Characterisation of Escherichia coli K-12 mutants defective in formate-dependent nitrite reduction: essential roles for hemN and the menFDBCE operon

Three Escherichia coli mutants defective in formate-dependent nitrite reduction (Nrf activity) were characterised. Two of the mutants, JCB354 and JCB356, synthesized all five c-type cytochromes previously characterised in anaerobic cultures of E. coli. The third mutant, JCB355, was defective for both cytochrome b and cytochrome c synthesis, but only during anaerobic growth. The insertion sites of the transposon in strains JCB354 and JCB356 mapped to the menFDBCE operon; the hemN gene was disrupted in strain JCB355. The mutation in strain JCB354 was complemented by a plasmid encoding only menD; strain JCB356 was complemented by a plasmid encoding only menBCE. A mutant defective in the methyltransferase activity involved in both ubiquinone synthesis and conversion of demethylmenaquinone to menaquinone expressed the same Nrf activity as the parental strain. The effects of men, ubiA and ubiE mutations on other cytochrome-c-dependent electron transfer pathways were also determined. The combined data establish that menaquinones are essential for cytochrome-c-dependent trimethylamine-N-oxide reductase (Tor) and Nrf activity, but that either menaquinone or ubiquinone, but not demethylmenaquinone, can transfer electrons to a third cytochrome-c-dependent electron transfer chain, the periplasmic nitrate reductase. Received: 9 December 1996 / Accepted: 11 June 1997     

The JCB DataViewer scales up

One of the major forces driving the birth of the field of cell biology was the application of electron microscopy to cells. Today, virtual nanoscopy has brought electron microscopy and the cell biology community to a new frontier in biological imaging and cell biological inquiry. The Journal of Cell Biology is pleased to announce that the JCB DataViewer is "going big" to host electron microscopy data at a whole new scale.     

The biogenesis of c-type cytochromes in Escherichia coli requires a membrane-bound protein, DipZ, with a protein disulphide isomerase-like domain

A mutant of Escherichia coli K-12, JCB606, which lacks all five c-type cytochromes synthesized during anaerobic growth in the presence of nitrite or tri-methylamine-N-oxide (TMAO), was totally defective in Nrf activity and also partially defective in TMAO reductase activity. The mutation in strain JCB606 was shown to affect expression of the tor operon, which contributes almost equally with the products of the dms operon to the rate of TMAO reduction by bacteria during anaerobic growth in the presence of TMAO. The mutation in strain JCB606, dipZ, was mapped by P1 transduction close to the mel operon at co-ordinate 4425 on the E. coli chromosome, the gene order being nrf–fdhF–mel–dipZ–ampC. Recombinant plasmids that restored Nrf activity to test-tube cultures of the mutant were isolated from a cosmid library. A 2.7 kb EcoRV–Smal fragment (co-ordinates 4443 to 4446 kb on the physical map of the E. coli chromosome) was found potentially to encode three genes arranged in at least two operons. The second gene, dipZ, was sufficient to complement the JCB606 mutation. The translated DNA sequence predicts that DipZ is a 53kDa integral membrane protein with a 37kDa N-terminal domain including at least six membrane-spanning helices and a 16kDa carboxy-terminal hydrophilic domain which includes a protein disulphide isomerase-like motif. It is suggested that DipZ is essential for maintaining cytochrome c apoproteins in the correct conformations for the covalent attachment of haem groups to the appropriate pairs of cysteine residues.     

Bringing Rad52 foci into focus

In 2007, we published the results of a genome-wide screen for ORFs that affect the frequency of Rad52 foci in yeast. That paper was published within the constraints of conventional online publishing tools, and it provided only a glimpse into the actual screen data. New tools in the JCB DataViewer now show how these data can—and should—be shared.

Complete screen data

https://doi.org/10.1083/jcb.201108095.dv The Rad52 protein has pivotal functions in double strand break repair and homologous recombination. The activity of Rad52 is often monitored by the subnuclear foci that it forms spontaneously in S phase or after DNA damage (Lisby et al., 2001). In mammals, the functions of yeast Rad52 may be divided between human RAD52 and the tumor suppressor BRCA2 (Feng et al., 2011). The full host of molecular players that govern Rad52 focus formation and maintenance was not well known when we initiated our screen. Using a high-content, image-based assay, we assessed the proportion of cells containing spontaneous Rad52-YFP foci in 4,805 viable Saccharomyces cerevisiae deletion strains (Alvaro et al., 2007). Starting with 96-well arrays of a deletion strain library, we created hybrid diploid strains (homozygous for the deletions) using systematic hybrid loss of heterozygosity (SHyLOH; Alvaro et al., 2006). We then manually and sequentially examined each strain using epifluorescence microscopy for the presence of Rad52-YFP foci. All of our image analysis was performed manually.As is often the case, our screen was published showing only a couple of representative images and providing data tables to summarize the findings. Tomes of data that could not be included in the published paper were relegated to supplemental Excel tables, typical of genome-wide screens. Also, the raw image data were sequestered in the laboratory on DVDs. With considerable help from JCB and Glencoe Software, we are delighted that the raw data from our Rad52 screen are now freely available online through the JCB DataViewer. A new interface within the JCB DataViewer brings presentation and preservation of high-content, multidimensional image-based screening data to a whole new level. To facilitate the development of this new interface, JCB required a dataset that was not time sensitive, and we were happy to provide our previously published Rad52 data. In the future, this new interface will be used to present high-content screening (HCS) datasets linked to published JCB papers. Indeed, the first publication of this sort appears in this issue of JCB (Rohn et al., 2011).The presentation of our data in the JCB DataViewer clearly shows the many benefits of this new publishing resource for the scientific community. Users now can view the complete collection of 3D image data across the entire screen, not just the two images in our original publication (Alvaro et al., 2007). Additionally, detailed information on image acquisition parameters, locus identities, and more is easily accessible (Fig. 1). Phenotypic scoring results can be visualized in interactive chart formats (Fig. 1), and search (Fig. 2) and database-linking tools (Fig. 1) allow extensive mining of the data for genes and phenotypes of interest. These tools provide an unprecedented view into HCS data in their entirety, as well as a means for authors to share and archive their data. This kind of accessibility to the direct visualization of the entire set of original screening data, on a scale previously only available to the scientists performing the screen, allows users to understand the full context of the image data analyzed in a screen. Furthermore, it is only through full access to the raw images and associated metadata that this information can be of maximum use to the community for large-scale data mining.Open in a separate windowFigure 1.The HCS interface of the JCB DataViewer provides interactive tools for the analysis of complete datasets from image-based screens. The miniviewer (top left) provides information for each gene in the screen through a zoomable and scrollable display of original multidimensional image data. It contains detailed metadata and a gene ontology (GO) summary, a link to a relevant external database (e.g., the Saccharomyces Genome Database [SGD]; top right), and a link to phenotypic scoring data for the complete screen in the chart view (bottom right). Within the chart view, hits designated by the screen authors are shown in blue, and the strain currently on display in the miniviewer is shown in red. The plate view (bottom left) shows the position of the strain of interest (red box) relative to other strains screened.Open in a separate windowFigure 2.The HCS interface of the JCB DataViewer provides search tools for the mining of complete datasets from image-based screens. (A) Users can search screen data by gene name or keywords (e.g., DNA repair). (B) Users can pick candidates for further analysis from the phenotypic scoring information in the chart view.As in all large-scale screens, the real data are variable; e.g., some strains provide a clear Rad52 focus phenotype, whereas others are more ambiguous. For our particular screen, images were not collected using automated technology but were acquired manually, strain by strain, over a period of months, leading to different levels of fluorescence intensity of Rad52-YFP as a result of, for example, changes in the intensity of our mercury arc lamp. Differences also exist in the number of fields and z stacks captured for each strain. In the absence of automated image collection, images from the primary screen in a few cases were not archived with the others and thus for all intents and purposes have been lost. In addition, our Rad52 screen only assayed nonessential genes, and some mutants are refractory to the SHyLOH methodology. Knowing all of this information allows users to view the data in a realistic manner and further highlights the importance of providing a central repository to archive HCS data.When published through conventional publication media, many important imaging details are known only to the original screeners. The new HCS interface of the JCB DataViewer shines a light on screening data as metadata become freely accessible, allowing any user to ask novel questions of the dataset. For example, the plate view for images (Fig. 1) allows users to assess whether neighboring colonies played any role in determining the phenotype and to delve deeper into why that might be. For example, are any “hits” a result of contamination from adjacent strains, resulting in clusters of positives? In the context of an automated screen, how were control and experimental samples arrayed across a plate during data collection? Did the controls on a particular plate behave as expected? Because our screen used a novel chromosome-specific loss of the heterozygosity method, users can ask whether mutations on specific chromosomes share features of Rad52 foci levels. The global resolution of the dataset provided through this new interface puts users of the dataset as close to the seat of the original screening scientist as possible, allowing them to ask, “what did the authors really see?”Presenting HCS data in the JCB DataViewer holds immense potential value to the scientific community. Through this new interface, users can access powerful interactive tools for analyzing scored phenotypes across the entire dataset (Fig. 1). Each gene ID can be charted against the phenotypic parameters scored in the original screen (e.g., the percentage of cells with Rad52 foci) and compared with all other loci (Fig. 1). Users can take our data and create their own list of hits based on their criteria, create a gallery of thumbnails for their selections (Fig. 2), and seamlessly move between their list of hits and the original data in the plate display format (Fig. 1). Users can also compare their candidates with our list (Fig. 2). The ability to visualize these data for comparative analyses creates a whole new perspective. The HCS interface of the JCB DataViewer allows users to look for their favorite gene, compare related genes, and discover new genes they never anticipated were involved in a given process.In summary, these new features of the JCB DataViewer will allow users to access the primary data from large-scale screens and to look at the full dataset to see what all of the images really look like. The ability to mine these data opens up whole new dimensions in data sharing and transparency. In the future, we anticipate that it will be possible to search many genome-wide screens, such as our Rad52 dataset, to identify commonalities in protein localization, concentration, cell morphology, etc. However, this will only occur if image data are archived and made freely available to the scientific community. We wholeheartedly support the efforts of JCB and hope that groups that use image-based HCS will increasingly make their images available using tools such as the JCB DataViewer.     

Levels of DNA strand breaks and superoxide in phorbol ester-treated human granulocytes

Phorbol ester treatment of granulocytes triggers release of superoxide (O) and a concomitant burst of DNA strand breaks. The relationship between the amount of O and the number of DNA breaks has not previously been explored. To quantify the relatively large amount of O generated over a 40-min period by 1 × 10⁶ granulocytes/mL, a discontinuous “10-min pulse” method employing cytochrome c was used; 140 nmol O per 1 × 10⁶ cells was detected. DNA strand breaks were quantified by fluorimetric analysis of DNA unwinding (FADU). To vary the level of O released by cells, inhibitors of the respiratory burst were used. Sodium fluoride (1–10 mM) and staurosporine (2–10 nM) both inhibited O production. In both cases, however, inhibition of strand breakage was considerably more pronounced than inhibition of O. Zinc chloride (50–200 μM) inhibited both O and DNA breaks, approximately equally. Dinophysistoxin-1 (okadaic acid) inhibited O production more effectively than it inhibited DNA breaks. O dismutes to H₂O₂, a reactive oxygen species known to cause DNA breaks. The addition of catalase to remove extracellular H₂O₂ had no effect on DNA breakage. Using pulse field gel electrophoresis, few double-stranded breaks were detected compared to the number detected by FADU, indicating that about 95% of breaks were single-stranded. The level of DNA breaks is not directly related to the amount of extracellular O or H₂O₂ in PMA-stimulated granulocytes. We conclude that either an intracellular pool of these reactive oxygen species is involved in breakage or that the metabolic inhibitors are affecting a novel strand break pathway. J. Cell. Biochem. 66:219–228, 1997. © 1997 Wiley-Liss Inc.     

Interplay of reactive oxygen species,intracellular Ca2+ and mitochondrial homeostasis in the apoptosis of prostate cancer cells by deoxypodophyllotoxin

The limited treatment option for recurrent prostate cancer and the eventual resistance to conventional chemotherapy drugs has fueled continued interest in finding new anti‐neoplastic agents of natural product origin. We previously reported anti‐proliferative activity of deoxypodophyllotoxin (DPT) on human prostate cancer cells. Using the PC‐3 cell model of human prostate cancer, the present study reveals that DPT induced apoptosis via a caspase‐3‐dependent pathway that is activated due to dysregulated mitochondrial function. DPT‐treated cells showed accumulation of the reactive oxygen species (ROS), intracellular Ca surge, increased mitochondrial membrane potential (MMP, ΔΨ_m), Bax protein translocation to mitochondria and cytochrome c release to the cytoplasm. This resulted in caspase‐3 activation, which in turn induced apoptosis. The antioxidant N‐acetylcysteine (NAC) reduced ROS accumulation, MMP and Ca surge, on the other hand the Ca²⁺ chelator BAPTA inhibited the Ca overload and MMP without affecting the increase of ROS, indicating that the generation of ROS occurred prior to Ca²⁺ flux. This suggested that both ROS and Ca signaling play roles in the increased MMP via Ca‐dependent and/or ‐independent mechanisms, since ΔΨ_m elevation was reversed by NAC and BAPTA. This study provides the first evidence for the involvement of both ROS‐ and Ca‐activated signals in the disruption of mitochondrial homeostasis and the precedence of ROS production over the failure of Ca²⁺ flux homeostasis. J. Cell. Biochem. 114: 1124–1134, 2013. © 2012 Wiley Periodicals, Inc.     

Lipid rafts as organizing platforms for cell chemotaxis and axon guidance

Lipid rafts are thought to serve as plasma membrane platforms for localized trafficking and signaling. Recent findings reported by Guirland et al. in this issue of Neuron and by Gómez-Moutón in a recent issue of JCB support a direct role of lipid microdomains in organizing spatial signaling during axon guidance and cell chemotaxis by concentrating the gradient-sensing machinery at the leading edge.     

Phenotypic characterization of transgenic mice harboring Nf1+/- or Nf1-/- osteoclasts in otherwise Nf1+/+ background

Skeletal abnormalities in neurofibromatosis type 1 syndrome (NF1) are observed in ～50% of patients. Here, we describe the phenotype of Nf1_Ocl mouse model with Nf1‐deficient osteoclasts. Nf1_Ocl mice with Nf1^+/? or Nf1^?/? osteoclasts in otherwise Nf1^+/+ background were successfully generated by mating parental Nf1flox/flox and TRAP‐Cre mice. Contrary to our original hypothesis, osteoporotic or fragile bone phenotype was not observed. The µCT analysis revealed that tibial bone marrow cavity, trabecular tissue volume, and the perimeter of cortical bone were smaller in Nf1 mice compared to Nf1 control mice. Nf1 mice also a displayed narrowed growth plate in the proximal tibia. In vitro analysis showed increased bone resorption capacity and cytoskeletal changes including irregular cell shape and abnormal actin ring formation in Nf1^?/? osteoclasts. Surprisingly, the size of spleen in Nf1 mice was two times larger than in controls and histomorphometric analysis showed splenic megakaryocytosis. In summary, Nf1Ocl mouse model presented with a mild but specific bone phenotype. This study shows that NF1‐deficiency in osteoclasts may have a role in the development of NF1‐related skeletal abnormalities, but Nf1‐deficiency in osteoclasts in Nf1^+/+ background is not sufficient to induce skeletal abnormalities analogous to those observed in patients with NF1. J. Cell. Biochem. 113: 2136–2146, 2012. © 2012 Wiley Periodicals, Inc.     

High confidence rule mining for microarray analysis

We present an association rule mining method for mining high confidence rules, which describe interesting gene relationships from microarray datasets. Microarray datasets typically contain an order of magnitude more genes than experiments, rendering many data mining methods impractical as they are optimised for sparse datasets. A new family of row-enumeration rule mining algorithms have emerged to facilitate mining in dense datasets. These algorithms rely on pruning infrequent relationships to reduce the search space by using the support measure. This major shortcoming results in the pruning of many potentially interesting rules with low support but high confidence. We propose a new row-enumeration rule mining method, MaxConf, to mine high confidence rules from microarray data. MaxConf is a support-free algorithm which directly uses the confidence measure to effectively prune the search space. Experiments on three microarray datasets show that MaxConf outperforms support-based rule mining with respect to scalability and rule extraction. Furthermore, detailed biological analyses demonstrate the effectiveness of our approach -- the rules discovered by MaxConf are substantially more interesting and meaningful compared with support-based methods.     

Combined dynamic arrays for storing and searching semi-ordered tandem mass spectrometry data.

When performing bioinformatics analysis on tandem mass spectrometry data, there is a computational need to efficiently store and sort these semi-ordered datasets. To solve this problem, a new data structure based on dynamic arrays was designed and implemented in an algorithm that parses semi-ordered data made by Mascot, a separate software program that matches peptide tandem mass spectra to protein sequences in a database. By accommodating the special features of these large datasets, the combined dynamic array (CDA) provides efficient searching and insertion operations. The operations on real datasets using this new data structure are hundreds times faster than operations using binary tree and red-black tree structures. The difference becomes more significant when the dataset size grows. This data structure may be useful for improving the speed of other related types of protein assembling software or other types of software that operate on datasets with similar semi-ordered features.     

Meta-analysis identifies pleiotropic loci controlling phenotypic trade-offs in sorghum

Community association populations are composed of phenotypically and genetically diverse accessions. Once these populations are genotyped, the resulting marker data can be reused by different groups investigating the genetic basis of different traits. Because the same genotypes are observed and scored for a wide range of traits in different environments, these populations represent a unique resource to investigate pleiotropy. Here, we assembled a set of 234 separate trait datasets for the Sorghum Association Panel, a group of 406 sorghum genotypes widely employed by the sorghum genetics community. Comparison of genome-wide association studies (GWAS) conducted with two independently generated marker sets for this population demonstrate that existing genetic marker sets do not saturate the genome and likely capture only 35–43% of potentially detectable loci controlling variation for traits scored in this population. While limited evidence for pleiotropy was apparent in cross-GWAS comparisons, a multivariate adaptive shrinkage approach recovered both known pleiotropic effects of existing loci and new pleiotropic effects, particularly significant impacts of known dwarfing genes on root architecture. In addition, we identified new loci with pleiotropic effects consistent with known trade-offs in sorghum development. These results demonstrate the potential for mining existing trait datasets from widely used community association populations to enable new discoveries from existing trait datasets as new, denser genetic marker datasets are generated for existing community association populations.     

ANOVA-simultaneous component analysis (ASCA): a new tool for analyzing designed metabolomics data

MOTIVATION: Datasets resulting from metabolomics or metabolic profiling experiments are becoming increasingly complex. Such datasets may contain underlying factors, such as time (time-resolved or longitudinal measurements), doses or combinations thereof. Currently used biostatistics methods do not take the structure of such complex datasets into account. However, incorporating this structure into the data analysis is important for understanding the biological information in these datasets. RESULTS: We describe ASCA, a new method that can deal with complex multivariate datasets containing an underlying experimental design, such as metabolomics datasets. It is a direct generalization of analysis of variance (ANOVA) for univariate data to the multivariate case. The method allows for easy interpretation of the variation induced by the different factors of the design. The method is illustrated with a dataset from a metabolomics experiment with time and dose factors.     

Microscopy Image Browser: A Platform for Segmentation and Analysis of Multidimensional Datasets

Understanding the structure–function relationship of cells and organelles in their natural context requires multidimensional imaging. As techniques for multimodal 3-D imaging have become more accessible, effective processing, visualization, and analysis of large datasets are posing a bottleneck for the workflow. Here, we present a new software package for high-performance segmentation and image processing of multidimensional datasets that improves and facilitates the full utilization and quantitative analysis of acquired data, which is freely available from a dedicated website. The open-source environment enables modification and insertion of new plug-ins to customize the program for specific needs. We provide practical examples of program features used for processing, segmentation and analysis of light and electron microscopy datasets, and detailed tutorials to enable users to rapidly and thoroughly learn how to use the program.     

Chaperone Caf1M stabilizes hybrid proteins containing sequences of F1 antigen subunit from Yersinia pestis

The Yersinia pestis (causative agent of plague) capsule antigen is a homopolymer of Caf1 protein. Export of the subunits is mediated by the periplasmic chaperone Caf1M. To study the mechanism of Caf1M activity, two hybrid genes including coding sequences for the Caf1 signal peptide, human granulocyte-macrophage colony-stimulating factor (GM-CSF) or interleukin-1 (IL-1) receptor antagonist, and mature Caf1 were constructed and expressed in Escherichia coli. We have shown that in the absence of Caf1M the majority of Caf1 moieties within the hybrid proteins undergo proteolysis in the periplasmic space, presumably by the DegP protease. The coexpression of a gene for chaperone Caf1M significantly increased the amount of full-size hybrid proteins in the periplasm, probably as a result of stabilization of the subunits spatial structure within the hybrid. This effect was not observed in JCB571 cells, which lack periplasmic disulfide isomerase DsbA, essential for Caf1M activity.     

适于癌基因表达数据集的新特征提取标准NFEC及其分类新算法研究

癌基因表达数据集具有小样本、高维数之特点,一般的机器学习机难以对其有效分类。因此,通常需要采用某些特征提取度量标准来进行降维处理。可是常用的一些特征提取度量标准亦会导致分类效果欠佳之问题。依据微分容量控制学习机DCCM,提出了一个新的特征提取度量标准NFEC,然后依据NFEC和DCCM,提出了适于癌基因表达数据集的特征提取算法DCCFE。实验表明,新的度量NFEC和新的特征提取算法DCCFE较之现有方法对癌基因表达数据集分类时更为有效。本文的工作意义在于:(1)提出了一个新的更有意义的特征提取度量标准;(2)DCCM可以采用比核函数更为一般的一阶可微函数,因而提出的新的特征提取算法更具普遍应用意义。     

A benchmark for statistical microarray data analysis that preserves actual biological and technical variance

Background  

Recent reanalysis of spike-in datasets underscored the need for new and more accurate benchmark datasets for statistical microarray analysis. We present here a fresh method using biologically-relevant data to evaluate the performance of statistical methods.