Small peptides,big roles ‒ RALFs regulate pollen tube growth and burst in plant reproduction

正In flowering plants,the pollen grain generates a pollen tube to deliver two immotile sperm cells to the embryo sac for double fertilization.After landing on the stigma of the pistil,the pollen grain hydrates and germinates to produce a pollen tube,which penetrates the style and grows into the transmitting tract.The pollen tube then emerges onto the surface of the septum,grows along the funiculus,responds to the attraction signals from the synergid cells of the embryo sac and targets the ovule micropyle.     

Adsorption of DNA by Bacteria and Their Composites with Minerals

Previous studies revealed the thermodynamic properties of DNA adsorption on pure minerals or biomasses; however, there has been little attempt to develop such studies on bacteria–mineral composites. Equilibrium adsorption experiments, attenuated total reflectance Fourier transform infrared spectroscopy, and isothermal titration calorimetry were employed to investigate the adsorption of DNA by Bacillus subtilis, Pseudomonas putida, and their composites with minerals. Similar capacity and affinity were observed for DNA adsorption on two bacterial cells. However, different patterns were found in the adsorption of DNA by bacteria–mineral composites. The Gram-positive bacterium B. subtilis enhanced the adsorption of DNA on its mineral composites compared with their individual components, while the composites of Gram-negative bacterial cells with kaolinite and goethite bound lower amounts of DNA than the predicted values. The thermodynamic parameters and the Fourier transform infrared spectra showed that van der Waals force and hydrogen bonding are responsible for the DNA adsorption on B. subtilis–minerals and P. putida–kaolinite. By contrast, the entropy increases of excluded water rearrangement and dehydration effect play key roles in the interaction between DNA and P. putida–montmorillonite/goethite composites.     

Host-Parasite Interactions and Purifying Selection in a Microsporidian Parasite of Honey Bees

To clarify the mechanisms of Nosema ceranae parasitism, we deep-sequenced both honey bee host and parasite mRNAs throughout a complete 6-day infection cycle. By time-series analysis, 1122 parasite genes were significantly differently expressed during the reproduction cycle, clustering into 4 expression patterns. We found reactive mitochondrial oxygen species modulator 1 of the host to be significantly down regulated during the entire infection period. Our data support the hypothesis that apoptosis of honey bee cells was suppressed during infection. We further analyzed genome-wide genetic diversity of this parasite by comparing samples collected from the same site in 2007 and 2013. The number of SNP positions per gene and the proportion of non-synonymous substitutions per gene were significantly reduced over this time period, suggesting purifying selection on the parasite genome and supporting the hypothesis that a subset of N. ceranae strains might be dominating infection.     

Phenotype Classification of Zebrafish Embryos by Supervised Learning

Zebrafish is increasingly used to assess biological properties of chemical substances and thus is becoming a specific tool for toxicological and pharmacological studies. The effects of chemical substances on embryo survival and development are generally evaluated manually through microscopic observation by an expert and documented by several typical photographs. Here, we present a methodology to automatically classify brightfield images of wildtype zebrafish embryos according to their defects by using an image analysis approach based on supervised machine learning. We show that, compared to manual classification, automatic classification results in 90 to 100% agreement with consensus voting of biological experts in nine out of eleven considered defects in 3 days old zebrafish larvae. Automation of the analysis and classification of zebrafish embryo pictures reduces the workload and time required for the biological expert and increases the reproducibility and objectivity of this classification.