Phenotype MicroArrays for High-Throughput Phenotypic Testing and Assay of Gene Function

Bochner, Barry R.; Gadzinski, Peter; Panomitros, Eugenia

doi:10.1101/gr.186501

Cited by 597 publications

(610 citation statements)

References 28 publications

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“…Growth phenotyping data (11), available from Biolog (Hayward CA; www.biolog.com), were used to identify missing reactions from the reconstructed genome-scale metabolic network of E. coli MG1655 (iJR904) (12). Using a flux balance model of E. coli, we identified 54 minimal medium conditions with different carbon or nitrogen sources that support growth experimentally in the Biolog data but for which the reconstructed metabolic network could not explain a growth state.…”

Section: Resultsmentioning

confidence: 99%

Systems approach to refining genome annotation

Reed¹,

Patel²,

Chen³

et al. 2006

Proc. Natl. Acad. Sci. U.S.A.

262

291

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Genome-scale models of Escherichia coli K-12 MG1655 metabolism have been able to predict growth phenotypes in most, but not all, defined growth environments. Here we introduce the use of an optimization-based algorithm that predicts the missing reactions that are required to reconcile computation and experiment when they disagree. The computer-generated hypotheses for missing reactions were verified experimentally in five cases, leading to the functional assignment of eight ORFs (yjjLMN, yeaTU, dctA, idnT, and putP) with two new enzymatic activities and four transport functions. This study thus demonstrates the use of systems analysis to discover metabolic and transport functions and their genetic basis by a combination of experimental and computational approaches.constraint-based ͉ flux balance analysis ͉ functional genomics ͉ metabolic reconstruction ͉ systems biology C urrent genome annotations include a substantial fraction of ORFs with unknown function (1, 2); methods are needed to provide insight into the possible function of these genes, without the need for screening individual gene products across a multitude of possible activities. Metabolic and regulatory networks are reconstructed from genome annotations and scientific literature to integrate and represent our current knowledge of network components and interactions (3). Dual-perturbation methods have been developed to study regulatory networks (4), which can be used to reconcile model predictions and experimental data, thus leading to possible iterative model refinements and experimentally testable hypotheses (4, 5). Iterative modelbuilding can be systematized through the use of computational algorithms (6). Such an approach is presented here, and it consists of four steps. First, computational analysis identified discrepancies between model predictions and growth phenotyping data by using a reconstructed genome-scale Escherichia coli metabolic network. Second, an algorithm then identified enzymatic and transport reactions that likely were missing from the current metabolic reconstruction that could reconcile model predictions and experimental observations. Third, ORFs that might be responsible for these missing activities then were identified by using literature searches, sequence-homology searches (7), context-based homology methods (8, 9), and in some cases unpublished microarray data. Fourth, experimental verification of the algorithm's predictions then were carried out by evaluating growth phenotypes of single-deletion strains available in the Keio collection (10) and gene-expression measurements. Here we present a comprehensive combined computational and experimental approach to analyze phenotypic data and genome annotation information in a global manner to uncover individual ORF function. ResultsGrowth phenotyping data (11), available from Biolog (Hayward CA; www.biolog.com), were used to identify missing reactions from the reconstructed genome-scale metabolic network of E. coli MG1655 (iJR904) (12). Using a flux balance model of E. coli, we ...

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Section: Resultsmentioning

confidence: 99%

Systems approach to refining genome annotation

Reed¹,

Patel²,

Chen³

et al. 2006

Proc. Natl. Acad. Sci. U.S.A.

262

291

View full text Add to dashboard Cite

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“…In comparison with the wild-type strain, the opgGH mutant had lower ATP levels during growth initiation in low-pH medium. Biolog-based analysis of cell phenotypes is based on measuring overall cellular metabolic rates, resulting in a change in the redox potential which is monitored by a dye (Bochner et al, 2001). In light of an apparent paradoxical situation where viable cell numbers could not corroborate high throughput Biolog data (which indicated lower growth potential for the opgGH mutant), we examined cellular ATP contents of cells grown under acidic conditions (pH 5.0).…”

Section: Discussionmentioning

confidence: 99%

Osmoregulated periplasmic glucans of Salmonella enterica serovar Typhimurium are required for optimal virulence in mice

et al. 2009

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We purified osmoregulated periplasmic glucans (OPGs) from Salmonella enterica serovar Typhimurium and found them to be composed of 100 % glucose with 2-linked glucose as the most abundant residue, with terminal glucose, 2,3-linked and 2,6-linked glucose also present in high quantities. The two structural genes for OPG biosynthesis, opgG and opgH, form a bicistronic operon, and insertion of a kanamycin resistance gene cassette into this operon resulted in a strain devoid of OPGs. The opgGH mutant strain was impaired in motility and growth under low osmolarity conditions. The opgGH mutation also resulted in a 2 log increase in the LD 50 in mice compared to the wild-type strain SL1344. Inability to synthesize OPGs had no significant impact on the organism's lipopolysaccharide pattern or its ability to survive antimicrobial peptides-, detergent-, pH-and nutrient-stress conditions. We observed that the opgGH-defective strain respired at a reduced rate under acidic growth conditions (pH 5.0) and had lower ATP levels compared to the wild-type strain. These data indicate that OPGs of S. Typhimurium contribute towards mouse virulence as well as growth and motility under low osmolarity growth conditions.

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“…Phenotypic microarrays provide a method for rapid assessment of the phenotype of an organism under a wide variety of growth conditions such as different substrates, stressors, or nutrients (Bochner et al 2001;Borglin et al 2012). A commercially available OmniLog phenotypic microarray (Biolog, Inc. Hayward, CA) can be used to collect kinetic data allowing the discovery of fundamental differences in the respiration behavior of distinct organisms and substrates (Vaas et al 2012).…”

Section: Discovering and Screening For Il Tolerant Microorganisms Relmentioning

confidence: 99%

Ionic liquid-tolerant microorganisms and microbial communities for lignocellulose conversion to bioproducts

Simmons

Singer

et al. 2016

Appl Microbiol Biotechnol

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Chemical and physical pretreatment of biomass is a critical step in the conversion of lignocellulose to biofuels and bioproducts. Ionic liquid (IL) pretreatment has attracted significant attention due to the unique ability of certain ILs to solubilize some or all components of the plant cell wall. However, these ILs not only inhibit enzyme activities, but also the growth and productivity of microorganisms used in downstream hydrolysis and fermentation processes.While pretreated biomass can be washed to remove residual IL and reduce inhibition, extensive washing is costly and not feasible in large-scale processes. IL tolerant microorganisms and microbial communities have been discovered from environmental samples and studies begun to elucidate mechanisms of IL tolerance. The discovery of IL tolerance in environmental microbial communities and individual microbes has lead to the proposal of molecular mechanisms of resistance. In this article, we review recent progress on discovering IL tolerant microorganisms, identifying metabolic pathways and mechanisms of tolerance, and engineering microorganisms for IL tolerance. Research in these areas will yield new approaches to overcome inhibition in lignocellulosic biomass bioconversion processes and increase opportunities for the use of ILs in biomass pretreatment.

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Phenotype MicroArrays for High-Throughput Phenotypic Testing and Assay of Gene Function

Cited by 597 publications

References 28 publications

Systems approach to refining genome annotation

Systems approach to refining genome annotation

Osmoregulated periplasmic glucans of Salmonella enterica serovar Typhimurium are required for optimal virulence in mice

Ionic liquid-tolerant microorganisms and microbial communities for lignocellulose conversion to bioproducts

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