Gut microbiome helps honeybee (Apis mellifera) resist the stress of toxic nectar plant (Bidens pilosa) exposure: Evidence for survival and immunity

Honeybee (Apis mellifera) ingestion of toxic nectar plants can threaten their health and survival. However, little is known about how to help honeybees mitigate the effects of toxic nectar plant poisoning. We exposed honeybees to different concentrations of Bidens pilosa flower extracts and found that B. pilosa exposure significantly reduced honeybee survival in a dose-dependent manner. By measuring changes in detoxification and antioxidant enzymes and the gut microbiome, we found that superoxide dismutase, glutathione-S-transferase and carboxylesterase activities were significantly activated with increasing concentrations of B. pilosa and that different concentrations of B. pilosa exposure changed the structure of the honeybee gut microbiome, causing a significant reduction in the abundance of Bartonella (p < 0.001) and an increase in Lactobacillus. Importantly, by using Germ-Free bees, we found that colonization by the gut microbes Bartonella apis and Apilactobacillus kunkeei (original classification as Lactobacillus kunkeei) significantly increased the resistance of honeybees to B. pilosa and significantly upregulated bee-associated immune genes. These results suggest that honeybee detoxification systems possess a level of resistance to the toxic nectar plant B. pilosa and that the gut microbes B. apis and A. kunkeei may augment resistance to B. pilosa stress by improving host immunity.     

The complex genome and adaptive evolution of polyploid Chinese pepper (Zanthoxylum armatum and Zanthoxylum bungeanum)

Zanthoxylum armatum and Zanthoxylum bungeanum, known as ‘Chinese pepper’, are distinguished by their extraordinary complex genomes, phenotypic innovation of adaptive evolution and species-special metabolites. Here, we report reference-grade genomes of Z. armatum and Z. bungeanum. Using high coverage sequence data and comprehensive assembly strategies, we derived 66 pseudochromosomes comprising 33 homologous phased groups of two subgenomes, including autotetraploid Z. armatum. The genomic rearrangements and two whole-genome duplications created large (~4.5 Gb) complex genomes with a high ratio of repetitive sequences (>82%) and high chromosome number (2n = 4x = 132). Further analysis of the high-quality genomes shed lights on the genomic basis of involutional reproduction, allomones biosynthesis and adaptive evolution in Chinese pepper, revealing a high consistent relationship between genomic evolution, environmental factors and phenotypic innovation. Our study provides genomic resources and new insights for investigating diversification and phenotypic innovation in Chinese pepper, with broader implications for the protection of plants under severe environmental changes.     

泥河湾盆地发现短喙象化石

本文记述泥河湾盆地河北蔚县两个地点发现的化石,它们被鉴定为短喙象类的?Anancus和Pentalopodon两个属。     

胶质母细胞瘤外泌体的作用机制研究进展

胶质母细胞瘤(glioblastoma,GBM)因组织学异质性、侵袭能力强、术后复发快等问题,致使患者经手术治疗、化疗和放疗后的预后差,总体生存期短。GBM细胞来源外泌体(GBM cell-derived exosome,GBM-exo)能够通过其携带的细胞因子、miRNA、DNA和蛋白质等调节GBM细胞的增殖和迁移,通过血管生成蛋白和非编码RNA促进肿瘤血管生成,通过调节因子、蛋白质和药物靶向免疫检查点等介导肿瘤免疫逃逸,以及通过非编码RNA对抗GBM细胞的耐药性,有望成为个性化治疗GBM的重要靶标,且可以作为GBM的诊断和预后标志物。本文阐述了GBM-exo的制备方法和生物学特征,及其在GBM细胞增殖、血管生成、免疫逃逸和耐药性方面的作用和分子机制,为研发诊治GBM的新策略提供参考。     

Multikink quantile regression for longitudinal data with application to progesterone data analysis

Motivated by investigating the relationship between progesterone and the days in a menstrual cycle in a longitudinal study, we propose a multikink quantile regression model for longitudinal data analysis. It relaxes the linearity condition and assumes different regression forms in different regions of the domain of the threshold covariate. In this paper, we first propose a multikink quantile regression for longitudinal data. Two estimation procedures are proposed to estimate the regression coefficients and the kink points locations: one is a computationally efficient profile estimator under the working independence framework while the other one considers the within-subject correlations by using the unbiased generalized estimation equation approach. The selection consistency of the number of kink points and the asymptotic normality of two proposed estimators are established. Second, we construct a rank score test based on partial subgradients for the existence of the kink effect in longitudinal studies. Both the null distribution and the local alternative distribution of the test statistic have been derived. Simulation studies show that the proposed methods have excellent finite sample performance. In the application to the longitudinal progesterone data, we identify two kink points in the progesterone curves over different quantiles and observe that the progesterone level remains stable before the day of ovulation, then increases quickly in 5 to 6 days after ovulation and then changes to stable again or drops slightly.     

Associating somatic mutation with clinical outcomes through kernel regression and optimal transport

Somatic mutations in cancer patients are inherently sparse and potentially high dimensional. Cancer patients may share the same set of deregulated biological processes perturbed by different sets of somatically mutated genes. Therefore, when assessing the associations between somatic mutations and clinical outcomes, gene-by-gene analysis is often under-powered because it does not capture the complex disease mechanisms shared across cancer patients. Rather than testing genes one by one, an intuitive approach is to aggregate somatic mutation data of multiple genes to assess their joint association with clinical outcomes. The challenge is how to aggregate such information. Building on the optimal transport method, we propose a principled approach to estimate the similarity of somatic mutation profiles of multiple genes between tumor samples, while accounting for gene–gene similarities defined by gene annotations or empirical mutational patterns. Using such similarities, we can assess the associations between somatic mutations and clinical outcomes by kernel regression. We have applied our method to analyze somatic mutation data of 17 cancer types and identified at least five cancer types, where somatic mutations are associated with overall survival, progression-free interval, or cytolytic activity.     

Thermostability enhancement of polyethylene terephthalate degrading PETase using self- and nonself-ligating protein scaffolding approaches

Polyethylene terephthalate (PET) hydrolase enzymes show promise for enzymatic PET degradation and green recycling of single-use PET vessels representing a major source of global pollution. Their full potential can be unlocked with enzyme engineering to render activities on recalcitrant PET substrates commensurate with cost-effective recycling at scale. Thermostability is a highly desirable property in industrial enzymes, often imparting increased robustness and significantly reducing quantities required. To date, most engineered PET hydrolases show improved thermostability over their parental enzymes. Here, we report engineered thermostable variants of Ideonella sakaiensis PET hydrolase enzyme (IsPETase) developed using two scaffolding strategies. The first employed SpyCatcher-SpyTag technology to covalently cyclize IsPETase, resulting in increased thermostability that was concomitant with reduced turnover of PET substrates compared to native IsPETase. The second approach using a GFP-nanobody fusion protein (vGFP) as a scaffold yielded a construct with a melting temperature of 80°C. This was further increased to 85°C when a thermostable PETase variant (FAST PETase) was scaffolded into vGFP, the highest reported so far for an engineered PET hydrolase derived from IsPETase. Thermostability enhancement using the vGFP scaffold did not compromise activity on PET compared to IsPETase. These contrasting results highlight potential topological and dynamic constraints imposed by scaffold choice as determinants of enzyme activity.