MaMYB4 is a negative regulator and a substrate of RING-type E3 ligases MaBRG2/3 in controlling banana fruit ripening.

Fruit ripening is a complex developmental process, which is modulated by both transcriptional and post-translational events. Control of fruit ripening is important in maintaining moderate quality traits and minimizing postharvest deterioration. In this study, we discovered that the transcription factor MaMYB4 acts as a negative regulator of fruit ripening in banana. The protein levels of MaMYB4 decreased gradually with banana fruit ripening, paralleling ethylene production, and decline in firmness. DNA affinity purification sequencing combined with RNA-sequencing analyses showed that MaMYB4 preferentially binds to the promoters of various ripening-associated genes including ethylene biosynthetic and cell wall modifying genes. Furthermore, ectopic expression of MaMYB4 in tomato delayed tomato fruit ripening, which was accompanied by downregulation of ethylene biosynthetic and cell wall modifying genes. Importantly, two RING finger E3 ligases MaBRG2/3, whose protein accumulation increased progressively with fruit ripening, were found to interact with and ubiquitinate MaMYB4, contributing to decreased accumulation of MaMYB4 during fruit ripening. Transient overexpression of MaMYB4 and MaBRG2/3 in banana fruit ripening delayed or promoted fruit ripening by inhibiting or stimulating ethylene biosynthesis, respectively. Taken together, we demonstrate that MaMYB4 negatively modulates banana fruit ripening, and that MaMYB4 abundance could be regulated by protein ubiquitination, thus providing insights into the role of MaMYB4 in controlling fruit ripening at both transcriptional and post-translational levels.

Relationship between the honeydew of mealy bugs and the growth of Phlebopus portentosus.

BACKGROUND: Phlebopus portentosus and mealy bugs form a fungus-insect gall on the roots of host plants. The fungus and mealy bugs benefit mutually through the gall, which is the key link in the nutritional mechanism of P. portentosus. The cavity of the fungus-insect gall provides an ideal shelter for mealy bugs survival and reproduction, but how does P. portentosus benefit from this symbiotic relationship? METHODOLOGY AND RESULTS: Anatomical examination of fungus-insect galls revealed that one or more mealy bugs of different generations were living inside the galls. The mealy bug's mouthpart could penetrate through the mycelium layer of the inside of the gall and suck plant juice from the host plant root. Mealy bugs excreted honeydew inside or outside the galls. The results of both honeydew agar medium and quartz tests showed that the honeydew can attract and promote the mycelial growth of P. portentosus. A test of the relationship between the honeydew and the formation of the fungus-insect gall showed that honeydew promoted gall formation. CONCLUSIONS: All experimental results in this study show that the honeydew secreted by mealy bugs can attract and promote the mycelial growth of P. portentosus, forming a fungus-insect gall, because mealy bugs' honeydew is rich in amino acids and sugars.

[Study on the Discrimination of Boletus Edulis from Different Years and Origins with FTIR].

In order to establish a rapid method for discriminating Boletus edulis mushroom, Fourier transform infrared spectroscopy combined with multivariate statistical analysis were used to study B. edulis which were collected from different origins and different years. The original infrared spectra of all the 152 B. edulis samples collected from 2011 to 2014 and 26 different areas of Yunnan Province were optimized with orthogonal signal correction and wavelet compression (OSCW) method. The spectral data that before and after being preprocessed with OSCW were analyzed with partial least squares discriminant analysis (PLS-DA). The classification results of PLS-DA were compared. Then the 152 B. edulis samples were randomly divided into a training set (120) and a validation set (32) to establish the PLS classification prediction model. The results showed that, after OSCW processing, the classification result of PLS-DA was significantly better than the other one which was not processed by OSCW. Principal component score plot can accurately distinguish B. edulis samples collected from different years and different origins. It indicated that OSCW can effectively eliminate the noise of spectra and reduce the unrelated interference information about the dependent variables to improve the accuracy and calculation speed of spectral analysis. Before OSCW preprocessed, the R2 and RMSEE of PLS model of the training set were 0.790 1 and 21.246 5 respectively while R2 and RMSEP of the model of validation set were 0.922 5 and 14.429 2. After OSCW pretreatment, R2 and RMSEE of the training set were 0.852 3 and 17.238 1 while R2 and RMSEP of validation set were 0.845 4 and 20.87. It suggested that OSCW could improve the predictive effect of the training set, but the over-fitting of OSCW-PLS may reduce the predictive ability of validation set. Therefore, it was unsuitable to establish a model with OSCW combined with PLS. In a conclusion, OSCW combined with PLS-DA can eliminate a large amount of spectrum interference information. This method could accurately distinguish B. edulis samples collected from different years and different origins. It could provide a reliable basis for the discrimination and classification of wild edible fungi.

[Discrimination of Boletus Tomentipes from Different Regions Based on Infrared Spectrum Combined with Principal Component Analysis and Cluster Analysis].

With the aim of establishing a rapid method to discriminate Boletus tomentipes samples from different regions, FTIR spectroscopy with the aid of principal component analysis and clustering analysis were used in the present study. The information of infrared spectra of B. tomentipes samples originated from 15 regions has been collected. The original infrared spectra was pretreated by multiplicative signal correction (MSC) in combination with second derivative and Norris smooth. The spectral data were analyzed by principal component analysis and cluster analysis after the optimal pretreatment of MSC+SD+ND (15, 5), and the reasons for the differences of B. tomentipes samples from different regions could be explained through the principal component loading plot. The results showed that, the RSDs of repeatability, accuracy and stability of the method were 0.17%, 0.08% and 0.27%, respectively, which indicated the method was stable and reliable. The cumulative contribution of first three principal components of PCA was 87.24% which could reflect the most information of the samples. Principal component scores scatter plot displaying the samples from same origin could clustered together and samples from different areas distributed in a relatively independent space. Which can distinguish samples collected from different origins, effectively. The loading plot of principal component showed that with the principal component contribution rate decreasing, the captured sample information of principal component was also reducing. In the wave number of 3 571, 2 958, 1 625, 1 456, 1 405, 1 340, 1 191, 1 143, 1 084, 935, 840, 727 cm-1, the first principal component captured a large amount of sample information which attributed to carbohydrates, proteins, amino acids, fat, fiber and other chemical substances. Which showed that the different contents of these chemical substances may be the basis of discrimination of B. tomentipes samples from different origins. Cluster analysis based on ward method and Euclidean distance has shown the classification and correlation among samples. Samples originated from 15 regions could be clustered correctly in accordance with the basic origins and the correct rate was 93.33%. Which can be used to identify and analyze B. tomentipes collected from different sites. Fourier transform infrared spectroscopy combined with principal component analysis and cluster analysis can be effectively used to discriminate origins of B. tomentipes mushrooms and the reasons for the differences of B. tomentipes samples from different regions could be explained. This method could provide a reliable basis for discrimination and application of wild edible mushrooms.

[Infrared Spectroscopy Combined with Chemometrics for Rapid Discrimination on Species of Bolete Mushrooms and an Analysis of Total Mercury].

Fourier transform infrared spectroscopy combined with chemometrics was used to establish a method for rapid identification of different species of bolete mushrooms and determination of total mercury (Hg). In this study, 15 species of bolete mushrooms were used and the information of infrared spectra of 48 samples was collected. Meanwhile, the total Hg was determined with cold-vapour atomic absorption spectroscopy and direct mercury analyzer. The food safety of bolete mushrooms was evaluated according to provisional tolerable weekly intake (PTWI) for Hg recommended by the United Nations food and agriculture organization and the World Health Organization (FAO/WHO). The original infrared spectra were optimized with Norris smooth, multiplicative signal correction (MSC), second derivative, orthogonal signal correction and wavelet compression (OSCW). The spectra data were analyzed with principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) after the optimal pretreatment. Then the discrimination model for different species of bolete mushrooms and prediction model of Hg content were established, respectively. The results showed that: (1) The cumulative contribution of first three principal components of PCA was 77.1%. Different species of boletes can be obviously distinguished in principal component score plot. It indicated that the chemical composition or contents were different in these species of boletes. (2) There were significant differences in total Hg contents in different samples and the total Hg content in the boletes were 0.17～15.2 mg·kg-1 dry weight (dw). If adults (60 kg) ate 300 g fresh bolete mushrooms a week, Hg intakes in a few samples were higher than the PTWI standard with potential risks. (3) The infrared spectra data in combination with the total Hg content was performed by partial least squares discriminant analysis. The mushroom samples with low (≤1.95 mg·kg-1 dw), medium (2.05～3.9 mg·kg-1 dw) and high (≥4.1 mg·kg-1 dw) total Hg content could be discriminated. Moreover, the more different the Hg content was, the more easily to distinguish. In addition, the prediction model of total Hg content of boletes was established. The R2 and RMSEE of the training set were 0.911 4 and 1.09, respectively while R2 and RMSEP of validation set were 0.949 7 and 0.669 5, respectively. The predictive values of total Hg content in boletes were approximate to the measured values which showed that the model has good predictive effect. Infrared spectroscopy combined with chemometrics can be used for rapid identification of bolete species and discrimination of bolete samples with different contents of total Hg. Furthermore, the total Hg content could also be predicted, accurately. This study may provide a rapid and simple method for quality control and edible safety assessment of wild-grown bolete mushrooms.