1,115 research outputs found
The genetic basis of energy conservation in the sulfate-reducing bacterium Desulfovibrio alaskensis G20.
Sulfate-reducing bacteria play major roles in the global carbon and sulfur cycles, but it remains unclear how reducing sulfate yields energy. To determine the genetic basis of energy conservation, we measured the fitness of thousands of pooled mutants of Desulfovibrio alaskensis G20 during growth in 12 different combinations of electron donors and acceptors. We show that ion pumping by the ferredoxin:NADH oxidoreductase Rnf is required whenever substrate-level phosphorylation is not possible. The uncharacterized complex Hdr/flox-1 (Dde_1207:13) is sometimes important alongside Rnf and may perform an electron bifurcation to generate more reduced ferredoxin from NADH to allow further ion pumping. Similarly, during the oxidation of malate or fumarate, the electron-bifurcating transhydrogenase NfnAB-2 (Dde_1250:1) is important and may generate reduced ferredoxin to allow additional ion pumping by Rnf. During formate oxidation, the periplasmic [NiFeSe] hydrogenase HysAB is required, which suggests that hydrogen forms in the periplasm, diffuses to the cytoplasm, and is used to reduce ferredoxin, thus providing a substrate for Rnf. During hydrogen utilization, the transmembrane electron transport complex Tmc is important and may move electrons from the periplasm into the cytoplasmic sulfite reduction pathway. Finally, mutants of many other putative electron carriers have no clear phenotype, which suggests that they are not important under our growth conditions, although we cannot rule out genetic redundancy
FastTree 2 – Approximately Maximum-Likelihood Trees for Large Alignments
Background: We recently described FastTree, a tool for inferring phylogenies for alignments with up to hundreds of thousands of sequences. Here, we describe improvements to FastTree that improve its accuracy without sacrificing scalability. Methodology/Principal Findings: Where FastTree 1 used nearest-neighbor interchanges (NNIs) and the minimum-evolution criterion to improve the tree, FastTree 2 adds minimum-evolution subtree-pruning-regrafting (SPRs) and maximumlikelihood NNIs. FastTree 2 uses heuristics to restrict the search for better trees and estimates a rate of evolution for each site (the ‘‘CAT’ ’ approximation). Nevertheless, for both simulated and genuine alignments, FastTree 2 is slightly more accurate than a standard implementation of maximum-likelihood NNIs (PhyML 3 with default settings). Although FastTree 2 is not quite as accurate as methods that use maximum-likelihood SPRs, most of the splits that disagree are poorly supported, and for large alignments, FastTree 2 is 100–1,000 times faster. FastTree 2 inferred a topology and likelihood-based local support values for 237,882 distinct 16S ribosomal RNAs on a desktop computer in 22 hours and 5.8 gigabytes of memory. Conclusions/Significance: FastTree 2 allows the inference of maximum-likelihood phylogenies for huge alignments
Horizontal gene transfer and the evolution of transcriptional regulation in Escherichia coli
Most Escherichia coli transcription factors have paralogs, but these usually arose by horizontal gene transfer rather than by duplication within the E. coli lineage, as previously believed
OpWise: Operons aid the identification of differentially expressed genes in bacterial microarray experiments
BACKGROUND: Differentially expressed genes are typically identified by analyzing the variation between replicate measurements. These procedures implicitly assume that there are no systematic errors in the data even though several sources of systematic error are known. RESULTS: OpWise estimates the amount of systematic error in bacterial microarray data by assuming that genes in the same operon have matching expression patterns. OpWise then performs a Bayesian analysis of a linear model to estimate significance. In simulations, OpWise corrects for systematic error and is robust to deviations from its assumptions. In several bacterial data sets, significant amounts of systematic error are present, and replicate-based approaches overstate the confidence of the changers dramatically, while OpWise does not. Finally, OpWise can identify additional changers by assigning genes higher confidence if they are consistent with other genes in the same operon. CONCLUSION: Although microarray data can contain large amounts of systematic error, operons provide an external standard and allow for reasonable estimates of significance. OpWise is available at
Orthologous Transcription Factors in Bacteria Have Different Functions and Regulate Different Genes
Transcription factors (TFs) form large paralogous gene families and have complex evolutionary histories. Here, we ask whether putative orthologs of TFs, from bidirectional best BLAST hits (BBHs), are evolutionary orthologs with conserved functions. We show that BBHs of TFs from distantly related bacteria are usually not evolutionary orthologs. Furthermore, the false orthologs usually respond to different signals and regulate distinct pathways, while the few BBHs that are evolutionary orthologs do have conserved functions. To test the conservation of regulatory interactions, we analyze expression patterns. We find that regulatory relationships between TFs and their regulated genes are usually not conserved for BBHs in Escherichia coli K12 and Bacillus subtilis. Even in the much more closely related bacteria Vibrio cholerae and Shewanella oneidensis MR-1, predicting regulation from E. coli BBHs has high error rates. Using gene–regulon correlations, we identify genes whose expression pattern differs between E. coli and S. oneidensis. Using literature searches and sequence analysis, we show that these changes in expression patterns reflect changes in gene regulation, even for evolutionary orthologs. We conclude that the evolution of bacterial regulation should be analyzed with phylogenetic trees, rather than BBHs, and that bacterial regulatory networks evolve more rapidly than previously thought
Functional genomics with a comprehensive library of transposon mutants for the sulfate-reducing bacterium Desulfovibrio alaskensis G20.
UnlabelledThe genomes of sulfate-reducing bacteria remain poorly characterized, largely due to a paucity of experimental data and genetic tools. To meet this challenge, we generated an archived library of 15,477 mapped transposon insertion mutants in the sulfate-reducing bacterium Desulfovibrio alaskensis G20. To demonstrate the utility of the individual mutants, we profiled gene expression in mutants of six regulatory genes and used these data, together with 1,313 high-confidence transcription start sites identified by tiling microarrays and transcriptome sequencing (5' RNA-Seq), to update the regulons of Fur and Rex and to confirm the predicted regulons of LysX, PhnF, PerR, and Dde_3000, a histidine kinase. In addition to enabling single mutant investigations, the D. alaskensis G20 transposon mutants also contain DNA bar codes, which enables the pooling and analysis of mutant fitness for thousands of strains simultaneously. Using two pools of mutants that represent insertions in 2,369 unique protein-coding genes, we demonstrate that the hypothetical gene Dde_3007 is required for methionine biosynthesis. Using comparative genomics, we propose that Dde_3007 performs a missing step in methionine biosynthesis by transferring a sulfur group to O-phosphohomoserine to form homocysteine. Additionally, we show that the entire choline utilization cluster is important for fitness in choline sulfate medium, which confirms that a functional microcompartment is required for choline oxidation. Finally, we demonstrate that Dde_3291, a MerR-like transcription factor, is a choline-dependent activator of the choline utilization cluster. Taken together, our data set and genetic resources provide a foundation for systems-level investigation of a poorly studied group of bacteria of environmental and industrial importance.ImportanceSulfate-reducing bacteria contribute to global nutrient cycles and are a nuisance for the petroleum industry. Despite their environmental and industrial significance, the genomes of sulfate-reducing bacteria remain poorly characterized. Here, we describe a genetic approach to fill gaps in our knowledge of sulfate-reducing bacteria. We generated a large collection of archived, transposon mutants in Desulfovibrio alaskensis G20 and used the phenotypes of these mutant strains to infer the function of genes involved in gene regulation, methionine biosynthesis, and choline utilization. Our findings and mutant resources will enable systematic investigations into gene function, energy generation, stress response, and metabolism for this important group of bacteria
A novel method for accurate operon predictions in all sequenced prokaryotes
We combine comparative genomic measures and the distance separating adjacent genes to predict operons in 124 completely sequenced prokaryotic genomes. Our method automatically tailors itself to each genome using sequence information alone, and thus can be applied to any prokaryote. For Escherichia coli K12 and Bacillus subtilis, our method is 85 and 83% accurate, respectively, which is similar to the accuracy of methods that use the same features but are trained on experimentally characterized transcripts. In Halobacterium NRC-1 and in Helicobacter pylori, our method correctly infers that genes in operons are separated by shorter distances than they are in E.coli, and its predictions using distance alone are more accurate than distance-only predictions trained on a database of E.coli transcripts. We use microarray data from six phylogenetically diverse prokaryotes to show that combining intergenic distance with comparative genomic measures further improves accuracy and that our method is broadly effective. Finally, we survey operon structure across 124 genomes, and find several surprises: H.pylori has many operons, contrary to previous reports; Bacillus anthracis has an unusual number of pseudogenes within conserved operons; and Synechocystis PCC 6803 has many operons even though it has unusually wide spacings between conserved adjacent genes
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