草鱼生肌因子5基因的克隆及其组织表达谱分析

目的:获得草鱼生肌因子5(Myf-5)基因序列,分析其在草鱼不同组织和不同发育阶段中的表达规律。方法:根据鲤鱼Myf-5基因序列设计引物,用草鱼肌肉组织总RNA,经RT-PCR扩增其Myf-5基因序列;利用半定量RT-PCR分析草鱼Myf-5基因在草鱼不同组织和不同发育阶段的mRNA表达特性。结果:获得了草鱼Myf-5基因开放读框序列723 bp,GenBank登录号为GU290227;该基因编码由240个氨基酸残基组成的蛋白,具有MyoD家族基因的典型性碱性螺旋-环-螺旋(bHLH)结构,其氨基酸序列与斑马鱼、鲤鱼、虹鳟、大西洋鲑等的同源性较高(74%~97%),与哺乳动物和禽类如人、小鼠、大鼠、猪、牛和鸡的同源性较低(56%~60%);在草鱼红肌、白肌、肝胰脏、肾脏、脑和肠中均检测到Myf-5基因的表达,红肌、白肌和脑组织中Myf-5基因mRNA的表达量显著高于其他组织(P<0.05);草鱼Myf-5基因的表达随着其生长发育呈下降趋势,在较大规格试验鱼(500 g)中的表达显著低于其他2种规格(50~60 g、120~130 g)的试验鱼(P<0.05)。结论:获得了草鱼Myf-5基因序列,其在红肌、白肌和脑组织中的表达量显著高于其他组织,并随生长发育呈下降趋势,为研究Myf-5在草鱼肌肉发育过程中的作用提供了基础资料。     

牦牛MEF2C基因克隆、生物信息学及表达谱分析

本试验旨在分析牦牛(Bos grunniens)肌细胞增强因子2C(myocyte enhancer factor 2C,MEF2C)基因的分子特征和表达规律,探索其影响牦牛肌肉发育的作用机制.试验以大通牦牛肌肉组织cDNA为模板,采用PCR扩增技术扩增牦牛MEF2C基因,用DNAStar,ExPASy,ABCpred等生物信息学软件分析MEF2C基因序列和其编码的蛋白质结构,利用实时荧光定量PCR技术(RT-qPCR)检测了 MEF2C基因的表达情况.试验克隆获得的牦牛MEF2C基因编码区全长1 302 bp,编码433个氨基酸;蛋白质结构预测结果显示,MEF2C蛋白具有30h的半衰期,为亲水性碱性蛋白,没有信号肽但拥有跨膜结构.系统关系中牦牛与普通牛的亲缘关系最为接近,与小鼠亲缘关系较远.组织表达谱结果显示,MEF2C基因在牦牛7个组织中都有表达且在臀二头肌组织中表达量最高;不同时期MEF2C基因表达情况为胎牛＞成年牛＞6月龄牛.研究结果将为进一步探讨MEF2C基因在牦牛肌肉发育中的作用提供科学依据,同时也为解析牦牛肌肉发育的分子机制提供数据支撑.     

Global Gene Expression Profiling Reveals SPINK1 as a Potential Hepatocellular Carcinoma Marker

Background

Liver cirrhosis is the most important risk factor for hepatocellular carcinoma (HCC) but the role of liver disease aetiology in cancer development remains under-explored. We investigated global gene expression profiles from HCC arising in different liver diseases to test whether HCC development is driven by expression of common or different genes, which could provide new diagnostic markers or therapeutic targets.

Methodology and Principal Findings

Global gene expression profiling was performed for 4 normal (control) livers as well as 8 background liver and 7 HCC from 3 patients with hereditary haemochromatosis (HH) undergoing surgery. In order to investigate different disease phenotypes causing HCC, the data were compared with public microarray repositories for gene expression in normal liver, hepatitis C virus (HCV) cirrhosis, HCV-related HCC (HCV-HCC), hepatitis B virus (HBV) cirrhosis and HBV-related HCC (HBV-HCC). Principal component analysis and differential gene expression analysis were carried out using R Bioconductor. Liver disease-specific and shared gene lists were created and genes identified as highly expressed in hereditary haemochromatosis HCC (HH-HCC) were validated using quantitative RT-PCR. Selected genes were investigated further using immunohistochemistry in 86 HCC arising in liver disorders with varied aetiology. Using a 2-fold cut-off, 9 genes were highly expressed in all HCC, 11 in HH-HCC, 270 in HBV-HCC and 9 in HCV-HCC. Six genes identified by microarray as highly expressed in HH-HCC were confirmed by RT qPCR. Serine peptidase inhibitor, Kazal type 1 (SPINK1) mRNA was very highly expressed in HH-HCC (median fold change 2291, p = 0.0072) and was detected by immunohistochemistry in 91% of HH-HCC, 0% of HH-related cirrhotic or dysplastic nodules and 79% of mixed-aetiology HCC.

Conclusion

HCC, arising from diverse backgrounds, uniformly over-express a small set of genes. SPINK1, a secretory trypsin inhibitor, demonstrated potential as a diagnostic HCC marker and should be evaluated in future studies.     

Gene Expression Profiling of Seizure Disorders

Seizure disorders affect a significant percentage of the population, and researchers worldwide continue to work toward a better understanding of what initiates, propagates, and results from aberrant and excessive neuronal excitation. During the past two decades, one aspect of this research effort has been to describe the effects of seizure activity upon neuronal gene expression, with hopes of identifying the molecular mechanisms that underlie subsequent changes in cell function and survival. Here we review this body of work from the perspective of how these gene profiling efforts have evolved, starting with one-by-one analyses of specific gene targets to the more recent use of DNA microarrays to survey literally thousands of genes simultaneously. With regard to the latter, we present some of our own work that suggests that molecular mechanisms contributing to normal brain development are reiterated during seizure-induced network reorganization.     

α-银环蛇毒素基因的克隆及其非融合型原核表达研究

根据文献报道α－银环蛇毒素的氨基酸序列推导出其DNA序列,设计并人工合成两两互补的14条寡核苷酸片段。经片段延伸、PCR、克隆,成功构建α-银环蛇毒素基因克隆质粒;质粒经XbaI和EcoRI双酶切回收后连接于表达载体pET28a(+)中,分别转化BL21（DE3）、BL21（DE3）Codonplus、BL21（DE3）plysS进行诱导表达,表达产物经Tris/tricine系统进行SDS-PAGE分析。结果表明：该基因已在大肠杆菌BL21（DE3）宿主菌中进行了非融合表达,其表达量占细菌总蛋白的11.98％,主要以包涵体形式存在;同时对表达条件进行了优化,其表达量可达16.28%。经Westernblot分析,在大约8kDa处出现明显的目的带,与预计蛋白分子量大小一致,说明表达产物与天然α-银环蛇毒素具有相似的免疫原性。表达产物纯化、复性后经动物毒性试验表明：表达的α-银环蛇毒素蛋白具有生物学活性,小鼠腹腔注射其LD50约为1.28μg/g。     

Gene Expression Profiling Within the Developing Neural Tube

The developing mammalian nervous system is subject to devastating congenital malformations with clinical significance that extends into the billions of health care dollars annually worldwide. Neural tube defects (NTDs) are among the most common of all human congenital defects, yet their etiology remains poorly understood. This is largely due to the complexity of the genetic factors regulating the intricate events involved in neurulation. Using mouse model systems and the application of modern molecular biological technologies, we have recently gained a greater appreciation for the factors that not only regulate normal neural tube closure (NTC), but those genetic factors that predispose an embryo to significant birth defects such as anencephaly or spina bifida. We have selected prominent murine mutants, both spontaneous and genetically modified, as well as the use of teratogenic agents, to examine the impact of altering the normal pattern of gene expression in the developing neural tube.     

Protein-Bound Uremic Toxin Profiling as a Tool to Optimize Hemodialysis

Aim

We studied various hemodialysis strategies for the removal of protein-bound solutes, which are associated with cardiovascular damage.

Methods

This study included 10 patients on standard (3x4h/week) high-flux hemodialysis. Blood was collected at the dialyzer inlet and outlet at several time points during a midweek session. Total and free concentration of several protein-bound solutes was determined as well as urea concentration. Per solute, a two-compartment kinetic model was fitted to the measured concentrations, estimating plasmatic volume (V₁), total distribution volume (V_tot) and intercompartment clearance (K₂₁). This calibrated model was then used to calculate which hemodialysis strategy offers optimal removal. Our own in vivo data, with the strategy variables entered into the mathematical simulations, was then validated against independent data from two other clinical studies.

Results

Dialyzer clearance K, V₁ and V_tot correlated inversely with percentage of protein binding. All Ks were different from each other. Of all protein-bound solutes, K₂₁was 2.7–5.3 times lower than that of urea. Longer and/or more frequent dialysis that processed the same amount of blood per week as standard 3x4h dialysis at 300mL/min blood flow showed no difference in removal of strongly bound solutes. However, longer and/or more frequent dialysis strategies that processed more blood per week than standard dialysis were markedly more adequate. These conclusions were successfully validated.

Conclusion

When blood and dialysate flow per unit of time and type of hemodialyzer are kept the same, increasing the amount of processed blood per week by increasing frequency and/or duration of the sessions distinctly increases removal.     

Assessment of the Effectiveness of a Nuclear-Launched TMV-Based Replicon as a Tool for Foreign Gene Expression in Plants in Comparison to Direct Gene Expression from a Nuclear Promoter

An environmentally safe Tobacco Mosaic Virus (TMV)-based expression replicon was constructed that lacks movement protein (MP) and coat protein (CP), and which expresses the green fluorescent protein (GFP) gene from a full CP subgenomic promoter. The TMV replicon, whose cDNA was positioned between an enhanced Cauliflower Mosaic Virus 35S promoter (CaMV) and a self-cleaving hammerhead ribozyme with a downstream nopaline synthase gene polyadenylation signal [nos-poly(A)], was assessed for its effectiveness to accumulate GFP upon agroinfiltration into plant leaves compared to a control construct in which GFP was directly expressed from the enhanced CaMV 35S promoter. It was determined that individually expressing cells produced ca. 9-fold more GFP from the TMV-based replicon than from the enhanced 35S promoter. In contrast, GFP measurements from total leaf extracts determined that leaves infiltrated with the TMV-based replicon produced ca. 7-fold less GFP than the control construct. These apparently contradictory results can be explained by the low infectivity of the TMV-based replicon as it was found that the number of foci expressing GFP produced in leaves agroinfiltrated with the TMV-based replicon was ca. 66-fold lower than produced by the control.     

Effective Classification and Gene Expression Profiling for the Facioscapulohumeral Muscular Dystrophy

The Facioscapulohumeral Muscular Dystrophy (FSHD) is an autosomal dominant neuromuscular disorder whose incidence is estimated in about one in 400,000 to one in 20,000. No effective therapeutic strategies are known to halt progression or reverse muscle weakness and atrophy. It is known that the FSHD is caused by modifications located within a D4ZA repeat array in the chromosome 4q, while recent advances have linked these modifications to the DUX4 gene. Unfortunately, the complete mechanisms responsible for the molecular pathogenesis and progressive muscle weakness still remain unknown. Although there are many studies addressing cancer databases from a machine learning perspective, there is no such precedent in the analysis of the FSHD. This study aims to fill this gap by analyzing two specific FSHD databases. A feature selection algorithm is used as the main engine to select genes promoting the highest possible classification capacity. The combination of feature selection and classification aims at obtaining simple models (in terms of very low numbers of genes) capable of good generalization, that may be associated with the disease. We show that the reported method is highly efficient in finding genes to discern between healthy cases (not affected by the FSHD) and FSHD cases, allowing the discovery of very parsimonious models that yield negligible repeated cross-validation error. These models in turn give rise to very simple decision procedures in the form of a decision tree. Current biological evidence regarding these genes shows that they are linked to skeletal muscle processes concerning specific human conditions.     

一个新葡萄糖淀粉酶基因的克隆与表达

根据已报道的米根霉葡萄糖淀粉酶基因序列,通过PCR方法,从天然少根根霉的总DNA中克隆到含有四个内含子的葡萄糖淀粉酶基因。通过设计引物并采取重叠PCR方法删除内含子,获得了新的少根根霉葡萄糖淀粉酶(Rhizopus arrhizu glucoamylase,RaGA)cDNA序列(Accession number:DQ903853)。该基因在毕赤酵母中成功表达,表达产物具有较高的葡萄糖淀粉酶活性。     

细菌视紫红质的基因克隆与表达

细菌视紫红质的基因克隆与表达卢春林,汪俭,梅祺,韦钰（东南大学吴建雄实验室,南京２１０Ｏ１８）叶寅,田波（中国科学院微生物研究所,北京１０００８０）关键词细菌视紫红质基因;聚合酶链反应（ＰＣＲ）;基因克隆与表达细菌视紫红质（ｂａｅ快ｒｉｏｒｈｏｄｏＰ...     

Tissue Compartment Analysis for Biomarker Discovery by Gene Expression Profiling

Background

Although high throughput technologies for gene profiling are reliable tools, sample/tissue heterogeneity limits their outcomes when applied to identify molecular markers. Indeed, inter-sample differences in cell composition contribute to scatter the data, preventing detection of small but relevant changes in gene expression level. To date, attempts to circumvent this difficulty were based on isolation of the different cell structures constituting biological samples. As an alternate approach, we developed a tissue compartment analysis (TCA) method to assess the cell composition of tissue samples, and applied it to standardize data and to identify biomarkers.

Methodology/Principal Findings

TCA is based on the comparison of mRNA expression levels of specific markers of the different constitutive structures in pure isolated structures, on the one hand, and in the whole sample on the other. TCA method was here developed with human kidney samples, as an example of highly heterogeneous organ. It was validated by comparison of the data with those obtained by histo-morphometry. TCA demonstrated the extreme variety of composition of kidney samples, with abundance of specific structures varying from 5 to 95% of the whole sample. TCA permitted to accurately standardize gene expression level amongst >100 kidney biopsies, and to identify otherwise imperceptible molecular disease markers.

Conclusions/Significance

Because TCA does not require specific preparation of sample, it can be applied to all existing tissue or cDNA libraries or to published data sets, inasmuch specific operational compartments markers are available. In human, where the small size of tissue samples collected in clinical practice accounts for high structural diversity, TCA is well suited for the identification of molecular markers of diseases, and the follow up of identified markers in single patients for diagnosis/prognosis and evaluation of therapy efficiency. In laboratory animals, TCA will interestingly be applied to central nervous system where tissue heterogeneity is a limiting factor.     

Methodological Considerations Regarding Single-Cell Gene Expression Profiling for Brain Injury

Genomic microarrays are rapidly becoming ubiquitous throughout a wide variety of biological disciplines. As their use has grown during the past few years, many important discoveries have been made in the fields of central nervous system (CNS) injury and disease using this emerging technology. In addition, single-cell mRNA amplification techniques are now being used along with microarrays to overcome many of the difficulties associated with the cellular heterogeneity of the brain. This development has extended the utility of gene expression profiling and has provided researchers with exciting new insights into the neuropathology of CNS injury and disease at a molecular and cellular level. New methodological, standardization, and statistical techniques are currently being developed to improve the reproducibility of microarrays and facilitate the analysis of large amounts of data. In this review, we will discuss the application of these techniques to experimental, clinically relevant models of traumatic brain injury.     

N-glycomic Profiling as a Tool to Separate Rectal Adenomas from Carcinomas

All human cells are covered by glycans, the carbohydrate units of glycoproteins, glycolipids, and proteoglycans. Most glycans are localized to cell surfaces and participate in events essential for cell viability and function. Glycosylation evolves during carcinogenesis, and therefore carcinoma-related glycan structures are potential cancer biomarkers. Colorectal cancer is one of the world''s three most common cancers, and its incidence is rising. Novel biomarkers are essential to identify patients for targeted and individualized therapy. We compared the N-glycan profiles of five rectal adenomas and 18 rectal carcinomas of different stages by matrix-assisted laser desorption-ionization time-of-flight mass spectrometry. Paraffin-embedded tumor samples were deparaffinized, and glycans were enzymatically released and purified. We found differences in glycosylation between adenomas and carcinomas: monoantennary, sialylated, pauci-mannose, and small high-mannose N-glycan structures were more common in carcinomas than in adenomas. We also found differences between stage I–II and stage III carcinomas. Based on these findings, we selected two glycan structures: pauci-mannose and sialyl Lewis a, for immunohistochemical analysis of their tissue expression in 220 colorectal cancer patients. In colorectal cancer, poor prognosis correlated with elevated expression of sialyl Lewis a, and in advanced colorectal cancer, poor prognosis correlated with elevated expression of pauci-mannose. In conclusion, by mass spectrometry we found several carcinoma related glycans, and we demonstrate a method of transforming these results into immunohistochemistry, a readily applicable method to study biomarker expression in patient samples.Glycans, the carbohydrate units of glycoproteins, glycolipids, and proteoglycans, that cover all human cells. Around 1% of the human genome participates in the biosynthesis of glycans(1). This biosynthesis is the most complex post-translational modification of proteins, and the great variability in glycan structures contains a tremendous ability to fine-tune the chemical and biological properties of glycoproteins. The glycosylation process occurs most abundantly in the Golgi apparatus and the endoplasmic reticulum, but also occurs in the cytoplasm and nucleus (2). Most glycoconjugates are localized to cell surfaces, where glycans participate in events essential for cell viability and function, such as cell adhesion, motility, and intracellular signaling (2). Changes in these functions are key steps seen when normal cells transform to malignant ones, and these are also reflected in changes of a cell''s glycan profile, observed in many cancers (3, 4). Specific structural changes in glycans may serve as cancer biomarkers (5, 6), and changes in glycosylation profiles are related to aggressive behavior in tumor cells (7–9).Cancer-associated asparagine-linked glycan (N-glycan) structures may play specific roles in supporting tumor progression; growth (10, 11), invasion (12, 13), and angiogenesis (14). Changes in the N-glycan profile emerge in numerous cancers, including lung (15, 16), breast (17), and colorectal cancer (CRC)¹ (16, 18). Balog et al. (18) comparing the N-glycomic profile of CRC tissue to adjacent normal mucosa, reported differences in specific glycan structures. Moreover, serum N-glycosylation profile from patients with CRC differ from those of healthy controls (19).Colorectal cancer is the third most common cause of cancer-related death worldwide and its incidence is rising; 40% of CRCs are of rectal origin. Roughly 40% of patients have localized disease (stage I–II; Dukes A–B), another 40% loco regional disease (stage III; Dukes C), and 20% metastasized disease (stage IV; Dukes D) (20). Although stage at diagnosis is the most important factor determining prognosis, clinical outcome, and response to adjuvant treatment can markedly vary within each stage. Adjuvant therapy routinely goes to stage III patients, but the benefit of adjuvant treatment for stage II patients is unclear. Of stage II patients, 80% are cured by radical surgery alone. To identify patients who will benefit from postoperative treatment, we need novel biomarkers. The glycan profile of the tumor tissue could provide new biomarkers for diagnosis and prognosis of cancer.In this study, we characterized the N-glycomic profiles of rectal adenomas and carcinomas by MALDI-TOF mass spectrometric (MS) profiling of asparagine-linked glycans. Our aim was to identify differences between adenomas and carcinomas, and also between cancers of different stages. Based on glycan profiling, we also chose, for immunohistochemical expression studies of a series of 220 CRC patients, two glycan markers: sialyl Lewis a and pauci-mannose.     

Gene Expression Profiling in Leiomyosarcomas and Undifferentiated Pleomorphic Sarcomas: SRC as a New Diagnostic Marker

Background

Undifferentiated Pleomorphic Sarcoma (UPS) and high-grade Leiomyosarcoma (LMS) are soft tissue tumors with an aggressive clinical behavior, frequently developing local recurrence and distant metastases. Despite several gene expression studies involving soft tissue sarcomas, the potential to identify molecular markers has been limited, mostly due to small sample size, in-group heterogeneity and absence of detailed clinical data.

Materials and Methods

Gene expression profiling was performed for 22 LMS and 22 UPS obtained from untreated patients. To assess the relevance of the gene signature, a meta-analysis was performed using five published studies. Four genes (BAD, MYOCD, SRF and SRC) selected from the gene signature, meta-analysis and functional in silico analysis were further validated by quantitative PCR. In addition, protein-protein interaction analysis was applied to validate the data. SRC protein immunolabeling was assessed in 38 UPS and 52 LMS.

Results

We identified 587 differentially expressed genes between LMS and UPS, of which 193 corroborated with other studies. Cluster analysis of the data failed to discriminate LMS from UPS, although it did reveal a distinct molecular profile for retroperitoneal LMS, which was characterized by the over-expression of smooth muscle-specific genes. Significantly higher levels of expression for BAD, SRC, SRF, and MYOCD were confirmed in LMS when compared with UPS. SRC was the most value discriminator to distinguish both sarcomas and presented the highest number of interaction in the in silico protein-protein analysis. SRC protein labeling showed high specificity and a positive predictive value therefore making it a candidate for use as a diagnostic marker in LMS.

Conclusions

Retroperitoneal LMS presented a unique gene signature. SRC is a putative diagnostic marker to differentiate LMS from UPS.