Identification of new genes in Sinorhizobium meliloti using the Genome Sequencer FLX system

Organism-specific rRNA capture system for application in next-generation sequencing

RNA-sequencing is a powerful tool in studying RNomics. However, the highly abundance of ribosomal RNAs (rRNA) and transfer RNA (tRNA) have predominated in the sequencing reads, thereby hindering the study of lowly expressed genes. Therefore, rRNA depletion prior to sequencing is often performed in order to preserve the subtle alteration in gene expression especially those at relatively low expression levels. One of the commercially available methods is to use DNA or RNA probes to hybridize to the target RNAs. However, there is always a concern with the non-specific binding and unintended removal of messenger RNA (mRNA) when the same set of probes is applied to different organisms. The degree of such unintended mRNA removal varies among organisms due to organism-specific genomic variation. We developed a computer-based method to design probes to deplete rRNA in an organism-specific manner. Based on the computation results, biotinylated-RNA-probes were produced by in vitro transcription and were used to perform rRNA depletion with subtractive hybridization. We demonstrated that the designed probes of 16S rRNAs and 23S rRNAs can efficiently remove rRNAs from Mycobacterium smegmatis. In comparison with a commercial subtractive hybridization-based rRNA removal kit, using organism-specific probes is better in preserving the RNA integrity and abundance. We believe the computer-based design approach can be used as a generic method in preparing RNA of any organisms for next-generation sequencing, particularly for the transcriptome analysis of microbes.

Whole transcriptome analysis of Acinetobacter baumannii assessed by RNA-sequencing reveals different mRNA expression profiles in biofilm compared to planktonic cells

Acinetobacterbaumannii has emerged as a dangerous opportunistic pathogen, with many strains able to form biofilms and thus cause persistent infections. The aim of the present study was to use high-throughput sequencing techniques to establish complete transcriptome profiles of planktonic (free-living) and sessile (biofilm) forms of A. baumannii ATCC 17978 and thereby identify differences in their gene expression patterns. Collections of mRNA from planktonic (both exponential and stationary phase cultures) and sessile (biofilm) cells were sequenced. Six mRNA libraries were prepared following the mRNA-Seq protocols from Illumina. Reads were obtained in a HiScanSQ platform and mapped against the complete genome to describe the complete mRNA transcriptomes of planktonic and sessile cells. The results showed that the gene expression pattern of A. baumannii biofilm cells was distinct from that of planktonic cells, including 1621 genes over-expressed in biofilms relative to stationary phase cells and 55 genes expressed only in biofilms. These differences suggested important changes in amino acid and fatty acid metabolism, motility, active transport, DNA-methylation, iron acquisition, transcriptional regulation, and quorum sensing, among other processes. Disruption or deletion of five of these genes caused a significant decrease in biofilm formation ability in the corresponding mutant strains. Among the genes over-expressed in biofilm cells were those in an operon involved in quorum sensing. One of them, encoding an acyl carrier protein, was shown to be involved in biofilm formation as demonstrated by the significant decrease in biofilm formation by the corresponding knockout strain. The present work serves as a basis for future studies examining the complex network systems that regulate bacterial biofilm formation and maintenance.

Efficient and robust RNA-seq process for cultured bacteria and complex community transcriptomes

We have developed a process for transcriptome analysis of bacterial communities that accommodates both intact and fragmented starting RNA and combines efficient rRNA removal with strand-specific RNA-seq. We applied this approach to an RNA mixture derived from three diverse cultured bacterial species and to RNA isolated from clinical stool samples. The resulting expression profiles were highly reproducible, enriched up to 40-fold for non-rRNA transcripts, and correlated well with profiles representing undepleted total RNA.

Molecular techniques in the biotechnological fight against halogenated compounds in anoxic environments

Microbial treatment of environmental contamination by anthropogenic halogenated organic compounds has become popular in recent decades, especially in the subsurface environments. Molecular techniques such as polymerase chain reaction-based fingerprinting methods have been extensively used to closely monitor the presence and activities of dehalogenating microbes, which also lead to the discovery of new dehalogenating bacteria and novel functional genes. Nowadays, traditional molecular techniques are being further developed and optimized for higher sensitivity, specificity, and accuracy to better fit the contexts of dehalogenation. On the other hand, newly developed high throughput techniques, such as microarray and next-generation sequencing, provide unsurpassed detection ability, which has enabled large-scale comparative genomic and whole-genome transcriptomic analysis. The aim of this review is to summarize applications of various molecular tools in the field of microbially mediated dehalogenation of various halogenated organic compounds. It is expected that traditional molecular techniques and nucleic-acid-based biomarkers will still be favoured in the foreseeable future because of relative low costs and high flexibility. Collective analyses of metagenomic sequencing data are still in need of information from individual dehalogenating strains and functional reductive dehalogenase genes in order to draw reliable conclusions.

An ABC-type cobalt transport system is essential for growth of Sinorhizobium meliloti at trace metal concentrations

We report expression and mutant phenotypes for a gene cluster in Sinorhizobium meliloti, designated cbtJKL, that has been shown to encode an ABC-type cobalt transport system. Transcription of cbtJKL initiated 384 nucleotides upstream from the cbtJ translation start codon, and the resulting 5' region contained a putative B(12)riboswitch. Expression of the cbtJKL genes appeared to be controlled by (cobalt-loaded) cobalamin interacting at the B(12)riboswitch, since (i) a putative B(12)riboswitch was located within this large upstream region, (ii) cbtJ transcription was repressed upon addition of cobalt or vitamin B(12), and (iii) deletions in the B(12)riboswitch resulted in constitutive cbtJKL transcription. Insertion mutants in cbtJKL failed to grow in LB medium, and growth was restored through the addition of cobalt but not other metals. This growth phenotype appeared to be due to the chelation of cobalt present in LB, and cbtJKL mutants also failed to grow in minimal medium containing the chelating agent EDTA unless the medium was supplemented with additional or excess cobalt. In uptake experiments, (57)Co(2+)accumulation was high in wild-type cells expressing the cbtJKL genes, whereas wild-type cells in which cbtJKL expression was repressed showed reduced accumulation. In cbtJKL mutant cells, (57)Co(2+)accumulation was reduced relative to that of the wild type, and presumably, this residual cobalt transport occurred via an alternate ion uptake system(s) that is not specific to cobalt. In symbiosis, the alternate system(s) appeared to mediate cobalt transport into bacteroid cells, as low cbtJKL expression was detected in bacteroids and cbtJKL mutants formed N(2)-fixing nodules on alfalfa.

Transcriptomic signatures of ash (Fraxinus spp.) phloem

BACKGROUND

Ash (Fraxinus spp.) is a dominant tree species throughout urban and forested landscapes of North America (NA). The rapid invasion of NA by emerald ash borer (Agrilus planipennis), a wood-boring beetle endemic to Eastern Asia, has resulted in the death of millions of ash trees and threatens billions more. Larvae feed primarily on phloem tissue, which girdles and kills the tree. While NA ash species including black (F. nigra), green (F. pennsylvannica) and white (F. americana) are highly susceptible, the Asian species Manchurian ash (F. mandshurica) is resistant to A. planipennis perhaps due to their co-evolutionary history. Little is known about the molecular genetics of ash. Hence, we undertook a functional genomics approach to identify the repertoire of genes expressed in ash phloem.

METHODOLOGY AND PRINCIPAL FINDINGS

Using 454 pyrosequencing we obtained 58,673 high quality ash sequences from pooled phloem samples of green, white, black, blue and Manchurian ash. Intriguingly, 45% of the deduced proteins were not significantly similar to any sequences in the GenBank non-redundant database. KEGG analysis of the ash sequences revealed a high occurrence of defense related genes. Expression analysis of early regulators potentially involved in plant defense (i.e. transcription factors, calcium dependent protein kinases and a lipoxygenase 3) revealed higher mRNA levels in resistant ash compared to susceptible ash species. Lastly, we predicted a total of 1,272 single nucleotide polymorphisms and 980 microsatellite loci, among which seven microsatellite loci showed polymorphism between different ash species.

CONCLUSIONS AND SIGNIFICANCE

The current transcriptomic data provide an invaluable resource for understanding the genetic make-up of ash phloem, the target tissue of A. planipennis. These data along with future functional studies could lead to the identification/characterization of defense genes involved in resistance of ash to A. planipennis, and in future ash breeding programs for marker development.

Characterization of the horseweed (Conyza canadensis) transcriptome using GS-FLX 454 pyrosequencing and its application for expression analysis of candidate non-target herbicide resistance genes

BACKGROUND

The de novo transcriptome sequencing of a weedy plant using GS-FLX 454 technologies is reported. Horseweed (Conyza canadensis L.) was the first broadleaf weed to evolve glyphosate resistance in agriculture, and also is the most widely distributed glyphosate-resistant weed in the United States and the world. However, available sequence data for this species are scant. The transcriptomic sequence should be useful for gene discovery, and to help elucidate the non-target-based glyphosate resistance mechanism and the genomic basis of weediness.

RESULTS

Sequencing experiments yielded 411 962 raw reads, an average read length of 233 bp and a total dataset of 95.8 Mb (NCBI accession number SRA010952). After trimming and quality control, 379 152 high-quality sequences were retained and assembled into contigs. The assembly resulted in 31 783 unique transcripts, including 16 102 contigs and 15 681 singletons. The average coverage depth for each contig and each nucleotide position was 22-fold and 12-fold respectively. A total of 16 306 unique sequences were annotated by searching a custom plant protein database. The utility of the transcriptome data was demonstrated by further exploration of ABC transporters, which were previously hypothesized to play a role in non-target glyphosate resistance. Real-time RT-PCR primers were designed from the transcriptome data, which made it possible to assess expression patterns of 17 ABC transporters from resistant and susceptible horseweed accessions from Tennessee, with and without glyphosate treatment.

CONCLUSION

These results show that GS-FLX 454 sequencing is a powerful and cost-effective platform for the development of functional genomic tools for a weed species.

Studying bacterial transcriptomes using RNA-seq

Genome-wide studies of bacterial gene expression are shifting from microarray technology to second generation sequencing platforms. RNA-seq has a number of advantages over hybridization-based techniques, such as annotation-independent detection of transcription, improved sensitivity and increased dynamic range. Early studies have uncovered a wealth of novel coding sequences and non-coding RNA, and are revealing a transcriptional landscape that increasingly mirrors that of eukaryotes. Already basic RNA-seq protocols have been improved and adapted to looking at particular aspects of RNA biology, often with an emphasis on non-coding RNAs, and further refinements to current techniques will improve our understanding of gene expression, and genome content, in the future.

Population-level transcriptome sequencing of nonmodel organisms Erynnis propertius and Papilio zelicaon

BACKGROUND

Several recent studies have demonstrated the use of Roche 454 sequencing technology for de novo transcriptome analysis. Low error rates and high coverage also allow for effective SNP discovery and genetic diversity estimates. However, genetically diverse datasets, such as those sourced from natural populations, pose challenges for assembly programs and subsequent analysis. Further, estimating the effectiveness of transcript discovery using Roche 454 transcriptome data is still a difficult task.

RESULTS

Using the Roche 454 FLX Titanium platform, we sequenced and assembled larval transcriptomes for two butterfly species: the Propertius duskywing, Erynnis propertius (Lepidoptera: Hesperiidae) and the Anise swallowtail, Papilio zelicaon (Lepidoptera: Papilionidae). The Expressed Sequence Tags (ESTs) generated represent a diverse sample drawn from multiple populations, developmental stages, and stress treatments. Despite this diversity, > 95% of the ESTs assembled into long (> 714 bp on average) and highly covered (> 9.6x on average) contigs. To estimate the effectiveness of transcript discovery, we compared the number of bases in the hit region of unigenes (contigs and singletons) to the length of the best match silkworm (Bombyx mori) protein--this "ortholog hit ratio" gives a close estimate on the amount of the transcript discovered relative to a model lepidopteran genome. For each species, we tested two assembly programs and two parameter sets; although CAP3 is commonly used for such data, the assemblies produced by Celera Assembler with modified parameters were chosen over those produced by CAP3 based on contig and singleton counts as well as ortholog hit ratio analysis. In the final assemblies, 1,413 E. propertius and 1,940 P. zelicaon unigenes had a ratio > 0.8; 2,866 E. propertius and 4,015 P. zelicaon unigenes had a ratio > 0.5.

CONCLUSIONS

Ultimately, these assemblies and SNP data will be used to generate microarrays for ecoinformatics examining climate change tolerance of different natural populations. These studies will benefit from high quality assemblies with few singletons (less than 26% of bases for each assembled transcriptome are present in unassembled singleton ESTs) and effective transcript discovery (over 6,500 of our putative orthologs cover at least 50% of the corresponding model silkworm gene).

A genome-wide survey of sRNAs in the symbiotic nitrogen-fixing alpha-proteobacterium Sinorhizobium meliloti

Background

Small untranslated RNAs (sRNAs) are widespread regulators of gene expression in bacteria. This study reports on a comprehensive screen for sRNAs in the symbiotic nitrogen-fixing alpha-proteobacterium Sinorhizobium meliloti applying deep sequencing of cDNAs and microarray hybridizations.

Results

A total of 1,125 sRNA candidates that were classified as trans-encoded sRNAs (173), cis-encoded antisense sRNAs (117), mRNA leader transcripts (379), and sense sRNAs overlapping coding regions (456) were identified in a size range of 50 to 348 nucleotides. Among these were transcripts corresponding to 82 previously reported sRNA candidates. Enrichment for RNAs with primary 5'-ends prior to sequencing of cDNAs suggested transcriptional start sites corresponding to 466 predicted sRNA regions. The consensus σ⁷⁰ promoter motif CTTGAC-N₁₇-CTATAT was found upstream of 101 sRNA candidates. Expression patterns derived from microarray hybridizations provided further information on conditions of expression of a number of sRNA candidates. Furthermore, GenBank, EMBL, DDBJ, PDB, and Rfam databases were searched for homologs of the sRNA candidates identified in this study. Searching Rfam family models with over 1,000 sRNA candidates, re-discovered only those sequences from S. meliloti already known and stored in Rfam, whereas BLAST searches suggested a number of homologs in related alpha-proteobacteria.

Conclusions

The screening data suggests that in S. meliloti about 3% of the genes encode trans-encoded sRNAs and about 2% antisense transcripts. Thus, this first comprehensive screen for sRNAs applying deep sequencing in an alpha-proteobacterium shows that sRNAs also occur in high number in this group of bacteria.

Dual control of Sinorhizobium meliloti RpoE2 sigma factor activity by two PhyR-type two-component response regulators

RpoE2 is an extracytoplasmic function (ECF) sigma factor involved in the general stress response of Sinorhizobium meliloti, the nitrogen-fixing symbiont of the legume plant alfalfa. RpoE2 orthologues are widely found among alphaproteobacteria, where they play various roles in stress resistance and/or host colonization. In this paper, we report a genetic and biochemical investigation of the mechanisms of signal transduction leading to S. meliloti RpoE2 activation in response to stress. We showed that RpoE2 activity is negatively controlled by two paralogous anti-sigma factors, RsiA1 (SMc01505) and RsiA2 (SMc04884), and that RpoE2 activation by stress requires two redundant paralogous PhyR-type response regulators, RsiB1 (SMc01504) and RsiB2 (SMc00794). RsiB1 and RsiB2 do not act at the level of rpoE2 transcription but instead interact with the anti-sigma factors, and we therefore propose that they act as anti-anti-sigma factors to relieve RpoE2 inhibition in response to stress. This model closely resembles a recently proposed model of activation of RpoE2-like sigma factors in Methylobacterium extorquens and Bradyrhizobium japonicum, but the existence of two pairs of anti- and anti-anti-sigma factors in S. meliloti adds an unexpected level of complexity, which may allow the regulatory system to integrate multiple stimuli.

RNA-seq: from technology to biology

Next-generation sequencing technologies are now being exploited not only to analyse static genomes, but also dynamic transcriptomes in an approach termed RNA-seq. Although these powerful and rapidly evolving technologies have only been available for a couple of years, they are already making substantial contributions to our understanding of genome expression and regulation. Here, we briefly describe technical issues accompanying RNA-seq data generation and analysis, highlighting differences to array-based approaches. We then review recent biological insight gained from applying RNA-seq and related approaches to deeply sample transcriptomes in different cell types or physiological conditions. These approaches are providing fascinating information about transcriptional and post-transcriptional gene regulation, and they are also giving unique insight into the richness of transcript structures and processing on a global scale and at unprecedented resolution.

Deep RNA sequencing of L. monocytogenes reveals overlapping and extensive stationary phase and sigma B-dependent transcriptomes, including multiple highly transcribed noncoding RNAs

Background

Identification of specific genes and gene expression patterns important for bacterial survival, transmission and pathogenesis is critically needed to enable development of more effective pathogen control strategies. The stationary phase stress response transcriptome, including many σ^B-dependent genes, was defined for the human bacterial pathogen Listeria monocytogenes using RNA sequencing (RNA-Seq) with the Illumina Genome Analyzer. Specifically, bacterial transcriptomes were compared between stationary phase cells of L. monocytogenes 10403S and an otherwise isogenic ΔsigB mutant, which does not express the alternative σ factor σ^B, a major regulator of genes contributing to stress response, including stresses encountered upon entry into stationary phase.

Results

Overall, 83% of all L. monocytogenes genes were transcribed in stationary phase cells; 42% of currently annotated L. monocytogenes genes showed medium to high transcript levels under these conditions. A total of 96 genes had significantly higher transcript levels in 10403S than in ΔsigB, indicating σ^B-dependent transcription of these genes. RNA-Seq analyses indicate that a total of 67 noncoding RNA molecules (ncRNAs) are transcribed in stationary phase L. monocytogenes, including 7 previously unrecognized putative ncRNAs. Application of a dynamically trained Hidden Markov Model, in combination with RNA-Seq data, identified 65 putative σ^B promoters upstream of 82 of the 96 σ^B-dependent genes and upstream of the one σ^B-dependent ncRNA. The RNA-Seq data also enabled annotation of putative operons as well as visualization of 5'- and 3'-UTR regions.

Conclusions

The results from these studies provide powerful evidence that RNA-Seq data combined with appropriate bioinformatics tools allow quantitative characterization of prokaryotic transcriptomes, thus providing exciting new strategies for exploring transcriptional regulatory networks in bacteria.

See minireivew http://jbiol.com/content/8/12/107.

Prokaryotic transcriptomics: a new view on regulation, physiology and pathogenicity

Transcriptome-wide studies in eukaryotes have been instrumental in the characterization of fundamental regulatory mechanisms for more than a decade. By contrast, in prokaryotes (bacteria and archaea) whole-transcriptome studies have not been performed until recently owing to the general view that microbial gene structures are simple, as well as technical difficulties in enriching for mRNAs that lack poly(A) tails. Deep RNA sequencing and tiling array studies are now revolutionizing our understanding of the complexity, plasticity and regulation of microbial transcriptomes.

RNA-seq: from technology to biology

Next-generation sequencing technologies are now being exploited not only to analyse static genomes, but also dynamic transcriptomes in an approach termed RNA-seq. Although these powerful and rapidly evolving technologies have only been available for a couple of years, they are already making substantial contributions to our understanding of genome expression and regulation. Here, we briefly describe technical issues accompanying RNA-seq data generation and analysis, highlighting differences to array-based approaches. We then review recent biological insight gained from applying RNA-seq and related approaches to deeply sample transcriptomes in different cell types or physiological conditions. These approaches are providing fascinating information about transcriptional and post-transcriptional gene regulation, and they are also giving unique insight into the richness of transcript structures and processing on a global scale and at unprecedented resolution.

Experimental approaches for the discovery and characterization of regulatory small RNA

Following the pioneering screens for small regulatory RNAs (sRNAs) in Escherichia coli in 2001, sRNAs are now being identified in almost every branch of the eubacterial kingdom. Experimental strategies have become increasingly important for sRNA discovery, thanks to increased availability of tiling arrays and fast progress in the development of high-throughput cDNA sequencing (RNA-Seq). The new technologies also facilitate genome-wide discovery of potential target mRNAs by sRNA pulse-expression coupled to transcriptomics, and immunoprecipitation with RNA-binding proteins such as Hfq. Moreover, the staggering rate of new sRNAs demands mechanistic analysis of target regulation. We will also review the available toolbox for wet lab-based research, including in vivo and in vitro reporter systems, genetic methods and biochemical co-purification of sRNA interaction partners.

Applications of new sequencing technologies for transcriptome analysis

Transcriptome analysis has been a key area of biological inquiry for decades. Over the years, research in the field has progressed from candidate gene-based detection of RNAs using Northern blotting to high-throughput expression profiling driven by the advent of microarrays. Next-generation sequencing technologies have revolutionized transcriptomics by providing opportunities for multidimensional examinations of cellular transcriptomes in which high-throughput expression data are obtained at a single-base resolution.

Transcriptome sequencing of the Microarray Quality Control (MAQC) RNA reference samples using next generation sequencing

Background

Transcriptome sequencing using next-generation sequencing platforms will soon be competing with DNA microarray technologies for global gene expression analysis. As a preliminary evaluation of these promising technologies, we performed deep sequencing of cDNA synthesized from the Microarray Quality Control (MAQC) reference RNA samples using Roche's 454 Genome Sequencer FLX.

Results

We generated more that 3.6 million sequence reads of average length 250 bp for the MAQC A and B samples and introduced a data analysis pipeline for translating cDNA read counts into gene expression levels. Using BLAST, 90% of the reads mapped to the human genome and 64% of the reads mapped to the RefSeq database of well annotated genes with e-values ≤ 10^-20. We measured gene expression levels in the A and B samples by counting the numbers of reads that mapped to individual RefSeq genes in multiple sequencing runs to evaluate the MAQC quality metrics for reproducibility, sensitivity, specificity, and accuracy and compared the results with DNA microarrays and Quantitative RT-PCR (QRTPCR) from the MAQC studies. In addition, 88% of the reads were successfully aligned directly to the human genome using the AceView alignment programs with an average 90% sequence similarity to identify 137,899 unique exon junctions, including 22,193 new exon junctions not yet contained in the RefSeq database.

Conclusion

Using the MAQC metrics for evaluating the performance of gene expression platforms, the ExpressSeq results for gene expression levels showed excellent reproducibility, sensitivity, and specificity that improved systematically with increasing shotgun sequencing depth, and quantitative accuracy that was comparable to DNA microarrays and QRTPCR. In addition, a careful mapping of the reads to the genome using the AceView alignment programs shed new light on the complexity of the human transcriptome including the discovery of thousands of new splice variants.

Sequencing and de novo analysis of a coral larval transcriptome using 454 GSFlx

BACKGROUND

New methods are needed for genomic-scale analysis of emerging model organisms that exemplify important biological questions but lack fully sequenced genomes. For example, there is an urgent need to understand the potential for corals to adapt to climate change, but few molecular resources are available for studying these processes in reef-building corals. To facilitate genomics studies in corals and other non-model systems, we describe methods for transcriptome sequencing using 454, as well as strategies for assembling a useful catalog of genes from the output. We have applied these methods to sequence the transcriptome of planulae larvae from the coral Acropora millepora.

RESULTS

More than 600,000 reads produced in a single 454 sequencing run were assembled into approximately 40,000 contigs with five-fold average sequencing coverage. Based on sequence similarity with known proteins, these analyses identified approximately 11,000 different genes expressed in a range of conditions including thermal stress and settlement induction. Assembled sequences were annotated with gene names, conserved domains, and Gene Ontology terms. Targeted searches using these annotations identified the majority of genes associated with essential metabolic pathways and conserved signaling pathways, as well as novel candidate genes for stress-related processes. Comparisons with the genome of the anemone Nematostella vectensis revealed approximately 8,500 pairs of orthologs and approximately 100 candidate coral-specific genes. More than 30,000 SNPs were detected in the coral sequences, and a subset of these validated by re-sequencing.

CONCLUSION

The methods described here for deep sequencing of the transcriptome should be widely applicable to generate catalogs of genes and genetic markers in emerging model organisms. Our data provide the most comprehensive sequence resource currently available for reef-building corals, and include an extensive collection of potential genetic markers for association and population connectivity studies. The characterization of the larval transcriptome for this widely-studied coral will enable research into the biological processes underlying stress responses in corals and evolutionary adaptation to global climate change.

A portal for rhizobial genomes: RhizoGATE integrates a Sinorhizobium meliloti genome annotation update with postgenome data

Sinorhizobium meliloti is a symbiotic soil bacterium of the alphaproteobacterial subdivision. Like other rhizobia, S. meliloti induces nitrogen-fixing root nodules on leguminous plants. This is an ecologically and economically important interaction, because plants engaged in symbiosis with rhizobia can grow without exogenous nitrogen fertilizers. The S. meliloti-Medicago truncatula (barrel medic) association is an important symbiosis model. The S. meliloti genome was published in 2001, and the M. truncatula genome currently is being sequenced. Many new resources and data have been made available since the original S. meliloti genome annotation and an update was needed. In June 2008, we submitted our annotation update to the EMBL and NCBI databases. Here we describe this new annotation and a new web-based portal RhizoGATE. About 1000 annotation updates were made; these included assigning functions to 313 putative proteins, assigning EC numbers to 431 proteins, and identifying 86 new putative genes. RhizoGATE incorporates the new annotion with the S. meliloti GenDB project, a platform that allows annotation updates in real time. Locations of transposon insertions, plasmid integrations, and array probe sequences are available in the GenDB project. RhizoGATE employs the EMMA platform for management and analysis of transcriptome data and the IGetDB data warehouse to integrate a variety of heterogeneous external data sources.

New tools for discovering and characterizing microbial diversity

To discover and characterize microbial diversity, approaches based on new sequencing technologies, novel isolation techniques, microfluidics, and metagenomics among others are being used. These approaches have contributed to discovery of novel genes from environmental samples, to massive characterization of functional and phylogenetic genes and to isolation of members of formerly uncultured yet ubiquitous groups like Verrucomicrobia, Acidobacteria, OP10, and methanogenic Archaea. Cheaper sequencing is key in this process by making available applications that were previously restricted to big research centers, complementing previously available methodologies and potentially replacing some of them. The new tools are reshaping the way we study the environment, increasing the resolution at which microbial communities, their complexities and dynamics, can be studied to reveal their genetic potential and their functional diversity.