Species identification and antifungal susceptibility of uncommon blood yeast isolates

Background/PurposeAccurate identification of Candida species is increasingly important in the era of emergence of Candida auris. We aimed to compare the identification performance of two matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) systems (Vitek MS and Bruker biotyper MS) and an oligonucleotide array for uncommon blood yeast isolates and demonstrate the susceptibilities among those isolates.MethodCandida species isolates from blood culture other than Candida albicans, Candida parapsilosis, Candida tropicalis, Candida glabrata, and Candida krusei identified by biochemical methods were collected from multiple hospitals and further identified by an oligonucleotide array based on the internal transcribed spacer-1 (ITS-1) and ITS-2 sequences of the rRNA genes, Vitek MS and Bruker biotyper MS. The minimal inhibitory concentrations (MICs) of these clinical isolates were determined by the Sensititre YeastOne (SYO) system.ResultsAmong 136 isolates, Candida guilliermondii was most common (52, 38.2%), followed by C. lusitaniae (13, 9.6%) and C. haemulonii (12, 8.8%). The oligonucleotide array, Vitek MS and Bruker biotyper MS correctly identified 89.7% (122), 90.4% (123), and 92.6% (126) of these isolates, respectively. Elevated minimal inhibitory concentrations (MICs) of fluconazole were observed for C. haemulonii (MIC₉₀: 256 mg/L), and C. guilliermondii (MIC₉₀: 16 mg/L) with 28.4% of uncommon Candida isolates with MIC ≧ 8 mg/L.ConclusionsFor uncommon Candida species, the unmet need for current databases of two commercial MALDI-TOF MS systems is highlighted, and the oligonucleotide array may serve as a supplement.     

基因芯片技术在乙型肝炎病毒分型和耐药突变检测中的应用

目的通过基因芯片检测系统，快速检测临床样品中乙型肝炎病毒的基因亚型和耐药突变情况。方法用基因芯片法检测352例临床样品，对慢性乙型肝炎患者感染的HBV亚型及耐药情况进行分析。结果在352例临床病例中，共检出耐药突变病例124例，检出率为35．7％。发现3种基因亚型，其中B型222例，占63．8％；C型115例，占33．0％；D型1例，占0．3％；B、C混合感染9例，占2．6％；型别未分1例，占0．3％。结论PCR与膜芯片杂交技术可检测乙型肝炎病毒基因亚型及耐药突变类型，并具有快速、高通量、敏感的特点，适合各临床医院开展应用。     

梅毒螺旋体寡核苷酸芯片探针的设计及筛选

【目的】设计梅毒螺旋体寡核苷酸探针,筛选出适合芯片检测的高敏感性和特异性寡核苷酸探针。【方法】根据梅毒螺旋体特异基因设计寡核苷酸探针,人工合成探针后制备寡核苷酸芯片。提取梅毒螺旋体的DNA,采用通用引物联合标记法进行标记,标记样品与芯片杂交,用芯片扫描仪检测杂交结果。【结果】设计出23条50 mer梅毒螺旋体寡核苷酸探针。标记样品与芯片杂交部分探针有较强的杂交信号,并筛选出符合要求的9条梅毒螺旋体寡核苷酸探针。【结论】以上方法能设计和筛选出敏感性和特异性较高的梅毒螺旋体寡核苷酸探针,可用于制备梅毒螺旋体寡核苷酸芯片。     

Gene expression changes in patient-matched gastric normal mucosa, adenomas, and carcinomas

A subset of gastric carcinomas shows histologic evidence of a multistep process, progressing from gastric adenoma to gastric carcinoma. We examined gene expression changes during the gastric adenoma-carcinoma sequence in 26 snap-frozen samples (normal mucosa, adenoma, and carcinoma samples from eight patients and two additional carcinomas) by oligonucleotide microarray. Unsupervised hierarchical clustering analysis demonstrated differential gene expression between gastric normal mucosa, adenomas and carcinomas.We identified 319 and 422 genes differentially regulated in adenoma and carcinoma, respectively, relative to normal mucosa, using a combination of Welch's t-test and fold-change analysis. Applying a combination of robust multi-category support vector machines to the data, reveal that 39 and 21 genes were gradually up- and down-regulated, respectively, in succession in normal mucosa, adenoma, and carcinoma samples. We validated gene expression levels of four genes: hydroxyprostaglandin dehydrogenase 15 (HPGD), follistatin-like 1, trefoil factor 1 (TTF1) and trefoil factor 2 (TFF2) by RT-PCR and found direct correlation with microarray results. The expressions of the TFF2 and HPGD genes were further evaluated by immunohistochemistry in 103 adenomas and 70 carcinomas; expression of both proteins was decreased in these tissues. The progressive alteration in gene expression in the transition from normal mucosa to carcinoma suggests that these changes may play critical roles in gastric carcinogenesis.     

成纤维细胞生长因子在软骨发育过程中的基因芯片分析及相关研究

目的 检测并分析促分裂原活化蛋白激酶(MAPK)信号通路中成纤维细胞生长因子(FGF)在软骨发育过程中的基因表达规律;通过细胞培养观察FGF基因对骨髓基质干细胞(BMSCs)生长特性的影响. 方法用基因芯片技术建立妊娠胎鼠肢芽软骨发育过程的基因表达谱,分析MAPK信号通路中碱性成纤维细胞生长因子(brGF)在软骨发育过程中的基因表达规律.构建bFGF质粒并转染至培养的BMSCs中,用MTT法、免疫组织化学、HE染色、RT-PCR及酶联免疫吸附法检测bFGF基因转染BMSCs的效果及产物表达. 结果 MAPK信号通路中的FGF在软骨发育过程中的软骨形成关键期表达显著上调,并启动MAPK信号通路,促进软骨形成.bFGF基因转染的BMSCs生长活力较强,可以保持2周以上;HE染色显示细胞增殖旺盛,胞核深染;RT-PCR表明有bFGF的基因表达;酶联免疫吸附法检测bFGF表达量高. 结论 FGF能够启动MAPK信号通路从而促进软骨彤成.bFGF质粒转染BMSCs后可促进BMSCs的增殖,细胞有向软骨细胞分化趋势.     

主成分分析在基因芯片聚类分析中的适用性评估

目的探讨在基因芯片聚类分析前对数据进行主成分分析是否有助于提高聚类的准确性。方法选取3组包含大量被生物学家人为分类基因的芯片数据集Budding yeast、Saccharomyces cerevisiae、Central nervous system作为实验数据,分别计算对原数据直接聚类和提取主成分后聚类的结果,并以信息变化量为指标衡量这些结果与人为分类的匹配度。采用启发式算法搜寻最优主成分组合,比较欧几里德距离和相似系数2种距离度量方法以及层次聚类和K-重心聚类2种聚类算法的结果。结果在3组数据集中,层次聚类算法相比K-重心聚类算法效果均略好,且以主成分代替原数据进行聚类分析都没有显著提高聚类的准确性,有些情况下甚至不如后者。仅在Saccharomyces cerevisiae数据集中,当主成分个数足以覆盖原数据中90％-95％方差时,特定的主成分组合才展现出一定优势,但这种组合与主成分大小顺序并无规律可循。结论在基因芯片数据模型不清时,应避免盲目地使用数据中提取的主成分作为聚类分析的输入。     

基因芯片技术在子痫前期外周血白细胞差异表达基因研究中的初步应用

目的:运用基因微阵列技术研究子痫前期和正常妊娠外周血白细胞差异表达基因。方法:Trizol法抽提外周血白细胞总RNA,经cDNA荧光标记、杂交与清洗后进行芯片扫描和图像分析,获得子痫前期外周血的差异表达基因。结果:在所检测的21 000个基因中,子痫前期组和正常妊娠对照组外周血白细胞存在差异表达基因195个,子痫前期组差异表达上调基因74个,下调基因121个,其中163个功能分类基因,这些基因涉及细胞代谢、信号传导、运输、转录调控、细胞增殖和凋亡等方面的功能,20个未分类基因,12个未知基因表达序列。结论:子痫前期是一种多因素疾病,其发病的分子机制可能涉及了一些基因表达的变化,基因芯片筛选子痫前期差异表达基因具有快速、高通量、高敏度等特点。     

胰岛素受体G6244A基因多态性与江苏东台农村地区原发性高血压的关系

目的探讨胰岛素受体G6244A基因多态性与江苏东台农村地区人群原发性高血压（EH）发病风险的相关性。方法选择东台农村地区190例EH患者（EH组）和94例血压正常者（对照组）作为研究对象。用基因芯片法检测胰岛素受体基因G6244A位点的基因型,比较EH组及对照组基因型分布及等住基因频率的差异。结果两组受检者身高、腰围、臀围、收缩压和舒张压间差异有统计学意义（P〈0．05）;其余指标间差异无统计学意义（P〉0．05）;EH组和对照组胰岛素受体G6244A位点的基因型分布及其等位基因频率间差异均无统计学意义（P〉0．05）。结论胰岛素受体基因G6244A位点多态性与江苏东台农村地区高血压发病风险尚未发现存在相关性,需在今后的研究中进一步证实。     

Microarray for molecular typing of Salmonella enterica serovars

We describe the development of a spotted array for the delineation of the most common 14 disease-causing Salmonella serovars in the United States. Our array consists of 414 70 mers targeting core genes of Salmonella enterica, subspecies I specific genes, fimbrial genes, pathogenicity islands, Gifsy elements and other variable genes. Using this array we were able to identify a unique gene presence/absence profile for each of the targeted serovar which was used as the serovar differentiating criteria. Based on this profile, we developed a Matlab programme that compares the profile of an unknown sample to all 14 reference serovar profiles and give out the closest serovar match. Since we have included probes targeting most of the virulence genes and variable genes in Salmonella, in addition to using for serovar detection this array could also be used for studying the virulence gene content and also for evaluating the genetic relation between different isolates of Salmonella.