Researchers from University of California San Diego, as part of a large collaboration with scientists around the world, have developed a new search tool to help researchers better understand the metabolism of microorganisms. Microbes are key players in virtually all biological and environmental systems, yet limitations in current techniques used to study microbial metabolism make it difficult to decode their interactions and activities.
The new research, published February 5, 2023 in Nature Microbiology, directly addresses these limitations, which could ultimately transform our understanding of both human health and the environment.
"Humans are walking ecosystems in which microbes vastly outnumber us, but we know so little about the metabolites that microbes produce," said senior study author Pieter Dorrestein, PhD, professor of pharmacology and pediatrics at UC San Diego School of Medicine and professor at Skaggs School of Pharmacy and Pharmaceutical Sciences at UC San Diego. "This technology allows us to match microbes to the metabolic signatures they produce without any prior knowledge, which represents a major leap forward in our ability to study microorganisms and their intricate relationships with humans and ecosystems."
The groundbreaking tool, which the scientists call microbeMASST, was developed by scientists at UC San Diego's Collaborative Microbial Metabolite Center, an NIH-supported initiative that aims to build an internationally-curated repository of microbial metabolomics data to help researchers studying the complex interaction between microbes and humans.
Beneficial microbes play a key role in human health by colonizing certain areas of the body, including the skin, where they protect us against external pathogens, and the gut, where they contribute to essential functions such as nutrient absorption and regulating the immune system. Disruption of the microbial communities in our body is associated with a wide range of diseases.
"This resource will help us mechanistically interrogate the role of the microbiome in health conditions such as liver disease, inflammatory bowel disease, diabetes, atherosclerosis and others," added Dorrestein.
Microbes are also at the center of important environmental processes, such as the carbon and nitrogen cycles. When microbial communities involved in these processes are disrupted, it can become harder for ecosystems to cycle nutrients, leading to a wide range of destructive ecological imbalances.
Because of their crucial role in the environment and their interactions with larger organisms, the metabolism of microbes is a driving force in virtually all aspects of biology. However, the vast metabolic potential of microbial communities is often overlooked in modern experiments, which generally only look at microbial metabolism with a wide lens.
"One of the challenges of studying microbes at the molecular level is that it's difficult to tell which microbes are producing which molecules unless you already know what you're looking for," said first author Simone Zuffa, a postdoctoral researcher working with Dorrestein. "If you think of colonies of microbes as crowded parties with lots of people talking, our current experiments can only record the sound, but we want to figure out a way to unscramble that audio to figure out who is saying what."
To help produce the new search tool, which the researchers have called microbeMASST, researchers from the Collaborative Microbial Metabolite Center at UC San Diego collected more than 100 million data points from 60,000 distinct microbial samples, gathered by scientists from across the world. This database has been meticulously curated from community contributions and metadata curation, and includes microbes from plants, soils, oceans, lakes, fish, terrestrial animals and humans.
By cross-referencing an experimental sample with this massive library of individual microbes, microbeMASST can detect which microbes are present in that sample.
"There's no existing tool that can do this, and ours can do it in seconds," added Zuffa.
Because microbeMASST can identify microbes in a sample without any prior knowledge, the researchers are confident that the applications of the technology extend into various fields of biology, such as aquaculture, agriculture, biotechnology, and studying microbial-mediated health conditions.
"We anticipate that microbeMASST will be a transformative resource for the life sciences research community," said Dorrestein. "Further, the tool will only improve over time as the community gathers more data for the system to reference."
Full link to study: https://www.nature.com/articles/s41564-023-01575-9
UC San Diego co-authors on the study include: Simone Zuffa, Robin Schmid, Anelize Bauermeister, Paulo Wender P. Gomes, Andres M. Caraballo-Rodriguez, Yasin El Abiead, Jasmine Zemlin, Michael J. Meehan, Allegra T. Aron, Nicole E. Avalon, Nuno Bandeira, William H. Gerwick, Ekaterina Buzun, Marvic Carrillo Terrazas, Chia-Yun Hsu, Renee Oles, Adriana Vasquez Ayala, Jiaqi Zhao, Hiutung Chu, Mirte C. M. Kuijpers, Sara L. Jackrel, Benjamin S. Pullman, Rob Knight and Daniel McDonald.
Additional co-authors include: Alegra T. Aron at University of Denver, Emily C. Gentry at Virginia Tech, Robert H. Cichewicz at University of Oklahoma, Fidele Tugizimana, Lerato Pertunia Nephali and Ian A. Dubery at University of Johannesburg, Ntakadzeni Edwin Madala at University of Venda, Eduarda Antunes Moreira, Leticia Veras Costa-Lotufo, Norberto Peporine Lopes and Paula Rezende-Teixeira at University of São Paulo, Paula C. Jimenez at Federal University of São Paulo, Bipin Rimal, Andrew D. Patterson, Matthew F. Traxler and Rita de Cassia Pessotti at Pennsylvania State University, Daniel Alvarado-Villalobos, Giselle Tamayo-Castillo, Priscila Chaverri, Efrain Escudero-Leyva and Luis-Manuel Quiros-Guerrero, at University of Costa Rica, Alexandre Jean Bory, Juliette Joubert, Adriano Rutz, Jean-Luc Wolfender and Pierre-Marie Allard at University of Geneva, Andreas Sichert and Sammy Pontrelli at ETH Zurich, Katia Gindro and Josep Massana-Codina at Agroscope, Berenike C. Wagner, Karl Forchhammer and Daniel Petras at University of Tuebingen, Nicole Aiosa and Neha Garg. At Georgia Institute of Technology, Manuel Liebeke and Patric Bourceau at Max Planck Institute for Marine Microbiology, Kyo Bin Kang at Sookmyung Women's University, Henna Gadhavi, Luiz Pedro Sorio de Carvalho and Mariana Silva dos Santos at The Francis Crick Institute, Alicia Isabel Pérez-Lorente, Carlos Molina-Santiago and Diego Romero at Universidad de Málaga-Consejo Superior de Investigaciones Científicas Raimo Franke and Mark Brönstrup at Helmholtz Centre for Infection Research, Arturo Vera Ponce de León, Phillip Byron Pope and Sabina Leanti La Rosa, Norwegian University of Life Sciences, Giorgia La Barbera and Henrik M. Roager at University of Copenhagen, Martin Frederik Laursen, Technical University of Denmark, Fabian Hammerle, Bianka Siewert and Ursula Peintner at University of Innsbruck, Cuauhtemoc Licona-Cassani and Lorena Rodriguez-Orduña at Tecnologico de Monterrey, Evelyn Rampler, Felina Hildebrand, Gunda Koellensperger, Harald Schoeny, Katharina Hohenwallner and Lisa Panzenboeck at University of Vienna, Rachel Gregor, at Massachusetts Institute of Technology, Ellis Charles O'Neill, Eve Tallulah Roxborough and Jane Odoi at University of Nottingham, Nicole J. Bale, Su Ding and Jaap S. Sinninghe Damsté at Netherlands Institute for Sea Research, Xue Li Guan at Nanyang Technological University, Jerry J. Cui and Kou-San Ju at The Ohio State University, Denise Brentan Silva and Fernanda Motta Ribeiro Silva at Federal University of Mato Grosso do Sul, Gilvan Ferreira da Silva at Embrapa Amazônia Ocidental, Hector H. F. Koolen at Universidade do Estado do Amazonas, Carlismari Grundmann at University of São Paulo, Ribeirão Preto, Jason A. Clement at Baruch S. Blumberg Institute, Hosein Mohimani at Carnegie Mellon University, Kirk Broders at the US Department of Agriculture, Kerry L. McPhail at Oregon State University, Sidnee E. Ober-Singleton at University of Oregon, Christopher M. Rath in Emmeryville CA and Mingxun Wang at University of California, Riverside.
This study was funded, in part, by the National Institutes of Health (grants U24DK133658, U19AG063744, 1DP2GM137413, F32AT011475, R01 GM107550, R01 GM137135, U01 DK119702, S10 OD021750, 1R01LM013115, 1R01GM132649, DP1AT010885, T32 DK007202), the National Science Foundation (grant 2152526), the U.S. Department of Agriculture, Agricultural Research Service, the National Research Foundation of Korea (grants NRF-2020R1C1C1004046, NRF-2022R1A5A2021216 and NRF-2022M3H9A2096191), the Austrian Science Fund (grant P31915), the German Research Foundation (grants EXC 2124 and TRR 261), the São Paulo Research Foundation (grants #2018/24865-4, #2019/03008-9, #2020/06430-0, #2022/12654-4, #2015/17177-6, #2020/02207-5, #2021/10603-0), National Council for Scientific and Technological Development (CNPq), the Research Council of Norway (grant 311913), the Novo Nordisk Foundation (grant NNF19OC0056246), the Independent Research Fund Denmark (grant 0171-00006B), ERA-Net Cofund project BlueBio (grant 311913), Fundação de Amparo à Pesquisa do Estado do Amazonas, Fundação de Apoio ao Desenvolvimento do Ensino, Ciência e Tecnologia do Estado de Mato Grosso do Sul - FUNDECT (grants 71/032.390/2022 and 311/2022), the Betty and Gordon Moore Foundation and the Max Planck Society.
