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Case study of combinatorial imaging: What protocol and what chlorophyll fluorescence image to use when visualizing infection of Arabidopsis thaliana by Pseudomonas syringae?

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Abstract

Localized infection of a plant can be mapped by a sequence of images capturing chlorophyll fluorescence transients in actinic light. Choice of the actinic light protocol co-determines fluorescence contrast between infected leaf segment and surrounding healthy tissue. Frequently, biology cannot predict with which irradiance protocol, in which fluorescence image of the sequence, and in which segment of the image there will be the highest contrast between the healthy and infected tissue. Here, we introduce a new technique that can be applied to identify the combination of chlorophyll fluorescence images yielding the highest contrast. The sets of the most contrasting images vary throughout the progress of the infection. Such specific image sets, stress-revealing fluorescence signatures, can be found for the initial and late phases of the infection. Using these signatures, images can be divided into segments that show tissue in different infection phases. We demonstrate the capacity of the algorithm in an investigation of infection of the model plant Arabidopsis thaliana by the bacterium Pseudomonas syringae. We show that the highest contrast is found with transients elicited by fluctuating, harmonically modulated irradiance with long periods.

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Notes

  1. Although not used in plant physiology, the F 0/F V parameter measured at 692 nm and at −196°C was introduced by Kitajima and Butler (1975) to estimate energy transport from Photosystem II to Photosystem I.

  2. Note that this procedure served only to evaluate the classification performance of a particular image set and not to classify leaf segments.

Abbreviations

A j :

Amplitude of the fundamental harmonic component of the fluorescence transient (j = 0), of the first upper harmonic component (j = 1), and of the second upper harmonic component (j = 2)

C 0 :

Set of pixels with transients of fluorescence from healthy tissue

C 1 :

Set of pixels from healthy tissue after advanced image segmentation

D ab :

Euklidian distance of fluorescence signals in pixels a and b

F a j :

Fluorescence signal in image j, pixel a

F 0 :

Fluorescence emission of a dark-adapted plant

F ′0 :

Fluorescence emission of a light adapted plant measured with the primary acceptor Q A oxidized

F M :

Fluorescence emission of a dark-adapted plant

F M(j)′:

Maximum fluorescence emission of a light adapted plant measured during a strong pulse of light(j is the index of the pulse)

F S :

steady-state fluorescence emission

F V = F M − F 0 :

Variable fluorescence measured in dark-adapted plant

F V/F M :

Maximum fluorescence yield of PSII

F p :

Fluorescence in the peak

I 0 :

Set of pixels and fluorescence transients from the half of the leaf that is inoculated with the bacteria

I 1 :

Sub-set of I 0 obtained by elimination of pixels that although from the inoculated leaf do not exhibit symptoms of an infection

k-NN:

k-nearest neighbor classifier

M :

number of erroneous classifications

N :

number of correct classifications

NPQ = (F M − F ′M(3) )/F ′M(3) ):

Non-photochemical quenching

P :

Performance of the classifier P = (N − M)/(N + M)

PSII:

Photosystem II

Q A , Q B :

Primary and secondary quinone acceptors of PSII

Rfd = (F P − F S)/F S :

Fluorescence decline ratio

SFFS:

Sequentional forward floating search

T :

Period of harmonically modulated actinic light

ΦPSII = (F ′M(3)  − F S)/F ′M(3) :

Quantum yield of PSII electron transport measured during the third saturating flash of light

ϕ j :

Phase of the fundamental harmonic component of the fluorescence transient (j = 0), of the first upper harmonic component (j = 1), and of the second upper harmonic component (j = 2)

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Acknowledgment

This work was supported in part by the Czech Ministry of Education, Sports and Youth under the Grant MSM6007665808, by the Czech Academy of Sciences Grant AV0Z60870520, by the Grant Agency of the Czech Republic GACR 206/05/0894 and by the cooperative grants DAAD/CAS D28-CZ31/04-05(TR) and the SFB 567 (SB). Authors thank Dr. Somol of the Institute of Information Theory and Automation of the Czech Academy of Sciences for reading the manuscript. Technical assistance of Ms. Sigrid Lux from Julius-von-Sachs-Institute of Biosciences, was essential for performing the biological experiments.

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Authors and Affiliations

  1. Institute of Systems Biology and Ecology, Academy of Sciences of the Czech Republic, Zámek 136, Nové Hrady, 37333, Czech Republic

    Karel Matouš, Zuzana Benediktyová & Ladislav Nedbal

  2. Institute of Physical Biology, University of S. Bohemia, Zámek 136, 37333, Nové Hrady, Czech Republic

    Karel Matouš, Zuzana Benediktyová & Ladislav Nedbal

  3. Department of Pharmaceutical Biology, Julius-von-Sachs-Institute of Biosciences, Julius-von-Sachs-Platz 2, 97082, Wurzburg, Germany

    Susanne Berger & Thomas Roitsch

Authors
  1. Karel Matouš
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  2. Zuzana Benediktyová
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  3. Susanne Berger
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  4. Thomas Roitsch
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  5. Ladislav Nedbal
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Correspondence to Ladislav Nedbal.

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Matouš, K., Benediktyová, Z., Berger, S. et al. Case study of combinatorial imaging: What protocol and what chlorophyll fluorescence image to use when visualizing infection of Arabidopsis thaliana by Pseudomonas syringae?. Photosynth Res 90, 243–253 (2006). https://doi.org/10.1007/s11120-006-9120-6

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