A new computer language helps to notice hidden pollutants

Mass spectrometry data is like a chemical fingerprint, showing scientists who are molecules in a pattern such as air, water or blood and in quantity. It helps recognize everything from pollutants in water to chemicals in new medicines.

Developed at UC Riverside, a massive language or massql language, functions like a search engine for mass spectrometry data, allowing researchers to find patterns that would otherwise require advanced programming skills. Technical details about language and an example of how to help identify chemicals that slow down the flames in public waterways, are described in a new Nature methods An article in a journal.

“We wanted to give chemists and biologists, who are generally not computer scientists, the ability to dig their data accurately as they want, without having to spend months or years learning to code,” said Mingxun Wang, Assistant Professor UCR, Informatics, who created the language.

Showing the efficiency of the language, Nina Zhao, UCRA postdoctoral student now at the UC San Diego, used Massql to sift throughout the world’s massive spectrometry data on water samples available to the public. She was looking for organophosphate estere, which are usually found with flame retards.

“There is literally billions of molecule measurements in these data. You can’t go hand at hand,” Wang said. “However, the language acts like a filter, in a sense, for these chemicals, and has pulled them thousands.”

In addition to finding famous chemicals in water samples, they also found organophosphate compounds that were not previously described or cataloged, and some chemicals that are the product of organophosphate that decay over time.

“These chemicals can cause a lot of problems for human health and animals, and for the whole ecosystems. They have designed to be flames or plasticizers, but they can cause disorders of the endocrine and sexual systems, as well as cardiovascular problems,” Zhao said.

Before plans for handling or removing toxic chemicals from our environment can be made, scientists need to know what is present. Here Massql is good for scientists like Zhao.

“The language allows me to follow everything that has ever been discovered in all air, soil, water, and even to the human body. Whatever exists, we can look for chemicals there,” she said.

One of the challenges in the creation of MassqL was to achieve a consensus of scientists about life to agree on the definition of terms that the software would use. “Both chemists and computer scientists have to understand this, and the software must be able to work on it,” Wang said.

For this reason, about 70 scientists were advised at the development phase. They all provided their feedback on the most important conditions of information and how to express them in Massql.

The research team also wanted to show that language could be useful in different real situations. In addition to Zhao’s project, the work is described in detail by more than 30 applications where Massql can be applied.

Cases of sample use include detection of fatty acids as alcohol poisoning markers, seeking new medicines to resolve the crisis of antibiotics resistance crisis, learning about chemicals that bacteria use to communicate with each other and find a chemical on the playground forever.

In the past, Wang would receive software requirements that could seek data forms specific to all these different types of apps.

“I thought I could do something to save time,” he said. “I wanted to create a language that could handle several types of inquiries. And now we have. I am excited when I hear the discovery that could come from this.”