Theoretical prediction and experimental verification of protein-coding genes in plant pathogen genome Agrobacterium tumefaciens strain C58

NAD(P)H-dependent thioredoxin-disulfide reductase TrxR is essential for tellurite and selenite reduction and resistance in Bacillus sp. Y3

Microbial reduction of selenite [Se(IV)] and tellurite [Te(IV)] to Se(0) and Te(0) can function as a detoxification mechanism and serve in energy conservation. In this study, Bacillus sp. Y3 was isolated and demonstrated to have an ability of simultaneous reduction of Se(IV) and Te(IV) during aerobic cultivation, with reduction efficiencies of 100% and 90%, respectively. Proteomics analysis revealed that the putative thioredoxin disulfide reductase (TrxR) and sulfate and energy metabolic pathway proteins were significantly upregulated after the addition of Se(IV) and Te(IV). qRT-PCR also showed an increased trxR transcription level in the presence of Se(IV) and Te(IV). Compared with a wild-type Escherichia coli strain, the TrxR-overexpressed E. coli strain showed higher Se(IV) and Te(IV) resistance levels and reduction efficiencies. Additionally, the TrxR showed in vitro Se(IV) and Te(IV) reduction activities when NADPH or NADH were present. When NADPH was used as the electron donor, the optimum conditions for enzyme activities were pH 8.0 and 37°C. The Km values of Te(IV) and Se(IV) were 16.31 and 2.91 mM, and the Vmax values of Te(IV) and Se(IV) were 12.23 and 11.20 µM min-1 mg-1, respectively. The discovery of the new reductive enzyme TrxR enriches the repertoire of the bacterial Se(IV) and Te(IV) resistance and reduction mechanisms. Bacillus sp. Y3 can efficiently reduce Se(IV) and Te(IV) simultaneously. Strain Y3 provides potential applications for selenite and tellurite bioremediation. The TrxR enzyme shows high catalytic activity for reducing Se(IV) and Te(IV). The discovery of TrxR enriches the bacterial Se(IV) and Te(IV) reduction mechanisms.

Balrog: A universal protein model for prokaryotic gene prediction

Low-cost, high-throughput sequencing has led to an enormous increase in the number of sequenced microbial genomes, with well over 100,000 genomes in public archives today. Automatic genome annotation tools are integral to understanding these organisms, yet older gene finding methods must be retrained on each new genome. We have developed a universal model of prokaryotic genes by fitting a temporal convolutional network to amino-acid sequences from a large, diverse set of microbial genomes. We incorporated the new model into a gene finding system, Balrog (Bacterial Annotation by Learned Representation Of Genes), which does not require genome-specific training and which matches or outperforms other state-of-the-art gene finding tools. Balrog is freely available under the MIT license at https://github.com/salzberg-lab/Balrog.

Annotating the protein-coding genes in a newly sequenced prokaryotic genome is a critical part of describing their biological function. Relative to eukaryotic genomes, prokaryotic genomes are small and structurally simple, with 90% of their DNA typically devoted to protein-coding genes. Current computational gene finding tools are therefore able to achieve close to 99% sensitivity to known genes using species-specific gene models. Though highly sensitive at finding known genes, all current prokaryotic gene finders also predict large numbers of additional genes, which are labelled as “hypothetical protein” in GenBank and other annotation databases. Many hypothetical gene predictions likely represent true protein-coding sequence, but it is not known how many of them represent false positives. Additionally, all current gene finding tools must be trained specifically for each genome as a preliminary step in order to achieve high sensitivity. This requirement limits their ability to detect genes in fragmented sequences commonly seen in metagenomic samples. We took a data-driven approach to prokaryotic gene finding, relying on the large and diverse collection of already-sequenced genomes. By training a single, universal model of bacterial genes on protein sequences from many different species, we were able to match the sensitivity of current gene finders while reducing the overall number of gene predictions. Our model does not need to be refit on any new genome. Balrog (Bacterial Annotation by Learned Representation of Genes) represents a fundamentally different yet effective method for prokaryotic gene finding.

Integrated Metabolomics and Targeted Gene Transcription Analysis Reveal Global Bacterial Antimonite Resistance Mechanisms

Antimony (Sb)-resistant bacteria have potential applications in the remediation of Sb-contaminated sites. However, the effect of Sb(III) exposure on whole-cell metabolic change has not been studied. Herein, we combined untargeted metabolomics with a previous proteomics dataset and confirmatory gene transcription analysis to identify metabolic responses to Sb(III) exposure in Agrobacterium tumefaciens GW4. Dynamic changes in metabolism between control and Sb(III)-exposed groups were clearly shown. KEGG pathway analysis suggested that with Sb(III) exposure: (1) the branching pathway of gluconeogenesis is down-regulated, resulting in the up-regulation of pentose phosphate pathway to provide precursors of anabolism and NADPH; (2) glycerophospholipid and arachidonic acid metabolisms are down-regulated, resulting in more acetyl-CoA entry into the TCA cycle and increased capacity to produce energy and macromolecular synthesis; (3) nucleotide and fatty acid synthesis pathways are all increased perhaps to protect cells from DNA and lipid peroxidation; (4) nicotinate metabolism increases which likely leads to increased production of co-enzymes (e.g., NAD⁺ and NADP⁺) for the maintenance of cellular redox and Sb(III) oxidation. Expectedly, the total NADP⁺/NADPH content, total glutathione, and reduced glutathione contents were all increased after Sb(III) exposure in strain GW4, which contribute to maintaining the reduced state of the cytoplasm. Our results provide novel information regarding global bacterial responses to Sb(III) exposure from a single gene level to the entire metabolome and provide specific hypotheses regarding the metabolic change to be addressed in future research.

Anaerobic Bacterial Immobilization and Removal of Toxic Sb(III) Coupled With Fe(II)/Sb(III) Oxidation and Denitrification

Antimony (Sb) pollution is a worldwide problem. In some anoxic sites, such as Sb mine drainage and groundwater sediment, the Sb concentration is extremely elevated. Therefore, effective Sb remediation strategies are urgently needed. In contrast to microbial aerobic antimonite [Sb(III)] oxidation, the mechanism of microbial anaerobic Sb(III) oxidation and the effects of nitrate and Fe(II) on the fate of Sb remain unknown. In this study, we discovered the mechanism of anaerobic Sb(III) oxidation coupled with Fe(II) oxidation and denitrification in the facultative anaerobic Sb(III) oxidizer Sinorhizobium sp. GW3. We observed the following: (1) under anoxic conditions with nitrate as the electron acceptor, strain GW3 was able to oxidize both Fe(II) and Sb(III) during cultivation; (2) in the presence of Fe(II), nitrate and Sb(III), the anaerobic Sb(III) oxidation rate was remarkably enhanced, and Fe(III)-containing minerals were produced during Fe(II) and Sb(III) oxidation; (3) qRT-PCR, gene knock-out and complementation analyses indicated that the arsenite oxidase gene product AioA plays an important role in anaerobic Sb(III) oxidation, in contrast to aerobic Sb(III) oxidation; and (4) energy-dispersive X-ray spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS) and powder X-ray diffraction (XRD) analyses revealed that the microbially produced Fe(III) minerals were an effective chemical oxidant responsible for abiotic anaerobic Sb(III) oxidation, and the generated Sb(V) was adsorbed or coprecipitated on the Fe(III) minerals. This process included biotic and abiotic factors, which efficiently immobilize and remove soluble Sb(III) under anoxic conditions. The findings revealed a significantly novel development for understanding the biogeochemical Sb cycle. Microbial Sb(III) and Fe(II) oxidation coupled with denitrification has great potential for bioremediation in anoxic Sb-contaminated environments.

Arsenite oxidation regulator AioR regulates bacterial chemotaxis towards arsenite in Agrobacterium tumefaciens GW4

Some arsenite [As(III)]-oxidizing bacteria exhibit positive chemotaxis towards As(III), however, the related As(III) chemoreceptor and regulatory mechanism remain unknown. The As(III)-oxidizing bacterium Agrobacterium tumefaciens GW4 displays positive chemotaxis towards 0.5–2 mM As(III). Genomic analyses revealed a putative chemoreceptor-encoding gene, mcp, located in the arsenic gene island and having a predicted promoter binding site for the As(III) oxidation regulator AioR. Expression of mcp and other chemotaxis related genes (cheA, cheY2 and fliG) was inducible by As(III), but not in the aioR mutant. Using capillary assays and intrinsic tryptophan fluorescence spectra analysis, Mcp was confirmed to be responsible for chemotaxis towards As(III) and to bind As(III) (but not As(V) nor phosphate) as part of the sensing mechanism. A bacterial one-hybrid system technique and electrophoretic mobility shift assays showed that AioR interacts with the mcp regulatory region in vivo and in vitro, and the precise AioR binding site was confirmed using DNase I foot-printing. Taken together, these results indicate that this Mcp is responsible for the chemotactic response towards As(III) and is regulated by AioR. Additionally, disrupting the mcp gene affected bacterial As(III) oxidation and growth, inferring that Mcp may exert some sort of functional connection between As(III) oxidation and As(III) chemotaxis.

Abiotic and biotic factors responsible for antimonite oxidation in Agrobacterium tumefaciens GW4

Antimonite [Sb(III)]-oxidizing bacteria can transform the toxic Sb(III) into the less toxic antimonate [Sb(V)]. Recently, the cytoplasmic Sb(III)-oxidase AnoA and the periplasmic arsenite [As(III)] oxidase AioAB were shown to responsible for bacterial Sb(III) oxidation, however, disruption of each gene only partially decreased Sb(III) oxidation efficiency. This study showed that in Agrobacterium tumefaciens GW4, Sb(III) induced cellular H₂O₂ content and H₂O₂ degradation gene katA. Gene knock-out/complementation of katA, anoA, aioA and anoA/aioA and Sb(III) oxidation and growth experiments showed that katA, anoA and aioA were essential for Sb(III) oxidation and resistance and katA was also essential for H₂O₂ resistance. Furthermore, linear correlations were observed between cellular H₂O₂ and Sb(V) content in vivo and chemical H₂O₂ and Sb(V) content in vitro (R² = 0.93 and 0.94, respectively). These results indicate that besides the biotic factors, the cellular H₂O₂ induced by Sb(III) also catalyzes bacterial Sb(III) oxidation as an abiotic oxidant. The data reveal a novel mechanism that bacterial Sb(III) oxidation is associated with abiotic (cellular H₂O₂) and biotic (AnoA and AioAB) factors and Sb(III) oxidation process consumes cellular H₂O₂ which contributes to microbial detoxification of both Sb(III) and cellular H₂O₂.

Effects upon metabolic pathways and energy production by Sb(III) and As(III)/Sb(III)-oxidase gene aioA in Agrobacterium tumefaciens GW4

Agrobacterium tumefaciens GW4 is a heterotrophic arsenite [As(III)]/antimonite [Sb(III)]-oxidizing strain. The As(III) oxidase AioAB is responsible for As(III) oxidation in the periplasm and it is also involved in Sb(III) oxidation in Agrobacterium tumefaciens 5A. In addition, Sb(III) oxidase AnoA and cellular H₂O₂ are also responsible for Sb(III) oxidation in strain GW4. However, the deletion of aioA increased the Sb(III) oxidation efficiency in strain GW4. In the present study, we found that the cell mobility to Sb(III), ATP and NADH contents and heat release were also increased by Sb(III) and more significantly in the aioA mutant. Proteomics and transcriptional analyses showed that proteins/genes involved in Sb(III) oxidation and resistance, stress responses, carbon metabolism, cell mobility, phosphonate and phosphinate metabolism, and amino acid and nucleotide metabolism were induced by Sb(III) and were more significantly induced in the aioA mutant. The results suggested that Sb(III) oxidation may produce energy. In addition, without periplasmic AioAB, more Sb(III) would enter bacterial cells, however, the cytoplasmic AnoA and the oxidative stress response proteins were significantly up-regulated, which may contribute to the increased Sb(III) oxidation efficiency. Moreover, the carbon metabolism was also activated to generate more energy against Sb(III) stress. The generated energy may be used in Sb transportation, DNA repair, amino acid synthesis, and cell mobility, and may be released in the form of heat.

An Oxidoreductase AioE is Responsible for Bacterial Arsenite Oxidation and Resistance

Previously, we found that arsenite (As^III) oxidation could improve the generation of ATP/NADH to support the growth of Agrobacterium tumefaciens GW4. In this study, we found that aioE is induced by As^III and located in the arsenic island near the As^III oxidase genes aioBA and co-transcripted with the arsenic resistant genes arsR1-arsC1-arsC2-acr3-1. AioE belongs to TrkA family corresponding the electron transport function with the generation of NADH and H⁺. An aioE in-frame deletion strain showed a null As^III oxidation and a reduced As^III resistance, while a cytC mutant only reduced As^III oxidation efficiency. With As^III, aioE was directly related to the increase of NADH, while cytC was essential for ATP generation. In addition, cyclic voltammetry analysis showed that the redox potential (ORP) of AioBA and AioE were +0.297 mV vs. NHE and +0.255 mV vs. NHE, respectively. The ORP gradient is AioBA > AioE > CytC (+0.217 ~ +0.251 mV vs. NHE), which infers that electron may transfer from AioBA to CytC via AioE. The results indicate that AioE may act as a novel As^III oxidation electron transporter associated with NADH generation. Since As^III oxidation contributes As^III detoxification, the essential of AioE for As^III resistance is also reasonable.

Disrupting ROS-protection mechanism allows hydrogen peroxide to accumulate and oxidize Sb(III) to Sb(V) in Pseudomonas stutzeri TS44

Background

Microbial antimonite [Sb(III)] oxidation converts toxic Sb(III) into less toxic antimonate [Sb(V)] and plays an important role in the biogeochemical Sb cycle. Currently, little is known about the mechanisms underlying bacterial Sb(III) resistance and oxidation.

Results

In this study, Tn5 transposon mutagenesis was conducted in the Sb(III)-oxidizing strain Pseudomonas stutzeri TS44 to isolate the genes responsible for Sb(III) resistance and oxidation. An insertion mutation into gshA, encoding a glutamate cysteine ligase involved in glutathione biosynthesis, generated a strain called P. stutzeri TS44-gshA₅₄₀. This mutant strain was complemented with a plasmid carrying gshA to generate strain P. stutzeri TS44-gshA-C. The transcription of gshA, the two superoxide dismutase (SOD)-encoding genes sodB and sodC as well as the catalase-encoding gene katE was monitored because gshA-encoded glutamate cysteine ligase is responsible for the biosynthesis of glutathione (GSH) and involved in the cellular stress defense system as are superoxide dismutase and catalase responsible for the conversion of ROS. In addition, the cellular content of total ROS and in particular H₂O₂ was analyzed. Compared to the wild type P. stutzeri TS44 and TS44-gshA-C, the mutant P. stutzeri TS44-gshA₅₄₀ had a lower GSH content and exhibited an increased content of total ROS and H₂O₂ and increased the Sb(III) oxidation rate. Furthermore, the transcription of sodB, sodC and katE was induced by Sb(III). A positive linear correlation was found between the Sb(III) oxidation rate and the H₂O₂ content (R² = 0.97), indicating that the accumulated H₂O₂ is correlated to the increased Sb(III) oxidation rate.

Conclusions

Based on the results, we propose that a disruption of the pathway involved in ROS-protection allowed H₂O₂ to accumulate. In addition to the previously reported enzyme mediated Sb(III) oxidation, the mechanism of bacterial oxidation of Sb(III) to Sb(V) includes a non-enzymatic mediated step using H₂O₂ as the oxidant.

Electronic supplementary material

The online version of this article (doi:10.1186/s12866-016-0902-5) contains supplementary material, which is available to authorized users.

Analysis of the multi-copied genes and the impact of the redundant protein coding sequences on gene annotation in prokaryotic genomes

The important roles of duplicated genes in evolutional process have been recognized in bacteria, archaebacteria and eukaryotes, while there is very little study on the multi-copied protein coding genes that share sequence identity of 100%. In this paper, the multi-copied protein coding genes in a number of prokaryotic genomes are comprehensively analyzed firstly. The results show that 0-15.93% of the protein coding genes in each genome are multi-copied genes and 0-16.49% of the protein coding genes in each genome are highly similar with the sequence identity ≥ 80%. Function and COG (Clusters of Orthologous Groups of proteins) analysis shows that 64.64% of multi-copied genes concentrate on the function of transposase and 86.28% of the COG assigned multi-copied genes concentrate on the COG code of 'L'. Furthermore, the impact of redundant protein coding sequences on the gene prediction results is studied. The results show that the problem of protein coding sequence redundancies cannot be ignored and the consistency of the gene annotation results before and after excluding the redundant sequences is negatively related with the sequences redundancy degree of the protein coding sequences in the training set.

Recognition of Protein-coding Genes Based on Z-curve Algorithms

Recognition of protein-coding genes, a classical bioinformatics issue, is an absolutely needed step for annotating newly sequenced genomes. The Z-curve algorithm, as one of the most effective methods on this issue, has been successfully applied in annotating or re-annotating many genomes, including those of bacteria, archaea and viruses. Two Z-curve based ab initio gene-finding programs have been developed: ZCURVE (for bacteria and archaea) and ZCURVE_V (for viruses and phages). ZCURVE_C (for 57 bacteria) and Zfisher (for any bacterium) are web servers for re-annotation of bacterial and archaeal genomes. The above four tools can be used for genome annotation or re-annotation, either independently or combined with the other gene-finding programs. In addition to recognizing protein-coding genes and exons, Z-curve algorithms are also effective in recognizing promoters and translation start sites. Here, we summarize the applications of Z-curve algorithms in gene finding and genome annotation.

GIIRA--RNA-Seq driven gene finding incorporating ambiguous reads

MOTIVATION

The reliable identification of genes is a major challenge in genome research, as further analysis depends on the correctness of this initial step. With high-throughput RNA-Seq data reflecting currently expressed genes, a particularly meaningful source of information has become commonly available for gene finding. However, practical application in automated gene identification is still not the standard case. A particular challenge in including RNA-Seq data is the difficult handling of ambiguously mapped reads.

RESULTS

We present GIIRA (Gene Identification Incorporating RNA-Seq data and Ambiguous reads), a novel prokaryotic and eukaryotic gene finder that is exclusively based on a RNA-Seq mapping and inherently includes ambiguously mapped reads. GIIRA extracts candidate regions supported by a sufficient number of mappings and reassigns ambiguous reads to their most likely origin using a maximum-flow approach. This avoids the exclusion of genes that are predominantly supported by ambiguous mappings. Evaluation on simulated and real data and comparison with existing methods incorporating RNA-Seq information highlight the accuracy of GIIRA in identifying the expressed genes.

AVAILABILITY AND IMPLEMENTATION

GIIRA is implemented in Java and is available from https://sourceforge.net/projects/giira/.

Reconciliation of sequence data and updated annotation of the genome of Agrobacterium tumefaciens C58, and distribution of a linear chromosome in the genus Agrobacterium

Two groups independently sequenced the Agrobacterium tumefaciens C58 genome in 2001. We report here consolidation of these sequences, updated annotation, and additional analysis of the evolutionary history of the linear chromosome, which is apparently limited to the biovar I group of Agrobacterium.