Component Parts of Bacteriophage Virions Accurately Defined by a Machine-Learning Approach Built on Evolutionary Features-Reference-Cited by-同舟云学术

Component Parts of Bacteriophage Virions Accurately Defined by a Machine-Learning Approach Built on Evolutionary Features

Published:2021-05-27 Issue: Volume: Page:
ISSN:2379-5077
Container-title:mSystems
language:en
Short-container-title:mSystems

Author:

Thung Tze Y.¹²³,White Murray E.¹²³,Dai Wei¹²⁴,Wilksch Jonathan J.¹²³,Bamert Rebecca S.¹²³,Rocker Andrea¹²,Stubenrauch Christopher J.¹²³^ORCID,Williams Daniel¹²³,Huang Cheng⁵⁶⁷,Schittelhelm Ralf⁵⁶⁷,Barr Jeremy J.³⁸^ORCID,Jameson Eleanor⁹,McGowan Sheena¹²³,Zhang Yanju⁴,Wang Jiawei¹²³^ORCID,Dunstan Rhys A.¹²³,Lithgow Trevor¹²³^ORCID

Affiliation:

1. Infection & Immunity Program, Biomedicine Discovery Institute, Monash University, Clayton, Australia

2. Department of Microbiology, Monash University, Clayton, Australia

3. Centre to Impact AMR, Monash University, Clayton, Australia

4. School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, China

5. Monash Proteomics & Metabolomics Facility, Monash University, Clayton, Australia

6. Biomedicine Discovery Institute, Monash University, Clayton, Australia

7. Department of Biochemistry and Molecular Biology, Monash University, Clayton, Australia

8. School of Biological Sciences, Monash University, Clayton, Australia

9. School of Life Sciences, University of Warwick, Coventry, United Kingdom

Abstract

In response to the global problem of antimicrobial resistance, there are moves to use bacteriophages (phages) as therapeutic agents. Selecting which phages will be effective therapeutics relies on interpreting features contributing to shelf-life and applicability to diagnosed infections.

Funder

Monash-Warwick Alliance

Australian Research Council

Publisher

American Society for Microbiology

Subject

Computer Science Applications,Genetics,Molecular Biology,Modeling and Simulation,Ecology, Evolution, Behavior and Systematics,Biochemistry,Physiology,Microbiology

Link

https://journals.asm.org/doi/pdf/10.1128/mSystems.00242-21

Reference72 articles.

1. Antibiotic resistance threats in the United States, 2019

2. The Review on Antimicrobial Resistance. 2016. Tackling drug-resistant infections globally: final report and recommendations. The Review on Antimicrobial Resistance London United Kingdom. https://amr-review.org/sites/default/files/160525_Final%20paper_with%20cover.pdf.

3. Luong T Salabarria AC Edwards RA Roach DR. 2020. Standardized bacteriophage purification for personalized phage therapy. Nat Protoc 15:2867–2890. doi:10.1038/s41596-020-0346-0.

4. Phage Therapy: What Have We Learned?

5. Bacteriophages: A Therapy Concept against Multi-Drug–Resistant Bacteria

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Phage resistance in Klebsiella pneumoniae and bidirectional effects impacting antibiotic susceptibility;Clinical Microbiology and Infection;2024-06

2. Tackling the Antimicrobial Resistance “Pandemic” with Machine Learning Tools: A Summary of Available Evidence;Microorganisms;2024-04-23

3. Antimicrobial resistance crisis: could artificial intelligence be the solution?;Military Medical Research;2024-01-23

4. Isolation and genome sequencing of five lytic bacteriophages from hospital wastewater in the Philippines;Microbiology Resource Announcements;2023-09-19

5. Diversified repertoire of phage defenses inKlebsiella pneumoniae: Bi-directional steering effects impacting antibiotic susceptibility;2022-11-15