Find out how artificially cultivated human brain organoids and AI-backed image analysis software can facilitate the study of Alzheimer’s disease. According to WHO the incidence of neurodegenerative disorders such as Alzheimer’s and dementia has been on the rise due to the general ageing of the world population and the wide-spread adoption of unhealthy lifestyles.
The spread of neurological brain diseases inflicts a massive burden on global healthcare systems. Recent advances in computer-assisted technology for the study of neurodegeneration shed new light on biochemical processes associated with Alzheimer. Particularly the automated analysis of image data gathered from artificially cultivated cerebral organoids promises great potential. We joined efforts with brain organoids technology provider NORGANOID to explore innovative methods to utilize engineered organoid tissue and artificial intelligence applications in neuroscience research.
This article throws light on our joint research project with the goal to develop an innovative app for the quantification of pathological processes Alzheimer’s disease related simulated with the help of brain organoids.
A strategic collaboration in brain organoid applications
In 2020 we brought a project funded by the DIGI-B-CUBE (EU Horizon 2020) initiative with the title OSQAM* to life. OSQAM* signifies “Online Service for quality monitoring of 3D-Brain-on-Chip and Alzheimer’s Disease Model.” The OSQAM-project combines our know-how in microscopy image analysis with NORGANOID’s expertise in culturing cerebral organoids.
Our collaboration partner on the project, NORGANOID, is an innovative organoids technology company. Their state-of-the-art platform supports studies in the field of neurodegenerative diseases and makes complex organoid assays and drug discovery possible.
NORGANOID founder and CEO Charlotte Ohonin is a household name in the field of organoids development. She has already supported a number of life science publications with her expertise in organoid technology.
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What are brain organoids?
Organoids are three-dimensional multicellular models that mimic the structures of human organ tissue and its microenvironment. Microfluidic technology makes use of organoid tissue in order to explore complex biological and biochemical dynamics within the artificial cell culture.
Microfluidic systems rely on the flow of different media like fluid or gas within the microenvironment of organoid culture. This process is invented to simulate the mechanism of interstitial flow between cells and their biochemical environment in real human tissue. In this way microfluidic systems find important applications in in vitro research, medical diagnostics, therapeutic studies and drug testing.
Cerebral organoids represent engineered mini brain models derived from pluripotent stem cells (iPSCs). The pluripotent stem cell culture used in the process are manipulated to develop into human brain-like structures. At the same time the fluid flow in the system simulates chemical transport processes within real human cerebral tissue.
The simplest artificial neural cell constructs are known as neurospheroids. Neural and cortical spheroids are 3D structures derived from stem cells that resemble human brain cells. Neurospheroids can form a simple neuronal network and interact with each other at touching points resembling synapses in a similar way real human brain cells do.
Modeling neurological diseases with human brain organoids
Brain organoids facilitate the in vitro study of pathological processes associated with neurodegenerative diseases such as Alzheimer’s on artificial brain cell culture. The organoid model is able to simulate specific structural and functional changes related to neurological brain disorders.
Although most prior research has been conducted using animal models, those have not always proven effective. Animal brains do not completely resemble human brains. For example most mammalian brains do not generate amyloid and tau proteins associated with the development of Alzheimer. A human brain organoid model simulates molecular processes associated with Alzeheimer’s disease pathology like the aggregation of amyloid and tau protein as well as abnormalities in endosomes.
Cerebral organoid cultures provide an invaluable in vitro method to investigate brain disorders while alleviating sampling and ethical issues associated with studies on real human brain cell culture.
So far modeling of neurodegeneration with the help of organoids has been conducted for different types of conditions: Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, autism, Zika virus infection and Creutzfeldt-Jakob disease.
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AI-algorithms provide for more efficiency in brain organoid image analysis
Automated software solutions enable the quantification and patterning of data derived from brain organoid models. These applications extract information about the cell count, cell size, cell shape, cell density and dynamics within the cerebral model.
Within organoid cell culture tiny particles known as microfluidic droplets are used to encapsulate iPSCs. Microfluidic droplets and bubbles can be easily quantified with the help of advanced microscopy image analysis software.
Powerful AI-algorithms provide invaluable tools for the automated, fast, precise and reproducible analysis of data generated with brain organoid structures on an easily accessible user interface.
The OSQAM-project focuses on the development of state-of-the-art deep learning algorithms for the detection, segmentation and classification of microfluidic particles occurring during the process of brain organoid culturing. A special emphasis is set on developing automated applications for the qualification of microfluidic droplets, bubbles and cell aggregates.
Our algorithms are intended to enable the visual segmentation of particular regions within organoid cell culture. The smart applications at work allow for the detection of microfluidic particles and their subsequent classification into categories such as “droplets,” “imperfect droplets” and “air bubbles.” In addition to that information the circularity i.e. the roundness of those objects can be derived.
Insights into a successful cooperation
Our collaboration with NORGANOID brought instruments to life intended to sustainably support neurodegenerative disease research. Our experts, DDr. Michael Mayrhofer, Project Manager, KML Vision GmbH and Charlotte Ohonin, Founder & CEO of NORGANOID provide answers on the use of AI-driven software tools in brain organoid image analysis.
Question: What is the relevance of the tools developed as part of the OSQAM-project for brain organoid research practice?
Mayrhofer: “We have been able to show that central quality factors during the organoid engineering process that are widely used in medical research can be precisely and efficiently tracked with the help of automated image analysis software. In this way therapies and medications for dementia and Alzheimer’s disease can be more easily and efficiently explored.”
Ohonin: “The quality assessment of engineered tissue is enormously important when the latter is used for drug screening. Within the project we concentrated mainly on morphological properties, though our technology can be applied to a wide range of physiological and molecular biology analyses. With this method all sorts of chemical and biochemical active substances can potentially be tested on different issue types”, stresses
Question: What challenges did you face with the OSQAM-project?
Mayrhofer:“One of the biggest challenges was surely the development of an algorithm capable of analyzing full image stacks, i.e. images showing the same brain organoid regions from different focus plans.”
Ohonin: “The pandemic did not make the project implementation easy for us. We had to deal with delays in delivery and access to relevant infrastructure was also limited.”
In the future, NORGANOID intents to commercialize an autonomous microfluidic system for the derivation of human organoids.
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*Disclaimer:
The content of this document represents the view of the author only and is his/her sole responsibility: it cannot be considered to reflect the views of the European Commission and/or the Executive Agency for Small and medium-size Enterprises (EASME). The European Commission and the Agency do not accept responsibility for the use that may be made of the information it contains.
*This project has received funding from DIGI-B-CUBE voucher framework which has been supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 824920.
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