Back

A fluorescence-based viability assay for Phytophthora agathidicida oospores

Fairhurst, M. J.; Deslippe, J. R.; Gerth, M. L.

2021-10-18 microbiology
10.1101/2021.10.17.464154 bioRxiv
Show abstract

Phytophthora are eukaryotic microbes that cause disease in a wide range of agriculturally and ecologically important plants. During the Phytophthora disease cycle, thick-walled oospores can be produced via sexual reproduction. These resting spores can survive in the soil for several years in the absence of a host plant, thus providing a long-term inoculum for disease. The ability to quantitatively evaluate oospore viability is an important part of many phytopathology studies. Here, we tested six fluorescent viability dyes for their ability to differentially stain Phytophthora agathidicida oospores: SYTO 9, FUN-1, fluorescein diacetate (FDA), 5-carboxyfluorescein diacetate (CFDA), propidium iodide, and TOTO-3 iodide. Each dye was first tested individually with untreated or heat-treated oospores as proxies for viable and non-viable oospores, respectively. SYTO9, FUN-1, CFDA and propidium iodide stained untreated and heat-treated oospores indiscriminately. In contrast, FDA (a green-fluorescent viable cell stain) and TOTO-3 (a red-fluorescent non-viable cell stain) differentially stained untreated or heat-treated oospores with no cross-fluorescence. We then tested the efficacy of dual viability staining and in conjunction with a pipeline for automated image analysis. To validate the method, untreated and heat-treated oospores were mixed at specific ratios, dual-stained, and analyzed using the pipeline. Linear regression of the resulting data showed a clear correlation between the expected and measured oospore ratios (dy/dx=0.95, R2=0.88). Overall, the combination of dual-fluorescence staining and automated image analysis provides a high-throughput method for quantitatively assessing oospore viability and therefore can facilitate further studies on this key part of the Phytophthora disease cycle.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

1
Phytopathology®
28 papers in training set
Top 0.1%
25.7%
2
PLOS ONE
4510 papers in training set
Top 25%
6.8%
3
Plant Pathology
16 papers in training set
Top 0.1%
6.4%
4
Scientific Reports
3102 papers in training set
Top 18%
6.4%
5
Journal of Microbiological Methods
11 papers in training set
Top 0.1%
6.3%
50% of probability mass above
6
New Phytologist
309 papers in training set
Top 1%
6.3%
7
mSphere
281 papers in training set
Top 1%
4.2%
8
Plant Disease
21 papers in training set
Top 0.1%
3.6%
9
Applied and Environmental Microbiology
301 papers in training set
Top 1%
2.7%
10
Frontiers in Plant Science
240 papers in training set
Top 3%
2.4%
11
Microbiology Spectrum
435 papers in training set
Top 2%
1.9%
12
Frontiers in Microbiology
375 papers in training set
Top 5%
1.7%
13
Pest Management Science
32 papers in training set
Top 0.6%
1.5%
14
PLOS Computational Biology
1633 papers in training set
Top 19%
1.3%
15
Plant Direct
81 papers in training set
Top 2%
1.1%
16
G3
33 papers in training set
Top 0.3%
1.0%
17
Journal of Fungi
31 papers in training set
Top 0.5%
0.8%
18
Fungal Genetics and Biology
14 papers in training set
Top 0.2%
0.8%
19
Environmental Microbiology
119 papers in training set
Top 3%
0.8%
20
Plant Methods
39 papers in training set
Top 0.7%
0.7%
21
mBio
750 papers in training set
Top 11%
0.7%
22
Journal of Visualized Experiments
30 papers in training set
Top 0.8%
0.7%
23
Methods in Ecology and Evolution
160 papers in training set
Top 2%
0.7%
24
Journal of Applied Microbiology
18 papers in training set
Top 0.5%
0.7%
25
Environmental Microbiology Reports
27 papers in training set
Top 0.8%
0.7%
26
BioTechniques
24 papers in training set
Top 0.4%
0.6%
27
Molecular Plant Pathology
22 papers in training set
Top 0.3%
0.6%
28
BMC Biology
248 papers in training set
Top 6%
0.6%