The Fish Pathogen "Candidatus Clavichlamydia salmonicola"-A Missing Link in the Evolution of Chlamydial Pathogens of Humans.

Chlamydiae like Chlamydia trachomatis and Chlamydia psittaci are well-known human and animal pathogens. Yet, the chlamydiae are a much larger group of evolutionary ancient obligate intracellular bacteria that includes predominantly symbionts of protists and diverse animals. This makes them ideal model organisms to study evolutionary transitions from symbionts in microbial eukaryotes to pathogens of humans. To this end, comparative genome analysis has served as an important tool. Genome sequence data for many chlamydial lineages are, however, still lacking, hampering our understanding of their evolutionary history. Here, we determined the first high-quality draft genome sequence of the fish pathogen "Candidatus Clavichlamydia salmonicola", representing a separate genus within the human and animal pathogenic Chlamydiaceae. The "Ca. Clavichlamydia salmonicola" genome harbors genes that so far have been exclusively found in Chlamydia species suggesting that basic mechanisms important for the interaction with chordate hosts have evolved stepwise in the history of chlamydiae. Thus, the genome sequence of "Ca. Clavichlamydia salmonicola" allows to constrain candidate genes to further understand the evolution of chlamydial virulence mechanisms required to infect mammals.

Validation and Application of Long-Read Whole-Genome Sequencing for Antimicrobial Resistance Gene Detection and Antimicrobial Susceptibility Testing.

Next-generation sequencing applications are increasingly used for detection and characterization of antimicrobial-resistant pathogens in clinical settings. Oxford Nanopore Technologies (ONT) sequencing offers advantages for clinical use compared with other sequencing methodologies because it enables real-time basecalling, produces long sequencing reads that increase the ability to correctly assemble DNA fragments, provides short turnaround times, and requires relatively uncomplicated sample preparation. A drawback of ONT sequencing, however, is its lower per-read accuracy than short-read sequencing. We sought to identify best practices in ONT sequencing protocols. As some variability in sequencing results may be introduced by the DNA extraction methodology, we tested three DNA extraction kits across three independent laboratories using a representative set of six bacterial isolates to investigate accuracy and reproducibility of ONT technology. All DNA extraction techniques showed comparable performance; however, the DNeasy PowerSoil Pro kit had the highest sequencing yield. This kit was subsequently applied to 42 sequentially collected bacterial isolates from blood cultures to assess Ares Genetics's pipelines for predictive whole-genome sequencing antimicrobial susceptibility testing (WGS-AST) performance compared to phenotypic triplicate broth microdilution results. WGS-AST results ranged across the organisms and resulted in an overall categorical agreement of 95% for penicillins, 82.4% for cephalosporins, 76.7% for carbapenems, 86.9% for fluoroquinolones, and 96.2% for aminoglycosides. Very major errors/major errors were 0%/16.7% (penicillins), 11.7%/3.6% (cephalosporins), 0%/24.4% (carbapenems), 2.5%/7.7% (fluoroquinolones), and 0%/4.1% (aminoglycosides), respectively. This work showed that, although additional refinements are necessary, ONT sequencing demonstrates potential as a method to perform WGS-AST on cultured isolates for patient care.

Analytical Performance Validation of Next-Generation Sequencing Based Clinical Microbiology Assays Using a K-mer Analysis Workflow.

Next-generation sequencing (NGS) enables clinical microbiology assays such as molecular typing of bacterial isolates which is now routinely applied for infection control and epidemiology. Additionally, feasibility for NGS-based identification of antimicrobial resistance (AMR) markers as well as genetic prediction of antibiotic susceptibility testing results has been demonstrated. Various bioinformatics approaches enabling NGS-based clinical microbiology assays exist, but standardized, computationally efficient and scalable sample-to-results workflows including validated quality control parameters are still lacking. Bioinformatics analysis workflows based on k-mers have been shown to allow for fast and efficient analysis of large genomics data sets as obtained from microbial sequencing applications. We here demonstrate applicability of k-mer based clinical microbiology assays for whole-genome sequencing (WGS) including variant calling, taxonomic identification, bacterial typing as well as AMR marker detection. The wet-lab and dry-lab workflows were developed and validated in line with Clinical Laboratory Improvement Act (CLIA) guidelines for laboratory-developed tests (LDTs) on multi-drug resistant ESKAPE pathogens. The developed k-mer based workflow demonstrated ≥99.39% repeatability, ≥99.09% reproducibility and ≥99.76% accuracy for variant calling and applied assays as determined by intra-day and inter-day triplicate measurements. The limit of detection (LOD) across assays was found to be at 20× sequencing depth and 15× for AMR marker detection. Thorough benchmarking of the k-mer based workflow revealed analytical performance criteria are comparable to state-of-the-art alignment based workflows across clinical microbiology assays. Diagnostic sensitivity and specificity for multilocus sequence typing (MLST) and phylogenetic analysis were 100% for both approaches. For AMR marker detection, sensitivity and specificity were 95.29 and 99.78% for the k-mer based workflow as compared to 95.17 and 99.77% for the alignment-based approach. Summarizing, results illustrate that k-mer based analysis workflows enable a broad range of clinical microbiology assays, potentially not only for WGS-based typing and AMR gene detection but also genetic prediction of antibiotic susceptibility testing results.

Species Identification and Antibiotic Resistance Prediction by Analysis of Whole-Genome Sequence Data by Use of ARESdb: an Analysis of Isolates from the Unyvero Lower Respiratory Tract Infection Trial.

Whole-genome sequencing (WGS) is now routinely performed in clinical microbiology laboratories to assess isolate relatedness. With appropriately developed analytics, the same data can be used for prediction of antimicrobial susceptibility. We assessed WGS data for identification using open-source tools and antibiotic susceptibility testing (AST) prediction using ARESdb compared to matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) identification and broth microdilution phenotypic susceptibility testing on clinical isolates from a multicenter clinical trial of the FDA-cleared Unyvero lower respiratory tract infection (LRTI) application (Curetis). For the trial, more than 2,000 patient samples were collected from intensive care units across nine hospitals and tested for LRTI. The isolate subset used in this study included 620 clinical isolates originating from 455 LRTI culture-positive patient samples. Isolates were sequenced using the Illumina Nextera XT protocol and FASTQ files with raw reads uploaded to the ARESdb cloud platform (ares-genetics.cloud; released for research use in 2020). The platform combines Ares Genetics' proprietary database ARESdb with state-of-the-art bioinformatics tools and curated public data. For identification, WGS showed 99 and 93% concordance with MALDI-TOF MS at the genus and species levels, respectively. WGS-predicted susceptibility showed 89% categorical agreement with phenotypic susceptibility across a total of 129 species-compound pairs analyzed, with categorical agreement exceeding 90% in 78 species-compound pairs and reaching 100% in 32. Results of this study add to the growing body of literature showing that, with improvement of analytics, WGS data could be used to predict antimicrobial susceptibility.

Correction to: Piphillin predicts metagenomic composition and dynamics from DADA2- corrected 16S rDNA sequences.

Following the publication of this article [1], the authors reported errors in Figs. 1, 2 and 5. Due to a typesetting error the asterisks denoting significance were missing from the published figures.

Piphillin predicts metagenomic composition and dynamics from DADA2-corrected 16S rDNA sequences.

BACKGROUND: Shotgun metagenomic sequencing reveals the potential in microbial communities. However, lower-cost 16S ribosomal RNA (rRNA) gene sequencing provides taxonomic, not functional, observations. To remedy this, we previously introduced Piphillin, a software package that predicts functional metagenomic content based on the frequency of detected 16S rRNA gene sequences corresponding to genomes in regularly updated, functionally annotated genome databases. Piphillin (and similar tools) have previously been evaluated on 16S rRNA data processed by the clustering of sequences into operational taxonomic units (OTUs). New techniques such as amplicon sequence variant error correction are in increased use, but it is unknown if these techniques perform better in metagenomic content prediction pipelines, or if they should be treated the same as OTU data in respect to optimal pipeline parameters. RESULTS: To evaluate the effect of 16S rRNA sequence analysis method (clustering sequences into OTUs vs amplicon sequence variant error correction into amplicon sequence variants (ASVs)) on the ability of Piphillin to predict functional metagenomic content, we evaluated Piphillin-predicted functional content from 16S rRNA sequence data processed through OTU clustering and error correction into ASVs compared to corresponding shotgun metagenomic data. We show a strong correlation between metagenomic data and Piphillin-predicted functional content resulting from both 16S rRNA sequence analysis methods. Differential abundance testing with Piphillin-predicted functional content exhibited a low false positive rate (< 0.05) while capturing a large fraction of the differentially abundant features resulting from corresponding metagenomic data. However, Piphillin prediction performance was optimal at different cutoff parameters depending on 16S rRNA sequence analysis method. Using data analyzed with amplicon sequence variant error correction, Piphillin outperformed comparable tools, for instance exhibiting 19% greater balanced accuracy and 54% greater precision compared to PICRUSt2. CONCLUSIONS: Our results demonstrate that raw Illumina sequences should be processed for subsequent Piphillin analysis using amplicon sequence variant error correction (with DADA2 or similar methods) and run using a 99% ID cutoff for Piphillin, while sequences generated on platforms other than Illumina should be processed via OTU clustering (e.g., UPARSE) and run using a 96% ID cutoff for Piphillin. Piphillin is publicly available for academic users (Piphillin server. http://piphillin.secondgenome.com/.).

Development of a DNA metabarcoding method for the identification of fifteen mammalian and six poultry species in food.

Meat products are prone to adulteration by the replacement of meat from more expensive animal species with meat from cheaper sources. We present a DNA metabarcoding method allowing the identification and differentiation of 15 mammalian and six poultry species in foodstuffs. The method, developed on the MiSeq® platform, targets a mitochondrial 16S rDNA region recently found to be suitable for the differentiation of 300 mammalian species. We designed a novel primer pair for poultry and applied it in combination with the primer pair for mammalian species in a duplex assay. The applicability of the method was investigated by analysing DNA extracts from muscle, DNA extract mixtures and extracts from model sausages. Our results indicated that the species of interest can be identified, differentiated and detected down to a proportion of 0.1%. Since 96 samples can be sequenced in one run, the method has high potential for application in routine analysis.

Leveraging sequence-based faecal microbial community survey data to identify a composite biomarker for colorectal cancer.

OBJECTIVE: Colorectal cancer (CRC) is the second leading cause of cancer-associated mortality in the USA. The faecal microbiome may provide non-invasive biomarkers of CRC and indicate transition in the adenoma-carcinoma sequence. Re-analysing raw sequence and metadata from several studies uniformly, we sought to identify a composite and generalisable microbial marker for CRC. DESIGN: Raw 16S rRNA gene sequence data sets from nine studies were processed with two pipelines, (1) QIIME closed reference (QIIME-CR) or (2) a strain-specific method herein termed SS-UP (Strain Select, UPARSE bioinformatics pipeline). A total of 509 samples (79 colorectal adenoma, 195 CRC and 235 controls) were analysed. Differential abundance, meta-analysis random effects regression and machine learning analyses were carried out to determine the consistency and diagnostic capabilities of potential microbial biomarkers. RESULTS: Definitive taxa, including Parvimonas micra ATCC 33270, Streptococcus anginosus and yet-to-be-cultured members of Proteobacteria, were frequently and significantly increased in stools from patients with CRC compared with controls across studies and had high discriminatory capacity in diagnostic classification. Microbiome-based CRC versus control classification produced an area under receiver operator characteristic (AUROC) curve of 76.6% in QIIME-CR and 80.3% in SS-UP. Combining clinical and microbiome markers gave a diagnostic AUROC of 83.3% for QIIME-CR and 91.3% for SS-UP. CONCLUSIONS: Despite technological differences across studies and methods, key microbial markers emerged as important in classifying CRC cases and such could be used in a universal diagnostic for the disease. The choice of bioinformatics pipeline influenced accuracy of classification. Strain-resolved microbial markers might prove crucial in providing a microbial diagnostic for CRC.

Growth of Chlamydia pneumoniae Is Enhanced in Cells with Impaired Mitochondrial Function.

Effective growth and replication of obligate intracellular pathogens depend on host cell metabolism. How this is connected to host cell mitochondrial function has not been studied so far. Recent studies suggest that growth of intracellular bacteria such as Chlamydia pneumoniae is enhanced in a low oxygen environment, arguing for a particular mechanistic role of the mitochondrial respiration in controlling intracellular progeny. Metabolic changes in C. pneumoniae infected epithelial cells were analyzed under normoxic (O2 ≈ 20%) and hypoxic conditions (O2 < 3%). We observed that infection of epithelial cells with C. pneumoniae under normoxia impaired mitochondrial function characterized by an enhanced mitochondrial membrane potential and ROS generation. Knockdown and mutation of the host cell ATP synthase resulted in an increased chlamydial replication already under normoxic conditions. As expected, mitochondrial hyperpolarization was observed in non-infected control cells cultured under hypoxic conditions, which was beneficial for C. pneumoniae growth. Taken together, functional and genetically encoded mitochondrial dysfunction strongly promotes intracellular growth of C. pneumoniae.

Piphillin: Improved Prediction of Metagenomic Content by Direct Inference from Human Microbiomes.

Functional analysis of a clinical microbiome facilitates the elucidation of mechanisms by which microbiome perturbation can cause a phenotypic change in the patient. The direct approach for the analysis of the functional capacity of the microbiome is via shotgun metagenomics. An inexpensive method to estimate the functional capacity of a microbial community is through collecting 16S rRNA gene profiles then indirectly inferring the abundance of functional genes. This inference approach has been implemented in the PICRUSt and Tax4Fun software tools. However, those tools have important limitations since they rely on outdated functional databases and uncertain phylogenetic trees and require very specific data pre-processing protocols. Here we introduce Piphillin, a straightforward algorithm independent of any proposed phylogenetic tree, leveraging contemporary functional databases and not obliged to any singular data pre-processing protocol. When all three inference tools were evaluated against actual shotgun metagenomics, Piphillin was superior in predicting gene composition in human clinical samples compared to both PICRUSt and Tax4Fun (p<0.01 and p<0.001, respectively) and Piphillin's ability to predict disease associations with specific gene orthologs exhibited a 15% increase in balanced accuracy compared to PICRUSt. From laboratory animal samples, no performance advantage was observed for any one of the tools over the others and for environmental samples all produced unsatisfactory predictions. Our results demonstrate that functional inference using the direct method implemented in Piphillin is preferable for clinical biospecimens. Piphillin is publicly available for academic use at http://secondgenome.com/Piphillin.

Functional Metagenomics of Spacecraft Assembly Cleanrooms: Presence of Virulence Factors Associated with Human Pathogens.

Strict planetary protection practices are implemented during spacecraft assembly to prevent inadvertent transfer of earth microorganisms to other planetary bodies. Therefore, spacecraft are assembled in cleanrooms, which undergo strict cleaning and decontamination procedures to reduce total microbial bioburden. We wanted to evaluate if these practices selectively favor survival and growth of hardy microorganisms, such as pathogens. Three geographically distinct cleanrooms were sampled during the assembly of three NASA spacecraft: The Lockheed Martin Aeronautics' Multiple Testing Facility during DAWN, the Kennedy Space Center's Payload Hazardous Servicing Facility (KSC-PHSF) during Phoenix, and the Jet Propulsion Laboratory's Spacecraft Assembly Facility during Mars Science Laboratory. Sample sets were collected from the KSC-PHSF cleanroom at three time points: before arrival of the Phoenix spacecraft, during the assembly and testing of the Phoenix spacecraft, and after removal of the spacecraft from the KSC-PHSF facility. All samples were subjected to metagenomic shotgun sequencing on an Illumina HiSeq 2500 platform. Strict decontamination procedures had a greater impact on microbial communities than sampling location Samples collected during spacecraft assembly were dominated by Acinetobacter spp. We found pathogens and potential virulence factors, which determine pathogenicity in all the samples tested during this study. Though the relative abundance of pathogens was lowest during the Phoenix assembly, potential virulence factors were higher during assembly compared to before and after assembly, indicating a survival advantage. Decreased phylogenetic and pathogenic diversity indicates that decontamination and preventative measures were effective against the majority of microorganisms and well implemented, however, pathogen abundance still increased over time. Four potential pathogens, Acinetobacter baumannii, Acinetobacter lwoffii, Escherichia coli and Legionella pneumophila, and their corresponding virulence factors were present in all cleanroom samples. This is the first functional metagenomics study describing presence of pathogens and their corresponding virulence factors in cleanroom environments. The results of this study should be considered for microbial monitoring of enclosed environments such as schools, homes, hospitals and more isolated habitation such the International Space Station and future manned missions to Mars.

ConsPred: a rule-based (re-)annotation framework for prokaryotic genomes.

MOTIVATION: The rapidly growing number of available prokaryotic genome sequences requires fully automated and high-quality software solutions for their initial and re-annotation. Here we present ConsPred, a prokaryotic genome annotation framework that performs intrinsic gene predictions, homology searches, predictions of non-coding genes as well as CRISPR repeats and integrates all evidence into a consensus annotation. ConsPred achieves comprehensive, high-quality annotations based on rules and priorities, similar to decision-making in manual curation and avoids conflicting predictions. Parameters controlling the annotation process are configurable by the user. ConsPred has been used in the institutions of the authors for longer than 5 years and can easily be extended and adapted to specific needs. SUMMARY: The ConsPred algorithm for producing a consensus from the varying scores of multiple gene prediction programs approaches manual curation in accuracy. Its rule-based approach for choosing final predictions avoids overriding previous manual curations. AVAILABILITY AND IMPLEMENTATION: ConsPred is implemented in Java, Perl and Shell and is freely available under the Creative Commons license as a stand-alone in-house pipeline or as an Amazon Machine Image for cloud computing, see https://sourceforge.net/projects/conspred/. CONTACT: thomas.rattei@univie.ac.atSupplementary information: Supplementary data are available at Bioinformatics online.

Phylogenetic and genomic analysis of Methanomassiliicoccales in wetlands and animal intestinal tracts reveals clade-specific habitat preferences.

Methanogenic Thermoplasmata of the novel order Methanomassiliicoccales were recently discovered in human and animal gastro-intestinal tracts (GITs). However, their distribution in other methanogenic environments has not been addressed systematically. Here, we surveyed Methanomassiliicoccales presence in wetland soils, a globally important source of methane emissions to the atmosphere, and in the GITs of different animals by PCR targeting their 16S rRNA and methyl:coenzyme M reductase (α-subunit) genes. We detected Methanomassiliicoccales in all 16 peat soils investigated, indicating their wide distribution in these habitats. Additionally, we detected their genes in various animal faeces. Methanomassiliicoccales were subdivided in two broad phylogenetic clades designated 'environmental' and 'GIT' clades based on differential, although non-exclusive, habitat preferences of their members. A well-supported cluster within the environmental clade comprised more than 80% of all wetland 16S rRNA gene sequences. Metagenome assembly from bovine rumen fluid enrichments resulted in two almost complete genomes of both Methanomassiliicoccales clades. Comparative genomics revealed that members of the environmental clade contain larger genomes and a higher number of genes encoding anti-oxidative enzymes than animal GIT clade representatives. This study highlights the wide distribution of Methanomassiliicoccales in wetlands, which suggests that they contribute to methane emissions from these climate-relevant ecosystems.

A viability-linked metagenomic analysis of cleanroom environments: eukarya, prokaryotes, and viruses.

BACKGROUND: Recent studies posit a reciprocal dependency between the microbiomes associated with humans and indoor environments. However, none of these metagenome surveys has considered the viability of constituent microorganisms when inferring impact on human health. RESULTS: Reported here are the results of a viability-linked metagenomics assay, which (1) unveil a remarkably complex community profile for bacteria, fungi, and viruses and (2) bolster the detection of underrepresented taxa by eliminating biases resulting from extraneous DNA. This approach enabled, for the first time ever, the elucidation of viral genomes from a cleanroom environment. Upon comparing the viable biomes and distribution of phylotypes within a cleanroom and adjoining (uncontrolled) gowning enclosure, the rigorous cleaning and stringent control countermeasures of the former were observed to select for a greater presence of anaerobes and spore-forming microflora. Sequence abundance and correlation analyses suggest that the viable indoor microbiome is influenced by both the human microbiome and the surrounding ecosystem(s). CONCLUSIONS: The findings of this investigation constitute the literature's first ever account of the indoor metagenome derived from DNA originating solely from the potential viable microbial population. Results presented in this study should prove valuable to the conceptualization and experimental design of future studies on indoor microbiomes aimed at inferring impact on human health.

New perspectives on microbial community distortion after whole-genome amplification.

Whole-genome amplification (WGA) has become an important tool to explore the genomic information of microorganisms in an environmental sample with limited biomass, however potential selective biases during the amplification processes are poorly understood. Here, we describe the effects of WGA on 31 different microbial communities from five biotopes that also included low-biomass samples from drinking water and groundwater. Our findings provide evidence that microbiome segregation by biotope was possible despite WGA treatment. Nevertheless, samples from different biotopes revealed different levels of distortion, with genomic GC content significantly correlated with WGA perturbation. Certain phylogenetic clades revealed a homogenous trend across various sample types, for instance Alpha- and Betaproteobacteria showed a decrease in their abundance after WGA treatment. On the other hand, Enterobacteriaceae, an important biomarker group for fecal contamination in groundwater and drinking water, were strongly affected by WGA treatment without a predictable pattern. These novel results describe the impact of WGA on low-biomass samples and may highlight issues to be aware of when designing future metagenomic studies that necessitate preceding WGA treatment.

Genomic factors related to tissue tropism in Chlamydia pneumoniae infection.

BACKGROUND: Chlamydia pneumoniae (Cpn) are obligate intracellular bacteria that cause acute infections of the upper and lower respiratory tract and have been implicated in chronic inflammatory diseases. Although of significant clinical relevance, complete genome sequences of only four clinical Cpn strains have been obtained. All of them were isolated from the respiratory tract and shared more than 99% sequence identity. Here we investigate genetic differences on the whole-genome level that are related to Cpn tissue tropism and pathogenicity. RESULTS: We have sequenced the genomes of 18 clinical isolates from different anatomical sites (e.g. lung, blood, coronary arteries) of diseased patients, and one animal isolate. In total 1,363 SNP loci and 184 InDels have been identified in the genomes of all clinical Cpn isolates. These are distributed throughout the whole chlamydial genome and enriched in highly variable regions. The genomes show clear evidence of recombination in at least one potential region but no phage insertions. The tyrP gene was always encoded as single copy in all vascular isolates. Phylogenetic reconstruction revealed distinct evolutionary lineages containing primarily non-respiratory Cpn isolates. In one of these, clinical isolates from coronary arteries and blood monocytes were closely grouped together. They could be distinguished from all other isolates by characteristic nsSNPs in genes involved in RB to EB transition, inclusion membrane formation, bacterial stress response and metabolism. CONCLUSIONS: This study substantially expands the genomic data of Cpn and elucidates its evolutionary history. The translation of the observed Cpn genetic differences into biological functions and the prediction of novel pathogen-oriented diagnostic strategies have to be further explored.

Complete Genome Sequence of Listeria monocytogenes Lm60, a Strain with an Enhanced Cold Adaptation Capacity.

The complete genome sequence of Listeria monocytogenes Lm60, a fast cold-adapting serotype 1/2a human isolate, is presented.

Biology of a widespread uncultivated archaeon that contributes to carbon fixation in the subsurface.

Subsurface microbial life contributes significantly to biogeochemical cycling, yet it remains largely uncharacterized, especially its archaeal members. This 'microbial dark matter' has been explored by recent studies that were, however, mostly based on DNA sequence information only. Here, we use diverse techniques including ultrastuctural analyses to link genomics to biology for the SM1 Euryarchaeon lineage, an uncultivated group of subsurface archaea. Phylogenomic analyses reveal this lineage to belong to a widespread group of archaea that we propose to classify as a new euryarchaeal order ('Candidatus Altiarchaeales'). The representative, double-membraned species 'Candidatus Altiarchaeum hamiconexum' has an autotrophic metabolism that uses a not-yet-reported Factor420-free reductive acetyl-CoA pathway, confirmed by stable carbon isotopic measurements of archaeal lipids. Our results indicate that this lineage has evolved specific metabolic and structural features like nano-grappling hooks empowering this widely distributed archaeon to predominate anaerobic groundwater, where it may represent an important carbon dioxide sink.

Recombination drives evolution of the Clostridium difficile 16S-23S rRNA intergenic spacer region.

PCR-ribotyping, a typing method based on size variation in 16S-23S rRNA intergenic spacer region (ISR), has been used widely for molecular epidemiological investigations of C. difficile infections. In the present study, we describe the sequence diversity of ISRs from 43 C. difficile strains, representing different PCR-ribotypes and suggest homologous recombination as a possible mechanism driving the evolution of 16S-23S rRNA ISRs. ISRs of 45 different lengths (ranging from 185 bp to 564 bp) were found among 458 ISRs. All ISRs could be described with one of the 22 different structural groups defined by the presence or absence of different sequence modules; tRNAAla genes and different combinations of spacers of different lengths (33 bp, 53 bp or 20 bp) and 9 bp direct repeats separating the spacers. The ISR structural group, in most cases, coincided with the sequence length. ISRs that were of the same lengths had also very similar nucleotide sequence, suggesting that ISRs were not suitable for discriminating between different strains based only on the ISR sequence. Despite large variations in the length, the alignment of ISR sequences, based on the primary sequence and secondary structure information, revealed many conserved regions which were mainly involved in maturation of pre-rRNA. Phylogenetic analysis of the ISR alignment yielded strong evidence for intra- and inter-homologous recombination which could be one of the mechanisms driving the evolution of C. difficile 16S-23S ISRs. The modular structure of the ISR, the high sequence similarities of ISRs of the same sizes and the presence of homologous recombination also suggest that different copies of C. difficile 16S-23S rRNA ISR are evolving in concert.

Characterization of 19 new microsatellite loci for the Omani barb Garra barreimiae from 454 sequences.

BACKGROUND: Garra barreimiae is a cyprinid fish from the southeastern Arabian Peninsula, which inhabits regularly desiccating wadis and survives in isolated ponds or underground. In 1984 a cave-dwelling population was found in the Al Hoota cave system and previous genetic analyses revealed some differentiation with limited gene flow between the surface populations and the cave population. Since no suitable markers are available for evaluation of gene flow between the cave population and the adjacent surface populations, we focused on designing and establishing novel microsatellite markers from next generation sequencing data. FINDINGS: 19 microsatellite markers containing di- and tetranucleotide simple sequence repeats were developed from 454 sequences. Forty-four individuals from two surface populations (Wadi Al Falahi and Misfat Al Abriyeen) of G. barreimiae (sampling permission number 13/2012, export permission number 29/2012) were used for analyses and characterization of the loci. On average, the number of alleles per locus is 7.6 (range: 2-20). Two markers displayed indication of linkage disequilibrium in both populations (DL6X, 9XNC). Significant deviation from Hardy-Weinberg equilibrium was observed at four loci in the Misfat Al Abriyeen population (2PUM, 88CM, 1EHE, 3Z7M) and at two loci in the Wadi Al Falahi population (QLIM, 3 N43). Three of the microsatellite loci were significant for null alleles in one of the two populations (Misfat Al Abriyeen: CJHG; Wadi Al Falahi: PH8A, 3ROZ). Expected and observed heterozygosities ranged from 0 to 95.0% respectively from 0 to 95.8% (Wadi Al Falahi) and from 0 to 89.1% respectively from 0 to 95.0% (Misfat Al Abriyeen). Fourteen of these markers were successfully cross-amplified in G. rufa. CONCLUSION: This 19 microsatellite loci provide a useful tool to understand the structure and genetic differences of populations. Moreover, these markers will help to evaluate species delimitation in G. barreimiae and potentially even in related species.