Project description:Background. Hematopoietic cell transplantation (HCT) is a potentially curative therapy for a wide range of pediatric malignant and nonmalignant diseases. However, complications, including blood stream infection (BSI) remain a major cause of morbidity and mortality. While certain bacteria that are abundant in the oral microbiome, such as S. mitis, can cause BSI, the role of the oral microbial community in the etiology of BSI is not well understood. The finding that the use of xylitol wipes, which specifically targets the cariogenic bacteria S. mutans is associated with reduced BSI in pediatric patients, lead us to investigate dental caries as a risk factor for BSI. Methods. A total of 41 pediatric patients admitted for allogenic or autologous HCT, age 8 months to 25 years, were enrolled. Subjects with high dental caries risk were identified as those who had dental restorations completed within 2 months of admission for transplant, or who had untreated decay. Fisher’s exact test was used to determine if there was a significant association between caries risk and BSI. Dental plaque and saliva were collected on a cotton swab from a subset of 4 high caries risk (HCR) and 4 low caries risk (LCR) children following pretransplant conditioning. 16SrRNA sequencing was used to compare the microbiome of HCR and LCR subjects and to identify microbes that were significantly different between the 2 groups. Results. There was a statistically significant association between caries risk and BSI (p<0.035) (Fisher’s exact test). Multivariate logistic regression analysis showed children in the high dental caries risk group were 21.39 times more likely to have BSI, with no significant effect of age or mucositis severity. HCR subjects showed significantly reduced microbial alpha diversity as compared to LCR subjects. LEfse metagenomic analyses, showed the oral microbiome in HCR children enriched in order Lactobacillales. This order includes Streptococcus and Lactobacillus, both which contain bacteria primarily associated with dental caries. Discussion. These findings support the possibility that the cariogenic microbiome can enhance the risk of BSI in pediatric populations. Future metagenomic analyses to measure microbial differences at, before, and after conditioning related to caries risk, may further unravel the complex relationship between the oral microbiome, and whether it affects health outcomes such as BSI.
Project description:Xiangjiang River (Hunan, China) has been contaminated with heavy metal for several decades by surrounding factories. However, little is known about the influence of a gradient of heavy metal contamination on the diversity, structure of microbial functional gene in sediment. To deeply understand the impact of heavy metal contamination on microbial community, a comprehensive functional gene array (GeoChip 5.0) has been used to study the functional genes structure, composition, diversity and metabolic potential of microbial community from three heavy metal polluted sites of Xiangjiang River. Three groups of samples, A, B and C. Every group has 3 replicates.
Project description:The present study focuses on the use of a metaproteomic approach to analyse Black Extrinsic Tooth Stains, a specific type of pigmented extrinsic substance, in a cohort of 96 Children. Metaproteomics is a powerful emerging technology that successfully enabled human protein and bacterial identification of this specific dental biofilm using mass spectrometry. 1600 bacterial proteins were identified in black stains (BS) samples and 2058 proteins in dental plaque (DP) samples whereas 607 and 582 human proteins identified in (BS and DP, respectively). 132 genera bacteria in black stains and dental plaque were identified using phylopeptidomic analysis, showing prevalence of Rothia, Kingella, Nesseria and Pseudopropionibatcterium in black stains samples. We additionally confirmed the metaproteomic approach by performing 16S rRNA. In this work, we showed an interesting diversity of the microbiota and proteome including significant difference between Black stain and dental plaque samples.
Project description:Xiangjiang River (Hunan, China) has been contaminated with heavy metal for several decades by surrounding factories. However, little is known about the influence of a gradient of heavy metal contamination on the diversity, structure of microbial functional gene in sediment. To deeply understand the impact of heavy metal contamination on microbial community, a comprehensive functional gene array (GeoChip 5.0) has been used to study the functional genes structure, composition, diversity and metabolic potential of microbial community from three heavy metal polluted sites of Xiangjiang River.
Project description:Samples of oil and production water were collected from five wells of the Qinghai Oilfield, China, and subjected to GeoChip hybridization experiments for microbial functional diversity profiling. Unexpectedly, a remarkable microbial diversity in oil samples, which was higher than that in the corresponding water samples, was observed, thus challenging previously believed assumptions about the microbial diversity in this ecosystem. Hierarchical clustering separated oil and water samples, thereby indicating distinct functional structures in the samples. Genes involved in the degradation of hydrocarbons, organic remediation, stress response, and carbon cycling were significantly abundant in crude oil, which is consistent with their important roles in residing in oil. Association analysis with environmental variables suggested that oil components comprising aromatic hydrocarbons, aliphatic hydrocarbons, and a polar fraction with nitrogen-, sulfur-, and oxygen-containing compounds were mainly influential on the structure of the microbial community. Furthermore, a comparison of microbial communities in oil samples indicated that the structures were depth/temperature-dependent. To our knowledge, this is the first thorough study to profile microbial functional diversity in crude oil samples. From the Qinghai Oilfield located in the Tibetan Plateau, northwest China, oil production mixtures were taken from four oil production wells (No. 813, 516, 48 and 27) and one injection well (No. 517) in the Yue-II block. The floating oil and water phases of the production mixtures were separated overnight by gravitational separation. Subsequently, the microbial community and the characteristics of the water solution (W813, W516, W48, and W27) and floating crude oil (O813, O516, O48, and O27) samples were analyzed. A similar analysis was performed with the injection water solution (W517).
Project description:Monitoring microbial communities can aid in understanding the state of these habitats. Environmental DNA (eDNA) techniques provide efficient and comprehensive monitoring by capturing broader diversity. Besides structural profiling, eDNA methods allow the study of functional profiles, encompassing the genes within the microbial community. In this study, three methodologies were compared for functional profiling of microbial communities in estuarine and coastal sites in the Bay of Biscay. The methodologies included inference from 16S metabarcoding data using Tax4Fun, GeoChip microarrays, and shotgun metagenomics.
Project description:Soil microbial community is a complex blackbox that requires a multi-conceptual approach (Hultman et al., 2015; Bastida et al., 2016). Most methods focus on evaluating total microbial community and fail to determine its active fraction (Blagodatskaya & Kuzyakov 2013). This issue has ecological consequences since the behavior of the active community is more important (or even essential) and can be different to that of the total community. The sensitivity of the active microbial community can be considered as a biological mechanism that regulates the functional responses of soil against direct (i.e. forest management) and indirect (i.e. climate change) human-induced alterations. Indeed, it has been highglihted that the diversity of the active community (analyzed by metaproteomics) is more connected to soil functionality than the that of the total community (analyzed by 16S rRNA gene and ITS sequencing) (Bastida et al., 2016). Recently, the increasing application of soil metaproteomics is providing unprecedented, in-depth characterisation of the composition and functionality of active microbial communities and overall, allowing deeper insights into terrestrial microbial ecology (Chourey et al., 2012; Bastida et al., 2015, 2016; Keiblinger et al., 2016). Here, we predict the responsiveness of the soil microbial community to forest management in a climate change scenario. Particularly, we aim: i) to evaluate the impacts of 6-years of induced drought on the diversity, biomass and activity of the microbial community in a semiarid forest ecocosystem; and ii) to discriminate if forest management (thinning) influences the resistance of the microbial community against induced drought. Furthermore, we aim to ascertain if the functional diversity of each phylum is a trait that can be used to predict changes in microbial abundance and ecosystem functioning.
Project description:Soil transplant serves as a proxy to simulate climate change in realistic climate regimes. Here, we assessed the effects of climate warming and cooling on soil microbial communities, which are key drivers in Earth’s biogeochemical cycles, four years after soil transplant over large transects from northern (N site) to central (NC site) and southern China (NS site) and vice versa. Four years after soil transplant, soil nitrogen components, microbial biomass, community phylogenetic and functional structures were altered. Microbial functional diversity, measured by a metagenomic tool named GeoChip, and phylogenetic diversity are increased with temperature, while microbial biomass were similar or decreased. Nevertheless, the effects of climate change was overridden by maize cropping, underscoring the need to disentangle them in research. Mantel tests and canonical correspondence analysis (CCA) demonstrated that vegetation, climatic factors (e.g., temperature and precipitation), soil nitrogen components and CO2 efflux were significantly correlated to the microbial community composition. Further investigation unveiled strong correlations between carbon cycling genes and CO2 efflux in bare soil but not cropped soil, and between nitrogen cycling genes and nitrification, which provides mechanistic understanding of these microbe-mediated processes and empowers an interesting possibility of incorporating bacterial gene abundance in greenhouse gas emission modeling.
Project description:Tibet is one of the most threatened regions by climate warming, thus understanding how its microbial communities function may be of high importance for predicting microbial responses to climate changes. Here, we report a study to profile soil microbial structural genes, which infers functional roles of microbial communities, along four sites/elevations of a Tibetan mountainous grassland, aiming to explore potential microbial responses to climate changes via a strategy of space-for-time substitution. Using a microarray-based metagenomics tool named GeoChip 4.0, we showed that microbial communities were distinct for most but not all of the sites. Substantial variations were apparent in stress, N and C cycling genes, but they were in line with the functional roles of these genes. Cold shock genes were more abundant at higher elevations. Also, gdh converting ammonium into urea was more abundant at higher elevations while ureC converting urea into ammonium was less abundant, which was consistent with soil ammonium contents. Significant correlations were observed between N-cycling genes (ureC, gdh and amoA) and nitrous oxide flux, suggesting that they contributed to community metabolism. Lastly, we found by CCA, Mantel tests and the similarity tests that soil pH, temperature, NH4+–N and vegetation diversity accounted for the majority (81.4%) of microbial community variations, suggesting that these four attributes were major factors affecting soil microbial communities. Based on these observations, we predict that climate changes in the Tibetan grasslands are very likely to change soil microbial community functional structure, with particular impacts on microbial N cycling genes and consequently microbe-mediated soil N dynamics.