Tilletia laevis strain:ATCC 42080
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA393337 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| Other | ||||
| SRR6305450_1.fastq.gz | Fastqsanger.gz | |||
| SRR6305450_2.fastq.gz | Fastqsanger.gz |
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Project description:It is of high importance to distinguish Tilletia caries and Tilletia laevis as causal agents of common bunt accurately from Tilletia controversa, the causal agent of dwarf bunt. All three of these wheat bunt diseases can lead to significant yield losses in crop production worldwide. But T. controversa is categorized as a quarantine pest in most areas of the world and must be discriminated from the T. caries / T. laevis complex. Usually, morphological characteristics of the teliospores are used to differentiate the three species. But due to natural hybridization and overlapping properties the discrimination is challenging. Germination behavior can also be considered for discrimination, but equivalent to their similar physiological and genetic traits the two agents of common bunt, T. caries and T. laevis could not be distinguished by this. It was suggested that the two species and maybe all three of those described Tilletia species might be conspecific. Up to now no molecular based method is available to differentiate the three species. Several studies have attempted the detection of the wheat bunt Tilletia species using PCR or other DNA-based methods. Other studies analyzed protein patterns with electrophoresis methods. But none of these approaches was able to distinguish between all of the three closely related Tilletia species. Several studies have shown that Matrix-Assisted Laser Desorption/Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) is a useful tool to differentiate closely related fungal species. The aim of this study was to assess whether MALDI-TOF MS analysis is able to distinguish specimens of the three closely related pathogens T. caries, T. laevis, and T. controversa and may constitute an alternative method to the usually used morphology-based identification. Therefore MALDI-TOF MS was used to create subproteome fingerprints of the teliospores of 69 Tilletia specimens. These fingerprints were analyzed by comparing the mass spectra to each other by high-throughput multidimensional scaling (HiT-MDS ) together with hierarchical cluster analysis (HCA). The second approach was performed by discriminant analysis of principal components (DAPC). MALDI-TOF MS has proven to be a useful method for distinguishing between T. controversa and the two causal agents of common bunt, using our developed method of direct analysis of teliospores, but was unable to separate T. caries and T. laevis species. We conclude a potentially conspecific status of T. caries and T. laevis or even two morphotypes of one common species, causing identical disease symptoms and sharing the same germination requirements along with a related protein composition, shown in this study. Our developed MALDI-TOF MS method can be helpful in testing Tilletia bunt balls collected during field inspections, especially with regard to quarantine regulations or for breeding applications and may also be transferred to analyze further challenging sample material.
2022-02-14 | PXD030401 | Pride
Project description:In this study the transcriptomes of Acinetobacter baumannii strains ATCC 17978 and 17978hm were compared. Strain 17978hm is a hns knockout derivative of strain ATCC 17978. Strain 17978hm displays a hyper-motile phenotype on semi-solid Mueller-Hinton (MH) media (0.25% agar). ATCC 17978 and 17978hm from an 37C overnight culture were transferred to the centre of the semi-solid MH plate and incubated at 37C for 8 hours. Only 17978hm cells displayed a motile phenotype and covered the complete surface of the plate. These motile 17978hm cells and the non-motile wild-type ATCC 17978 cells were harvested and RNA was isolated. The comparative transcriptome analysis was performed using the FairPlay labeling kit and a custom made Agilent MicroArray with probes designed to coding regions of the ATCC 17978 genome. The data was analyzed using Agilent GeneSpring GX9 and the significance analysis of microarray MS Excel add-on.
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