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Maude M. David

Assistant Professor
Department of Microbiology

Maude M. David

Assistant Professor
Department of Microbiology

Dr. David is accepting new graduate students.


Dr. Maude M. David work focused on microbiota-gut-brain axis and applying new analytical methods to analyze multi-omics microbial datasets. After two postdoctoral positions at Lawrence Berkeley National Laboratory and Stanford School of Medicine, she joined Oregon State University as an Assistant Professor in January 2018, where she has a joined appointment in Microbiology and Pharmaceutical Sciences.


Dr. Maude David's laboratory studies the gut-brain axis, to understand how microbes can impact our behavior, specifically in Autism Spectrum Disorder and Anxiety. She uses a crowd-sourced approach to collect lifestyle type information, diet habits, and samples. Her team is also working on identifying bottlenecks in microbial ecology and bioinformatics, bringing novel solutions to unravel microbial molecular mechanisms by applying notably deep learning approaches to microbiome datasets.

Research Interests

  • Computational Biology
  • Artifical Intelligence
  • Microbial Ecology
  • Microbiota-Gut-Brain axis


Ph.D. Ecole Centrale de Lyon, U. of Lyon, France

Postdoctoral researcher, Lawrence Berkeley National Laboratory

Postdoctoral researcher, Stanford School of Medicine

College strategic research areas

Biomedical Science


  • Morton JT, Jin DM, Mills RH, Shao Y, Rahman G, McDonald D, Zhu Q, Balaban M, Jiang Y, Cantrell K, Gonzalez A, Carmel J, Frankiensztajn LM, Martin-Brevet S, Berding K, Needham BD, Zurita MF, David MM. Multi-level analysis of the gut–brain axis shows autism spectrum disorder-associated molecular and microbial profiles. 2023.
  • Deitzler GE, Martin A, Singla P, Phillips A, David MM. Supplementation of Clostridiales affects microbial profile and induces sex- specific social behavior deficits in mice following prenatal immune insult. 2023.
  • Pope Q, Varma R, Tataru C, David MM, Fern X. Learning a deep language model for microbiomes: the power of large scale unlabeled microbiome data. 2023. bioRxiv 2023.07.17.549267; doi:
  • Tataru C, Peras M, Rutherford E, Dunlap K, Yin X, Chrisman BS, DeSantis TZ, Wall DP, Iwai S, David MM. Topic modeling for multi-omic integration in the human gut microbiome and implications for Autism. 2023.
  • Tataru C, Eaton A, David MM. GMEmbeddings: An R Package to Apply Embedding Techniques to Microbiome Data. Front Bioinform. 2022 Apr 26;2:828703. doi: 10.3389/fbinf.2022.828703. PMID: 36304322; PMCID: PMC9580954.
  • David MM, Tataru C, Pope Q, Baker LJ, English MK, Epstein HE, Hammer A, Kent M, Sieler MJ Jr, Mueller RS, Sharpton TJ, Tomas F, Vega Thurber R, Fern XZ. Revealing General Patterns of Microbiomes That Transcend Systems: Potential and Challenges of Deep Transfer Learning. mSystems. 2022 Feb 22;7(1):e0105821. doi: 10.1128/msystems.01058-21. Epub 2022 Jan 18. PMID: 35040699; PMCID: PMC8765061.
  • Deitzler GE, Bira NP, Davidson JR, David MM. An open-source, low-cost voluntary running activity tracking tool for in vivo rodent studies. PLoS One. 2022 Sep 9;17(9):e0273865. doi: 10.1371/journal.pone.0273865. PMID: 36084055; PMCID: PMC9462748.
  • West KA, Yin X, Rutherford EM, Wee B, Choi J, Chrisman BS, Dunlap KL, Hannibal RL, Hartono W, Lin M, Raack E, Sabino K, Wu Y, Wall DP, David MM, Dabbagh K, DeSantis TZ, Iwai S. Multi-angle meta-analysis of the gut microbiome in Autism Spectrum Disorder: a step toward understanding patient subgroups. Sci Rep. 2022 Oct 11;12(1):17034. doi: 10.1038/s41598-022-21327-9. PMID: 36220843; PMCID: PMC9554176.
  • David MM, Tataru C, Daniels J, Schwartz J, Keating J, Hampton-Marcell J, Gottel N, Gilbert JA, Wall DP. Children with Autism and Their Typically Developing Siblings Differ in Amplicon Sequence Variants and Predicted Functions of Stool-Associated Microbes. mSystems. 2021 Apr 6;6(2):e00193-20. doi: 10.1128/mSystems.00193-20. PMID: 33824194; PMCID: PMC8561662.
  • Tataru, C. and David, M.M. 2020. Decoding the language of microbiomes using word-embedding techniques, and applications in inflammatory bowel disease. PLoS Comput Biol 4;16(5):e1007859. doi: 10.1371/journal.pcbi.1007859.
  • Chrisman BS, Paskov KM, Stockham N, Jung JY, Varma M, Washington PY, Tataru C, Iwai S, DeSantis TZ, David M, Wall DP. Improved detection of disease-associated gut microbes using 16S sequence-based biomarkers. BMC Bioinformatics. 2021 Oct 19;22(1):509. doi: 10.1186/s12859-021-04427-7. PMID: 34666677; PMCID: PMC8527694.
  • David MM. The Role of the Microbiome in Autism: All That We Know about All That We Don't Know. mSystems. 2021 Apr 6;6(2):e00234-21. doi: 10.1128/mSystems.00234-21. PMID: 33824195; PMCID: PMC8546973.
  • David MM, Tataru C, Daniels J, Schwartz J, Keating J, Hampton-Marcell J, Gottel N, Gilbert JA, Wall DP. Children with Autism and Their Typically Developing Siblings Differ in Amplicon Sequence Variants and Predicted Functions of Stool-Associated Microbes. mSystems. 2021 Apr 6;6(2):e00193-20. doi: 10.1128/mSystems.00193-20. PMID: 33824194; PMCID: PMC8561662.
  • Kimbrel, J.A., Ballor, N., Wu, Y.W., David, M.M., Hazen, T.C., Simmons, B.A., Singer, S.W. and Jansson, J.K. 2018. Microbial Community Structure and Functional Potential Along a Hypersaline Gradient. Front Microbiol. 9:1492.
  • Diaz-Beltran, L., Esteban, F.J., Varma, M., Ortuzk, A., David, M. and Wall, D.P. 2017. Cross-disorder comparative analysis of comorbid conditions reveals novel autism candidate genes. BMC Genomics 19(1):315.
  • David, M.M., Enard, D., Ozturk, A., Daniels, J., Jung, J.Y., Diaz-Beltran, L., and D.P. Wall. 2016. Comorbid analysis of genes associated with autism spectrum disorders reveals differential evolutionary constraints. 2016. PloS ONE 11(7)e0157937.
  • Hultman, J., Waldrop, M.P., Mackelprang, R., David, M., McFarland, J., Blazewicz, S.J., Harden, J., Turetsky, M.R., McGuire, A.D., Shah, M.B., VerBerkmoes, N.C., Lee, L.H., Mavrommatis, K., and Jansson, J.K. 2015. Multi-omics of permafrost, active layer and thermokarst bog soil microbiomes. Nature 521(7551):208-212.
  • Sochat, V., David, M., and Wall, D.P. 2015. Translational meta-analytical methods to localize the regulatory patterns of neurological disorders in the human brain. AMIA Ann. Symp. Proc. 2015, 2073.
  • David, M.M., Cecillon, S., Warne, B., Prestat, E., Jansson, J.K., and Vogel, T.M. 2015. Microbial ecology of chlorinated solvent biodegradation. Environ. Microbiol. 17(12):4835-4850.
  • Prestat, E., David, M.M., Hultman, J., Tas, N., Lamendella, R., Dvornik, J., Mackelprang, R., Myrold, D.D., Jumpponen, A., Tringe, S.G., Holman, E., Mavromatis, K. and Jansson, J.K. 2014. FOAM (Functional Ontology Assignments for Metagenomes): A hidden Markov Model (HMM) database with environmental focus. Nucleic Acids Res. 42(10):e145-e145.
  • Bravo, D., Martin, G., David, M.M., Cailleau, G., Verrecchia, E. and Junier, P. 2013. Identification of active oxalotrophic bacteria by Bromodeoxyuridine DNA labeling in a microcosm soil experiment. FEMS Microbiol. Letts. 348(2):103-111.
  • Mackelprang, R., Waldrop, M.P., DeAngelis, K.M., David, M.M., Chavarria, K.L., Blazewicz, S.J., Rubin, E.M., and Jansson, J.K. 2011. Metagenomic analysis of a permafrost microbial community reveals a rapid response to thaw. Nature 480 (7377):368-371.