Living plants detect arsenic by way of embedded nanosensors

There’s a lot of arsenic in the world and it’s often a factor in making water undrinkable. When that water is used in farming It also pollutes soil and enters food-producing plants. A December 11, 2020 news item on Nanowerk announces research into arsenic detectors in plants,

Researchers have developed a living plant-based sensor that can in real-time detect and monitor levels of arsenic, a highly toxic heavy metal, in the soil. Arsenic pollution is a major threat to humans and ecosystems in many Asia Pacific countries.

Caption: Non-destructive plant nanobionic sensor embedded within leaves to report arsenic levels within plants to portable electronics, enabling real-time monitoring of arsenic uptake in living plants. Credit: Dr. Tedrick Thomas Salim Lew

I was not able to find the source for the news item but I did locate something close. From a December 13, 2020 Singapore-Massachusetts Institute of Technology (MIT) Alliance for Research and Technology (SMART), also on EurekAlert,

Scientists from the Disruptive and Sustainable Technologies for Agricultural Precision (DiSTAP) research group at the Singapore-MIT Alliance for Research and Technology (SMART), MIT’s research enterprise in Singapore, have engineered a novel type of plant nanobionic optical sensor that can detect and monitor, in real time, levels of the highly toxic heavy metal arsenic in the underground environment. This development provides significant advantages over conventional methods used to measure arsenic in the environment and will be important for both environmental monitoring and agricultural applications to safeguard food safety, as arsenic is a contaminant in many common agricultural products such as rice, vegetables, and tea leaves.

Arsenic and its compounds are a serious threat to humans and ecosystems. Long-term exposure to arsenic in humans can cause a wide range of detrimental health effects, including cardiovascular disease such as heart attack, diabetes, birth defects, severe skin lesions, and numerous cancers including those of the skin, bladder, and lung. Elevated levels of soil arsenic as a result of anthropogenic activities such as mining and smelting are also harmful to plants, inhibiting growth and resulting in substantial crop losses.

Food crops can absorb arsenic from the soil, leading to contamination of food and produce consumed by humans. Arsenic in underground environments can also contaminate groundwater and other underground water sources, the long-term consumption of which can cause severe health issues. As such, developing accurate, effective, and easy-to-deploy arsenic sensors is important to protect both the agriculture industry and wider environmental safety.

The novel optical nanosensors exhibit changes in their fluorescence intensity upon detecting arsenic. Embedded in plant tissues, with no detrimental effects on the plant, these sensors provide a nondestructive way to monitor the internal dynamics of arsenic taken up by plants from the soil. This integration of optical nanosensors within living plants enables the conversion of plants into self-powered detectors of arsenic from their natural environment, marking a significant upgrade from the time- and equipment-intensive arsenic sampling methods of current conventional methods.

“Our plant-based nanosensor is notable not only for being the first of its kind, but also for the significant advantages it confers over conventional methods of measuring arsenic levels in the below-ground environment, requiring less time, equipment, and manpower,” says Lew. “We envision that this innovation will eventually see wide use in the agriculture industry and beyond. I am grateful to SMART DiSTAP and the Temasek Life Sciences Laboratory (TLL), both of which were instrumental in idea generation and scientific discussion as well as research funding for this work.”

Besides detecting arsenic in rice and spinach, the team also used a species of fern, Pteris cretica, which can hyperaccumulate arsenic. This fern species can absorb and tolerate high levels of arsenic with no detrimental effect — engineering an ultrasensitive plant-based arsenic detector, capable of detecting very low concentrations of arsenic, as low as 0.2 parts per billion. In contrast, the regulatory limit for arsenic detectors is 10 parts per billion. Notably, the novel nanosensors can also be integrated into other species of plants. The researchers say this is the first successful demonstration of living plant-based sensors for arsenic and represents a groundbreaking advancement that could prove highly useful in both agricultural research (e.g., to monitor arsenic taken up by edible crops for food safety) and general environmental monitoring.

Previously, conventional methods of measuring arsenic levels included regular field sampling, plant tissue digestion, extraction, and analysis using mass spectrometry. These methods are time-consuming, require extensive sample treatment, and often involve the use of bulky and expensive instrumentation. The new approach couples nanoparticle sensors with plants’ natural ability to efficiently extract analytes via the roots and transport them. This allows for the detection of arsenic uptake in living plants in real time, with portable, inexpensive electronics such as a portable Raspberry Pi platform equipped with a charge-coupled device camera akin to a smartphone camera.

Co-author, DiSTAP co-lead principal investigator, and MIT Professor Michael Strano adds, “This is a hugely exciting development, as, for the first time, we have developed a nanobionic sensor that can detect arsenic — a serious environmental contaminant and potential public health threat. With its myriad advantages over older methods of arsenic detection, this novel sensor could be a game-changer, as it is not only more time-efficient, but also more accurate and easier to deploy than older methods. It will also help plant scientists in organizations such as TLL to further produce crops that resist uptake of toxic elements. Inspired by TLL’s recent efforts to create rice crops which take up less arsenic, this work is a parallel effort to further support SMART DiSTAP’s efforts in food security research, constantly innovating and developing new technological capabilities to improve Singapore’s food quality and safety.”

The research is carried out by SMART and supported by the National Research Foundation (NRF) Singapore under its Campus for Research Excellence And Technological Enterprise (CREATE) program.

Led by MIT’s Strano and Singapore co-lead principal investigator Professor Chua Nam Hai, DiSTAP is one of the five Interdisciplinary Research Groups (IRGs) in SMART. The DiSTAP program addresses deep problems in food production in Singapore and the world by developing a suite of impactful and novel analytical genetic and biosynthetic technologies. The goal is to fundamentally change how plant biosynthetic pathways are discovered, monitored, engineered, and ultimately translated to meet the global demand for food and nutrients. Scientists from MIT, TTL, Nanyang Technological University, and National University of Singapore are collaboratively developing new tools for the continuous measurement of important plant metabolites and hormones for novel discovery, deeper understanding and control of plant biosynthetic pathways in ways not yet possible, especially in the context of green leafy vegetables; leveraging these new techniques to engineer plants with highly desirable properties for global food security, including high yield density production, drought and pathogen resistance and biosynthesis of high-value commercial products; developing tools for producing hydrophobic food components in industry-relevant microbes; developing novel microbial and enzymatic technologies to produce volatile organic compounds that can protect and/or promote growth of leafy vegetables; and applying these technologies to improve urban farming.

Here’s a link to and a citation for the paper,

Plant Nanobionic Sensors for Arsenic Detection by Tedrick Thomas Salim Lew, Minkyung Park, Jianqiao Cui, Michael S. Strano. Advanced Materials DOI: https://doi.org/10.1002/adma.202005683 First published: 26 November 2020

This paper is behind a paywall.

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