Simplified automated image analysis for detection and phenotyping of Mycobacterium tuberculosis on porous supports by monitoring growing microcolonies.
BACKGROUND: Even with the advent of nucleic acid (NA) amplification technologies the culture of mycobacteria for diagnostic and other applications remains of critical importance. Notably microscopic observed drug susceptibility testing (MODS), as opposed to traditional culture on solid media or auto...
Main Authors: | , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2010-01-01
|
Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC2882339?pdf=render |
id |
doaj-53e698ad542c4761b10b1f43de561d40 |
---|---|
record_format |
Article |
spelling |
doaj-53e698ad542c4761b10b1f43de561d402020-11-25T01:47:58ZengPublic Library of Science (PLoS)PLoS ONE1932-62032010-01-0156e1100810.1371/journal.pone.0011008Simplified automated image analysis for detection and phenotyping of Mycobacterium tuberculosis on porous supports by monitoring growing microcolonies.Alice L den HertogDennis W VisserColin J InghamFrank H A G FeyPaul R KlatserPaul R KlatserRichard M AnthonyBACKGROUND: Even with the advent of nucleic acid (NA) amplification technologies the culture of mycobacteria for diagnostic and other applications remains of critical importance. Notably microscopic observed drug susceptibility testing (MODS), as opposed to traditional culture on solid media or automated liquid culture, has shown potential to both speed up and increase the provision of mycobacterial culture in high burden settings. METHODS: Here we explore the growth of Mycobacterial tuberculosis microcolonies, imaged by automated digital microscopy, cultured on a porous aluminium oxide (PAO) supports. Repeated imaging during colony growth greatly simplifies "computer vision" and presumptive identification of microcolonies was achieved here using existing publically available algorithms. Our system thus allows the growth of individual microcolonies to be monitored and critically, also to change the media during the growth phase without disrupting the microcolonies. Transfer of identified microcolonies onto selective media allowed us, within 1-2 bacterial generations, to rapidly detect the drug susceptibility of individual microcolonies, eliminating the need for time consuming subculturing or the inoculation of multiple parallel cultures. SIGNIFICANCE: Monitoring the phenotype of individual microcolonies as they grow has immense potential for research, screening, and ultimately M. tuberculosis diagnostic applications. The method described is particularly appealing with respect to speed and automation.http://europepmc.org/articles/PMC2882339?pdf=render |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Alice L den Hertog Dennis W Visser Colin J Ingham Frank H A G Fey Paul R Klatser Paul R Klatser Richard M Anthony |
spellingShingle |
Alice L den Hertog Dennis W Visser Colin J Ingham Frank H A G Fey Paul R Klatser Paul R Klatser Richard M Anthony Simplified automated image analysis for detection and phenotyping of Mycobacterium tuberculosis on porous supports by monitoring growing microcolonies. PLoS ONE |
author_facet |
Alice L den Hertog Dennis W Visser Colin J Ingham Frank H A G Fey Paul R Klatser Paul R Klatser Richard M Anthony |
author_sort |
Alice L den Hertog |
title |
Simplified automated image analysis for detection and phenotyping of Mycobacterium tuberculosis on porous supports by monitoring growing microcolonies. |
title_short |
Simplified automated image analysis for detection and phenotyping of Mycobacterium tuberculosis on porous supports by monitoring growing microcolonies. |
title_full |
Simplified automated image analysis for detection and phenotyping of Mycobacterium tuberculosis on porous supports by monitoring growing microcolonies. |
title_fullStr |
Simplified automated image analysis for detection and phenotyping of Mycobacterium tuberculosis on porous supports by monitoring growing microcolonies. |
title_full_unstemmed |
Simplified automated image analysis for detection and phenotyping of Mycobacterium tuberculosis on porous supports by monitoring growing microcolonies. |
title_sort |
simplified automated image analysis for detection and phenotyping of mycobacterium tuberculosis on porous supports by monitoring growing microcolonies. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2010-01-01 |
description |
BACKGROUND: Even with the advent of nucleic acid (NA) amplification technologies the culture of mycobacteria for diagnostic and other applications remains of critical importance. Notably microscopic observed drug susceptibility testing (MODS), as opposed to traditional culture on solid media or automated liquid culture, has shown potential to both speed up and increase the provision of mycobacterial culture in high burden settings. METHODS: Here we explore the growth of Mycobacterial tuberculosis microcolonies, imaged by automated digital microscopy, cultured on a porous aluminium oxide (PAO) supports. Repeated imaging during colony growth greatly simplifies "computer vision" and presumptive identification of microcolonies was achieved here using existing publically available algorithms. Our system thus allows the growth of individual microcolonies to be monitored and critically, also to change the media during the growth phase without disrupting the microcolonies. Transfer of identified microcolonies onto selective media allowed us, within 1-2 bacterial generations, to rapidly detect the drug susceptibility of individual microcolonies, eliminating the need for time consuming subculturing or the inoculation of multiple parallel cultures. SIGNIFICANCE: Monitoring the phenotype of individual microcolonies as they grow has immense potential for research, screening, and ultimately M. tuberculosis diagnostic applications. The method described is particularly appealing with respect to speed and automation. |
url |
http://europepmc.org/articles/PMC2882339?pdf=render |
work_keys_str_mv |
AT aliceldenhertog simplifiedautomatedimageanalysisfordetectionandphenotypingofmycobacteriumtuberculosisonporoussupportsbymonitoringgrowingmicrocolonies AT denniswvisser simplifiedautomatedimageanalysisfordetectionandphenotypingofmycobacteriumtuberculosisonporoussupportsbymonitoringgrowingmicrocolonies AT colinjingham simplifiedautomatedimageanalysisfordetectionandphenotypingofmycobacteriumtuberculosisonporoussupportsbymonitoringgrowingmicrocolonies AT frankhagfey simplifiedautomatedimageanalysisfordetectionandphenotypingofmycobacteriumtuberculosisonporoussupportsbymonitoringgrowingmicrocolonies AT paulrklatser simplifiedautomatedimageanalysisfordetectionandphenotypingofmycobacteriumtuberculosisonporoussupportsbymonitoringgrowingmicrocolonies AT paulrklatser simplifiedautomatedimageanalysisfordetectionandphenotypingofmycobacteriumtuberculosisonporoussupportsbymonitoringgrowingmicrocolonies AT richardmanthony simplifiedautomatedimageanalysisfordetectionandphenotypingofmycobacteriumtuberculosisonporoussupportsbymonitoringgrowingmicrocolonies |
_version_ |
1725013708758843392 |