Automated Stem Cell Based High Throughput Drug Screening for ALS and Parkinson’s
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Hosted by: Brandy Sargent
Dr. Bruder began our interview by talking about the importance of using an iPS-based screening model and how this compares to other models, including animal models. He described the biggest challenge in neurodegenerative disease modeling as cell sourcing and he provides an explanation for this. Accessing diseased cells in neurodegenerative diseases means taking a portion of a patient’s brain, and not surprisingly, that is not a popular option. Another challenge is that in Parkinson’s Disease for example, dopaminergic neurons are dying and by the time one receives a diagnosis, there could be up to 80% dopaminergic neuron loss, making it very difficult to study the underlying disease mechanisms.
Even if researchers are able to access a sample from the biopsy of a Parkinson’s patient, neurons are post mitotic so the cells can’t be expanded in culture. Thus, you are not able to generate enough cells to really run meaningful experiments. Lastly, he talks about how a great deal of research has demonstrated that animal models don’t best mirror human physiology or biochemistry, particularly in neurological applications. He provides examples of drugs that have dropped out of clinical trials due to either lack of efficacy or toxicity. This is where the iPS cells provide such a great option as they circumvent the cell sourcing issue and allow the creation of disease models to explore questions about disease initiation, progression, and potential treatment.
He then went on to describe his group’s work on Parkinson’s Disease and creating an automated system for creating dopaminergic neurons and large compound screens against the disease. The first step for them was to generate an iPS line from patients that carry a gene mutation, which predisposes them to the disease. However, iPS cells are not really suitable as a starting point for an automated system as they require expensive growth factors and manual monitoring. It is possible, but not ideal. So, they developed a precursor cell type that is very proliferative and easy to maintain. Using these precursor cells, they can generate dopaminergic neurons in only two weeks. To automate the system they take the precursor cells that are in manual culture and transfer them to automated culture by moving them to their liquid handling system, the Beckman Coulter Biomek FXP automation workstation.
Over the course of two weeks they add differentiation factors then direct the cells to develop into dopaminergic neurons that carry a Parkinson’s disease mutation. However, they were surprised initially to find that generated neurons were healthy looking, when they expected them to be diseased. Yet, this made sense after some thought because Parkinson’s Disease does not affect people until they are 50-60 years old. So in order to make a functional disease model, they needed to artificially age the neurons.
Dr. Bruder then discussed the advantages of moving this type of work to automation. He stated three primary advantages:
- It allowed them to scale up the number of compounds they could test by a factor of 100.
- It reduced the cost because they could run using 384-well plates.
- It reduced the experimental error by standardizing the operation.
I then asked Dr. Bruder about what his automated workflow looked like and how it compared to previous methods. He described that previously they used a manual, larger format of 96- or 48-well plates. Even with automation they start the cells in manual culture to generate the precursor cells. The precursor cells are then moved to the Beckman Coulter Biomek FXP and 384-well plates where cell culture media is changed daily in the beginning, and every 2 days in later stages.
The screen is subdivided into several batches. Each batch has positive and negative control plates and a clear plate. The final readout is a luciferase readout, so they run the screen in white opaque plates, which is great because it boosts the luciferase signal, but also difficult because they can’t follow along with the cells. This is troublesome particularly during differentiation, thus the clear plate is included to allow them to track cell morphology. After two weeks they have dopaminergic neurons that they add the compounds to and let incubate for 24 hours. They then add the cellular stress and have it sit for 2 days. After this time, they evaluate the impact that the compound had on the cells.
They had to make many adjustments to get the process running smoothly. The biggest hurdle being that they begin with a hardy robust precursor cell, then after 2 weeks, they have a more sensitive and delicate cell type that needs different handling. They needed to create a system that would work for both the starting cell type and the ending cell type.
So far the results of their biochemical screens have shown that most of the compounds have no activity and quite a few were toxic, which is pretty typical in large compound screens. About 0.1% were beneficial with the best compound showing a boost in cell survival of up to 87% of the control.
Dr. Bruder then summarizes why this work could not have been done without using automation. One of the primary issues is that with a hit rate that is so low, many thousands of samples have to be run to get a hit, which would not be possible by hand. Another factor is if you aren’t able to scale down to at least the size of a 384-well format, the cost of running a screen this size and in this format would be too cost-prohibitive.
We then switched gears and discussed his work on ALS and Frontemporal Dementia (FTD). He described the link between the two diseases and the human cell-based system they created to screen for compounds relevant to ALS and FTD. They screened over 50,000 compounds using this model and found about 100 that significantly boosted cell survival. They are looking for funding and support to examine how these compounds work and if they work on the same or related pathways.
In closing, I asked Dr. Bruder if he had any advice for those who might be interested in developing an automated high throughput drug screening process for their disease of interest. He said that one must be patient and go into it with the knowledge that it won’t work right out of the box. There must be lots of trial and error to find what works best. This is why it is critical to have good support from the manufacturer to troubleshoot both hardware and software, and they have been lucky to have this support on the Biomek FXP from Beckman Coulter. He also recommended that one person be designated to handle the transfer from manual culture to automated culture. The reason being is that there are several lessons learned from just doing the work and if this is distributed among several people some of that is lost. At the end of the interview, Dr. Bruder wishes those looking to automate their system good luck and welcomes listeners to contact him with questions or to share ideas.
*This interview was conducted by telephone.