Biology subjects

Leung, J.

Publications and source records attributed to Leung, J..

At least 19 recordsLinked to original sources

bioRxiv2026

Phased Chromosome-level Genome and Organellar Assemblies of Castilleja foliolosa Provide Vital Resource for Orobanchaceae Genomics

Castilleja (Orobanchaceae) is a diverse, facultatively hemiparasitic plant genus characterized by a complex evolutionary history of reticulate evolution and significant taxonomic ambiguity. High-quality genomic resources have historically been limited, hindering robust macro-evolutionary and macro-ecological inquiries. Here, we present the first high-quality, phased, chromosome-level reference genome for the diploid species Castilleja foliolosa. Utilizing a hybrid assembly strategy, we integrated long-read PacBio HiFi sequencing with Omni-C proximity ligation data to generate a highly contiguous nuclear assembly, complemented by reconstructed mitochondrial and chloroplastic genomes. The primary nuclear haplotype spans approximately 510 Mbp, containing 39,417 predicted genes and a substantial repetitive landscape covering ~66% of the genome. Our organellar assemblies reveal notable structural complexity: the chloroplast maintains heteroplasmy via two primary structural haplotypes, while the 611 kbp mitogenome adopts a circular master topology existing in two isomeric forms. Comparative genomic analyses demonstrate a largely conserved chromosomal architecture relative to the closely related Pedicularis cranolopha, punctuated by the presence of lineage-specific genes. Functional enrichment of Castilleja-specific orthogroups identifies a consistent association with telomere maintenance, DNA integration, and zinc ion binding, likely stemming from the substantial repeat content. This reference genome provides a robust framework for dissecting the genomic drivers of taxonomic diversification and adaptation within the Orobanchaceae family. This resource significantly enhances our capacity to untangle reticulate evolutionary patterns, offering a definitive foundation for future comparative studies of genome evolution in the Orobanchaceae lineage of parasitic plants.

plant biology↗

bioRxiv2026

Organelle Capture, Lineage-Specific Genomic Responses, and the Lability of Dioecy in Amaranthus

The transition from combined to separate sexes in plants drives genomic change, from recombination suppression at sex-determining loci to shifts in selection across autosomes and cytoplasmic genomes. In Amaranthus, a genus that includes ancient grain crops and noxious weeds, separate sexes arose twice through non-homologous sex-determining architectures, with at least one reversion to monoecy, yet plastid and mitochondrial phylogenies group the two dioecious lineages together despite independent origins. The source of this discordance and whether independent origins of dioecy produced parallel or lineage-specific genomic responses remain unknown. We sampled nuclear, plastid, and mitochondrial genomes across 19 species, resolving the backbone phylogeny of the genus and dating the crown to 2-5 Ma. Coalescent simulations rejected incomplete lineage sorting in favor of multiple organelle capture events, implying historical exchange across reproductive barriers separating the two dioecious clades. Nuclear allele sharing was concentrated within each dioecious clade rather than between them, consistent with recombination eroding nuclear donor ancestry while captured cytoplasmic genomes persist. Dioecy was associated with genome-wide shifts in selection intensity, with positive selection concentrated on the stems of each dioecious clade but targeting largely non-overlapping genes and leaving little signature within sex-determining regions. Plastid coding sequences evolved under relaxed purifying selection, and nuclear-encoded plastid-targeted genes were enriched for episodic positive selection, consistent with compensatory cytonuclear evolution. The probable reversion to monoecy in A. pumilus, within a lineage shaped by repeated organelle capture, raises the possibility that hybridization and the lability of separate sexes are connected in this group.

evolutionary biology↗

bioRxiv2026

Pathway Representation via Intrinsic Structural Medoids (PRISM): A Structural Mapping Approach to Clustering Molecular Pathways

We present Pathway Representation via Intrinsic Structural Medoids (PRISM), a state-aware framework for clustering pathways from molecular dynamics simulations of biomolecular transitions. In PRISM, each pathway is mapped to a small set of structural medoids obtained via a deterministic k-means clustering scheme. Pairwise pathway dissimilarities are computed using a weighted average Hausdorff distance between these representative sets, effectively capturing mean nearest-neighbor structural deviations while reducing sensitivity to outliers. Hierarchical agglomerative clustering of the resulting dissimilarity matrix defines pathway families. We evaluate PRISM across three biomolecular transitions of increasing complexity: alanine dipeptide C7eq [->] C7ax isomerization, adenylate kinase opening, and HIF-2 PAS-B ligand unbinding. PRISM consistently yields robust cluster assignments, with medoids faithfully representing distinct conformational states. By combining a state-based description with robust geometric dissimilarities, PRISM provides a scalable framework for organizing complex transition pathways.

biophysics↗

bioRxiv2026

Direct Counting of mRNA Copies Inside Individual Lipid Nanoparticles Using In Situ Lysis and Labeling

The optimization of mRNA-lipid nanoparticles (mRNA-LNPs) for therapeutic applications is limited in part by the inadequate characterization of mRNA payload heterogeneity. One current challenge is accurately measuring the number of mRNA copies within individual LNPs, where the standard method of intensity-based mRNA number determination is sensitive to fluorescent dye-dye interactions and heterogeneity of mRNA labeling. Here we present a single-particle microscopy method that combines direct counting of the mRNA copies per LNP with LNP size measurements. While confined in microwells, individual mRNA-LNPs are lysed to release their cargo and stained with a dye such that the number of mRNA molecules in each well can be directly counted using fluorescence microscopy. Since the method stains the mRNA cargo in situ, it enables characterization of LNPs formulated with therapeutic grade (e.g., unlabeled) mRNA. We applied this approach to two Onpattro(R)-based LNP formulations prepared using different formulation buffers, where the two formulations had different average mRNA copy number, particle size, and fraction of LNPs lacking mRNA. The ability to directly count the number of mRNA molecules in LNPs establishes a complimentary method to intensity-based mRNA number determination and supports the characterization and screening of clinically relevant LNP formulations.

biophysics↗

bioRxiv2025

A scalable transposon mutagenesis system for non-model bacteria

Transposon mutagenesis enables genome-wide interrogation of gene function with a single self-contained genetic construct. However, its application to non-model bacteria remains limited because transposition efficiency depends on multiple host factors that are difficult to predict a priori including transposase activity, antibiotic resistance marker performance, and regulatory element compatibility. Here, we present a scalable system to identify functional transposon configurations in non-model bacteria through pooled library screening. We selected 18 promoters across multiple bacterial phyla to independently drive expression of the transposase and antibiotic resistance marker, generating 324 promoter combinatorial variants for each of six antibiotic resistance markers. We developed a high-throughput, automated workflow to deliver all 1,944 mariner-based transposon variants in a single experiment and applied this to 92 non-model bacteria spanning multiple phyla. From this, we identified functional transposons for 43 strains, with high-level mutagenesis (102-104 unique insertions) in 13 species, including seven with no previously described transposon mutagenesis. We then expanded to a dual-transposase system, mariner or Tn5, and devised a single transposon insertion sequencing method for high-throughput screening of 3,888 configurations. To demonstrate the practical utility of our screening approach, we used a top-performing variant to generate a genome-wide transposon mutant library for Comamonas testosteroni KF-1, a bacterium that metabolizes plastic- and lignin-derived polymers. We assayed this C. testosteroni mutant library to identify enzymatic pathways, transporter genes, and regulators essential for the metabolism of plastics-associated monomer terephthalate and lignin-associated monomer 4-hydroxybenzoate. Together, this work establishes a scalable approach to construct and identify genetic perturbation systems in non-model bacteria, expanding our ability to systematically probe gene function across the bacterial tree of life.

synthetic biology↗

bioRxiv2025

A genetic platform for a biocementation bacterium

Sporosarcina pasteurii is the most widely studied bacterium for microbially-induced calcium carbonate precipitation (MICP), a process of intense interest for materials and construction applications. Despite two decades of investigation, S. pasteurii has remained genetically intractable, limiting our mechanistic understanding of biomineralization pathways and constraining efforts to engineer scalable solutions. Here, we present the first genetic toolkit for S. pasteurii, including a stable replicating plasmid, a conjugation-based DNA delivery protocol, engineered inducible promoters, and methods for genome modification. Using homologous recombination, we precisely deleted 5.7 kb of the genome spanning two operons encoding urease activity and demonstrated complete loss of biocementation. We also screened a library of engineered transposon constructs for activity in S. pasteurii and generated a genome-wide mutant library with >15,000 unique insertion sites. Using this library, we identified putative genes affecting ureolytic growth, revealing previously inaccessible aspects of S. pasteurii genetics. This work establishes S. pasteurii as a genetically tractable platform for rational engineering of MICP and constitutes the first genetic modification capability within the Sporosarcina genus.

synthetic biology↗

bioRxiv2025

Active learning guides automated discovery of DNA delivery via electroporation for non-model microbes

Delivery of recombinant DNA is foundational for understanding and engineering a target organism. Electroporation can be applied to any cell type, yet identification of a working protocol for new organisms remains bespoke and laborious because no systematic framework exists, and appropriate instrumentation is lacking. Here, we describe an automated high-throughput platform which uses active learning to discover electroporation protocols for non-model microbes. We first devised a 24-condition electroporation screen, based on systematic evaluation and selection of key parameters, that can be applied to any microbe. Facilitated by a custom-built fully-programmable electroporator, we successfully identified electroporation protocols for eight non-model bacteria using this screen alone. We then combined this electroporation screen with our pooled POSSUM plasmid library to simultaneously evaluate 408 experimental conditions per organism and identified both a protocol and a replicating plasmid for five non-model Proteobacteria spanning three major classes (alpha-, beta-, and gamma-). We report the first electroporation protocols for Shewanella indica, Shewanella putrefaciens 200, Shewanella putrefaciens 95, Halomonas elongata, Piscinibacter sakaiensis, and Duganella zoogloeoides, as well as multiple alternative protocols for Shewanella amazonensis, Shewanella oneidensis, Azospirillum brasilense, Cupriavidus necator, Pseudomonas alcaliphila, and Escherichia coli. Finally, we developed an active learning pipeline to guide the selection of parameters based on gathered experimental data. Using our robotic platform, we iteratively tested 538 conditions over three iterations to improve electroporation for the emerging industrial chassis C. necator, achieving 8.6-fold higher transformation efficiency than state of the art. This work establishes a discovery platform for DNA delivery to diverse and recalcitrant microbes that can be extended broadly to non-model organisms in our biosphere.

microbiology↗

bioRxiv2025

Functional genomics in a microbe that degrades and metabolizes PET plastic

Piscinibacter sakaiensis (formerly Ideonella sakaiensis) was the first bacterial species known to both completely degrade and assimilate polyethylene terephthalate (PET). However, the absence of efficient genetic tools has limited direct engineering of this organism, forcing most efforts to rely on heterologous expression of PET-degrading enzymes in model hosts. Here, we establish foundational genetic tools to engineer P. sakaiensis. We identify a functional plasmid origin of replication, multiple new selectable markers, and a transposon system for the strain. We use these tools to construct a genome-wide, barcoded transposon mutant library for pooled high-throughput functional screens. We apply this mutant library to growth on PET and identify metabolic and physiological genes that impact PET biodegradation. We also use this library to reveal mutants with improved DNA uptake for genome engineering. Together, these advances provide a platform for functional genomics in P. sakaiensis and positions this naturally evolved plastic-degrading bacterium as an engineerable chassis for synthetic biology and sustainable materials research.

microbiology↗

bioRxiv2025

Single-particle multi-parametric microscopy reveals structural, size, and payload heterogeneity in mRNA-loaded lipid nanoparticles

Deciphering the heterogeneity of mRNA-containing lipid nanoparticles (LNPs) is essential for understanding the relationship between their microscopic properties and therapeutic function. Here, by combining alternating laser excitation (ALEX) with Convex Lens-induced Confinement (CLiC) microscopy, we simultaneously measure size, multi-color fluorescence, mRNA payload, and Forster resonance energy transfer (FRET) of individual suspended LNPs containing labeled lipid and mRNA molecules. By varying formulation parameters, including ionizable lipids, formulation buffers, and molecular ratios, we investigated and correlated key microscopic properties for relevant vaccine formulations. While the per-particle lipid fluorescence was lower for empty versus mRNA-loaded particles for all formulations, the relative size of empty versus mRNA-loaded particles depended upon the formulation and intraparticle structure. When comparing CLiC-ALEX to cryogenic transmission electron microscopy measurements (Cryo-TEM), for the LNP formulations that display blebs, the fraction of bleb LNPs is in close agreement with the fraction of mRNA-containing LNPs. CLiC-ALEX also enabled quantification of the per-particle mRNA fluorescence and FRET signals, and thus the heterogeneity in the mRNA copy number and mRNA-LNP structural arrangements, where the results were compared with biophysical estimates based on the LNP formulations. These rigorous biophysical insights are critical to inform our understanding of structure-activity relationships and inform rational design of nanomedicines.

biophysics↗

bioRxiv2025

SHINE: Deterministic Many-to-Many clustering of Molecular Pathways

State-of-the-art molecular dynamics (MD) simulation methods can generate diverse ensembles of pathways for complex biological processes. Analyzing these pathways using statistical mechanics tools demands identifying key states that contribute to both the dynamic and equilibrium properties of the system. This task becomes especially challenging when analyzing multiple MD simulations simultaneously, a common scenario in enhanced sampling techniques like the weighted ensemble strategy. Here, we present a new module of the MDANCE package designed to streamline the analysis of pathway ensembles. This module integrates n-ary similarity, cheminformatics-inspired tools, and hierarchical clustering to improve analysis efficiency. We present the theoretical foundation behind this approach, termed Sampling Hierarchical Intrinsic N-ary Ensembles (SHINE), and demonstrate its application to simulations of alanine dipeptide and adenylate kinase.

biophysics↗

bioRxiv2025

Advanced Manufacturing of Coil-Reinforced Multilayer Vascular Grafts to Optimize Biomechanical Performance

Small diameter vascular grafts require a complex balance of biomechanical properties to achieve target burst pressure, arterial compliance-matching, and kink resistance to prevent failure. Iterative design of our multilayer vascular was previously used to achieve high compliance while retaining the requisite burst pressure and suture retention strength for clinical use. To impart kink resistance, a custom 3D solution printer was used to add a polymeric coil to the electrospun polyurethane graft to support the graft during bending. The addition of this reinforcing coil increased kink resistance but reduced compliance. A matrix of grafts were fabricated and tested to establish key structure-property relationships between coil parameters (spacing, diameter, modulus) and biomechanical properties (compliance, kink radius). A successful graft design was identified with a compliance similar to saphenous vein grafts (4.1 {+/-} 0.4 %/mmHgx10-2) while maintaining comparable kink resistance to grafts used currently in the clinic. To explore graft combinations that could increase graft compliance to match arterial values while retaining this kink resistance, we utilized finite element (FE) models of compliance and kink radius that simulated experimental testing. The FE-predicted graft compliance agreed well with experimental values. Although the kink model over-predicted the experimental kink radius values, key trends between graft parameters and kink resistance were reproduced. As an initial proof-of-concept, the validated models were then utilized to parse through a targeted graft design space. Although this initial parameter range tested did not yield a graft that improved upon the previous balance of graft properties, this combination of advanced manufacturing and computational framework paves the way for future model-driven design to further optimize graft performance. TOC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=97 SRC="FIGDIR/small/633374v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@faca56org.highwire.dtl.DTLVardef@f9dccforg.highwire.dtl.DTLVardef@fbb5corg.highwire.dtl.DTLVardef@d5c021_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2024

A Computational Framework to Optimize the Mechanical Behavior of Synthetic Vascular Grafts

The failure of synthetic small-diameter vascular grafts has been attributed to a mismatch in the compliance between the graft and native artery, driving mechanisms that promote thrombosis and neointimal hyperplasia. Additionally, the buckling of grafts results in large deformations that can lead to device failure. Although design features can be added to lessen the buckling potential, the addition is detrimental to decreasing compliance (e.g., reinforcing coil). Herein, we developed a novel finite element framework to inform vascular graft design by evaluating compliance and resistance to buckling. A batch-processing scheme iterated across the multi-dimensional design parameter space, which included three parameters: coil thickness, modulus, and spacing. Three types of finite element models were created in FEBio for each unique coil-reinforced graft parameter combination to simulate pressurization, axial buckling, and bent buckling, and results were analyzed to quantify compliance, buckling load, and kink radius, respectively, from each model. Importantly, model validation demonstrated that model predictions agree qualitatively and quantitatively with experimental observations. Subsequently, data for each design parameter combination were integrated into an optimization function for which a minimum value was sought. The optimization values identified various candidate graft designs with promising mechanical properties. Our investigation successfully demonstrated the model-directed framework identified vascular graft designs with optimal mechanical properties, which can potentially improve clinical outcomes by addressing device failure. In addition, the presented computational framework promotes model-directed device design for a broad range of biomaterial and regenerative medicine strategies.

bioengineering↗

bioRxiv2024

Unsupervised learning of progress coordinates during weighted ensemble simulations: Application to millisecond protein folding

A major challenge for many rare-event sampling strategies is the identification of progress coordinates that capture the slowest relevant motions. Machine-learning methods that can identify progress coordinates in an unsupervised manner have therefore been of great interest to the simulation community. Here, we developed a general method for identifying progress coordinates "on-the-fly" during weighted ensemble (WE) rare-event sampling via deep learning (DL) of outliers among sampled conformations. Our method identifies outliers in a latent space model of the systems sampled conformations that is periodically trained using a convolutional variational autoencoder. As a proof of principle, we applied our DL-enhanced WE method to simulate a millisecond protein folding process. To enable rapid tests, our simulations propagated discrete-state synthetic molecular dynamics trajectories using a generative, fine-grained Markov state model. Results revealed that our on-the-fly DL of outliers enhanced the efficiency of WE by >3-fold in estimating the folding rate constant. Our efforts are a significant step forward in the unsupervised learning of slow coordinates during rare event sampling.

biophysics↗

bioRxiv2024

Autophosphorylation of the Tousled-like kinases TLK1 and TLK2 regulates recruitment to damaged chromatin via PCNA interaction

Tousled-like kinases 1 and 2 (TLK1 and 2) are cell cycle-regulated serine/threonine kinases that are involved in multiple biological processes. Mutation of TLK1 and 2 confer neurodegenerative diseases. Recent studies demonstrate that TLK1 and 2 are involved in DNA repair. However, there is no direct evidence that TLK1 and 2 function at DNA damage sites. Here, we show that both TLK1 and TLK2 are hyper-autophosphorylated at their N-termini, at least in part, mediated by their homo-or hetero-dimerization. We found that TLK1 and 2 hyper-autophosphorylation suppresses their recruitment to damaged chromatin. Furthermore, both TLK1 and 2 associate with PCNA specifically through their evolutionarily conserved non-canonical PCNA-interacting protein (PIP) box at the N-terminus, and mutation of the PIP-box abolishes their recruitment to DNA damage sites. Mechanistically, the TLK1 and 2 hyper-autophosphorylation masks the PIP-box and negatively regulates their recruitment to the DNA damage site. Overall, our study dissects the detailed genetic regulation of TLK1 and 2 at damaged chromatin, which provides important insights into their emerging roles in DNA repair.

genetics↗

bioRxiv2024

Exploring Mechanisms of Lipid Nanoparticle-Mucus Interactions in Healthy and Cystic Fibrosis Conditions

Mucus forms the first defense line of human lungs, and as such hampers the efficient delivery of therapeutics to the underlying epithelium. This holds particularly true for genetic cargo such as CRISPR-based gene editing tools which cannot readily surmount the mucosal barrier. While lipid nanoparticles (LNPs) emerged as versatile non-viral gene delivery systems that could help overcome the delivery challenge, many knowledge gaps remain, especially for diseased states such as cystic fibrosis (CF). This study provides fundamental insights into Cas9 mRNA or ribonucleoprotein-loaded LNP-mucus interactions in healthy and diseased states by assessing the impact of the genetic cargo, mucin sialylation, mucin concentration, ionic strength, pH, and polyethylene glycol (PEG) concentration and nature on LNP diffusivity leveraging experimental approaches and Brownian dynamics simulations. Taken together, this study identifies key mucus and LNP characteristics that are critical to enabling a rational LNP design for transmucosal delivery. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/575680v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@10b1c0dorg.highwire.dtl.DTLVardef@5ebce4org.highwire.dtl.DTLVardef@1c34c1corg.highwire.dtl.DTLVardef@b9eb2d_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2024

Inferring strain-level mutational drivers of phage-bacteria interaction phenotypes

The enormous diversity of bacteriophages and their bacterial hosts presents a significant challenge to predict which phages infect a focal set of bacteria. Infection is largely determined by complementary - and largely uncharacterized - genetics of adsorption, injection, cell take-over and lysis. Here we present a machine learning approach to predict phage-bacteria interactions trained on genome sequences of and phenotypic interactions amongst 51 Escherichia coli strains and 45 phage{lambda} strains that coevolved in laboratory conditions for 37 days. Leveraging multiple inference strategies and without a priori knowledge of driver mutations, this framework predicts both who infects whom and the quantitative levels of infections across a suite of 2,295 potential interactions. We found that the most effective approach inferred interaction phenotypes from independent contributions from phage and bacteria mutations, accurately predicting 86% of interactions while reducing the relative error in the estimated strength of the infection phenotype by 40%. Feature selection revealed key phage{lambda} and E. coli mutations that have a significant influence on the outcome of phage-bacteria interactions, corroborating sites previously known to affect phage{lambda} infections, as well as identifying mutations in genes of unknown function not previously shown to influence bacterial resistance. The methods success in recapitulating strain-level infection outcomes arising during coevolutionary dynamics may also help inform generalized approaches for imputing genetic drivers of interaction phenotypes in complex communities of phage and bacteria.

bioinformatics↗

bioRxiv2023

Hydrogel-Polyurethane Fiber Composites With Enhanced Microarchitectural Control For Heart Valve Replacement

Polymeric heart valves offer the potential to overcome the limited durability of tissue based bioprosthetic valves and the need for anticoagulant therapy of mechanical valve replacement options. However, developing a single-phase material with requisite biological properties and target mechanical properties remains a challenge. In this study, a composite heart valve material was developed where an electrospun mesh provides tunable mechanical properties and a hydrogel coating confers an antifouling surface for thromboresistance. Key biological responses were evaluated in comparison to glutaraldehyde-fixed pericardium. Platelet and bacterial attachment were reduced by 38% and 98%, respectively, as compared to pericardium that demonstrated the antifouling nature of the hydrogel coating. There was also a notable reduction (59%) in the calcification of the composite material as compared to pericardium. A custom 3D printed hydrogel coating setup was developed to make valve composites for device-level hemodynamic testing. Regurgitation fraction (9.6 {+/-} 1.8%) and effective orifice area (1.52 {+/-} 0.34 cm2) met ISO 5840-2:2021 requirements. Additionally, the mean pressure gradient was comparable to current clinical bioprosthetic heart valves demonstrating preliminary efficacy. Although the hemodynamic properties are promising, it is anticipated that the random microarchitecture will result in suboptimal strain fields and peak stresses that may accelerate leaflet fatigue and degeneration. Previous computational work has demonstrated that bioinspired fiber microarchitectures can improve strain homogeneity of valve materials toward improving durability. To this end, we developed advanced electrospinning methodologies to achieve polyurethane fiber microarchitectures that mimic or exceed the physiological ranges of alignment, tortuosity, and curvilinearity present in the native valve. Control of fiber alignment from a random fiber orientation at a normalized orientation index (NOI) 14.2 {+/-} 6.9% to highly aligned fibers at a NOI of 85.1 {+/-} 1.4%. was achieved through increasing mandrel rotational velocity. Fiber tortuosity and curvilinearity in the range of native valve features were introduced through a post-spinning annealing process and fiber collection on a conical mandrel geometry, respectively. Overall, these studies demonstrate the potential of hydrogel-polyurethane fiber composite as a heart valve material. Future studies will utilize the developed advanced electrospinning methodologies in combination with model-directed fabrication toward optimizing durability as a function of fiber microarchitecture.

bioengineering↗

bioRxiv2023

A common mechanism processes auditory and visual motion

We report behavioural findings implying common motion processing for auditory and visual motion. We presented brief translational motion stimuli drifting leftwards or rightwards in the visual or auditory modality at various speeds. Observers made a speed discrimination on each trial, comparing current speed against mean speed (i.e., method of single stimuli). Data were compiled into psychometric functions and means and slopes compared. Slopes between auditory and visual motion were identical, consistent with a common noise source, although mean speed for audition was veridical while visual speeds were significantly underestimated. An inter-trial analysis revealed clear motion priming in both audition and vision (i.e., faster perceived speed after a fast preceding speed, and vice versa - a positive serial dependence). Plotting priming as a function of preceding speed revealed the same slope for each modality. We also tested whether motion priming was modality specific. Whether vision preceded audition, or audition preceded vision, a positive serial bias (i.e., priming) was always observed. We conclude a common process underlies auditory and visual motion, and that this explains the closely matched data in vision and audition, as well as the crossmodal data showing equivalent motion priming regardless of the preceding trials modality.

animal behavior and cognition↗