Immunohistochemical detection of Mycobacterium tuberculosis in tissues of consumptives using laser scanning microscopy

Ерохина, М.В.; Nezlin, Leonid P.; Авдиенко, В. Г.; Voronezhska, E. E.; Лепеха, Л.Н.

doi:10.1134/s1062359016010052

Cited by 4 publications

(2 citation statements)

References 11 publications

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“…17221/69/202117221/69/ -CJFS 2015. Another technique represents immunohistochemical detection of mycobacterial antigens in tissue sections using antibodies conjugated to an enzyme (mostly horseradish peroxidase or alkaline phosphatase) catalysing a colour-producing reaction or antibodies tagged with a fluorophore (Humphrey and Weiner 1987;Mustafa et al 2006;Erokhina et al 2016;Solomon et al 2017).…”

Section: Reviewmentioning

confidence: 99%

Instrumental analytical tools for mycobacteria characterisation

Ozana¹,

Hruška²

2021

Czech J. Food Sci.

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Mycobacteria in drinking water and in the water of swimming pools, whirlpools, hydrotherapy facilities and aquaria contribute significantly to human exposure to triggers of immune regulated chronic inflammatory and autoimmune diseases. Technological elements of water distribution systems, especially their inner surface, taps, shower heads and blind spots where sediments settle, affect the number of mycobacteria in the water. The review presents the possibilities of using analytical instruments for rapid determination of mycobacteria and for their typing as an alternative to classical culture and a method of monitoring specific nucleic acid sequences by polymerase chain reaction (PCR). Information about the use of flow cytometry (FCM), matrix-assisted laser desorption ionisation time-of-flight (MALDI-TOF) spectrometry, Raman and infrared (IR) spectroscopy and biosensors are presented.

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Section: Reviewmentioning

confidence: 99%

Instrumental analytical tools for mycobacteria characterisation

Ozana¹,

Hruška²

2021

Czech J. Food Sci.

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“…Earlier, the following algorithm of analysis was developed for the search and identification of M. tuberculosis with the use of LSCM in lung tissue samples: (i) Automatic step-by-step scanning of a large slice (up to 10 mm 2 ) and subsequent stitching of the images, selection of the regions of caseous necrosis and the perifocal zone, based on morphological heterogeneity; (ii) Automatic scanning of full volumes (20–40 μm), in selected zones, at high resolution (using the objective 63×/1.40), subsequent search for M. tuberculosis in the stacks, evaluation of their distribution in the tissue, selection of the zones with their different distribution, and selection of the zones for further analysis; (iii) Morphological analysis of the colonies and solitary bacteria, 3D reconstructions if necessary (see below); and (iv) If necessary, confirmation of the specificity of immunochemical labelling [27].…”

Section: Introductionmentioning

confidence: 99%

Application of Laser Scanning Confocal Microscopy for the Visualization of M. tuberculosis in Lung Tissue Samples with Weak Ziehl–Neelsen Staining

Ерохина

Лепеха

Voronezhskaya

et al. 2019

JCM

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One of the key requirements for the diagnosis of pulmonary tuberculosis is the identification of M. tuberculosis in tissue. In this paper, we present the advantages of specific fluorescent antibody labelling, combined with laser scanning confocal microscopy (LSCM), for the detection of M. tuberculosis in histological specimens of lung tissues. We demonstrate that the application of LSCM allows: (i) The automatic acquisition of images of the whole slice and, hence, the determination of regions for subsequent analysis; (ii) the acquisition of images of thick (20–40 μm) slices at high resolution; (iii) single bacteria identification; and (iv) 3D reconstruction, in order to obtain additional information about the distribution, size, and morphology of solitary M. tuberculosis; as well as their aggregates and colonies, in various regions of tuberculosis inflammation. LSCM allows for the discrimination of the non-specific fluorescence of bacteria-like particles and their aggregates presented in histological lung samples, from the specific fluorescence of labelled M. tuberculosis, using spectrum emission analysis. The applied method was effective in the identification of M. tuberculosis in lung histological samples with weak Ziehl–Neelsen staining. Altogether, combining immunofluorescent labelling with the application of LSCM visualization significantly increases the effectiveness of M. tuberculosis detection.

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