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Real-time detection and identification of nematode eggs genus and species through optical imaging
Nematode eggs are pervasive pathogens that infect billions of people and livestock every year. Adult parasitic nematode worms can be distinguished based on their size and morphology. However, their eggs, particularly their species Ascaris lumbricoides and Ascaris suum cannot be identified from each...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7190725/ https://www.ncbi.nlm.nih.gov/pubmed/32350308 http://dx.doi.org/10.1038/s41598-020-63747-5 |
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author | Qazi, Farah Khalid, Asma Poddar, Arpita Tetienne, Jean-Philippe Nadarajah, Athavan Aburto-Medina, Arturo Shahsavari, Esmaeil Shukla, Ravi Prawer, Steven Ball, Andrew S. Tomljenovic-Hanic, Snjezana |
author_facet | Qazi, Farah Khalid, Asma Poddar, Arpita Tetienne, Jean-Philippe Nadarajah, Athavan Aburto-Medina, Arturo Shahsavari, Esmaeil Shukla, Ravi Prawer, Steven Ball, Andrew S. Tomljenovic-Hanic, Snjezana |
author_sort | Qazi, Farah |
collection | PubMed |
description | Nematode eggs are pervasive pathogens that infect billions of people and livestock every year. Adult parasitic nematode worms can be distinguished based on their size and morphology. However, their eggs, particularly their species Ascaris lumbricoides and Ascaris suum cannot be identified from each other. Identifying eggs of helminths from wastewater and sludge is important from a public health perspective to minimize the spread of Ascaris infections. Numerous methods exist for nematode identification, from a morphological-based approach to high throughput sequencing technology. However, these techniques are not consistent and often laborious and time-consuming. In this study, we demonstrate that non-invasive real-time identification of eggs is possible based on their intrinsic fluorescence. Using confocal microscopy, we investigate the autofluorescence properties of five species of nematode eggs and observe clear differences between genus and for the first time their species in sludge samples. This non-invasive imaging technique could lead to better understanding of these species and may assist in early control of diseases. |
format | Online Article Text |
id | pubmed-7190725 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-71907252020-05-05 Real-time detection and identification of nematode eggs genus and species through optical imaging Qazi, Farah Khalid, Asma Poddar, Arpita Tetienne, Jean-Philippe Nadarajah, Athavan Aburto-Medina, Arturo Shahsavari, Esmaeil Shukla, Ravi Prawer, Steven Ball, Andrew S. Tomljenovic-Hanic, Snjezana Sci Rep Article Nematode eggs are pervasive pathogens that infect billions of people and livestock every year. Adult parasitic nematode worms can be distinguished based on their size and morphology. However, their eggs, particularly their species Ascaris lumbricoides and Ascaris suum cannot be identified from each other. Identifying eggs of helminths from wastewater and sludge is important from a public health perspective to minimize the spread of Ascaris infections. Numerous methods exist for nematode identification, from a morphological-based approach to high throughput sequencing technology. However, these techniques are not consistent and often laborious and time-consuming. In this study, we demonstrate that non-invasive real-time identification of eggs is possible based on their intrinsic fluorescence. Using confocal microscopy, we investigate the autofluorescence properties of five species of nematode eggs and observe clear differences between genus and for the first time their species in sludge samples. This non-invasive imaging technique could lead to better understanding of these species and may assist in early control of diseases. Nature Publishing Group UK 2020-04-29 /pmc/articles/PMC7190725/ /pubmed/32350308 http://dx.doi.org/10.1038/s41598-020-63747-5 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Qazi, Farah Khalid, Asma Poddar, Arpita Tetienne, Jean-Philippe Nadarajah, Athavan Aburto-Medina, Arturo Shahsavari, Esmaeil Shukla, Ravi Prawer, Steven Ball, Andrew S. Tomljenovic-Hanic, Snjezana Real-time detection and identification of nematode eggs genus and species through optical imaging |
title | Real-time detection and identification of nematode eggs genus and species through optical imaging |
title_full | Real-time detection and identification of nematode eggs genus and species through optical imaging |
title_fullStr | Real-time detection and identification of nematode eggs genus and species through optical imaging |
title_full_unstemmed | Real-time detection and identification of nematode eggs genus and species through optical imaging |
title_short | Real-time detection and identification of nematode eggs genus and species through optical imaging |
title_sort | real-time detection and identification of nematode eggs genus and species through optical imaging |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7190725/ https://www.ncbi.nlm.nih.gov/pubmed/32350308 http://dx.doi.org/10.1038/s41598-020-63747-5 |
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