Extinction risk of Chinese angiosperms varies between woody and herbaceous species

Aim

Understanding how species' traits and environmental contexts relate to extinction risk is a critical priority for ecology and conservation biology. This study aims to identify and explore factors related to extinction risk between herbaceous and woody angiosperms to facilitate more effective conservation and management strategies and understand the interactions between environmental threats and species' traits.

Location

China.

Taxon

Angiosperms.

Methods

We obtained a large dataset including five traits, six extrinsic variables, and 796,118 occurrence records for 14,888 Chinese angiosperms. We assessed the phylogenetic signal and used phylogenetic generalized least squares regressions to explore relationships between extinction risk, plant traits, and extrinsic variables in woody and herbaceous angiosperms. We also used phylogenetic path analysis to evaluate causal relationships among traits, climate variables, and extinction risk of different growth forms.

Results

The phylogenetic signal of extinction risk differed among woody and herbaceous species. Angiosperm extinction risk was mainly affected by growth form, altitude, mean annual temperature, normalized difference vegetation index, and precipitation change from 1901 to 2020. Woody species' extinction risk was strongly affected by height and precipitation, whereas extinction risk for herbaceous species was mainly affected by mean annual temperature rather than plant traits.

Main conclusions

Woody species were more likely to have higher extinction risks than herbaceous species under climate change and extinction threat levels varied with both plant traits and extrinsic variables. The relationships we uncovered may help identify and protect threatened plant species and the ecosystems that rely on them.     

崖椒茎的化学成分

从崖椒（Zanthoxglum schinifolutm Sieb.et Zucc.)茎的石油醚、二氯甲烷提取物中分离得到8个化合物。经物理常数测定及光谱（UV,IR,MS,NMR)分析鉴定其为（1）白鲜碱（dictamning),（2）茵芋碱（skimmianine),(3)滨蒿内酯（scoparone),(4)崖椒内酯（schinifolin),(5)莨菪亭（scopoletin),（6）7-羟基-8-甲氧基香豆素（7-hydroxy-8-methoxycoumarin),（7）N-甲基弗林辛（N-methylflindersine),（8）β-谷甾醇（β-sitosterol),其中化合物（5）、（6）和（7）为首次从该植物中分离。     

药用寄生植物菟丝子属,列当属和无根藤属氨基酸的分析

本文测定了菟丝子属、列当属和无根藤属某些种的种子和植株氨基酸的种类组成和含量。结果表明,3个属种子和植株氨基酸均在15种以上,且含量丰富,特别是必需氨基酸的含量较高。文中讨论了氨基酸的药用和在种子鉴定与化学分类上的作用,探讨了开发应用的前景。     

Phytopathogenic bacteria utilize host glucose as a signal to stimulate virulence through LuxR homologues

Chemical signal-mediated biological communication is common within bacteria and between bacteria and their hosts. Many plant-associated bacteria respond to unknown plant compounds to regulate bacterial gene expression. However, the nature of the plant compounds that mediate such interkingdom communication and the underlying mechanisms remain poorly characterized. Xanthomonas campestris pv. campestris (Xcc) causes black rot disease on brassica vegetables. Xcc contains an orphan LuxR regulator (XccR) which senses a plant signal that was validated to be glucose by HPLC-MS. The glucose concentration increases in apoplast fluid after Xcc infection, which is caused by the enhanced activity of plant sugar transporters translocating sugar and cell-wall invertases releasing glucose from sucrose. XccR recruits glucose, but not fructose, sucrose, glucose 6-phosphate, and UDP-glucose, to activate pip expression. Deletion of the bacterial glucose transporter gene sglT impaired pathogen virulence and pip expression. Structural prediction showed that the N-terminal domain of XccR forms an alternative pocket neighbouring the AHL-binding pocket for glucose docking. Substitution of three residues affecting structural stability abolished the ability of XccR to bind to the luxXc box in the pip promoter. Several other XccR homologues from plant-associated bacteria can also form stable complexes with glucose, indicating that glucose may function as a common signal molecule for pathogen–plant interactions. The conservation of a glucose/XccR/pip-like system in plant-associated bacteria suggests that some phytopathogens have evolved the ability to utilize host compounds as virulence signals, indicating that LuxRs mediate an interkingdom signalling circuit.     

IL-33-ST2 pathway regulates AECII transdifferentiation by targeting alveolar macrophage in a bronchopulmonary dysplasia mouse model

Evidence points to the indispensable function of alveolar macrophages (AMs) in normal lung development and tissue homeostasis. However, the importance of AMs in bronchopulmonary dysplasia (BPD) has not been elucidated. Here, we identified a significant role of abnormal AM proliferation and polarization in alveolar dysplasia during BPD, which is closely related to the activation of the IL-33-ST2 pathway. Compared with the control BPD group, AMs depletion partially abolished the epithelialmesenchymal transition process of AECII and alleviated pulmonary differentiation arrest. In addition, IL-33 or ST2 knockdown has protective effects against lung injury after hyperoxia, which is associated with reduced AM polarization and proliferation. The protective effect disappeared following reconstitution of AMs in injured IL-33 knockdown mice, and the differentiation of lung epithelium was blocked again. In conclusion, the IL-33-ST2 pathway regulates AECII transdifferentiation by targeting AMs proliferation and polarization in BPD, which shows a novel strategy for manipulating the IL-33–ST2-AMs axis for the diagnosis and intervention of BPD.     

Isolation and characterization of deteriosomes from rat liver

Deteriosomes, a new class of microvesicles, have been isolated from rat liver tissue. These microvesicles are similar to those isolated previously from plant tissue [Yao et al., Proc Natl Acad Sci USA 88:2269–2273, 1991] in that they are nonsedimentable and enriched in membrane catabolites, particularly products of phospholipid degradation. Liver deteriosomes range in size from 0.05 μm to 0.11 μm in radius. They are also much more permeable than microsomal membrane vesicles indicating that the deteriosome bilayer is perturbed. The data are consistent with the proposal that deteriosomes are formed from membranes by microvesiculation and that they represent an intermediate stage of membrane deterioration. Furthermore, liver deteriosomes were found to contain phospholipase A₂ activity. This suggests that they not only serve as a means of moving destabilizing macromolecular catabolites out of membranes into the cytosol but also possess enzymatic activity. The fact that the specific activity of phospholipase A₂ is higher in deteriosomes than in deteriosome-free cytosol suggests that some of the enzymatic activity traditionally assumed to be cytosolic may in fact be associated with deteriosomes.     

Cross-trait prediction accuracy of summary statistics in genome-wide association studies

In the era of big data, univariate models have widely been used as a workhorse tool for quickly producing marginal estimators; and this is true even when in a high-dimensional dense setting, in which many features are “true,” but weak signals. Genome-wide association studies (GWAS) epitomize this type of setting. Although the GWAS marginal estimator is popular, it has long been criticized for ignoring the correlation structure of genetic variants (i.e., the linkage disequilibrium [LD] pattern). In this paper, we study the effects of LD pattern on the GWAS marginal estimator and investigate whether or not additionally accounting for the LD can improve the prediction accuracy of complex traits. We consider a general high-dimensional dense setting for GWAS and study a class of ridge-type estimators, including the popular marginal estimator and the best linear unbiased prediction (BLUP) estimator as two special cases. We show that the performance of GWAS marginal estimator depends on the LD pattern through the first three moments of its eigenvalue distribution. Furthermore, we uncover that the relative performance of GWAS marginal and BLUP estimators highly depends on the ratio of GWAS sample size over the number of genetic variants. Particularly, our finding reveals that the marginal estimator can easily become near-optimal within this class when the sample size is relatively small, even though it ignores the LD pattern. On the other hand, BLUP estimator has substantially better performance than the marginal estimator as the sample size increases toward the number of genetic variants, which is typically in millions. Therefore, adjusting for the LD (such as in the BLUP) is most needed when GWAS sample size is large. We illustrate the importance of our results by using the simulated data and real GWAS.