiently modify gene regulatory elements and the target genes upon which they act are poorly understood. We investigated the regulatory function and origins of the fastest evolved regions in the human genome, termed Human Ancestor Quickly Evolved Regions (HAQERs), in their native genomic context during human cerebral cortex development. ResultsWe identified 50 HAQERs with accessible chromatin in developing human cortex, largely arising from previously unconstrained ancestral sequences. To test the necessity of these HAQERs for gene regulation, we established an all-in-one CRISPRi lentiviral vector and linked 26 HAQERs to nearby target genes across cell types and Wnt pathway activation contexts. Rapid gains of CpGs distinguished HAQERs active during cortical development and displaying human-specific epigenomic marks. As a high density of CpG sites can drive formation of permissive chromatin, we identified 107 HAQERs with at least 17 human-specific CpG gains per kb, termed HAQER CpG Beacons. These HAQERs emerged via contributions from GC-biased gene conversion (gBGC) with evidence for selection preferentially fixing CpG sites. Notably, the CHL1 and DPP10 loci, both implicated in human neurological disorders, each harbored two gene-linked HAQER CpG Beacons. ConclusionsOur findings reveal HAQER target genes and support a model where gBGC and natural selection jointly drive regulatory-altering CpG variants to fixation, forging regulatory innovations in the human cortex.

evolutionary biology↗

bioRxiv2025

Lack of Reproducibility of Gulf War Illness-like Behavioral Effects in War-related Chemical Agents and Stressor Exposure Rat Models

Gulf War illness (GWI) is characterized by a range of neurological and neuropsychiatric symptoms, including chronic pain, fatigue, mood problems, and cognitive issues. The pathophysiology is associated with war-related environmental chemical exposure and psychological stress, which are known to disrupt glutamatergic synaptic structure and function. The goal of this study was to evaluate the efficacy of the investigational new drug LH-001, a candidate for enhancing tripartite glutamatergic synapses, in a rat model of GWI. We began by attempting to induce GWI-like phenotypes in rats using a previously published protocol involving exposure to specific chemical agents and mild stress. However, these efforts were unsuccessful, as the expected GWI symptoms were not observed. We then performed two protocol modifications--using more potent chemical exposures and higher stress levels--but were still unable to produce the desired phenotypes. Our results highlight significant issues with the reliability of current GWI rat models. A comparative analysis of other studies suggests that GWI-like behavioral effects, when induced in rats by chemical agents and stress, show a broader lack of reproducibility across different laboratories. This calls into question the robustness of current rat models for GWI and poses challenges for preclinical drug development.

neuroscience↗

bioRxiv2025

Intraspecific sequence variation and complete genomes refine the identification of rapidly evolved regions in humans

Summary Humans exhibit significant phenotypic differences from other great apes, yet pinpointing the underlying genetic changes has been limited by incomplete reference genomes and a reliance on single assemblies to represent a species. We aligned 20 telomere-to-telomere (T2T) assemblies spanning great ape divergence and variation to define 1,596 Consensus HAQERs (consensus human ancestor quickly evolved regions), regions that diverged rapidly between the human-chimpanzee ancestor and an ancestral node of modern humans. Unlike prior HAQER sets, Consensus HAQERs incorporate population variation, reducing the likelihood of intraspecies variation appearing as interspecies divergence. Consensus HAQERs exhibit signatures of elevated mutation rates, ancient positive selection, bivalent regulatory function, are enriched in disease-linked loci, and often emerged in previously inaccessible repetitive DNA. Through multiplex, single-cell enhancer assays, we identify HAQERs as active enhancers in the developing brain and cardiomyocytes, highlighting their potential contributions to human-specific gene regulation across multiple tissues. Highlights[bullet] Telomere-to-telomere alignments of diverse human and great ape genomes identify 1,596 Consensus HAQERs, regions of rapid sequence divergence separating human ancestors from other great apes. [bullet]Consensus HAQERs exhibit signatures of both elevated mutation rates and ancient positive selection. [bullet]HAQERs are enriched in bivalent regulatory elements and disease-linked loci. [bullet]Multiplex, single-cell gene regulatory assays identify HAQERs as enhancers in the developing heart and brain.

genomics↗

bioRxiv2025

HydroMEA: A 3D Hydrogel Based Microfluidic Device to Study Electrophysiology for Myelinated Nerve-on-Chip

Engineered in vitro platforms are powerful systems to study information flow in the nervous system. While existing polydimethylsiloxane (PDMS)-based microfluidic platforms offer precise architectures, the cultured neurons grow on two-dimensional (2D) planar multielectrode arrays (MEA). To mimic the native microenvironment, where neurons grow in three-dimensional (3D) extracellular matrices (ECM), 3D hydrogels can be designed to encapsulate cells and enable physiologically-mimicked behaviors. Here, we describe hydroMEA, a 3D platform fabricated by placing PDMS microstructures on a high-density MEA and filled with a desired hydrogel, to offer controlled topologies, physiologically-relevant microenvironments, and real-time electrophysiological measurements. First, we developed a gelatin methacryloyl (GelMA) hydrogel with incorporated ECM components and tuned the mechanical properties to match those of nerve tissue. The hydrogel was able to support: 1) the growth of iPSC-derived sensory neurons (hSNs) for >100 days; 2) co-cultures of hSN with human embryonic stem cell-derived Schwann cells (hSCs), to enable reliable 3D myelination. Next, hydroMEA were prepared for topologically- defined 3D growth and myelination in designated compartments. Finally, electrophysiological evaluation of hSN-hSCs co-cultures revealed increased conduction speeds indicating functional myelin. This platform is a promising tool to study cell-cell interactions and to functionally evaluate the effect of pharmacological compounds in a more translational manner.

bioengineering↗

bioRxiv2025

Genome Sequence of a Marine Threespine Stickleback (Gasterosteus aculeatus) from Rabbit Slough in the Cook Inlet

The Threespine Stickleback, Gasterosteus aculeatus, is an emerging model system for understanding the genomic basis of vertebrate adaptation. A strength of the system is that marine populations have repeatedly colonized freshwater environments, serving as natural biological replicates. These replicates have enabled researchers to efficiently identify phenotypes and genotypes under selection during this transition. While this repeated adaptation to freshwater has occurred throughout the northern hemisphere, the Cook Inlet in south-central Alaska has been an area of focus. The freshwater lakes in this area are being studied extensively and there is a high-quality freshwater reference assembly from a population in the region, Bear Paw Lake. Using a freshwater reference assembly is a potential limitation because genomic segments are repeatedly lost during freshwater adaptation. This scenario results in some of the key regions associated with marine-freshwater divergence being absent from freshwater genomes, and therefore absent from the reference assemblies. It may also be that isolated freshwater populations are more genetically diverged, potentially increasing reference biases. Here we present a highly-continuous marine assembly from Rabbit Slough in the Cook Inlet. All contigs are from long-read sequencing and have been ordered and oriented with Hi-C. The contigs are anchored to chromosomes and form a 454 Mbp assembly with an N50 of 1.3 Mbp, an L50 of 95, and a BUSCO score over 97%. The organization of the chromosomes in this marine individual is similar to existing freshwater assemblies, but with important structural differences, including the 3 previously known inversions that repeatedly separate marine and freshwater ecotypes. We anticipate that this high-quality marine assembly will more accurately reflect the ancestral population that founded the freshwater lakes in the area and will more closely match most other populations from around the world. This marine assembly, which includes the repeatedly deleted segments and offers a closer reference sequence for most populations, will enable more comprehensive and accurate computational and functional genomic investigations of Threespine Stickleback evolution.

genomics↗

bioRxiv2024

Engineered biological neural networks as basic logic operators

We present an in vitro neuronal network with controlled topology capable of performing basic Boolean computations, such as NAND and OR. Neurons cultured within polydimethylsiloxane (PDMS) microstructures on high-density microelectrode arrays (HD-MEAs) enable precise interaction through extracellular voltage stimulation and spiking activity recording. The architecture of our system allows for creating non-linear functions with two inputs and one output. Additionally, we analyze various encoding schemes, comparing the limitations of rate coding with the potential advantages of spike-timing-based coding strategies. This work contributes to the advancement of hybrid intelligence and biocomputing by offering insights into neural information encoding and decoding with the potential to create fully biological computational systems.

neuroscience↗

bioRxiv2024

Minus the Error: Estimating dN/dS and Testing for Natural Selection in the Presence of Residual Alignment Errors

Positive selection is an evolutionary process which increases the frequency of advantageous mutations because they confer a fitness benefit. Inferring the past action of positive selection on protein-coding sequences is fundamental for deciphering phenotypic diversity and the emergence of novel traits. With the advent of genome-wide comparative genomic datasets, researchers can analyze selection not only at the level of individual genes but also globally, delivering systems-level insights into evolutionary dynamics. However, genome-scale datasets are generated with automated pipelines and imperfect curation that does not eliminate all sequencing, annotation, and alignment errors. Positive selection inference methods are highly sensitive to such errors. We present BUSTED-E: a method designed to detect positive selection for amino acid diversification while concurrently identifying some alignment errors. This method builds on the flexible branch-site random effects model (BUSTED) for fitting distributions of dN/dS, with a critical modification: it incorporates an "error-sink" component to represent an abiological evolutionary regime. Using several genome-scale biological datasets that were extensively filtered using state-of-the art automated alignment tools, we show that BUSTED-E identifies pervasive residual alignment errors, produces more realistic estimates of positive selection, reduces bias, and improves biological interpretation. The BUSTED-E model promises to be a more stringent filter to identify positive selection in genome-wide contexts, thus enabling further characterization and validation of the most biologically relevant cases.

evolutionary biology↗

bioRxiv2024

Three positively charged binding sites on the eastern equine encephalitis virus E2 glycoprotein coordinate heparan sulfate- and protein receptor-dependent infection

Naturally circulating strains of eastern equine encephalitis virus (EEEV) bind heparan sulfate (HS) receptors and this interaction has been linked to its neurovirulence. Previous studies associated EEEV-HS interactions with three positively charged amino acid clusters on the E2 glycoprotein. One of these sites has recently been reported to be critical for binding EEEV to very-low-density lipoprotein receptor (VLDLR), an EEEV receptor protein. The proteins apolipoprotein E receptor 2 (ApoER2) isoforms 1 and 2, and LDLR have also been shown to function as EEEV receptors. Herein, we investigate the individual contribution of each HS interaction site to EEEV HS- and protein receptor-dependent infection in vitro and EEEV replication in animals. We show that each site contributes to both EEEV-HS and EEEV-protein receptor interactions, providing evidence that altering these interactions can affect disease in mice and eliminate mosquito infectivity. Thus, multiple HS-binding sites exist in EEEV E2, and these sites overlap functionally with protein receptor interaction sites, with each type of interaction contributing to tissue infectivity and disease phenotypes.

microbiology↗

bioRxiv2024

Aged mice exhibit faster acquisition of intravenous opioid self-administration with variable effects on intake

Although opioid abuse is more prevalent in young individuals, opioid use, overdose, and use disorders continue to climb at a rapid rate among the elderly. Little is known about abuse potential in a healthy aged population, in part due to technical and logistical difficulties testing intravenous self-administration in aged rodents. The goal of this study was to address the critical gap in the literature regarding age-dependent differences in opioid (remifentanil and fentanyl) self-administration between old and young mice. Male and female mice were grouped into young (mean: 19 weeks) and old (mean: 101 weeks), and were trained to self-administer intravenous fentanyl or remifentanil in daily sessions. In both old and young mice, acquisition, intake, and cue-responding after forced abstinence were measured for both drugs, and a dose-response curve (remifentanil) and dose-escalation (fentanyl) were conducted. Surprisingly, old mice learned to self-administer both remifentanil and fentanyl faster and more accurately than young mice. Baseline intake of remifentanil was also substantially greater in old mice compared to their young counterparts; however, we did not see increased intake of fentanyl with age at either dose tested. Further, compared to young mice, the old mice showed a greater incubation of responding for cues previously associated with remifentanil after a forced abstinence, but again this was not observed with fentanyl. Together these data suggest that an aged population may have an increased drug-abuse vulnerability for opioids compared to young counterparts and underscore the importance of future work on mechanisms responsible for this increased vulnerability.

animal behavior and cognition↗

bioRxiv2024

Impact of microchannel width on axons for brain-on-chip applications

Technologies for axon guidance for in vitro disease models and bottom up investigations are increasingly being used in neuroscience research. One of the most prevalent patterning methods is using polydimethylsiloxane (PDMS) microstructures due to compatibility with microscopy and electrophysiology which enables systematic tracking of axon development with precision and efficiency. Previous investigations of these guidance platforms have noted axons tend to follow edges and avoid sharp turns; however, the specific impact of spatial constraints remains only partially explored. We investigated the influence of microchannel width beyond a constriction point, as well as the number of available microchannels, on axon growth dynamics. Further, by manipulating the size of micron/submicron-sized PDMS tunnels we investigated the space restriction that prevents growth cone penetration showing that restrictions smaller than 350nm were sufficient to exclude axons. This research offers insights into the interplay of spatial constraints, axon development, and neural behavior. The findings are important for designing in vitro platforms and in vivo neural interfaces for both fundamental neuroscience and translational applications in rapidly evolving neural implant technologies.

neuroscience↗

bioRxiv2024

AUTO-TUNE: SELECTING THE DISTANCE THRESHOLD FOR INFERRING HIV TRANSMISSION CLUSTERS

Molecular surveillance of viral pathogens and inference of transmission networks from genomic data play an increasingly important role in public health efforts, especially for HIV-1. For many methods, the genetic distance threshold used to connect sequences in the transmission network is a key parameter informing the properties of inferred networks. Using a distance threshold that is too high can result in a network with many spurious links, making it difficult to interpret. Conversely, a distance threshold that is too low can result in a network with too few links, which may not capture key insights into clusters of public health concern. Published research using the HIV-TRACE software package frequently uses the default threshold of 0.015 substitutions/site for HIV pol gene sequences, but in many cases, investigators heuristically select other threshold parameters to better capture the underlying dynamics of the epidemic they are studying. Here, we present a general heuristic scoring approach for tuning a distance threshold adaptively, which seeks to prevent the formation of giant clusters. We prioritize the ratio of the sizes of the largest and the second largest cluster, maximizing the number of clusters present in the network. We apply our scoring heuristic to outbreaks with different characteristics, such as regional or temporal variability, and demonstrate the utility of using the scoring mechanisms suggested distance threshold to identify clusters exhibiting risk factors that would have otherwise been more difficult to identify. For example, while we found that a 0.015 substitutions/site distance threshold is typical for US-like epidemics, recent outbreaks like the CRF07_BC subtype among men who have sex with men (MSM) in China have been found to have a lower optimal threshold of 0.005 to better capture the transition from injected drug use (IDU) to MSM as the primary risk factor. Alternatively, in communities surrounding Lake Victoria in Uganda, where there has been sustained hetero-sexual transmission for many years, we found that a larger distance threshold is necessary to capture a more risk factor-diverse population with sparse sampling over a longer period of time. Such identification may allow for more informed intervention action by respective public health officials.

bioinformatics↗