Biology subjects

Brown, A.

Publications and source records attributed to Brown, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Genome assemblies and annotations of the poneroid ants Platythyrea mocquerysi (Ponerinae) and Stigmatomma oregonense (Amblyoponinae)

We present draft genome assemblies for two poneroid ant species with distinctive life history traits: Platythyrea mocquerysi Emery, 1899 (Ponerinae) and Stigmatomma oregonense Wheeler, 1915 (Amblyoponinae). Platythyrea mocquerysi is a Malagasy ant in which larvae produce secretions from a ventral tubercle that are consumed by adults, representing an unusual form of larva-to-adult trophallaxis. Stigmatomma oregonense, a North American "dracula ant," feeds non-lethally on larval haemolymph. Using PacBio HiFi long-read sequencing, we assembled the P. mocquerysi genome (187 Mb, 307 scaffolds, N50 = 5.26 Mb, BUSCO 99.2% complete) and the S. oregonense genome (262 Mb, 1,189 scaffolds, N50 = 0.84 Mb, BUSCO 98.3% complete). These genomes encode 10,860 and 12,354 protein-coding genes, respectively. Repeat content is higher in S. oregonense than in P. mocquerysi, 54.3% against a lower bound of 15.7%. Most of the difference is in unclassified repeats, which we show to be diverged transposable elements. Comparative analysis with two additional poneroid genomes from closely related species reveals that genome size variation across poneroid ants is largely explained by transposable element dynamics, with notable expansions in several gene families including carboxylesterases, serine proteases, and lipid metabolism genes in Amblyoponinae. These genomes provide essential resources for investigating the molecular basis of unconventional brood management strategies in ants.

genomics↗

bioRxiv2026

Staphylococcus aureus GpsB, Stk, and VraSR form a cell wall surveillance network to maintain cell envelope integrity and mediate antibiotic resistance

Antibiotic resistance is an alarming threat to public health worldwide. Specifically, drug-resistant Staphylococcus aureus remains a major contributor to global mortality. Therefore, in-depth understanding of antibiotic resistance mechanisms is urgently needed to inform alternative therapeutic strategies. We previously showed that GpsB is a critical regulator of cell wall synthesis in S. aureus. GpsB executes its regulatory role via protein-protein interactions. Yet, how GpsB function is modulated in this organism has remained unclear. Intriguingly, a prior proteomics report indicated that GpsB is phosphorylated at six different residues by the sole serine/threonine kinase Stk. Hence, we explored the physiological significance of GpsB phosphorylation. We identify three phosphosites that are each independently sufficient to drive GpsB phosphoregulation, which likely alters its partner preference. We find that cells lacking gpsB exhibit heightened fosfomycin sensitivity, and that this is exacerbated by stk deletion. Our findings reveal that GpsB collaborates with Stk and the VraSR cell wall stress response system to coordinate the demand-driven availability of cell wall precursors. Collectively, this report establishes GpsB as a pivotal peptidoglycan supply chain sentinel that together with Stk and VraSR forms an integrated cell wall stress monitoring network that maintains cell envelope homeostasis and aids in antibiotic resistance.

microbiology↗

bioRxiv2026

Fecal Contributors to an Urbanized Estuary Identified by a Multi-Species qPCR Approach

Coastal waters often experience fecal contamination from human (e.g., septic systems, wastewater treatment catchments and outfalls) and non-human (e.g., wildlife, domesticated pets, and livestock) origins, posing human health risks through contaminated fisheries and recreational waters. Quantitative PCR (qPCR) methods can identify and quantify fecal origins for their management by targeting Bacteroides, a dominant group of gastrointestinal bacteria with high host specificity. This study identified major contributors and drivers of fecal contamination to Mobile Bay, Alabama, an urbanized estuary in the southern United States. We utilized a multi-species qPCR source tracking approach targeting total Bacteroides and human-, pig-, dog-, cow-, and fowl-associated Bacteroides. Water samples and environmental parameters were collected over one year from 13 sites that represent a range of potential fecal inputs common to coastal waters. Human-associated feces were a consistent major contributor to the system (positive in 82% of samples), with localized inputs from pig (wild or domestic) and dog. Freshwater discharge and nitrogen constituents were good predictors of Bacteroides concentrations in this system, while areas with impervious surfaces and developed land cover may be contributing elevated fecal indicator levels. The multi-species qPCR source tracking approach described in this study can be implemented in other watersheds to support the development of better detection, identification, and fecal management strategies for community health of coastal areas.

microbiology↗

bioRxiv2026

Distinct Motor Cortex Somatotopy in Experimental Alzheimers Disease

Alzheimers Disease (AD) and related dementias (AD/RDs) impact cortical motor and sensory biology whereas the precise changes to these systems, and their clinical relevance, remain under debate. We hypothesized that cortical representations of complex and simple movements are differently altered during disease progression in 5XFAD mice, a well-established model of AD. Motor cortex somatotopy was determined in 5XFAD and Wild-Type Control (WT Control) mice at 6 and 12 months (mos.) of age using long-duration intracortical microstimulation (LD-ICMS) to systematically identify cortical sites evoking complex and simple forelimb movements. At 6 mos. of age, 5XFAD mice exhibited a significant expansion of motor cortical sites representing simple movements, specifically Elbow Flexion (p=0.0004) and Wrist Flexion (p=0.024). The over-sized territory for Elbow Flexion significantly distinguished 5XFAD from WT mice (Receiver Operating Characteristic [ROC] area under the curve [AUC]= 0.94, p= 0.0009) whereas discriminative performance of Wrist Flexion was a non-significant trend (AUC=0.75, p=0.059). By 12 mos. of age, motor cortex organization was markedly reorganized in 5XFAD mice, with significantly fewer cortical sites evoking complex Advance movement (p<0.0001) as well as simple Shoulder (p=0.0001), Elbow Extension (p=0.024), and Wrist Extension (p=0.003) movements. The number of sites for simple Wrist Flexion was significantly increased (p=0.011) in 12 mo. old 5XFAD mice. At 12 mos., territory size of several of these movement zones highly distinguished 5XFAD from WT mice, including Advance (AUC= 0.96, p= 0.0005), Shoulder (AUC= 0.97, p= 0.0004), Elbow Extension (AUC=0.78, p=0.034), Wrist Extension (AUC=0.85, p= 0.0082), and Wrist Flexion (AUC=0.80, p= 0.023). These findings demonstrate progressive, age-dependent remodeling of motor cortex somatotopy in 5XFAD mice, characterized by early expansion of specific simple movement cortical sites followed by deterioration of both complex and simple motor cortical maps as disease advances. Motor cortex somatotopic remodeling may provide a sensitive biomarker of AD/RDs progression.

neuroscience↗

bioRxiv2026

MetaboXcan: A multiomic framework linking genetically predicted metabolites, gene expression, and complex traits

Genetically regulated molecular phenotypes, such as gene expression and metabolites, are widely thought to mediate the effect of disease-relevant genetic loci identified by genome-wide association studies (GWAS); however, molecular mechanisms connecting genetic variation to disease remain poorly understood. While transcriptome-wide association studies (TWAS) have identified disease-associated genes, strategies that integrate the metabolome remain underexplored. Here, we introduce MetaboXcan, a framework for predicting plasma metabolite levels from genetic data and associating them with complex traits using GWAS summary statistics. We trained lasso regression models on plasma metabolite and genotype data from the Metabolic Syndrome in Men Study (METSIM); these models outperform existing genetic metabolite predictors and generalize well across independent cohorts. MetaboXcan leverages these models to perform four complementary association analyses: (i) gene-to-trait (TWAS), (ii) gene-to-metabolite (M-TWAS), (iii) metabolite-to-trait (MWAS), and (iv) gene-expression-based metabolite-to-trait associations (g-MWAS). The framework further organizes results into metabolic pathways and gene-metabolite interaction networks to facilitate biological interpretation. Applied to chronic kidney disease (CKD), MetaboXcan identified known disease risk genes (PDILT/UMOD, SPATA5L1/GATM), as well as multiple CKD-relevant metabolites (e.g., glycine, homoarginine). Our integrated multiomic analysis enables biological interpretation by revealing glycine availability-centered biochemical axes spanning oxidative stress, cellular energetics, and vascular signaling, while nominating candidate mechanisms for downstream investigation. These results validate known disease-related biology with genetic evidence and generate new hypotheses for further investigation. MetaboXcan is publicly available and broadly applicable to any GWAS phenotype.

genetics↗

bioRxiv2026

Rapid vaccine induction of macaque HIV-1 V2 Apex broadly neutralizing antibodies with immunogenetic signatures that are potentially translatable to humans

Due to the complex biology of HIV-1 broadly neutralizing antibodies (bnAbs), HIV-1 vaccines must target unmutated germline precursor antibodies with B cell receptors that have the appropriate specificity and genetic features to develop neutralization breadth. Previous work has shown that immunization or infection in macaques primes unmutated precursor antibodies that target the broadly neutralizing epitope composed of the second variable region and proximal glycans (termed V2-apex site) of HIV-1 envelope (Env). Macaque V2-apex bnAb precursors elicited thus far have homogeneous usage of the second reading frame of a diversity (D) gene found only in macaques, calling into question whether HIV-1 Env immunogens can elicit only this canonical, macaque-specific V2-apex antibody response, limiting human vaccination success. Here, we show that vaccination of rhesus macaques with Env conjugated to a ferritin nanoparticle (OPT4-scNP) rapidly elicited V2-apex bnAbs with distinct D gene segment usage and motifs that are not restricted only to macaques. After two priming immunizations, V2-apex antibodies with non-canonical HCDR3s exhibited greater neutralization potency and breadth than V2-apex antibodies with previously observed HCDR3 motifs. Following sequential boosting immunizations, a V2-apex bnAb lineage with a novel HCDR3-encoded EDGED motif increased its neutralization breadth, including neutralization of viral isolates bearing the N130 glycan, which shields the V2-apex from recognition. High-resolution structures of two members of this V2-apex bnAb lineage, called DH2050, defined a novel binding mode in which it used its EDGED motif to contact the C-strand peptide and the N160 glycan within the V2-apex site. Altogether, we define a novel bnAb binding mode to the V2 Apex and demonstrate that HIV-1 Env sequential vaccination elicits V2-apex bnAbs with immunogenetic signatures that are potentially translatable to the human immune system.

immunology↗

bioRxiv2026

Continuous negative autoregulation fine-tunes dosage-sensitive transcription factor expression to maintain post-mitotic neuron identity

How post-mitotic neurons maintain precise transcription factor (TF) levels throughout life remains a fundamental open question. Here, we challenge the prevailing model of positive autoregulation by demonstrating that UNC-3 (Collier/EBF1-4), a dosage-sensitive TF continuously required for cholinergic motor neuron identity in C. elegans, negatively regulates its own expression. Using genetics, biochemistry, and inducible protein depletion, we show this self-repression occurs directly at the transcriptional level and persists beyond development. CRISPR/Cas9 disruption of negative autoregulation causes motor neuron identity and locomotion defects, establishing its functional necessity. Mechanistically, the UNC-3 DNA-binding domain is required and sufficient for self-repression, with an AlphaFold2 screen implicating chromatin factors as interaction partners. Critically, UNC-3 self-repression is continuously counterbalanced by positive input from the HOX cofactor CEH-20/PBX, revealing a dynamic "balancing act" between opposing regulatory inputs that stabilize TF dosage over time. Mutations in the unc-3 ortholog EBF3 cause a neurodevelopmental syndrome, and disease-associated variants disrupt UNC-3 self-repression, revealing a key molecular mechanism underlying the disorder. We propose that negative autoregulation continuously counteracted by positive input represents a broadly applicable principle for maintaining dosage-sensitive TF expression to secure post-mitotic cell identity.

developmental biology↗

bioRxiv2026

A novel Flavobacterium quisquiliarum porphyrin binding protein independently disrupts Pseudomonas aeruginosa biofilms

Bacterial biofilms underpin chronic infection and antimicrobial resistance, notably in Pseudomonas aeruginosa. Here we deconvolute a commercial alginate lyase preparation from Flavobacterium quisquiliarum and identify a previously uncharacterised [~]21 kDa porphyrin-binding protein (FqPBP). Structural, biophysical and docking analyses reveal high-affinity tetrapyrrole binding. Recombinant FqPBP independently inhibits and disperses P. aeruginosa biofilms, implicating porphyrin sequestration and iron homeostasis in biofilm control and highlighting a potential therapeutic strategy targeting iron acquisition pathways.

microbiology↗

bioRxiv2026

From genes to collective modes: biological constraints shape metabolic evolution

Population genetics has been successful in explaining how drift, selection, and mutation shape allele frequencies. However, we still lack an understanding of how biological and evolutionary constraints arising from genotype-phenotype maps shape evolutionary dynamics. To explore this question, we developed a new framework for simulating the evolution of an inherently polygenic and epistatic trait - metabolism - combining population genetics with flux balance analysis. We found that the evolution of metabolic networks exhibits surprisingly simple, reproducible dynamics. We identify evolutionary collective modes (EvCMs) - linear combinations of genes with high, constant selective pressure - as organizers of the long-term dynamics and the origin of this simplicity. EvCMs arise through the interaction of physical constraints, evolvability, and the requirements for growth. We developed a theoretical framework to predict EvCMs from large-scale metabolic models and found quantitative agreement between theory and simulation of E. coli central metabolism. Inspired by these results, we re-analyzed mutational data from Lenskis long-term evolution experiment and found compelling evidence for the existence of EvCMs. This work suggests that biological constraints encoded in genotype-phenotype maps play an important role in shaping evolutionary dynamics, offering a new perspective on complex trait evolution -- one that shifts focus from individual genes to collective modes.

evolutionary biology↗

bioRxiv2026

Local Confinement within Plasma Membrane Nanodomains Drives Constitutive Activity of GPCRs

Many G protein coupled receptors (GPCRs) exhibit constitutive (basal) activity, where they can signal in the absence of ligand binding through spontaneous conformational transitions that facilitate G protein coupling and downstream signaling. This intrinsic baseline activity is critical for cellular homeostasis and can be modulated by the receptors conformational ensemble, membrane organization, and interactions with intracellular effectors. In this study, we use live-cell signaling assays, fluorescence cross-correlation spectroscopy (FCCS), and single-particle tracking (SPT) to investigate how membrane organization influences the basal activity of two class A GPCRs: the M1 muscarinic receptor (M1R) and the adenosine A2A receptor (A2AR). In live-cell signalling assays, M1R showed minimal agonist-independent Ca{superscript 2} responses, while A2AR exhibited significant basal cAMP production that was eliminated by an inverse agonist. FCCS showed that, without ligand, only a small portion of M1R co-diffuses with its cognate G11 protein, whereas a much larger fraction of A2AR co-diffuses with the GS protein. SPT revealed that A2AR, but not M1R, is enriched in slowly diffusing, confined states with spatial scales around 150-200 nm and sensitivity to cholesterol- and raft-modulating agents, consistent with localization in lipid-raft nanodomains. Dual-color tracking and diffusion mapping demonstrated that a significant portion of A2AR and GS share confinement domains under basal conditions, while M1R and G11 only show such co-confinement in the active state. These findings support a model where the co-confinement of GPCRs and G proteins within plasma membrane nanodomains--rather than stable pre-coupled RG complexes-- determines the level of constitutive GPCR activity.

biophysics↗

bioRxiv2026

It is not just about the science - the impact of undergraduate research projects and COVID-19 on graduate attributes and employability.

Over the past two decades, Higher Education Institutions have increasingly prioritised transferrable skills to enhance graduate employability. Graduate Attributes (GAs) now act as key indicators of student competencies for both learners and employers. Final-year research projects, typically high in credit value, represent capstone experiences that promote subject expertise and GA development through research, written work, and oral presentations. This study analyses pre- and post-project survey data from RQF Level 6 biomedical and biomolecular science students at a Russell Group University over four years (2019-2023). Most projects were laboratory-based, though the 2020-2021 cohort completed theirs remotely due to COVID-19. Students reflected on expectations and experiences of GA development, subject knowledge, and employability. Initial responses revealed anxiety and uncertainty, particularly among the 2020-2021 cohort, but most anticipated gains in skills and employability. Post-project feedback confirmed this, identifying critical thinking, confidence, resilience, collaboration, and future focus as key outcomes. Digital capability was notably strengthened, especially during remote delivery. The findings emphasise the importance of a shared understanding of GAs in bioscience education and the value of embedding structured reflection and preparatory support to help students recognise and articulate their evolving skills.

scientific communication and education↗

bioRxiv2026

A whole organism screening platform identifies gut microbiome microproteins that modulate host metabolism

Advances in metagenomic sequencing over the past two decades have identified vast numbers of previously uncharacterised small open reading frames that may encode microproteins (<50aa). Although computational tools have accelerated gene sequence prediction from metagenomic data, the function of most annotated proteins remains unknown and untested, especially in the context of host-microbiome interactions. Here, we present a scalable phenotypic screening pipeline to identify gut microbiome-derived proteins that modulate host function. Using the nematode worm Caenorhabditis elegans as a whole animal model that is amenable to systematic screening approaches, our pipeline integrates high-throughput cloning, expression and delivery to worms via feeding, followed by behavioural phenomics screening. We apply this approach to a pilot library of 126 uncharacterised microproteins (< 50 aa) from healthy human gut metagenomes, identifying a set of high-interest targets with potential activity and ultimately validating a microprotein that modulates host fatty acid metabolism when expressed. With protein-based therapies increasingly recognised as a promising alternative to traditional small molecules, this work highlights the potential of a target-agnostic approach for the systematic screening and discovery of novel bioactive proteins.

microbiology↗

bioRxiv2026

Habitat and Hydrodynamics Influence Coral Reef and Seagrass Microbial and Exometabolite Dynamics

Coral reef and seagrass ecosystems provide critical storm protection and economic revenue to tropical coastal communities. Effective monitoring and restoration strategies are essential given increasing impacts from climate change and human development. Microorganisms, and the metabolites they produce and consume, are key drivers of coastal ecosystem function. However, microbially-mediated metabolite recycling remains poorly understood, limiting its inclusion in conservation and restoration strategies. Here we examine how seawater exometabolites and microorganisms in coastal ecosystems vary in relation to habitat (seagrass or coral reef), temporal scales and hydrodynamics. We characterized benthic seawater from two St. John, U.S. Virgin Islands coral reefs (Yawzi and Tektite) and one seagrass meadow at dawn and mid-day over four consecutive days. Using quantitative metabolomics and SSU rRNA gene amplicon sequencing, we found that habitat served as the primary driver of exometabolite and microbial community composition, while daily changes and hydrodynamics strongly influenced system variability. Hydrodynamic modeling indicated offshore water intrusion at mid-day at Yawzi reef, likely driving exometabolite and microbial shifts towards oligotrophic taxa (e.g., SAR11, SAR86). In contrast, a high percentage of coastal source water in the seagrass habitat maintained stable exometabolite pools and supported diverse microbial communities. These findings demonstrate that coastal habitat and hydrodynamics strongly influence exometabolite and microbial assemblages, with lesser contributions from temporal changes. Integrating exometabolites, microorganisms, and hydrodynamics provides new insights into coastal ecosystem functioning useful for habitat monitoring and restoration strategies.

ecology↗

bioRxiv2025

Frontoamygdala hyperconnectivity predicts autonomic dysregulation and persisting symptoms in sports-related concussion

OBJECTIVEWe investigated longitudinal trajectories of resting-state fMRI (rsfMRI), autonomic function, and symptoms after sport-related concussion (SRC). BACKGROUNDLimbic circuitry may be particularly vulnerable to traumatic brain injury (TBI), which could explain the affective and autonomic dysfunction some patients develop. Relatively few studies have performed longitudinal rsfMRI analyses in concussion and fewer have combined imaging with autonomic and symptom data. We leveraged published limbic rsfMRI networks centered on the amygdala that include central autonomic structures in frontal and temporal lobes and their visceromotor targets. We hypothesized that frontoamygdala connectivity would differentiate athletes with SRC from matched, in-sport controls (ISC), predict autonomic function, and predict symptom recovery. DESIGN/METHODSUsing independent-samples t-tests, we compared rsfMRI connectivity strength in amygdala networks in college athletes with SRC (SRC: n=31, female=14) at three time points after concussion (T1[≤]4 days, T2=10-14 days, T3=60-90 days) and healthy, matched controls without a concussion in the same sport (ISC: n=36, female=17). RESULTSSRC athletes showed significantly greater frontoamygdala connectivity compared to ISCs at the acute and subacute post-injury time points (T1 p=0.003, T2 p=0.014) that normalized to control-level connectivity by the chronic time point (T3 p=0.182). When testing whether autonomic function interacts with network connectivity trajectory, we found that opposing trajectories of frontoamygdala connectivity between SRC athletes with higher versus lower acute heart rate variability (HRV), as measured by pNN50 (percentage of intervals between successive normal sinus beats greater than 50ms). SRC athletes with higher HRV acutely post-injury had significantly greater acute frontoamygdala connectivity compared to ISCs at T1; connectivity in these high-HRV SRC athletes normalized to control level over time (T1 p=0.001, T2 p=0.055, T3 p=0.576). SRC athletes with lower HRV acutely post-injury had control-level frontoamygdala connectivity at T1; connectivity in these low-HRV SRC athletes significantly exceeded control-level connectivity at T3 (T1 p=0.429, T2 p=0.050, T3 p=0.002). Furthermore, those SRC athletes with the greatest frontoamygdala connectivity at T3, had the most persistent symptoms on the graded symptom checklist at T3 (r=0.635, p=0.001). Differences in diffusion-tensor-imaging-based measures of structural connectivity in the uncinate fasciculus, the fiber bundle most critical to our frontoamygdala network, could not account for these relationships. CONCLUSIONSThese results suggest that increased connectivity in amygdala circuitry acutely after a concussion and its normalization over time may be protective or compensatory; acute measures of amygdala network connectivity and measures of HRV may be valuable biomarkers for predicting symptom persistence.

neuroscience↗

bioRxiv2025

Organelles harbour pH gradients

Organelle pH is critical to organelle identity and function. Resident proteins that define each organelle modify transiting cargo proteins, with both retention and trafficking between organelles governed by pH-dependent mechanisms. For example, lysosomal enzymes bind mannose-6-phosphate receptors at the higher pH ([~]6.5) of the Golgi and dissociate at the lower pH ([~]5.5) of late endosomes1. Proteins that stray from the endoplasmic reticulum (ER) are captured by KDEL receptors in the acidic Golgi and returned into the neutral ER2,3. This pH-tuned trafficking system compartmentalizes organelle function and prevents mis-localization of critical enzymes4. Dysregulated organelle pH disrupts their function and leads to various diseases. Because protons move rapidly in water, the pH within a single organelle is currently assumed to be spatially uniform5. Here, using a reporter sensitive from pH 5.5 - 10.5 to map a spectrum of organelles at high resolution, we discovered that pH gradients exist within single, large or long organelles such as the ER and mitochondria, and in membrane-less organelles without ion-transporting proteins such as the nucleolus. These new findings upend our understanding of organellar pH, prompting new questions about proton diffusion within the cell, and its potential consequences on organelle function.

cell biology↗

bioRxiv2025

Personalized biventricular mechanics and sensitivity to model morphology

AO_SCPLOWBSTRACTC_SCPLOWWe present a computational framework for constructing patient-specific models of cardiac mechanics based on standard clinical data, including electrocardiogram (ECG), cuff blood pressure, and electrocardiography-gated computed tomography angiography (CTA) imaging. The model is coupled to a closed-loop lumped parameter network (LPN) circulatory model and incorporates rule-based fiber architecture, as well as spatially varying epicardial boundary conditions to approximate surrounding tissue support. Model parameters are personalized through a multistep procedure that sequentially tunes circulatory dynamics, passive mechanics, and active contraction. The resulting personalized BiV model closely matches clinical pressure and volume measurements and reasonably agrees with image-based myocardial deformation. To assess the impact of anatomical model choice, we compare the BiV model to two commonly-used simplifications: a truncated BiV (t-BiV) model cut at the basal plane and a left ventricle-only (LV) model. For these models, we also evaluate their sensitivity to plausible variations in boundary conditions and contractile strength. With all other inputs held fixed, the LV model exhibits similar global pressure/volume behavior, despite moderate differences in regional deformation. In contrast, the t-BiV model produces substantial differences in both global function and local myocardial mechanics. These results suggest that while LV-only models may be sufficient for biomechanical studies, truncation at the basal plane strongly impacts model outputs and should be used with caution.

bioengineering↗

bioRxiv2025

Parsing Contributions of Physical Phenomena to smFRET Statistical Inhomogeneity via Multiparameter Stochastic Simulations

Single-molecule Forster Resonance Energy Transfer (smFRET) affords access to nanometre-scale structural and kinetic information for individual biomolecular species. Conventional analyses presuppose a strict separation of the underlying dynamical processes into distinct timescales - an assumption that is frequently violated and seldom verifiable a posteriori. To address this limitation, we present an integrated Brownian dynamics/stochastic simulation framework that treats the three principal dynamic contributors to smFRET observables - (i) diffusion of the molecules centre of mass, (ii) photophysical state-cycling, and (iii) intramolecular diffusion - in a fully time-resolved manner. Each contribution can be selectively activated, deactivated, and parametrically adjusted, thereby providing a controlled computational testbed for determining the extent to which distinct dynamical contributions alter smFRET data. By systematically varying these contributions, the individual and collective impact of specific physical processes on smFRET measurements can be delineated, and therefore the biologically-relevant information (iii) can be more precisely estimated.

biophysics↗

bioRxiv2025

MetaBeeAI: an AI pipeline for full-text systematic reviews in biology

The volume and complexity of scientific literature are expanding rapidly, making it increasingly difficult to extract and synthesise information across studies. This challenge is particularly acute in the biological sciences, where evidence spans multiple levels of organisation and heterogeneous experimental designs. Large Language Model (LLM) pipelines offer a scalable route to evidence synthesis, but many existing approaches lack transparency, modularity, and effective mechanisms for human oversight. We present MetaBeeAI, an open-source, modular pipeline that integrates established LLM techniques into a coherent, auditable workflow for structured data extraction in biology. MetaBeeAI combines modular prompting, multi-pass extraction, and expert-in-the-loop validation within an interface that presents model outputs alongside source text, enabling inspection, correction, and iterative refinement. The pipeline produces machine-readable records of prompts, configurations, and expert annotations, supporting reproducibility and continuous improvement. We apply MetaBeeAI to 924 research papers on bees and pesticides, extracting structured information on species, compounds, exposure designs, and experimental context. Evaluation demonstrates improved consistency, convergence with expert judgement, and robustness across heterogeneous biological studies, highlighting the value of expert-guided refinement. MetaBeeAI provides a transparent and extensible framework for scalable evidence synthesis, supporting reliable integration of LLMs into biological research workflows.

ecology↗