The Expanded Diversity of Methylophilaceae from Lake Washington through Cultivation and Genomic Sequencing of Novel Ecotypes

We describe five novel Methylophilaceae ecotypes from a single ecological niche in Lake Washington, USA, and compare them to three previously described ecotypes, in terms of their phenotype and genome sequence divergence. Two of the ecotypes appear to represent novel genera within the Methylophilaceae. Genome-based metabolic reconstruction highlights metabolic versatility of Methylophilaceae with respect to methylotrophy and nitrogen metabolism, different ecotypes possessing different combinations of primary substrate oxidation systems (MxaFI-type methanol dehydrogenase versus XoxF-type methanol dehydrogenase; methylamine dehydrogenase versus N-methylglutamate pathway) and different potentials for denitrification (assimilatory versus respiratory nitrate reduction). By comparing pairs of closely related genomes, we uncover that site-specific recombination is the main means of genomic evolution and strain divergence, including lateral transfers of genes from both closely- and distantly related taxa. The new ecotypes and the new genomes contribute significantly to our understanding of the extent of genomic and metabolic diversity among organisms of the same family inhabiting the same ecological niche. These organisms also provide novel experimental models for studying the complexity and the function of the microbial communities active in methylotrophy.     

A Method Adapting Microarray Technology for Signature-Tagged Mutagenesis of Desulfovibrio desulfuricans G20 and Shewanella oneidensis MR-1 in Anaerobic Sediment Survival Experiments

Signature-tagged mutagenesis (STM) is a powerful technique that can be used to identify genes expressed by bacteria during exposure to conditions in their natural environments. To date, there have been no reports of studies in which this approach was used to study organisms of environmental, rather than pathogenic, significance. We used a mini-Tn10 transposon-bearing plasmid, pBSL180, that efficiently and randomly mutagenized Desulfovibrio desulfuricans G20 in addition to Shewanella oneidensis MR-1. Using these organisms as model sediment-dwelling anaerobic bacteria, we developed a new screening system, modified from former STM procedures, to identify genes that are critical for sediment survival. The screening system uses microarray technology to visualize tags from input and output pools, allowing us to identify those lost during sediment incubations. While the majority of data on survival genes identified will be presented in future papers, we report here on chemotaxis-related genes identified by our STM method in both bacteria in order to validate our method. This system may be applicable to the study of numerous environmental bacteria, allowing us to identify functions and roles of survival genes in various habitats.     

Reconstruction and Validation of a Genome-Scale Metabolic Model for the Filamentous Fungus Neurospora crassa Using FARM

The filamentous fungus Neurospora crassa played a central role in the development of twentieth-century genetics, biochemistry and molecular biology, and continues to serve as a model organism for eukaryotic biology. Here, we have reconstructed a genome-scale model of its metabolism. This model consists of 836 metabolic genes, 257 pathways, 6 cellular compartments, and is supported by extensive manual curation of 491 literature citations. To aid our reconstruction, we developed three optimization-based algorithms, which together comprise Fast Automated Reconstruction of Metabolism (FARM). These algorithms are: LInear MEtabolite Dilution Flux Balance Analysis (limed-FBA), which predicts flux while linearly accounting for metabolite dilution; One-step functional Pruning (OnePrune), which removes blocked reactions with a single compact linear program; and Consistent Reproduction Of growth/no-growth Phenotype (CROP), which reconciles differences between in silico and experimental gene essentiality faster than previous approaches. Against an independent test set of more than 300 essential/non-essential genes that were not used to train the model, the model displays 93% sensitivity and specificity. We also used the model to simulate the biochemical genetics experiments originally performed on Neurospora by comprehensively predicting nutrient rescue of essential genes and synthetic lethal interactions, and we provide detailed pathway-based mechanistic explanations of our predictions. Our model provides a reliable computational framework for the integration and interpretation of ongoing experimental efforts in Neurospora, and we anticipate that our methods will substantially reduce the manual effort required to develop high-quality genome-scale metabolic models for other organisms.     

Functional Knowledge Transfer for High-accuracy Prediction of Under-studied Biological Processes

A key challenge in genetics is identifying the functional roles of genes in pathways. Numerous functional genomics techniques (e.g. machine learning) that predict protein function have been developed to address this question. These methods generally build from existing annotations of genes to pathways and thus are often unable to identify additional genes participating in processes that are not already well studied. Many of these processes are well studied in some organism, but not necessarily in an investigator''s organism of interest. Sequence-based search methods (e.g. BLAST) have been used to transfer such annotation information between organisms. We demonstrate that functional genomics can complement traditional sequence similarity to improve the transfer of gene annotations between organisms. Our method transfers annotations only when functionally appropriate as determined by genomic data and can be used with any prediction algorithm to combine transferred gene function knowledge with organism-specific high-throughput data to enable accurate function prediction.We show that diverse state-of-art machine learning algorithms leveraging functional knowledge transfer (FKT) dramatically improve their accuracy in predicting gene-pathway membership, particularly for processes with little experimental knowledge in an organism. We also show that our method compares favorably to annotation transfer by sequence similarity. Next, we deploy FKT with state-of-the-art SVM classifier to predict novel genes to 11,000 biological processes across six diverse organisms and expand the coverage of accurate function predictions to processes that are often ignored because of a dearth of annotated genes in an organism. Finally, we perform in vivo experimental investigation in Danio rerio and confirm the regulatory role of our top predicted novel gene, wnt5b, in leftward cell migration during heart development. FKT is immediately applicable to many bioinformatics techniques and will help biologists systematically integrate prior knowledge from diverse systems to direct targeted experiments in their organism of study.     

Genome –Scale Reconstruction of Metabolic Networks of Lactobacillus casei ATCC 334 and 12A

Lactobacillus casei strains are widely used in industry and the utility of this organism in these industrial applications is strain dependent. Hence, tools capable of predicting strain specific phenotypes would have utility in the selection of strains for specific industrial processes. Genome-scale metabolic models can be utilized to better understand genotype-phenotype relationships and to compare different organisms. To assist in the selection and development of strains with enhanced industrial utility, genome-scale models for L. casei ATCC 334, a well characterized strain, and strain 12A, a corn silage isolate, were constructed. Draft models were generated from RAST genome annotations using the Model SEED database and refined by evaluating ATP generating cycles, mass-and-charge-balances of reactions, and growth phenotypes. After the validation process was finished, we compared the metabolic networks of these two strains to identify metabolic, genetic and ortholog differences that may lead to different phenotypic behaviors. We conclude that the metabolic capabilities of the two networks are highly similar. The L. casei ATCC 334 model accounts for 1,040 reactions, 959 metabolites and 548 genes, while the L. casei 12A model accounts for 1,076 reactions, 979 metabolites and 640 genes. The developed L. casei ATCC 334 and 12A metabolic models will enable better understanding of the physiology of these organisms and be valuable tools in the development and selection of strains with enhanced utility in a variety of industrial applications.     

Broad Distribution of TPI-GAPDH Fusion Proteins among Eukaryotes: Evidence for Glycolytic Reactions in the Mitochondrion?

Glycolysis is a central metabolic pathway in eukaryotic and prokaryotic cells. In eukaryotes, the textbook view is that glycolysis occurs in the cytosol. However, fusion proteins comprised of two glycolytic enzymes, triosephosphate isomerase (TPI) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH), were found in members of the stramenopiles (diatoms and oomycetes) and shown to possess amino-terminal mitochondrial targeting signals. Here we show that mitochondrial TPI-GAPDH fusion protein genes are widely spread across the known diversity of stramenopiles, including non-photosynthetic species (Bicosoeca sp. and Blastocystis hominis). We also show that TPI-GAPDH fusion genes exist in three cercozoan taxa (Paulinella chromatophora, Thaumatomastix sp. and Mataza hastifera) and an apusozoan protist, Thecamonas trahens. Interestingly, subcellular localization predictions for other glycolytic enzymes in stramenopiles and a cercozoan show that a significant fraction of the glycolytic enzymes in these species have mitochondrial-targeted isoforms. These results suggest that part of the glycolytic pathway occurs inside mitochondria in these organisms, broadening our knowledge of the diversity of mitochondrial metabolism of protists.     

Shuffling of Promoters for Multiple Genes To Optimize Xylose Fermentation in an Engineered Saccharomyces cerevisiae Strain

We describe here a useful metabolic engineering tool, multiple-gene-promoter shuffling (MGPS), to optimize expression levels for multiple genes. This method approaches an optimized gene overexpression level by fusing promoters of various strengths to genes of interest for a particular pathway. Selection of these promoters is based on the expression levels of the native genes under the same physiological conditions intended for the application. MGPS was implemented in a yeast xylose fermentation mixture by shuffling the promoters for GND2 and HXK2 with the genes for transaldolase (TAL1), transketolase (TKL1), and pyruvate kinase (PYK1) in the Saccharomyces cerevisiae strain FPL-YSX3. This host strain has integrated xylose-metabolizing genes, including xylose reductase, xylitol dehydrogenase, and xylulose kinase. The optimal expression levels for TAL1, TKL1, and PYK1 were identified by analysis of volumetric ethanol production by transformed cells. We found the optimal combination for ethanol production to be GND2-TAL1-HXK2-TKL1-HXK2-PYK1. The MGPS method could easily be adapted for other eukaryotic and prokaryotic organisms to optimize expression of genes for industrial fermentation.     

Use of Single-Point Genome Signature Tags as a Universal Tagging Method for Microbial Genome Surveys

We developed single-point genome signature tags (SP-GSTs), a generally applicable, high-throughput sequencing-based method that targets specific genes to generate identifier tags from well-defined points in a genome. The technique yields identifier tags that can distinguish between closely related bacterial strains and allow for the identification of microbial community members. SP-GSTs are determined by three parameters: (i) the primer designed to recognize a conserved gene sequence, (ii) the anchoring enzyme recognition sequence, and (iii) the type IIS restriction enzyme which defines the tag length. We evaluated the SP-GST method in silico for bacterial identification using the genes rpoC, uvrB, and recA and the 16S rRNA gene. The best distinguishing tags were obtained with the restriction enzyme Csp6I upstream of the 16S rRNA gene, which discriminated all organisms in our data set to at least the genus level and most organisms to the species level. The method was successfully used to generate Csp6I-based tags upstream of the 16S rRNA gene and allowed us to discriminate between closely related strains of Bacillus cereus and Bacillus anthracis. This concept was further used successfully to identify the individual members of a defined microbial community.     

Phylogeny of Microorganisms Populating a Thick, Subaerial, Predominantly Lithotrophic Biofilm at an Extreme Acid Mine Drainage Site

An unusually thick (~1 cm) slime developed on a slump of finely disseminated pyrite ore within an extreme acid mine drainage site at Iron Mountain, near Redding, Calif. The slime was studied over the period of 1 year. The subaerial form of the slime distinguished it from more typical submerged streamers. Phylogenetic analysis of 16S rRNA genes revealed a diversity of sequences that were mostly novel. Nearest relatives to the majority of sequences came from iron-oxidizing acidophiles, and it appears that iron oxidation is the predominant metabolic characteristic of the organisms in the slime. The most abundant of the 16S rRNA genes detected were from organisms related to Leptospirillum species. The dominant sequence (71% of clones) may represent a new genus. Sequences within the Archaea of the Thermoplasmales lineage were detected. Most of these were only distantly related to known microorganisms. Also, sequences affiliating with Acidimicrobium were detected. Some of these were closely related to “Ferromicrobium acidophilus,” and others were affiliated with a lineage only represented by environmental clones. Unexpectedly, sequences that affiliated within the delta subdivision of the Proteobacteria were detected. The predominant metabolic feature of bacteria of this subdivision is anaerobic sulfate or metal reduction. Thus, microenvironments of low redox potential possibly exist in the predominantly oxidizing environments of the slime. These results expand our knowledge of the biodiversity of acid mine drainage environments and extend our understanding of the ecology of extremely acidic systems.     

metaSHARK: software for automated metabolic network prediction from DNA sequence and its application to the genomes of Plasmodium falciparum and Eimeria tenella

The metabolic SearcH And Reconstruction Kit (metaSHARK) is a new fully automated software package for the detection of enzyme-encoding genes within unannotated genome data and their visualization in the context of the surrounding metabolic network. The gene detection package (SHARKhunt) runs on a Linux system and requires only a set of raw DNA sequences (genomic, expressed sequence tag and/or genome survey sequence) as input. Its output may be uploaded to our web-based visualization tool (SHARKview) for exploring and comparing data from different organisms. We first demonstrate the utility of the software by comparing its results for the raw Plasmodium falciparum genome with the manual annotations available at the PlasmoDB and PlasmoCyc websites. We then apply SHARKhunt to the unannotated genome sequences of the coccidian parasite Eimeria tenella and observe that, at an E-value cut-off of 10⁻²⁰, our software makes 142 additional assertions of enzymatic function compared with a recent annotation package working with translated open reading frame sequences. The ability of the software to cope with low levels of sequence coverage is investigated by analyzing assemblies of the E.tenella genome at estimated coverages from 0.5× to 7.5×. Lastly, as an example of how metaSHARK can be used to evaluate the genomic evidence for specific metabolic pathways, we present a study of coenzyme A biosynthesis in P.falciparum and E.tenella.     

Statistical analysis of pentose phosphate pathway genes from eubacteria and eukarya reveals translational selection as a major force in shaping codon usage pattern

Comparative analysis of metabolic pathways among widely diverse species provides an excellent opportunity to extract information about the functional relation of organisms and pentose phosphate pathway exemplifies one such pathway. A comparative codon usage analysis of the pentose phosphate pathway genes of a diverse group of organisms representing different niches and the related factors affecting codon usage with special reference to the major forces influencing codon usage patterns was carried out. It was observed that organism specific codon usage bias percolates into vital metabolic pathway genes irrespective of their near universality. A clear distinction in the codon usage pattern of gram positive and gram negative bacteria, which is a major classification criterion for bacteria, in terms of pentose phosphate pathway was an important observation of this study. The codon utilization scheme in all the organisms indicates the presence of translation selection as a major force in shaping codon usage. Another key observation was the segregation of the H. sapiens genes as a separate cluster by correspondence analysis, which is primarily attributed to the different codon usage pattern in this genus along with its longer gene lengths. We have also analyzed the amino acid distribution comparison of transketolase protein primary structures among all the organisms and found that there is a certain degree of predictability in the composition profile except in A. fumigatus and H. sapiens, where few exceptions are prominent. In A. fumigatus, a human pathogen responsible for invasive aspergillosis, a significantly different codon usage pattern, which finally translated into its amino acid composition model portraying a unique profile in a key pentose phosphate pathway enzyme transketolase was observed.     

The degree of redundancy in metabolic genes is linked to mode of metabolism

An understanding of the factors favoring the maintenance of duplicate genes in microbial genomes is essential for developing models of microbial evolution. A genome-scale flux-balance analysis of the metabolic network of Saccharomyces cerevisiae has suggested that gene duplications primarily provide increased enzyme dosage to enhance metabolic flux because the incidence of gene duplications in essential genes is no higher than that in nonessential genes. Here, we used genome-scale metabolic models to analyze the extent of genetic and biochemical redundancy in prokaryotes that are either specialists, with one major mode of energy generation, or generalists, which have multiple metabolic strategies for conservation of energy. Surprisingly, the results suggest that generalists, such as Escherichia coli and Bacillus subtilis, are similar to the eukaryotic generalist, S. cerevisiae, in having a low percentage (<10%) of essential genes and few duplications of these essential genes, whereas metabolic specialists, such as Geobacter sulfurreducens and Methanosarcina barkeri, have a high percentage (>30%) of essential genes and a high degree of genetic redundancy in these genes compared to nonessential genes. Furthermore, the specialist organisms appear to rely more on gene duplications rather than alternative-but-equivalent metabolic pathways to provide resilience to gene loss. Generalists rely more on alternative pathways. Thus, the concept that the role of gene duplications is to boost enzymatic flux rather than provide metabolic resilience may not be universal. Rather, the degree of gene duplication in microorganisms may be linked to mode of metabolism and environmental niche.     

Expression of Aeromonas caviae ST pyruvate dehydrogenase complex components mediate tellurite resistance in Escherichia coli

Potassium tellurite (K₂TeO₃) is harmful to most organisms and specific mechanisms explaining its toxicity are not well known to date. We previously reported that the lpdA gene product of the tellurite-resistant environmental isolate Aeromonas caviae ST is involved in the reduction of tellurite to elemental tellurium. In this work, we show that expression of A. caviae ST aceE, aceF, and lpdA genes, encoding pyruvate dehydrogenase, dihydrolipoamide transacetylase, and dihydrolipoamide dehydrogenase, respectively, results in tellurite resistance and decreased levels of tellurite-induced superoxide in Escherichia coli. In addition to oxidative damage resulting from tellurite exposure, a metabolic disorder would be simultaneously established in which the pyruvate dehydrogenase complex would represent an intracellular tellurite target. These results allow us to widen our vision regarding the molecular mechanisms involved in bacterial tellurite resistance by correlating tellurite toxicity and key enzymes of aerobic metabolism.     

Identifying evolutionarily conserved genes in the dietary restriction response using bioinformatics and subsequent testing in Caenorhabditis elegans

Dietary restriction (DR) increases life span, health span and resistance to stress in a wide range of organisms. Work from a large number of laboratories has revealed evolutionarily conserved mechanisms that mediate the DR response. Here, we analyzed the genome-wide gene expression profiles of Caenorhabditis elegans under DR versus ad libitum conditions. Using the Ortho2ExpressMatrix tool, we searched for C. elegans orthologs of mouse genes that have been shown to be differentially expressed under DR conditions in nearly 600 experiments. Based on our bioinformatic approaches, we obtained 189 DR-responsive genes, and 45 of these are highly conserved from worm to man. Subsequent testing of sixteen genes that are up-regulated under DR identified eight genes that abolish the DR-induced resistance to heat stress in C. elegans. Further analyses revealed that fkb-4, dod-22 and ikb-1 genes also abolish increased life span in response to DR. The identified genes that are necessary for the DR response are sensitive to certain stress signals such as metabolic perturbances (dod-22, fkb-4 and nhr-85), DNA damage (ikb-1), heat shock (hsp-12.6) and cancer-like overgrowth (prk-2 and tsp-15). We propose that most of the DR-responsive genes identified are components of the recently discovered cellular surveillance-activated detoxification and defenses pathway, which is, among others, important for the survival of organisms in times of food deprivation.

Electronic supplementary material

The online version of this article (doi:10.1007/s12263-013-0363-5) contains supplementary material, which is available to authorized users.     

Differential Requirement for Pten Lipid and Protein Phosphatase Activity during Zebrafish Embryonic Development

The lipid- and protein phosphatase PTEN is one of the most frequently mutated tumor suppressor genes in human cancers and many mutations found in tumor samples directly affect PTEN phosphatase activity. In order to understand the functional consequences of these mutations in vivo, the aim of our study was to dissect the role of Pten phosphatase activities during zebrafish embryonic development. As in other model organisms, zebrafish mutants lacking functional Pten are embryonically lethal. Zebrafish have two pten genes and pten double homozygous zebrafish embryos develop a severe pleiotropic phenotype around 4 days post fertilization, which can be largely rescued by re-introduction of pten mRNA at the one-cell stage. We used this assay to characterize the rescue-capacity of Pten and variants with mutations that disrupt lipid, protein or both phosphatase activities. The pleiotropic phenotype at 4dpf could only be rescued by wild type Pten, indicating that both phosphatase activities are required for normal zebrafish embryonic development. An earlier aspect of the phenotype, hyperbranching of intersegmental vessels, however, was rescued by Pten that retained lipid phosphatase activity, independent of protein phosphatase activity. Lipid phosphatase activity was also required for moderating pAkt levels at 4 dpf. We propose that the role of Pten during angiogenesis mainly consists of suppressing PI3K signaling via its lipid phosphatase activity, whereas the complex process of embryonic development requires lipid and protein phosphatase of Pten.