来自奥地利和丹麦的科学家，利用videometer多光谱成像系统发表了题为Identification of a bio-signature for barley resistance against Pyrenophora teres infection based on physiological, molecular and sensor-based phenotyping的文章，文章发表于Plant Science。

基于生理、分子和传感器表型鉴定大麦抗网斑病感染的生物标记

要点 

用表型组学方法评价四种大麦基因型对网斑病侵染

抗网斑病酶活性指纹图谱的鉴定

基因表达谱的不同时间动态反映了病原体的抗性

电阻与特定的反射率和荧光信号相关

基于传感器成像的病原体感染症状前检测

摘要 

大麦叶片感染网斑病期间诱导的坏死和褪绿症状表明一种相容的相互作用，使半生物营养真菌网斑病能够在寄主上定居。然而，这种真菌在侵染过程中如何影响抗病和感病品种的生理反应尚不清楚。为了评估四个不同品种的抗性程度，我们量化了可见症状和真菌DNA，并对参与植物防御和活性氧清除的基因进行了表达分析。为了深入了解真菌与宿主之间的相互作用，我们测定了碳水化合物和抗氧化代谢的19种关键酶的活性。通过基于传感器的多反射和荧光成像，病原体的影响也可非侵入性地表现出来。

症状、胁迫相关基因的调控和病原体DNA含量使品种Guld具有抗性。净斑点症状的严重程度也与感染第一天内的酶活性动态密切相关。与抗病品种相比，三个感病品种在七个光谱带上表现出更高的反射率，在特定激发波长下表现出更高的荧光强度。将半高通量生理和分子分析与非侵入性表型分析相结合，能够识别区分抗性品种和敏感品种的生物特征。

Identification of a bio-signature for barley resistance against Pyrenophora teres infection based on physiological, molecular and sensor-based phenotyping

Highlights 

Phenomics approach to assess infection of four barley genotypes by P. teres

Identification of an enzyme activity fingerprint for resistance against P. teres

Distinct temporal dynamics of gene expression profiles reflect pathogen resistance

Resistance correlates with a specific reflectance and fluorescence signaturePre-symptomatic detection of pathogen infection by sensor-based imaging

Abstract

Necrotic and chlorotic symptoms induced during Pyrenophora teres infection in barley leaves indicate a compatible interaction that allows the hemi-biotrophic fungus Pyrenophora teres to colonise the host. However, it is unexplored how this fungus affects the physiological responses of resistant and susceptible cultivars during infection. To assess the degree of resistance in four different cultivars, we quantified visible symptoms and fungal DNA and performed expression analyses of genes involved in plant defence and ROS scavenging. To obtain insight into the interaction between fungus and host, we determined the activity of 19 key enzymes of carbohydrate and antioxidant metabolism. The pathogen impact was also phenotyped non-invasively by sensor-based multireflectance and –fluorescence imaging.

Symptoms, regulation of stress-related genes and pathogen DNA content distinguished the cultivar Guld as being resistant. Severity of net blotch symptoms was also strongly correlated with the dynamics of enzyme activities already within the first day of infection. In contrast to the resistant cultivar, the three susceptible cultivars showed a higher reflectance over seven spectral bands and higher fluorescence intensities at specific excitation wavelengths. The combination of semi high-throughput physiological and molecular analyses with non-invasive phenotyping enabled the identification of bio-signatures that discriminates the resistant from susceptible cultivars.

Keywords

crop resistance

enzyme activity signatures

expression analysis

multispectral imaging

fungal DNA

PhenoLab

pre-symptomatic

bio-signatures