RPN2与肝癌患者预后及对肝癌细胞生长的作用

目的:探讨核糖蛋白2(ribophorin II,RPN2)在肝细胞肝癌(HCC)组织中的表达和对HCC患者生存的影响,同时分析RPN2对肝癌HepG2细胞生长和克隆形成的作用。方法:应用免疫组化方法和HCC公共芯片数据,从蛋白和m RNA水平检测HCC组织中RPN2的表达,同时分析RPN2与HCC患者临床参数的关系及预后相关性;进一步利用MTS法和克隆形成实验在肝癌HepG2细胞中检测RPN2对细胞生长的作用。结果:98例肝癌组织中,RPN2阳性表达率88.78%,对应癌旁肝组织中,RPN2阳性表达率74.49%;癌组织中RPN2染色评分为5.80±3.15,癌旁肝组织RPN2染色评分为2.13±1.59,肝癌组织中RPN2表达显著上调(P0.001)。3个肝癌公共芯片数据(共522例肝癌)中RPN2的m RNA表达水平同样显著升高(均P0.001)。98例肝癌患者RPN2表达水平与肿瘤直径(P=0.004)、门脉侵袭(P=0.012)和TNM分期(P=0.009)相关;RPN2高表达的患者总体生存期(OS)和无复发生存期(RFS)较RPN2低表达的患者短(OS:P=0.027;RFS:P=0.036)。肝癌HepG2细胞转染RPN2小干扰RNA后,细胞生长能力显著受抑制。结论:RPN2在肝癌中表达显著升高,RPN2的表达与肝癌的恶性进展有关,RPN2显著促进肝癌细胞生长。     

中国植被分类系统修订方案

为了推动《中国植被志》研编工作, 该文回顾了中国植被分类系统的发展过程和主要阶段性成果, 提出了作为《中国植被志》研编技术框架组成部分的中国植被分类系统修订方案, 对各植被型组及各植被型进行了简单定义和描述, 并针对中国植被分类系统若干问题, 特别就中国植被分类系统总体框架、混交林的界定以及土壤在植被分类中的重要性等问题进行了讨论。1960年侯学煜在《中国的植被》中首次提出了中国植被分类的原则和系统, 1980年出版的《中国植被》制定了分类等级和划分依据等更加完善的系统, 之后《中国植被及其地理格局——中华人民共和国1:1 000 000植被图说明书》和《中国植物区系与植被地理》以及很多省区的植被专著对该系统进行过修订。2017年宋永昌在《植被生态学》中提出了一个分类等级单位调整的方案。本次提出的中国植被分类系统修订方案基本沿用《中国植被》的植被分类原则、分类单位及系统, 采用“植物群落学-生态学”分类原则, 主要以植物群落特征及其与环境的关系作为分类依据, 包含三级主要分类单位, 即植被型(高级单位)、群系(中级单位)和群丛(低级单位); 在三个主要分类单位之上分别增加辅助单位植被型组、群系组和群丛组, 在植被型和群系之下主要根据群落的生态差异和实际需要可再增加植被亚型或亚群系。修订方案包含了森林、灌丛、草本植被(草地)、荒漠、高山冻原与稀疏植被、沼泽与水生植被(湿地)、农业植被、城市植被和无植被地段9个植被型组, 划分为48个植被型(含30个自然植被型、12个农业植被型、5个城市植被型和无植被地段)。自然植被中有23个植被型进一步划分出了81个植被亚型。     

Tori lines mitigate seabird bycatch in a pelagic longline fishery

Reviews in Fish Biology and Fisheries - Albatross bycatch has been increasing over the past decade in the US tuna longline fishery of the central North Pacific. A controlled field...     

Profiling Protein Kinases and Other ATP Binding Proteins in Arabidopsis Using Acyl-ATP Probes

Many protein activities are driven by ATP binding and hydrolysis. Here, we explore the ATP binding proteome of the model plant Arabidopsis thaliana using acyl-ATP (AcATP)¹ probes. These probes target ATP binding sites and covalently label lysine residues in the ATP binding pocket. Gel-based profiling using biotinylated AcATP showed that labeling is dependent on pH and divalent ions and can be competed by nucleotides. The vast majority of these AcATP-labeled proteins are known ATP binding proteins. Our search for labeled peptides upon in-gel digest led to the discovery that the biotin moiety of the labeled peptides is oxidized. The in-gel analysis displayed kinase domains of two receptor-like kinases (RLKs) at a lower than expected molecular weight, indicating that these RLKs lost the extracellular domain, possibly as a result of receptor shedding. Analysis of modified peptides using a gel-free platform identified 242 different labeling sites for AcATP in the Arabidopsis proteome. Examination of each individual labeling site revealed a preference of labeling in ATP binding pockets for a broad diversity of ATP binding proteins. Of these, 24 labeled peptides were from a diverse range of protein kinases, including RLKs, mitogen-activated protein kinases, and calcium-dependent kinases. A significant portion of the labeling sites could not be assigned to known nucleotide binding sites. However, the fact that labeling could be competed with ATP indicates that these labeling sites might represent previously uncharacterized nucleotide binding sites. A plot of spectral counts against expression levels illustrates the high specificity of AcATP probes for protein kinases and known ATP binding proteins. This work introduces profiling of ATP binding activities of a large diversity of proteins in plant proteomes. The data have been deposited in ProteomeXchange with the identifier PXD000188.ATP binding and hydrolysis are the driving processes in all living organisms. Hundreds of cellular proteins are able to bind and hydrolyze ATP to unfold proteins, transport molecules over membranes, or phosphorylate small molecules or proteins. Proteins with very different structures are able to bind ATP. A large and important class of ATP binding proteins is that of the kinases, which transfer the gamma phosphate from ATP to substrates. Kinases, and particularly protein kinases, play pivotal roles in signaling and protein regulation.The genome of the model plant Arabidopsis thaliana encodes for over 1099 protein kinases and hundreds of other ATP binding proteins (1, 2). Protein kinases are involved in nearly all signaling cascades and regulate processes ranging from cell cycle to flowering and from immunity to germination. Many protein kinases in plants are receptor-like kinases (RLKs), often carrying extracellular leucine-rich repeats (LRRs). The RLK class contains at least 610 members (3), including famous examples such as receptors involved in development (e.g. BRI1, ER, CLV1) and immunity (e.g. FLS2, EFR). Other important classes are mitogen-activated protein (MAP) kinases (MPKs) (20 different members), MPK kinase kinase kinases (MAP3Ks) (60 different members (4)), and calcium-dependent protein kinases (CPKs) (34 different members (5)). Because of their diverse and important roles, protein kinases have been intensively studied in plant science. The current approach is to study protein kinases individually—a daunting task, considering the remaining hundreds of uncharacterized protein kinases. New approaches are necessary in order to study protein kinases and other ATP binding proteins globally rather than individually.ATP binding activities of protein kinases and other proteins can be detected globally by acyl-ATP (AcATP) probes (6, 7) (Fig. 1A). AcATP binds to the ATP pocket of ATP binding proteins and places the acyl group in close proximity to conserved lysine residues in the ATP binding pocket. The acyl phosphonate moiety serves as an electrophilic warhead that can be nucleophilically attacked by the amino group of the lysine, resulting in a covalent attachment of the acyl reporter of the AcATP probe on the lysine and a concomitant release of ATP. The reporter tag is usually a biotin to capture and identify the labeled proteins. Labeled proteins can be displayed on protein blots using streptavidin-HRP. However, because AcATP labels many ATP binding proteins and protein kinases are of relatively low abundance, mass spectrometry is more often used to identify and quantify labeling with AcATP probes. The analysis is preferably done using Xsite, a procedure that involves trypsination of the entire labeled proteome, followed by analysis of the biotinylated peptides rather than the biotinylated proteins (8). This “KiNativ ” approach provides enough depth and resolving power to monitor ∼160 protein kinases in a crude mammalian proteome (7). Of the 518 human protein kinases (9), 394 (76%) have been detected via AcATP labeling (6).Open in a separate windowFig. 1.Structure and mechanism of labeling with BHAcATP. A, BHAcATP contains ATP, an acyl phosphate reactive group, and a biotin tag. When BHAcATP binds to the ATP binding pocket of a protein, the amino group of the nearby lysine reacts with the carbonyl carbon, which results in the covalent binding of the biotin tag to the protein while ATP is released. B, typical BHAcATP labeling profile of Arabidopsis leaf proteome. Arabidopsis leaf extracts were labeled with BHAcATP and the biotinylated proteins were detected on protein blots using streptavidin-HRP. Coomassie Brilliant Blue staining indicates equal loading. Asterisks indicate endogenously biotinylated proteins MCCA and BCCP. White, black, and gray arrowheads indicate bands containing ATBP+RBCL, PGK1, and a mix of ATP binding proteins, respectively. Abbreviations: MCCA, 3-methylcrotonyl-CoA carboxylase; BCCP, biotin carboxyl carrier protein; ATPB, chloroplastic ATPase; RBCL, ribulose-bisphosphate carboxylase; PGK1, phosphoglycerate kinase-1.KiNativ has mostly been used to validate targets of human drugs that target protein kinases using competitive labeling experiments. This approach has been used to identify selective inhibitors of, for example, Parkinson''s disease protein kinase LRRK2 (10), the BMK1 and JNK MAP kinases (11, 12), and the mTOR kinase (13). Importantly, the correlation of the biological activity of protein-kinase-inhibiting drugs with inhibitor affinity detected using KiNativ is better than that achieved when affinities are determined by assays using heterologously expressed protein kinases (7). This improved correlation illustrates that assays in the native environment provide a more realistic measure of protein kinase function.In addition to characterizing inhibitors selectively, AcATP probes can also display differential ATP binding activities of protein kinases. For example, labeling with AcATP probes during infection with dengue virus displayed a 2- to 8-fold activation of a DNA-dependent protein kinase (14) Similarly, AcATP labeling revealed an unexpected Raf kinase activation in extracts upon protein kinase inhibitor treatment (7). In conclusion, profiling with AcATP probes is a powerful approach for monitoring protein kinases and offers unprecedented opportunities to identify selective protein kinase inhibitors and discover protein kinases with differential ATP binding activities.In this work, we introduce AcATP profiling of plant proteomes. In addition to the analysis of labeled peptides, we characterized labeling using gel-based approaches and discovered that biotin is often oxidized in this procedure. We also performed an in-depth analysis of labeling sites in proteins other than protein kinases, which had not been done before. We discuss labeling outside known nucleotide binding pockets and investigate the correlation of labeling sites with protein abundance. We describe 63 labeling sites of known nucleotide binding pockets, of which 24 represent a remarkable diversity of protein kinases, including several LRR-RLKs. This work launches a new approach to study ATP binding proteins in plant science.     

Secondary galling: a novel feeding strategy among ‘non‐pollinating’ fig wasps from Ficus curtipes

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Variability in host plant resistance of Sorghum to Striga Hermonthica infestation in West Africa

Fourteen elite sorghum lines were evaluated for their resistance to Striga hermonthica at three locations in Nigeria and Mali. Results showed that many of the lines especially MALISOR 84-1, SAMSORG 41, 97-SB-F5DT-64 (Keninkédié) and the check SRN 39 remained resistant to Striga in all locations with low emerged Striga counts, while SAMSORG 14 had the highest Striga infestation in all locations. Considerable variation in reaction to Striga infestation was observed on Séguètana, 97-SB-F5DT-63 (Wasa), 97-SB-F5DT-65, CMDT 38, CMDT 39 and CMDT 45 which were susceptible to Striga at Samaru, Nigeria but were resistant to Striga at both locations in Mali. Based on low Striga resistance and high grain yield, lines MALISOR 84-1, SAMSORG 41, 97-SB-F5DT-64, 97-SB-F5DT-65, CMDT 39 and SAMSORT 14 have been nominated for wider evaluation across more West African countries.     

One-dimensional TRFLP-SSCP is an effective DNA fingerprinting strategy for soil Archaea that is able to simultaneously differentiate broad taxonomic clades based on terminal fragment length polymorphisms and closely related sequences based on single stranded conformation polymorphisms

DNA fingerprinting methods provide a means to rapidly compare microbial assemblages from environmental samples without the need to first cultivate species in the laboratory. The profiles generated by these techniques are able to identify statistically significant temporal and spatial patterns, correlations to environmental gradients, and biological variability to estimate the number of replicates for clone libraries or next generation sequencing (NGS) surveys. Here we describe an improved DNA fingerprinting technique that combines terminal restriction fragment length polymorphisms (TRFLP) and single stranded conformation polymorphisms (SSCP) so that both can be used to profile a sample simultaneously rather than requiring two sequential steps as in traditional two-dimensional (2-D) gel electrophoresis. For the purpose of profiling Archaeal 16S rRNA genes from soil, the dynamic range of this combined 1-D TRFLP-SSCP approach was superior to TRFLP and SSCP. 1-D TRFLP-SSCP was able to distinguish broad taxonomic clades with genetic distances greater than 10%, such as Euryarchaeota and the Thaumarchaeal clades g_Ca. Nitrososphaera (formerly 1.1b) and o_NRP-J (formerly 1.1c) better than SSCP. In addition, 1-D TRFLP-SSCP was able to simultaneously distinguish closely related clades within a genus such as s_SCA1145 and s_SCA1170 better than TRFLP. We also tested the utility of 1-D TRFLP-SSCP fingerprinting of environmental assemblages by comparing this method to the generation of a 16S rRNA clone library of soil Archaea from a restored Tallgrass prairie. This study shows 1-D TRFLP-SSCP fingerprinting provides a rapid and phylogenetically informative screen of Archaeal 16S rRNA genes in soil samples.