Biology subjects

Bartlett, M.

Publications and source records attributed to Bartlett, M..

13 recordsLinked to original sources

bioRxiv2026

Chronic Electrophysiology Captures Progressive Variability in DNA-Damaged Cardiac Networks

Electrophysiological recordings provide a key functional readout of cardiac health. Most in vitro studies rely on acute measurements rather than recording evolving functional changes. Here, we implement a microelectrode array (MEA) based system for chronic electrophysiological monitoring of human induced pluripotent stem cell-derived cardiomyocyte (iPSC-CM) monolayers. Electrophysiology recordings were maintained for up to 40 days, enabling longitudinal assessment of field potential amplitude, field potential duration, beat frequency, conduction velocity, and waveform morphology. Untreated iPSC-CM monolayers exhibited stable electrophysiological behavior throughout chronic culture. Following exposure to the cardiotoxic chemotherapeutic doxorubicin, chronic recordings captured progressive deterioration in electrical activity, including reduced field potential amplitude, altered repolarization dynamics, increased beat-to-beat variability, and reduced conduction that persisted after drug removal. Electrode-resolved analyses further revealed pronounced progressive spatial variability, highlighting localized responses that would be obscured by population-averaged measurements. Endpoint assays indicated reduced calcium transient amplitude and altered calcium reuptake, decreased mitochondrial membrane potential, and loss of connexin 43, findings consistent with the impaired electrical activity observed in chronic recordings. Together, these results establish chronic electrophysiological monitoring as a powerful approach for resolving the spatiotemporal progression of cardiotoxicity and other dynamic cardiac processes in vitro.

bioengineering↗

bioRxiv2026

BSA101: Unlocking Historical Mutant Collections with BSA-Seq

Forward genetics is a powerful approach for gene discovery, but identifying causal mutations becomes difficult when mutants are maintained in heterogeneous populations with uncertain pedigrees. This is exemplified by classical tasselseed (ts) mutants, which have long served as a genetic model for studying sex determination and carpel suppression. Decades of repeated outcrossing to diverse inbred lines have created substantial genetic heterogeneity, limiting the effectiveness of conventional bulked-segregant analysis sequencing (BSA-Seq). To address this, we developed a BSA-Seq framework that integrates flexible experimental designs, multiple reference genomes, and complementary statistical methods tailored for genetically heterogeneous populations. Applying this framework revealed that reference genome selection is critical for mapping success and that Euclidean distance raised to the fourth power (ED4) outperformed homozygosity mapping (HM). Furthermore, the framework enables simultaneous mapping of multiple mutations within a single population, eliminating the need for additional mapping populations. Applying this framework to 26 ts mutant stocks from the Maize Genetics Cooperation Stock Center, we successfully mapped 24 mutants to genomic intervals containing known ts genes, while the remaining mutants mapped to distinct genomic intervals, defining novel candidate regions underlying carpel suppression. Together, these results demonstrate that historical mutant collections represent an underutilized resource for gene discovery and establish a generalizable mapping strategy for unlocking their genetic potential across diverse species.

plant biology↗

bioRxiv2026

Modeling Parkinsonian Freezing and Deep Brain Stimulation Effects in a Basal Ganglia Network

The precise mechanism through which Deep Brain Stimulation (DBS) mitigates freezing episodes in Parkinsons disease remains unknown. We modelled Parkinsonian freezing using a model of the basal ganglia that adopts a Dynamic Neural Field network for simultaneous action selection (selecting which action is executed) and specification (resolving the continuous parameters governing how that action is performed). Action selection success was based on whether activation surpassed a threshold. The model robustly differentiated healthy and dopamine-depleted (Parkinsonian) conditions, producing stable action selection under healthy dopamine and impaired, freeze-prone dynamics following depletion. We then modelled DBS as a scaled reduction in afferent drive to the subthalamic nucleus and globus pallidus internus. While this formulation has succeeded in previous computational work, it did not yield consistent restoration of action selection within our framework, motivating future investigation of alternative DBS formulations.

neuroscience↗

bioRxiv2026

Neural Representational Geometry of Feature Binding Operations

The brain faces the feature binding problem: how are multiple stimulus features and variables combined into coherent representations that support flexible behavior? A key finding from neuroscience is that some brain regions employ factorized representations, where distinct features are encoded in neural state space in such a way that enables independent readout and robust generalization. Various algebraic operations have been proposed to model multi-variable representations, but despite extensive study of their theoretical properties (e.g., capacity, noise robustness), it remains unclear which operations produce the representational geometries observed in neural recordings. We systematically evaluate six binding operations implemented in recurrent spiking neural networks performing a working memory task. We find that only superposition and binding with slot-filler structure produce factorized geometry with favorable scaling, while the alternatives do not. These results provide a taxonomy linking algebraic binding operations to neural representational signatures, offering guidance for both computational modelers and experimentalists.

neuroscience↗

bioRxiv2026

Novel model combining intrinsic and learned behaviours captures divergent effects of dopaminergic drugs on different types of motivation

Motivation-based symptoms occur in an array of neurological and neurodegenerative disorders, including Schizophrenia and Parkinsons Disease. Unfortunately, there is, as yet, no agreed treatment approach. To establish a better understanding of motivation, and so highlight potential avenues for treatment, motivation is often investigated using operant behavioural paradigms such as the Effort for Reward (EfR) task. Performance on these tasks is thought to be influenced by reinforcement learning (RL) mechanisms, such that disorders of motivation can be described in terms of altered interactions with RL processes. Recently, foraging behaviour has been increasingly adopted as an ethologically valid approach to investigating cognitive mechanisms, including motivation. One example of this is the recently developed Effort Based Foraging task (EBF). Foraging behaviour, unlike the strictly controlled and contrived operant behavioural paradigms, involves a series of complex behavioural processes, each potentially driven by different cognitive processes. It is therefore important to identify which portion of the foraging behavioural sequence is driven by the same RL mechanisms as classical operant behavioural paradigms, and therefore can be used to investigate motivation. In this work we set out to establish whether the same RL mechanisms could be used to account for behaviours observed in both EfR and EBF tasks. We identified where, within the EBF task, RL mechanisms were no long sufficient and developed a novel hybrid model of the behaviour. This model successfully accounted for external influences on motivation, including previously unpredicted effects of clinically used dopaminergic drugs. This work reveals that motivation in complex, naturalistic tasks cannot be fully explained by learning-based models alone. Incorporating intrinsic behavioural drives may be needed as neuroscience moves toward more ethological behavioural assays.

neuroscience↗

bioRxiv2025

A Computational Model of Action Specification in the Basal Ganglia

The basal ganglia has traditionally been modelled as a system that represents the available, discrete action space using a finite set of distinct and non-overlapping representational units. This limits these models from addressing questions around how the basal ganglia is involved in action specification: the selection of continuously valued action dynamics such as speed and vigor. In this article we present a novel computational model of the basal ganglia which incorporates vector-symbolic algebras in order to represent continuous action spaces. The stages of model development are presented along with simulation experiments to test the basic properties of the model. This work represents a promising foundational step in providing a mechanistic account for neuroscientific and behavioural evidence implicating the basal ganglia in action specification, thereby filling a gap in the literature.

neuroscience↗

bioRxiv2025

Antagonistic interactions between CLAVATA receptors shape maize ear development

Meristem activity is controlled by the CLAVATA (CLV) signaling pathway, which involves a suite of leucine rich receptor (LRR) receptors, receptor-like proteins and CLV- EMBRYO SURROUNDING REGION (CLE) peptide ligands. FASCIATED EAR 3 (FEA3) is a leucine rich receptor (LRR) receptor-like protein important for meristem maintenance in maize, and acts independently of canonical CLV receptors. Weak alleles of fea3 can increase yield-related traits in maize, so understanding how FEA3 controls inflorescence development can maximize its potential as a crop improvement target. To identify FEA3s interaction network, we used TurboID-based proximity labeling in maize meristems, and identified a putative co-receptor, BARELY ANY MERISTEM 1D (BAM1D). BAM1D and FEA3 proximity labeling proteomes shared over 100 proteins, including many signaling proteins, suggesting they feed into a common signaling pathway. fea3 was epistatic to bam1d in the control of IM size, supporting the idea that FEA3 and BAM1D interact physically. However, fea3 and bam1d act antagonistically, because fea3 mutants had larger inflorescence meristems (IMs), whereas bam1d mutants produced smaller IMs. Together, this study demonstrates how in vivo TurboID-based proximity labeling clarifies complex genetic interactions between CLV receptors and expands our knowledge of downstream signaling components of CLV signaling pathways, which are largely uncharacterized. Our findings support the notion that multiple, partially overlapping CLV receptor complexes coordinately control meristem maintenance.

plant biology↗

bioRxiv2024

Wound state monitoring by multiplexed, electrochemical, real-time, localized, inflammation-tracking nitric oxide sensor (MERLIN)

Nitric oxide (NO) released endogenously by induced nitric oxide synthase (iNOS) in macrophages is a key regulatory biomarker for wound inflammation. Detecting NO directly on the wound bed is challenging due to its short half-life time (6 - 50 s), low physiological concentration (nM - {micro}M) and interferences in the complex wound environment. Existing NO sensors suffer from limitations such as rigid substrates, single point of detection and complex measurement setup. Here we present a compliant, multiplexed, electrochemical, real-time, localized, inflammation-tracking nitric oxide sensor (MERLIN) array for in vivo spatiotemporal measurement of NO, with high sensitivity (15.6 {+/-} 5.0 nA/M for 1.5 mm diameter electrodes), selectivity against nitrites (ca. 27900-fold), ascorbic acid (ca. 3800-fold), and uric acid (ca. 6900-fold), and low limit of detection (8.00 nM). We developed a robust device fabrication protocol, comprehensive and highly reproducible in vitro characterization yielding a consistent device performance deployed for wound healing diagnostics. MERLIN spatiotemporally tracked NO on rat skin wounds for 7 days and results indicated that NO peaks on day 3, in line with previously reported iNOS activity. MERLIN allows spatial mapping of the NO gradient across the wound bed, which can be used to provide diagnostic information to assist wound care.

bioengineering↗

bioRxiv2021

Boundary domain genes were recruited to suppress bract growth and promote branching in maize

Grass inflorescence development is diverse and complex and involves sophisticated but poorly understood interactions of genes regulating branch determinacy and leaf growth. Here, we use a combination of transcript profiling, genetic and phylogenetic analyses to investigate tasselsheath1 (tsh1) and tsh4, two maize genes that simultaneously suppress inflorescence leaf growth and inhibit branching. We identify a regulatory network of inflorescence leaf suppression that involves the phase change gene tsh4 upstream of tsh1 and the ligule identity gene liguleless2 (lg2). We also find that a series of duplications in the tsh1 gene lineage facilitated its shift from boundary domain in non-grasses to suppressed inflorescence leaves of grasses. Collectively, these results suggest that the boundary domain genes tsh1 and lg2 were recruited to inflorescence leaves where they suppress growth and regulate a non-autonomous signaling center that promotes inflorescence branching, an important component of yield in cereal grasses.

plant biology↗

bioRxiv2021

Maize RAMOSA3 accumulates in nuclear condensates enriched in RNA POLYMERASE II isoforms during the establishment of axillary meristem determinacy.

Brief AbstractMaize meristem determinacy is regulated by Trehalose-6-Phosphate Phosphatase (TPP) metabolic enzymes RAMOSA3 and TPP4. However, this function is independent of their enzymatic activity, suggesting they have an unpredicted, or moonlighting function. Using whole-mount double immunolabeling and imaging processing, we investigated the co-localization of RA3 nuclear speckles with markers for transcription, chromatin state and splicing. We find evidence for RA3 co-localization with RNA POL II, a transcription marker, and not with markers for promoter chromatin remodeling or mRNA processing, suggesting a function of nuclear RA3 in mediating a transcriptional response during meristem determinacy.

plant biology↗

bioRxiv2020

Evolutionary variation in MADS-box dimerization affects floral development and protein degradation dynamics

Shifting interactions between MADS-box transcription factors may have been critical in the emergence of the flower, and in floral diversification. However, how evolutionary variation in MADS-box interactions affects the development and evolution of floral form remains unknown. Interactions between B-class MADS-box proteins are variable across the grass family. Here, we test the functional consequences of this evolutionary variability using maize as an experimental system. We found that differential B-class dimerization was associated with subtle, quantitative differences in stamen shape. In contrast, differential dimerization resulted in large-scale changes to protein complex composition and downstream gene expression. Differential dimerization also affected B-class complex abundance, independent of RNA levels. Thus, differential dimerization may affect protein stability. This reveals an important consequence for evolutionary variability in MADS-box interactions, adding complexity to the evolution of developmental gene networks. Our results show that floral development is robust to molecular change, even coding change in a master regulator of development. This robustness may contribute to the evolvability of floral form.

plant biology↗

bioRxiv2018

Of puzzles and pavements: a quantitative exploration of leaf epidermal cell shape

SummaryThe epidermal cells of leaves lend themselves readily to observation and display many shapes and types: tabular pavement cells, complex trichomes, and stomatal complexes1. Pavement cells from Zea mays (maize) and Arabidopsis thaliana (arabidopsis) both have highly undulate anticlinal walls and are held as representative of monocots and eudicots, respectively. In these two model species, we have a nuanced understanding of the molecular mechanisms that generate undulating pavement cell shape2-9. This model-system dominance has led to two common assumptions: first, that particular plant lineages are characterized by particular pavement cell shapes; and second, that undulatory pavement cell shapes are common enough to be model shapes. To test these assumptions, we quantified pavement cell shape in the leaves of 278 vascular plant taxa and assessed cell shape metrics across large taxonomic groups. We settled on two metrics that described cell shape diversity well in this dataset: aspect ratio (degree of cell elongation) and solidity (a proxy for margin undulation). We found that pavement cells in the monocots tended to have weakly undulating margins, pavement cells in ferns had strongly undulating margins, and pavement cells in the eudicots showed no particular degree of undulation. Indeed, we found that cells with strongly undulating margins, like those of arabidopsis and maize, were in the minority in seed plants. At the organ level, we found a trend towards cells with more undulating margins on the abaxial leaf surface vs. the adaxial surface. We also detected a correlation between cell and leaf aspect ratio: highly elongated leaves tended to have highly elongated cells (low aspect ratio), but not in the eudicots. This indicates that while plant anatomy and plant morphology can be connected, superficially similar leaves can develop through very different underlying growth dynamics (cell expansion and division patterns). This work reveals the striking diversity of pavement cell shapes across vascular plants, and lays the quantitative groundwork for testing hypotheses about pavement cell form and function.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=139 SRC=\"FIGDIR/small/361717_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (83K):\norg.highwire.dtl.DTLVardef@1a571a8org.highwire.dtl.DTLVardef@c8cf7dorg.highwire.dtl.DTLVardef@1ae3090org.highwire.dtl.DTLVardef@f666ce_HPS_FORMAT_FIGEXP M_FIG C_FIG

plant biology↗

bioRxiv2018

Bulked-Segregant Analysis Coupled to Whole Genome Sequencing (BSA-Seq) for Rapid Gene Cloning in Maize

Forward genetics remains a powerful method for revealing the genes underpinning organismal form and function, and for revealing how these genes are tied together in gene networks. In maize, forward genetics has been tremendously successful, but the size and complexity of the maize genome made identifying mutant genes an often arduous process with traditional methods. The next generation sequencing revolution has allowed for the gene cloning process to be significantly accelerated in many organisms, even when genomes are large and complex. Here, we describe a bulked-segregant analysis sequencing (BSA-Seq) protocol for cloning mutant genes in maize. Our simple strategy can be used to quickly identify a mapping interval and candidate single nucleotide polymorphisms (SNPs) from whole genome sequencing of pooled F2 individuals. We employed this strategy to identify narrow odd dwarf as an enhancer of teosinte branched1, and to identify a new allele of defective kernel1. Our method provides a quick, simple way to clone genes in maize.\n\nReferences numbers for supporting data:figshare and NCBI SRA links to follow

plant biology↗