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.
Courtesy: Dr Tedrick Thomas Salim Lew.
Scientists
from Disruptive & Sustainable Technologies for Agricultural Precision
(DiSTAP), an Interdisciplinary Research Group (IRG) 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 belowground 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.
This new
approach is described in a paper titled, "Plant Nanobionic Sensors for
Arsenic Detection," published recently in Advanced Materials. The paper
was led by Dr. Tedrick Thomas Salim Lew, a recent graduate student of the
Massachusetts Institute of Technology (MIT) and co-authored by Michael Strano,
co-lead principal investigator of DiSTAP and Carbon P. Dubbs Professor at MIT,
as well as Minkyung Park and Jianqiao Cui, both Graduate Students at MIT.
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 arsenic in soil as a result of
anthropogenic activities such as mining and smelting is also harmful to plants,
inhibiting growth and resulting in substantial crop losses. More troublingly,
food crops can absorb arsenic from the soil, leading to contamination of food
and produce consumed by humans. Arsenic in belowground 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.
These
novel optical nanosensors developed by SMART DiSTAP exhibit changes in their
fluorescence intensity upon the detection of arsenic. Embedded in plant tissues
with no detrimental effects on the plant, these sensors provide a
non-destructive 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.
Lead
author Dr. Tedrick Thomas Salim Lew said, "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 belowground environment, requiring less time, equipment, and manpower. We
envisage that this innovation will eventually see wide use in the agriculture
industry and beyond. I am grateful to SMART DiSTAP and Temasek Life Sciences
Laboratory (TLL), both of which were instrumental in idea generation,
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 species of fern 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
(ppb). 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. This is the first successful demonstration of living
plant-based sensors for arsenic and represents a groundbreaking advancement
which could prove highly useful in both agricultural research (e.g. to monitor
arsenic taken up by edible crops for food safety), as well as in 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.
SMART DiSTAP's novel method of coupling nanoparticle sensors with plants'
natural ability to efficiently extract analytes via the roots and transport
them 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 (CCD) camera, akin to a
smartphone camera.
Co-author,
DiSTAP co-lead Principal Investigator, and MIT Professor Michael Strano added,
"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."