Targeting nucleolin to obstruct vasculature feeding with an intelligent DNA nanorobot

A prototype of DNA nanorobot with the ability to transport molecular payloads was designed to target cancer cells in tissue culture. Moreover, a further step was taken to succeed in the first in vivo application of the DNA nanorobot for cancer therapy. The robot was constructed using aptamer and DNA origami to fold a 90‐nm tubular device to carry the blood coagulation protease thrombin inside, shielded from circulating platelets and plasma fibrinogen. The recognition and binding of the aptamer to its tumour‐specific target molecule triggered the robot unfolding to expose thrombin to the blood, which in turn activated coagulation at the local tumour site, resulting in tumour necrosis and inhibition of tumour growth. Since all solid‐tumour feeding vessels are virtually the same, this strategy could be effective against many types of malignant diseases.     

Discovery of genomic regions and candidate genes controlling shelling percentage using QTL‐seq approach in cultivated peanut (Arachis hypogaea L.)

Cultivated peanut (Arachis hypogaea L.) is an important grain legume providing high‐quality cooking oil, rich proteins and other nutrients. Shelling percentage (SP) is the 2nd most important agronomic trait after pod yield and this trait significantly affects the economic value of peanut in the market. Deployment of diagnostic markers through genomics‐assisted breeding (GAB) can accelerate the process of developing improved varieties with enhanced SP. In this context, we deployed the QTL‐seq approach to identify genomic regions and candidate genes controlling SP in a recombinant inbred line population (Yuanza 9102 × Xuzhou 68‐4). Four libraries (two parents and two extreme bulks) were constructed and sequenced, generating 456.89–790.32 million reads and achieving 91.85%–93.18% genome coverage and 14.04–21.37 mean read depth. Comprehensive analysis of two sets of data (Yuanza 9102/two bulks and Xuzhou 68‐4/two bulks) using the QTL‐seq pipeline resulted in discovery of two overlapped genomic regions (2.75 Mb on A09 and 1.1 Mb on B02). Nine candidate genes affected by 10 SNPs with non‐synonymous effects or in UTRs were identified in these regions for SP. Cost‐effective KASP (Kompetitive Allele‐Specific PCR) markers were developed for one SNP from A09 and three SNPs from B02 chromosome. Genotyping of the mapping population with these newly developed KASP markers confirmed the major control and stable expressions of these genomic regions across five environments. The identified candidate genomic regions and genes for SP further provide opportunity for gene cloning and deployment of diagnostic markers in molecular breeding for achieving high SP in improved varieties.     

CYC类基因在被子植物花发育中的研究进展

CYCLOIDEA(CYC)类基因属于TCP基因家族成员,在花发育过程中具有重要作用。CYC类基因在被子植物进化过程中发生基因复制事件,形成CYC1、CYC2和CYC3三大分支,其中CYC2分支成员在花对称性形成方面具有主要调控作用。CYC1和CYC3分支成员开展研究较少。综述了国内外CYC类基因的研究现状及其存在问题,并对CYC类基因的研究前景做了展望。     

北京地区油菜软腐病病原菌的鉴定

摘要:【目的】确定引发北京地区油菜［Brassica campestris L．ssp．chinensis (L.) Makino var． communis Tsen et Lee］软腐病的病原。【方法】结合病原菌形态、BIOLOG 及生理生化、16S rＲNA 基因序列及亚种IGS区特征分析,对从北京大兴和通州区油菜软腐病样中病原菌进行生物学鉴定。【结果】分离的40 个菌株均能引发 油菜软腐病,但分别为胡萝卜果胶杆菌(Pectobacterium carotovorum) 的2个不同亚种,其中13株为P．carotovorum subsp．carotovorum(Pcc),另27株为P．arotovorum subsp． brasiliensis(Pcb)。接种白菜(Brassica campestris L．ssp．pekinensis)致病力测定分析表明,亚种内、来源相同与16S rRNA基因序列相同的菌株间均存在明显的致病力分化。【结论】Pectobacterium carotovorum subsp．carotovorum和Pectobacterium carotovorum subsp. brasiliensis是引发北京地区油菜软腐病的致病菌,后者为首次报道能引起白菜类蔬菜软腐病的常见致病菌。     

中国维管植物属中文普通名选定规则新探

<正>自18世纪瑞典博物学家林奈奠定了植物科学命名的基础之后,国际上通用以拉丁语命名的植物学名(scientific name)作为学术交流的标准。除学名之外,植物的其他任何名称(包括所有非拉丁语名称)都叫作俗名(vernacular name)。在同一种语言的俗名中,又分普通名和别名(王锦秀和汤彦承,2005)。普通名是使用该语言的共同体普遍接受的名称,通常是综合性、权威性的植物志或植物名录中用作分类群正式名称的单一名称;而别名是普通名之外的其他所有俗名的统称,其应用常常存在局限性。     

Sodium butyrate suppresses NOD1-mediated inflammatory molecules expressed in bovine hepatocytes during iE-DAP and LPS treatment

Nucleotide oligomerization domain protein-1 (NOD1), a cytosolic pattern recognition receptor for the γ-D-glutamyl-meso-diaminopimelic acid (iE-DAP) is associated with the inflammatory diseases. Very little is known how bovine hepatocytes respond to specific ligands of NOD1 and sodium butyrate (SB). Therefore, the aim of our study was to investigate the role of bovine hepatocytes in NOD1-mediated inflammation during iE-DAP or LPS treatment or SB pretreatment. To achieve this aim, hepatocytes separated from cows at ∼160 days in milk (DIM) were divided into six groups: The nontreated control group (CON), the iE-DAP-treated group (DAP), the lipopolysaccharide-treated group (LPS), iE-DAP with SB group (DSB), LPS with SB group (LSB), and the SB group. Both iE-DAP and LPS highly increased the expression of both NOD1 and RIPK2, the two key factors for the immune response in hepatocytes. IκBα, NF-κB/p65, and MAP kinases (ERK, JNK, and p38) were activated through phosphorylation. The activation of NF-κB and MAPK pathway consequently increased the proinflammatory cytokines, IL-6, TNF-α, IL-8, and IFN-γ and the chemokines CCL5, CCL20, and CXCL-10. Both treatments improved iNOS/NOS2 expression. However, iE-DAP was failed to express acute phase protein SAA3, but HP and LPS HP but SAA3. These ligands also increased LRRK2, TAK1, TAB1, and β-defensins expression. The SB pretreatment at lower dose restored the function of hepatocytes by suppressing these increased molecules, as HDAC3 was inhibited. The activated NOD1 negatively regulated the expression of FOXA2. Altogether these data suggest an important role of bovine hepatocytes to promote immune responses via NOD1 expression during infection in the liver and a key role of SB to attenuate inflammation.     

Identification and validation of key genes associated with non-small-cell lung cancer

Non-small-cell lung cancer (NSCLC) is one of the main causes of death induced by cancer globally. However, the molecular aberrations in NSCLC patients remain unclearly. In the present study, four messenger RNA microarray datasets (GSE18842, GSE40275, GSE43458, and GSE102287) were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between NSCLC tissues and adjacent lung tissues were obtained from GEO2R and the overlapping DEGs were identified. Moreover, functional and pathway enrichment were performed by Funrich, while the protein–protein interaction (PPI) network construction were obtained from STRING and hub genes were visualized and identified by Cytoscape software. Furthermore, validation, overall survival (OS) and tumor staging analysis of selected hub genes were performed by GEPIA. A total of 367 DEGs (95 upregulated and 272 downregulated) were obtained through gene integration analysis. The PPI network consisted of 94 nodes and 1036 edges in the upregulated DEGs and 272 nodes and 464 edges in the downregulated DEGs, respectively. The PPI network identified 46 upregulated and 27 downregulated hub genes among the DEGs, and six (such as CENPE, NCAPH, MYH11, LRRK2, HSD17B6, and A2M) of that have not been identified to be associated with NSCLC so far. Moreover, the expression differences of the mentioned hub genes were consistent with that in lung adenocarcinoma and lung squamous cell carcinoma in the TCGA database. Further analysis showed that all the six hub genes were associated with tumor staging except MYH11, while only the upregulated DEG CENPE was associated with the worse OS of patients with NSCLC. In conclusion, the current study showed that CENPE, NCAPH, MYH11, LRRK2, HSD17B6, and A2M might be the key genes contributed to tumorigenesis or tumor progression in NSCLC, further functional study is needed to explore the involved mechanisms.     

Protein structure prediction assisted with sparse NMR data in CASP13

CASP13 has investigated the impact of sparse NMR data on the accuracy of protein structure prediction. NOESY and ¹⁵N-¹H residual dipolar coupling data, typical of that obtained for ¹⁵N,¹³C-enriched, perdeuterated proteins up to about 40 kDa, were simulated for 11 CASP13 targets ranging in size from 80 to 326 residues. For several targets, two prediction groups generated models that are more accurate than those produced using baseline methods. Real NMR data collected for a de novo designed protein were also provided to predictors, including one data set in which only backbone resonance assignments were available. Some NMR-assisted prediction groups also did very well with these data. CASP13 also assessed whether incorporation of sparse NMR data improves the accuracy of protein structure prediction relative to nonassisted regular methods. In most cases, incorporation of sparse, noisy NMR data results in models with higher accuracy. The best NMR-assisted models were also compared with the best regular predictions of any CASP13 group for the same target. For six of 13 targets, the most accurate model provided by any NMR-assisted prediction group was more accurate than the most accurate model provided by any regular prediction group; however, for the remaining seven targets, one or more regular prediction method provided a more accurate model than even the best NMR-assisted model. These results suggest a novel approach for protein structure determination, in which advanced prediction methods are first used to generate structural models, and sparse NMR data is then used to validate and/or refine these models.     

超声引导下前列腺穿刺联合外周血循环肿瘤细胞检测对前列腺癌预后分析

目的探讨超声引导下前列腺穿刺联合外周血循环肿瘤细胞(CTCs)检测对前列腺癌预后的预测效果。方法选取2011年1月至2017年12月期间于郑州大学第二附属医院收治的83例前列腺癌患者为研究对象,全部患者均根据超声引导下经直肠前列腺穿刺活检术确诊为前列腺癌,检测病理标本中CK34BE12、p63、α-甲酰基辅酶A消旋酶(AMACR)等免疫标志物的表达状况,并采用Cell Search细胞搜索系统检测外周血CTCs的数量,据此分为阳性组(≥5个/7.5 ml)和阴性组(<5个/7.5 ml)。分析穿刺组织中免疫标志物表达状况、外周血CTCs计数与患者临床病理特征、生存状况的相关性。各标志物的阳性例数、Gleason评分>7分的比例、TNM分期等定性资料的比较采用x^2检验或Fisher确切概率法,年龄、血常规、凝血功能、肝功能、PSA水平等定量资料的比较采用t检验。采用Kaplan-Meier法进行生存分析,采用多因素Cox比例风险回归模型分析患者预后的预测因素。结果(1)全部患者中外周血CTCs、穿刺组织中CK34BE12、p63、AMACR的阳性率分别为31.33、3.61、3.61、86.75。CTCs阳性组的AMACR阳性率为100.00,高于CTCs阴性组的80.70,差异有统计学意义(x^2=4.227,P<0.05)。(2)AMACR阳性组患者的血红蛋白(HB)低于AMACR阴性组[(123.66±13.33)g/L比(134.89±20.08)g/L,t=2.420,P=0.018],血小板(PLT)、血清谷丙转氨酶、D-二聚体(DD)、前列腺特异抗原(PSA)水平、Gleason评分>7分的比例均高于AMACR阴性组[(197.23±36.98)×10^9/L比(172.83±33.33)×10^9/L,t=2.062,P=0.042;(38.80±10.03)U/L比(31.46±7.83)U/L,t=2.317,P=0.023;(255.00±38.80)μg/L比(220.81±30.99)μg/L,t=2.785,P=0.007;(26.60±12.23)ng/ml比(17.90±8.88)ng/ml,t=2.263,P=0.026;45.83比9.09,x^2=3.916,P=0.048],差异有统计学意义(P<0.05)。CTCs阳性组患者的HB低于CTCs阴性组[(121.69±15.89)g/L比(132.73±18.85)g/L,t=2.767,P=0.007],血清碱性磷酸酶、DD、PSA水平、Gleason评分>7分、T3~T4期、M1期的比例均高于CTCs阴性组[(105.69±30.56)U/L比(88.89±35.58)U/L,t=2.205,P=0.030;(256.63±35.86)μg/L比(236.98±33.30)μg/L,t=2.368,P=0.020;(30.09±11.89)ng/ml比(23.33±10.99)ng/ml,t=2.533,P=0.013;57.69比33.33,x^2=4.381,P=0.036;30.77比8.77,x^2=4.981,P=0.026;50.00比17.54,x^2=9.390,P=0.002],差异有统计学意义(P<0.05)。(3)全部患者的中位生存时间为58.33个月,1、3、5年的生存率分别为88.95、51.81、30.12。AMACR阳性组、CTCs阳性组患者的中位生存时间为40.93、36.93个月,低于AMACR阴性组、CTCs阴性组的66.66、69.56个月,差异有统计学意义(P<0.05)。多因素Cox比例风险回归模型分析结果表明,Gleason评分>7分、M1期、AMACR阳性、CTCs阳性是患者死亡的独立危险因素(HR=1.883、3.666、2.009、2.923,P<0.05)。结论超声引导下前列腺穿刺联合外周血CTCs检测对前列腺癌患者的预后具有重要的预测价值,临床上可根据穿刺组织中AMACR表达水平和外周血CTCs计数进行预后的综合分析。