Work done in the lab of Prof. Bernhard O. Palsson at University of California San Diego
About author
Akanksha Rajput obtained her Bachelor’s honors degree and Master’s degree in Biotechnology from Banasthali University, Rajasthan. Subsequently, she joined the lab of Dr. Manoj Kumar, CSIR-Institute of Microbial Technology, Chandigarh, India for her Ph.D. in Bioinformatics. During her Ph.D. she explored microbial communications and their consequences like antibiotics resistance, biofilms, etc. After receiving her Ph.D. degree, she moved to the University of California San Diego and is working as a Postdoctoral scholar till now. During her postdoctoral research, she explored microbial interaction through various systems biology approaches. Broadly, her research work is focused on exploring the microbial (Bacteria, Virus, and Archaea) mechanisms using multivariate computational analysis followed by validation through experimental techniques.
Interview
How would you explain your research outcomes to the non-scientific community?
Large data sets and machine learning are impacting a growing number of areas of research in the life sciences. Once the compendia of bacterial transcriptomes reached a critical size, we could use source signal extraction algorithms to find lists of co-regulated genes (called iModulons) associated with a transcription factor (TF) to them. The gene composition of iModulons and their condition-dependent activity levels constitute a quantitative description of the composition of bacterial transcriptomes. This study shows how this approach can be used to reveal the responses of Pseudomonas aeruginosa to antibiotics and thus yield a deep regulatory understanding of pathogenicity properties. This study motivates the execution of similar studies for the other ESKAPEEs to yield a broad understanding of the role of Transcriptional Regulatory Networks (TRNs) in antibiotic responses to this urgent threat of bacterial pathogens.
How do these findings contribute to your research area?
P. aeruginosa is an important member of the ESKAPEE group of pathogenic bacteria. It is an opportunistic pathogen and shows high resistance to diverse classes of antibiotics. In the current study, we used Independent Component Analysis (ICA) on 411 expression profiles of P. aeruginosa to generate 116 iModulons. Our analysis reveals various important aspects of P. aeruginosa transcriptional regulation, such as the prediction of Two component systems (TCSs) regulating the efflux pumps, specific macromolecules and antibiotics which activate transcription of TCS-dependent efflux pumps, differential behavior of beta-lactam antibiotics in bacteriological and physiological media, the impact of beta-lactam antibiotics on the PBPs and cell division, and the role of the PprB iModulon in the transition to biofilm growth under stress conditions.
We found that the iModulons are an important tool for the reconstruction of the TRN of P. aeruginosa to address various biological queries, including predicting the regulators and substrates of efflux pumps, examining the differential behavior of beta-lactam antibiotics in different media, exploring the role of biofilm-specific antibiotic resistance systems in the virulence of P. aeruginosa, and elucidating the molecular mechanism of beta-lactam antibiotics on PBPs and cell division. This study demonstrates that iModulon-based TRNs can provide new insights when new transcriptomic data is added; this work can therefore serve as the basis for further studies. With increasing scale, we hope that this approach will culminate in a comprehensive, quantitative, irreducible TRN for this important pathogen.
“This study demonstrates that iModulon-based TRNs can provide new insights when new transcriptomic data is added.”
What was the exciting moment during your research?
The current study is focused on elucidating the antibiotic-specific behavior of P. aeruginosa through the application of machine learning to a compendium of transcriptomic profiles. In this study, we were very excited to identify the novel regulator of some efflux pumps. As well as to identify the effect of media composition on the antibiotic’s behavior in P. aeruginosa. Thus, getting such important insights from the transcriptomic data was very exciting during the whole process.
What do you hope to do next?
In the future, I would like to explore the microbial world through multi-omics analysis. From my 10+ years of research career, I explored the microbial world through various approaches, but still think that a large diaspora of the microbial world needs to be explored. So I would like to pursue my career in the same direction.
Where do you seek scientific inspiration from?
I seek inspiration from my mentors and my family. I am very fortunate to have awesome mentors both in my Ph.D. (Dr. Manoj Kumar, Senior Principal Scientist, CSIR-IMTech, Chandigarh, India) as well as during the Postdoc (Prof. Bernhard O. Palsson, Gallenti Professor, University of California San Diego). Apart from my mentors, my greatest inspiration is my mother.
How do you intend to help Indian science improve?
I think collaborative research would be an important step to improve Indian science. We should focus on increasing the collaboration between experimentalists and bioinformaticians both within and outside the country. However, another important step would be to make research open access to benefit a large number of researchers.
Reference
Rajput A, Tsunemoto H, Sastry AV, Szubin R, Rychel K, Chauhan SM, Pogliano J, Palsson BO “Advanced transcriptomic analysis reveals the role of efflux pumps and media composition in antibiotic responses of Pseudomonas aeruginosa.” Nucleic acids research, gkac743. 12 Sep. 2022, doi:10.1093/nar/gkac743.
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