iBIN - Challenge areas identified

Computational

• Develop mathematical models to interpret 3D imaging data and define collective behaviours
• Machine learning tools: Background noise removal and compensating for/tracking movement
• Quantitative analysis of shape changes in 3D volumes
• Unsupervised data acquisition – identification of features whilst imaging at different scales (AI); low resolution non-toxic to high resolution
• Developed software needs to be open source – use of online repositories (potentially through connection from IBIN hub website)

Probe Development

• Probes with long emission lifetimes to discriminate from background fluorescence. More excitation/emission wavelengths, improved QY/brightness, tuneable singlet/triplet coupling for improved blinking performance, low molecular weight and can be used in live cells
• Optogenetic probes (red/far-red) to trigger cell death/signalling in cell subpopulations
• New probes for STORM/PALM – especially for multi-colour imaging
• Need better lipid-specific dyes for live imaging and probes to image cell membrane curvature
•  Need long-term probes for tracking/imaging over multiple days for 3D samples
• Need tension sensor probes that are not protein specific
• A centralised way to share probes and knowledge (website links to pre-prints and white papers)

Super-Resolution

• Need standardisation/QC and ground truth tools, calibration slides and standard samples
• Finding ways to make STORM/PALM data easier to acquire/analyse from 3D samples
• New approaches to correlate super-resolution, AFM and EM datasets from same sample
• 3D Super-resolution: deep tissue (adaptive optics, multiphoton, optogenetics)
• Imaging exosomes in situ: ways to identify populations and characterise surface markers in 3D
• 3D Bioimaging Instrumentation
• Instrumentation and methods for rapid accurate spectral unmixing from multiple z-slices within 3D samples (≥300um)
• Combine label-free and label multimodal, compatible with live cell/tissues – eg: Spectral imaging, fluorescence lifetime, bioluminescence (luciferase), Raman and Brillouin etc.
• Single-cell optogenetic targeting in 3D (precision); needs to be low photon dose
• Improving resolution in 3D systems; eg: adaptive optics, 2-photon light sheet

3D Biomechanics

• Analysing relationships between cells and forces combined with functional imaging of signalling
• Reproducibility of 3D models: Hydrogels to incorporate native proteins, Control pore size/crosslink/stiffness and physical properties.
• Imaging of short-term mechanical events and longer-term cell fates
• Ways to image tension between cells and nuclear morphology changes in dense 3D cultures/tissues
• Cytoskeleton tension sensors to uncouple fluidity and tension