MIT Research News' Journal

Microfluidics device helps diagnose sepsis in minutes

A novel sensor designed by MIT researchers could dramatically accelerate the process of diagnosing sepsis, a leading cause of death in U.S. hospitals that kills nearly 250,000 patients annually.

Sepsis occurs when the body’s immune response to infection triggers an inflammation chain reaction throughout the body, causing high heart rate, high fever, shortness of breath, and other issues. If left unchecked, it can lead to septic shock, where blood pressure falls and organs shut down. To diagnose sepsis, doctors traditionally rely on various diagnostic tools, including vital signs, blood tests, and other imaging and lab tests.

In recent years, researchers have found protein biomarkers in the blood that are early indicators of sepsis. One promising candidate is interleukin-6 (IL-6), a protein produced in response to inflammation. In sepsis patients, IL-6 levels can rise hours before other symptoms begin to show. But even at these elevated levels, the concentration of this protein in the blood is too low overall for traditional assay devices to detect it quickly.

In a paper being presented this week at the Engineering in Medicine and Biology Conference, MIT researchers describe a microfluidics-based system that automatically detects clinically significant levels of IL-6 for sepsis diagnosis in about 25 minutes, using less than a finger prick of blood.

In one microfluidic channel, microbeads laced with antibodies mix with a blood sample to capture the IL-6 biomarker. In another channel, only beads containing the biomarker attach to an electrode. Running voltage through the electrode produces an electrical signal for each biomarker-laced bead, which is then converted into the biomarker concentration level.

“For an acute disease, such as sepsis, which progresses very rapidly and can be life-threatening, it’s helpful to have a system that rapidly measures these nonabundant biomarkers,” says first author Dan Wu, a PhD student in the Department of Mechanical Engineering. “You can also frequently monitor the disease as it progresses.”

Joining Wu on the paper is Joel Voldman, a professor and associate head of the Department of Electrical Engineering and Computer Science, co-director of the Medical Electronic Device Realization Center, and a principal investigator in the Research Laboratory of Electronics and the Microsystems Technology Laboratories.

Integrated, automated design

Traditional assays that detect protein biomarkers are bulky, expensive machines relegated to labs that require about a milliliter of blood and produce results in hours. In recent years, portable “point-of-care” systems have been developed that use microliters of blood to get similar results in about 30 minutes.

But point-of-care systems can be very expensive since most use pricey optical components to detect the biomarkers. They also capture only a small number of proteins, many of which are among the more abundant ones in blood. Any efforts to decrease the price, shrink down components, or increase protein ranges negatively impacts their sensitivity.

In their work, the researchers wanted to shrink components of the magnetic-bead-based assay, which is often used in labs, onto an automated microfluidics device that’s roughly several square centimeters. That required manipulating beads in micron-sized channels and fabricating a device in the Microsystems Technology Laboratory that automated the movement of fluids.

The beads are coated with an antibody that attracts IL-6, as well as a catalyzing enzyme called horseradish peroxidase. The beads and blood sample are injected into the device, entering into an “analyte-capture zone,” which is basically a loop. Along the loop is a peristaltic pump — commonly used for controlling liquids — with valves automatically controlled by an external circuit. Opening and closing the valves in specific sequences circulates the blood and beads to mix together. After about 10 minutes, the IL-6 proteins have bound to the antibodies on the beads.

Automatically reconfiguring the valves at that time forces the mixture into a smaller loop, called the “detection zone,” where they stay trapped. A tiny magnet collects the beads for a brief wash before releasing them around the loop. After about 10 minutes, many beads have stuck on an electrode coated with a separate antibody that attracts IL-6. At that time, a solution flows into the loop and washes the untethered beads, while the ones with IL-6 protein remain on the electrode.

The solution carries a specific molecule that reacts to the horseradish enzyme to create a compound that responds to electricity. When a voltage is applied to the solution, each remaining bead creates a small current. A common chemistry technique called “amperometry” converts that current into a readable signal. The device counts the signals and calculates the concentration of IL-6.

“On their end, doctors just load in a blood sample using a pipette. Then, they press a button and 25 minutes later they know the IL-6 concentration,” Wu says.

The device uses about 5 microliters of blood, which is about a quarter the volume of blood drawn from a finger prick and a fraction of the 100 microliters required to detect protein biomarkers in lab-based assays. The device captures IL-6 concentrations as low as 16 picograms per milliliter, which is below the concentrations that signal sepsis, meaning the device is sensitive enough to provide clinically relevant detection.

A general platform

The current design has eight separate microfluidics channels to measure as many different biomarkers or blood samples in parallel. Different antibodies and enzymes can be used in separate channels to detect different biomarkers, or different antibodies can be used in the same channel to detect several biomarkers simultaneously.

Next, the researchers plan to create a panel of important sepsis biomarkers for the device to capture, including interleukin-6, interleukin-8, C-reactive protein, and procalcitonin. But there’s really no limit to how many different biomarkers the device can measure, for any disease, Wu says. Notably, more than 200 protein biomarkers for various diseases and conditions have been approved by the U.S. Food and Drug Administration.

“This is a very general platform,” Wu says. “If you want to increase the device’s physical footprint, you can scale up and design more channels to detect as many biomarkers as you want.”

The work was funded by Analog Devices, Maxim Integrated, and the Novartis Institutes of Biomedical Research.

Uncovering the riches of traditional global medicine

Kava (Piper methysticum) is a plant native to the Polynesian islands that people there have used in a calming drink of the same name in religious and cultural rituals for thousands of years. The tradition of cultivating kava and drinking it during important gatherings is a cultural cornerstone shared throughout much of Polynesia, although the specific customs — and the strains of kava — vary from island to island. Over the past few decades, kava has been gaining interest outside of the islands for its pain-relief and anti-anxiety properties as a potentially attractive alternative to drugs like opioids and benzodiazepines because kavalactones, the molecules of medicinal interest in kava, use slightly different mechanisms to affect the central nervous system and appear to be non-addictive. Kava bars have been springing up around the United States, kava supplements and teas lining the shelves at stores like Walmart, and sports figures in need of safe pain relief are touting its benefits.

This growing usage suggests that there would be a sizeable market for kavalactone-based medical therapies, but there are roadblocks to development: for one, kava is hard to cultivate, especially outside of the tropics. Kava takes years to reach maturity and, as a domesticated species that no longer produces seeds, it can only be propagated using cuttings. This can make it difficult for researchers to get a large enough quantity of kavalactones for investigations or clinical trials.

Now, research from Whitehead Institute member and MIT associate professor of biology Jing-Ke Weng and postdoc Tomáš Pluskal, published online in Nature Plants July 22, describes a way to solve that problem, as well as to create kavalactone variants not found in nature that may be more effective or safer as therapeutics.

“We’re combining historical knowledge of this plant’s medicinal properties, established through centuries of traditional usage, with modern research tools in order to potentially develop new drugs,” Pluskal says.

Weng’s lab has shown that if researchers figure out the genes behind a desirable natural molecule — in this case, kavalactones — they can clone those genes, insert them into species like yeast or bacteria that grow quickly and are easier to maintain in a variety of environments than a temperamental tropical plant, and then get these microbial bio-factories to mass produce the molecule. In order to achieve this, first Weng and Pluskal had to solve a complicated puzzle: How does kava produce kavalactones? There is no direct kavalactone gene; complex metabolites like kavalactones are created through a series of steps using intermediate molecules. Cells can combine these intermediates, snip out parts of them, and add bits onto them to create the final molecule — most of which is done with the help of enzymes, cells’ chemical reaction catalysts. So, in order to recreate kavalactone production, the researchers had to identify the complete pathway plants use to synthesize it, including the genes for all of the enzymes involved.

The researchers could not use genetic sequencing or common gene editing tools to identify the enzymes because the kava genome is huge; it has 130 chromosomes compared to humans’ 46. Instead they turned to other methods, including sequencing the plant’s RNA to survey the genes expressed, to identify the biosynthetic pathway for kavalactones.

“It’s like you have a lot of Lego pieces scattered on the floor,” Weng says, “and you have to find the ones that fit together to build a certain object.”

Weng and Pluskal had a good starting point: They recognized that kavalactones had a similar structural backbone to chalcones, metabolites shared by all land plants. They hypothesized that one of the enzymes involved in producing kavalactones must be related to the one involved in producing chalcones, chalcone synthase (CHS). They looked for genes encoding similar enzymes and found two synthases that had evolved from an older CHS gene. These synthases, which they call PmSPS1 and PmSPS2, help to shape the basic scaffolding of kavalactones molecules.

Then, with some trial and error, Pluskal found the genes encoding a number of the tailoring enzymes that modify and add to the molecules’ backbone to create a variety of specific kavalactones. In order to test that he had identified the right enzymes, Pluskal cloned the relevant genes and confirmed that the enzymes they encode produced the expected molecules. The team also identified key enzymes in the biosynthetic pathway of flavokavains, molecules in kava that are structurally related to kavalactones and have been shown in studies to have anti-cancer properties.

Once the researchers had their kavalactone genes, they inserted them into bacteria and yeast to begin producing the molecules. This proof of concept for their microbial bio-factory model demonstrated that using microbes could provide a more efficient and scalable production vehicle for kavalactones. The model could also allow for the production of novel molecules engineered by combining kava genes with other genes so the microbes would produce modified kavalactones. This could allow researchers to optimize the molecules for efficiency and safety as therapeutics.

“There’s a very urgent need for therapies to treat mental disorders, and for safer pain relief options,” Weng says. “Our model eliminates several of the bottlenecks in drug development from plants by increasing access to natural medicinal molecules and allowing for the creation of new-to-nature molecules.”

Kava is only one of many plants around the world containing unique molecules that could be of great medicinal value. Weng and Pluskal hope that their model — combining the use of drug discovery from plants used in traditional medicine, genomics, synthetic biology, and microbial mass production — will be used to better harness the great diversity of plant chemistry around the world in order to help patients in need.

This work was supported by grants from the Smith Family Foundation, Edward N. and Della L. Thome Memorial Foundation, the Family Larsson-Rosenquist Foundation, and the National Science Foundation. Tomáš Pluskal is a Simons Foundation Fellow of the Helen Hay Whitney Foundation. Jing-Ke Weng is supported by the Beckman Young Investigator Program, Pew Scholars Program in the Biomedical Sciences, and the Searle Scholars Program.