Complete genome sequencing and analysis of a Lancefield group G Streptococcus dysgalactiae subsp. equisimilis strain causing streptococcal toxic shock syndrome (STSS)

<p>Abstract</p> <p>Background</p> <p><it>Streptococcus dysgalactiae </it>subsp. <it>equisimilis </it>(SDSE) causes invasive streptococcal infections, including streptococcal toxic shock syndrome (STSS), as does Lancefield group A <it>Streptococcus pyogenes </it>(GAS). We sequenced the entire genome of SDSE strain GGS_124 isolated from a patient with STSS.</p> <p>Results</p> <p>We found that GGS_124 consisted of a circular genome of 2,106,340 bp. Comparative analyses among bacterial genomes indicated that GGS_124 was most closely related to GAS. GGS_124 and GAS, but not other streptococci, shared a number of virulence factor genes, including genes encoding streptolysin O, NADase, and streptokinase A, distantly related to SIC (DRS), suggesting the importance of these factors in the development of invasive disease. GGS_124 contained 3 prophages, with one containing a virulence factor gene for streptodornase. All 3 prophages were significantly similar to GAS prophages that carry virulence factor genes, indicating that these prophages had transferred these genes between pathogens. SDSE was found to contain a gene encoding a superantigen, streptococcal exotoxin type G, but lacked several genes present in GAS that encode virulence factors, such as other superantigens, cysteine protease <it>speB</it>, and hyaluronan synthase operon <it>hasABC</it>. Similar to GGS_124, the SDSE strains contained larger numbers of clustered, regularly interspaced, short palindromic repeats (CRISPR) spacers than did GAS, suggesting that horizontal gene transfer via streptococcal phages between SDSE and GAS is somewhat restricted, although they share phage species.</p> <p>Conclusion</p> <p>Genome wide comparisons of SDSE with GAS indicate that SDSE is closely and quantitatively related to GAS. SDSE, however, lacks several virulence factors of GAS, including superantigens, SPE-B and the <it>hasABC </it>operon. CRISPR spacers may limit the horizontal transfer of phage encoded GAS virulence genes into SDSE. These findings may provide clues for dissecting the pathological roles of the virulence factors in SDSE and GAS that cause STSS.</p

Taxonomic classification for microbiome analysis, which correlates well with the metabolite milieu of the gut

Abstract Background 16S rRNA gene amplicon sequencing analysis (16S amplicon sequencing) has provided considerable information regarding the ecology of the intestinal microbiome. Recently, metabolomics has been used for investigating the crosstalk between the intestinal microbiome and the host via metabolites. In the present study, we determined the accuracy with which 16S rRNA gene data at different classification levels correspond to the metabolome data for an in-depth understanding of the intestinal environment. Results Over 200 metabolites were identified using capillary electrophoresis and time-of-flight mass spectrometry (CE-TOFMS)-based metabolomics in the feces of antibiotic-treated and untreated mice. 16S amplicon sequencing, followed by principal component analysis (PCA) of the intestinal microbiome at each taxonomic rank, revealed differences between the antibiotic-treated and untreated groups in the first principal component in the family-, genus, and species-level analyses. These differences were similar to those observed in the PCA of the metabolome. Furthermore, a strong correlation between principal component (PC) scores of the metabolome and microbiome was observed in family-, genus-, and species-level analyses. Conclusions Lower taxonomic ranks such as family, genus, or species are preferable for 16S amplicon sequencing to investigate the correlation between the microbiome and metabolome. The correlation of PC scores between the microbiome and metabolome at lower taxonomic levels yield a simple method of integrating different “-omics” data, which provides insights regarding crosstalk between the intestinal microbiome and the host

Taxonomic classification for microbiome analysis, which correlates well with the metabolite milieu of the gut

Abstract Background 16S rRNA gene amplicon sequencing analysis (16S amplicon sequencing) has provided considerable information regarding the ecology of the intestinal microbiome. Recently, metabolomics has been used for investigating the crosstalk between the intestinal microbiome and the host via metabolites. In the present study, we determined the accuracy with which 16S rRNA gene data at different classification levels correspond to the metabolome data for an in-depth understanding of the intestinal environment. Results Over 200 metabolites were identified using capillary electrophoresis and time-of-flight mass spectrometry (CE-TOFMS)-based metabolomics in the feces of antibiotic-treated and untreated mice. 16S amplicon sequencing, followed by principal component analysis (PCA) of the intestinal microbiome at each taxonomic rank, revealed differences between the antibiotic-treated and untreated groups in the first principal component in the family-, genus, and species-level analyses. These differences were similar to those observed in the PCA of the metabolome. Furthermore, a strong correlation between principal component (PC) scores of the metabolome and microbiome was observed in family-, genus-, and species-level analyses. Conclusions Lower taxonomic ranks such as family, genus, or species are preferable for 16S amplicon sequencing to investigate the correlation between the microbiome and metabolome. The correlation of PC scores between the microbiome and metabolome at lower taxonomic levels yield a simple method of integrating different “-omics” data, which provides insights regarding crosstalk between the intestinal microbiome and the host

Evolutionary paths of streptococcal and staphylococcal superantigens

<p>Abstract</p> <p>Background</p> <p><it>Streptococcus pyogenes</it> (GAS) harbors several superantigens (SAgs) in the prophage region of its genome, although <it>speG</it> and <it>smez</it> are not located in this region. The diversity of SAgs is thought to arise during horizontal transfer, but their evolutionary pathways have not yet been determined. We recently completed sequencing the entire genome of <it>S. dysgalactiae</it> subsp. <it>equisimilis</it> (SDSE), the closest relative of GAS. Although <it>speG</it> is the only SAg gene of SDSE, <it>speG</it> was present in only 50% of clinical SDSE strains and <it>smez</it> in none. In this study, we analyzed the evolutionary paths of streptococcal and staphylococcal SAgs.</p> <p>Results</p> <p>We compared the sequences of the 12–60 kb <it>speG</it> regions of nine SDSE strains, five <it>speG</it>⁺ and four <it>speG</it>^<it>–</it>. We found that the synteny of this region was highly conserved, whether or not the <it>speG</it> gene was present. Synteny analyses based on genome-wide comparisons of GAS and SDSE indicated that <it>speG</it> is the direct descendant of a common ancestor of streptococcal SAgs, whereas <it>smez</it> was deleted from SDSE after SDSE and GAS split from a common ancestor. Cumulative nucleotide skew analysis of SDSE genomes suggested that <it>speG</it> was located outside segments of steeper slopes than the stable region in the genome, whereas the region flanking <it>smez</it> was unstable, as expected from the results of GAS. We also detected a previously undescribed staphylococcal SAg gene, <it>selW</it>, and a staphylococcal SAg -like gene, <it>ssl</it>, in the core genomes of all <it>Staphylococcus aureus</it> strains sequenced. Amino acid substitution analyses, based on dN/dS window analysis of the products encoded by <it>speG</it>, <it>selW</it> and <it>ssl</it> suggested that all three genes have been subjected to strong positive selection. Evolutionary analysis based on the Bayesian Markov chain Monte Carlo method showed that each clade included at least one direct descendant.</p> <p>Conclusions</p> <p>Our findings reveal a plausible model for the comprehensive evolutionary pathway of streptococcal and staphylococcal SAgs.</p

C. elegans AMPKs promote survival and arrest germline development during nutrient stress

Summary Mechanisms controlling development, growth, and metabolism are coordinated in response to changes in environmental conditions, enhancing the likelihood of survival to reproductive maturity. Much remains to be learned about the molecular basis underlying environmental influences on these processes. C. elegans larvae enter a developmentally dormant state called L1 diapause when hatched into nutrient-poor conditions. The nematode pten homologue daf-18 is essential for maintenance of survival and germline stem cell quiescence during this period (Fukuyama et al., 2006; Sigmond et al., 2008), but the details of the signaling network(s) in which it functions remain to be elucidated. Here, we report that animals lacking both aak-1 and aak-2, which encode the two catalytic α subunits of AMP-activated protein kinase (AMPK), show reduced viability and failure to maintain mitotic quiescence in germline stem cells during L1 diapause. Furthermore, failure to arrest germline proliferation has a long term consequence; aak double mutants that have experienced L1 diapause develop into sterile adults when returned to food, whereas their continuously fed siblings are fertile. Both aak and daf-18 appear to maintain germline quiescence by inhibiting activity of the common downstream target, TORC1 (TOR Complex 1). In contrast, rescue of the lethality phenotype indicates that aak-2 acts not only in the intestine, as does daf-18, but also in neurons, likely promoting survival by preventing energy deprivation during L1 diapause. These results not only provide evidence that AMPK contributes to survival during L1 diapause in a manner distinct from that by which it controls dauer diapause, but they also suggest that AMPK suppresses TORC1 activity to maintain stem cell quiescence