Kernel hierarchical gene clustering from microarray expression data

MOTIVATION: Unsupervised analysis of microarray gene expression data attempts to find biologically significant patterns within a given collection of expression measurements. For example, hierarchical clustering can be applied to expression profiles of genes across multiple experiments, identifying groups of genes that share similar expression profiles. Previous work using the support vector machine supervised learning algorithm with microarray data suggests that higher-order features, such as pairwise and tertiary correlations across multiple experiments, may provide significant benefit in learning to recognize classes of co-expressed genes. RESULTS: We describe a generalization of the hierarchical clustering algorithm that efficiently incorporates these higher-order features by using a kernel function to map the data into a high-dimensional feature space. We then evaluate the utility of the kernel hierarchical clustering algorithm using both internal and external validation. The experiments demonstrate that the kernel representation itself is insufficient to provide improved clustering performance. We conclude that mapping gene expression data into a high-dimensional feature space is only a good idea when combined with a learning algorithm, such as the support vector machine that does not suffer from the curse of dimensionality. AVAILABILITY: Supplementary data at www.cs.columbia.edu/compbio/hiclust. Software source code available by request.     

Robust regression for periodicity detection in non-uniformly sampled time-course gene expression data

Background  

In practice many biological time series measurements, including gene microarrays, are conducted at time points that seem to be interesting in the biologist's opinion and not necessarily at fixed time intervals. In many circumstances we are interested in finding targets that are expressed periodically. To tackle the problems of uneven sampling and unknown type of noise in periodicity detection, we propose to use robust regression.     

Global gene expression in Escherichia coli biofilms

It is now apparent that microorganisms undergo significant changes during the transition from planktonic to biofilm growth. These changes result in phenotypic adaptations that allow the formation of highly organized and structured sessile communities, which possess enhanced resistance to antimicrobial treatments and host immune defence responses. Escherichia coli has been used as a model organism to study the mechanisms of growth within adhered communities. In this study, we use DNA microarray technology to examine the global gene expression profile of E. coli during sessile growth compared with planktonic growth. Genes encoding proteins involved in adhesion (type 1 fimbriae) and, in particular, autoaggregation (Antigen 43) were highly expressed in the adhered population in a manner that is consistent with current models of sessile community development. Several novel gene clusters were induced upon the transition to biofilm growth, and these included genes expressed under oxygen-limiting conditions, genes encoding (putative) transport proteins, putative oxidoreductases and genes associated with enhanced heavy metal resistance. Of particular interest was the observation that many of the genes altered in expression have no current defined function. These genes, as well as those induced by stresses relevant to biofilm growth such as oxygen and nutrient limitation, may be important factors that trigger enhanced resistance mechanisms of sessile communities to antibiotics and hydrodynamic shear forces.     

外源基因在大肠杆菌中的高效表达

为了提高外源蛋白在大杨杆菌中的表达量,人们对大肠杆菌表达系统进行了许多研究。作者综述了有关外源基因在大肠杆菌中高效表达的研究进展。     

Regulated expression of the Escherichia coli dam gene

Regulated expression of the Escherichia coli dam gene has been achieved with the araBAD promoter lacking a ribosome binding site. Cultures of dam mutants containing plasmid pMQ430 show no detectable methylation in the absence of arabinose and complete methylation in its presence. Dam methyltransferase is a substrate for the Lon protease.     

Optimization and in situ detection of Escherichia coli beta-galactosidase gene expression in Dictyostelium discoideum

We show that a fusion gene, containing the promoter and 5'-noncoding region of a Dictyostelium discoideum actin 6 gene linked to the Escherichia coli beta-galactosidase (beta Gal) gene (lacZ), directs the production of functionally active beta Gal in D. discoideum and that the enzyme can be detected by staining in situ; a procedure which will be of great value in analyzing cell-type-specific gene expression. We illustrate this by fusing lacZ to the promoter of the prespore-specific gene, D19, and localizing expressing cells in migrating slugs. Optimal expression requires the inclusion of termination and polyadenylylation signals and we describe pDDlac, a vector containing a multiple cloning site upstream from a lacZ-Dictyostelium terminator fusion, which can be used to analyze regulated promoters.     

Processivity errors of gene expression in Escherichia coli

Not all ribosomes that initiate translation of an mRNA sequence will successfully complete it and produce a full-length protein product. By comparing the amounts of lacZ monomer and lacZ dimer protein expressed from a plasmid in a strictly controlled assay, we calculate a dimer to monomer ratio of 0.76. We interpret this to mean that ribosomes have a 76% chance of completing the synthesis of a beta-galactosidase polypeptide. The remaining 24% of the initiated chains end in processivity accidents. For the wild-type, premature RNA polymerase termination is found to account for roughly one-third of the processivity accidents. For the hyperaccurate SmP mutant, we observe a processivity of 0.28, but the presence of streptomycin improves this to 0.50. Thus, the hyperaccuracy with respect to missense substitutions for this mutant is accompanied by a reduced processivity. Addition of streptomycin increase the first error class and reduces the second one. This finding is relevant to the optimization of ribosome function and the growth performance of ribosome mutants.     

Knowledge-based assessment of gene expression data from chemiluminescence detection.

The first problem in gene expression profiling to be solved is choosing the appropriate gene array, detection procedure, image analysis and data generation depending on the organism of interest, equipment and budget. The next one is how to deduce biologically meaningful data. We assessed gene expression data from chemiluminescent detection and empirically found criteria for the reliable identification of biologically meaningful expression ratios. Current statistical assessments are often applied unreflectedly concerning problems occurring in practice. So interesting results are considered to be irrelevant. This requires a laborious data check. We suggest automation. Our empirically found criteria were transformed into and validated by a knowledge-based system. This system is adaptable to all other methods of expression profiling. We compared the experience-based and new knowledge-based assessment of the expression data from our chemiluminescent and additionally radioactive detection of several experiments with published data to evaluate our entire procedure. With our adaptation of chemiluminescence detection to commercially available Escherichia coli gene arrays we present a useful alternative to common procedures in gene expression monitoring. Moreover, with our consideration of plasmid-harbouring E. coli strains we provide the opportunity to monitor gene expression during processes requiring any plasmids (e.g. recombinant protein expression).     

Another gene affecting sexual expression of Escherichia coli

We have examined the relationship between two chromosomal mutations of Escherichia coli K-12, fexA (0 min) and fexB (85 min), in regulating expression of the F sex factor. Together, fexA and fexB exert a pleiotropic effect on the expression of the F tra genes. F pilus synthesis, conjugal donor activity, and surface exclusion activity are all inhibited in the fexA fexB mutant. Either fex mutation alone is cryptic.     

Direct expression of urogastrone gene in Escherichia coli

Human epidermal growth factor (urogastrone; UG) is a 53-amino acid polypeptide hormone. A 192-bp DNA fragment containing the coding sequence for methionyl UG (Met-UG) and the ribosome-binding site (RBS) was chemically synthesized and placed downstream from the promotor for the Escherichia coli outer-membrane lipoprotein gene (lpp) on a plasmid. E. coli cells harboring the plasmid directed the synthesis of Met-UG at 10(2)-10(3) molecules per cell. Next, the coding sequence for Met-UG was inserted in a runaway-replication plasmid and expressed under the control of the lpp promoter and the RBS derived from bacteriophage Mu cII gene. Upon heat induction, the cells harboring the recombinant plasmid synthesized 10(5) molecules of Met-UG per cell.     

枯草芽孢杆菌Mn-SOD基因的克隆及原核表达

为了实现Mn-SOD基因在大肠杆菌(E.coli)中的可溶性表达,根据枯草芽孢杆菌(Bacillus subtilis)168sodA核酸序列设计引物,以枯草芽孢杆菌ATCC 9372基因组为模板,PCR扩增获得了Mn-SOD基因.将此基因重组至原核表达载体pET-28a,构建含Mn-SOD基因的重组表达质粒,并转化至大肠杆菌BL21(DE3).异丙基-β-D-硫代半乳糖苷(IPTG)诱导表达获得Mn-SOD,蛋白分子量约为26kD,占全菌蛋白的5.6%.改良的连苯三酚自氧化法测定SOD活力,菌体可溶性总蛋白SOD比活为51.09U·mg^-1,是对照组的.8倍.枯草芽孢杆菌ATCC 9372 Mn-SOD基因在大肠杆菌BL21(DE3)中首次成功表达,产物具有较高的可溶性和活性,为大量制备Mn-SOD奠定了基础.     

D-乳酸高产菌菊糖芽胞乳杆菌Y2-8磷酸果糖激酶基因在大肠杆菌中的克隆和表达

以D-乳酸高产菌菊糖芽胞乳杆菌Y2-8基因组DNA为模板,通过PCR扩增得到960 bp的磷酸果糖激酶基因(pfk)。氨基酸序列比对分析表明,该磷酸果糖激酶(PFK)与其他乳酸菌PFK具有保守的底物结合位点,但是其变构效应物结合位点存在差异。将pfk基因克隆到表达载体pSE380上,获得重组菌E-pSE-pfk。进一步通过诱导条件的优化,重组菌的PFK比酶活达到4.89 U/mg,是优化前的4.79倍。采用低温诱导策略有助于实现菊糖芽胞乳杆菌pfk基因在大肠杆菌中可溶性表达。     

Bayesian hierarchical error model for analysis of gene expression data

MOTIVATION: Analysis of genome-wide microarray data requires the estimation of a large number of genetic parameters for individual genes and their interaction expression patterns under multiple biological conditions. The sources of microarray error variability comprises various biological and experimental factors, such as biological and individual replication, sample preparation, hybridization and image processing. Moreover, the same gene often shows quite heterogeneous error variability under different biological and experimental conditions, which must be estimated separately for evaluating the statistical significance of differential expression patterns. Widely used linear modeling approaches are limited because they do not allow simultaneous modeling and inference on the large number of these genetic parameters and heterogeneous error components on different genes, different biological and experimental conditions, and varying intensity ranges in microarray data. RESULTS: We propose a Bayesian hierarchical error model (HEM) to overcome the above restrictions. HEM accounts for heterogeneous error variability in an oligonucleotide microarray experiment. The error variability is decomposed into two components (experimental and biological errors) when both biological and experimental replicates are available. Our HEM inference is based on Markov chain Monte Carlo to estimate a large number of parameters from a single-likelihood function for all genes. An F-like summary statistic is proposed to identify differentially expressed genes under multiple conditions based on the HEM estimation. The performance of HEM and its F-like statistic was examined with simulated data and two published microarray datasets-primate brain data and mouse B-cell development data. HEM was also compared with ANOVA using simulated data. AVAILABILITY: The software for the HEM is available from the authors upon request.     

山梨糖脱氢酶基因在大肠杆菌染色体上整合及表达

以质粒pKF3为模板,扩增出两翼与ptsG基因上下游序列同源,中间为氯霉素抗性基因的DNA片段,连至pMD18T载体,构建得到pMD18PC。以质粒pQE60SDH为模板,扩增山梨糖脱氢酶基因sdh,与pMD18PC连接,得到pMD18PCSDH。将其用PvuⅡ酶切,回收含ptsG1catsdhptsG2的目的片段,电转化至JM109/pKD46,在Red重组酶的作用下,外源DNA片段与染色体上对应区域发生同源重组,将基因ptsG敲除,替换为catsdh基因,获得整合sdh基因的JM109s。经检测JM109s具有山梨糖脱氢酶活性。以 ptsG基因上下游序列为引物,JM109s基因组DNA为模板进行PCR,扩增产物测序结果表明sdh基因染色体整合成功。