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The Antiviral System of Bacteria and Archaea: CRISPR01:23

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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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High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
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HRMAn 2.0: Next-generation artificial intelligence-driven analysis for broad host-pathogen interactions.

Daniel Fisch1,2, Robert Evans1,2, Barbara Clough1

  • 1Institute of Microbiology and Infection, School of Biosciences, University of Birmingham, Edgbaston, UK.

Cellular Microbiology
|April 30, 2021
PubMed
Summary
This summary is machine-generated.

Manual counting of infection dynamics is challenging. Host Response to Microbe Analysis (HRMAn) 2.0 uses AI for unbiased, automated analysis of host-pathogen interactions, improving accuracy and efficiency.

Keywords:
artificial intelligencehost-pathogen interactionimage analysis

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Area of Science:

  • Microbiology
  • Immunology
  • Bioimage analysis

Background:

  • Manual enumeration of imaging-based infection assays is standard but prone to bias and errors.
  • Automated analysis is needed to overcome limitations of manual methods in studying host-pathogen dynamics.

Purpose of the Study:

  • To present HRMAn 2.0, an enhanced automated image analysis tool for host-pathogen interaction studies.
  • To demonstrate HRMAn 2.0's expanded capabilities for analyzing diverse pathogens and host responses.

Main Methods:

  • Utilized machine learning and artificial intelligence within the KNIME Analytics platform.
  • Developed HRMAn 2.0 for unbiased quantification of pathogen growth, killing, and host cell defense activation.
  • Applied HRMAn 2.0 to Toxoplasma gondii, Chlamydia trachomatis, and Cryptococcus neoformans.

Main Results:

  • HRMAn 2.0 provides unbiased and reproducible quantification of intracellular infection dynamics.
  • The tool measures multiple parameters including pathogen load and host defense activation.
  • Successfully extended HRMAn 2.0's application to bacterial and fungal pathogens beyond T. gondii.

Conclusions:

  • HRMAn 2.0 offers a robust, automated solution for analyzing host-pathogen interactions.
  • The platform's adaptability facilitates broader applications in infectious disease research.
  • Automated analysis significantly improves the efficiency and reliability of infection dynamics studies.