At the time of writing this post, no scientist had yet discovered the secret to immortality. In our world, we’ve come to accept that living things are born, grow old and die—the circle of life.
And yet, for many years, life scientists believed that the circle of life did not apply to our constituent cells when cultured in a laboratory. That is, cultured normal human cells were immortal, and they would continue to grow and proliferate forever, as long as they were provided with the necessary nutrients.
Pioneering work published in 1961 by Leonard Hayflick and Paul Moorhead challenged that theory (reviewed in 1). Their research showed that normal cells in culture have a finite capacity to replicate. After they reach a certain number of replicative cycles, cells stop dividing. Hayflick and Moorhead made the important distinction between normal human cells and cultured cancer cells, which are truly immortal. In later years, the limit to the number of replicative cycles normal human cells can undergo became known as the Hayflick limit. Although some scientists still express skepticism about these findings, the Hayflick limit is widely recognized as a fundamental principle of cell biology.
You are studying the effects of a compound(s) on your cells. You want to know how the compound affects cell health over a period of hours, or even days. Real-time assays allow you to monitor cell viability, cytotoxicity and apoptosis continuously, to detect changes over time.
Why use a real-time assay? A real-time assay enables you to repeatedly measure specific events or conditions over time from the same sample or plate well. Repeated measurement is possible because the cells are not harmed by real-time assay reagents. Real-time assays allow you to collect data without lysing the cells.
Advantages of Real-Time Measurement Real-time assays allow you to:
This blog is written by guest author, Maggie Bach, Sr. Product Manager, Promega Corporation.
Researchers are increasingly relying on cells grown in three-dimensional (3D) structures to help answer their research questions. Monolayer, or 2D cell culture, was the go-to cell culture method for the past century. Now, the need to better represent in vivo conditions is driving the adoption of 3D cell culture models. Cells grown in 3D structures better mimic tissue-like structures, better exhibit differentiated cellular functions, and better predict in vivo responses to drug treatment.
Switching to 3D cell culture models comes with challenges. Methods to interrogate these models need to be adaptable and reliable for the many types of 3D models. Some of the most popular 3D models include spheroids grown in ultra-low attachment plates, and cells grown in an extracellular matrix, such as Matrigel® from Corning. Even more complex models include medium flow over the cells in microfluidic or organ-on-a-chip devices. Will an assay originally developed for cells grown in monolayer perform consistently with various 3D models? How is measuring a cellular marker different when cells are grown in 3D models compared to monolayer growth?
In recent years, scientists have been hot on the trail of transcription factor FOXO3, tracing its involvement in various tumor-centric activities comprising the many trademarks of cancer, from drug resistance to metastasis to tumor angiogenesis.
FOXO3 is a member of the O sub-class of the forkhead box family of transcription factors. The forkhead box (FOX) family is characterized by a fork head DNA-binding domain (DBD), comprised of around 100 amino acids. They have also proven themselves to be a family of many hats, functioning in diverse roles ranging from metabolism, immunology, cell-cycle control, development, as well as cancer (1). The forkhead box O (FOXO) sub-class alone has demonstrated involvement in a variety of cellular outcomes, from drug resistance and longevity to apoptosis induction.
Due to its pro-apoptotic and anti-proliferative proclivity, FOXO3 has been previously identified as a tumor suppressor gene. However, more and more studies have begun to flip the narrative on FOXO3, portraying it more as a devoted henchman, due to its roles in drug and radiotherapy resistance, cell-cycle arrest and long-term maintenance of leukemia-initiating stem cells in a variety of cancer types, including breast cancer, pancreatic cancer, glioblastoma, and both acute and chronic myeloid leukemia.
When someone is admitted to a hospital for an illness, the hope is that medical care and treatment will help them them feel better. However, nosocomial infections—infections acquired in a health-care setting—are becoming more prevalent and are associated with an increased mortality rate worldwide. This is largely due to the misuse of antibiotics, allowing some bacteria to become resistant. Furthermore, when an antibiotic wipes out the “good” bacteria that comprise the human microbiome, it leaves a patient vulnerable to opportunistic infections that take advantage of disruptions to the gut microbiota.
One such bacteria, Clostridium difficile, is of growing concern world-wide since it is resistant to many different antibiotics. When a patient is treated with an antibiotic, C. difficile can thrive in the intestinal tract without other bacteria populating the gut. C. difficile infection is the leading cause of antibiotic-associated diarrhea. While symptoms can be mild, aggressive infection can lead to pseudomembranous colitis—a severe inflammation of the colon which can be life-threatening.
Over a hundred years ago William B Coley, the “Father of Immunotherapy”, discovered that injection of bacteria or bacterial toxins into tumors could cause those tumors to shrink. The introduction of bacteria had the side-effect of stimulating the immune system to attack the tumor. The field of cancer immunotherapy research—which today includes many different approaches for generating anti-tumor immune responses—originated with these early experiments.
Use of bacteria is one way to stimulate the immune system to attack cancer cells, others include use of cytokines, immune checkpoint blockades and vaccines. This Nature animation provides a simple overview of these methods.
What if you could uncover a small but significant cellular response as your population of cells move toward apoptosis or necrosis? What if you could view the full picture of cellular changes rather than a single snapshot at one point? You can! There are real-time assays that can look at the kinetics of changes in cell viability, apoptosis, necrosis and cytotoxicity—all in a plate-based format. Seeking more information? Multiplex a real-time assay with endpoint analysis. From molecular profiling to complementary assays (e.g., an endpoint cell viability assay paired with a real-time apoptosis assay), you can discover more information hidden in the same cells during the same experiment.
Whether your research involves screening a panel of compounds or perturbing a regulatory pathway, a more complete picture of cellular changes gives you the benefit of more data points for better decision making. Rather than assessing the results of your experiment using a single time point, such as 48 hours, you could monitor cellular changes at regular intervals. For instance, a nonlytic live-cell reagent can be added to cultured cells and measurements taken repeatedly over time. Pairing a real-time cell health reagent with a detection instrument that can maintain the cells at the correct temperature means you can automate the measurements. These repeated measurements over time reveal the kinetic changes in the cells you are testing, giving a real-time status update of the cellular changes from the beginning to the end of your experiment. Continue reading “Reveal More Biology: How Real-Time Kinetic Cell Health Assays Prove Their Worth”
When I consider that major surgery was performed long before anesthetics were developed, I am grateful to be alive in the anesthesia era. Just the thought of being subjected to various cutting and retracting instruments without general anesthesia calls to mind a phrase: The cure is worse than the disease. Despite the advantages of unconsciousness during surgery, anesthesia can have side effects. Studies in neonatal nonhuman primates have demonstrated that the anesthetic ketamine has toxic effects. However, the differences between humans and nonhuman primates mean the outcome in one species is not the same in another. In an article recently published in PLOS ONE, scientists were interested in creating an experimental model of developing human neurons and using the model to better understand the toxic effects of ketamine on human cells. Continue reading “Developing a Model System to Test Ketamine Toxicity”
The concept of cell death as a normal cell fate was articulated only three years after Schleiden and Schwann introduced the Cell Theory when, in 1874, Vogt described natural cell death as an integral part of toad development (as cited in Cotter and Curtin, 2003). Since these early observations, natural cell death has been described “anew” several times. In 1885 Flemming provided the first morphological description of a natural cell death process, which we now label “apoptosis”, a term coined by Kerr and colleagues to describe the unique morphology associated with a cell death that differs from necrosis (as cited in Kerr et al. 1972).
In the 1970s and 1980s, studies revealed that apoptosis not only had specific morphological characteristics but that it was also a tightly regulated process with specific biochemical characteristics. Studies of cell lineage in the nematode, Caenorhabditis elegans, showed that apoptosis was a normal feature of the nematode’s invariant developmental program (Hengartner, 1997). At the biochemical level, Wyllie showed that DNA degradation by a specific endonuclease during apoptosis resulted in a DNA ladder composed of mono- and oligonucleosomal-sized fragments (Wyllie, 1980).
These and many other studies have proven that apoptosis is a critical component of development, and when it doesn’t happen appropriately, it can be pathological, leading to cancers or other diseases. Therefore, understanding how and when apoptosis occurs and the many signals that can trigger this process is a focus of many laboratory experiments.
Determining the exact cause/effect relationship between a treatment and a cellular outcome is not a simple matter, but is critical for really understanding how therapeutic treatments affect target cells or exercise any off-target effects.
Four key factors are critical for determining whether or not a particular treatment or compound is toxic.
By clicking “Accept All”, you consent to the use of ALL the cookies. However you may visit Cookie Settings to provide a controlled consent.
If you are located in the EEA, the United Kingdom, or Switzerland, you can change your settings at any time by clicking Manage Cookie Consent in the footer of our website.
Necessary cookies are absolutely essential for the website to function properly. These cookies ensure basic functionalities and security features of the website, anonymously.
This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Analytics".
The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional".
This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Other.
The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Advertisement".
This cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary".
This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Performance".
6 months 2 days
This cookie is set by the provider Media.net. This cookie is used to check the status whether the user has accepted the cookie consent box. It also helps in not showing the cookie consent box upon re-entry to the website.
This cookie is used to store the language preferences of a user to serve up content in that stored language the next time user visit the website.
Analytical cookies are used to understand how visitors interact with the website. These cookies help provide information on metrics the number of visitors, bounce rate, traffic source, etc.
This cookie is associated with Sitecore content and personalization. This cookie is used to identify the repeat visit from a single user. Sitecore will send a persistent session cookie to the web client.
This domain of this cookie is owned by Vimeo. This cookie is used by vimeo to collect tracking information. It sets a unique ID to embed videos to the website.
1 month 18 hours 24 minutes
This cookie is used to calculate unique devices accessing the website.
This cookie is installed by Google Analytics. The cookie is used to calculate visitor, session, campaign data and keep track of site usage for the site's analytics report. The cookies store information anonymously and assign a randomly generated number to identify unique visitors.
This cookie is installed by Google Analytics. The cookie is used to store information of how visitors use a website and helps in creating an analytics report of how the website is doing. The data collected including the number visitors, the source where they have come from, and the pages visted in an anonymous form.
Advertisement cookies are used to provide visitors with relevant ads and marketing campaigns. These cookies track visitors across websites and collect information to provide customized ads.
1 year 24 days
Used by Google DoubleClick and stores information about how the user uses the website and any other advertisement before visiting the website. This is used to present users with ads that are relevant to them according to the user profile.
This cookie is set by doubleclick.net. The purpose of the cookie is to determine if the user's browser supports cookies.
5 months 27 days
This cookie is set by Youtube. Used to track the information of the embedded YouTube videos on a website.
Performance cookies are used to understand and analyze the key performance indexes of the website which helps in delivering a better user experience for the visitors.
This cookies is set by Youtube and is used to track the views of embedded videos.
This is a pattern type cookie set by Google Analytics, where the pattern element on the name contains the unique identity number of the account or website it relates to. It appears to be a variation of the _gat cookie which is used to limit the amount of data recorded by Google on high traffic volume websites.