Whole Slide Imaging (WSI) and Region of Interest (ROI)

Most folks have used a conventional microscope at some point in their life to view specimens on a glass slide, prepared either in their native state or stained using a variety of methods to help identify different structures within the sample. Over the past several decades, there has been a shift in the way microscopy samples are viewed. Physical slides are now being transformed into digital images using whole slide imaging (WSI). The digitized format provides a resource that is easily shared for a wide range of uses, such as educational aids for scientists and physicians, research tools for academia and industry, and for diagnostic purposes in pathology and clinical medicine.

The specimens come from a wide spectrum of sources that are just as varied as the methods in which they are prepared on the slides. Physical slides can contain a single or several tissue sections, cell types, organisms or structures from both related and unrelated sources. Whole slide imaging is meant to capture the entirety of the slide so as not to miss any important samples that may be present. However, there is a cost to imaging such large areas, especially when higher magnification objectives are used for increased resolution. Of primary concern is the large amount of data that is generated, given that many samples require several images per field of view to capture all of the colors that may represent the true visual aspects of a sample.

Recent advances in imaging instrumentation can help to alleviate the need to image an entire slide at high magnification to capture the detail needed for analysis. The recent launch of the Cytation™ 7 by BioTek Instruments provides a method to rapidly image a whole slide or part of a slide to determine the region(s) of interest (ROIs).

Once the ROI selection(s) is made (as shown outlined in green above), subsequent imaging of those particular regions at a higher resolution and/or with more complex imaging methods, such as fluorescence imaging, high contrast brightfield, phase contrast or color brightfield, can be performed using automated methods as seen below.

The image below shows a ROI of cardiac tissue (tissue section on the left in the above image) imaged at 10x with one individual tile shown in an exploded view.

The combination of an upright microscope and inverted fluorescence microscope in a single instrument provides a unique opportunity for users to determine the most important areas to image, using more sophisticated, automated imaging techniques while saving valuable time and data storage resources.

By: BioTek Instruments, Peter J. Brescia Jr., MSc, MBA

Monarch butterfly: A Beautiful Creature That Feasts on Poison

A recent Facebook post by a work colleague regarding his son being a budding scientist caught my attention. The two of them had found a Monarch butterfly wing in their yard and were looking at it under a microscope.

Figure 1.  Female Monarch butterfly.

The Monarch butterfly (Danaus plexippus) is certainly one of the most beautiful of all butterflies and as its name suggests, is considered the king of the butterflies by many. As with all insects, Monarch butterflies go through four stages during one life cycle. The four stages of the Monarch butterfly life cycle are the egg, the larvae (caterpillar), the pupa (chrysalis), and the adult butterfly.

Figure 2.  Life cycle stages of the Monarch butterfly. (Composite of images provided by Wikipedia.)

At the start, the eggs are laid on milkweed plants. They hatch into baby caterpillars, also called the larvae. It takes about four days for the eggs to hatch. Then the baby caterpillar doesn’t do much more than eat the milkweed in order to grow. After about two weeks, the caterpillar will be fully-grown and find a place to attach itself so that it can start the process of metamorphosis. It will attach itself to a stem or a leaf using silk and transform into a chrysalis. Over the 10 days of the chrysalis phase, the body parts of the caterpillar undergo a remarkable transformation, called metamorphosis, to become the beautiful parts of the butterfly. The Monarch butterfly will emerge from the chrysalis and fly away, feeding on flowers for its remaining short life of about two to six weeks.

When I was child, it was fascinating to capture a few Monarch caterpillars from milkweed plants and watch them form a chrysalis and eventually turn into a butterfly. The observations took place at home or in the school classroom.

Figure 3. Milkweed (Asclepias syriaca) showing flowers and latex. (Courtesy of Wikipedia)

The interesting point of this is that milkweed (Asclepias), which the larva (caterpillar) feeds on exclusively is quite toxic. Asclepias is a genus of perennial flowering plants known as milkweeds, named for their latex, a milky substance containing cardiac glycosides termed cardenolides, exuded where cells are damaged. Cardiac glycosides affect the sodium (Na+/K+-ATPase) pump of cells. Sodium ion pumps create ion imbalances in cells critical for cardiac and nerve cell function. These are the type of compounds that Agatha Christie featured in a number of her murder mysteries such as Herb of Death, Postern of Fate, and Appointment with Death. Milkweed should kill the caterpillar, but it doesn’t. In fact, the caterpillars store the toxins in their bodies as a defense mechanism against birds that would like to eat them. The bright orange coloring of their wings is actually an “Unsafe to eat” message to animals. So what should kill them actually makes them stronger; the question is how? In a recent article in Nature, researchers used genome editing to retrace the evolution of toxin resistance in the Monarch butterfly. It turns out that only three gene mutations are necessary. These involve amino acid changes at position 111, 119, and 122 of the ATPα subunit of the Na+/K+-ATPase pump. These gene mutations did not occur at once, but rather developed sequentially. Using CRISPR/Cas-9 to edit genes, the group was actually able to make Drosophila fruit flies resistant to milkweed. Studies showed that the mutant flies were 1000 times more resistant to milkweed than the wild type. Using fruit flies, biologists found that these adaptive mutations are not without a cost. It turns out that these mutations had to occur in a specific order. The first mutation, while altering the structure of the pump and conferring some resistance to milkweed also causes neurological problems. The second mutation amended the pump slightly and fixed the neurological problem. This allowed the last mutation, which confers most of the milkweed resistance. The third mutation alone resulted in intolerable neurological seizure issues. Only with the second mutation, would the neurological issues with the third mutation be alleviated.

Figure 4.  The budding scientist at work in his lab.

Oh, back to the budding scientist. His Dad works with me at BioTek, where we manufacture a wide variety of research instrumentation including automated microscopes and imagers, and the software necessary to capture and process image files. He is also a camera buff who is obviously sharing his passion with his son. They managed to take a number of microscopic images of the Monarch butterfly wing, and using BioTek’s Gen5™ software, stitched the individual images into an amazing composite. You can see their work in Figure 5. I think he has a future in science!

Figure 5.   Composite stitched image of wing cells from a Monarch butterfly wing using Gen5. 

By: BioTek Instruments, Paul Held PhD, Laboratory Manager

Laser Focused and Then Some

When most people hear the word “laser”,  they think of sci-fi thrillers such as Star Wars,  with its hand- held laser blasters, but Albert Einstein proposed the idea of a laser over 100 years ago. Einstein based his theory of stimulated light emission on fundamental physics, more specifically quantum theory. Having recently shown that light was derived of packets of energy (photons), Einstein postulated that if the atoms making up the material are provided with excess energy, individual excited atoms emitting photons could stimulate other excited atoms nearby to do the same. As a result, all photons will have equal energy and move off in the same direction. While the theory was sound, it would take decades before suitable technology was available that would allow the idea to be put into practice. Ultimately, it was shown that when a material is pumped with energy in a mirrored cavity, photons bounce back and forth amplifying the emission of photons. The photons were then allowed to escape through a transparent section in the mirrored surface as a laser beam. Charles Townes at Columbia University produced the first device proving the theory in 1953. The device was capable of amplifying microwaves and was coined the maser.

Tatoute. 2006. Wikipedia.

In 1960, Theodore Maiman, at the Hughes Research Labs in California, produced the first visible-light laser with ruby as the laser medium. However, at this time the laser had few applications,  as did many discoveries stemming from basic research. This was to change toward the  end of the 20th century,  as laser research saw a large expansion and development of high-powered gas, chemical and semiconductor-based lasers. It was not until the development of a laser that worked at room temperature with little or no cooling, that the first widespread use outside of research was realized, in the form of  the compact disk (CD). Today most lasers are of the semiconductor diode type and found throughout industry as well as consumer products of all types. Many lasers have been adapted for biological and biomedical applications ranging from basic research to medical procedures.

Demonstration of a Helium-Neon laser at the Kastler-Brossel Laboratory in Paris. Monniaux, D. 2004. Wikipedia.

Over the past several years, BioTek has implemented lasers in several instruments. The first  was a 680 nm semiconductor laser incorporated into the Synergy Neo for use with PerkinElmer AlphaScreen® technology. BioTek then incorporated a red semiconductor laser as a rapid focusing method during image acquisition for our Cytation™ and Lionheart™ product lines. Most recently, a nitrogen laser operating a 337 nm is an option for the Synergy™ Neo2 Hybrid Multi-Mode Reader
for peak TR-FRET performance. The laser produces approximately 6x more energy than a xenon flash lamp at that wavelength and can flash approximately 2x faster. This results in ideal performance for high throughput screening where both sensitivity and high sample throughput are required. Typical assays include GPCR, kinase, biomarker and cytokine assays using technologies such as Cisbio HTRF®, LanthaScreen™, DELFIA® and LANCE®.

BioTek Instruments, Inc. Synergy Neo2 w/ laser module.

Learn more about BioTek’s patented Laser Autofocus utilized in the Lionheart Automated Microscope and Cytation Cell Imaging Readers.

By: BioTek Instruments, Peter J. Brescia Jr., MSc, MBA

Scratch Assay Starter Kit: Simplifying and Streamlining the Wound Healing Assay

Cell migration is a fundamental biological process important for normal tissue development and pathological processes such as wound healing, tissue repair, and cancer metastasis. Migrating cells undergo coordinated changes in shape and size via carefully orchestrated polymerization and depolymerization of cytoskeletal components. This dramatic rearrangement of cellular components generates motile force and establishes directionality to move the cell along toward its destination. With so many moving parts and biochemical pathways involved, keeping track of the details quickly becomes overwhelming. To model cell migration in vitro, scientists use the well-known scratch assay to measure, probe, and characterize this phenomenon in pursuit of medical research and drug discovery. At first glance the scratch assay is simple; a confluent cell monolayer is physically scraped to leave a gap or wound that the remaining cells can migrate into and “heal”. Look closer though and it is easy to quickly get lost in the details. Whether it is generating uniform and consistent scratches, acquiring high-quality time lapse images, or processing and analyzing images in a robust and objective way, there are many opportunities to introduce variability and prevent accurate quantification.

That’s where BioTek’s Scratch Assay Starter Kit comes in. Consisting of the AutoScratch Wound Making Tool, the Scratch Assay App software, and the necessary cleaning reagents, this kit provides a simple workflow to automate and analyze your scratch assay experiments. At the push of a button, the AutoScratch generates consistent, 800 micron wide scratches in 24-well or 96-well microplates. After scratching, move your plate to a BioTek imager and use the Scratch Assay App to automatically acquire time lapse images of each of your scratches and apply an optimized image analysis. Wound closure rates are tracked and graphed automatically; the healing process is easily visualized with time lapse movies. The Scratch Assay Starter Kit streamlines and automates your assays to increase throughput and ensure reproducibility and accuracy. This lets you focus on the complex biology of cell migration without getting bogged down by data collection and analysis.

Watch BioTek's Webinar on Demand:
A fully automated solution for conducting cell migration assays using the AutoScratch Wound Making Tool
Presenter: Joe Clayton, PhD., Principal Scientist

By: BioTek Instruments, Michael Sfregola, Product Specialist, Imaging

Black Holes: From the Abstract to Reality

I am a cell biologist at BioTek Instruments, where we manufacture a variety of research instrumentation, some of which are digital microscopes. Like many scientists, I’m also a geek that is interested in fields of science other than my area of research, astronomy for example. One thing about astronomy that has fascinated me is that images of stars in space and cultured cells on a slide look very similar. With astronomy, very large objects (stars) are imaged from very far away. As such, they appear really small and need to be magnified in order to see them. With microscopy, things are very close; the objects are very small and need to be magnified to be seen. Both project as bright objects on a dark background.

Figure 1. NIH3T3 Mouse fibroblasts expressing GFP.

Then just a few days ago the first images of a black hole was released. Black holes are one of those things you always read about in science fiction novels or see in SciFi movies or shows, not on the front page news. I’m not going to lie; my first thought was it looked like the eye of Sauron in the movie adaptation of The Lord of the Rings.

Figure 2. Image from the Event Horizon Telescope showing the supermassive black hole in the elliptical galaxy M87, surrounded by superheated material. (EHT Collaboration)

Certainly this is a watershed moment for physics, but it took years of work and the collaboration of hundreds of scientists to make it happen. It also required about half a ton of hard drives. Yes, 1000 pounds of computer hard drives. This is another example of the similarity between microscopy and astronomy - data storage requirements. Before I started working with digital microscopes, my experiments required very little data storage. With digital microscopy, I quickly needed a 1Tb hard drive for my PC, then a 4Tb drive, then a 10Tb drive. Currently, I use a 110 Tb RAID array, but soon that won’t be large enough!

Data collection for the historic black hole image began in 2017 with a coordinated effort called the Event Horizon Telescope (EHT), which is a collection of seven radio telescopes from around the world that are linked to combine the capacity of all those telescopes, creating a “virtual” telescope the size of the Earth.

The now-famous image of a black hole comes from data collected over a period of seven days. At the end of that observation, the EHT didn’t have an image — it had a mountain of data. Scientists at MIT had to develop algorithms to take 5 Petabytes of data and make sense of it. That’s 5000 Terabytes!

While not on the same scale, BioTek Instruments provides Gen5™ as a software tool to combine, process and analyze microscopy images for biomedical research. In the end we hope to provide the tools that our customers need to solve their scientific questions in the microscopic world, but we still salute the cosmic success of MIT and the EHT team.


By: BioTek Instruments, Paul Held PhD, Laboratory Manager

Win Cash, or Better Yet, Bragging Rights! Enter BioTek’s 2019 Imaging Competition

If you've been following us for a while, you probably remember that last year we kicked off our 1st annual Imaging Competition called Imaging Perspectives. Researchers from around the world submitted images captured with their Cytation or Lionheart for a chance to win cash prizes and have their image featured in BioTek's annual wall calendar. Well, the competition proved a success! We loved seeing all of the images and learning about the various applications customers are running with their instruments. So much so that we decided to do it again!

Here’s your chance to show the world what you are working on, and to share the art and beauty that’s often found in science. If you have a favorite image (or three!) that you’ve captured using a BioTek Cytation or Lionheart imager, visit our contest page and submit your entry today! You could win one of three cash prizes (1st place = $1,000, 2nd place = $500, 3rd place = $250) as well as the chance for your image to be featured in our 2020 wall calendar.

To get your creative juices flowing, here are the top three photos from last year:

You can click here to see all of our 2018 winners.

Entries for our 2019 competition will be accepted now through the end of July. We can’t wait to see what this year’s submissions will bring!!

Enter now at www.biotek.com/perspectives.

By: BioTek Instruments, Tara Vanderploeg, Marketing Specialist

BioTek Insights User Group Meeting at NIH

On February 7th, BioTek Instruments held its inaugural user’s group meeting, Insights 2019, at the NIH campus in Bethesda, MD. The meeting offered a venue for the exchange of ideas and a chance to develop new collaborations among our customers. Seven BioTek customers presented their research, with topics ranging from novel imaging methods for the screening of drugs inhibiting the sickling of red blood cells, to machine learning for the quantification of morphology changes in zebrafish. Apart from the customer presentations, attendees participated in workshops that demonstrated the following applications:

• Normalization of Agilent Seahorse OCR and ECAR data using cell counting with Cytation™ 5 
• Barrier integrity assays using Mimetas OrganoPlate Technology and Cytation 1 
• Automated media exchange for spheroid proliferation assays using MultiFlo™ FX and the AMX module 
• Automated scratch assays in 24- and 96-well microplates using AutoScratch™ and Lionheart™ FX

Customers can continue this networking and collaboration through discussion groups on BioTek’s Customer Resource Center (CRC). View discussions and login to post or comment. If you’re not already a CRC user, register with a BioTek instrument serial number or customer number for immediate access.

Many thanks to our presenters and attendees for their participation in this event!

By: BioTek Instruments

SLAS 2019: Time is money…

The old adage “Time is money” initially came to mind when I walked around the exhibition floor at the 2019 Society for Laboratory Automation and Screening (SLAS) conference in Washington DC. Attendees of this conference have embraced laboratory automation to its full extent. As I perused the floor and talked to different vendors, I couldn’t help but think that all of this laboratory automation equipment was designed for one purpose only: to save time…and time equals money.

It is easy to make this assumption. I used to watch the cartoon The Jetsons growing up and couldn’t help but think how nice it would be if we had Rosie, the robot maid in our house. Imagine all the time we would save by having a robot do our chores! The reason behind laboratory automation is a bit more complex than just saving time.

As a long time field sales representative for BioTek, I have seen my share of researchers make the assumption that laboratory automation is designed solely to help them save time. I would walk into labs and quickly scan the benches to see what was going on. Sometimes I would notice stacks of spent ELISA plates occupying the benches. I would immediately approach the PI or lab manager and asked if they have ever considered a BioTek automated microplate washer or dispenser to help them with their plate washing or dispensing needs. Many of these customers would laugh at me. The conversation would go a bit like this:

Me: I see you are running a lot of ELISA’s in your lab and don’t have a plate washer. How do you wash your plates?

Customer: Oh…we wash them by hand. It is a tedious process that takes a lot of time, but that is the way we have always done this.

Me: Have you ever considered a BioTek automated microplate washer? I see you have a BioTek microplate reader in your lab.

Customer: [Customer chuckles] We have grad students for that and grad student time is cheap. We don’t need a washer.

Me: What if I told you that an automated plate washer will not just save you time but that it can help your lab create more “publishable” results?

Customer: Tell me more….

The main reason behind laboratory automation has less to do with time than it does with consistency and reproducibility. Reproducible results are publishable results. In this example, an automated microplate washer for this customer’s ELISA plates would provide more consistent dispensing and aspiration of wash buffer into the ELISA plate leading to tighter CV’s.

BioTek booth at SLAS 2019

This brings me back to SLAS 2019 and some of the newer technologies we presented there. Systems like the BioTek AutoScratch™ were a big hit at the show. Scratch wound assays can provide cancer researchers with a way of quantifying how different conditions affect cell migration - an important element in the study of cancer metastasis.¹ The typical “non-automated” method of creating a scratch in your cell monolayer requires the use of pipette tips and then manually scratching your cells to create a “wound” in the monolayer. Results can be inconsistent when this is done manually - varying downward pressure and scratch inconsistency can result in highly variable results as demonstrated in our recent application note.

After AutoScratch makes the perfect scratch wounds, you can load your assay plates on our BioSpa Live Cell Imaging System or Lionheart™ FX Automated Microscope. BioTek’s Gen5™ software can then use a predefined scratch assay application protocol to image and automatically quantify cell migration because we know exactly where the scratch is on every single well. Our customers at SLAS saw the value in a completely automated workflow solution for this application.

Another hit at SLAS was the new AMX™ Automated Media Exchange module for our MultiFlo™ FX system. Standard plate washers (such as the BioTek 405™ TS or EL406™) are very well established products for washing adherent or lightly adherent cells on microplates. The popularity of 3D cell cultures has required researchers to find new ways of washing non-adherent cells (e.g., spheroids) in microplates. Standard plate washers don’t do well with spheroids as the aspiration pressure would suck the spheroid out of the well. A gentler approach is needed.

I have seen researchers setup wash routines for spheroid washing on complex and expensive pipetting robots. I would describe this as the “killing a fly with a shotgun” approach. You would never use a complex pipetting robot for more standard plate washing routines.

Others have decided to take a step backward and go completely manual with this method; they use hand-held multichannel pipettes to wash their spheroid cultures. I would describe this as the “Karate Kid” approach…or “catching a fly with a set of chopsticks.”

Many of these researchers have explained to me that they have gotten very good with the manual approach and are pretty fast…even faster than the MultiFlo FX with AMX. The problem is consistency and reproducibility. You may miss a well here and there, skip a column on your plate or accidentally aspirate your spheroids when this is done manually. This is where the AMX comes in. It gives you consistent and reproducible results in an automated platform.

We had a great time presenting our new products at SLAS 2019 to our customer base that typically embraces automation. The next time you think about adding automation in your lab, think less about the time savings and more about how automation provides more publishable results!

1. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3857040/


By: BioTek Instruments,  Bikram Chakraborty, Product Manager, Commercial

The Joy of Counting: A recipe for accurate cell-based assays

We have a shelf in our family kitchen that is filled with beautiful books that have more than a few stains and singed pages – badges of honor for any respectable cookbook. Sadly, we only have one chef in my house and I am most certainly not it. Fortunately for all of us though, my wife loves to cook and is a master of culinary improvisation. In this way, our well-loved cookbooks act more as guides than sets of strict instructions to follow.

Often my enthusiasm (if not my skill) is called upon to assist in the preparation of ingredients. I will frequently ask the chef, “How much of this do you want?” and “Should I add more?” My questions are met with casual replies like “a bit more” or “that looks good.” As much as I admire the freewheeling nature of this process, as a scientist, I pine for precise, defined quantities – and the tools to measure them!

In the applications lab at BioTek, we design cell-based assays to run on our life science instruments, including the Cytation™ and Lionheart™ automated imaging systems. These powerful tools enable robust and reproducible measurements for a broad range of applications. One important variable in cell-based assays is the number of cells contributing to a signal of interest. Many factors can lead to variations in cell number across conditions, including pipetting errors and treatment-induced effects. Lacking a reliable method to quantify and adjust for these variations can generate misleading results.

Counting cells directly using automated image acquisition and analysis is the most straightforward and accurate method for measuring the size of a cell population. Coupled with powerful Gen5™ software, the Cytation and Lionheart systems deliver intuitive and accurate cell counts using both label-free and fluorescent label-based techniques. Cell counts provide a sensitive metric for cell proliferation and viability assays, as well as a powerful method for normalizing results across conditions and replicates.

There are a number of similarities between cooking a great meal and conducting a successful assay. Both require thoughtful selection of ingredients, access to the right tools, and recognition of the diverse factors that influence how these components come together. In science, accurate measurements – and adjusting for the variables that can affect them – are crucial for interpreting results correctly and the ability to reproduce them. And while preparing a delicious meal may not require precise measurements, appreciating all the elements that contributed to its creation certainly adds to the experience of those who get to sit down and enjoy it.

Below are just a few examples of how cell counting can be used to add accuracy and reproducibility to your cell-based assays…we hope you enjoy.

Quantitative Evaluation of Cell Proliferation Using Label-Free Direct Cell Counting

Label-free methods of measuring cell growth kinetics are preferable over the use of stains that can influence proliferation rates. Although confluence level can be used for some applications, cell counting is the most direct quantitative measure of cell proliferation over a broad range of cell population densities.

High contrast brightfield cell counts over time relative to confluence. A comparison of NIH3T3 direct cell counts and percent confluence over time demonstrate the different characteristics of the two cell growth metrics. Label free cell counts indicate robust logarithmic cell growth up to full confluence (dashed line).

Profiles from 5 drug concentrations demonstrate a cell type-dependent differential dose response. NIH3T3, HeLa and HCT116 cell proliferation profiles enable quantitative analysis of drug response. Cell counts per mm2 were calculated every 2 hours for 5 days or until cells reached full confluence.

Related Application Note: Kinetic Proliferation Assay Using Label-Free Cell Counting 

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Evaluation of relative levels of apoptosis and necrosis in a population using cell counting

The use of apoptosis and necrosis fluorescent probes were used in combination with automated kinetic imaging to quantitatively assess the effects of known inducers of cell death in multiple cell lines. Label-free high contrast brightfield imaging is used to assess the total number of cells in the population, and fluorescent probes to quantify early stage apoptosis at the level of plasma membrane inversion of phosphatidyl serine, and plasma membrane rupture associated with necrosis. This allows for accurate determination of percent apoptosis and necrosis in each cell population throughout the experiment.

Image analysis of apoptotic and necrotic cells. HT1080 cells were treated with camptothecin in order to determine the effect of the drug on the apoptotic and necrotic response of HT1080 cells. The first row (A-C) shows pre-processed high contrast brightfield images along with GFP and PI at 0 (A), 12 (B), and 24 (C) hours after treatment. The next row of images (D-F) shows the primary mask surrounding each individual cell as delineated by the pre-processed high contrast bright field image. Row G-I shows the expanded mask which captures more of the cell area and encompasses the GFP and PI signal. Row J-L shows the apoptotic cells highlighted in blue. Row M-O indicates necrotic cells highlighted in blue.

HT1080 cells treated with Camptothecin. Apoptosis and necrosis increase in a dose dependent manner as demonstrated by time course (A,B) and dose response (C,D).

Related Application Note: Live Cell Imaging of Apoptosis and Necrosis

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Data Normalization for cellular metabolism analysis

The real-time measurement of oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) using the Agilent Seahorse XF analyzer are widely accepted as the industry standard for obtaining in vitro cellular metabolic parameters. The metabolic rate difference caused by cell amount variation can be eliminated by cell count-based normalization. Here counts of cells stained with Hoechst 33342 are automatically determined and integrated into the data reduction pathway using a Cytation Cell Imaging Multi-Mode Reader.

Example of Seahorse XF data normalization using in situ nuclear staining and in situ cell counting. (A) Raw OCR and ECAR change with serial injections of oligomycin/FCCP (green arrow) and Hoechst 33342 (red arrow) before normalization. (B) Representative images of nuclei fluorescently labeled by Hoechst 33342 injection (upper panel) and nuclei identified and outlined by Gen5 software (lower panel). (C) OCR and ECAR normalized by in situ cell counts using Cytation Cell Imaging Multi-Mode Reader.

Related Application Notes: Normalization of Agilent Seahorse XF Data by In-situ Cell Counting Using a BioTek Cytation 5, XF Data Normalization by the Agilent Seahorse XF Imaging and Normalization System


By: BioTek Instruments, Joe Clayton, PhD., Principal Scientist

How Cell Counts Provide More Context to Your Data

A couple of months ago I, like most of the country, was captivated by the $1.6 billion dollar lottery drawings. After plunking down my $10, I let myself dream about hitting that jackpot and all the trappings of immense wealth. My mind drifted as I could smell the ocean standing on the lanai of my beachside home on some distant Hawaiian Island. Eventually snapped back to reality (Boston traffic does that to you quickly) – I realized I fell into a common pitfall – focusing on a result without accounting for variables. In the case of the lottery, the biggest variable being the odds of winning. With a possible 302 million combinations, the odds of hitting my numbers were about 6 times higher than getting killed by a falling coconut (1 out of 50 million).

All of this discussion of odds got me thinking about data sets I see at our customers’ sites. I often glance at heat maps of raw data as they are generated from our instruments. The high contrasting colors always look promising at first, but unlike the lottery, as scientist we are trained to account for variability. One critical variable in any cell-based assay is that differing numbers of cells between individual assay points can skew data. Typically cell cultures are optimized to account for proliferation rates, rate of cell death, cell adhesion so that cell numbers are consistent before performing any assays. Even with optimized conditions, there can be small variations that can affect the final cell density. These differences can ultimately cause increased variability across replicate data and throughout the experiment. Thus getting an accurate cell count within the assay well would allow for normalization of the data and remove this source of variability.

There are many strategies for normalizing cell population but the preferred method for normalization involves counting fluorescently stained cells in each well of a microplate via microscopy. With BioTek’s imaging and microscopy products, we provide an automated solution for cell counting that historically had been a tedious manual process or required the use of expensive imaging instruments. In the following example we use the nuclear stain DAPI to identify the cell nucleus then BioTek’s Gen5™ software automatically sets a threshold to provide accurate cell counts.

Figure 1: In-Situ Nuclear Staining (A) Threshold Analysis for object selection and count

As a Field Applications Scientist, I see firsthand how this powerful tool helps advance our customers’ research. Earlier this year, we launched a new integrated solution with Agilent Technologies that combined Agilent’s cellular metabolic analysis with BioTek’s imaging technologies. Centered around Agilent’s Seahorse XFe analyzers, customers can monitor real-time oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) of live cells in a multi-well plate, interrogating key cellular functions such as mitochondrial respiration and glycolysis. When coupled with BioTek Cytation™ line, we now provide a powerful and intuitive turnkey platform for normalizing metabolic data. Perhaps the most impressive part of the system is how seamless the interface and workflow is for the customer. With a unified software look and feel provided by Agilent (with Gen5 powerful tools running in the background), the image based normalization is initiated with a simple barcode scan and a few confirmation checks. All of the data is centralized into the Agilent Wave software for complete analysis and interpretation. When the Agilent system is not active, the customer can utilize the Cytation as a stand-alone imager for other quantitative microscopy applications.

For more detailed information, see the XF Data Normalization by the Agilent Seahorse XF Imaging and Normalization System Application Note.

By: BioTek Instruments, Jared Amuan, Field Application Scientist