Research

The scientific objective of FLIMagin3D is to synergistically evolve key aspects in FLIM imaging across disciplines by advancing the acquisition of FLIM data and the analysis pipeline, by developing improved platforms that facilitate imaging for a wide range of (bio)medical, chemical and biophysical applications, and by advancing the state-of-the-art in FLIM biosensors. Through real-world biological and biomedical research lines across the partners we can showcase the validity and power of our developments and unify in streamlining FLIM as an accessible and robust tool.


This aim will be achieved by the following Research Objectives (RO):

RO.1 : To create, characterise, standardise and test cost-effective platforms adaptability to all of the various user communities, and to enhance existing imaging capabilities [Doctoral Candidates (DC)2, 6, 9]]

RO.2: Optimise the data acquisition and user-data interface whereby large amounts of data are quickly and correctly acquired, processed and interpreted under control of intelligent software [DCs 1, 7, 8, 10]

RO.3: Establish a library of tools to act as biosensors, perturbers (‘actuators’) and microenvironments to assess biological activities and processes, and interrogate such activity non-invasively and reproducibly. [DCs  3, 4,5, 10]

Project 1


Automated Machine Learning Pipeline to classify cell behaviour and phenotype based on endogenous and exogenous biosensor probes readouts

Project 2


Coordinated measurement of FLIM photonics with electrophysiological measurements and stimulation

Project 3


FLIM-assisted analysis of the intestinal organoid metabolism

Project 4


Sensing and manipulating hypoxia with innovative biosensing and tissue engineering tools

Project 5


Development of Isotropic lightsheet fluorescence lifetime imaging for 3D super-resolution 

Project 6


Rapid development of FRET sensors optimized for FLIM readouts of mechanobiological sensing and cellular response in imaging cancer

Project 7


Hypoxia versus tissue stiffness in blood vessel disease

Project 8


Computational prediction of the metabolic microenvironment in cancer models developed in vitro and ex vivo

Project 9


Mapping the O2 microenvironment, photosynthesis and respiratory activity in biofilms and 3D bioprinted constructs

Project 10


Pooled FLIM screening to efficiently elucidate cell signalling

Project 11


Imaging mechanobiological sensing and cellular response in cancer

Project 12


Development of Isotropic lightsheet fluorescence lifetime imaging for 3D super-resolution

Project 1


Project title:

Automated Machine Learning Pipeline to classify cell behaviour and phenotype based on endogenous and exogenous biosensor probes readouts

Objectives:

1) To train the DC in theory of python coding and application of appropriate machine learning approaches in preparing a classification algorithm based on multiparametric input and output data.

2) Apply machine learning classification to human macrophages stimulated towards two contrasting phenotypes DC will establish a semi-automated system whereby any data file containing FLIM data; (FLIM algorithm library that supports the most popular FLIM file formats and can be utilized and modified easily by a developer;) that will ultimately present as a intuitive FLIM analysis tool that uses the library and yet still can be used easily and directly by the bench biologist; and the integration of FLIM analysis with versatile microscopy image analysis.

3) While working on their own application (that being the model of macrophage polarisation); the DC will engage with other DCs in adjusting the pipeline to the analysis of data and additional sensor readouts.

Host Academic Institution: Trinity College Dublin

Project 2


Project title:

Coordinated measurement of FLIM photonics with electrophysiological measurements and stimulation

Objectives:

1) Transparent Microelectrode Arrays (tMEA) developed and commercialised by NMI (Reutlingen) capable of both stimulation and recording, will be adapted to the FLIM facility in TCD (and adapted to a design pipeline where its application to other system configurations can be achieved).

2) Experiments performed on 2D monolayer cultures and allow cell-specific electrophysiological recordings (and single cell FLIM imaging); whereby the two can be matched to an individual cell.

3) Similarly in 2D; co-culture of iPSC-derived cardiomyocytes with complimentary cell types (macrophages, endothelial cells, fibroblasts) will be performed to establish a system whereby one can uncover the impact of stimulation and cell re/de polarisation on adjacent cells.

4) Scale up to proof of concept 3D cardiomyocyte modelTo train the DC in theory of python coding and application of appropriate machine learning approaches in preparing a classification algorithm based on multiparametric input and output data.

Host Academic Institution: Trinity College Dublin

Project 3


Project title:

FLIM-assisted analysis of the intestinal organoid metabolism

Objectives:

The current analysis of the stem cell-derived organoid models is limited by the lack of visualisation tools for live analysis of cell metabolism, proliferation, differentiation and specific cell type labeling. We aim at developing

1) standardised set of biosensing tools (O2 probes, NAD(P)H-FLIM, biosensor scaffold materials)

2) their cross-validation and combining in a unified readout and a set of chosen growth / imaging media, and

3) using them to produce ‘cell type-specific atlas of cell bioenergetics’ in the intestinal organoids.

Host Academic Institution: Ghent University

Project 4


Project title:

Sensing and manipulating hypoxia with innovative biosensing and tissue engineering tools

Objectives:

Oxygen supply and tissue hypoxia are of paramount importance for tissue development, repair and recreating tumor microenvironment. The Dmitriev group and collaborators intend to address

1) development of innovative O2 sensing probes having shortened emission lifetimes (<1 us) compatible with fast-PLIM and widely available FLIM platforms, including multiphoton FLIM and PLIM. Such probes will be modified and produced in biocompatible form, to address their applications in intracellular and extracellular (ECM-associated) sensing modes. In addition, expanded biocompatibility with 3D models of microbial biofilms, aquatic organisms and interspecies communities are sought.

2) While  ‘sensing’ and mapping cell and microtissue oxygenation and their gradients, it is intended to explore use of ‘active’ oxygen-binding proteins, enabling microfabrication of O2 gradients in 3D cultures, organoids and ‘assembloids’

Host Academic Institution: Ghent University

Project 5


Project title:

Development of Isotropic lightsheet fluorescence lifetime imaging for 3D super-resolution 

Objectives:

1) Together with associate partners at KCL- develop an isotropic resolution 3D imaging platform for fluorescence lifetime imaging (ISO-FLIM) to visualise fast molecular dynamics associated with cardiomyocyte function within live bioengineered human pluripotent stem cell (hPSC) derived cardiomyocyte cultures-  acquire quantitative fluorescence imaging data from live stem-cell derived cardiomyocytes in 3D cultures with a massively parallel video-rate multifocal multiphoton system for fluorescence lifetime imaging employing a truly isotropic light-sheet modality.

2) With this new imaging platform we will acquisition quantitative data on calcium, voltage, ATP metabolism and any other fast-changing dynamic process that directly affects neuronal activity, within live cells through simultaneous imaging of physiologically relevant volumes.

Host Academic Institution: Trinity College Dublin

Project 6


Project title:

Rapid development of FRET sensors optimized for FLIM readouts of mechanobiological sensing and cellular response in imaging cancer

Objectives:

With only very few exceptions, FRET sensors have been tediously optimized to display an optimal change in ratio of intensities, which typically takes several years of trial-and-error mutations and rigorous testing. To be able to employ those sensors with our quantitative FLIM technology, we thus aim to develop an approach to convert good ratiosensors to good FLIM sensors without engaging in new and tedious characterization.  Unpublished work (straight-forward biophysical experiments using FLIM and FCCS experimentation by NKI partner) has yielded important clues as to the cause of this paradox. Based on these insights, NKI have developed a simple (undisclosed) strategy to convert (the majority of the) well-characterized  ratio-FRET sensors into good FLIM sensors.

1) Compare, characterize the two showcase converted sensors recently validated in the Kalink Lab. Y1.

2) Extend the set of FLIM-optimized sensors using a selection of 5-10 ratiosensors rationalised from literature.

3) Collaborate with others in showcasing the efficacy of new FLIM sensors in screening experiments and/or in cell biological experiments. 

4) implementation and multiplexing of FLIM-based sensors to probe membrane tension, mechanoresponsive protein activation and biochemical signals in cells within 3D scaffolds of tuned stiffness and e) cross correlate this with phenotypic endpoints and

5) define metabolic changes associated with these force transmission events for further investigation as mechano-sensitive drivers of tumour progression. We will use 3D cultures and organoids from breast and head & neck cancers to explore these parameters. These models will enable in situ monitoring of how manipulation of mediators of biomechanical signalling affect cell phenotypes and drug-induced cell toxicity. The DC will first establish a model of cancer in a microwell chamber adapted to the FLIM imaging platform (in collaboration with DC8) and team up with DC1 in the multiplexed data modelling using a Machine Learning approach towards classification of drug induced responses. 

Host Academic Institution: Ghent University

Project 7


Project title:

Hypoxia versus tissue stiffness in blood vessel disease

Objectives:

Hypoxic conditions in blood vessels as well as alterations in tissue stiffness can impact the contractility of smooth muscle cells (SMCs). To resolve mechanobiological effects and tensional states on the single cells level, our team and collaborators will establish a platform and readout modalities for simultaneous assessment of cellular metabolism and mechanobiology. This will include

1) the implementation of a microfluidic platform for 3D cell culture of vascular cells (SMCs, microvascular endothelial cells), integrating microelectrode arrays (MEA) for electrophysiological stimulation on our FLIM system.

2) The simulation of healthy and hypoxic conditions in the 3D vascular model and evaluation by FLIM microscopy. FLIM-based oxygen sensing and FLIM-FRET tension sensing of intracellular mechanobiology (e.g. vinculin, nesprin) will be established in correlation to electrophysiological stimulation. Additional analyses will include Calcium and Raman imaging. And

3) the data generation, establishment of correlative analytical approaches and proof-of-concept studies on pathophysiological in vitro models: an aneurysm (decreased stiffness) and an atherosclerosis scenario (increased stiffness and integration of immune/foam cells) will be established and investigated with the developed tools.

Host Academic Institution: Eberhard Karls University Tubingen

Project 8


Project title:

Computational prediction of the metabolic microenvironment in cancer models developed in vitro and ex vivo

Objectives:

Predict the mechanical and mass transport field variables to which any cells are subjected during culture in (in this particular model- 3D cancer models) developed in vitro and implanted in embryonated avian eggs.

1) in silico modelling to accurately predict the concentration of soluble signals, nutrients, and metabolic by-products within the cell microenvironment in advanced cell models of breast and ovarian cancer, based on 3D cellularised scaffolds maintained in perfused culture in a bioreactor and/or

2) implanted in the chorioallantoic membrane (CAM) of embryonated avian eggs. c) set-up of computational models of 3D cell micro environments based on 3D reconstructions of the construct geometry obtained from fluorescence time-lapse/z-stack confocal microscopy images acquired intravitally through imaging windows. We plan to set the main simulation parameters based on actual measurements. For example, we will measure in vitro the consumption coefficients of solutes and gases for the cell populations involved, to accurately predict cell consumption as a function of the cell density quantified intravitally.

Host Academic Institution: Politecnico di Milano

Project 9


Project title:

Mapping the O2 microenvironment, photosynthesis and respiratory activity in biofilms and 3D bioprinted constructs

Objectives:

3D mapping of the chemical microenvironment in microbial biofilms remains a major challenge to our understanding of this most common microbial lifestyle. Our team and collaborators will develop new experimental platforms for

1) the application of O2 sensing probes compatible with PLIM and FLIM platforms in biofilms,

2) the incorporation of such sensing probes within functionalized bioinks, and

3) realizing 3D mapping of O2 and biomass in natural and bioprinted biofilms containing phototrophic and heterotrophic microbes. Together with collaborators, we will also explore imaging of NAD(P)H and develop computational models for O2 dynamics and distribution in such structures.

Host Academic Institution: University of Copenhagen

Project 10


Project title:

Pooled FLIM screening to efficiently elucidate cell signalling

Objectives:

1) In a pooled screening concept, we will use (existing) viral CRISPR gene knockout libraries to effectively knock down one single gene per cell in a large population of cells. This results in a mix of ~ 21,000 knockdown cells representing all genes (except for the lethal ones). We have shown that using the new FLIM instrumentation we can perform dynamic screens at ~150,000 cells in parallel on a single coverslip, and we developed technology to analyse signals and pick out individual hits (cells with an aberrant phenotype) within a single afternoon. Thus, a 100-fold covering of the entire genome should be feasible within 1-2 weeks already, and this may be further optimized.  

2) Given the vast amount of data generated using this screen we will use innovate machine learning algorithms to classify knockouts in a step-wise and logical sequence c) Focusing initially on the cAMP response signalling cascade; we will rank the machine learning parameters according to their statistical weightings and delineate specific pathways using conventional cell biological methods.

Host Academic Institution: Netherlands Cancer Institute

Project 11


Project title:

Imaging mechanobiological sensing and cellular response in cancer

Objectives:

1) implementation and multiplexing of FLIM-based sensors to probe membrane tension, mechanoresponsive protein activation and biochemical signals in cells within 3D scaffolds of tuned stiffness and

2) cross correlate this with phenotypic endpoints and

3) define metabolic changes associated with these force transmission events for further investigation as mechano-sensitive drivers of tumour progression. We will use 3D cultures and organoids from breast and head & neck cancers to explore these parameters. These models will enable in situ monitoring of how manipulation of mediators of biomechanical signalling affect cell phenotypes and drug induced cell toxicity.

The DC will first establish the model of cancer in a microwell chamber adapted to the FLIM imaging platform (in collaboration with DC8) and team up with DC1 in the multiplexed data modelling using a Machine Learning approach towards classification of drug induced responses.

Host Academic Institution: King’s College London

Project 12


Project title:

Development of Isotropic lightsheet fluorescence lifetime imaging for 3D super-resolution

Objectives:

1) develop an isotropic resolution 3D imaging platform for fluorescence lifetime imaging (ISO-FLIM) to visualise fast molecular dynamics associated with neuronal activity within live bioengineered human pluripotent stem cell (hPSC) derived neural cultures- acquire quantitative fluorescence imaging data from live stem-cell derived neurons in 3D cultures with a massively parallel video-rate multifocal multiphoton system for fluorescence lifetime imaging employing a truly isotropic light-sheet modality.

2) With this new imaging platform we will acquisition quantitative data on calcium, voltage, ATP metabolism and any other fast-changing dynamic process that directly affects neuronal activity, within live cells through simultaneous imaging of physiologically relevant volumes.

Host Academic Institution: King’s College London