Generating induced pluripotent stem cells (IPSCs) is a laborious and time consuming process--and so is studying each line individually.
What if you could monitor hundreds of them in real time?
That's one of the things that Kamal Garcha of the Center for Commercialization of Regenerative Medicine in Toronto wants his group to be able to do.
And Nikon Instruments is providing his team with a fascinating all-in-one cell incubator and scanning device to make it happen.
Garcha, who holds a PhD in Cellular and Physiological Sciences from the University of British Columbia, is Director of Cell Reprogramming and Engineering at CCRM, one of the center's three core platforms (the other two are Biomaterials and Devices, and Cell Manufacturing).
"We generate cells for the academic community," he told me in an interview by phone. "Derived from patients, non-diseased cells, so they can be skin cells, fibroblasts, other tissues such as bone marrow stromal cells, and even peripheral blood samples."
Garcha takes those mature cells and turns back the clock, in the now standard method for generating iPSCs, by using reprogramming 'cocktails' --made of four genes that are overexpressed.
"The iPSCs end up resembling and functioning like embryonic stem cells," he said, "but without the moral or ethical concern that embryonic stem cells have. So, that's the first phase to generate pluripotent cells.
"But what we're also working on is generating cell lines that are instructive research tools that will report on the status of the iPSCs, so when we're making tissues out of these cells--and that's where the benefit of these cells is found--we can make personalized tissue constructs from them."
Tissue-specific lineages to better model diseases in a dish
The idea is, find a group of people who suffer from the same disease, for example Alzheimer's or Parkinson's, generate iPS cells from their skin or other tissue cells--then differentiate them into the target tissue. If it's Alzheimers, it will be neurons, where the disease manifests itself.
You can then study the differences between these diseased neurons and the neurons generated from the stem cells of people who don't suffer from the condition.
The goal, Garcha explained, is to better understand how to make predictive models of disease. "And that's where the iPSCs are best suited: modeling diseases at a personal level."
"The advantage is that you can obtain a sample from any person, and you can turn it into any tissue type. What we want to do is to have a better way to understand what happens to these cells in response to genes, or to drugs, or--in the case of disease--what happens to tissues when you have a defective gene in these cells."
Enter the Nikon BioStation CT.
From the outside, the device looks a little like a vending machine with a really cool touchscreen and no windows. But it's an incubator, carefully maintaining temperature, humidity, carbon dioxide and oxygen levels for the cell cultures it is designed to house within.
A tall, tower shaped carousel stands on one side of the machine's interior, consisting of racks that can house the cassettes of wells in which individual cell studies, or assays, are held. A cassette can hold from as few as 12 wells to as many as 96.
A robotic arm removes one cassette from the tower at a time, slides it smoothly over to the scanning station on the other side of the BioStation's interior, where the wells can be viewed from above and below.
"The Nikon has a camera that provides an overview of the plate, so you can see what the plate looks like," said Garcha, "but there's a converted microscope built-in so the the lenses are actually beneath the plate."
The microscope will center the plate, depending on the format (e.g., whether it's a 96-well plate, or a 12-well plate), and then perform a patterned scan throughout the plate to identify events or cells individually.
"So, if you're interested in the entire well, it will spend a longer period of time observing the cells within that well," said Garcha. "If we give it a specific number, for example if we tell it to look at the middle and then the sides of the well, it will automatically do that."
But the microscope can also stage through and track cells over time. "So, if we have a unique event that's occurring, we can specify in the software that this is a cell that's of interest, and it will monitor that cell over a period we specify.
"It's not just a static platform and you have to tell it exactly where something is."
Because in biology, he added, rarely are things where you predict them to be. "The BioStation will find the events for you; it will do a scan throughout the well and it will capture everything within that well."
And it will do it automatically for multiple plates. "Simply by specifying in the software what cells or what wells you want to image, the BioStation will automatically step through them over the specified period of time you tell it to. It's not just end-point analysis when the cells are fixed or they've been stripped apart to look at the genes inside these cells. We can actually monitor these in real time."
Optical power to look at experiments with higher resolution
"Normally, we have people who will sit down with a plate of cells on a microscope and look at each individual well," said Garcha. "But after a while, how much work can you get out of a scientist in a given day? What this machine allows us to do is work around the clock to address the question: how many wells can you look at?"
They can also monitor the process remotely from a laptop in the office or home
"Rather than opening the machine and looking inside it, what we can do is monitor it remotely," said Garcha. "Being in a facility like ours, we have approximately 6,000 square feet here, the offices may be some distance from the equipment. And what we want to do is eliminate the need for people to check up on the experiment itself.
"It's the middle of the night and someone wants to determine how their experiment's going, they can go online and determine how this is actually performing. So it eliminates that need to physically walk over and take a look inside."
Given that, quite often, you change the environment in which the cells are growing when you open the door, he added, this is another advantage.
The BioStation CT includes a customized software program that Nikon has built into the platform (called the CL-Quant Analysis). "It's a learning software where you teach the computer as you go," said Garcha.
A major advantage for CCRM's partnership with Nikon: Garcha and his team can help the programmers determine how upgrades to the software can directly address questions and problems that arise as the researchers get deeper into their use of the BioStation.
For example: Every data file or image is time-stamped, with a certain amount of metadata with each file. The images are collected and stored in a database, and as the algorithms are developed for new tasks, the researchers can go back and re-analyze sets of images they've already acquired.
The CCRM's BioStation is expected to be delivered next week. And Garcha is excited.
"This is a unique opportunity to pair with a manufacturer in which we can use their device not just for internal quality control and validation experiments, but we can also work with their software engineers to develop unique program packages or algorithms that will help us better understand the biology behind different views or differentiation of cells to certain tissue lineages."
It's too soon to say, perhaps, because this technology is so new. And I've only had a peek at an older model in action.
But the question arises: although it is certainly powerful and practically quite useful, whenever automation is introduced into research you can't help wondering about the things that a machine will inevitably miss.
Even with teachable software.
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