Community Highlight: Jia Wang
Jia Wang (JW) is a microbiologist with degrees in Chemical and Biological Engineering from the South Dakota School of Mines and Technology. Jia currently researches genomics and metagenomics of foodborne pathogens in the Department of Food Science at the University of Tennessee – Knoxville. Jia studied the formation and mechanisms of microbial communities as a postdoctoral research associate in the Plant Microbe Interfaces (PMI) Science Focus Area (SFA) at Oak Ridge National Laboratory.
What was your research focus in the PMI SFA?
(JW) My research for the PMI project primarily used computational models and multi-omics analysis to understand the functional roles and metabolic interactions of rhizospheric (or plant root-associated) microbial communities. The greater aim of the project is managing renewable energy sources. Synthetic microbial communities were constructed to observe how communities form, while computational modeling of multi-species microbial communities was established to elucidate the mechanisms by which metabolic interactions influence community assembly. Additionally, I collaborated with fellow researchers in the PMI group to devise strategies for integrating proteomic and metabolomic approaches with genome-scale computational modeling.
How have you benefited from working with KBase?
(JW) Collaborating with KBase has been an invaluable learning experience for me. I’ve gained proficiency in the entire research process, from genome annotation to community flux-balance analysis modeling. This greater understanding has enabled me to investigate and simulate metabolic exchanges within microbial communities, thereby deepening my comprehension of interactions between microorganisms within these communities.
What is your favorite part about using KBase?
(JW) As a microbiologist with limited coding experience, I initially found navigating bioinformatic software tools to be challenging. However, KBase’s integration of numerous analysis tools with graphical user interfaces proved to be a game-changer. These user-friendly interfaces eliminate the need for coding skills, significantly streamlining my workflow and saving considerable time. Moreover, while some software necessitates high-performance computers, KBase’s server-based processing negates the need for powerful PCs, making computational tasks accessible and efficient.
What role do you see KBase having in open science principles?
(JW) By utilizing and creating public Narratives, I believe KBase plays a significant role in sharing scientific knowledge and findings to diverse audiences, thereby promoting scientific literacy and fostering public engagement with science.
What is one “behind the scenes” thing you want to share about your project?
(JW) One intriguing aspect I’d like to share from behind the scenes is the availability of public Narratives. These Narratives were referenced in the articles I consulted while researching methods for simulating microbial community growth using KBase (Henry et al. 2016; https://narrative.kbase.us/narrative/13807). It’s incredibly handy and efficient to have clickable links to these public Narratives, as they provide comprehensive details about the KBase applications (tools, version, and parameters) utilized in the referenced articles. Through these Narratives, I gained insights into the rationale behind the selection of specific applications for constructing metabolic models.
Furthermore, coding cells within Narratives allow me to tailor analysis for my own research endeavors. Overall, public Narratives serve as invaluable resources for learning and advancing my work.
LINKS
C.S. Henry, H.C. Bernstein, P. Weisenhorn, R.C. Taylor, J.Y. Lee, J. Zucker, H.S. Song. “Microbial community metabolic modeling: a community data‐driven network reconstruction.” Journal of Cellular Physiology 231(11), 2339-2345 (2016). https://doi.org/10.1002/jcp.25428
- https://narrative.kbase.us/narrative/13806
- https://narrative.kbase.us/narrative/13807
- https://narrative.kbase.us/narrative/13838
J. Wang, M.R. Appidi, L.H. Burdick, P.E. Abraham, R.L. Hettich, D.A. Pelletier, M.J. Doktycz. “Formation of a constructed microbial community in a nutrient-rich environment indicates bacterial interspecific competition.” mSystems 9:e00006-24 (2024). https://doi.org/10.1128/msystems.00006-24
J. Wang, D.L. Carper, L.H. Burdick, H.K. Shrestha, M.R. Appidi, P.E. Abraham, C.M. Timm, R.L. Hettich, D.A. Pelletier and M.J. Doktycz. “Formation, characterization and modeling of emergent synthetic microbial communities.” Computational and Structural Biotechnology Journal 19: 1917-1927 (2021). https://doi.org/10.1016/j.csbj.2021.03.034