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Lemay Lab
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LEMAY LAB

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    • Danielle G. Lemay, Ph.D.

      Research Leader / Research Molecular Biologist

      Associate Adjunct Professor, UC Davis Department of Nutrition

      Faculty Member, UC Davis Genome Center

      Office: (530) 752-4748

      Email address: danielle.lemay@usda.gov

      Google Scholar page

      Research Interests

      Does what you eat affect your gastrointestinal health? Should dietary guidance depend on your gut microbiome? Dr. Lemay is interested in how dietary components, especially fermentable carbohydrates, affect host response and whether that response is modulated by the functional capabilities of resident microbiota. The lab also applies big data techniques, such as sequencing technologies and machine learning, to understand the effects of diet on human health.

      Lemay Lab Themes

      1. Effect of diet on intestinal inflammation

      • Ex vivo experiments to determine effect of fermentations (from Kable Lab) and/or dietary components on intestinal epithelial cells

      • Assessment of gut barrier function and/or GI inflammation in clinical trials

      2. Methods of quantifying microbial consortia function (functional metagenomics, metatranscriptomics); application of these methods to understand diet-microbe host relationships

      3. Stool and plasma markers for GI inflammation and/or GI barrier function

      4. Application of big data techniques (omics and machine learning) to dietary data and nutritional phenotyping in order to build models for personalized nutrition.

      Historically, the Lemay Lab has focused on milk science—everything from how genes are regulated to produce milk to how dairy consumption affects the consumer. We continue to work on milk-themed projects but will more broadly include studies of other dietary components in the future.


    • ARS Employees

      Zeynep Alkan, Chemist (Lab Manager)

      Postdoctoral Research Associates

      Elizabeth Chin, PhD, 2018-Present

      Zhengyao "Zeya" Xue, PhD, 2019-Present

      Graduate Students

      Yasmine Bouzid, PhD student, Graduate Group in Nutritional Biology, 2019-Present

      Ismael Acedo, PhD student rotation, Integrated Genetics and Genomics Graduate Group, Fall 2019

      Undergraduate Students

      Sarah Spearman, 2018-Present

      Alumni

      Emily Yamashita, Undergraduate, 2018-2019, Graduated 2019

      Gabriel Simmons, 2019, co-mentored with Ilias Tagkopoulis, Graduated 2019

      Michelle Treiber, UC Davis Junior Specialist (Bioinformatics), 2017-2018

      Samuel Westreich, PhD, Integrative Genetics and Genomics, Graduated December 2017

      Chad Masarweh, PhD student rotation, Microbiology, Winter Quarter 2017

      Yuchen Li, Statistics, PhD student project, Spring Quarter 2017

      Eric Kwok, BS, Genetics, Graduated 2017

      Seren Pollard, Undergraduate Intern from University College Dublin 2017

      Shannon Joslin, PhD program, Genetics, July 2016-June 2017

      Kristen Beck, PhD, Biochemistry, Molecular, Cellular and Developmental Biology, Graduated 2015

      Pedro Ivo Silva, undergraduate intern summer 2013

      Matthew Porter, MS student summer 2013

      Gina Turco, PhD student rotation, 2012

      Stella Hartono, PhD student rotation, 2011

    • Methods and Technique

      The Lemay Lab develops methods for omics experiments, especially functional metagenomics and metatranscriptomics, and for multi-omics integration and analysis. Endpoints analyzed in the Lemay Lab:

      • Metagenomics/metatranscriptomics assessment of human gut microbial communities

      • Stool and plasma biomarkers of gastrointestinal health

      • Trans-epithelial resistance of intestinal epithelial cells; inflammatory response

      We also apply machine learning methods for dietary analysis and human health outcomes.

      Software

      SAMSA2: a standalone metatranscriptome analysis pipeline

      SAMSA: a comprehensive metatranscriptome analysis pipeline

      The Gene Neighborhood Scoring Tool (G-NEST) G-NEST combines genome location, gene expression, and evolutionary sequence conservation data to score putative gene neighborhood locations in eukaryotic genomes.

      The Globulator Given images of slides of milk, the Globulator software automates the quantification of milk fat globules and nucleic acids (DNA, RNA)."