Biology subjects

Cole, E.

Publications and source records attributed to Cole, E..

7 recordsLinked to original sources

bioRxiv2025

Cellular and Spatial Drivers of Unresolved Injury and Functional Decline in the Human Kidney

Building upon a foundational Human Kidney resource, we present a comprehensive multi-modal atlas that defines spatially resolved versus unresolved repair states and mechanisms in human kidney disease. Homeostatic interactions between injured kidney epithelium and its surrounding milieu determine successful repair outcomes, while pathogenic signaling promotes unresolved inflammation and fibrosis leading to chronic disease. We integrated multiple single-cell and spatial modalities across [~]700 samples from >350 patients ([~]250 research biopsies), analyzing [~]1.7 million cells alongside complementary mouse multi-omic profiles spanning acute-to-chronic injury and aging (>300,000 cells) and spatial transcriptomic analysis of >150 human biopsies. This cross-species atlas delineates functional pathways and druggable targets across the nephron and defines gene regulatory networks and chromatin landscapes governing tubular, fibroblast, and immune cell transitions from injury to either recovery or failed repair states. We identified distinct cellular states associated with specific pathological features that show dynamic distributions between acute kidney injury (AKI) and chronic kidney disease (CKD), organized within unique spatial niches that reveal progression mechanisms from early injury to unresolved disease. Gene regulatory analyses prioritized key transcription factor activities (SOX4, SOX9, NFKB1, REL, KLFs) and their target networks establishing disease states and tissue microenvironments. These regulatory programs were directly linked to clinical outcomes, identifying molecular signatures of recovery and secreted biomarkers predictive of AKI-to-CKD progression, providing a key resource for therapeutic development and precision medicine approaches in kidney disease.

molecular biology↗

bioRxiv2025

Rapid and Reproducible Multimodal Biological Foundation Model Development with AIDO.ModelGenerator

Foundation models (FMs) for DNA, RNA, proteins, cells, and tissues have begun to close long-standing performance gaps in biological prediction tasks, yet each modality is usually studied in isolation. Bridging them requires software that can ingest heterogeneous data, apply large pre-trained backbones from various sources, and perform multimodal benchmarking studies at scale. We present AIDO.ModelGenerator, an open-source toolkit that turns these needs into declarative experiment recipes through a structured experimental framework. AIDO.ModelGenerator provides (i) 300+ datasets covering DNA, RNA, protein, cell, spatial, and multimodal data types; (ii) 30+ pretrained FMs ranging from 3M to 16B parameters; (iii) 10+ plug-and-play use-cases covering inference, adaptation, prediction, generation, and zero-shot evaluation; and (iv) YAML-driven experiment recipes that enable exact reproducibility. On a sequence-to-expression prediction task, AIDO.ModelGenerator systematically builds and tests unimodal and multimodal models, achieving a new SOTA by combining DNA and RNA FMs that outperforms unimodal baselines by over 10%. In a Crohns disease case-study, the frameworks simulated knockout protocol ranks the clinically implicated target SOX4 6,000 positions higher than differential-expression baselines, illustrating its utility for therapeutic target discovery. We release code, tutorials, checkpoints, datasets, and API reference to accelerate multimodal FM research in the life sciences1.

bioinformatics↗

bioRxiv2025

Multimodal Benchmarking of Foundation Model Representations for Cellular Perturbation Response Prediction

The decreasing cost of single-cell RNA sequencing (scRNA-seq) has enabled the collection of massive scRNA-seq datasets, which are now being used to train transformer-based cell foundation models (FMs). One of the most promising applications of these FMs is perturbation response modeling. This task aims to forecast how cells will respond to drugs or genetic interventions. Accurate perturbation response models could drastically accelerate drug discovery by reducing the space of interventions that need to be tested in the wet lab. However, recent studies have shown that FM-based models often struggle to outperform simpler baselines for perturbation response prediction. A key obstacle is the lack of understanding of the components driving performance in FM-based perturbation response models. In this work, we conduct the first systematic pan-modal study of perturbation embeddings, with an emphasis on those derived from biological FMs. We benchmark their predictive accuracy, analyze patterns in their predictions, and identify the most successful representation learning strategies. Our findings offer insights into what FMs are learning and provide practical guidance for improving perturbation response modeling.

bioinformatics↗

bioRxiv2025

Impact of Segmentation Errors in Analysis of Spatial Transcriptomics Data.

Spatial transcriptomics aims to elucidate cell coordination within biological tissues by linking the state of the cell with its local tissue microenvironment. Imaging-based assays are particularly promising for exploring such interdependencies, as they can resolve molecular and cellular features with subcellular resolution in three dimensions. Quantification and analysis of cellular state in such data, however, ultimately depends on the ability to recognize which molecules belong to each cell. Despite computational and experimental progress, this cell segmentation task remains challenging. Here we re-analyze data from multiple tissues and platforms and find that segmentation errors currently confound most downstream analysis of cellular state, including analysis of differential expression, inference of neighboring cell influence, and ligand-receptor interactions. The extent to which mis-segmented molecules impact the results can be striking, often dominating the set of top hits. We show that factorization of molecular neighborhoods can be effective at isolating such molecular admixtures and minimizing their impact on downstream analysis, analogous to doublet filtering of scRNA-seq data. As applications of spatial transcriptomics assays become more widespread, we expect corrections for the confounding effect of segmentation errors to become increasingly important for being able to resolve molecular mechanisms of tissue biology.

bioinformatics↗

bioRxiv2024

Ungulate personality and the human shield contribute to long-distance migration loss

Long-distance ungulate migrations are declining and past research has focused on preserving migration paths where habitat fragmentation and loss disrupts movement corridors. However, changing residency-migration tradeoffs are the stronger driver of long-distance migration loss in some populations. The human shield effect relative to predation risk and anthropogenic food resources likely shapes these tradeoffs, but individual animals also vary in their propensity to tolerate proximity to humans and developed areas. We investigated how personality relative to human-habituation affects migration behavior. We categorized elk as bold or shy based on use of anthropogenic food resources identified through a clustering algorithm applied to GPS collar data. Bold elk were 4 times more likely to select wintering areas close to human activity and migrated 60% shorter distances compared to shy elk. As a result, elk wintering grounds were spatially structured such that conflict- and disease-prone individuals selected areas adjacent to human activity. Our results suggest that bold personality traits act as a precursor to human-habituation, which permits bold elk to reap the forage and predation rewards that occur in suburban landscapes. A multi-pronged approach beyond just maintaining habitat corridors may be necessary to conserve long-distance migrations for species that can become human-habituated.

ecology↗

bioRxiv2024

Different types of social links contrastingly shape reproductive wellbeing in a multi-level society of wild songbirds

The social environment has diverse consequences for individuals welfare, health, reproductive success, and survival. This environment consists of different kinds of dyadic bonds that exist at different levels; in many social species, smaller social units come together in larger groups, creating multilevel societies. In great tits (Parus major), individuals have four major types of dyadic bonds: pair mates, breeding neighbours, flockmates, and spatial associates, all of which have been previously linked to fitness outcomes. Here, we show that these different types of dyadic bonds are differentially linked with subsequent reproductive success metrics in this wild population and that considering spatial effects provides further insights into these relationships. We provide evidence that more social individuals had a higher number of fledglings, and individuals with more spatial associates had smaller clutch sizes. We also show individuals with stronger bonds with their pair mate had earlier lay dates. Our study highlights the importance of considering different types of dyadic relationships when investigating the relationship between wellbeing and sociality, and the need for future work aimed at experimentally testing these relationships, particularly in spatially structured populations.

ecology↗

bioRxiv2024

Improved Temporal and Spatial Focality of Non-invasive Deep-brain Stimulation using Multipolar Single-pulse Temporal Interference with Applications in Epilepsy

Temporal Interference (TI) is an emerging method to non-invasively stimulate deep brain structures. This innovative technique is increasingly recognized for its potential applications in the treatment of various neurological disorders, including epilepsy, depression, and Alzheimers disease. However, several drawbacks to the TI method exist that we aim to improve upon. To begin, the applied electric field in the TI target is not much higher than what non-invasive transcranial alternating current stimulation (TACS) provides in the cortex. Additionally, the TI stimulation onset is dependent on the envelope of the amplitude modulated (AM) signal, where for example 1 Hz and 100 Hz envelopes have significantly different rise times to reach maximum envelope amplitude - unlike square biphasic pulses. This limitation in turn prevents classic TI, from applying bursts of pulses. Finally, the electric field intensity of TI cannot be increased or decreased at the target without dramatically altering the spatial profile of the stimulation focus. In the work presented here, we efficiently address all three of these limitations. First, we performed two-photon calcium imaging to show that individual neurons selectively respond to the TI envelope frequency, providing evidence that TI modulates neural activity with temporal specificity. This marks a significant advancement, representing the first empirical demonstration of neuronal activation at the {Delta}f frequency within the context of TI and in an imaging modality. Subsequently, we compared the AM signals of TI with phase-shift keying (PSK) modulated signals to highlight the superior effectiveness of noninvasive pulses in contrast to the traditional TI method, particularly in inducing epileptic activity (after-discharges) in mice. We also added a multipolar configuration to create a significant increase in the electric field at the target without significantly altering the spatial profile and applied Fourier components to replicate classic biphasic bursts of square pulses - all transcranially, without the use of penetrating electrodes. These innovations aim to enhance the precision and efficacy of TI stimulation, to advance its application in neurological research and therapy. Key Points / HighlightsO_LINon-invasive temporal interference stimulation modulates the activity of individual neurons at the envelope frequency. C_LIO_LIA non-invasive multi-pulse TI stimulation paradigm improves both temporal and spatial focality in the deep target neural tissue when compared to traditional continuous wave (amplitude-modulated) TI stimulation. C_LIO_LIPulse TI paradigms can stimulate deep neural targets with reduced amplitude of the topical high-frequency stimulation, decreasing off-target stimulation when compared to continuous wave TI patterns. As a consequence, pulse TI stimulation reduces the risk of undesired side effects such as high-frequency conduction block in off-target tissues or cortical areas. C_LIO_LIBoth temporal and spatial focality of the TI stimulation pattern positively correlate with the efficacy of the stimulation to induce seizures in the mouse hippocampus. C_LI

neuroscience↗