2021 FDA-NIH-NIST-USDA Joint Agency Microbiome (JAM) Symposium
FDA-NIH-NIST-USDA
Welcome to the Virtual Poster Session for the 2021 JAM Annual Symposium! Note that posters will be accessible for attendees to peruse throughout the 2-day symposium.
The Joint Agency Microbiome (JAM) Working Group's mission is to communicate, across Federal Agencies, ongoing microbiome-focused research. The JAM was founded in 2017 by researchers from FDA and NIH. In 2019, NIST joined the JAM. And in 2021, USDA joined the JAM. The JAM has quarterly virtual meetings and an annual face-to-face meeting. Albeit the 2021 annual face-to-face meeting is being held virtually due to the pandemic.
Bacteriomic analyses of Asian citrus psyllid and citrus samples infected with ‘Candidatus Liberibacter asiaticus’ in southern California and HLB management implications
Jianchi Chen
The Neuro-Endo-Microbio-OmeStudy: Neurobiological Alterations in Bariatric Surgery
K. Agarwal; K. A. Maki; C. Vizioli; S. Carnell; E. Goodman; M. Hurley; C. Harris; R. Colwell; K. Steele; P.V. Joseph
Background: Plausible mechanisms regarding physiologic effects and resulting weight loss following bariatric surgery include neural contributions, gut hormones and microbiome changes.. This pilot study aims to study the associations and inter-relationships of these factors comparing vertical sleeve gastrectomy (VSG), Roux-en Y gastric bypass (RYGB) to medical weight loss (MWL).
Methods: BS subjects included VSG, n=7 and RYGB, n=9 versus non-BS/MWL, n=6 as controls. Ghrelin, glucagon peptide-1 (GLP1), peptide-YY (PYY), gut microbiome, and resting state functional magnetic resonance imaging (rsfMRI; using fractional amplitude of low-frequency fluctuations [fALFF]) were measured pre and post-BS and MWL in both fasting and fed states. We explored phenotype characterization using clustering on gut hormone, microbiome and rsfMRI and a combined analysis.
Results: More fALFF differences were seen in post-BS versus post-MWL In fed state, fALFF amplitude decreased in food reward regions post-BS. Differential relative abundance of several gut microbiome bacterial species increased post-BS. The combined gut hormone, microbiome, and rsfMRI analysis most accurately clustered samples into pre- and post-BS groups.
Conclusion: Post-BS appears to have greater phenotypic differences in interactions of the gut hormone, microbiome and rsfMRI versus MWL. These results will inform future prospective research studying gut-brain changes post-BS.
Microbiome Diversity in Psyllids, "Non-vector" compared to a "vector" of Huanglongbing
Wayne B. Hunter, Douglas S. Stuehler, Jawwad Qureshi, Surya Saha, Liliana M. Cano
Effects of consuming cooked rice with different levels of resistant starch on intestinal microbial composition in a rodent model
Jiawei Wan†, ‡, §, ‖, Yanbei Wu‡, §,⊥, Quynhchi Pham‡, Robert W. LiΔ, Liangli Yu§, Ming-Hsuan Chen#, Stephen M. Boue+, Wallace Yokoyama〒, Bin Li†, ‖*, Thomas T.Y. Wang‡*
Organic soil amendments influence taxonomic and functional variation of bacteria in the soil microbiome
Nicholas LeBlanc
ONE HEALTH MICROBIOME RESEARCH ACROSS FDA CENTERS Contributed by the Microbiome Working Group (MWG)
Silvia Pineiro, Andrea Ottesen, Daniel Tadesse, Jennifer Brzezinski, Paul Morin, Paul Carlson, Siobhan Cowley, Kathleen Clouse, Odile Engel, Joseph Briggs, Alyxandria Schubert, David Craft, Aimee Cunningham, Bruce Erickson, Sangeeta Khare, Khaled Bouri, Shari Solomon, Lauren Viebrock, Jayanthi Gangiredla, Carmen Tartera
Deciphering the role of gut microbiota in drug-induced inflammation through Single Cell analysis
Soumen Roy1*, Carolyne Smith1, Ratnadeep Mukherjee2, Raquel Costa1, Lauren Amble1, Jonathan Badger1, Amiran Dzutsev1, April Huang1, Simone Difilippantonio3, Sharon Bargo1, Gregoire Altan-Bonnet2, Giorgio Trinchieri1
Microbial Communities Associated With Soil Health In Wheat
Daniel C. Schlatter, Jeremy Hansen, David R Huggins, Brian Carlson, Timothy C. Paulitz
Geographic variation in the oral microbiome of NIH-AARP Diet and Health Study participants
Ian D. Buller, Emily Vogtmann, Mary H. Ward, Christian Abnet, Rashmi Sinha, Linda M. Liao, Yunhu Wan, Mitchell H. Gail, Rena R. Jones
Unsupervised analysis methods for flow cytometry data from microbial reference materials
Kirsten Parratt, Sandra Da Silva, Joy Dunkers, Monique Hunter, Stephanie Servetas, Scott Jackson, Nancy J. Lin
Evaluation of Candidate NIST Whole Cell Reference Material
Monique E. Hunter, Kirsten H. Parratt, Stephanie L. Servetas, Jennifer N. Dootz, Jason G. Kralj, Samuel P. Forry, Nancy J. Lin, Scott A. Jackson
Evaluation of alcohol-free mouthwash for studies of the oral microbiome
Yukiko Yano, Emily Vogtmann, Alaina Shreves, Stephanie Weinstein, Mia Gaudet, Amanda Black, Norma Diaz-Mayoral, Bari Ballew, Yunhu Wan, Xing Hua, Casey Dagnall, Amy Hutchinson, Kristine Jones, Kathleen Wyatt, Nicolas Wentzensen, Christian Abnet
Quantifying Genome Copies of a Candidate Whole Cell E. coli Reference Material
Joy P. Dunkers, Sandra M. Da Silva, Kirsten H. Parratt, Samuel T. Hailemichael, Guilherme Pinheiro*, Stephanie L. Servetas, Jason G. Kralj and Nancy J. Lin
NIST is developing a viable whole cell RM as a surrogate for microbial targets of interest to assess workflow parameters such as sampling or DNA extraction efficiency, cell count, limit of detection, and bioinformatics pipelines. A nonpathogenic Escherichia coli (NIST0056) candidate RM is being characterized for total and viable cell number and genome copies/cell using flow cytometry, digital droplet PCR (ddPCR) and wide-field microscopy.
Engineering Complex Whole Cell Microbial Reference Materials
S.L. Servetas, J. N. Dootz, M.E. Hunter, S. P. Forry, S. A. Jackson
“Comparative analysis of leaf-associated bacterial and fungal microbiomes of resistant and susceptible corn inbred lines subjected to Tar-spot disease”
Raksha Singh, Charles Crane and Stephen B. Goodwin
Metagenomic NGS (mNGS) Performance Metrics Using an Organism-centric Approach
Jason G. Kralj, Stephanie L. Servetas, Samuel P. Forry, Scott A. Jackson