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Related Concept Videos

Development of Antibiotic Resistance01:30

Development of Antibiotic Resistance

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Antibiotic resistance is a major public health concern that arises when bacteria evolve mechanisms to withstand the effects of antibiotic treatments. This resistance can be intrinsic, acquired through genetic mutations, or transferred between bacteria via horizontal gene transfer. The development of antibiotic resistance poses significant challenges in treating bacterial infections and necessitates ongoing research to develop new therapeutic strategies.Intrinsic resistance occurs when bacterial...
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CRISPR stands for Clustered Regularly Interspaced Short Palindromic Repeats is a adaptive immune system found in bacteria and archaea that protects against viral infections. This system enables prokaryotic cells to identify, remember, and neutralize foreign genetic elements, primarily bacteriophages, by storing fragments of the invader’s DNA as a genetic memory.The CRISPR immune response begins during an initial infection. Cas (CRISPR-associated) proteins play a central role in this...
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The effectiveness of antimicrobial agents depends on various factors influencing their ability to eliminate microbial populations. Larger microbial populations require more time for complete eradication, emphasizing the importance of population size analysis when evaluating antimicrobial efficacy.Microbial resistance to antimicrobial agents varies significantly. Highly resilient microorganisms include endospores, gram-negative bacteria, and non-enveloped viruses, while prions are exceptionally...
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Related Experiment Video

Updated: Nov 30, 2025

Isolation and Identification of Waterborne Antibiotic-Resistant Bacteria and Molecular Characterization of their Antibiotic Resistance Genes
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PARMAP: A Pan-Genome-Based Computational Framework for Predicting Antimicrobial Resistance.

Xuefei Li1, Jingxia Lin1, Yongfei Hu1

  • 1Dermatology Hospital, Southern Medical University, Guangzhou, China.

Frontiers in Microbiology
|November 16, 2020
PubMed
Summary

A new tool, PARMAP, accurately predicts antimicrobial resistance (AMR) in bacteria like Neisseria gonorrhoeae using machine learning and pan-genome analysis. It identifies genetic alterations linked to AMR, aiding in understanding and combating this global health threat.

Keywords:
AMR predictionNeisseria gonorrhoeaeantibiotic resistance genesantimicrobial resistance (AMR)machine learning (ML)pan-genome

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Area of Science:

  • Microbiology
  • Genomics
  • Computational Biology

Background:

  • Antimicrobial resistance (AMR) is a critical global health challenge.
  • Accurate detection of AMR phenotypes is essential for controlling resistant strains.
  • Existing methods may not fully capture the genetic basis of AMR.

Purpose of the Study:

  • To develop and validate PARMAP, a machine learning tool for predicting AMR phenotypes.
  • To identify AMR-associated genetic alterations using bacterial pan-genome data.
  • To investigate the genetic heterogeneity of AMR in bacterial populations.

Main Methods:

  • Development of PARMAP utilizing machine learning algorithms.
  • Analysis of bacterial pan-genome data for genetic alterations.
  • Application of PARMAP to Neisseria gonorrhoeae, Mycobacterium tuberculosis, and Escherichia coli strains.

Main Results:

  • PARMAP accurately predicted AMR phenotypes in Neisseria gonorrhoeae.
  • Identified 328 genetic alterations in known AMR genes and discovered novel AMR-associated alterations.
  • Demonstrated robustness across different bacterial species, including M. tuberculosis and E. coli.

Conclusions:

  • PARMAP precisely predicts AMR phenotypes and identifies genetic drivers of resistance.
  • The tool accelerates the investigation of AMR mechanisms using whole-genome sequencing data.
  • PARMAP is a valuable framework for studying AMR in various human pathogens.