This blog is written by guest blogger Ben Rushton, Application Specialist/Territory Manager at Promega Australia.
When you’re monitoring marine biodiversity at scale, every drop of seawater tells a story. At Minderoo OceanOmics Centre at the University of Western Australia, scientists are uncovering that story through environmental DNA (eDNA)—and automation is helping them listen more clearly.
Laura Missen, a Scientific Officer at OceanOmics Centre, shares how automating their DNA extraction workflow with the Maxwell® RSC 48 system has transformed how they gather and interpret data from marine ecosystems.
Discovered in 1983 and initially dismissed as ‘cellular dust,’ exosomes have since emerged as pivotal players in biomedical research due to their roles in intercellular communication, potential as drug delivery vectors and as biomarkers for various diseases. These small extracellular vesicles, measuring 30–150nm, are crucial for transferring proteins, lipids, and nucleic acids — including microRNA (miRNA), mRNA, and non-coding RNA– between cells (1). miRNAs are particularly critical as they regulate gene expression and offer insights into the cellular mechanisms underlying diseases like cancer, enhancing the value of exosomes in cancer research.
Beyond exosomes importance in understanding intracellular communication and organ cross-talk, exosomes can also alter the functions of recipient cells based on their cargo. This capability makes them extremely valuable in providing insights into alterations in cellular communication, tumor microenvironments, metastasis and immune evasion.
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.
Before the respiratory virus SARS-CoV-2 ever emerged, Tom Friedrich was already studying how viruses evolve to cause pandemics. His PhD training focused on how HIV adapts to escape detection by the immune system. Since opening his lab at the University of Wisconsin—Madison in 2008, he’s studied how viruses like influenza and Zika overcome evolutionary barriers to spread and cause disease. For nearly two years, he’s been analyzing viral sequencing data generated from positive COVID-19 test samples around the state of Wisconsin.
Thomas Friedrich, professor of pathobiological sciences in the School of Veterinary Medicine. Photo by Jeff Miller / UW-Madison, provided by Thomas Friedrich.
As the COVID-19 pandemic persists, Tom continues to make important contributions to both SARS-CoV-2 research and the relevant public health response. However, his experiences have led him to ask an even bigger question: How can we prepare for the next pandemic while still battling the current one?
“What has characterized our responses to these types of disease outbreaks in the past is sort of a boom and bust cycle,” Tom says. “We spin up a massive response that often tends to get going just as the thing itself is petering out. Then interest and funding wane so that we’re not really left with any sustainable infrastructure. But with Ebola, Zika and now COVID-19 in a pretty rapid cadence, I think people are finally getting the idea that we need to have a more sustainable infrastructure that is not totally specific to the particular disease that’s causing this outbreak today.”
Many research labs around the world have temporarily closed their doors in response to the COVID-19 pandemic, while others are experiencing unprecedented need for reagents to perform viral testing. This urgency has led many scientists to make new connections and build creative, collaborative solutions.
“In labs that are still open for testing or other purposes, there’s certainly heightened anxiety,” says Tony Vanden Bush, Client Support Specialist. “I feel that right now, I need to help them deal with that stress however possible.”
Last week, Tony was contacted by a lab at the University of Minnesota that was preparing to serve as a secondary COVID-19 testing facility for a nearby hospital lab. The two labs needed to process up to 6,000 samples per day, and the university lab was far short of that capacity.
Human Ferrochelatase 2 angstrom crystal structure. Generated from 1HRK (RCSB PDB) using Pymol. Copyright: Sarah Wilson / CC BY-SA
Understanding how disease states arise from genetic variants is important for understanding disease resistance and progression. What can complicate our understanding of disease development is when two people have the same genetic variant, but only one has the disease. To investigate what might be happening with ferrochelatase (FECH) variant alleles that result in erythropoietic protoporphyria (EPP), scientists used next-generation sequencing (NGS) along with RNA analysis and DNA methylation testing to assess the FECH locus in 72 individuals from 24 unrelated families with EPP.
What is FECH and its relationship to EPP?
FECH is the gene for ferrochelatase, the last enzyme in the pathway that synthesizes heme. The inherited metabolic disorder, EPP, is caused when the activity of FECH is reduced to less than a third of normal levels thus, increasing the levels of protoporphyrin (PPIX) without metal in erythrocytes. The consequences of the low-metal PPIX include severe phototoxic skin reactions and hepatic injury due to PPIX accumulation in the liver.
How does FECH expression affect EPP?
The EPP disease state is not simply the lack of two functional FECH genes. Disease occurs with a hypomorphic allele, mutations in FECH that reduce its function, in trans to a null FECH allele. Researchers focused on three common variants called the GTC haplotype that are associated with expression quantitative trait loci (eQTL) that reduce FECH activity. Interestingly, these three variants have been found in trans, but researchers wanted to learn if there were individuals who were homozygous for the GTC allele and how EPP manifested for them.
Tradeoffs are a constant source of challenge in any research lab. To get faster results, you will probably need to use more resources (people, money, supplies). The powerful lasers used to do live cell imaging may well kill those cells in the process. Purifying DNA often leaves you to choose between purity and yield.
Working with biologics also involves a delicate balancing act. Producing compounds in biological models rather than by chemical synthesis offers many advantages, but it is not without certain challenges. One of those tradeoffs results from scaling up; the more plasmid that is produced, the greater probability of endotoxin contamination.
Implementing automated nucleic acid purification or making changes to your high-throughput (HT) workflow can be complicated and time-consuming. There are also many barriers to success such as challenging samples types and maintaining desirable downstream results that can add to the stress, not to mention actually getting the robotic instrumentation to do what you want it to. All of this makes it easy to understand why many labs avoid automating or own expensive instrumentation that goes unused. Continue reading “High-Throughput Purification with Experts Included”
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