Tips and Tools

Same Symptoms, Different Parasite: Cyclospora and Cryptosporidium Up Close

Posted on by Shannon Sindermann
Cryptosporidum up close

Cyclospora and Cryptosporidium are easy to confuse. The names nearly rhyme, the illnesses look alike and both slip past routine stool tests; however, the resemblance mostly ends there.

Cryptosporidium is far more common, causing an estimated 800,000+ US illnesses a year, often spread through contaminated water (1). Cyclospora is typically rarer, with lab-confirmed US cases totaling 1,180 between May and August 2025, but over the same window in 2026, fueled in part by a lettuce-linked outbreak, that count neared 20,000 (2).

So if they seem so alike, what actually separates the two?

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Simplifying Protein Purification with HaloTag® Technology

Posted on by Simon Moe

Introduction

artists view inside a cell

Detecting and isolating proteins is challenging when they’re expressed at low native abundance, lack good antibodies, or localize to complex subcellular compartments. Promega developed HaloTag® technology to address these challenges. The system is quite simple. A HaloTag® protein fusion tag is added to your protein of interest, which can be paired with one of many interchangeable ligands to form a highly specific covalent bond. The range of synthetic ligands includes chemical probes, affinity handles, and fluorescent dyes.

Beyond the ligand binding, HaloTag itself functions as a powerful foothold for protein isolation studies. The Magne® HaloTag® Beads enable magnetic capture and isolation of a protein of interest with minimal non-specific binding, supporting clean downstream pull-downs and purification.
Below I highlight an exciting publication that demonstrates the power of HaloTag in enriching phosphotyrosine peptides, a classically challenging area of proteomics.

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Invisible Leishmaniasis: How a One Health Approach Changed Everything in Honduras

Posted on by Teresa Simon

Imagine a parasite circulating actively in a community, infecting dogs, spreading through insect vectors, moving between multiple species—and no one notices. Not because people aren’t looking, but because traditional disease surveillance only watches clinical cases in humans, missing the invisible circulation happening all around them. Research on emerging zoonotic diseases confirms this dynamic is not unique to Honduras, it reflects a global risk intensified by urbanization and climate change. Read more about this in our Promega Connections blog (2).

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The Template That Stayed Behind: Why DNA Removal After In Vitro Transcription Is Harder Than It Looks

Posted on by Promega
In Vitro Transcription

Every in vitro transcription (IVT) reaction starts with DNA you put there on purpose. A linearized plasmid or polymerase chain reaction (PCR) template goes in, the polymerase does its work and a few hours later you have RNA, often a lot of it. The template’s job is done.

In theory, a quick DNase step takes care of the rest.

In practice, the template doesn’t always leave quietly.

The DNA you added is the hardest DNA to remove

In an IVT reaction, the DNA was added deliberately, often in microgram amounts. It sits in a buffer designed to make the polymerase as productive as possible, which is not the same as making DNase productive.

That’s the trade-off at the center of IVT cleanup. The easiest place to digest the template is the reaction tube, right after transcription, with no extra purification step. But IVT reactions carry high ionic strength and a crowded mix of other components, conditions that suppress the activity of many DNase I enzymes (1,2). The reaction is good at making RNA and bad at getting rid of what made it.

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Adapting a Cell-Based Immunoassay for HTS: From the Bench to a 7,000-Compound Screen 

Posted on by Anna Bennett

High-throughput screening (HTS) has been a central approach in small-molecule drug discovery since the late 1980s. It gives researchers a systematic way to find hits: compounds that act on a target and can be refined into drug candidates. The assays used in those screens matter, and cell-based assays are especially valuable because they bridge biochemical assays and in vivo models. Biochemical assays give direct readouts but miss the cellular context, while in vivo models are informative, but costly and slow. Cell-based assays enable scientists to study signaling pathways, target modulation and cytotoxicity in a more native environment, at a practical scale. 

image of puprle and blue antibodies coming together to form a luminescent compelx (lumit assay)

Many cell-based screens depend on engineered reporter systems: cells genetically modified so a pathway of interest produces a measurable signal, such as light or fluorescence. These cell lines take significant time and effort to build and maintain, and because they’re modified, they may not reflect disease-relevant cell states. As drug discovery moves toward primary cells and patient-derived lines, assays that detect endogenous proteins without genetic manipulation become more appealing. Those assays work across more cell types and are faster to set up. 

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Midges on the Move: Tracking The Oropouche Virus Into New Territory

Posted on by Anna Bennett

For decades, Oropouche virus (OROV) was considered a problem limited to the Amazon Rainforest. OROV is transmitted to humans and animals through the bite of tiny blood-feeding insects called Culicoides midges. The virus causes Oropouche fever, which leads to debilitating symptoms like a high fever and severe headache1. While the virus was first isolated in Trinidad in 1955, it has since been associated primarily with outbreaks in the Amazon Basin. However, in the last two years, over 29,000 confirmed cases have been reported across the Americas, suggesting the virus has expanded well beyond its historical range.

One of the most concerning expansions is the state of Minas Gerais in southeastern Brazil. Unlike the Amazon, Minas Gerais sits within the Atlantic Forest biome, a heavily fragmented landscape shaped by agriculture, urbanization, and a climate distinct from the humid tropics where OROV has traditionally circulated. With more than 1,600 cases of Oropouche fever since January 2024, a consortium of researchers from universities in Brazil and the US have combined their efforts to try to understand the urgent question: what is driving OROV transmission in this unfamiliar territory2?

Image of flies swarming in the sky.
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ADC Development: The Questions Running in the Background

Posted on by Elise Johnson

You’ve had food stuck in your teeth at some point during a conversation you thought was going well. Or toilet paper trailing from the back of your shoe on a day you felt particularly put together. Maybe you’ve even forgotten to color in your very blonde eyebrows and spent the rest of the day looking like someone erased the top half of your face. But you had no idea. You’re walking around with the quiet, complete confidence of someone operating on incomplete information.

You weren’t wrong about anything you could see. You just couldn’t see everything, which is a different problem than getting a bad result. A bad result tells you something is wrong, but this doesn’t. This happens in the lab too. The number is clean, the program is advancing, and somewhere in the data, something is happening that your readout has no way to show you.

Antibody-drug conjugate (ADC) development has a version of this problem. The cytotoxicity readout is real, reliable, and correct. It’s also an aggregate, and an aggregate compresses everything that happened into a single number. That number can’t tell you which mechanisms produced it, which ones are underperforming, or what to change if the program stops working. It just tells you cells died, or they didn’t. You’re walking around with the quiet, complete confidence of someone operating on incomplete information.

Cytotoxicity: Where Every Program Begins

Cell viability assays were built to answer one question: did the cells die? Increase the dose, more cells die. Decrease it, fewer do. The curve is clean, the data is reliable, and the payload is doing what it was designed to do. For cytotoxicity, it’s the right question to ask.

That question has an established platform with consistent, reproducible data: our CellTiter-Glo® and RealTime-Glo™ Assays.

For most ADC programs, this is where the measurement work starts and stops, but it should only be where it starts. The question they answer well is only one of several your ADC is raising. The number means what it says, but the question it answers has a boundary, and the boundary leaves you with an incomplete picture.

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AI Identifies the Target. Someone Still Has to Validate It.

Posted on by Elise Johnson

Did you see the movie where Spider-Man files his taxes? Or the one where Wonder Woman sits on hold with her insurance company while her pasta water boils over? Or where Captain America finds blight on his tomato plants and drives to the county extension office where he spends fifty minutes with a seventy-four-year-old master gardener named Marlys then leaves with a handwritten note covering his soil composition, his watering schedule, and what Marlys calls “the mulching situation”?

No. Because the ordinary day-to-day doesn’t stand a chance next to the saving of the world.

We spend most of our lives in the ordinary. Not because we’re failing to reach the extraordinary, but because the ordinary is what holds everything together while we get there. It’s not the backdrop but the foundation. It’s what the story depends on, whether or not it gets any credit.

Drug Discovery Has a Storytelling Problem

Drug discovery runs almost entirely on ordinary days, punctuated by the moments that make the news: a new target gets identified, a compound shows promise, a trial produces results. Those moments get the headlines, press releases and keynote slots. What doesn’t get the same attention is the years of work behind those moments: the assays, the failed experiments, the redesigns, the slow accumulation of evidence that either holds up or doesn’t. That work has always been the majority of drug discovery.

Some of the most important work in drug discovery ends in a result nobody publishes, but a dead end isn’t a failure of the program. It’s the program working. The researcher who rules something out has learned something true. That knowledge travels forward even when it doesn’t make the headline because it can redirect the next hypothesis, narrow the next experiment or just quietly move things along. That work moves research forward without anyone announcing it.

The Shiniest Thing in the Room

Artificial intelligence is drug discovery’s latest extraordinary announcement, and the fanfare is legitimate. Most of the druggable proteome has never been touched. Of approximately 4,500 human proteins considered druggable, all approved drugs to date work through only 716 distinct targets. Drug hunters knew there was more biology to address but lacked a way to find and prioritize candidates at scale. AI is changing that. By scanning genetic evidence, biological networks and scientific literature at a scale no human team can match, AI is surfacing targets that were previously out of reach and ranking them by the strength of the evidence behind them.

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How Mass Spectrometry Is Reshaping Animal Health Research

Posted on by Sara Millevolte

Livestock, sustainable and herd of cattle on a farm in the countryside for eco friendly environment. Agriculture, animals and cows for meat, dairy or beef trade production industry in a grass field

Veterinary medicine increasingly demands the same analytical rigor applied in human clinical research. Whether researchers are characterizing the protein composition of an equine regenerative therapy, detecting drug residues in livestock or profiling pathogen virulence factors in production animals, the questions are complex, and the tools must be equal to them.

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Another Crack in the RAS Code: The Measurement Story Behind Daraxonrasib

Posted on by Elise Johnson

In late May 2026, a clinical trial result landed in the New England Journal of Medicine and immediately rewrote what oncologists believed was possible for patients with metastatic pancreatic cancer. Before the paper was published, people in the field were already calling it “transformative.” The data, when it came, agreed. In a disease where most second-line treatments offer months at best, a drug called daraxonrasib nearly doubled how long patients lived compared to those who received chemotherapy.1 It was approved by the FDA in August 2026 as RASONQUE, six months ahead of schedule.2

RAS proteins, which regulate cell growth and are mutated in more than a third of all human cancers,3 had spent forty years resisting every attempt to drug them. The protein’s surface offered no obvious foothold for a small molecule. Once the word “undruggable” attached itself to the RAS protein family, most of the field moved on to more cooperative targets.

Some researchers stayed. And Promega stayed committed to the question that never goes away: does this new compound work inside a living cell? When the next chapter of the RAS story arrived, the tools were ready. Daraxonrasib is one culmination of a much longer story, one that matters for every researcher pursuing a target the field has written off.

The First Answer

To understand what daraxonrasib represents, it helps to see how an earlier chapter of the RAS story faced the same fundamental measurement challenge.

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