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Improving microbial phylogeny with citizen science within a mass-market video game

  • Roman Sarrazin-Gendron,
  • Parham Ghasemloo Gheidari,
  • Alexander Butyaev,
  • Timothy Keding,
  • Eddie Cai,
  • Jiayue Zheng,
  • Renata Mutalova,
  • Julien Mounthanyvong,
  • Yuxue Zhu,
  • Elena Nazarova,
  • Chrisostomos Drogaris,
  • Kornél Erhart,
  • David Bélanger,
  • Michael Bouffard,
  • Joshua Davidson,
  • Mathieu Falaise,
  • Vincent Fiset,
  • Steven Hebert,
  • Dan Hewitt,
  • Jonathan Huot,
  • Seung Kim,
  • Jonathan Moreau-Genest,
  • David Najjab,
  • Steve Prince,
  • Ludger Saintélien,
  • Amélie Brouillette,
  • Gabriel Richard,
  • Randy Pitchford,
  • Sébastien Caisse,
  • Mathieu Blanchette,
  • Daniel McDonald,
  • Rob Knight,
  • Attila Szantner,
  • Jérôme Waldispühl

摘要

Citizen science video games are designed primarily for users already inclined to contribute to science, which severely limits their accessibility for an estimated community of 3 billion gamers worldwide. We created Borderlands Science (BLS), a citizen science activity that is seamlessly integrated within a popular commercial video game played by tens of millions of gamers. This integration is facilitated by a novel game-first design of citizen science games, in which the game design aspect has the highest priority, and a suitable task is then mapped to the game design. BLS crowdsources a multiple alignment task of 1 million 16S ribosomal RNA sequences obtained from human microbiome studies. Since its initial release on 7 April 2020, over 4 million players have solved more than 135 million science puzzles, a task unsolvable by a single individual. Leveraging these results, we show that our multiple sequence alignment simultaneously improves microbial phylogeny estimations and UniFrac effect sizes compared to state-of-the-art computational methods. This achievement demonstrates that hyper-gamified scientific tasks attract massive crowds of contributors and offers invaluable resources to the scientific community.