115 research outputs found
Protein secretion systems in bacterial-host associations, and their description in the Gene Ontology
Protein secretion plays a central role in modulating the interactions of bacteria with their environments. This is particularly the case when symbiotic bacteria (whether pathogenic, commensal or mutualistic) are interacting with larger host organisms. In the case of Gram-negative bacteria, secretion requires translocation across the outer as well as the inner membrane, and a diversity of molecular machines have been elaborated for this purpose. A number of secreted proteins are destined to enter the host cell (effectors and toxins), and thus several secretion systems include apparatus to translocate proteins across the plasma membrane of the host also. The Plant-Associated Microbe Gene Ontology (PAMGO) Consortium has been developing standardized terms for describing biological processes and cellular components that play important roles in the interactions of microbes with plant and animal hosts, including the processes of bacterial secretion. Here we survey bacterial secretion systems known to modulate interactions with host organisms and describe Gene Ontology terms useful for describing the components and functions of these systems, and for capturing the similarities among the diverse systems
MARVEL, a Tool for Prediction of Bacteriophage Sequences in Metagenomic Bins
Here we present MARVEL, a tool for prediction of double-stranded DNA bacteriophage sequences in metagenomic bins. MARVEL uses a random forest machine learning approach. We trained the program on a dataset with 1,247 phage and 1,029 bacterial genomes, and tested it on a dataset with 335 bacterial and 177 phage genomes. We show that three simple genomic features extracted from contig sequences were sufficient to achieve a good performance in separating bacterial from phage sequences: gene density, strand shifts, and fraction of significant hits to a viral protein database. We compared the performance of MARVEL to that of VirSorter and VirFinder, two popular programs for predicting viral sequences. Our results show that all three programs have comparable specificity, but MARVEL achieves much better performance on the recall (sensitivity) measure. This means that MARVEL should be able to identify many more phage sequences in metagenomic bins than heretofore has been possible. In a simple test with real data, containing mostly bacterial sequences, MARVEL classified 58 out of 209 bins as phage genomes; other evidence suggests that 57 of these 58 bins are novel phage sequences. MARVEL is freely available at https://github.com/LaboratorioBioinformatica/MARVEL
Sequence verification of synthetic DNA by assembly of sequencing reads
Gene synthesis attempts to assemble user-defined DNA sequences with base-level precision. Verifying the sequences of construction intermediates and the final product of a gene synthesis project is a critical part of the workflow, yet one that has received the least attention. Sequence validation is equally important for other kinds of curated clone collections. Ensuring that the physical sequence of a clone matches its published sequence is a common quality control step performed at least once over the course of a research project. GenoREAD is a web-based application that breaks the sequence verification process into two steps: the assembly of sequencing reads and the alignment of the resulting contig with a reference sequence. GenoREAD can determine if a clone matches its reference sequence. Its sophisticated reporting features help identify and troubleshoot problems that arise during the sequence verification process. GenoREAD has been experimentally validated on thousands of gene-sized constructs from an ORFeome project, and on longer sequences including whole plasmids and synthetic chromosomes. Comparing GenoREAD results with those from manual analysis of the sequencing data demonstrates that GenoREAD tends to be conservative in its diagnostic. GenoREAD is available at www.genoread.or
Dynamic expression of Ralstonia solanacearum virulence factors and metabolism-controlling genes during plant infection
Altres ajuts: CERCA Programme/Generalitat de Catalunya. P. Sebastià received the support of a fellowship (code is LCF/BQ/IN17/11620004) from la Caixa Foundation (identifier [ID] 100010434)Background: Ralstonia solanacearum is the causal agent of bacterial wilt, a devastating plant disease responsible for serious economic losses especially on potato, tomato, and other solanaceous plant species in temperate countries. In R. solanacearum, gene expression analysis has been key to unravel many virulence determinants as well as their regulatory networks. However, most of these assays have been performed using either bacteria grown in minimal medium or in planta, after symptom onset, which occurs at late stages of colonization. Thus, little is known about the genetic program that coordinates virulence gene expression and metabolic adaptation along the different stages of plant infection by R. solanacearum. Results: We performed an RNA-sequencing analysis of the transcriptome of bacteria recovered from potato apoplast and from the xylem of asymptomatic or wilted potato plants, which correspond to three different conditions (Apoplast, Early and Late xylem). Our results show dynamic expression of metabolism-controlling genes and virulence factors during parasitic growth inside the plant. Flagellar motility genes were especially up-regulated in the apoplast and twitching motility genes showed a more sustained expression in planta regardless of the condition. Xylem-induced genes included virulence genes, such as the type III secretion system (T3SS) and most of its related effectors and nitrogen utilisation genes. The upstream regulators of the T3SS were exclusively up-regulated in the apoplast, preceding the induction of their downstream targets. Finally, a large subset of genes involved in central metabolism was exclusively down-regulated in the xylem at late infection stages. Conclusions: This is the first report describing R. solanacearum dynamic transcriptional changes within the plant during infection. Our data define four main genetic programmes that define gene pathogen physiology during plant colonisation. The described expression of virulence genes, which might reflect bacterial states in different infection stages, provides key information on the R. solanacearum potato infection process
A Versatile Computational Pipeline for Bacterial Genome Annotation Improvement and Comparative Analysis, with \u3cem\u3eBrucella\u3c/em\u3e as a Use Case
We present a bacterial genome computational analysis pipeline, called GenVar. The pipeline, based on the program GeneWise, is designed to analyze an annotated genome and automatically identify missed gene calls and sequence variants such as genes with disrupted reading frames (split genes) and those with insertions and deletions (indels). For a given genome to be analyzed, GenVar relies on a database containing closely related genomes (such as other species or strains) as well as a few additional reference genomes. GenVar also helps identify gene disruptions probably caused by sequencing errors. We exemplify GenVar’s capabilities by presenting results from the analysis of four Brucella genomes. Brucella is an important human pathogen and zoonotic agent. The analysis revealed hundreds of missed gene calls, new split genes and indels, several of which are species specific and hence provide valuable clues to the understanding of the genome basis of Brucella pathogenicity and host specificity
Identification and analysis of seven effector protein families with different adaptive and evolutionary histories in plant-associated members of the Xanthomonadaceae.
The Xanthomonadaceae family consists of species of non-pathogenic and pathogenic γ-proteobacteria that infect different hosts, including humans and plants. In this study, we performed a comparative analysis using 69 fully sequenced genomes belonging to this family, with a focus on identifying proteins enriched in phytopathogens that could explain the lifestyle and the ability to infect plants. Using a computational approach, we identified seven phytopathogen-enriched protein families putatively secreted by type II secretory system: PheA (CM-sec), LipA/LesA, VirK, and four families involved in N-glycan degradation, NixE, NixF, NixL, and FucA1. In silico and phylogenetic analyses of these protein families revealed they all have orthologs in other phytopathogenic or symbiotic bacteria, and are involved in the modulation and evasion of the immune system. As a proof of concept, we performed a biochemical characterization of LipA from Xac306 and verified that the mutant strain lost most of its lipase and esterase activities and displayed reduced virulence in citrus. Since this study includes closely related organisms with distinct lifestyles and highlights proteins directly related to adaptation inside plant tissues, novel approaches might use these proteins as biotechnological targets for disease control, and contribute to our understanding of the coevolution of plant-associated bacteria
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Genetic resources for methane production from biomass described with the Gene Ontology
Methane (CH₄) is a valuable fuel, constituting 70–95% of natural gas, and a potent
greenhouse gas. Release of CH₄ into the atmosphere contributes to climate change.
Biological CH₄ production or methanogenesis is mostly performed by methanogens, a
group of strictly anaerobic archaea. The direct substrates for methanogenesis are H₂
plus CO₂, acetate, formate, methylamines, methanol, methyl sulfides, and ethanol or a
secondary alcohol plus CO₂. In numerous anaerobic niches in nature, methanogenesis
facilitates mineralization of complex biopolymers such as carbohydrates, lipids and
proteins generated by primary producers. Thus, methanogens are critical players in the
global carbon cycle. The same process is used in anaerobic treatment of municipal,
industrial and agricultural wastes, reducing the biological pollutants in the wastes and
generating methane. It also holds potential for commercial production of natural gas
from renewable resources. This process operates in digestive systems of many animals,
including cattle, and humans. In contrast, in deep-sea hydrothermal vents methanogenesis
is a primary production process, allowing chemosynthesis of biomaterials from H₂ plus
CO₂. In this report we present Gene Ontology (GO) terms that can be used to describe
processes, functions and cellular components involved in methanogenic biodegradation
and biosynthesis of specialized coenzymes that methanogens use. Some of these GO
terms were previously available and the rest were generated in our Microbial Energy
Gene Ontology (MENGO) project. A recently discovered non-canonical CH₄ production
process is also described. We have performed manual GO annotation of selected
methanogenesis genes, based on experimental evidence, providing “gold standards” for
machine annotation and automated discovery of methanogenesis genes or systems in
diverse genomes. Most of the GO-related information presented in this report is available
at the MENGO website (http://www.mengo.biochem.vt.edu/).This is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by the Frontiers Research Foundation. The published article can be found at: http://www.frontiersin.org/Microbiology.Keywords: Carbon cycle, Gene Ontology, Bioenergy, Methanogen, Biodegradation, Waste treatment, Biomass, MethanogenesisKeywords: Carbon cycle, Gene Ontology, Bioenergy, Methanogen, Biodegradation, Waste treatment, Biomass, Methanogenesi
Next-Generation Phage Display: Integrating and Comparing Available Molecular Tools to Enable Cost-Effective High-Throughput Analysis
Background: Combinatorial phage display has been used in the last 20 years in the identification of protein-ligands and protein-protein interactions, uncovering relevant molecular recognition events. Rate-limiting steps of combinatorial phage display library selection are (i) the counting of transducing units and (ii) the sequencing of the encoded displayed ligands. Here, we adapted emerging genomic technologies to minimize such challenges. Methodology/Principal Findings: We gained efficiency by applying in tandem real-time PCR for rapid quantification to enable bacteria-free phage display library screening, and added phage DNA next-generation sequencing for large-scale ligand analysis, reporting a fully integrated set of high-throughput quantitative and analytical tools. The approach is far less labor-intensive and allows rigorous quantification; for medical applications, including selections in patients, it also represents an advance for quantitative distribution analysis and ligand identification of hundreds of thousands of targeted particles from patient-derived biopsy or autopsy in a longer timeframe post library administration. Additional advantages over current methods include increased sensitivity, less variability, enhanced linearity, scalability, and accuracy at much lower cost. Sequences obtained by qPhage plus pyrosequencing were similar to a dataset produced from conventional Sanger-sequenced transducing-units (TU), with no biases due to GC content, codon usage, and amino acid or peptide frequency. These tools allow phage display selection and ligand analysis at.1,000-fold faster rate, and reduce costs,250fol
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Genetic resources for advanced biofuel production described with the Gene Ontology
Dramatic increases in research in the area of microbial biofuel production coupled with
high-throughput data generation on bioenergy-related microbes has led to a deluge of
information in the scientific literature and in databases. Consolidating this information and
making it easily accessible requires a unified vocabulary. The Gene Ontology (GO) fulfills that
requirement, as it is a well-developed structured vocabulary that describes the activities
and locations of gene products in a consistent manner across all kingdoms of life. The
Microbial ENergy processes Gene Ontology (http://www.mengo.biochem.vt.edu) project
is extending the GO to include new terms to describe microbial processes of interest
to bioenergy production. Our effort has added over 600 bioenergy related terms to the
Gene Ontology. These terms will aid in the comprehensive annotation of gene products
from diverse energy-related microbial genomes. An area of microbial energy research
that has received a lot of attention is microbial production of advanced biofuels. These
include alcohols such as butanol, isopropanol, isobutanol, and fuels derived from fatty
acids, isoprenoids, and polyhydroxyalkanoates. These fuels are superior to first generation
biofuels (ethanol and biodiesel esterified from vegetable oil or animal fat), can be generated
from non-food feedstock sources, can be used as supplements or substitutes for gasoline,
diesel and jet fuels, and can be stored and distributed using existing infrastructure. Here
we review the roles of genes associated with synthesis of advanced biofuels, and at the
same time introduce the use of the GO to describe the functions of these genes in a
standardized way.This is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by the Frontiers Research Foundation. The published article can be found at: http://www.frontiersin.org/Microbiology. Supplementary Material can be found at: http://www.frontiersin.org/journal/10.3389/fmicb.2014.00528/.Keywords: Gene Ontology, Advanced biofuels, Synthetic biology, Fatty acid-derived fuel, Advanced alcohols, Cellulosome, Isoprenoid-derived fue
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Sequence verification of synthetic DNA by assembly of sequencing reads
Gene synthesis attempts to assemble user-defined DNA sequences with base-level precision. Verifying the sequences of construction intermediates and the final product of a gene synthesis project is a critical part of the workflow, yet one that has received the least attention. Sequence validation is equally important for other kinds of curated clone collections. Ensuring that the physical sequence of a clone matches its published sequence is a common quality control step performed at least once over the course of a research project. GenoREAD is a web-based application that breaks the sequence verification process into two steps: the assembly of sequencing reads and the alignment of the resulting contig with a reference sequence. GenoREAD can determine if a clone matches its reference sequence. Its sophisticated reporting features help identify and troubleshoot problems that arise during the sequence verification process. GenoREAD has been experimentally validated on thousands of gene-sized constructs from an ORFeome project, and on longer sequences including whole plasmids and synthetic chromosomes. Comparing GenoREAD results with those from manual analysis of the sequencing data demonstrates that GenoREAD tends to be conservative in its diagnostic. GenoREAD is available at www.genoread.org.This is the publisher’s final pdf. The published article is copyrighted by Oxford University Press and can be found at: http://www.oxfordjournals.org/Keywords: Bioinformatics, Gene synthesis, Genome, Retrieval, Biology, Alignmen
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