SnTox3 Acts in Effector Triggered Susceptibility to Induce Disease on Wheat Carrying the Snn3 Gene

The necrotrophic fungus Stagonospora nodorum produces multiple proteinaceous host-selective toxins (HSTs) which act in effector triggered susceptibility. Here, we report the molecular cloning and functional characterization of the SnTox3-encoding gene, designated SnTox3, as well as the initial characterization of the SnTox3 protein. SnTox3 is a 693 bp intron-free gene with little obvious homology to other known genes. The predicted immature SnTox3 protein is 25.8 kDa in size. A 20 amino acid signal sequence as well as a possible pro sequence are predicted. Six cysteine residues are predicted to form disulfide bonds and are shown to be important for SnTox3 activity. Using heterologous expression in Pichia pastoris and transformation into an avirulent S. nodorum isolate, we show that SnTox3 encodes the SnTox3 protein and that SnTox3 interacts with the wheat susceptibility gene Snn3. In addition, the avirulent S. nodorum isolate transformed with SnTox3 was virulent on host lines expressing the Snn3 gene. SnTox3-disrupted mutants were deficient in the production of SnTox3 and avirulent on the Snn3 differential wheat line BG220. An analysis of genetic diversity revealed that SnTox3 is present in 60.1% of a worldwide collection of 923 isolates and occurs as eleven nucleotide haplotypes resulting in four amino acid haplotypes. The cloning of SnTox3 provides a fundamental tool for the investigation of the S. nodorum-wheat interaction, as well as vital information for the general characterization of necrotroph-plant interactions.This work was supported by USDA-ARS CRIS projects 5442-22000-043-00D and 5442-22000-030-00D

Identification of quantitative trait loci conferring resistance to tan spot in a biparental population derived from two Nebraska hard red winter wheat cultivars

Tan spot, caused by Pyrenophora triticirepentis (Ptr), is a destructive foliar disease in all types of cultivated wheat worldwide. Genetics of tan spot resistance in wheat is complex, involving insensitivity to fungal-produced necrotrophic effectors (NEs), major resistance genes, and quantitative trait loci (QTL) conferring race-nonspecific and race-specific resistance. The Nebraska hard red winter wheat (HRWW) cultivar ‘Wesley’ is insensitive to Ptr ToxA and highly resistant to multiple Ptr races, but the genetics of resistance in this cultivar is unknown. In this study, we used a recombinant inbred line (RIL) population derived from a cross between Wesley and another Nebraska cultivar ‘Harry’ (Ptr ToxA sensitive and highly susceptible) to identify QTL associated with reaction to tan spot caused by multiple races/isolates. Sensitivity to Ptr ToxA conferred by the Tsn1 gene was mapped to chromosome 5B as expected. The Tsn1 locus was a major susceptibility QTL for the race 1 and race 2 isolates, but not for the race 2 isolate with the ToxA gene deleted. A second major susceptibility QTL was identified for all the Ptr ToxC-producing isolates and located to the distal end of the chromosome 1A, which likely corresponds to the Tsc1 locus. Three additional QTL with minor effects were identified on chromosomes 7A, 7B, and 7D. This work indicates that both Ptr ToxA-Tsn1 and Ptr ToxC-Tsc1 interactions are important for tan spot development in winter wheat, and Wesley is highly resistant largely due to the absence of the two tan spot sensitivity genes

Multidisciplinary team meetings and their impact on workflow in radiology and pathology departments

<p>Abstract</p> <p>Background</p> <p>The development of multidisciplinary team meetings (MDTMs) for radiology and pathology is a burgeoning area that increasingly impacts on work processes in both of these departments. The aim of this study was to examine work processes and quantify the time demands on radiologists and pathologists associated with MDTM practices at a large teaching hospital. The observations reported in this paper reflect a general trend affecting hospitals and our conclusions will have relevance for others implementing clinical practice guidelines.</p> <p>Methods</p> <p>For one month, all work related to clinical meetings between pathology and radiology with clinical staff was documented and later analysed.</p> <p>Results</p> <p>The number of meetings to which pathology and radiology contribute at a large university teaching hospital, ranges from two to eight per day, excluding grand rounds, and amounts to approximately 50 meetings per month for each department. For one month, over 300 h were spent by pathologists and radiologists on 81 meetings, where almost 1000 patients were discussed. For each meeting hour, there were, on average, 2.4 pathology hours and 2 radiology hours spent in preparation. Two to three meetings per week are conducted over a teleconferencing link. Average meeting time is 1 h. Preparation time per meeting ranges from 0.3 to 6 h for pathology, and 0.5 to 4 for radiology. The review process in preparation for meetings improves internal quality standards. Materials produced externally (for example imaging) can amount to almost 50% of the material to be reviewed on a single patient. The number of meetings per month has increased by 50% over the past two years. Further increase is expected in both the numbers and duration of meetings when scheduling issues are resolved. A changing trend in the management of referred patients with the development of MDTMs and the introduction of teleconferencing was noted.</p> <p>Conclusion</p> <p>Difficulties are being experienced by pathology and radiology departments participating fully in several multidisciplinary teams. Time spent at meetings, and in preparation for MDTMs is significant. Issues of timing and the coordination of materials to be reviewed are sometimes irreconcilable. The exchange of patient materials with outside institutions is a cause for concern when full data are not made available in a timely fashion. The process of preparation for meetings is having a positive influence on quality, but more resources are needed in pathology and radiology to realise the full benefits of multidisciplinary team working.</p

Robust automated detection of microstructural white matter degeneration in Alzheimer’s disease using machine learning classification of multicenter DTI data

Diffusion tensor imaging (DTI) based assessment of white matter fiber tract integrity can support the diagnosis of Alzheimer’s disease (AD). The use of DTI as a biomarker, however, depends on its applicability in a multicenter setting accounting for effects of different MRI scanners. We applied multivariate machine learning (ML) to a large multicenter sample from the recently created framework of the European DTI study on Dementia (EDSD). We hypothesized that ML approaches may amend effects of multicenter acquisition. We included a sample of 137 patients with clinically probable AD (MMSE 20.6±5.3) and 143 healthy elderly controls, scanned in nine different scanners. For diagnostic classification we used the DTI indices fractional anisotropy (FA) and mean diffusivity (MD) and, for comparison, gray matter and white matter density maps from anatomical MRI. Data were classified using a Support Vector Machine (SVM) and a Naïve Bayes (NB) classifier. We used two cross-validation approaches, (i) test and training samples randomly drawn from the entire data set (pooled cross-validation) and (ii) data from each scanner as test set, and the data from the remaining scanners as training set (scanner-specific cross-validation). In the pooled cross-validation, SVM achieved an accuracy of 80% for FA and 83% for MD. Accuracies for NB were significantly lower, ranging between 68% and 75%. Removing variance components arising from scanners using principal component analysis did not significantly change the classification results for both classifiers. For the scanner-specific cross-validation, the classification accuracy was reduced for both SVM and NB. After mean correction, classification accuracy reached a level comparable to the results obtained from the pooled cross-validation. Our findings support the notion that machine learning classification allows robust classification of DTI data sets arising from multiple scanners, even if a new data set comes from a scanner that was not part of the training sample

Functional Analysis of the Two Brassica AP3 Genes Involved in Apetalous and Stamen Carpelloid Phenotypes

The Arabidopsis homeotic genes APETALA3 (AP3) and PISTILLATA (PI) are B genes which encode MADS-box transcription factors and specify petal and stamen identities. In the current study, the stamen carpelloid (SC) mutants, HGMS and AMS, of B. rapa and B. napus were investigated and two types of AP3 genes, B.AP3.a and B.AP3.b, were functional characterized. B.AP3.a and B.AP3.b share high similarity in amino acid sequences except for 8 residues difference located at the C-terminus. Loss of this 8 residues in B.AP3.b led to the change of PI-derived motifs. Meanwhile, B.AP3.a specified petal and stamen development, whereas B.AP3.b only specified stamen development. In B. rapa, the mutations of both genes generated the SC mutant HGMS. In B. napus that contained two B.AP3.a and two B.AP3.b, loss of the two B.AP3.a functions was the key reason for the apetalous mutation, however, the loss-of-function in all four AP3 was related to the SC mutant AMS. We inferred that the 8 residues or the PI-derived motif in AP3 gene probably relates to petal formation

SnTox3 Acts in Effector Triggered Susceptibility to Induce Disease on Wheat Carrying the Snn3 Gene

The necrotrophic fungus Stagonospora nodorum produces multiple proteinaceous host-selective toxins (HSTs) which act in effector triggered susceptibility. Here, we report the molecular cloning and functional characterization of the SnTox3-encoding gene, designated SnTox3, as well as the initial characterization of the SnTox3 protein. SnTox3 is a 693 bp intron-free gene with little obvious homology to other known genes. The predicted immature SnTox3 protein is 25.8 kDa in size. A 20 amino acid signal sequence as well as a possible pro sequence are predicted. Six cysteine residues are predicted to form disulfide bonds and are shown to be important for SnTox3 activity. Using heterologous expression in Pichia pastoris and transformation into an avirulent S. nodorum isolate, we show that SnTox3 encodes the SnTox3 protein and that SnTox3 interacts with the wheat susceptibility gene Snn3. In addition, the avirulent S. nodorum isolate transformed with SnTox3 was virulent on host lines expressing the Snn3 gene. SnTox3-disrupted mutants were deficient in the production of SnTox3 and avirulent on the Snn3 differential wheat line BG220. An analysis of genetic diversity revealed that SnTox3 is present in 60.1% of a worldwide collection of 923 isolates and occurs as eleven nucleotide haplotypes resulting in four amino acid haplotypes. The cloning of SnTox3 provides a fundamental tool for the investigation of the S. nodorum–wheat interaction, as well as vital information for the general characterization of necrotroph–plant interactions

Aeroelastic and Aerothermoelastic Behavior in Hypersonic Flow

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/77151/1/AIAA-36711-537.pd

Erratum to: 36th International Symposium on Intensive Care and Emergency Medicine

[This corrects the article DOI: 10.1186/s13054-016-1208-6.]