PreprintArticleVersion 3Preserved in Portico This version is not peer-reviewed
Genome Analysis of Three Bacteriophages Targeting Multi Drug Resistant Clinical Isolate of E. coli, Host Receptor Prediction Using Machine Learning Tools and the Evaluation of Monophages and Cocktail In Vitro and In Vivo
Both the authors have contributed equally for the work
Version 1
: Received: 30 December 2022 / Approved: 4 January 2023 / Online: 4 January 2023 (02:04:36 CET)
Version 2
: Received: 6 July 2023 / Approved: 6 July 2023 / Online: 7 July 2023 (02:05:31 CEST)
Version 3
: Received: 7 July 2023 / Approved: 10 July 2023 / Online: 10 July 2023 (08:28:28 CEST)
How to cite:
Sundaramoorthy, N.S.; KU, V.; Nair, V.; Bharathi, K.; JBB, J.S.R.; R, M.; Srikanth, S.; S, S.K.; Sankaran, P.; Mohan, S.; Nagarajan, S. Genome Analysis of Three Bacteriophages Targeting Multi Drug Resistant Clinical Isolate of E. coli, Host Receptor Prediction Using Machine Learning Tools and the Evaluation of Monophages and Cocktail In Vitro and In Vivo. Preprints2023, 2023010036. https://doi.org/10.20944/preprints202301.0036.v3
Sundaramoorthy, N.S.; KU, V.; Nair, V.; Bharathi, K.; JBB, J.S.R.; R, M.; Srikanth, S.; S, S.K.; Sankaran, P.; Mohan, S.; Nagarajan, S. Genome Analysis of Three Bacteriophages Targeting Multi Drug Resistant Clinical Isolate of E. coli, Host Receptor Prediction Using Machine Learning Tools and the Evaluation of Monophages and Cocktail In Vitro and In Vivo. Preprints 2023, 2023010036. https://doi.org/10.20944/preprints202301.0036.v3
Sundaramoorthy, N.S.; KU, V.; Nair, V.; Bharathi, K.; JBB, J.S.R.; R, M.; Srikanth, S.; S, S.K.; Sankaran, P.; Mohan, S.; Nagarajan, S. Genome Analysis of Three Bacteriophages Targeting Multi Drug Resistant Clinical Isolate of E. coli, Host Receptor Prediction Using Machine Learning Tools and the Evaluation of Monophages and Cocktail In Vitro and In Vivo. Preprints2023, 2023010036. https://doi.org/10.20944/preprints202301.0036.v3
APA Style
Sundaramoorthy, N.S., KU, V., Nair, V., Bharathi, K., JBB, J.S.R., R, M., Srikanth, S., S, S.K., Sankaran, P., Mohan, S., & Nagarajan, S. (2023). Genome Analysis of Three Bacteriophages Targeting Multi Drug Resistant Clinical Isolate of <em>E. coli, </em>Host Receptor Prediction Using Machine Learning Tools and the Evaluation of Monophages and Cocktail In Vitro and In Vivo. Preprints. https://doi.org/10.20944/preprints202301.0036.v3
Chicago/Turabian Style
Sundaramoorthy, N.S., Suma Mohan and Saisubramanian Nagarajan. 2023 "Genome Analysis of Three Bacteriophages Targeting Multi Drug Resistant Clinical Isolate of <em>E. coli, </em>Host Receptor Prediction Using Machine Learning Tools and the Evaluation of Monophages and Cocktail In Vitro and In Vivo" Preprints. https://doi.org/10.20944/preprints202301.0036.v3
Abstract
The objective of the present study is to isolate phages targeting multidrug resistant (MDR), extended spectrum beta lactamase (ESBL) positive clinical isolate of E. coli ( U1007), sequence and analyze the phage genome and use machine learning tools to predict host cell surface receptorand finally evaluate the efficiency of monophage and phage cocktail in vitro and in vivo in a zebrafish model. Phage specific for E. coli U1007 was isolated from Ganges River (designated as U1G), Cuoom River (designated as CR) and Hospital waste water (designated as M phage). The obtained phages were triple purified and enriched. U1G phages had a greater burst size of 124 PFU/cell and a latent time of 25 min.M phage had a burst size of 150 PFU/cell with a shortlatent time of 20min. Similarly CR phage has a short latent 20 min and a burst size of 115 PFU/cell. Based on capsid architecture, U1G phage resembles Podoviridae, CR phage is structurally similar to Myoviridae and M phage has morphology that resembles Siphoviridae.Genome sequencing and analysis revealed that the size of the U1G phage genome is 73275 bp Whereas that of CR phage and M phage are 45236 bp and 45294 bp, respectively. All three genomes were marked by the absence of genes encoding tRNA sequence, antibiotic resistant or virulent genes. A machine learning (ML) based multi-class classification model using algorithms such as Random Forest, Logistic Regression, and Decision Tree were employed to predict the host receptor targeted by all 3 phages and the best performing algorithm Random Forest predicted LPS O antigen , LamB or OmpC for U1G FhuA, OmpC for CR phage and FhuA, LamB, TonB or OmpF for the M phage as the host receptor targeted by the receptor binding protein (RBP) of the phages. In vitro time kill assay showed that treatment with monophages alone and along with colistin resulted in regrowth whereas phage combinations significantly reduced the regrowth and by 24h the phage cocktail along with colistin produced a significant 3 log declinein cell counts relative to the untreated control. In vivo intramuscular infection study in zebrafish showed that phages were non toxic and a cocktail of dual (U1G +M) phage along with colsitin resulted in a significant 3.5 log decline in cell counts whereas triple phage combination along with colistin resulted in 3 log decline in cell counts probably due to host receptor competition. Our study highlights the potential of phage cocktail therapy in mitigating MDR clinical isolate of E. coliin vitro and in vivo.
Biology and Life Sciences, Immunology and Microbiology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Received:
10 July 2023
Commenter:
Saisubramanian Nagarajan
Commenter's Conflict of Interests:
Author
Comment:
Based on the observations by the reviewer we have completely revamped the entire study we have isolated two more phages targeting same host colistin resistant MDR U1007 strain from Cuoom River, Chennai designated as CR phage and from Hospital Waste water designated as M phage and have carried out complete studies including characterization, whole genome sequencing, Receptor prediction, TEM imaging and finally we have shown that the phages cocktail along with colistin caused a significant 3.5 log reduction in colony counts in zebrafish infection model (Figure 6). We have also alleviated concern by the reviewer regarding response of this strain to colistin by proving that the strain is colistin heteroresistant and ESBL positive (Figure S11) and hence falls under category of critical priority pathogen (ESBL producing Enterobacteriaceae and hence is important for development of phage therapy. Lastly we have also validated prediction by ML tool by growth under conditions that upregulate OmpC receptor which results in higher phage titers thereby confirming that OmpC indeed is the receptor for U1G phage as predicted by ML tools (Figure 4).
Commenter: Saisubramanian Nagarajan
Commenter's Conflict of Interests: Author