Biology subjects

Eliceiri, K. W.

Publications and source records attributed to Eliceiri, K. W..

At least 19 recordsLinked to original sources

bioRxiv2026

A self-organized signaling hierarchy patterns the cortex during cell repair

Cells generate dynamic patterns of Rho GTPase activation to direct the subsequent patterning of Rho GTPase effectors needed to remodel the cell cortex during processes ranging from cell division to cell repair. To understand how such patterns arise, we used live cell imaging, time-resolved Rho GTPase manipulations, and a novel computational tool to study the spatiotemporal dynamics of Rho, Cdc42 and several downstream Cdc42 targets in wounded Xenopus laevis oocytes. We find that the characteristic wound-induced segregation of Rho and Cdc42 activity into concentric zones is followed by polarization of the Cdc42 zone such that Toca-1 progressively concentrates at the back of the Cdc42 zone while Arp2/3, cofilin, cortactin, and the Rho GAP p190RhoGAP progressively concentrate at the front of the Cdc42 zone, where it overlaps the Rho zone. Remarkably, the juxtaposition of Rho activity to Cdc42 is required for the polarization of p190RhoGAP, while p190RhoGAP is responsible for establishing the boundary between the Cdc42 and Rho zones. The results indicate that the characteristic segregation of the Rho and Cdc42 zones, as well as the polarization of the Cdc42 zone, arise from cortical self-organization. Further, these findings reveal a simple mechanism for hierarchical establishment of cortical patterns: recruitment of new proteins to regions of signaling compartment overlap.

cell biology↗

bioRxiv2026

Critical period plasticity enables credit assignment

Synaptic plasticity is often guided by instructive inputs to neural circuits, but learning only succeeds when these instructions reach neurons that mediate relevant outputs. This creates the credit assignment problem: how does a neuron receive instructions suited to its own behavioral function? Here we report a developmental mechanism that enables credit assignment by using instructive inputs to organize the downstream architecture through which learning is expressed. In the olivocerebellar learning system, the inferior olive provides instructive inputs that guide plasticity within the cerebellum. During circuit assembly in zebrafish, we find these same inputs regulate long-range cerebellar projections during a highly plastic, two-day critical period. Developmental experience caused specific maturation of projections to targets that were coactivated with olivary inputs. Mathematical theory and computational modeling show how the resulting architecture constrains later learning, such that a single input can sculpt downstream connectivity and then leverage that circuit to assign credit. Simulated learning became paradoxically more robust if we reduced plasticity after a developmental critical period, protecting key architecture from corruption during learning. Thus, instructive inputs can first build the circuits they later teach, coordinating development and learning to enable effective credit assignment.

neuroscience↗

bioRxiv2026

Engineering physically optimized T cells for increased sampling of complex tumor microenvironments

Pancreatic ductal adenocarcinoma (PDA) remains highly lethal, in part, because its dense fibroinflammatory stroma restricts therapy distribution, including adoptive T cell immunotherapies where direct interactions between T and carcinoma cells are essential for effective therapy. While T cell function must be maintained once effector-target engagement occurs, without inducing co-localization subsequent cytotoxic function steps cannot be undertaken. We therefore developed a strategy to "physically optimize" T cells to more effectively sample complex tumor volumes. Informed by pharmacologic perturbations and mathematical modeling we shifted T cell phenotype through expression of constitutively activated RhoA to increase cortical contractility, activation, migration, and sampling in PDA, while showing decreases in exhaustion markers. In CAR T cells this results in more efficient targeting through decreased sampling time and increased engagement with carcinoma cells, consistent with modeling predictions. This significantly increases T cell infiltration and distribution in PDA, resulting in improved tumor control in vivo, suggesting that this is an effective strategy to overcome stromal constraints, improve tumor engagement, and enhance the therapeutic performance of engineered T cell therapies in solid tumors.

bioengineering↗

bioRxiv2025

Non-invasive longitudinal imaging reveals aging-associated changes in neuroimmune cells in adult zebrafish

Zebrafish are a powerful model for imaging studies of development and neurobiology. However, most studies have focused on developing zebrafish due to technical and biological challenges of imaging adult stages. These include increased tissue opacity and illumination depth limitations, and difficulty maintaining life support and anesthesia in a 2-4cm long fish. There are currently limited tools for intravital imaging of the adult zebrafish brain. The ability to image the brain in the same individual repeatedly without physical damage would allow zebrafish to be better utilized to study aging and neurodegenerative disease. We designed and applied a 3D-printable device for non-invasive, repeatable multiphoton neural imaging of genetically non-pigmented adult zebrafish from 2 months to 19 months old. Animals successfully recovered after multi-hour imaging sessions and can be imaged repeatedly over periods of weeks to years. We show the utility of this approach through imaging the neuroimmune system, revealing that microglia in aged zebrafish have enhanced cellular dynamics. This technique could be widely used and beneficial for other cell-scale neuroimaging studies in the adult fish. Summary StatementAn open-source, 3D printable device that enables non-invasive neuroimaging in adult zebrafish reveals aging-associated changes in neuroimmune cell behavior.

neuroscience↗

bioRxiv2025

Regional and Temporal Changes in Early Structural Remodeling Following Myocardial Infarction via Semi-Automatic Image Analysis

Reperfusion therapy, the restoration of blood flow following a myocardial infarction (MI), is one of the most effective treatment strategies. Unlike early reperfusion therapy, differences in infarct size or collagen content have not been reported in late reperfusion therapy. To evaluate the spatial-temporal effects of late reperfusion therapy, we conducted multimodal imaging of histologic sections of rat myocardium following permanent coronary artery occlusion or three hours of occlusion. Semi-automatic partitioning identified the infarct core, infarct border, and healthy periphery regions from label-free liquid crystal based polarized light microscopy (PolScope) images taken throughout the first 5 days of healing. Associated brightfield and standard polarized light microscopy images of hematoxylin-eosin or Picrosirius Red stained sections were also used to determine cellular and collagen fiber densities, respectively. Even when we consider multiple definitions for the vulnerable infarct border, its size decreased faster in late reperfusion therapy samples. Temporal patterns in collagen density also indicated late reperfusion led to a more rapid progression through the necrotic phase of healing (when the infarct is vulnerable to rupture) and earlier progression to the fibrotic phase of healing (when the infarct stabilizes). Notably, we also observed a broader region of provisional non-collagenous matrix in late reperfusion samples during the necrotic phase of healing. Together these findings suggest late reperfusion therapy accelerates healing and potentially changes the spatial pattern of provisional matrix deposition during the period the heart is most susceptible to rupture events.

pathology↗

bioRxiv2024

Real time imaging reveals a role for macrophage protrusive motility in melanoma invasion

Macrophages are primary cells of the innate immune system that mediate tumor progression. However, the motile behavior of macrophages and interactions with tumor cells are not well understood. Here, we exploit the optical transparency of larval zebrafish and perform real time imaging of macrophage-melanoma interactions. We found that macrophages are highly motile in the tumor microenvironment. Macrophages extend dynamic projections between tumor cells that precedes invasive melanoma migration. Modulating macrophage motility with a dominant inhibitory mutation in Rac2 inhibits recruitment to the tumor and impairs tumor invasion. However, a hyperactivating mutation in Rac2 does not affect macrophage recruitment but limits macrophage projections into the melanoma mass and reduces invasive melanoma cell migration. Taken together, these findings reveal a role for Rac2-mediated macrophage protrusive motility in melanoma invasion.

cell biology↗

bioRxiv2024

A mouse model of TB-associated lung fibrosis reveals persistent inflammatory macrophage populations during treatment

Post-TB lung disease (PTLD) causes a significant burden of global disease. Fibrosis is a central component of many clinical features of PTLD. To date, we have a limited understanding of the mechanisms of TB-associated fibrosis and how these mechanisms are similar to or dissimilar from other fibrotic lung pathologies. We have adapted a mouse model of TB infection to facilitate the mechanistic study of TB-associated lung fibrosis. We find that the morphologies of fibrosis that develop in the mouse model are similar to the morphologies of fibrosis observed in human tissue samples. Using Second Harmonic Generation (SHG) microscopy, we are able to quantify a major component of fibrosis, fibrillar collagen, over time and with treatment. Inflammatory macrophage subpopulations persist during treatment; matrix remodeling enzymes and inflammatory gene signatures remain elevated. Our mouse model suggests that there is a therapeutic window during which adjunctive therapies could change matrix remodeling or inflammatory drivers of tissue pathology to improve functional outcomes after treatment for TB infection.

microbiology↗

bioRxiv2024

Piximi - An Images to Discovery web tool for bioimages and beyond

Deep learning has greatly accelerated research in biological image analysis yet it often requires programming skills and specialized tool installation. Here we present Piximi, a modern, no-programming image analysis tool leveraging deep learning. Implemented as a web application at Piximi.app, Piximi requires no installation and can be accessed by any modern web browser. Its client-only architecture preserves the security of researcher data by running all computation locally. Piximi offers four core modules: a deep learning classifier, an image annotator, measurement modules, and pre-trained deep learning segmentation modules. Piximi is interoperable with existing tools and workflows by supporting import and export of common data and model formats. The intuitive researcher interface and easy access to Piximi allows biological researchers to obtain insights into images within just a few minutes. Piximi aims to bring deep learning-powered image analysis to a broader community by eliminating barriers to entry.

cell biology↗

bioRxiv2024

Machine learning assisted mid-infrared spectrochemical fibrillar collagen imaging in clinical tissues

SignificanceLabel-free multimodal imaging methods that can provide complementary structural and chemical information from the same sample are critical for comprehensive tissue analyses. These methods are specifically needed to study the complex tumor-microenvironment where fibrillar collagens architectural changes are associated with cancer progression. To address this need, we present a multimodal computational imaging method where mid-infrared spectral imaging (MIRSI) is employed with second harmonic generation (SHG) microscopy to identify fibrillar collagen in biological tissues. AimTo demonstrate a multimodal approach where a morphology-specific contrast mechanism guides a mid-infrared spectral imaging method to detect fibrillar collagen based on its chemical signatures. ApproachWe trained a supervised machine learning (ML) model using SHG images as ground truth collagen labels to classify fibrillar collagen in biological tissues based on their mid-infrared hyperspectral images. Five human pancreatic tissue samples (sizes are in the order of millimeters) were imaged by both MIRSI and SHG microscopes. In total, 2.8 million MIRSI spectra were used to train a random forest (RF) model. The remaining 68 million spectra were used to validate the collagen images generated by the RF-MIRSI model in terms of collagen segmentation, orientation, and alignment. ResultsCompared to the SHG ground truth, the generated MIRSI collagen images achieved a high average boundary F-score (0.8 at 4 pixels threshold) in the collagen distribution, high correlation (Pearsons R 0.82) in the collagen orientation, and similarly high correlation (Pearsons R 0.66) in the collagen alignment. ConclusionsWe showed the potential of ML-aided label-free mid-infrared hyperspectral imaging for collagen fiber and tumor microenvironment analysis in tumor pathology samples.

bioengineering↗

bioRxiv2023

Bridging Imaging Users to Imaging Analysis - A community survey

The "Bridging Imaging Users to Imaging Analysis" survey was conducted in 2022 by the Center for Open Bioimage Analysis (COBA), Bioimaging North America (BINA), and the Royal Microscopical Society Data Analysis in Imaging Section (RMS DAIM) to understand the needs of the imaging community. Through multi-choice and open-ended questions, the survey inquired about demographics, image analysis experiences, future needs, and suggestions on the role of tool developers and users. Participants of the survey were from diverse roles and domains of the life and physical sciences. To our knowledge, this is the first attempt to survey cross-community to bridge knowledge gaps between physical and life sciences imaging. Survey results indicate that respondents overarching needs are documentation, detailed tutorials on the usage of image analysis tools, user-friendly intuitive software, and better solutions for segmentation, ideally in a format tailored to their specific use cases. The tool creators suggested the users familiarize themselves with the fundamentals of image analysis, provide constant feedback, and report the issues faced during image analysis while the users would like more documentation and an emphasis on tool friendliness. Regardless of the computational experience, there is a strong preference for written tutorials to acquire knowledge on image analysis. We also observed that the interest in having office hours to get an expert opinion on their image analysis methods has increased over the years. In addition, the community suggests the need for a common repository for the available image analysis tools and their applications. The opinions and suggestions of the community, released here in full, will help the image analysis tool creation and education communities to design and deliver the resources accordingly.

scientific communication and education↗

bioRxiv2023

Metabolic response of microglia to amyloid deposition during Alzheimer's disease progression in a mouse model

Alzheimers disease (AD) drives metabolic changes in the central nervous system (CNS). In AD microglia are activated and proliferate in response to amyloid {beta} plaques. To further characterize the metabolic changes in microglia associated with plaque deposition in situ, we examined cortical tissue from 2, 4, and 8-month-old wild type and 5XFAD mice, a mouse model of plaque deposition. 5XFAD mice exhibited progressive microgliosis and plaque deposition as well as changes in microglial morphology and neuronal dystrophy. Multiphoton-based fluorescent lifetime imaging microscopy (FLIM) metabolic measurements showed that older mice had an increased amount of free NAD(P)H, indicative of a shift towards glycolysis. Interestingly in 5XFAD mice, we also found an abundant previously undescribed third fluorescence component that suggests an alternate NAD(P)H binding partner associated with pathology. This work demonstrates that FLIM in combination with other quantitative imaging methods, is a promising label-free tool for understanding the mechanisms of AD pathology.

neuroscience↗

bioRxiv2023

Light sheet autofluorescence lifetime imaging with a single photon avalanche diode array

Single photon avalanche diode (SPAD) array sensors can increase the imaging speed for fluorescence lifetime imaging microscopy (FLIM) by transitioning from laser scanning to widefield geometries. While a SPAD camera in epi-fluorescence geometry enables widefield FLIM of fluorescently labeled samples, label-free imaging of single-cell autofluorescence is not feasible in an epi-fluorescence geometry because background fluorescence from out-of-focus features masks weak cell autofluorescence and biases lifetime measurements. Here, we address this problem by integrating the SPAD camera in a light sheet illumination geometry to achieve optical sectioning and limit out-of-focus contributions, enabling fast label-free FLIM of single-cell NAD(P)H autofluorescence. The feasibility of this NAD(P)H light sheet FLIM system was confirmed with time-course imaging of metabolic perturbations in pancreas cancer cells with 10 s integration times, and in vivo NAD(P)H light sheet FLIM was demonstrated with live neutrophil imaging in a zebrafish tail wound, also with 10 s integration times. Finally, the theoretical and practical imaging speeds for NAD(P)H FLIM were compared across laser scanning and light sheet geometries, indicating a 30X to 6X frame rate advantage for the light sheet compared to the laser scanning geometry. This light sheet system provides faster frame rates for 3D NAD(P)H FLIM for live cell imaging applications such as monitoring single cell metabolism and immune cell migration throughout an entire living organism.

bioengineering↗

bioRxiv2023

The Autophagy Receptor NBR1 Directs the Clearance of Photodamaged Chloroplasts

The ubiquitin-binding NBR1 autophagy receptor plays a prominent role in recognizing ubiquitylated protein aggregates for vacuolar degradation by macroautophagy. Here, we show that upon exposing Arabidopsis plants to intense light, NBR1 associates with photodamaged chloroplasts independently of ATG7, a core component of the canonical autophagy machinery. NBR1 coats both the surface and interior of chloroplasts, which is then followed by direct engulfment of the organelles into the central vacuole via a microautophagy-type process. The relocalization of NBR1 into chloroplasts does not require the chloroplast translocon complexes embedded in the envelope but is instead greatly enhanced by removing the self-oligomerization mPB1 domain of NBR1. The delivery of NBR1-decorated chloroplasts into vacuoles depends on the ubiquitin-binding UBA2 domain of NBR1 but is independent of the ubiquitin E3 ligases SP1 and PUB4, known to direct the ubiquitylation of chloroplast surface proteins. Compared to wild-type plants, nbr1 mutants have altered levels of a subset of chloroplast proteins and display abnormal chloroplast density and sizes upon high light exposure. We postulate that, as photodamaged chloroplasts lose envelope integrity, cytosolic ligases reach the chloroplast interior to ubiquitylate thylakoid and stroma proteins which are then recognized by NBR1 for autophagic clearance. This study uncovers a new function of NBR1 in the degradation of damaged chloroplasts by microautophagy.

cell biology↗

bioRxiv2021

KLC4 shapes axon arbors during development and mediates adult behavior

Development of elaborate and polarized neuronal morphology requires precisely regulated transport of cellular cargos by motor proteins such as kinesin-1. Kinesin-1 has numerous cellular cargos which must be delivered to unique neuronal compartments. The process by which this motor selectively transports and delivers cargo to regulate neuronal morphogenesis is poorly understood, although the cargo-binding kinesin light chain (KLC) subunits contribute to specificity. Our work implicates one such subunit, KLC4, as an essential regulator of axon branching and arborization pattern of sensory neurons during development. Using live imaging approaches in klc4 mutant zebrafish, we show that KLC4 is required for stabilization of nascent axon branches, proper microtubule (MT) dynamics, and endosomal transport. Furthermore, KLC4 is required for proper tiling of peripheral axon arbors: in klc4 mutants, peripheral axons showed abnormal fasciculation, a behavior characteristic of central axons. This result suggests that KLC4 patterns axonal compartments and helps establish molecular differences between central and peripheral axons. Finally, we find that klc4 mutant larva are hypersensitive to touch and adults show anxiety-like behavior in a novel tank test, implicating klc4 as a new gene involved in stress response circuits.

neuroscience↗

bioRxiv2021

2020 BioImage Analysis Survey: Community experiences and needs for the future

In this paper, we summarize a global survey of 484 participants of the imaging community, conducted in 2020 through the NIH Center for Open BioImage Analysis (COBA). This 23-question survey covered experience with image analysis, scientific background and demographics, and views and requests from different members of the imaging community. Through open-ended questions we asked the community to provide feedback for the open-source tool developers and tool user groups. The communitys requests for tool developers include general improvement of tool documentation and easy-to-follow tutorials. Respondents encourage tool users to follow the best practices guidelines for imaging and ask their image analysis questions on the Scientific Community Image forum (forum.image.sc). We analyzed the communitys preferred method of learning, based on level of computational proficiency and work description. In general, written step-by-step and video tutorials are preferred methods of learning by the community, followed by interactive webinars and office hours with an expert. There is also enthusiasm for a centralized location online for existing educational resources. The survey results will help the community, especially developers, trainers, and organizations like COBA, decide how to structure and prioritize their efforts. Impact statementThe Bioimage analysis community consists of software developers, imaging experts, and users, all with different expertise, scientific background, and computational skill levels. The NIH funded Center for Open Bioimage Analysis (COBA) was launched in 2020 to serve the cell biology communitys growing need for sophisticated open-source software and workflows for light microscopy image analysis. This paper shares the result of a COBA survey to assess the most urgent ongoing needs for software and training in the community and provide a helpful resource for software developers working in this domain. Here, we describe the state of open-source bioimage analysis, developers and users requests from the community, and our resulting view of common goals that would serve and strengthen the community to advance imaging science.

bioinformatics↗

bioRxiv2020

FLIMJ: an open-source ImageJ toolkit for fluorescence lifetime image data analysis

In the field of fluorescence microscopy, there is continued demand for dynamic technologies that can exploit the complete information from every pixel of an image. One imaging technique with proven ability for yielding additional information from fluorescence imaging is Fluorescence Lifetime Imaging Microscopy (FLIM). FLIM allows for the measurement of how long a fluorophore stays in an excited energy state and is affected by changes in its chemical microenvironment, such as proximity to other fluorophores, pH, and hydrophobic regions. This ability to provide information about the microenvironment has made FLIM a powerful tool for cellular imaging studies ranging from metabolic measurement to measuring distances between proteins. The increased use of FLIM has necessitated the development of computational tools for integrating FLIM analysis with image and data processing. To address this need, we have created FLIMJ, an ImageJ plugin, and toolkit that allows for easy use and development of extensible image analysis workflows with FLIM data. Built on the FLIMLib decay curve fitting library and the ImageJ Ops framework, FLIMJ offers FLIM fitting routines with seamless integration with other ImageJ components, and the ability to be extended to create complex FLIM analysis workflows. Building on ImageJ Ops also enables FLIMJs routines to be used with Jupyter notebooks and integrate naturally with science-friendly programming in, e.g., Python and Groovy. We show the extensibility of FLIMJ in two analysis scenarios: lifetime-based image segmentation and image colocalization. We also validate the fitting routines by comparing against industry FLIM analysis standards.

bioengineering↗

bioRxiv2020

Modelling early thermal injury using an ex vivo human skin model of contact burns

BackgroundEarly mechanisms underlying the progressive tissue death and the regenerative capability of burn wounds are understudied in human skin. A clinically relevant, reproducible model for human burn wound healing is needed to elucidate the early changes in the human burn wound environment. This study reports a reproducible contact burn model on human skin that explores the extent of tissue injury and healing over time, and defines the inter-individual variability in human skin to enable use in mechanistic studies on burn wound progression and healing. MethodsUsing a customized burn device, contact burns of various depths were created on human skin by two operators and were evaluated for histologic depth by three raters to determine reproducibility. Early burn wound progression and wound healing were also evaluated histologically after the thermally injured human skin was cultured ex vivo for up to 14 days. ResultsBurn depths were reproducibly generated on human skin in a temperature- or time-dependent manner. No significant difference in operator-created or rater-determined depth was observed within each patient sample. However, significant inter-individual variation was identified in burn depth in ten patient samples. Burn-injured ex vivo human skin placed into culture demonstrated differential progression of cell death and collagen denaturation for high and low temperature contact burns, while re-epithelialization was observed in superficial burn wounds over a period of 14 days. ConclusionThis model represents an invaluable tool to evaluate the inter-individual variability in early burn wound progression and wound healing to complement current animal models and enhance the translation of preclinical research to improvements in patient care.

cell biology↗

bioRxiv2020

Transient Room Lighting for Ambient Light Multiphoton Microscopy

Laser scanning microscopy techniques such as confocal and multiphoton fluorescence microscopy have been widely adopted by the biological research community due to their ability to monitor intact specimens at high spatial and temporal resolution. However, they have been limited for many biomedical, clinical and industrial applications by their fundamental need to operate in near absolute darkness. We present a lighting system that allows the use of light-sensitive imaging techniques in a fully-lit room by interleaving capture and illumination at a high frequency and exploiting the light averaging properties of the human eye. We use this system with a multiphoton fluorescence microscope to illustrate that this method is capable of image capture in a well-lit room on par with capture in absolute darkness. This comparison is quantified through noise analysis of the images. This system has been implemented for laser scanning microscopy but has potential for widefield fluorescence imaging suitable for open-field surgery.

bioengineering↗