This blog was written in collaboration with our partners at Promega GmbH.
Scientists are comfortable speaking to people who know their field. Speaking to scientists outside of their field of expertise can become a little more challenging, and many find the greatest challenge of all is speaking to people who do not have a science background and are hearing about a scientific concept for the first time, such as journalists in the popular media. What can scientists and journalists do to make the most of the interface of science and journalism?
The importance of the interface between science and journalism is increasingly visible with scientific topics appearing on the national news more frequently due to COVID-19, climate change, and diseases like cancer. So, where can journalists go to learn best practices for interviewing scientists and writing about scientific topics? Promega GmbH offers a platform in which scientists and journalists come together and learn from each other in a constructive exchange. In this workshop setting, scientists speak about a certain topic, and journalists from all kinds of backgrounds can ask questions. When the journalist authors an article about what they learned in that workshop, both sides benefit. The scientists’ work becomes visible, and society learns more about scientific research and discovery that can help all of us to better understand the world and contribute to a brighter future.
Here we describe several common themes that have emerged from these science journalism workshops that may help you the next time you find yourself trying to explain your research to someone unfamiliar with your field.
The Promega Corporate Responsibility Report captures a variety of stories of how we’ve supported our employees, customers and communities over the past year. For example, in 2020, 735 million samples were tested for SARS-CoV-2 using Promega reagents. We launched a new scholarship to support students from underserved backgrounds, and we completed our three largest solar arrays on our Madison, WI campus. As we look to the future, we recognize that there are always more opportunities to reduce our environmental impact. That’s why we’re setting our most ambitious sustainability goals ever.
Lynch syndrome is an inherited condition that significantly increases the risk of developing colorectal and other cancers, often at a young age. People with this condition have close to an 80% chance of developing colorectal cancer in their lifetime. It is the most common form of hereditary colon cancer and causes roughly 3% of all colon cancers. The mutations that cause Lynch syndrome are inherited in an autosomal dominant manner— meaning you only need to have one copy of the gene with a Lynch-associated mutation to be at an increased risk.
It is estimated that 1 in every 279 people have inherited a Lynch-associated mutation (1). Yet despite this prevelence, Lynch syndrome is not well known and ~95% of those with the syndrome don’t know they have it (1).
Lynch Syndrome Cause and Detection
Lynch syndrome is caused by mutations that result in the loss of function of one of the four different major mismatch repair proteins. These proteins act as “proof readers” that correct errors in the DNA sequence that can occur during DNA replication. To determine if Lynch syndrome is likely, simple screening tests can be performed on tumor (cancer) tissue to indicate if more specific genetic testing should be considered. One such screening looks for high levels of microsatellite instability (MSI) in the tumor tissue. High microsatellite instability (MSI-H) in tumor tissue is a functional indication that one or more of the major mismatch repair proteins is not functioning properly.
Watch this short video to learn more about microsatellite instability.
For those who develop colorectal cancer at an early age or have a family history (immediate family member or multiple family members with colorectal cancer or polyps), screening for Lynch syndrome can offer valuable insight for both patients and their family, as well as for their healthcare provider.
New MSI IVD Test for Colorectal Cancer to Help Identify Lynch Syndrome
The Promega OncoMate™ MSI Dx Analysis System has received clearance from the FDA as an IVD Medical Device (link to Press Release) and can be used to determine the MSI status of colorectal cancer tumors to aid in identifying those who should be further tested for Lynch syndrome. The OncoMate™ MSI Dx Analysis System builds upon the company’s fifteen year history of supporting global cancer researchers with one of the leading standard tests for MSI status detection. The OncoMate™ MSI Dx Analysis System offers an improved formulation while using the same five markers that have become the gold standard for MSI detection in the research community and is referenced in over 140 peer review publications (2,3).
The OncoMate™ MSI Dx Analysis System is designed to provide physicians with a functional, molecular measurement of the level of DNA mismatch repair deficiency demonstrated within their patient’s colorectal cancer tumor. MSI testing is recommended to identify candidates for further diagnostic testing for Lynch syndrome. (2–4). The System is part of a broader workflow that includes DNA extraction from FFPE tissue samples, quantitation of DNA, amplification of specific microsatellite markers using multiplex PCR, fragment separation by capillary electrophoresis, and data analysis and interpretation software. The OncoMate™ MSI Dx Analysis System is available in certain countries. Visit the OncoMate™ MSI Dx Analysis System webpage to learn more.
Promega previously announced a CE-marked version of the OncoMate™ MSI Dx Analysis System in France, Germany, Austria, Poland, UK, Ireland, Belgium, Netherlands, Luxembourg, Spain, Italy, Switzerland, Denmark, Sweden and Norway.
It’s been just over 10 years since the world lost a pioneering immunologist and biochemist, Dr. Jürg Tschopp. He died tragically during a hiking trip in the Swiss Alps on March 22, 2011. A host of academic journals, including Science, Nature and Cell, paid tribute to Dr. Tschopp with obituaries that highlighted his many accomplishments in the fields of apoptosis and immunology.
In 2002, a team led by Dr. Tschopp at the University of Lausanne, Switzerland, was studying the role of the proinflammatory cytokine interleukin 1 beta (IL-1β). This cytokine is produced in the cytoplasm as an inactive precursor (pro-IL-1β). It is cleaved by caspase-1 to the active form, but the exact process by which caspase-1 itself is activated was unknown at the time. Several members of the caspase family contain a conserved region known as the caspase recruitment domain or CARD, and it was proposed that this domain was essential to caspase activation.
Based on similarity to another protein containing an N-terminal CARD motif (Apaf-1) that is involved in activation of caspase-9, the researchers examined the roles of a family of proteins known as NALP1, NALP2 and NALP3 (1). In particular, they were interested in NALP1, which is involved in the immune response. Unlike Apaf-1, NALP1 contains a CARD motif at the C terminus, while the N terminus contains a related motif known as a pyrin-like domain (PYD). The research team had previously showed that the PYD region of NALP1 interacted with an adapter protein known as PYCARD or ASC, which also contains an N-terminal PYD and C-terminal CARD.
The results of the team’s in vitro binding, activation and immunodetection studies showed that a multi-unit protein complex is responsible for caspase activation, and they called this complex the “inflammasome” (1). It is composed of caspase-1, caspase-5, PYCARD/ASC and NALP1.
The Brazilian state of Amazonas experienced two distinct waves of COVID-19 infections in 2020. After the first wave, a team from the University of Sao Paolo projected that the city of Manaus would reach the theoretical threshold for herd immunity by the end of the summer. However, a second COVID-19 wave erupted in December 2020, coinciding with the rise of Variant of Concern (VOC) P.1.
New research published in Nature Medicineexamined the different lineages of COVID-19 present in Brazil over time and determined that the two waves were driven by different variants. The first wave was driven by the variant B.1.195, which was imported from Europe in the spring. The second wave was largely driven by VOC P.1. The Nature Medicine study is the first to use viral sequences from samples collected throughout 2020 to explore the epidemiological and virological factors behind the two distinct COVID-19 waves.
Detecting VOC P.1 in Amazonas Samples
The researchers started by generating whole-genome sequences of 250 SARS-CoV-2 samples collected between March 2020 and January 2021. The survey showed that 20% of the sequences belonged to the B.1.195 lineage, and these mostly corresponded with the first exponential growth phase. 24% of the samples belonged to the P.1 lineage, and all of these samples corresponded with the rise of the second exponential growth phase. The largest share belonged to B.1.1.28 (37%), which replaced B.1.195 as the dominant variant in Brazil shortly after the first wave until the rise of VOC P.1.
The team also used real-time RT-PCR to analyze 1,232 positive samples collected in Amazonas between November 1, 2020 and January 21, 2021. The assay was designed to detect a deletion in NSP6, which is a signature mutation of VOC P.1. None of the samples collected before December 16 showed the NSP6 deletion, but it was common in samples starting in mid-December. Combining the two analysis methods, the team found the P.1 lineage in 0% of samples collected in November 2020, but by January 1-15 it was present in 73.8% of samples.
This data supports the theory that VOC P.1 first emerged in December 2020 and was the dominant lineage driving the second wave in Amazonas.
Two COVID-19 Waves: Virological and Epidemiological Factors
In addition to tracking the prevalence of lineages throughout the pandemic, the researchers also offered suggestions for how Amazonas experienced two distinct waves of COVID-19 infections.
Using computer modeling, the team found a significant reduction in reproductive efficiency (Re) of lineages B.1.195 and B.1.1.28 in April-May 2020, around the same time that Amazonas increased social distancing measures. Transmission rates remained low until the interventions were relaxed in September 2020. This suggests that the reduction in cases was not a result of herd immunity. Instead, nonpharmaceutical interventions (NPI) limited the first wave and contained the spread through the summer.
Using real-time RT-PCR, the researchers found that the viral load of P.1 infections was nearly ten times the viral load of non-P.1 infection. They also referenced other research that found that VOC P.1 has a stronger affinity for the human receptor ACE2 than B.1.195 and B.1.1.28. P.1 is clearly a highly transmissible VOC, and it evolved in an ideal environment for rapid spread. Amazonas had relaxed social distancing measures by late 2020, P.1 was able to quickly reach extremely high infection rates.
The study did not directly address theories that P.1 evades immunity developed from prior infections, but they concluded that a combination of epidemiological and virological factors allowed P.1 to drive a second wave of COVID-19 in Amazonas starting in December.
The paper includes a supplementary note suggesting that NPIs instituted in Manaus in January 2021 significantly reduced transmission rates of VOC P.1. The team ends the paper by reiterating the importance of adequate social distancing measures to limit the spread of COVID-19 and prevent the emergence of new Variants of Concern.
This study used the Maxwell® RSC Viral Total Nucleic Acid Purification Kit to extract viral RNA from samples. Learn more about the kit and its uses during the COVID-19 pandemic here.
When we think of viruses, we often think of diseases, pandemics and death. Our impression of viruses is that they are “bad”. But viruses could also be a possible cure for the deadliest disease in modern history: cancer. The therapeutic effects of “good” cancer-killing oncolytic viruses have been documented over a century ago. Records from as early as 1904 described a 42-year old woman with acute leukemia who experienced temporary remission after an influenza infection. Other early reports showed spontaneous remission of Hodgkin lymphoma and Burkitt’s lymphoma after natural infections with the measles virus.
Despite the long history, oncolytic viruses have only recently gained momentum in the scientific community. Dr. Aldo Pourchet, CSO and co-founder of Omios Biologics—a biotech startup in the San Francisco Bay area—is determined to harness the power of oncolytic viruses to develop a new generation of cancer immunotherapy.
How Oncolytic Viruses Work
“One thing that we know for sure is that you need the immune system to fight the cancer,” says Pourchet. “You need to recruit the immune system, and probably the best thing we know for recruiting the immune system is viruses. Our immune system evolved to detect them immediately. That’s why we are still on Earth. It’s because we have been able to fight deadly viruses.”
Today’s guest blog is written by Melissa Martin, a global marketing intern with Promega this summer. She will be a senior this fall at the University of Wisconsin-Madison where she is double majoring in zoology and life sciences communication, with a certificate in environmental studies.
Congrats! You are attending a university and pursuing a challenging, yet rewarding, undergraduate science degree. Getting to this moment probably included lots of late nights spent studying or worrying while applying to your dream college. However, now that you are here you will find that classes provide a lot of information. You can even take your education one step further by getting hands-on experience in a research lab.
Working in a lab is not only about making your resume look good. It offers a real-world experience that directly enhances your learning experience and can even guide your future. For example, your experiences in the lab can teach you basic skills (pipetting, determining concentrations, performing titrations, etc.) that will be useful in a variety of science professions.
This post was written by guest blogger, Nicole Werner, Product Management Support at Promega GmbH.
“You have cancer.” – a statement that fundamentally changes life in a second. After the first shock, the insight often arises: “If only I had stopped smoking sooner!”
Lung cancer, while not the leading cause of death worldwide, is the leading preventable cause of death in developed countries. According to the WHO, eight million people die each year as a result of smoking, including one million as a result of passive smoking [1]. Currently, 80% of those affected die within the next 13 months after diagnosis [1]. New therapeutic approaches, such as treatment with immune checkpoint inhibitors, bring hope.
Promega supports research in this area with the high-precision tools needed to develop this new form of therapy.
Today’s post is written by Michael Curtin, Senior Product Manager, Reporters and Signaling.
Inflammation is a defense mechanism that the body employs in which the immune system recognizes and removes harmful and foreign stimuli and begins the healing process. Inflammation can be either acute or chronic. Chronic inflammation is also referred to as slow, long-term inflammation and can last for prolonged periods (several months to years); chronic inflammation is caused by immune dysregulation. This typically takes the form of the body’s inability to resolve inflammation resulting from overproduction of inflammatory cytokines and chemokines, as well as danger-associated molecular patterns (DAMPs) released from dying cells (2). Tumor Necrosis Factor (TNF) is the primary cytokine involved in many common inflammatory diseases and is where many therapies targeting inflammation are focused.
Recent research that RIP kinases (RIPK1 and RIPK3) are important regulators of innate immunity via their key roles in cell death signaling during cellular stress and following exposure to inflammatory and infectious stimuli. RIPK1 has an important scaffolding role in pro-inflammatory signaling where it interacts with TRADD, TRAF1 TRAF2, and TRAF3 and TRADD can act as an adaptor protein to recruit RIPK1 to the TNFR1 complex in a TNF-dependent process. RIPK1 plays a kinase activity-dependent role in both apoptotic and necroptotic cell death. A review article by Speir et al. (1) discusses the role of RIP kinases in chronic inflammation and the potential of RIPK1 inhibitors as a new therapeutic approach for the treatment of chronic inflammation. RIPK1 or Receptor Interacting Protein Kinase 1 is a serine/threonine kinase that was originally identified as interacting with the cytoplasmic domain of FAS. Promega offers several reagents that make studying RIPK1 easier- these include our RIPK1 Kinase Enzyme Systems which includes RIPK1 (Human, recombinant; amino acids 1-327), myelin basic protein (MBP) substrate, reaction buffer, MnCl2, and DTT and is optimized for use with our ADP-Glo Kinase Assay.
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?
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