“Native DNA is so highly sought after that people are looking for proxy data, and one of the big proxy data is the microbiome,” Yracheta said. “If you are an Aboriginal person, you have to take all of these variables into account if you want to protect your people and your culture.
In a presentation at the conference, Joslynn Lee, a member of the Navajo, Laguna Pueblo and Acoma Pueblo Nations and biochemist at Fort Lewis College in Durango, Colo., Spoke about her experience tracking changes in microbial communities in rivers that have experienced a mining wastewater spill in Silverton, Colorado. Dr Lee also offered practical advice on how to plan a microbiome analysis, from collecting a sample to processing it.
In a data science career panel, Rebecca Pollet, biochemist and member of the Cherokee Nation, noted how many traditional pharmaceutical drugs have been developed based on the traditional knowledge and plant medicine of indigenous peoples. The antimalarial drug quinine, for example, was developed from the bark of a species of cinchona, which the Quechua people historically used as a medicine. Dr Pollet, who studies the effects of pharmaceutical drugs and traditional foods on the gut microbiome, asked, “How do we honor this traditional knowledge and compensate for what has been covered up? “
One participant, Elder Lakota Les Ducheneaux, added that he believed medicine derived from traditional knowledge wrongly suppressed prayers and rituals that traditionally accompanied treatment, making medicine less effective. “You have to constantly weigh the scientific part of medicine with the cultural and spiritual part of what you do,” he said.
IndigiData in the future
During the IndigiData conference, attendees also discussed ways to empower their own data to serve their communities.
Mason Grimshaw, data scientist and member of the board of directors of Indigenous in AI., spoke about his research with linguistic data on the Wakashan International AI Consortium. The consortium, led by engineer Michael Running Wolf, is developing an automatic speech recognition AI for Wakashan languages, a family of endangered languages spoken in several First Nations communities. Researchers believe that automatic speech recognition models can preserve mastery of the Wakashan languages and revitalize their use by future generations.
