Lawrence Berkeley National Lab
Biological Systems and Engineering
Principal Investigator
amukhopadhyay@lbl.gov
(510) 495-2628
Dr. Mukhopadhyay’s work is centered in the Environmental Atlas, focused on understanding membrane transport, signaling, stress response, and tolerance phenotypes in environmental microbes. She utilizes a wide variety of microbiological, biochemical, and systems biology tools to examine environmentally important organisms such as sulfate and metal-reducing bacteria as well as cyanobacteria. She has a specific interest in signaling mechanisms in novel non-model organisms like Pseudomonas stuzeri, Desulfovibrio vulgaris. Her latest work characterizes plasmids isolated from the field site, evaluating these environmental plasmids’ role in the microbial community and their use as biodesign tools, to genetically manipulate isolates from ORR and other bacteria of interest. She is also interested in using viral DNA as a predictor of hosts.
She works on signaling systems and mobile genetic elements and evaluate their ecological significance. In order to examine signaling systems, she primarily focuses on response regulators that act via transcriptional activation and implement the DAP-seq approach. They explore mobile genetic elements, spanning both plasmids and viruses, in samples collected from the ORR, by implementing plasmidome assays. Her lab evaluates functional genes on these mobile genetic elects in the context of the ecology of the site and mine the plasmids tools development, such as creating a library of natural vectors for the isolate collection.
A successful outcome of this work is key publications outlining the signaling and regulatory systems for a select group of Pseudomonas and Rhodanobacter strains in the isolate collection. Further, they are working on 2-3 plasmidomics studies to compare samples across nitrate, pH gradients, and groundwater vs. sediment. She is establishing an origins library and determining a selection of isolates and model bacteria that can be transformed using them.
Relevant Publications
Machine Learning Reveals Patterns of REC Protein Domain Evolution - Bacteria can evolve by exchanging genetic material through a process called recombination. This study used machine learning models combined with functional laboratory experiments to show that after recombination, a bacterial signaling system changed and expanded its protein family, despite considerable selective pressures in place that constrained new modifications. More →
Host Bacteria Are Helped By Viral Genomes - Kothari, Ankita.; S. Roux, H. Zhang, A. Prieto, J-M Chandonia, S. Spencer, X. Wu, A M. Deutschbauer, A. P. Arkin, E J. Alm, R. Chakraborty, A Mukhopadhyay (2021) Ecogenomics of groundwater viruses suggests niche differentiation linked to specific environmental tolerance. mSystems [doi]:1128/mSystems.00537-21 {PMID}: 34184913 PMCID: PMC8269241 OSTI:1807913 Niche Specific Genes from Phage Genomes are Advantageous for Communities of Groundwater Bacteria Ground water… More →