A new gene coding for <Emphasis Type="Italic">p</Emphasis>-coumarate 3-hydroxylase from <Emphasis Type="Italic">Ginkgo biloba</Emphasis>

p-Coumarate 3-hydroxylase (C3H) is a rate-limiting enzyme involved in monolignol biosynthesis. The full-length cDNA from Ginkgo biloba and genomic DNA sequence encoding C3H (designated as GbC3H) were cloned and characterized for the first time by rapid amplification of cDNA ends technique. The full-length cDNA of GbC3H was of 1860 bp containing a 1527 bp open reading frame encoding a cytochrome P450 protein of 508 amino acids with a calculated mol wt of 57.46 kD and an isoelectric point of 7.09. Two introns were present in the GbC3H gene. Comparative and bioinformatic analyses revealed that GbC3H had close similarity with C3Hs from other species and contained a conserved cytochrome P450 cysteine heme-iron ligand signature. Phylogenetic analysis indicated that GbC3H shared a common evolutionary origin based on sequence and had the closest relationship to C3H from gymnosperm species. Southern blot analysis indicated that GbC3H belonged to a small-gene family. Tissue expression pattern analysis revealed the highest expression of GbC3H in roots followed by leaves, and no expression was detected in stems. Only a few proteins of this class have been found, so the cloning and characterization of GbC3H will be useful in understanding the role of C3Hs in the lignin biosynthesis at the molecular level. This text was submitted by the authors in English.     

Survey and molecular detection of Melissococcus plutonius,the causative agent of European Foulbrood in honeybees in Saudi Arabia

A large-scale field survey was conducted to screen major Saudi Arabian beekeeping locations for infection by Melissococcus plutonius. M. plutonius is one of the major bacterial pathogens of honeybee broods and is the causative agent of European Foulbrood disease (EFB). Larvae from samples suspected of infection were collected from different apiaries and homogenized in phosphate buffered saline (PBS). Bacteria were isolated on MYPGP agar medium. Two bacterial isolates, ksuMP7 and ksuMP9 (16S rRNA GenBank accession numbers, KX417565 and KX417566, respectively), were subjected to molecular identification using M. plutonius -specific primers, a BLAST sequence analysis revealed that the two isolates were M. plutonius with more than 98% sequence identity. The molecular detection of M. plutonius from honeybee is the first recorded incidence of this pathogen in Saudi Arabia. This study emphasizes the need for official authorities to take immediate steps toward treating and limiting the spread of this disease throughout the country.     

河南省16个主栽小麦品种抗叶锈基因分析

为了明确河南省小麦品种的抗叶锈性及抗叶锈基因的分布,为小麦品种推广与合理布局、叶锈病防治及抗病育种提供依据,本研究利用2015年采自河南省的5个小麦叶锈菌流行小种混合菌株,对近几年河南省16个主栽小麦品种进行了苗期抗性鉴定,然后选用12个小麦叶锈菌生理小种对这些品种进行苗期基因推导,同时利用与24个小麦抗叶锈基因紧密连锁(或共分离)的30个分子标记对该16个品种进行了抗叶锈基因分子检测。结果显示,供试品种苗期对小麦叶锈菌混合流行小种均表现高度感病;基因推导与分子检测结果表明,供试品种可能含有Lr1、Lr16、Lr26和Lr30这4个抗叶锈基因,其中先麦8号含有Lr1和Lr26;郑麦366和郑麦9023含有Lr1;西农979和怀川916含有Lr16;中麦895、偃展4110、郑麦7698、平安8号、众麦1号、周麦16、衡观35和矮抗58含有Lr26;周麦22中含有Lr26,还可能含有Lr1和Lr30;豫麦49-198和洛麦23可能含有本研究中检测以外的其他抗叶锈基因。因此,河南省主栽小麦品种的抗叶锈基因丰富度较低,今后育种工作应注重引入其他抗叶锈性基因,提高抗叶锈性,有效控制小麦叶锈病。     

Focus: A Multifaceted Battle Against Cancer: Extracting Knowledge from Chemical Imaging Data Using Computational Algorithms for Digital Cancer Diagnosis

Fourier transform infrared (FTIR) spectroscopic imaging is an emerging microscopy modality for clinical histopathologic diagnoses as well as for biomedical research. Spectral data recorded in this modality are indicative of the underlying, spatially resolved biochemical composition but need computerized algorithms to digitally recognize and transform this information to a diagnostic tool to identify cancer or other physiologic conditions. Statistical pattern recognition forms the backbone of these recognition protocols and can be used for highly accurate results. Aided by biochemical correlations with normal and diseased states and the power of modern computer-aided pattern recognition, this approach is capable of combating many standing questions of traditional histology-based diagnosis models. For example, a simple diagnostic test can be developed to determine cell types in tissue. As a more advanced application, IR spectral data can be integrated with patient information to predict risk of cancer, providing a potential road to precision medicine and personalized care in cancer treatment. The IR imaging approach can be implemented to complement conventional diagnoses, as the samples remain unperturbed and are not destroyed. Despite high potential and utility of this approach, clinical implementation has not yet been achieved due to practical hurdles like speed of data acquisition and lack of optimized computational procedures for extracting clinically actionable information rapidly. The latter problem has been addressed by developing highly efficient ways to process IR imaging data but remains one that has considerable scope for progress. Here, we summarize the major issues and provide practical considerations in implementing a modified Bayesian classification protocol for digital molecular pathology. We hope to familiarize readers with analysis methods in IR imaging data and enable researchers to develop methods that can lead to the use of this promising technique for digital diagnosis of cancer.     

An intelligent system for estimating frog community calling activity and species richness

Over the past decade, dramatic declines in frog populations have been noticed worldwide. To examine this decline, monitoring frogs is becoming increasingly important. Compared to traditional field survey methods, recent advances in acoustic sensor technology have greatly extended spatial and temporal scales for monitoring animal populations. In this paper, we examine the problem of monitoring frog populations by analysing acoustic sensor data, where the population is reflected by community calling activity and species richness. Specifically, a novel acoustic event detection (AED) algorithm is first proposed to filter out those recordings without frog calls. Then, multi-label learning is used to classify each individual recording with six acoustic features: linear predictive coding coefficients, Mel-frequency cepstral coefficients, linear-frequency cepstral coefficients, acoustic complexity index, acoustic diversity index, and acoustic evenness index. Next, frog community calling activity and species richness are estimated by accumulating the results of AED and multi-label learning, respectively. Finally, ordinary least squares regression (OLS) is conducted to reveal the relationship between frog populations (frog calling activity and species richness) and weather variables (maximum temperature and rainfall). Experimental results demonstrate that our proposed intelligent system can significantly facilitate the effort to estimate frog community calling activity and species richness with comparable accuracies. The statistical results of OLS indicate that rainfall pattern has a lagged impact on frog community calling activity (significant in the first day after rainy day) and species richness (significant in the fourth day after rainy day). Temperature is shown to affect species richness but is less likely to change calling activity.     

Urbanization and biological invasion shape animal personalities

Novel selective pressures derived from human activities challenge the persistence of animal populations worldwide. Behavior is expected to be a major factor driving animals’ responses to global change because it largely determines how animals interact with the environment. However, the role of individual variation in behavior to facilitate the persistence of animals in changing environments remains poorly understood. Here, we adopted an animal personality approach to investigate whether different behavioral traits allow animals to deal with two major components of global change: urbanization and biological invasions. By studying six populations of Anolis sagrei lizards, we found for the first time that anoles vary consistently in their behavior across different times and contexts. Importantly, these animal personalities were consistent in the wild and in captivity. We investigated whether behavioral traits are pulled in different directions by different components of global change. On the one hand, we found that lizards from urban areas differ from nearby forest lizards in that they were more tolerant of humans, less aggressive, bolder after a simulated predator attack, and they spent more time exploring new environments. Several of these risk‐taking behaviors constituted a behavioral syndrome that significantly differed between urban and forest populations. On the other hand, the behavior of urban A. sagrei coexisting with the invasive predatory lizard Leiocephalus carinatus was associated with dramatic changes in their foraging niche. Overall, we provide evidence that differences in animal personalities facilitate the persistence of animals under novel selective regimes by producing adaptive behaviors relevant to their ecology such as predator avoidance. Our results suggest that natural selection can favor certain behaviors over others when animals are confronted with different ecological challenges posed by global change. Therefore, we underscore the need to incorporate behavioral ecology into the study of how animals adaptively respond to human‐induced environmental changes.     

加纳籽中5-羟基色氨酸的研究进展

5-羟基色氨酸主要存在于豆科植物中,尤其在加纳籽中含量居多。在体内,5-羟基色氨酸是5-羟色胺的前体,是一类重要的神经类药物。对5-羟基色氨酸的生物学作用、检测、生产方面的最新研究进行了概述,并对5-羟基色氨酸资源匮乏的问题提出了建议。     

Bioclimatic transect networks: Powerful observatories of ecological change

Transects that traverse substantial climate gradients are important tools for climate change research and allow questions on the extent to which phenotypic variation associates with climate, the link between climate and species distributions, and variation in sensitivity to climate change among biomes to be addressed. However, the potential limitations of individual transect studies have recently been highlighted. Here, we argue that replicating and networking transects, along with the introduction of experimental treatments, addresses these concerns. Transect networks provide cost‐effective and robust insights into ecological and evolutionary adaptation and improve forecasting of ecosystem change. We draw on the experience and research facilitated by the Australian Transect Network to demonstrate our case, with examples, to clarify how population‐ and community‐level studies can be integrated with observations from multiple transects, manipulative experiments, genomics, and ecological modeling to gain novel insights into how species and systems respond to climate change. This integration can provide a spatiotemporal understanding of past and future climate‐induced changes, which will inform effective management actions for promoting biodiversity resilience.