New methods of removing debris and high-throughput counting of cyst nematode eggs extracted from field soil
Autoři:
Upender Kalwa aff001; Christopher Legner aff001; Elizabeth Wlezien aff002; Gregory Tylka aff002; Santosh Pandey aff001
Působiště autorů:
Department of Electrical and Computer Engineering, Iowa State University, Ames, Iowa, United States of America
aff001; Department of Plant Pathology and Microbiology, Iowa State University, Ames, Iowa, United States of America
aff002
Vyšlo v časopise:
PLoS ONE 14(10)
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pone.0223386
Souhrn
The soybean cyst nematode (SCN), Heterodera glycines, is the most damaging pathogen of soybeans in the United States. To assess the severity of nematode infestations in the field, SCN egg population densities are determined. Cysts (dead females) of the nematode must be extracted from soil samples and then ground to extract the eggs within. Sucrose centrifugation commonly is used to separate debris from suspensions of extracted nematode eggs. We present a method using OptiPrep as a density gradient medium with improved separation and recovery of extracted eggs compared to the sucrose centrifugation technique. Also, computerized methods were developed to automate the identification and counting of nematode eggs from the processed samples. In one approach, a high-resolution scanner was used to take static images of extracted eggs and debris on filter papers, and a deep learning network was trained to identify and count the eggs among the debris. In the second approach, a lensless imaging setup was developed using off-the-shelf components, and the processed egg samples were passed through a microfluidic flow chip made from double-sided adhesive tape. Holographic videos were recorded of the passing eggs and debris, and the videos were reconstructed and processed by custom software program to obtain egg counts. The performance of the software programs for egg counting was characterized with SCN-infested soil collected from two farms, and the results using these methods were compared with those obtained through manual counting.
Klíčová slova:
Imaging techniques – Filter paper – Deep learning – Computer software – Microfluidics – Sucrose – Centrifugation – Density gradient centrifugation
Zdroje
1. Allen TW, Bradley CA, Sisson AJ, Byamukama E, Chilvers MI, Coker CM, et al. Soybean yield loss estimates due to diseases in the United States and Ontario, Canada, from 2010 to 2014. Plant Heal Prog. 2017;18: 19–27. doi: 10.1094/PHP-RS-16-0066
2. Gerdemann JW. Relation of a large soil-borne spore to phycomycetous mycorrhizal infections. Mycologia. 1955;47: 619. doi: 10.2307/3755574
3. Byrd DW, Barker KR, Ferris H, Nusbaum CJ, Griffin WE, Small RH, et al. Two semi-automatic elutriators for extracting nematodes and certain fungi from soil. J Nematol. 1976;8: 206–12. Available: http://www.ncbi.nlm.nih.gov/pubmed/19308224%0Ahttp://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC2620186 19308224
4. Niblack TL, Heinz RD, Smith GS, Donald PA. Distribution, density, and diversity of Heterodera glycines in Missouri. J Nematol. 1993;25: 880–6. Available: http://www.ncbi.nlm.nih.gov/pubmed/19279857%0Ahttp://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC2619456 19279857
5. Faghihi J, Ferris JM. An efficient new device to release eggs from Heterodera glycines. J Nematol. 2000;32: 411–413. Available: http://journals.fcla.edu/jon/article/view/67182%5Cnhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC2620471 19270996
6. Beeman AQ, Tylka GL. Assessing the effects of ILeVO and VOTiVO seed treatments on reproduction, hatching, motility, and root penetration of the soybean cyst nematode, Heterodera glycines. Plant Dis. 2018;102: 107–113. doi: 10.1094/PDIS-04-17-0585-RE 30673448
7. Hajihassani A, Dandurand L-M. An improved technique for sorting developmental stages and assessing egg viability of Globodera pallida using high-throughput complex object parametric analyzer and sorter. Plant Dis. 2018;102: 2001–2008. doi: 10.1094/PDIS-09-17-1428-RE 30133359
8. Tylka GL, Niblack TL, Walk TC, Harkins KR, Barnett L, Baker NK. Flow cytometric analysis and sorting of Heterodera glycines eggs. J Nematol. 1993;25: 596–602. Available: http://www.ncbi.nlm.nih.gov/pubmed/19279815 19279815
9. Jenkins WR. A rapid centrifugal-flotation technique for separating nematodes from soil. Plant Dis Report. 1964;48.
10. Deng D, Zipf A, Tilahun Y, Sharma GC, Jenkins J, Lawrence K. An improved method for the extraction of nematodes using iodixanol (OptiPrep TM). J Microbiol. 2008; 167–170.
11. Beeman AQ, Njus ZL, Pandey S, Tylka GL. Chip technologies for screening chemical and biological agents against plant-parasitic nematodes. Phytopathology. 2016;106: 1563–1571. doi: 10.1094/PHYTO-06-16-0224-R 27452899
12. Tylka GL. Acid Fuchsin Stain Preparation [Internet]. 2012. Available: https://www.plantpath.iastate.edu/tylkalab/content/acid-fuchsin-stain-preparation
13. XU Z, Cheng XE. Zebrafish tracking using convolutional neural networks. Sci Rep. Nature Publishing Group; 2017;7: 42815. doi: 10.1038/srep42815 28211462
14. Masci J, Meier U, Cireşan D, Schmidhuber J. Stacked convolutional auto-encoders for hierarchical feature extraction. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2011. pp. 52–59. doi: 10.1007/978-3-642-21735-7_7
15. Ronneberger O, Fischer P, Brox T. U-net: Convolutional networks for biomedical image segmentation. Lect Notes Comput Sci (including Subser Lect Notes Artif Intell Lect Notes Bioinformatics). 2015;9351: 234–241. doi: 10.1007/978-3-319-24574-4_28
16. Kingma DP, Ba J. Adam: A method for stochastic optimization. Proc 12th Annu Conf Genet Evol Comput—GECCO ‘10. 2014; 103. doi: 10.1145/1830483.1830503
17. Chollet François. Keras: The python deep learning library. keras.io. 2015. doi: 10.1086/316861
18. Abadi M, Barham P, Chen J, Chen Z, Davis A, Dean J, et al. TensorFlow: A system for large-scale machine learning. 12th USENIX Symposium on Operating Systems Design and Implementation. 2016. pp. 265–283.
19. Structural analysis and shape descriptors [Internet]. 2018. Available https://docs.opencv.org/2.4/modules/imgproc/doc/structural_analysis_and_shape_descriptors.html
20. Mudanyali O, Tseng D, Oh C, Isikman SO, Sencan I, Bishara W, et al. Compact, light-weight and cost-effective microscope based on lensless incoherent holography for telemedicine applications. Lab Chip. 2010;10: 1417. doi: 10.1039/c000453g 20401422
21. Silvanmelchior. RPi_Cam_Web_Interface [Internet]. github.com; 2014. Available: https://github.com/silvanmelchior/RPi_Cam_Web_Interface
22. Isikman SO, Greenbaum A, Lee M, Bishara W, Mudanyali O. Modern trends in imaging viii: lensfree computational microscopy tools for cell and tissue imaging at the point-of-care and in low-resource settings. Anal Cell Pathol. 2012;35: 229–247. doi: 10.3233/ACP-2012-0057 22433451
23. Dovhaliuk RY. Review of digital holography reconstruction methods. In: Angelsky O V., editor. Thirteenth International Conference on Correlation Optics. SPIE; 2018. p. 5. doi: 10.1117/12.2300759
24. Bao P, Situ G, Pedrini G, Osten W. Lensless phase microscopy using phase retrieval with multiple illumination wavelengths. Appl Opt. 2012;51: 5486–94. doi: 10.1364/AO.51.005486 22859039
25. Zuo C, Sun J, Zhang J, Hu Y, Chen Q. Lensless phase microscopy and diffraction tomography with multi-angle and multi-wavelength illuminations using a LED matrix. Opt Express. 2015;23: 14314. doi: 10.1364/OE.23.014314 26072796
26. Van Bezooijen J. Methods and techniques for nematology. Wageningen University; 2006.
27. Akintayo A, Tylka GL, Singh AK, Ganapathysubramanian B, Singh A, Sarkar S. A deep learning framework to discern and count microscopic nematode eggs. Sci Rep. 2018;8: 9145. doi: 10.1038/s41598-018-27272-w 29904135
Článok vyšiel v časopise
PLOS One
2019 Číslo 10
- Metamizol jako analgetikum první volby: kdy, pro koho, jak a proč?
- Nejasný stín na plicích – kazuistika
- Masturbační chování žen v ČR − dotazníková studie
- Těžké menstruační krvácení může značit poruchu krevní srážlivosti. Jaký management vyšetření a léčby je v takovém případě vhodný?
- Fixní kombinace paracetamol/kodein nabízí synergické analgetické účinky
Najčítanejšie v tomto čísle
- Correction: Low dose naltrexone: Effects on medication in rheumatoid and seropositive arthritis. A nationwide register-based controlled quasi-experimental before-after study
- Combining CDK4/6 inhibitors ribociclib and palbociclib with cytotoxic agents does not enhance cytotoxicity
- Experimentally validated simulation of coronary stents considering different dogboning ratios and asymmetric stent positioning
- Risk factors associated with IgA vasculitis with nephritis (Henoch–Schönlein purpura nephritis) progressing to unfavorable outcomes: A meta-analysis