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Researchers at Tokyo Institute of Technology have proposed a peptide sensor that can detect water-soluble polymers in wastewater. Water-soluble polymers are considered to be an important factor causing pollution at the same level as microplastics.
The new method uses the bonds that occur between peptides and various polymers to train machine learning algorithms that can determine and measure a large number of contaminants in a single solution.
From dying coral reefs to declining fish populations, ocean pollution caused by plastic is an emerging global problem. Most of the recent discussions about plastic pollution mainly involve microplastics-small pieces of plastic that are difficult to remove from the water.
However, people are increasingly interested in water-soluble synthetic polymers that are known to be sources of marine pollution, especially the threats they pose to the soil and water environment.
Since the polymer is water-soluble, it cannot be recovered by conventional filtration methods. The development of alternative methods to eliminate these pollutants is key. Therefore, understanding the exact nature of water-soluble polymer pollutants and measuring their content in wastewater has become the focus of attention of scientists.
Polymers are long-chain chemicals composed of smaller and repeating units. Although they have little connection with the term, proteins can also be considered polymers because they are composed of thousands of subunits called "amino acids." This short chain of amino acids is called a peptide.
Peptides can participate in specific and non-specific interactions with molecules (such as polymers) in various methods with different levels of affinity. In a new study reported in the journal ACS Applied Materials & Interfaces, scientists at Tokyo Tech have used this interaction to design a new peptide sensor for identifying water-soluble polymers in mixed solutions. Things.
Our technology relies on machine learning model analysis that simulates mammalian smell and taste recognition. Just like how our nose and tongue use a limited number of receptor proteins to distinguish countless odors and tastes, our single peptide sensor can also be used to detect multiple polymers and other molecules.
Takeshi Serizawa, Research Director and Professor, Tokyo Institute of Technology
The research team developed the method using a peptide linked to a synthetic polymer called poly(N-isopropylacrylamide) (PNIPAM). In addition, they activated a fluorescent "tag" called N-(1-anilinonaphthyl-4)maleimide (ANM) in the peptide to help obtain signals for its different interactions.
The fluorescence of ANM varies depending on protein interactions, thereby providing a detectable signal. The scientists quantified the signal from ANM in the well-known solution concentration of various polymers and used it to train the so-called "linear discriminant analysis" algorithm. This is considered to be one of the monitored machine learning.
The researchers validated their method with unfamiliar samples and found that sensors and algorithms can determine the polymer in the mixed solution.
In addition, after adding a small amount of sodium chloride or ethanol to the solution to slightly change the chemical interaction, machine learning algorithms can distinguish polymers with similar properties. Finally, the researchers tested new peptide sensors and algorithms in actual wastewater, and verified the potential of detecting various water-soluble polymers.
Our technology can be used not only to detect macromolecular pollutants such as polymers dissolved in water, but also to analyze how they enter the environment.
Takeshi Serizawa, Research Director and Professor, Tokyo Institute of Technology
The research team plans to extend the technology to other polymers and peptides. This effective research helps repair and protect the marine environment.
Suzuki, S., etc. (2021) Identify water-soluble polymers by distinguishing multiple light signals from a single peptide sensor. ACS applied materials and interfaces. doi.org/10.1021/acsami.1c11794.
Source: https://www.titech.ac.jp/english
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