High Throughput Fluorescence Imaging for Plant Sciences
Lead Research Organisation:
University of Oxford
Department Name: Plant Sciences
Abstract
Research cell and developmental biology relies on imaging structures and molecules within living cells. In this way biological process can be followed in 3D over time scales ranging from tens of milliseconds to tens of hours. The most widely applied method for collecting such images is confocal fluorescence microscopy which provides clear images from within living tissues without the need to kill and physically section the specimen. The effectiveness of the method depends, first, on the ability to tag specific molecules with a fluorescent label and, second, on the ability of the microscope to form an image with high resolution and contrast whilst excluding out-of-focus information. Recent advances in structured illumination techniques, such as the Zeiss apotome system, have allowed optical sectioning at lower-magnifications which greatly facilitates initial fluorescence screening prior to confocal imaging, or measurements of physiological and developmental processes operating at much larger spatial scales (several cm squared) needed to image entire intact plant tissues and organs. Thus the ideal solution to be able to track developmental and physiological responses needs to combine low-magnification fluorescence for initial screening with high-resolution follow-up for detailed cellular and sub-cellular resolution. The addition of a robotic system tailored to the demands of plant specimens maximises the efficiency of data collection needed to achieve high-throughput for screening projects, or to allow long-term unattended operation for developmental studies. Such automated high-throughput fluorescence screening is routine in animal studies, where cells can be easily grown in multi-well culture plates, but a pipeline specifically tailored to handle the range of spatial scales and developmental time periods appropriate for plant systems would be unique in the UK.
Technical Summary
The use of fluorescent reporters and live-cell imaging has revolutionised our ability to probe plant and fungal development and physiology in unprecedented detail. The latest generation of microscopes are sufficiently sensitive to visualise responses in three (x,y,z) and four (x,y,z,t) dimensions for multiple probes at different wavelengths over a wide range of temporal and spatial scales to determine how plants grow and respond to their environment. However, operating these microscopes is time-consuming and requires considerable expertise to collect good quality data, particularly from plant tissues, often limiting the throughput of the instruments, and the type of research questions that can be tackled within a reasonable time frame. Thus, we have developed an automated fluorescence imaging system specifically tailored to the demands of plant systems that comprises a low-magnification Zeiss AxioZoom V16 fluorescence microscope as the front-end, that is fed samples in a variety of plate formats using a Peak Analysis and Automation (PAA) KiNEDx robotic automation system, with specimens maintained in a custom-built illuminated carousel growth incubator. The robot also interfaces directly to a Zeiss LSM 880 AiryScan confocal system for high-resolution follow-up measurements for regions-of-interest (ROIs), where co-ordinates are automatically transferred within the Overlord software environment. Both microscopes are equipped with motorized sample stages to allow registration and seamless integration of data collected at low magnification to provide context, with images collected at high-resolution to provide detail. The system can operate in three modes to allow high-throughput automated screening of reporter lines, repeated sampling over extended time periods for developmental studies at low and high spatial resolution, and both multiplexed, wide-field of view physiological studies to complement cell-specific high-resolution measurements.
Planned Impact
The world-class research that is supported by the microscopy facility in the Department of Plant Sciences is focused on providing a deep understanding of fundamental plant and microbial biology and is disseminated through major academic publications and conference publications. This fundamental research also underpins patent applications, technology transfer and supports spin-out companies to commercialise applications of the research.
For example research into chloroplast biogenesis has led to new opportunities to protect plants against the sorts of environmental stresses that are likely to become increasingly problematic in agriculture as climates change ( Jarvis, P. (2016) Plant discovery could help develop stress-resistant crops. BBSRC Business Winter 2016, p. 17.; http://www.bbsrc.ac.uk/news/food-security/2015/150918-pr-plant-discovery-help-develop-stress-resistant-crops/). This and research into the evolution of rooting structures (Dolan) in the earliest land plants has resulted in Follow-On Funding for commercialisation of research findings and similar strategies are being followed by other users of the facility, though details are commercially sensitive.
Other work supported by the facility in the Moore lab has provided unexpected insights into the cellular function of a protein involved in human neurodegenerative disease (Of Axons and Root Hairs: Plants in the Neurodegeneration Lab? http://www.alzforum.org/news/research-news/axons-and-root-hairs-plants-neurodegeneration-lab).
The facility also has impact in the commercial sector, supporting the R&D activities of the University spin-out company, Oxford Nanopore Technologies Ltd over several years, in the development of their biological analysis tools such as the worlds first and only nanopore DNA sequencer, the MinION. Other users of the microscope based in Engineering Science use the microscopy facility study bacterial biofilms and their impact on water quality and industrial processes.
Finally, the facility is used regularly for outreach and University access activities with members of the public or prospective students who may not consider applying to university or pursuing a career in plant biology. The images that are acquired also form the basis of public engagement activities in local museums, botanic gardens, and further afield and provide insight into a hidden world of cellular structure and dynamics rarely fails to impress.
For example research into chloroplast biogenesis has led to new opportunities to protect plants against the sorts of environmental stresses that are likely to become increasingly problematic in agriculture as climates change ( Jarvis, P. (2016) Plant discovery could help develop stress-resistant crops. BBSRC Business Winter 2016, p. 17.; http://www.bbsrc.ac.uk/news/food-security/2015/150918-pr-plant-discovery-help-develop-stress-resistant-crops/). This and research into the evolution of rooting structures (Dolan) in the earliest land plants has resulted in Follow-On Funding for commercialisation of research findings and similar strategies are being followed by other users of the facility, though details are commercially sensitive.
Other work supported by the facility in the Moore lab has provided unexpected insights into the cellular function of a protein involved in human neurodegenerative disease (Of Axons and Root Hairs: Plants in the Neurodegeneration Lab? http://www.alzforum.org/news/research-news/axons-and-root-hairs-plants-neurodegeneration-lab).
The facility also has impact in the commercial sector, supporting the R&D activities of the University spin-out company, Oxford Nanopore Technologies Ltd over several years, in the development of their biological analysis tools such as the worlds first and only nanopore DNA sequencer, the MinION. Other users of the microscope based in Engineering Science use the microscopy facility study bacterial biofilms and their impact on water quality and industrial processes.
Finally, the facility is used regularly for outreach and University access activities with members of the public or prospective students who may not consider applying to university or pursuing a career in plant biology. The images that are acquired also form the basis of public engagement activities in local museums, botanic gardens, and further afield and provide insight into a hidden world of cellular structure and dynamics rarely fails to impress.
Organisations
Publications
Moody L
(2018)
Genetic Regulation of the 2D to 3D Growth Transition in the Moss Physcomitrella patens
in Current Biology
Moody LA
(2018)
Somatic hybridization provides segregating populations for the identification of causative mutations in sterile mutants of the moss Physcomitrella patens.
in The New phytologist
Pain C
(2019)
Quantitative analysis of plant ER architecture and dynamics.
in Nature communications
Kalde M
(2019)
Interactions between Transport Protein Particle (TRAPP) complexes and Rab GTPases in Arabidopsis.
in The Plant journal : for cell and molecular biology
Hughes TE
(2020)
SCARECROW gene function is required for photosynthetic development in maize.
in Plant direct
Elliott L
(2020)
Spatio-temporal control of post-Golgi exocytic trafficking in plants.
in Journal of cell science
Elliott L
(2020)
The importance of being edgy: cell geometric edges as an emerging polar domain in plant cells.
in Journal of microscopy
Garcia VJ
(2020)
TRIPP Is a Plant-Specific Component of the Arabidopsis TRAPPII Membrane Trafficking Complex with Important Roles in Plant Development.
in The Plant cell
Mendes MA
(2020)
The RNA-dependent DNA methylation pathway is required to restrict SPOROCYTELESS/NOZZLE expression to specify a single female germ cell precursor in Arabidopsis.
in Development (Cambridge, England)
Rutten PJ
(2021)
Multiple sensors provide spatiotemporal oxygen regulation of gene expression in a Rhizobium-legume symbiosis.
in PLoS genetics
Moreno-Ruiz D
(2021)
Stress-Activated Protein Kinase Signalling Regulates Mycoparasitic Hyphal-Hyphal Interactions in Trichoderma atroviride.
in Journal of fungi (Basel, Switzerland)
Durr J
(2021)
A Novel Signaling Pathway Required for Arabidopsis Endodermal Root Organization Shapes the Rhizosphere Microbiome.
in Plant & cell physiology
Moody LA
(2021)
NO GAMETOPHORES 2 Is a Novel Regulator of the 2D to 3D Growth Transition in the Moss Physcomitrella patens.
in Current biology : CB
Jaeger R
(2021)
A fundamental developmental transition in Physcomitrium patens is regulated by evolutionarily conserved mechanisms.
in Evolution & development
Soldan R
(2021)
From macro to micro: a combined bioluminescence-fluorescence approach to monitor bacterial localization
in Environmental Microbiology
Sandor A
(2021)
IntEResting structures: formation and applications of organized smooth endoplasmic reticulum in plant cells
in Plant Physiology
Hoehne M
(2022)
Spatial and temporal control of mitochondrial H 2 O 2 release in intact human cells
in The EMBO Journal
Serra L
(2022)
Flip-Flap: A Simple Dual-View Imaging Method for 3D Reconstruction of Thick Plant Samples.
in Plants (Basel, Switzerland)
Aguilar-Trigueros CA
(2022)
Network traits predict ecological strategies in fungi.
in ISME communications
Spatola Rossi T
(2023)
Recombinant expression and subcellular targeting of the particulate methane monooxygenase (pMMO) protein components in plants.
in Scientific reports
Sandor A
(2024)
Characterization of intracellular membrane structures derived from a massive expansion of endoplasmic reticulum (ER) membrane due to synthetic ER-membrane-resident polyproteins.
in Journal of experimental botany
| Description | The grant was for development of high-throughput fluorescence imaging in plant sciences and has contributed to numerous projects within the department. The msot notable published work is automated quantitation of the sub-cellular architecture and dynamics of the plant endoplasmic reticulum. This provides imaging protocols and a complete software packaged developed using the equipment that is available on-line for other scientist to use in their research. Other projects include time-lapse imaging of root colonisation by N2-fixing bacteria, imaging 3D growth development in plants, and extended, time-lapse quantitation of fungal mycelial networks and functional traits. |
| Exploitation Route | The equipment is already widely used by researchers in Plant Sciences and also Zoology. The general strategy for the facility also includes making all software and protocols available on-line for other users. |
| Sectors | Agriculture Food and Drink |
| Title | AnalyzER |
| Description | AnalyzER: Quantitative analysis of plant ER architecture and dynamics The endoplasmic reticulum (ER) forms a complex and dynamic network of tubules and sheet-like cisternae that ramify throughout the cytoplasm. This software package is designed to quantify ER organisation in plant epidermal cells, where the ER is confined to a very thin layer of cytoplasm appressed to the periclinal cell wall as a planar, 2-D network. The input image typically comprises single plane (x,y) confocal fluorescence images of ER-targeted fluorescent proteins. The aim of the AnalyzER program is to quantify: The length, width, morphology and protein distribution along the ER tubules; The degree and branch angles at junctions (nodes) in the tubular network; The size, shape and protein distribution in cisternal sheets and around the perimeter of the cisternae; The topological organisation of the tubular and cisternal network determined using graph-theoretic metrics; The distribution of immobile nodes, tubules and cisternae using persistency mapping; The local speed and direction of movement of tubules and cisternae using optical flow; The size and shape of the polygonal regions enclosed by the network; Overview The simplest method to identify the ER automatically would be an intensity-based segmentation of the fluorescent image to give a binary image, with ones representing the ER structure and zeros for the background. However, the resultant binary image is critically dependent on the value for the threshold used, and it is rare that a single threshold provides adequate segmentation without either losing dimmer structures if it is set too high, or artificially expanding and fusing adjacent regions if it is set too low. Thus the approach adopted here exploits additional intensity-independent information over a range of scales and orientations to enhance the network structure, prior to segmentation as a single-pixel wide skeleton. The skeleton is then used as a template to interrogate the image locally to provide an estimate of the relative amount of fluorescent probe present and to provide an indication of the tubule width. The expected width of the ER tubule is only 50-70nm, which is below the resolution of the confocal microscope, but can just be resolved with super-resolution techniques, such as stimulated emission depletion microscopy (STED). For most laboratories, access to super-resolution techniques may be limited, necessitating the development of approaches that can be used on a routine basis with existing tools. Thus, with additional assumptions about the distribution of the fluorescent lumenal marker and the point-spread-function (psf) of the microscope, the width of the ER can be estimated, even if this is below the resolution limit of the microscope system. We have implemented some basic routines to estimate the relative tubule width convolved with the psf, and also introduced additional measures using the intensity values to infer the actual sub-resolution tubule width. Topological measures of the ER network structure can also be extracted following conversion of the pixel skeleton to a weighted, un-directed graph, where nodes represent junction points and edges represent the tubules that connect them. Unlike morphological measurements, the topology of the network is less sensitive to the resolution of the imaging system as it reflects the connectivity of the ER rather than the physical size of the components. The AnaylzER package The AnalyzER package is implemented in MatLab and available from the download link as a MatLab app for MatLab 2022a or later, or as a standalone package for Windows 10. All aspects of the analysis are handles through a single graphical user interface to provide an integrated platform. |
| Type Of Technology | Software |
| Year Produced | 2023 |
| Impact | Allows quantitative measurements on ER structure and dynamics from imaging data and statistical comparison between treatments |
| URL | https://zenodo.org/record/6386982 |
| Title | AnalyzER |
| Description | AnalyzER: Quantitative analysis of plant ER architecture and dynamics The endoplasmic reticulum (ER) forms a complex and dynamic network of tubules and sheet-like cisternae that ramify throughout the cytoplasm. This software package is designed to quantify ER organisation in plant epidermal cells, where the ER is confined to a very thin layer of cytoplasm appressed to the periclinal cell wall as a planar, 2-D network. The input image typically comprises single plane (x,y) confocal fluorescence images of ER-targeted fluorescent proteins. The aim of the AnalyzER program is to quantify: The length, width, morphology and protein distribution along the ER tubules; The degree and branch angles at junctions (nodes) in the tubular network; The size, shape and protein distribution in cisternal sheets and around the perimeter of the cisternae; The topological organisation of the tubular and cisternal network determined using graph-theoretic metrics; The distribution of immobile nodes, tubules and cisternae using persistency mapping; The local speed and direction of movement of tubules and cisternae using optical flow; The size and shape of the polygonal regions enclosed by the network; Overview The simplest method to identify the ER automatically would be an intensity-based segmentation of the fluorescent image to give a binary image, with ones representing the ER structure and zeros for the background. However, the resultant binary image is critically dependent on the value for the threshold used, and it is rare that a single threshold provides adequate segmentation without either losing dimmer structures if it is set too high, or artificially expanding and fusing adjacent regions if it is set too low. Thus the approach adopted here exploits additional intensity-independent information over a range of scales and orientations to enhance the network structure, prior to segmentation as a single-pixel wide skeleton. The skeleton is then used as a template to interrogate the image locally to provide an estimate of the relative amount of fluorescent probe present and to provide an indication of the tubule width. The expected width of the ER tubule is only 50-70nm, which is below the resolution of the confocal microscope, but can just be resolved with super-resolution techniques, such as stimulated emission depletion microscopy (STED). For most laboratories, access to super-resolution techniques may be limited, necessitating the development of approaches that can be used on a routine basis with existing tools. Thus, with additional assumptions about the distribution of the fluorescent lumenal marker and the point-spread-function (psf) of the microscope, the width of the ER can be estimated, even if this is below the resolution limit of the microscope system. We have implemented some basic routines to estimate the relative tubule width convolved with the psf, and also introduced additional measures using the intensity values to infer the actual sub-resolution tubule width. Topological measures of the ER network structure can also be extracted following conversion of the pixel skeleton to a weighted, un-directed graph, where nodes represent junction points and edges represent the tubules that connect them. Unlike morphological measurements, the topology of the network is less sensitive to the resolution of the imaging system as it reflects the connectivity of the ER rather than the physical size of the components. The AnaylzER package The AnalyzER package is implemented in MatLab and available from the download link as a MatLab app for MatLab 2022a or later, or as a standalone package for Windows 10. All aspects of the analysis are handles through a single graphical user interface to provide an integrated platform. |
| Type Of Technology | Software |
| Year Produced | 2023 |
| Impact | Allows quantitative measurements on ER structure and dynamics from imaging data and statistical comparison between treatments |
| URL | https://zenodo.org/record/6386983 |
| Title | AnalyzER : Quantitative analysis of plant ER architecture and dynamics. |
| Description | The AnalyzER program is designed to automatically extract ER tubules and cisternae from multi-dimensional fluorescence images of plant ER. It automatically quantifies: (i) The length, width, morphology and protein distribution along ER tubules; (ii) The degree and branch angles at junctions (nodes) in the tubular network; (iii) The size, shape, and protein distribution in cisternae and around the perimeter of the cisternae; (iv) The topological organisation of the tubular and cisternal network determined using graph-theoretic metrics; (v) The distribution of immobile nodes, tubules and cisternae using persistency mapping; (vi) The local speed, direction, coherence, divergence and curl of movement of tubules and cisternae using optical flow; and (vii) The size and shape of the polygonal regions enclosed by the network. |
| Type Of Technology | Software |
| Year Produced | 2018 |
| Open Source License? | Yes |
| Impact | Publication in press in Nature communications |
| URL | https://ora.ox.ac.uk/objects/uuid:cb0e2845-2a9c-495a-84f0-4dd2c5164463 |
| Title | Dynamic calcium-mediated stress response and recovery signatures in the fungal pathogen, Candida albicans- GCaMP Analysis Software |
| Description | C_albicans_GCaMP_CSA.zip Calcium Spike Analysis (CSA) MATLAB software developed by Prof Mark Fricker (University of Oxford) for GCaMP6 signal analysis in C. albicans. MATLAB APP install files included in ZIP files for CSA analysis and GCaMP spike plotting software. Please see Preprint: Dynamic calcium-mediated stress response and recovery signatures in the fungal pathogen, Candida albicans in BioRxiv for more information on how the software is used to analyse data: https://doi.org/10.1101/2023.04.20.537637 Dependencies for Software: MATLAB plus the following toolboxes: •'Signal Processing Toolbox' • 'Image Processing Toolbox' • 'Statistics and Machine Learning Toolbox' • 'Curve Fitting Toolbox' • 'Bioinformatics Toolbox' • 'Computer Vision System Toolbox' BioFormats package for importing microscopy data (http://www.openmicroscopy.org/), ensure this is in your MATLAB search path when installed The latest version of Java (http://www.java.com/en/) GhostScript: http://www.ghostscript.com/ XPDF Reader :https://www.xpdfreader.com/download.html |
| Type Of Technology | Software |
| Year Produced | 2023 |
| Open Source License? | Yes |
| Impact | Calcium (Ca2+) is an important second messenger for activating stress response signaling and cell adaptation in eukaryotic cells yet intracellular Ca2+-dynamics in fungi are poorly understood due to lack of effective real-time Ca2+ reporters. We engineered the GCaMP6f construct for use in the fungal pathogen, Candida albicans, and used live-cell imaging to observe both dynamic Ca2+ spiking and slower changes in non-spiking Ca2+-GCaMP signals elicited by stress or gene deletion. Short-term exposure to membrane, osmotic or oxidative stress generated immediate stress-specific responses and repeated exposure revealed differential recovery signatures. Osmotic stress caused yeast cell shrinkage and no adaptation response, where Ca2+-GCaMP spiking was inhibited by 1 M NaCl but not by 0.666 M CaCl2. Treatment with sodium dodecylsulfate (SDS) caused a spike-burst, raised the non-spiking Ca2+-GCaMP signals, and caused significant cell death, but surviving cells adapted over subsequent exposures. Treatment with 5 mM H2O2 abolished spiking and caused transient non-GCaMP-related autofluorescence, but cells adapted such that spiking returned and autofluorescence diminished on repeated exposure. Adaptation to H2O2 was dependent on Cap1, extracellular Ca2+, and calcineurin but not on its downstream target, Crz1. Ca2+-dynamics were not affected by H2O2 in the hog1? or yvc1? mutants, suggesting a pre-adapted, resistant state, possibly due to changes in membrane permeability. Live-cell imaging of Ca2+-GCaMP responses in individual cells has, therefore, revealed the dynamics of Ca2+-influx, signaling and homeostasis, and their role in the temporal stress response signatures of C. albicans. |
| URL | https://zenodo.org/record/7995559 |
| Title | Fungal Network Analysis |
| Description | Software to extract and analyse fungal networks. FungalNetworkAnalysis.mlappinstall - installs the software as a matlab app (requires Matlab 2023b or later). FungalNetworkAnalysis.exe - installs a standalone package for Windows 11. This will automatically download the Matlab runtime library from the web during installation. . FungalNetworkAnalysis_Manual.pdf - A user manual describing installation and use of the software. Images of fungal mycelia can be loaded into the FungalNetworkAnalysis GUI and processed through a standard pipeline that includes noise reduction, background correction, network enhancement, segmentation, skeletonization, width estimation and network graph representation. As fungal mycelia span a range of scales, with differing contrast and noise levels depending on the imaging method, a number of different curvilinear feature enhancement methods and skeletonisation algorithms are provided to extract the network structure as a single-pixel wide binary skeleton. One of the most critical features of network analysis is to ensure that parts of the network do not become accidentally disconnected during extraction, as this may have a major impact on prediction of functional flows on the network and robustness measurements. Thus, the approach used here initially over-segments the network to ensure connectivity, calculates an initial graph and then prunes the individual edges using a combination of metrics. The pruned skeleton is then re-converted to a fully weighted graph representation, with nodes at the junctions or branch points, linked by edges with a vector of properties such as width, length and orientation. Once in a graph format, a wide range of graph theoretic measures can be calculated. V1.00.14 includes the option to save large images to disk, rather than work in RAM. If there are any issues please contact me: mark.fricker@biology.ox.ac.uk Please cite: Aguilar-Trigueros, C.A., Boddy, L., Rillig, M.C. and Fricker, M.D. (2022) Network traits predict ecological strategies in fungi. ISME Communications. 2, 2 https://doi.org/10.1038/s43705-021-00085-1 The original images and parameter files from the paper can also be downloaded from: https://doi.org/10.5281/zenodo.5725750 |
| Type Of Technology | Software |
| Year Produced | 2024 |
| Open Source License? | Yes |
| Impact | Colonization of terrestrial environments by filamentous fungi relies on their ability to form networks that can forage for and connect resource patches. Despite the importance of these networks, ecologists rarely consider network features as functional traits because their measurement and interpretation are conceptually and methodologically difficult. To address these challenges, we have developed a pipeline to translate images of fungal mycelia, from both micro- and macro-scales, to weighted network graphs that capture ecologically relevant fungal behaviour. We focus on four properties that we hypothesize determine how fungi forage for resources, specifically: connectivity; relative construction cost; transport efficiency; and robustness against attack by fungivores. Constrained ordination and Pareto front analysis of these traits revealed that foraging strategies can be distinguished predominantly along a gradient of connectivity for micro- and macro-scale mycelial networks that is reminiscent of the qualitative 'phalanx' and 'guerilla' descriptors previously proposed in the literature. At one extreme are species with many inter-connections that increase the paths for multidirectional transport and robustness to damage, but with a high construction cost; at the other extreme are species with an opposite phenotype. Thus, we propose this approach represents a significant advance in quantifying ecological strategies for fungi using network information. |
| URL | https://zenodo.org/doi/10.5281/zenodo.10717873 |