Literature DB >> 26790948

Survival proteomes: the emerging proteotype of antimicrobial resistance.

Amber J Park1, Jonathan R Krieger2, Cezar M Khursigara3.   

Abstract

Antimicrobial resistance is one of the greatest challenges in modern medicine. Infectious diseases that have historically been eliminated with routine antibiotic therapy are now re-emerging as life threatening illnesses. A better understanding of the specific mechanisms that contribute to resistance are required to optimize the treatment of infectious microorganisms and limit the survival of recalcitrant populations. This challenging area of research is made more problematic by the observation that multiple, overlapping, and/or compensatory resistance mechanism are often present within a single bacterial species. High-resolution proteomics has emerged as an effective tool to study antimicrobial resistance as it allows for the quantitative investigation of multiple systems concurrently. Furthermore, the ability to examine extracellular mechanisms of resistance and important post-translational modifications make this research tool well suited for the challenge. This review discusses how proteomics has contributed to the understanding of antimicrobial resistance and focuses on advances afforded by the more recent development of technologies that produce quantitative high-resolution proteomic information. We discuss current strategies for studying resistance, including comparative analysis of resistant and susceptible strains and protein-based responses to antimicrobial challenge. Lastly, we suggest specific experimental approaches aimed at advancing our understanding of protein-based resistance mechanisms and maximizing therapeutic outcomes in the future. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Keywords:  antimicrobial resistance; experimental design; mass-spectrometry; pathogenic bacteria; post-translational modifications; proteomics

Mesh:

Substances:

Year:  2016        PMID: 26790948     DOI: 10.1093/femsre/fuv051

Source DB:  PubMed          Journal:  FEMS Microbiol Rev        ISSN: 0168-6445            Impact factor:   16.408


  12 in total

1.  Investigating Lactococcus lactis MG1363 Response to Phage p2 Infection at the Proteome Level.

Authors:  Marie-Laurence Lemay; Andreas Otto; Sandra Maaß; Kristina Plate; Dörte Becher; Sylvain Moineau
Journal:  Mol Cell Proteomics       Date:  2019-01-24       Impact factor: 5.911

2.  Outer membrane vesicles from β-lactam-resistant Escherichia coli enable the survival of β-lactam-susceptible E. coli in the presence of β-lactam antibiotics.

Authors:  Si Won Kim; Seong Bin Park; Se Pyeong Im; Jung Seok Lee; Jae Wook Jung; Tae Won Gong; Jassy Mary S Lazarte; Jaesung Kim; Jong-Su Seo; Jong-Hwan Kim; Jong-Wook Song; Hyun Suk Jung; Gwang Joong Kim; Young Ju Lee; Suk-Kyung Lim; Tae Sung Jung
Journal:  Sci Rep       Date:  2018-03-29       Impact factor: 4.379

3.  Detection of Antimicrobial Resistance Using Proteomics and the Comprehensive Antibiotic Resistance Database: A Case Study.

Authors:  Chih-Yu Chen; Clifford G Clark; Stacie Langner; David A Boyd; Amrita Bharat; Stuart J McCorrister; Andrew G McArthur; Morag R Graham; Garrett R Westmacott; Gary Van Domselaar
Journal:  Proteomics Clin Appl       Date:  2020-02-28       Impact factor: 3.494

Review 4.  Antimicrobial Resistance in Veterinary Medicine: An Overview.

Authors:  Ernesto Palma; Bruno Tilocca; Paola Roncada
Journal:  Int J Mol Sci       Date:  2020-03-11       Impact factor: 5.923

5.  Berkchaetoazaphilone B has antimicrobial activity and affects energy metabolism.

Authors:  Xudong Ouyang; Jelmer Hoeksma; Gisela van der Velden; Wouter A G Beenker; Maria H van Triest; Boudewijn M T Burgering; Jeroen den Hertog
Journal:  Sci Rep       Date:  2021-09-21       Impact factor: 4.379

Review 6.  Proteomics As a Tool for Studying Bacterial Virulence and Antimicrobial Resistance.

Authors:  Francisco J Pérez-Llarena; Germán Bou
Journal:  Front Microbiol       Date:  2016-03-31       Impact factor: 5.640

7.  Selective Proteomic Analysis of Antibiotic-Tolerant Cellular Subpopulations in Pseudomonas aeruginosa Biofilms.

Authors:  Brett M Babin; Lydia Atangcho; Mark B van Eldijk; Michael J Sweredoski; Annie Moradian; Sonja Hess; Tim Tolker-Nielsen; Dianne K Newman; David A Tirrell
Journal:  MBio       Date:  2017-10-24       Impact factor: 7.867

8.  Systems level profiling of arginine starvation reveals MYC and ERK adaptive metabolic reprogramming.

Authors:  Caitlyn B Brashears; Meltem Barlin; William R Ehrhardt; Richa Rathore; Matthew Schultze; Shin-Chen Tzeng; Brian A Van Tine; Jason M Held
Journal:  Cell Death Dis       Date:  2020-08-20       Impact factor: 8.469

9.  Comparative Proteomics of Extended-Spectrum Cephalosporin-Resistant Neisseria gonorrhoeae Isolates Demonstrates Altered Protein Synthesis, Metabolism, Substance Transport, and Membrane Permeability.

Authors:  Nannan Diao; Guoquan Yan; Yang Yang; Yuan Dong; Ying Wang; Weiming Gu
Journal:  Front Microbiol       Date:  2020-02-19       Impact factor: 5.640

10.  Fast and Accurate Bacterial Species Identification in Urine Specimens Using LC-MS/MS Mass Spectrometry and Machine Learning.

Authors:  Florence Roux-Dalvai; Clarisse Gotti; Mickaël Leclercq; Marie-Claude Hélie; Maurice Boissinot; Tabiwang N Arrey; Claire Dauly; Frédéric Fournier; Isabelle Kelly; Judith Marcoux; Julie Bestman-Smith; Michel G Bergeron; Arnaud Droit
Journal:  Mol Cell Proteomics       Date:  2019-10-04       Impact factor: 5.911

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