Several reactive oxygen species (ROS) are continuously produced in plants as byproducts of aerobic metabolism. Depending on the nature of the ROS species, some are highly toxic and rapidly detoxified by various cellular enzymatic and nonenzymatic mechanisms. Whereas plants are surfeited with mechanisms to combat increased ROS levels during abiotic stress conditions, in other circumstances plants appear to purposefully generate ROS as signaling molecules to control various processes including pathogen defense, programmed cell death, and stomatal behavior. This review describes the mechanisms of ROS generation and removal in plants during development and under biotic and abiotic stress conditions. New insights into the complexity and roles that ROS play in plants have come from genetic analyses of ROS detoxifying and signaling mutants. Considering recent ROS-induced genome-wide expression analyses, the possible functions and mechanisms for ROS sensing and signaling in plants are compared with those in animals and yeast.

REACTIVE OXYGEN SPECIES: Metabolism, Oxidative Stress, and Signal Transduction

Motivation: Gene expression microarray experiments can generate data sets with multiple missing expression values. Unfortunately, many algorithms for gene expression analysis require a complete matrix of gene array values as input. For example, methods such as hierarchical clustering and K-means clustering are not robust to missing data, and may lose effectiveness even with a few missing values. Methods for imputing missing data are needed, therefore, to minimize the effect of incomplete data sets on analyses, and to increase the range of data sets to which these algorithms can be applied. In this report, we investigate automated methods for estimating missing data. Results: We present a comparative study of several methods for the estimation of missing values in gene microarray data. We implemented and evaluated three methods: a Singular Value Decomposition (SVD) based method (SVDimpute), weighted K-nearest neighbors (KNNimpute), and row average. We evaluated the methods using a variety of parameter settings and over different real data sets, and assessed the robustness of the imputation methods to the amount of missing data over the range of 1–20% missing values. We show that KNNimpute appears to provide a more robust and sensitive method for missing value estimation than SVDimpute, and both SVDimpute and KNNimpute surpass the commonly used row average method (as well as filling missing values with zeros). We report results of the comparative experiments and provide recommendations and tools for accurate estimation of missing microarray data under a variety of conditions. Availability: The software is available at http://smi-web.

/pdf/missing-value-estimation-methods-for-dna-microarrays-k2b284lyfd.pdf

Missing value estimation methods for DNA microarrays.

We have determined how most of the transcriptional regulators encoded in the eukaryote Saccharomyces cerevisiaeassociate with genes across the genome in living cells. Just as maps of metabolic networks describe the potential pathways that may be used by a cell to accomplish metabolic processes, this network of regulator-gene interactions describes potential pathways yeast cells can use to regulate global gene expression programs. We use this information to identify network motifs, the simplest units of network architecture, and demonstrate that an automated process can use motifs to assemble a transcriptional regulatory network structure. Our results reveal that eukaryotic cellular functions are highly connected through networks of transcriptional regulators that regulate other transcriptional regulators.

https://science.sciencemag.org/content/sci/298/5594/799.full.pdf

Transcriptional Regulatory Networks in Saccharomyces cerevisiae

A large number of clustering approaches have been proposed for the analysis of gene expression data obtained from microarray experiments. However, the results from the application of standard clustering methods to genes are limited. This limitation is imposed by the existence of a number of experimental conditions where the activity of genes is uncorrelated. A similar limitation exists when clustering of conditions is performed. For this reason, a number of algorithms that perform simultaneous clustering on the row and column dimensions of the data matrix has been proposed. The goal is to find submatrices, that is, subgroups of genes and subgroups of conditions, where the genes exhibit highly correlated activities for every condition. In this paper, we refer to this class of algorithms as biclustering. Biclustering is also referred in the literature as coclustering and direct clustering, among others names, and has also been used in fields such as information retrieval and data mining. In this comprehensive survey, we analyze a large number of existing approaches to biclustering, and classify them in accordance with the type of biclusters they can find, the patterns of biclusters that are discovered, the methods used to perform the search, the approaches used to evaluate the solution, and the target applications.

/pdf/biclustering-algorithms-for-biological-data-analysis-a-1rk317ema5.pdf

Biclustering Algorithms for Biological Data Analysis: A Survey

We demonstrate an integrated approach to build, test, and refine a model of a cellular pathway, in which perturbations to critical pathway components are analyzed using DNA microarrays, quantitative proteomics, and databases of known physical interactions. Using this approach, we identify 997 messenger RNAs responding to 20 systematic perturbations of the yeast galactose-utilization pathway, provide evidence that approximately 15 of 289 detected proteins are regulated posttranscriptionally, and identify explicit physical interactions governing the cellular response to each perturbation. We refine the model through further iterations of perturbation and global measurements, suggesting hypotheses about the regulation of galactose utilization and physical interactions between this and a variety of other metabolic pathways.

/pdf/integrated-genomic-and-proteomic-analyses-of-a-3dp6ibi8g5.pdf

Integrated genomic and proteomic analyses of a systematically perturbed metabolic network.

We explored genomic expression patterns in the yeast Saccharomyces cerevisiae responding to diverse environmental transitions. DNA microarrays were used to measure changes in transcript levels over time for almost every yeast gene, as cells responded to temperature shocks, hydrogen peroxide, the superoxide-generating drug menadione, the sulfhydryl-oxidizing agent diamide, the disulfide-reducing agent dithiothreitol, hyper- and hypo-osmotic shock, amino acid starvation, nitrogen source depletion, and progression into stationary phase. A large set of genes (approximately 900) showed a similar drastic response to almost all of these environmental changes. Additional features of the genomic responses were specialized for specific conditions. Promoter analysis and subsequent characterization of the responses of mutant strains implicated the transcription factors Yap1p, as well as Msn2p and Msn4p, in mediating specific features of the transcriptional response, while the identification of novel sequence elements provided clues to novel regulators. Physiological themes in the genomic responses to specific environmental stresses provided insights into the effects of those stresses on the cell.

/pdf/genomic-expression-programs-in-the-response-of-yeast-cells-4xrnicxf7t.pdf

Genomic expression programs in the response of yeast cells to environmental changes.

Macrocyclic polyketides have been subjects of great interest in synthetic and biosynthetic chemistry because of their structural complexity and medicinal activities. With expression of the entire 6-deoxyerythronolide B synthase (DEBS) (10,283 amino acids) in a heterologous host, substantial quantities of 6-deoxyerythronolide B (6dEB), the aglycone of the macrolide antibiotic erythromycin, and 8,8a-deoxyoleandolide, a 14-membered lactone ring identical to 6dEB except for a methyl group side chain in place of an ethyl unit, were synthesized in Streptomyces coelicolor. The biosynthetic strategy utilizes a genetic approach that facilitates rapid structural manipulation of DEBS or other modular polyketide synthases (PKSs), including those found in actinomycetes with poorly developed genetic methods. From a technological viewpoint, this approach should allow the rational design of biosynthetic products and may eventually lead to the generation of diverse polyketide libraries by means of combinatorial cloning of naturally occurring and mutant PKS modules.

https://science.sciencemag.org/content/sci/265/5171/509.full.pdf

Engineered biosynthesis of a complete macrolactone in a heterologous host

The filamentous bacterium Streptomyces coelicolor differentiates by forming specialized, spore-bearing aerial hyphae that grow into the air. Using microarrays, we identified genes that are down-regulated in a mutant unable to erect aerial hyphae. Through this route, we identified a previously unknown layer of aerial mycelium surface proteins (the “chaplins”). The chaplins share a hydrophobic domain of ∼40 residues (the “chaplin domain”), and all have a secretion signal. The five short chaplins (ChpD,E,F,G,H) have one chaplin domain, whereas the three long chaplins (ChpA,B,C) have two chaplin domains and a C-terminal “sorting signal” that targets them for covalent attachment to the cell wall by sortase enzyme. Expression of the two chaplin genes examined (chpE, chpH) depended on aerial hyphae formation but not sporulation, and egfp fusions showed their expression localized to aerial structures. Mass spectrometry of cell wall extracts confirmed that the short chaplins localized to the cell surface. Deletion of chaplin genes caused severe delays in aerial hyphae formation, a phenotype rescued by exogenous application of chaplin proteins. These observations implicate the chaplins in aerial mycelium formation, and suggest that coating of the envelope by the chaplins is required for aerial hyphae to grow out of the aqueous environment of the substrate mycelium into the air.

/pdf/the-chaplins-a-family-of-hydrophobic-cell-surface-proteins-2ge6xy0jvz.pdf

The chaplins: a family of hydrophobic cell-surface proteins involved in aerial mycelium formation in Streptomyces coelicolor

A complex programme of regulation governs gene expression during development of the morphologically and biochemically complex eubacterial genus Streptomyces. Earlier work has suggested a model in which 'higher level' pleiotropic regulators activate 'pathway-specific' regulators located within chromosomal gene clusters encoding biosynthesis of individual antibiotics. We used mutational analysis and adventitious overexpression of key Streptomyces coelicolor regulators to investigate functional interactions among them. We report here that cluster-situated regulators (CSRs) thought to be pathway-specific can also control other antibiotic biosynthetic gene clusters, and thus have pleiotropic actions. Surprisingly, we also find that CSRs exhibit growth-phase-dependent control over afsR2/afsS, a 'higher level' pleiotropic regulatory locus not located within any of the chromosomal gene clusters it targets, and further demonstrate that cross-regulation by CSRs is modulated globally and differentially during the S. coelicolor growth cycle by the RNaseIII homologue AbsB. Our results, which reveal a network of functional interactions among regulators that govern production of antibiotics and other secondary metabolites in S. coelicolor, suggest that revision of the currently prevalent view of higher-level versus pathway-specific regulation of secondary metabolism in Streptomyces species is warranted.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1365-2958.2005.04879.x

Cross‐regulation among disparate antibiotic biosynthetic pathways of Streptomyces coelicolor

Novel polyketides and novel methods of efficiently producing both new and known polyketides, using recombinant technology, are disclosed. In particular, a novel host-vector system is described which is used to produce polyketide synthases which in turn catalyze the production of a variety of polyketides.

Camilla M. Kao

Papers

Genomic expression programs in the response of yeast cells to environmental changes.

Engineered biosynthesis of a complete macrolactone in a heterologous host

The chaplins: a family of hydrophobic cell-surface proteins involved in aerial mycelium formation in Streptomyces coelicolor

Cross‐regulation among disparate antibiotic biosynthetic pathways of Streptomyces coelicolor

Recombinant production of novel polyketides