Degradation of 2,3-dihydroxybenzoate by a novel meta-cleavage pathway.

2,3-Dihydroxybenzoate is the precursor in the biosynthesis of several siderophores and an important plant secondary metabolite that, in bacteria, can be degraded via meta-cleavage of the aromatic ring. The dhb cluster of Pseudomonas reinekei MT1 encodes a chimeric meta-cleavage pathway involved in the catabolism of 2,3-dihydroxybenzoate. While the first two enzymes, DhbA and DhbB, are phylogenetically related to those involved in 2,3-dihydroxy-p-cumate degradation, the subsequent steps are catalyzed by enzymes related to those involved in catechol degradation (DhbCDEFGH). Characterization of kinetic properties of DhbA extradiol dioxygenase identified 2,3-dihydroxybenzoate as the preferred substrate. Deletion of the encoding gene impedes growth of P. reinekei MT1 on 2,3-dihydroxybenzoate. DhbA catalyzes 3,4-dioxygenation with 2-hydroxy-3-carboxymuconate as the product, which is then decarboxylated by DhbB to 2-hydroxymuconic semialdehyde. This compound is then subject to dehydrogenation and further degraded to citrate cycle intermediates. Transcriptional analysis revealed genes of the dhB gene cluster to be highly expressed during growth with 2,3-dihydroxybenzoate, whereas a downstream-localized gene encoding 2-hydroxymuconic semialdehyde hydrolase, dispensable for 2,3-dihydroxybenzoate metabolism but crucial for 2,3-dihydroxy-p-cumate degradation, was only marginally expressed. This is the first report describing a gene cluster encoding enzymes for the degradation of 2,3-dihydroxybenzoate

Importance of Different tfd Genes for Degradation of Chloroaromatics by Ralstonia eutropha JMP134†

The tfdC(I)D(I)E(I)F(I,) and tfdD(II)C(II)E(II)F(II) gene modules of plasmid pJP4 of Ralstonia eutropha JMP134 encode complete sets of functional enzymes for the transformation of chlorocatechols into 3-oxoadipate, which are all expressed during growth on 2,4-dichlorophenoxyacetate (2,4-D). However, activity of tfd(I)-encoded enzymes was usually higher than that of tfd(II)-encoded enzymes, both in the wild-type strain grown on 2,4-D and in 3-chlorobenzoate-grown derivatives harboring only one tfd gene module. The tfdD(II)-encoded chloromuconate cycloisomerase exhibited special kinetic properties, with high activity against 3-chloromuconate and poor activity against 2-chloromuconate and unsubstituted muconate, thus explaining the different phenotypic behaviors of R. eutropha strains containing different tfd gene modules. The enzyme catalyzes the formation of an equilibrium between 2-chloromuconate and 5-chloro- and 2-chloromuconolactone and very inefficiently catalyzes dehalogenation to form trans-dienelactone as the major product, thus differing from all (chloro)muconate cycloisomerases described thus far

A Gene Cluster Involved in Degradation of Substituted Salicylates via ortho Cleavage in Pseudomonas sp. Strain MT1 Encodes Enzymes Specifically Adapted for Transformation of 4-Methylcatechol and 3-Methylmuconate

Pseudomonas sp. strain MT1 has recently been reported to degrade 4- and 5-chlorosalicylate by a pathway assumed to consist of a patchwork of reactions comprising enzymes of the 3-oxoadipate pathway. Genes encoding the initial steps in the degradation of salicylate and substituted derivatives were now localized and sequenced. One of the gene clusters characterized (sal) showed a novel gene arrangement, with salA, encoding a salicylate 1-hydroxylase, being clustered with salCD genes, encoding muconate cycloisomerase and catechol 1,2-dioxygenase, respectively, and was expressed during growth on salicylate and chlorosalicylate. A second gene cluster (cat), exhibiting the typical catRBCA arrangement of genes of the catechol branch of the 3-oxoadipate pathway in Pseudomonas strains, was expressed during growth on salicylate. Despite their high sequence similarities with isoenzymes encoded by the cat gene cluster, the catechol 1,2-dioxygenase and muconate cycloisomerase encoded by the sal cluster showed unusual kinetic properties. Enzymes were adapted for turnover of 4-chlorocatechol and 3-chloromuconate; however, 4-methylcatechol and 3-methylmuconate were identified as the preferred substrates. Investigation of the substrate spectrum identified 4- and 5-methylsalicylate as growth substrates, which were effectively converted by enzymes of the sal cluster into 4-methylmuconolactone, followed by isomerization to 3-methylmuconolactone. The function of the sal gene cluster is therefore to channel both chlorosubstituted and methylsubstituted salicylates into a catechol ortho cleavage pathway, followed by dismantling of the formed substituted muconolactones through specific pathways

Eradication of chronic HCV infection: improvement of dysbiosis only in patients without liver cirrhosis.

It is well accepted that liver diseases and their outcomes are associated with intestinal microbiota but causality is difficult to establish. The intestinal microbiota is altered in patients with hepatitis C. As chronic HCV infection can now be cured in almost all patients, it is an ideal model to study the influence of liver disease on the microbiota. We aimed to analyze prospectively the changes in the gut microbiome in patients who received direct acting antivirals (DAA) and achieved sustained virological response (SVR). Amplicon sequencing of the V1-V2 region in the 16S rRNA gene was performed in stool samples of patients with chronic hepatitis C. Patients in the treatment group received direct acting antivirals (n=65) whereas in the control group no DAA were given (n=33). Only patients achieving SVR were included. The alpha diversity increased numerical but not significantly from baseline to SVR24/48 (2.784±0.248 vs. 2.846±0.224; p= 0.057). When stratifying for the presence of liver cirrhosis, a significant increase in diversity was only seen in patients without cirrhosis. Differences in the microbial community structure induced by the achievement of SVR were only observed in patients without liver cirrhosis. In patients with liver cirrhosis and in the control group, no significant differences were observed. In conclusion, the achievement of SVR24/48 in patients with chronic HCV was associated with changes in the intestinal microbiota. However, these changes were only seen in patients without liver cirrhosis. A major role of liver remodeling on the intestinal microbiota is indicated by the dynamics of the intestinal microbial community structure depending on the stage of fibrosis in patients resolving chronic hepatitis C

Exploring the bacterial assemblages along the human nasal passage.

The human nasal passage, from the anterior nares through the nasal vestibule to the nasal cavities, is an important habitat for opportunistic pathogens and commensals alike. This work sampled four different anatomical regions within the human nasal passage across a large cohort of individuals (n = 79) comprising individuals suffering from chronic nasal inflammation clinically known as chronic rhinosinusitis (CRS) and individuals not suffering from inflammation (CRS-free). While individuals had their own unique bacterial fingerprint that was consistent across the anatomical regions, these bacterial fingerprints formed into distinct delineated groups comprising core bacterial members, which were consistent across all four swabbed anatomical regions irrespective of health status. The most significant observed pattern was the difference between the global bacterial profiles of swabbed and tissue biopsy samples from the same individuals, being also consistent across different anatomical regions. Importantly, no statistically significant differences could be observed concerning the global bacterial communities, any of the bacterial species or the range of diversity indices used to compare between CRS and CRS-free individuals, and between two CRS phenotypes (without nasal polyps and with nasal polyps). Thus, the role of bacteria in the pathogenesis of sinusitis remains uncertain

Gender-specific changes of the gut microbiome correlate with tumor development in murine models of pancreatic cancer

Summary: Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with a dismal outcome. To improve understanding of sequential microbiome changes during PDAC development we analyzed mouse models of pancreatic carcinogenesis (KC mice recapitulating pre-invasive PanIN formation, as well as KPC mice recapitulating invasive PDAC) during early tumor development and subsequent tumor progression. Diversity and community composition were analyzed depending on genotype, age, and gender. Both mouse models demonstrated concordant abundance changes of several genera influenced by one or more of the investigated factors. Abundance was significantly impacted by gender, highlighting the need to further elucidate the impact of gender differences. The findings underline the importance of the microbiome in PDAC development and indicate that microbiological screening of patients at risk and targeting the microbiome in PDAC development may be feasible in future

High-resolution taxonomic profiling of the subgingival microbiome for biomarker discovery and periodontitis diagnosis.

The oral microbiome plays a key role for caries, periodontitis, and systemic diseases. A method for rapid, high-resolution, robust taxonomic profiling of subgingival bacterial communities for early detection of periodontitis biomarkers would therefore be a useful tool for individualized medicine. Here, we used Illumina sequencing of the V1-V2 and V5-V6 hypervariable regions of the 16S rRNA gene. A sample stratification pipeline was developed in a pilot study of 19 individuals, 9 of whom had been diagnosed with chronic periodontitis. Five hundred twenty-three operational taxonomic units (OTUs) were obtained from the V1-V2 region and 432 from the V5-V6 region. Key periodontal pathogens like Porphyromonas gingivalis, Treponema denticola, and Tannerella forsythia could be identified at the species level with both primer sets. Principal coordinate analysis identified two outliers that were consistently independent of the hypervariable region and method of DNA extraction used. The linear discriminant analysis (LDA) effect size algorithm (LEfSe) identified 80 OTU-level biomarkers of periodontitis and 17 of health. Health- and periodontitis-related clusters of OTUs were identified using a connectivity analysis, and the results confirmed previous studies with several thousands of samples. A machine learning algorithm was developed which was trained on all but one sample and then predicted the diagnosis of the left-out sample (jackknife method). Using a combination of the 10 best biomarkers, 15 of 17 samples were correctly diagnosed. Training the algorithm on time-resolved community profiles might provide a highly sensitive tool to detect the onset of periodontitis