Virtual Program

Osteoclast recycling and the osteomorph:  mechanism behind the therapeutic response to denosumab withdrawal

Michelle M. McDonald

The anti-RANKL treatment Denosumab (Dmab) is an effective treatment for osteoporosis. However, rapid bone loss and increased fracture have been associated with treatment withdrawal. To examine this in real-time in vivo, we developed a novel intravital imaging methodology to visualize osteoclast dynamics in tibia in live mice. We showed that in addition to apoptosis, osteoclasts undergo fission and recycle their cellular constituents (osteomorphs) as they re-fuse, and used scRNAseq to define these novel osteomorphs. We also showed accumulation of osteomorphs and their re-fusion following withdrawal of RANKL inhibition, providing a mechanism for rebound bone loss and following Denosumab withdrawal.

Lighting up the pathways of caspase activation

Lisa Bouchier-Hayes

The caspase family of proteases are essential for the initiation and execution of apoptosis and innate immune signaling. Initiator caspases are the first activated in their pathway and are activated by proximity-induced dimerization upon recruitment to large molecular weight activation platforms. We have adapted bimolecular fluorescence complementation (BiFC) to measure caspase induced proximity, the first step in initiator caspase activation. By fusing non-fluorescent fragments of Venus to each caspase, we monitor the induced proximity of specific caspases through the refolding of Venus and resulting fluorescence. This allows for accurate spatial and temporal measurements of specific caspase activation in live cells. 

Establishing a functional organoid model of placental development

Mrs Claire Richards, PhD Candidate, University of Technology Sydney

Co Authors
Dr Amy Bottomley, University of Technology Sydney
Dr Louise Cole, University of Technology Sydney
Dr Kristine McGrath, University of Technology Sydney
Dr Lana McClements, University of Technology Sydney

Introduction: Preeclampsia is a cardiovascular disorder of pregnancy with no effective prevention or treatment. Research into the pathogenesis of preeclampsia has been limited due to ethical limitations and a lack of reliable models of the disease. Inadequate trophoblast invasion and remodelling of maternal uterine arteries are major contributing factors in the development of preeclampsia, thus a 3D trophoblast model would aid future research.

Aim: To establish a simple, cost-effective, reproducible and low-risk 3D cell model of the early placenta using a custom-made first trimester trophoblast cell line.
Methods/Results: Trophoblasts were either manually seeded in Matrigel droplets or bioprinted in an equivalent matrix and allowed to form 3D organoids in their normal culture medium. Organoids were imaged using an Incucyte Live-Cell Analysis System for 14 days and demonstrated invasive capabilities. Some organoids were sectioned and stained by haematoxylin and eosin (H&E) or immunofluorescence (IF) for visualisation. Others were fixed in situ and probed for IF imaging using Nikon TiE2 wide-field and Nikon A1 inverted confocal microscopy. In situ images were denoised and clarified by NIS Elements Ver 5.3 software. Heterogeneous cell morphologies were seen within the organoids by H&E and probing for subtype-specific markers such as E-cadherin for villous trophoblasts and human leukocyte antigen G (HLA-G) for extravillous trophoblasts.

Conclusions: Collectively, these data support the establishment of a 3D organoid model that has been characterised to show morphology of early placental tissue development. This model presents an opportunity to investigate key factors involved in trophoblast proliferation, differentiation and cellular function important for placental development

Shedding light onto the structural secrets inside pluripotent stem cells in real-time

Dr Jennifer Zenker, Group Leader, Australian Regenerative Medicine Institute, Monash University

Co Authors
Dr Asma Aberkane, Monash University
Ms Azelle Hawdon, Monash University
Ms Gemma Stathotos, Monash University
Dr Jessica Greaney, Monash University
Ms Yi Louise Li, Monash University

The organisation of a cell’s interior, the cytoskeleton and organelles, is fundamental for every cell’s functionality. However, unlike most differentiated cells, our knowledge about the contribution of the sub-cellular architecture to pluripotency remains scarce. Using advanced live imaging, we discovered polarised non-centrosomal microtubules as central player for the pluripotent state of the in vivo early mammalian embryo and induced pluripotent stem cells (iPSCs). Each cell contains an apical pole highly enriched with CAMSAP3-nucleated microtubules, growing in a longitudinal direction towards the base of PSCs. These non-centrosomal microtubules initiate an asymmetry of organelles and metabolites. We further establish their rearrangement upon differentiation in a germ layer-specific manner. Dissecting how intrinsic cellular regulation contributes to pluripotency will lead a revolutionary era of regenerative and reproductive medicine.

Intravital imaging of mammary stem cells during organogenesis

Dr Caleb Dawson, Postdoc, WEHI

Organogenesis is a vitally important process but it is difficult to capture by live imaging in vivo. Mammary gland development provides a unique opportunity for studying organogenesis because it occurs in adolescence and is far more accessible than embryonic tissues. We developed a surgical technique to reveal the migrating tips of mammary ducts in puberty and filmed these using long-term multiphoton intravital imaging. We combined this with mosaic ‘confetti’ tracing of distinct mammary stem cell subsets to uncover single-cell behaviours that contribute to duct elongation. Custom-designed optical filters and alternative excitation allowed us to image the four confetti proteins and two additional markers in six separate channels. This revealed microenvironment interactions and tissue context as well as single-cell tracking. We then combined intravital imaging with cell behaviour modelling and subsequent immunostaining and 3D imaging. The resulting high-dimensional quantitative datasets have given us important new insights into mammary stem cell dynamics during organ development. This approach can also be applied to multiphoton imaging more broadly to help uncover complex tissue dynamics at the single-cell level.

Deterministic early endosomal maturation driven by EEA1 noise suppression

Mr Harrison York, PhD Student, Monash University

Co Authors
Mr Kunaal Joshi, Purdue University
Dr Charles Wright, Purdue University
Mr Ullhas Moorthi, Monash University
Dr Hetvi Gandhi, Monash University
Mr Abhishek Patil, Monash University
Dr Srividya Iyer-Biswas, Purdue University
Dr Senthil Arumugam, Monash University

Endosomal trafficking in single cells is built of generation of membrane vesicles, their motor protein mediated transport, morphological alterations such as tubulation, fusion and fission, and dynamic maintenance of various identities, which is defined by the lipid composition and localization of specific proteins on them. Endosomal maturation is a major process in endosomal trafficking in which endosomes shed one specific protein and acquire another, resulting in an identity change. Individual processes that build up endosomal trafficking, including conversions, are interlinked and are inherently stochastic. While the general biochemical interactions have been well described, how all the events come together to overcome the inherent noise and stochasticity is much less explored. Here, capitalising on the rapid volumetric imaging capability of Lattice-light sheet, we capture whole-cell volumes, enabling post-acquisition analysis of all conversion events as well as other dynamic characteristics. We show that early endosome maturation is driven by endosomal collision-induced conversions. Furthermore, using live-cell Förster Resonance Energy Transfer, we demonstrate that this is underpinned by cyclical conformational changes in EEA1, which promotes the biochemical maturation of these vesicles through its asymmetric binding capacity and clustering on the endosomal membranes. Using simulations, we recapture the experimentally observed characteristics in the reaction scheme and the activity of EEA1. Based on these experiments, we describe an EEA1-dependent mechanism that enables deterministic outcomes in ensemble endosomal conversions in an otherwise stochastic system.

In situ visualisation of the plasma cell niche in blood cancer and autoimmunity. 

Associate Professor Edwin Hawkins, Walter and Eliza Hall Institute

The generation of antibody that protects an individual for their lifetime is the cornerstone of the immune system. However, the mechanisms that select for, and maintain long-lived antibody producing cells in the bone marrow are not completely understood. By combining novel lineage tracing mouse models, multi-day 4 dimensional whole organ intravital imaging and single cell genomics, we have characterised a specialised niche in the bone marrow that drives this process. We illustrate how these niches lead to clonal selection of pathogenic plasma cells that drive diseases such as Lupus (autoimmunity) and Myeloma (an incurable blood cancer).

Automated annotation and visualisation of high-resolution spatial proteomic mass spectrometry imaging data using HIT-MAP

A/Prof Thomas Cox, Laboratory Head, Garvan Institute of Medical Research

Biological tissues are highly compartmentalized due to their complex and diverse functions. Organs and tissues are partitioned into histologically distinct, yet functionally co-dependent sub-regions that exhibit diverse cellular and molecular compositions. Importantly, the unique set of expressed proteins, specific to a particular cell type, location, or place in time and space, critically underpins tissue and organ function. Significant changes in these proteomes are observed in almost all disease-states.

Mass Spec Imaging has the potential to significantly advance our understanding of biology, physiology and medicine. Matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) is a powerful tool in the spatial proteomics field, enabling direct detection and registration of protein abundance and distribution across tissues. MALDI-MSI preserves spatial distribution and histology allowing unbiased analysis of complex, heterogeneous tissues.

However, MALDI-MSI faces the challenge of simultaneous peptide quantification and identification. To overcome this, we developed and validated HIT-MAP (High-resolution Informatics Toolbox in MALDI-MSI Proteomics), an open-source bioinformatics workflow using peptide mass fingerprint analysis and a dual scoring system to computationally assign peptide and protein annotations to high mass resolution MSI datasets and generate customisable spatial distribution maps.

The unbiased nature of MALDI-MSI allows for the interrogation of whole proteomes. Furthermore, the integration and co-registration of MALDI-MSI datasets with other established and/or emerging technology platforms (such as histology and spatial transcriptomics) will significantly increase our understanding of health and disease through combining complementary orthogonal data types.

HIT-MAP will be a valuable resource for the spatial proteomics community for analysing newly generated and retrospective datasets in both normal and disease contexts.

Multiplexed Ion Beam Imaging (MIBI) analysis pipeline: in situ characterisation of tissue architecture by open-source analysis

Mrs Nina Tubau Ribera, Bioimage analyst, WEHI

Co-authors
Ms Claire Marceaux, WEHI
Dr Kelly Rogers, WEHI
Dr Marie-Liesse Asselin-Labat, WEHI
Dr Lachlan Whitehead, WEHI

Multiplexed Ion Beam Imaging (MIBI) is a recent technology enabling comprehensive phenotypic profiling and spatial analysis of solid tissue. It uses a dynamic secondary ion mass spectrometer instrument with a time-of-flight mass analyser to image antibodies tagged with monoisotopic metal reporters and map their location in a multi-channel image. The system allows to visualise up to 40 markers on paraffin-embedded or fresh-frozen samples at subcellular resolution. This platform is available at Walter and Eliza Hall Institute of Medical Research since January. The system generates multi-layer TIFF images that are supported by Bio-Formats and are analysed in our recently developed pipeline using the open-source software QuPath.

First, we implemented a tiling and stitching pipeline, so users can easily image multiple fields of view of larger tissue sections. The image preprocessing consists of an isobaric correction and Voronoi tesselation filtering. A further step of normalisation has been added in order to complete any meaningful quantification. Within QuPath, we have implemented a segmentation tool using Deep Cell machine learning segmentation that provides state-of-the-art cell detection. In addition to the segmentation, we added a tool to measure the cell positivity to each marker based on mean intensity throughout the previously segmented cell. From the cell phenotypes we directly perform spatial analysis and visualise the results. Our current work resides in joining all these steps in a single-button pipeline allowing users an easy, quick and reproducible workflow for highly multiplexed analysis.

Gut Analysis Toolbox

Dr Pradeep Rajasekhar, Research Officer, Walter and Eliza Hall Institute of Medical Research

Co-authors
Dr Daniel Poole, Monash Institute of Pharmaceutical Sciences
Dr Simone Carbone, Monash Institute of Pharmaceutical Sciences
Mr Luke Sorensen, Monash Institute of Pharmaceutical Sciences

The gastrointestinal (GI) tract consists of an intricate network of neurons and glial cells forming the enteric nervous system (ENS) which coordinates essential functions, such as motility, secretion, and digestion. Functional disorders associated with diseases of the GI tract are characterised by a reduction in the number of enteric neurons or alteration in subpopulations of neuronal subtypes. Due to inconsistencies in analysis methods, there are conflicting reports in the literature about the extent and importance of neuronal loss in disease. There is a need for standardisation and automation of analysis workflows to improve reproducibility and reduce operator bias. To address this, we have developed the Gut Analysis Toolbox (GAT), a collection of FIJI macros that automate the segmentation and quantification of enteric neurons and glial cells in 2D in gut wholemounts. We have generated custom deep learning models using StarDist and DeepImageJ to segment cells and ganglia respectively. The ground truth data was generated manually using images from different species, acquired using different instruments, modalities and across different labs to increase the generalisability of the models. GAT increases throughput significantly and works across images on gut tissue from different species, regions of the gut, and acquired using different imaging modalities. We plan to extend the analysis to other cell types within the gut and include 3D analysis in the future.

Comparison of Quantitative Image Analysis Methods: Different Ways To Study Fenestrations In Liver Sinusoidal Endothelial Cells

Ms Karolina Szafranska, PhD student, University of Tromsø

Co-authors
Prof Peter McCourt, University of Tromsø
Ms Larissa Kruse, University of Tromsø
Mr Christopher Holte, University of Tromsø
Mr Barlomiej Zapotoczny, Institute of Nuclear Physics Poland

Liver Sinusoidal Endothelial Cells (LSECs) line the hepatic vasculature providing blood filtration via transmembrane nanopores called fenestrations. These structures are 50-300 nm in diameter, which is below the resolution limit of a conventional light microscopy. Fenestrations are dynamic structures that can react to various drugs and adapt their diameter and/or number within minutes or even seconds. Both the number and diameter of fenestrations are important for liver function. However, to date, there is no standardized method of fenestration image analysis.
Comparison of three different approaches: manual measurements, a semi-automatic (threshold-based) method, and an automatic method based on open source machine learning software. Images were obtained using three super resolution techniques – AFM, SEM, and SIM. Parameters describing fenestrations such as diameter, area, roundness, frequency, and porosity were measured. Finally, the user bias was studied by comparison of the data obtained by five different users applying provided analysis methods.

The data from all three imaging techniques suggests that the precision of both automatic methods is similar and linear correlation allows their use for comparison of the parameters between experimental groups. For fenestration size measurements, both automatic methods showed a systematic error that needs to be taken into consideration. User comparison also showed that there is significant user bias for manual measurements of fenestration diameter. Fenestration frequency and porosity show similar differences among the users for all three methods.
The best analysis method should be selected based on the following criteria: the available imaging technique, the achievable quality of the images, the time for the analysis and the predicted outcome in measured parameters. The results show that the semi-automatic and automatic methods can be a timesaving alternative to the standard manual approach.

Image Segmentation with Machine Learning

Dr Anna Kreshuk, EMBL Heidleberg

A Semi-automated Method Quantifying Changes in IL-1beta Co-localising with Different Neural Cell Types in Mouse Brain, in Response to Long-term Hypercapnia.

Miss Emma O'Rourke, Honours Graduate, UNSW

Co-authors
Ms Irit Markus, UNSW
Miss June M Sun, UNSW
Ms Latifa Bulbul, UNSW
Dr Natasha N Kumar, UNSW

We investigated inflammatory responses to long-term hypercapnia (elevated arterial CO2) in the brainstem respiratory chemosensing circuit (RCC). Aim: Within the RCC, to identify co-localisation of the inflammatory cytokine, interleukin 1-beta (IL-1beta), in cell populations including Phox2b neurons (tagged with green fluorescent protein; Phox2b-GFP+) and microglia (ionized calcium binding adapter molecule 1; Iba1+). To achieve this in an unbiased way, we designed a workflow using an open-source software QuPath (v. 0.2.1). Methods: Adult Phox2b-eGFP mice were divided into two experimental groups; control (10-day 0% CO2 exposure) and long-term hypercapnia (LH) (10-day 8% CO2 exposure). A multiplex immunofluorescent assay followed with 30 µm thick coronal sections. Using the QuPath ‘positive cell detection’ function, we automated identification of IL-1beta+ cells within the retrotrapezoid nucleus (RTN) region for whole slide scans, at 10x magnification. GFP+ or Iba1+ annotated cells that fell within IL-1beta+ detected outlines, were manually counted as co-localising if cell profiles overlayed. Results: In RTN, IL-1beta co-localised with a high proportion of Phox2b neurons but low levels of microglia both caudally (59 +/- 4.7 %, n=5; 8.5 +/- 0.9 %, n= 6) and rostrally (82 +/- 4.0 %, n=6; 19.4 +/- 3.5 %, n=7), respectively, at baseline. Exposure to LH did not significantly change the proportion of Phox2b or microglial cells that co-localised with IL-1beta when compared to baseline conditions. Whilst we detected no cellular response of IL-1beta to LH, IL-1beta could be an important neuromodulator in RCC. Our QuPath workflow allowed for rapid processing of data and a conclusion reached efficiently.

Artificial Intelligence in Bioimage Analysis

Professor Erik Meijering, UNSW Sydney

Advanced light microscopy imaging technologies are having an enormous impact on biomedical research, as they allow visualizing the structure and function of cells and even molecules with high sensitivity and specificity. The large data volumes generated in such studies require fully automated computational methods for accurate and reproducible quantitative analysis and interpretation of these data. To this end we develop advanced computer vision methods. Increasingly these methods are based on deep learning using artificial neural networks. This talk will highlight methods we have been developing specifically for cell and particle tracking and motion analysis.

Automated segmentation of glomeruli in mouse kidneys using machine learning

Dr Greg Bass, Senior Scientist, CSL Innovation

Co-authors
Mr Somesh Mehra, CSL Innovation
Dr Sandro Prato, CSL Innovation
Ms Yun Dai, CSL Innovation
Ms Amanda Turner, CSL Innovation
Dr Helen Cao, CSL Innovation
Ms Ana Maluenda, CSL Innovation
Dr Monther Alhamdoosh, CSL Innovation
Dr Greg Bass, CSL Innovation

Histopathological assessment of kidney tissue is commonly used in preclinical drug development, allowing scientists to monitor disease progression or assess the therapeutic potential of drug candidates in animal models. Kidney tissues contain hundreds of capillary tufts called glomeruli, which play an important role in the filtration of blood. Current analyses of glomeruli are generally low-throughput and labour-intensive, requiring manual segmentation of these small heterogeneous regions of interest from large whole-slide images (WSI). To accelerate the analysis of WSIs, we developed a machine learning-based pipeline in Python to automatically recognize and quantify glomeruli in H-PAS stained mouse kidney tissue. We used an ensemble of convolutional neural networks to locate glomeruli in a WSI, combined with a UNET to segment glomerular boundaries. We then applied various image analysis techniques to extract individual features of the glomeruli, enabling clinically relevant quantitative measures of kidney disease progression. We found that our algorithm is robust to the range of staining and structural variations that are expected across different batches or disease models. Finally, we utilized the open-source Streamlit framework to develop a user-friendly web application for life scientists to use. Our end-to-end solution enables scalable characterisation of glomeruli in WSIs, and consequently improves both the efficiency and statistical power of kidney tissue analyses widely used in the biopharmaceutical industry.

Super-resolved view of PfCERLI1, a rhoptry associated protein essential for Plasmodium falciparum merozoite invasion of erythrocytes

Dr Sonja Frolich, Postdoctoral Researcher, The University of Adelaide

Dr Frolich completed her PhD training in Molecular Parasitology in 2014 at the iThree Institute (i3) characterising the mechanisms of Eimeria maxima oocyst wall formation for interrupting parasitic disease of poultry, coccidiosis. In 2014, she was appointed as junior academic in the Climate Change Cluster (C3, UTS) to work on an ARC funded Linkage project grant with GE Health to establish protein expression platform in green algae Chlamydomonas. During this period, she co-supervised undergraduate students, and lectured to undergraduate and Masters students in Parasitology, Microbiology, and Microscopy and Flowcytometry. She is the recipient of several awards and travel grants, including Dean’s Academic Excellence Award (UTS) and Australian Technion Society Award. In March 2015, Dr Frolich has joined the Genome Integrity Unit at Children’s Medical Research Institute to develop automated microscopy-assisted high-content assays and optimise immunolabelling methods and applied state-of-the-art super-resolution imaging technologies (3D SIM, STED, STORM and Airyscan) to structural studies of telomeres for which she was awarded Research Excellence Award. In April 2016, Sonja joined the Research Centre of Infectious Diseases to work on an NHMRC funded project focusing on the biosynthesis of structural proteins in medically important parasite, Plasmodium falciparum.

Super-resolving the nanoscale dynamics of Botulinum Neurotoxin Type-A intoxication in hippocampal neurons

Dr Merja Joensuu, ARC DECRA Research Fellow, Queensland Brain Institute, The University of Queensland

Co-authors
Dr Vanessa Lanoue, Queensland Brain Institute, The University of Queensland
Dr Alisa Blum, Queensland Brain Institute, The University of Queensland
Dr Stefan Mahrhold, Institut für Toxikologie, Medizinische Hochschule Hannover, Hannover, Germany
Miss Nadja Krez, Institut für Toxikologie, Medizinische Hochschule Hannover, Hannover, Germany
A/Prof Giuseppe Ballistreri, University of Helsinki
Dr Andreas Rummel, Institut für Toxikologie, Medizinische Hochschule Hannover, Hannover, Germany
Prof Frederic Meunier, Queensland Brain Institute, The University of Queensland

Neuronal communication is encoded by neurotransmitters stored in synaptic vesicles (SVs) that undergo Ca2+-dependent fusion with the presynaptic plasma membrane (PM) upon stimulation, after which the SVs are rapidly reformed through endocytosis. Neurotoxins, such as Botulinum Neurotoxin Type-A (BoNT/A), the most potent toxin known, hijacks this endocytic pathway to be internalized into nerve terminals as part of their intoxication strategy to incapacitate neuronal communication. According to the long-standing dual-receptor hypothesis, BoNT/A first binds to a specific ganglioside (such as GT1b) on the plasma membrane, and then subsequently to an intraluminal epitope of plasma membrane-stranded synaptic vesicle protein 2 (SV2), thereby launching receptor-mediated endocytosis. Following translocation from SVs into the cytoplasm, the toxin’s light chain proteolytic activity then cleaves SNAP-25, a SNARE protein responsible for mediating fusion of SVs with the plasma membrane, leading to neurotransmission block and flaccid paralysis. I will discuss our recent discoveries that challenge the current receptor hypothesis, and introduce a novel hypothesis based on a coincidental engagement of the toxin to both ganglioside and SV2 within nanoclusters that controls the endocytic uptake and sorting of the BoNT/A in primary hippocampal neurons. Using super-resolution and confocal imaging, and electron microscopy, we studied the nanoscale dynamics and mechanisms by which BoNT/A is selectively targetted into SVs. Genetic inactivation of the BoNT/A’s GT1b and SV2 binding sites perturbed PM binding and clustering of the toxins, and the subsequent entry, sorting and retrograde trafficking, indicating that coincidental engagement of BoNT/A with both of the receptors is required for correct entry of the toxin. Single-molecule imaging uncovers an unprecedented dynamic view of the cascade of nanoscale events underpinning BoNT/A intoxication.

Imaging the trans-synaptic transfer mechanism of rabies virus.

Dr Vinod Sundaramoorthy, ARC DECRA Research fellow, Deakin University & CSIRO-ACDP

Rabies is a lethal neurotrophic virus which spreads exclusively within interconnected neurons in the host nervous system by transferring across neuronal junctions (synapses). This ability enables the rabies virus to mostly evade immune detection and cause irreversible damage to the nervous system. The trans-synaptic transfer ability of attenuated rabies virus is also exploited beneficially as an anatomical neuronal circuit tracer and as a potential vector system to carry therapeutics to the brain. However, the mechanisms that facilitate the transfer of rabies virus across the synapse is unknown. While the envelope protein (glycoprotein) of rabies virus is responsible for this trans-synaptic transmission, the specific neuronal receptors and associated ultrastructural changes occurring at the neuronal synapse to facilitate viral transfer remains unknown.

In this study, we employed advanced confocal and electron microscopy imaging techniques in high-containment PC3 laboratories to study trans-synaptic transfer of rabies virus in neurons. Using ex-vivo neuronal models, we performed ultrastructural investigation of rabies virus transfer between neurons in live and fixed cultures. In these studies, we identified novel trans-synaptic transfer mechanisms utilised by highly-neuroinvasive and low-neuroinvasive rabies strains in neurons. We also identified novel abilities of rabies virus glycoprotein to efficiently control and modify synaptic architecture in neurons to enable virus transfer. These studies present new information about how rabies spreads through the nervous system, generating valuable knowledge to develop future strategies for rabies treatment and to design next-generation rabies-derived vector systems for brain research and drug delivery.

Cellular remodelling during necroptosis characterized by live cell imaging

Dr Ying Zhang, Research Officer, Walter and Eliza Hall Institute

Co-authors
Dr Niall Geoghegan, Walter and Eliza Hall Institute
Dr Andre Samson, Walter and Eliza Hall Institute
Dr Kelly Rogers, Walter and Eliza Hall Institute
A/Prof James Murphy, Walter and Eliza Hall Institute
Prof Guillaume Lessene, Walter and Eliza Hall Institute

Necroptosis is a form of caspase-independent programmed cell death that has been suggested to play a role in the pathogenesis of various diseases. Necroptosis is executed by the activation of RIPK3 and MLKL that leads to the assembly of necrosome and subsequent rupture of plasma membrane. Due to the release of cell content, such as damage-associated molecular patterns (DAMPs), from ruptured membrane, necroptosis triggers inflammatory responses. Currently, the key biological markers that can distinguish necroptosis from other types of cell death is MLKL phosphorylation and membrane translocation, while the morphological changes, the release of DAMPs and the process of MLKL activation have not been well characterized.

Here, we employed Lattice Light Sheet Microscopy (LLSM) that can quickly generate three-dimensional (3D) super-resolution images with very limited phototoxicity to monitor the process of necroptosis in live cells. We observed a series of necroptosis-specific morphological changes and reorganization of actin cytoskeleton and further explored their relationships with DAMPs release. Our study also focuses on MLKL and investigated the involvement and the role of this pseudo-kinase in the process of cellular remodelling. This work provides new insight into the cellular events associated with necroptotic cell death with potential implications for fundamental and translational research.

A super-resolution microscopy study of drug-induced microtubule filament dysfunction

Dr Ashley Rozario, Research Assistant, Monash University

Co-authors
Dr Sam Duwé, Hasselt University, Diepenbeek, Belgium
Mr Cade Elliott, Monash University
Mr Riley Hargreaves, Monash University
Dr Gregory Moseley, Monash University
A/Prof Peter Dedecker, KU Leuven, Leuven, Belgium
Dr Donna Whelan, La Trobe University
Dr Toby Bell, Monash University

The microtubule (MT) network comprises tubular filaments ~25 nm wide and serves vital roles in cellular transport, structural integrity and cell division. The importance of MTs for cell health has motivated the characterization of MT dysfunction caused by anticancer drugs to better understand drug mechanisms. Direct observation of individual MT filaments in situ can be achieved using super-resolution microscopies that surpass the 200 - 300 nm diffraction limit of conventional imaging methods. Single molecule localization microscopy (SMLM) reaches as good as 20-nm spatial resolution, ideal for interrogating individual MT filaments in fixed cells. To image MTs in live cells, fluctuation correlation-based microscopy (SOFI) provides milder imaging conditions (i.e. low laser power) for subdiffraction time-lapse movies of live-cell MT filament dynamics.

Here we apply complementary super-resolution imaging strategies for a holistic perspective of MT dysfunction induced by low doses of antimitotic drug colcemid. SMLM shows MT filament curvature to be more pronounced, increasing with colcemid concentrations from 7 - 80 nM. Aberrant filament curvature induced by 50 - 80 nM of colcemid, quantified using SIFNE, was found to reach up to 2 µm/rad, a value associated with MT filament breakage. Higher colcemid doses at 100 and 200 nM revealed short and few MT filaments, suggesting MT fragmentation as a possible drug mechanism. Live cell SOFI reveals MT filament dynamics to be suppressed with as low as 18 nM of colcemid without aberrant filament curvature present.

Building and Using a Multifunctional Single Molecule/Super-Resolution Microscope

Dr Donna Whelan, DECRA Fellow, La Trobe University

This seminar will detail the design, build, and use of a bespoke, multimodal/super-resolution fluorescence microscope which we have established at La Trobe, Bendigo. In particular, I will describe how this setup was built with increased flexibility and a more user-friendly nature, compared to previous custom and commercial options. I will also detail the pipeline for our current single-molecule/super-resolution experiments from sample preparation and design, through acquisition and image rendering, and finally analysis. This includes recent results in the field of DNA damage and repair which identified previously unknown mechanisms in damage mitigation and disease avoidance(1, 2). Other applications that will be highlighted – all using the same microscope – have made use of fluorescence single particle tracking and darkfield microscopy in studies addressing motor neuron disease(3), anti-viral response(4), and metabolism(5, 6).

1.Whelan DR, et al. Plos Genetics. 2020;16(12): e1009256.
2.Whelan DR, Rothenberg E. Proceedings of the National Academy of Sciences. 2021;118(11):e2021963118.
3.Konopka A, et al. Molecular Neurodegeneration. 2020;15(1):51.
4.Monson EA, Whelan DR, Helbig KJ. Int J Mol Sci. 2021;22(9).
5.Sievers W, et al. Plos One. 2020;15(7):e0236286.
6.Van Schaik L, et al. Scientific Reports. 2021;11(1):113.

Imaging of interactions and inhibition of hGIIA in prostate cancer cells

Mr Timothy Mann, PhD Student, Western Sydney University

Co-authors
A/Prof Kieran Scott, Western Sydney University
Dr William Church, Sydney University
Dr Anya Salih, Fluoresci Research
Ms Mila Sajinovic, Ingham Institute
A/Prof Albert Mellick, UNSW
Dr Ryung Rae Kim, SpeeDX

Inflammation, a hallmark of cancer, is driven in part by activation of a fatty acid oxidation pathway that generates a myriad of signalling lipids termed eicosanoids. The eicosanoid pathway, begins with the rate-limiting step of release of the 20-carbon fatty acid arachidonic acid from phospholipid membranes, predominantly by phospholipase A2 (PLA2). The secreted PLA2,? hGIIA, is aberrantly over-expressed in prostate cancer (PCa), increases eicosanoid production and PCa cell proliferation, making it an attractive target for inhibition.

This research uses live imaging of tagged hGIIA in prostate cancer cell lines to identify that hGIIA enters the cell through autocrine and paracrine pathways, and is sequestered into the caveolae. Vesicle tracking found that hGIIA docks to vimentin and is trafficked around the cell. Direct binding of hGIIA to vimentin is confirmed with FLIM-FRET and Co-IP. Furthermore, the cyclic peptide c2, currently in clinical trial for the treatment of PCa, inhibits the hGIIA/vimentin interaction in vitro. c2 is autofluorescent with a unique fluorescent lifetime, allowing live cell imaging of c2 entry into the cell which colocalises with hGIIA in caveolae. Treatment of cells with c2 also results in altered vimentin filament organisation and hGIIA movement around the cell. These studies show that vimentin is likely involved in hGIIA’s proliferative effect, and that c2’s mechanism of action is likely through perturbation of the novel hGIIA vimentin interaction.

Dr Emma Gordon, Institute for Molecular Bioscience

Blood vessels are a critical component of the body, supplying oxygen and nutrients to all tissues. During vessel sprouting, endothelial cells behave in a collective manner and display heterogeneous gene expression, morphology and movement. A balance between adhesion and migration allows cells to actively migrate past one another in a fluid but controlled fashion, yet how this is controlled remains unclear. Using novel imaging approaches in cell and mouse models, we have identified the tyrosine kinase c-Src as a key mediator of cell adhesion and vascular sprouting, highlighting the importance of cellular signalling during blood vessel growth and function.

Solution for large sample image acquisition and visualization

Georgia Gofis, Andor

In this talk we will introduce Andor Dragonfly high speed confocal microscope system for large size sample imaging and Imaris software for visualization of the 3D image result.

AX/AX R Confocal laser scanning microscope system

Baharak Mahyad, Nikon

Confocal Endoscopy in Medicine and Research

Lindsay Bussai, Optiscan

The talk will start with an introduction to endomicroscopy, also known as ‘virtual histology’, ‘optical biopsy’ or 'confocal laser endomicroscopy' (CLE). Endomicroscopy is a technique for obtaining cellular and subcellular images from inside the living body or tissue sample in real-time. Confocal endomicroscopy uses the tip of an optical fiber for both illumination and detection pinholes, simplifying the design and enabling miniaturisation of confocal microscopes. The technology has applications in both medical imaging and academic research. After the introduction, the talk will provide a short summary of the technological developments in the field and then focus on the latest applications of endomicroscopy.

Intravital imaging technology guides FAK mediated priming in pancreatic cancer precision medicine according to Merlin status

Ms Kendall Murphy, Garvan Medical Research Institute

Intravital subcellular and single molecule imaging reveals multiple actin filament populations collaborate in the remodelling of the secretory granule membrane 

Mr Marco Heydecker, UNSW Sydney

Synergistic Combination of Reductionist and Holistic Approaches in the in vigilo Experiments on Awake Behaving Mice".

Dr Leonard Khirug, University of Helsinki

After decades of reductionist research to Neuroscience, animal experimentation is becoming increasingly more holistic as multimodal imaging and recording techniques are combined in a single experiment on the brain of awake behaving animal. This newly emerged approach can be called in vigilo (from Latin 'in awake' or 'in vigilant state'). The reductionist phase was the time to cast away stones as we kept splitting the subject matter into smaller and smaller “building blocks”. In this talk, I will argue that it is now time to gather stones, and indeed this has been a dominant trend during the last two decades.

SNT: a unifying toolbox for quantitative neuroanatomy

Dr Tiago Ferreira, Howard Hughes Medical Institute Janelia Research Campus

Multi-dimensional and multi-modal imagery are becoming commonplace in cellular neuroscience. Historically, software for neuronal reconstruction has not been amenable to such datasets. To this end, we have developed SNT, an end-to-end framework for neuronal morphometry that supports tracing, proof-editing, visualization, quantification, and modeling of neuroanatomy with support for whole-brain projectomes. With an open architecture, a large user base, community-based documentation, support for complex imagery and several model organisms, SNT became a broad resource for the broad neuroscience community. SNT is both a desktop application and multi-language scripting library, and it is available through the Fiji distribution of ImageJ.

Computational 3D fluorescence microscopy

Associate Professor Laura Waller, University of California Berkley

We describe a compact and inexpensive computational microscope that encodes 3D information into a single 2D sensor measurement, then exploits sparsity to reconstruct the volume with good resolution across a large volume.  Our system uses simple hardware and scalable software for easy reproducibility and adoption. The inverse algorithm is based on large-scale nonlinear optimization with self-calibration of aberrations and we discuss computational optical design approaches for optimizing the system’s performance. We demonstrate applications in whole organism bioimaging and neural activity tracking in vivo.

Leica BOND RX – Multiplexing and beyond: Expanding the BOND RX capabilities

Jessica Unwin, Leica Biosystems

Future of Image Analysis- Introduction to Aivia

Hoyin Lai, Leica Microsystems

Thermo scientific AMIRA software

Thermofisher

Imaging Biological Structures of cells below 100nm using SIM

Gavin Symonds, Carl Zeiss

There are a number of imaging techniques that provide resolution below the diffraction limit of the optical microscope. However imaging of biological structures below 100nm, not only for fixed samples but especially for live cells, presents a number of challenges. These challenges include the choice of special fluorescent markers and sample chemistry, potentially high laser powers at the sample plane, and extended image acquisition times depending on the technique. Double the traditional SIM resolution is now possible with a new dual iterative processing method implemented as SIM^2. With this presentation we will briefly introduce the concept of SIM and SIM^2 processing, and show several examples.

A novel toolkit for the spatial analysis of multiplexed microscopy images

Dr Anna Trigos, Postdoctoral Researcher, Peter MacCallum Cancer Centre

Co-authors
Ms Yuzhou Feng, Peter MacCallum Cancer Centre
Mr Tianpei Yang, Peter MacCallum Cancer Centre
Ms Mabel Li, Peter MacCallum Cancer Centre
Mr Volkan Ozcoban,Peter MacCallum Cancer Centre
Dr Greg Bass, CSL Innovation Melbourne
Dr Simon Keam, Peter MacCallum Cancer Centre
Prof Rick Pearson, Peter MacCallum Cancer Centre
Dr David Goode, Peter MacCallum Cancer Centre
A/Prof Paul Neeson, Peter MacCallum Cancer Centre
A/Prof Shahneen Sandhu, Peter MacCallum Cancer Centre

Novel multiplexed microscopy technologies, such as OPAL, CODEX and MIBI, provide detail information about marker intensities and location of cells at single-cell resolution. These are rapidly gaining popularity and are likely to become commonplace. After image processing and cell segmentation, the resulting data generally includes the X, Y coordinates of hundreds of thousands of cells, cell phenotypes and marker levels. However, to date, the tools for the analysis of this downstream spatial data are largely underdeveloped, making us severely underpowered in our ability to perform quantitative and statistical spatial analyses.

We have developed SPIAT (Spatial Image Analysis of Tissues), an R package with a suite of data processing, quality control, visualisation, data handling and data analysis tools. SPIAT allows automated prediction of cell phenotypes without the need for manually defined thresholds, significantly reducing this time-consuming process. SPIAT also includes novel algorithms for the identification of cell clusters, cell gradients, the calculation of neighbourhood proportions and spatial statistics, as well as specialised algorithms to profile the immune microenvironment in cancer. SPIAT’s intuitive implementation makes it compatible with data generated from a diversity of platforms, including OPAL, CODEX and MIBI and derived with InForm, HALO, CellProfiler, among others. SPIAT is a user-friendly and time-efficient toolkit that is set to become a go-to package for spatial analysis.

SRRF ‘n’ TIRF - Simultaneous spatiotemporal super-resolution and multiparametric fluorescence microscopy

Professor Thorsten Wohland, National University of Singapore

The full description of biological systems requires the measurement of structure and dynamics. The quality of data depends on the signal to noise ratio and thus on the photons detected. However, good spatial resolution requires small pixels and thus longer exposure times for high photon counts. And good dynamics resolution requires fast measurements and thus larger pixels to obtain the required signal to noise ratio. Attempts in the past to combine the two, had limitations on instrumentation or labels. Here we combine computational super-resolution with imaging fluorescence correlation spectroscopy to obtain high spatiotemporal resolution with standard instrumentation and fluorescent proteins.

Super-resolution expansion microscopy

Professor Markus Sauer, University of Wurzberg, Germany

In the last decade, super-resolution microscopy has evolved as a very powerful method for sub-diffraction resolution fluorescence imaging of cells and structural investigations of cellular organelles. Super-resolution microscopy methods can now provide a spatial resolution that is well below the diffraction limit of light microscopy, enabling invaluable insights into the spatial organization of proteins in biological samples. However, current super-resolution measurements become error-prone below 25 nm. An alternative approach to bypass the diffraction limit and enable “super-resolution imaging” on standard fluorescence microscopes, is the physical expansion of the cellular structure of interest. By linking a protein of interest into a dense, cross-linked network of a swellable polyelectrolyte hydrogel, biological specimens can be physically expanded allowing ~70 nm lateral resolution by confocal laser scanning microscopy. Since its first introduction by Boyden and co-workers in 2015, expansion microscopy (ExM) has shown impressive results including the magnified visualization of pre- or post-expansion labeled proteins and RNAs with fluorescent proteins, antibodies, and oligonucleotides, respectively, in cells, tissues, and human clinical specimen. By combining ExM with single-molecule localization microscopy (SMLM) it is potentially possible to approach the resolution of electron microscopy. However, current attempts to combine both methods remained challenging because of protein and fluorophore loss during digestion or denaturation, gelation, and the incompatibility of expanded polyelectrolyte hydrogels with photoswitching buffers. Here we show that re-embedding of expanded hydrogels enables dSTORM imaging of expanded samples and demonstrate that post-labeling ExM resolves the current limitations of super-resolution microscopy. Using reference structures, neurons and brain slices, we demonstrate that post-labeling Ex-SMLM can be used advantageously for super-resolution imaging. It preserves ultrastructural details, improves the labeling efficiency and reduces the positional error arising from linking fluorophores into the gel thus paving the way for super-resolution imaging of immunolabeled endogenous proteins with true molecular resolution.

Adaptive Optics and Adaptive Illumination - Key Ingredients for 3D and Live cell STED superresolution

Carola Thoni, Lastek

Latest developments of Luxendo lightsheet in advancing Life Science applications

Zheng Chao, Scitech

In the past few years, light sheet microscopy has greatly expanded its use in biological research. Its unique advantage of capturing images of whole organisms and tissues in real time has brought researchers into an exciting new era. This discussion focusses on recent developments of lightsheet microscopy from Luxendo. Some of the exciting new developments including photo-manipulation module, TAG lens and MEMS module, Lattice lightsheet module as well as optimized big data processing algorithms. Brief introduction of the technologies, functionalities and applications will be presented in the workshop.

Livecyte- The Time dimension

Pete Davis, ATA Scientific

New Tools for 3D Micro Imaging and Analysis

Chunsong Yan, Olympus

There are many new developments emerging in light microscopy field. Olympus Australia is proud to be part of this journey and provide some of exciting solutions which may assist with your scientific research. I would like to take this fantastic opportunity provided by LMA 2021 organizers to share an overview of recently released products. There will be two amazing light sheet systems, a 3D cell analysis software and a smart 24/7 remote cell monitoring system.

Cleared Tissued lIghtsheet

Edward Lachica, 3i