How Avian Influenza Crosses Species

Avian influenza, commonly known as bird flu, has become an increasingly severe public health issue. According to the CDC, the frequency of avian influenza outbreaks and diversity of virus subtypes have increased significantly in the past decade. In 2022, there were reports of sporadic H5 virus infections in mammals across several U.S. states, Canada, and other countries. Affected animals included fox kits, bobcats, coyote pups, raccoons, skunks, mink, and even seals. Human cases of H5N6 and other subtypes following poultry exposures were reported in China, with several cases resulting in severe or critical illness and death.

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Expert Insights: A Look Forward at Multiplexing for in vivo Bioluminescence Imaging

Bioluminescent in vivo imaging tools

NanoLuc, NLuc

With advancements made over the past few decades, the future of in vivo bioluminescence imaging (BLI) continues to gain momentum. In vivo BLI provides a non-invasive way to image endogenous biological processes in whole animals. This provides an easier method to assess relevant systems and functions. Unlike fluorescent imaging, BLI relies on a combination of enzymes and substrates to produce light, greatly reducing background signal (Refaat et al., 2022). Traditional fluorescent tags are also quite large and may interfere with normal biological function. In vivo BLI research has been around for quite some time, primarily utilizing Firefly luciferase (Luc2/luciferin). A recent advancement was the creation of the small and bright NanoLuc® luciferase (NLuc). Promega offers an wide portfolio of NLuc products that provide ways to study genes, protein dynamics, and protein:protein interactions. To fully grasp the power of these tools, I interviewed several key investigators to determine their perspectives on the future of in vivo BLI. I was specifically interested in their thoughts on NLuc multiplexing potential with Firefly (FLuc), and future research areas. These two investigators are Dr. Thomas Kirkland, Sr. Scientific Investigator at Promega, and Dr. Laura Mezzanotte, Associate Professor at Erasmus MC.

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Transform Your Research Lab with our Comprehensive Automation Resources

Futuristic Artificial Intelligence Robotic Arm Operates and Moves a Metal Object, Picks It Up and Puts it Down. Scene is Taken in a High Tech Research Laboratory with Modern Equipment.

In an era where science moves at a rapid pace, integrating automation into your lab is not just beneficial but essential. When you automate your lab, you free up an invaluable resource: time. From scaling up operations and handling increased demand to improving consistency and reducing manual errors, automation can be the key to achieving higher throughput, saving costs, and—most importantly—enabling researchers to focus on the science rather than the process. However, embarking on a lab automation project requires careful planning, clear goals and an understanding of the intricacies involved in automating complex biological workflows.

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Dynein Motor Proteins Could Be the Moving Power Behind Cancer Metastasis

3D Cancer Cell

“The cancer has spread.” are perhaps some of the most frightening words for anyone touched by cancer. It means that cancer cells have migrated away from the primary tumor, invaded health tissues and firmed secondary tumors. Called metastasis, this event is the deadliest feature of any type of cancer (1). The cellular mechanisms that play a role in metastasis could serve as powerful therapeutic targets. Unfortunately, understanding of these mechanisms is limited. However, some studies have suggested a link between the dysregulation of microtubule motors and cancer progression. A new study by a team from Penn State has revealed that the motor protein dynein plays a pivotal role in the movement of metastatic breast cancer cells through two model systems simulating soft tissues (1).

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The Tiniest Test Tube: Studying Cell-Specific Protein Secretion

Free floating single cells, blue
Researchers explore an innovative method for single-cell analysis

Cells produce proteins that serve different purposes in maintaining human health. These bioactive secretions range from growth factors to antibodies to cytokines and vary between different types of cells. Even within a certain cell type, however, there are individual cells that produce more secretions than others, a phenomenon that especially interests scientists studying cell-based therapies. In contrast to molecular therapies, which typically involve specific genes or proteins, a primary challenge to crafting cell therapies is the wide range of functional outputs seen in cells that have the same genetic template. This leads to the question of what molecular properties, from a genomic and transcriptomic perspective, would lead one cell to produce more of a protein than its companions. 

There have been few investigative strategies put forth that allow scientists to connect a cell’s characteristics and genetic coding with its secretions. In July 2023 a team of scientists published a paper in Nature Communications outlining an innovative solution: little hydrogel particles, or “nanovials”, that essentially serve as tiny test tubes and can be used to measure protein secretion, track transcriptome data, and identify relevant surface markers in a single cell.

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Blending Art and Science in a Costa Rica Physics Lab

Sophia Speece engaged her passions for art and science during her internship in Costa Rica.
UW-Madison student Sophia Speece (left) spent the summer in Costa Rica for the “Artist in the Science Lab” internship hosted by alum Dr. Mariela Porras Chaverri (right)

My name is Sophia Speece. I am a junior at the University of Wisconsin-Madison studying Biomedical Engineering and Music Performance. As you can imagine, there is not a lot of overlap between these two passions of mine.

This past summer I was given the unique opportunity to combine these two areas. I applied and was accepted for the “Artist in the Science Lab” internship abroad in Costa Rica!

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How do Self-Amplifying RNA Vaccines Work?

In late November 2023, regulatory authorities in Japan approved a new SARS-CoV-2 vaccine. Unlike earlier messenger RNA (mRNA) vaccines used to protect against COVID-19, this one relies on a technology called self-amplifying mRNA, or saRNA. Though researchers have long pursued saRNA-based vaccines, this represents the first full approval for the technology in humans and marks an exciting advance in the ongoing development of mRNA vaccines.

Continue reading for an overview of how saRNA vaccines work and some of their advantages relative to standard mRNA vaccines.

A syringe withdraws clear liquid from a sealed glass vial.
 A new type of COVID-19 mRNA vaccine, a self-amplifying RNA vaccine, was recently approved in Japan.
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Will Artificial Intelligence (AI) Transform the Future of Life Science Research?

Artificial intelligence (AI) is not a new technological development. The idea of intelligent machines has been popular for several centuries. The term “artificial intelligence” was coined by John McCarthy for a workshop at Dartmouth College in 1955 (1), and this workshop is considered the birthplace of AI research. Modern AI owes much of its existence to an earlier paper by Alan Turing (2), in which he proposed the famous Turing Test to determine whether a machine could exhibit intelligent behavior equivalent to—or indistinguishable from—that of a human.

The explosive growth in all things AI over the past few years has evoked strong reactions from the general public. At one end of the spectrum, some people fear AI and refuse to use it—even though they may have unwittingly been using a form of AI in their work for years. At the other extreme, advocates embrace all aspects of AI, regardless of potential ethical implications. Finding a middle ground is not always easy, but it’s the best path forward to take advantage of the improvements in efficiency that AI can bring, while still being cautious about widespread adoption. It’s worth noting that AI is a broad, general term that covers a wide range of technologies (see sidebar).

AI personified looking at a dna double helix against an abstract cosmic background
Image generated with Adobe Firefly v.2.

For life science researchers, AI has the potential to address many common challenges; a previous post on this blog discussed how AI can help develop a research proposal. AI can help with everyday tasks like literature searches, lab notebook management, and data analysis. It is already making strides on a larger scale in applications for lab automation, drug discovery and personalized medicine (reviewed in 3–5). Significant medical breakthroughs have resulted from AI-powered research, such as the discovery of novel antibiotic classes (6) and assessment of atherosclerotic plaques (7). A few examples of AI-driven tools and platforms covering various aspects of life science research are listed here.

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More Than a Scientist: Paraj Mandrekar’s Career & Contributions to Tabletop Roleplaying Games

Paraj Mandrekar began his career at Promega in 1998 in the Genetic Identity Research and Development program. In 2001, he was a consultant at the World Trade Center to help meet the urgent need to identify victims of the 9/11 attacks. Two products, one of them being our DNA IQ™ System, that Paraj and others used for automating forensic DNA purification at the time were featured in the R&D 100 Award in 2002.

As he progressed through the successive ranks in R&D, Paraj took on more responsibility for the research, design, and development of novel chemistry. A significant high point in his career was being promoted to Senior R&D Scientist 1 in 2010. At that point, he was working on both forensic and non-forensic chemistries with paramagnetic particles. Promega’s non-forensic kit (AS1290) was launched with a new chemistry in March 2010, and a few months later, he got a new version of the Maxwell forensic sample kit (AS1240) out the door.

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Cell-Based Target Engagement and Functional Assays for NLRP3 Inhibitor Profiling Help Identify Successes and Failures

Identifying Inflammasome Inhibitors: What’s Missing
The NLRP3 inflammasome is implicated in a wide range of diseases. The ability to inhibit this protein complex could provide more precise, targeted relief to inflammatory disease sufferers than current broad-spectrum anti-inflammatory compounds, potentially without side effects.

Studies of NLRP3 inflammasome inhibitors have relied on cell-free assays using purified NLRP3. But cell-free assays cannot assess physical engagement of the inhibitor and target in the cellular micro-environment. Cell-free assays cannot show if an NLRP3 inhibitor enters the cell, binds the target and how long the inhibitor binding lasts.

Cell-based assays that interrogate the physical interaction of the NLRP3 target and inhibitor inside cells are needed.

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