Host S-nitrosylation inhibits clostridial small molecule-activated glucosylating toxins

The global prevalence of severe Clostridium difficile infection highlights the profound clinical significance of clostridial glucosylating toxins. Virulence is dependent on the autoactivation of a toxin cysteine protease, which is promoted by the allosteric cofactor inositol hexakisphosphate (InsP(6)). Host mechanisms that protect against such exotoxins are poorly understood. It is increasingly appreciated that the pleiotropic functions attributed to nitric oxide (NO), including host immunity, are in large part mediated by S-nitrosylation of proteins. Here we show that C. difficile toxins are S-nitrosylated by the infected host and that S-nitrosylation attenuates virulence by inhibiting toxin self-cleavage and cell entry. Notably, InsP(6)- and inositol pyrophosphate (InsP(7))-induced conformational changes in the toxin enabled host S-nitrosothiols to transnitrosylate the toxin catalytic cysteine, which forms part of a structurally conserved nitrosylation motif. Moreover, treatment with exogenous InsP(6) enhanced the therapeutic actions of oral S-nitrosothiols in mouse models of C. difficile infection. Allostery in bacterial proteins has thus been successfully exploited in the evolutionary development of nitrosothiol-based innate immunity and may provide an avenue to new therapeutic approaches.     

Blood profile of proteins and steroid hormones predicts weight change after weight loss with interactions of dietary protein level and glycemic index

Background

Weight regain after weight loss is common. In the Diogenes dietary intervention study, high protein and low glycemic index (GI) diet improved weight maintenance.

Objective

To identify blood predictors for weight change after weight loss following the dietary intervention within the Diogenes study.

Design

Blood samples were collected at baseline and after 8-week low caloric diet-induced weight loss from 48 women who continued to lose weight and 48 women who regained weight during subsequent 6-month dietary intervention period with 4 diets varying in protein and GI levels. Thirty-one proteins and 3 steroid hormones were measured.

Results

Angiotensin I converting enzyme (ACE) was the most important predictor. Its greater reduction during the 8-week weight loss was related to continued weight loss during the subsequent 6 months, identified by both Logistic Regression and Random Forests analyses. The prediction power of ACE was influenced by immunoproteins, particularly fibrinogen. Leptin, luteinizing hormone and some immunoproteins showed interactions with dietary protein level, while interleukin 8 showed interaction with GI level on the prediction of weight maintenance. A predictor panel of 15 variables enabled an optimal classification by Random Forests with an error rate of 24±1%. A logistic regression model with independent variables from 9 blood analytes had a prediction accuracy of 92%.

Conclusions

A selected panel of blood proteins/steroids can predict the weight change after weight loss. ACE may play an important role in weight maintenance. The interactions of blood factors with dietary components are important for personalized dietary advice after weight loss.

Registration

ClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT00390637","term_id":"NCT00390637"}}NCT00390637     

Assessment of the Relationship between Self-Declared Ethnicity,Mitochondrial Haplogroups and Genomic Ancestry in Brazilian Individuals

In populations that have a high degree of admixture, such as in Brazil, the sole use of ethnicity self-declaration information is not a good method for classifying individuals regarding their ethnicity. Here, we evaluate the relationship of self-declared ethnicities with genomic ancestry and mitochondrial haplogroups in 492 individuals from southeastern Brazil. Mitochondrial haplogroups were obtained by analyzing the hypervariable regions of the mitochondrial DNA (mtDNA), and the genomic ancestry was obtained using 48 autosomal insertion-deletion ancestry informative markers (AIM). Of the 492 individuals, 74.6% self-declared as White, 13.8% as Brown and 10.4% as Black. Classification of the mtDNA haplogroups showed that 46.3% had African mtDNA, and the genomic ancestry analysis showed that the main contribution was European (57.4%). When we looked at the distribution of mtDNA and genomic ancestry according to the self-declared ethnicities from 367 individuals who self-declared as White, 37.6% showed African mtDNA, and they had a high contribution of European genomic ancestry (63.3%) but also a significant contribution of African ancestry (22.2%). Of the 68 individuals who self-declared as Brown, 25% showed Amerindian mtDNA and similar contribution of European and African genomic ancestries. Of the 51 subjects who self-declared as black, 80.4% had African mtDNA, and the main contribution of genomic ancestry was African (55.6%), but they also had a significant proportion of European ancestry (32.1%). The Brazilian population had a uniform degree of Amerindian genomic ancestry, and it was only with the use of genetic markers (autosomal or mitochondrial) that we were able to capture Amerindian ancestry information. Additionally, it was possible to observe a high degree of heterogeneity in the ancestry for both types of genetic markers, which shows the high genetic admixture that is present in the Brazilian population. We suggest that in epidemiological studies, the use of these methods could provide complementary information.     

Structure of the Shigella dysenteriae haem transport locus and its phylogenetic distribution in enteric bacteria

The ability to transport and use haemin as an iron source is frequently observed in clinical isolates of Shigella spp. and pathogenic Escherichia coli . We found that many of these haem-utilizing E. coli strains contain a gene that hybridizes at high stringency to the S. dysenteriae type 1 haem receptor gene, shuA . These shuA -positive strains belong to multiple phylogenetic groups and include clinical isolates from enteric, urinary tract and systemic infections. The distribution of shuA in these strains suggests horizontal transfer of the haem transport locus. Some haem-utilizing pathogenic E. coli strains did not hybridize with shuA , so at least one other haem transport system is present in this group. We also characterized the chromosomal region containing shuA in S. dysenteriae . The shuA gene is present in a discrete locus, designated the haem transport locus, containing eight open reading frames. Several of the proteins encoded in this locus participate with ShuA in haem transport, as a Salmonella typhimurium strain containing the entire haem transport locus used haem much more efficiently than the same strain containing only shuA . The haem transport locus is not present in E. coli K-12 strains, but the sequences flanking the haem transport locus in S. dysenteriae matched those at the 78.7 minute region of E. coli K-12. The junctions and flanking sequences in the shuA -positive pathogenic E. coli strains tested were nearly identical to those in S. dysenteriae , indicating that, in these strains, the haem transport locus has an organization similar to that in S. dysenteriae , and it is located in the same relative position on the chromosome.     

Disturbances, elevation, topography and spatial proximity drive vegetation patterns along an altitudinal gradient of a top biodiversity hotspot

The correlation between vegetation patterns (species distribution and richness) and altitudinal variation has been widely reported for tropical forests, thereby providing theoretical basis for biodiversity conservation. However, this relationship may have been oversimplified, as many other factors may influence vegetation patterns, such as disturbances, topography and geographic distance. Considering these other factors, our primary question was: is there a vegetation pattern associated with substantial altitudinal variation (10–1,093 m a.s.l.) in the Atlantic Rainforest—a top hotspot for biodiversity conservation—and, if so, what are the main factors driving this pattern? We addressed this question by sampling 11 1-ha plots, applying multivariate methods, correlations and variance partitioning. The Restinga (forest on sandbanks along the coastal plains of Brazil) and a lowland area that was selectively logged 40 years ago were floristically isolated from the other plots. The maximum species richness (>200 spp. per hectare) occurred at approximately 350 m a.s.l. (submontane forest). Gaps, multiple stemmed trees, average elevation and the standard deviation of the slope significantly affected the vegetation pattern. Spatial proximity also influenced the vegetation pattern as a structuring environmental variable or via dispersal constraints. Our results clarify, for the first time, the key variables that drive species distribution and richness across a large altitudinal range within the Atlantic Rainforest.     

Interspecific synchrony of seabird population growth rate and breeding success

Environmental variability can destabilize communities by causing correlated interspecific fluctuations that weaken the portfolio effect, yet evidence of such a mechanism is rare in natural systems. Here, we ask whether the population dynamics of similar sympatric species of a seabird breeding community are synchronized, and if these species have similar exceptional responses to environmental variation. We used a 24‐year time series of the breeding success and population growth rate of a marine top predator species group to assess the degree of synchrony between species demography. We then developed a novel method to examine the species group – all species combined – response to environmental variability, in particular, whether multiple species experience similar, pronounced fluctuations in their demography. Multiple species were positively correlated in breeding success and growth rate. Evidence of “exceptional” years was found, where the species group experienced pronounced fluctuations in their demography. The synchronous response of the species group was negatively correlated with winter sea surface temperature of the preceding year for both growth rate and breeding success. We present evidence for synchronous, exceptional responses of a species group that are driven by environmental variation. Such species covariation destabilizes communities by reducing the portfolio effect, and such exceptional responses may increase the risk of a state change in this community. Our understanding of the future responses to environmental change requires an increased focus on the short‐term fluctuations in demography that are driven by extreme environmental variability.