Project description:Macropinocytosis is a unique pathway of endocytosis characterised by the nonspecific internalisation of large amounts of extracellular fluid, solutes and membrane in large endocytic vesicles known as macropinosomes. Macropinocytosis is important in a range of physiological processes, including antigen presentation, nutrient sensing, recycling of plasma proteins, migration and signalling. It has become apparent in recent years from the study of specialised cells that there are multiple pathways of macropinocytosis utilised by different cell types, and some of these pathways are triggered by different stimuli. Understanding the physiological function of macropinocytosis requires knowledge of the regulation and fate of the macropinocytosis pathways in a range of cell types. Here, we compare the mechanisms of macropinocytosis in different primary and immortalised cells, identify the gaps in knowledge in the field and discuss the potential approaches to analyse the function of macropinocytosis in vivo.
Project description:ObjectiveThe classification of anorexia nervosa (AN) into subtypes is relevant due to their different symptomatology. However, subtypes (restricting type: AN-R; purging type: AN-P) differ also in terms of their personality functioning. Knowledge about these differences would allow for better treatment stratification. A pilot study indicated differences in structural abilities that can be assessed by the operationalized psychodynamic diagnosis (OPD) system. The aim of this study was therefore to systematically explore differences in personality functioning and personality between the two AN subtypes and bulimia nervosa (BN) using three personality (functioning) constructs.MethodsA total of N = 110 inpatients with AN-R (n = 28), AN-P (n = 40), or BN (n = 42) were recruited in three clinics for psychosomatic medicine. Assignment to the three groups was performed using a comprehensive questionnaire validated for diagnostic purposes (Munich-ED-Quest). Personality functioning was examined using OPD Structure Questionnaire (OPD-SQ), personality by using the Personality Inventory for DSM-5-Brief Form and Big Five Inventory-10. (M)ANOVAs were used to examine differences across eating disorder groups. In addition, correlation and regression analyses were conducted.ResultsWe observed differences on several sub- and main scales of the OPD-SQ. Whereas patients with BN showed the lowest levels, AN-R patients displayed the highest levels of personality functioning. On some sub- and main scales, such as "affect tolerance," the subtypes of AN differed from BN, whereas on the scale "affect differentiation," AN-R, differed from the other two groups. The total eating disorder pathology score of the Munich-ED-Quest best predicted overall personality structure [stand. β = 0.650; t(104) = 6.666; p < 0.001] and self-regulation [stand. β = 0.449; t(104) = 3.628; p < 0.001].DiscussionOur findings confirm most of the results of the pilot study. These findings can facilitate the development of stratified treatment approaches for eating disorders.
Project description:IntroductionMicroorganisms play an important role in the multifunctionality of soil ecosystems. Soil microbial diversity and functions have a great impact on plant growth and development. The interactions between tea trees and soil microbiota can be linked with planting patterns and management strategies, whose effects on soil microbial community structure and metabolites are still unclear.MethodsHere we used amplicon sequencing and metabolomic analysis to investigate the differences in soil microbial composition and metabolites among three tea production systems: organic, non-organic, and intercropping.ResultsWe detected significant differences among the three systems and found that Firmicutes, Proteobacteria, Acidobacteriota, Actinobacteriota and Chloroflexi were the main bacteria in the three soil groups, although they varied in relative abundance. Acidobacteria bacterium increased significantly in the organic and intercropping groups. For fungi, Ascomycota and Basidiomycota were the main differential fungal phyla. Fungi alpha-diversity in the non-organic group was significantly higher than that in the other two groups, and was correlated with multiple soil physical and chemical factors. Moreover, network analysis showed that bacteria and fungi were strongly correlated. The changes in soil microorganisms caused by management and planting patterns may affect soil quality through corresponding changes in metabolites. Metabolomic analysis showed differences in metabolite composition among different groups. It was also found that the arachidonic acid metabolic pathway was affected by changes in soil microorganisms, and may further affect soil quality in an essential manner.DiscussionPlanting patterns and management strategies may significantly affect soil microorganisms and therefore metabolites. Changes in soil microorganisms, especially in fungi, may alter soil quality by affecting soil physicochemical properties and metabolites. This study will provide new insights into soil quality monitoring from a microbiological perspective.
Project description:Tropical peatlands, which play a crucial role in the maintenance of different ecosystem services, are increasingly drained for agriculture, forestry, peat extraction and human settlement purposes. The present study investigated the differences between natural and drained sites of a tropical peatland in the community structure of soil bacteria and archaea and their potential to perform nitrogen transformation processes. The results indicate significant dissimilarities in the structure of soil bacterial and archaeal communities as well as nirK, nirS, nosZ, nifH and archaeal amoA gene-possessing microbial communities. The reduced denitrification and N2-fixing potential was detected in the drained tropical peatland soil. In undisturbed peatland soil, the N2O emission was primarily related to nirS-type denitrifiers and dissimilatory nitrate reduction to ammonium, while the conversion of N2O to N2 was controlled by microbes possessing nosZ clade I genes. The denitrifying microbial community of the drained site differed significantly from the natural site community. The main reducers of N2O were microbes harbouring nosZ clade II genes in the drained site. Additionally, the importance of DNRA process as one of the controlling mechanisms of N2O fluxes in the natural peatlands of the tropics revealed from the results of the study.
Project description:Bacterial communities that enrich in high-temperature Daqu are important for the Chinese maotai-flavor liquor brewing process. However, the bacterial communities in three different types of high-temperature Daqu (white Daqu, black Daqu, and yellow Daqu) are still undercharacterized. In this study, the bacterial diversity of three different types of high-temperature Daqu was investigated using Illumina MiSeq high-throughput sequencing. The bacterial community of high-temperature Daqu is mainly composed of thermophilic bacteria, and seven bacterial phyla along with 262 bacterial genera were identified in all 30 high-temperature Daqu samples. Firmicutes, Actinobacteria, Proteobacteria, and Acidobacteria were the dominant bacterial phyla in high-temperature Daqu samples, while Thermoactinomyces, Staphylococcus, Lentibacillus, Bacillus, Kroppenstedtia, Saccharopolyspora, Streptomyces, and Brevibacterium were the dominant bacterial genera. The bacterial community structure of three different types of high-temperature Daqu was significantly different (p < .05). In addition, the results of microbiome phenotype prediction by BugBase and bacterial functional potential prediction using PICRUSt show that bacteria from different types of high-temperature Daqu have similar functions as well as phenotypes, and bacteria in high-temperature Daqu have vigorous metabolism in the transport and decomposition of amino acids and carbohydrates. These results offer a reference for the comprehensive understanding of bacterial diversity of high-temperature Daqu.
Project description:BACKGROUND: Soil bacteria are important drivers for nearly all biogeochemical cycles in terrestrial ecosystems and participate in most nutrient transformations in soil. In contrast to the importance of soil bacteria for ecosystem functioning, we understand little how different management types affect the soil bacterial community composition. METHODOLOGY/PRINCIPAL FINDINGS: We used pyrosequencing-based analysis of the V2-V3 16S rRNA gene region to identify changes in bacterial diversity and community structure in nine forest and nine grassland soils from the Schwäbische Alb that covered six different management types. The dataset comprised 598,962 sequences that were affiliated to the domain Bacteria. The number of classified sequences per sample ranged from 23,515 to 39,259. Bacterial diversity was more phylum rich in grassland soils than in forest soils. The dominant taxonomic groups across all samples (>1% of all sequences) were Acidobacteria, Alphaproteobacteria, Actinobacteria, Betaproteobacteria, Deltaproteobacteria, Gammaproteobacteria, and Firmicutes. Significant variations in relative abundances of bacterial phyla and proteobacterial classes, including Actinobacteria, Firmicutes, Verrucomicrobia, Cyanobacteria, Gemmatimonadetes and Alphaproteobacteria, between the land use types forest and grassland were observed. At the genus level, significant differences were also recorded for the dominant genera Phenylobacter, Bacillus, Kribbella, Streptomyces, Agromyces, and Defluviicoccus. In addition, soil bacterial community structure showed significant differences between beech and spruce forest soils. The relative abundances of bacterial groups at different taxonomic levels correlated with soil pH, but little or no relationships to management type and other soil properties were found. CONCLUSIONS/SIGNIFICANCE: Soil bacterial community composition and diversity of the six analyzed management types showed significant differences between the land use types grassland and forest. Furthermore, bacterial community structure was largely driven by tree species and soil pH.
Project description:Understanding biological diversity and distribution patterns at multiple spatial scales is a central issue in ecology. Here, we investigated the biogeographical patterns of functional genes in soil microbes from 24 arctic heath sites using GeoChip-based metagenomics and principal coordinates of neighbour matrices (PCNM)-based analysis. Functional gene richness varied considerably among sites, while the proportions of each major functional gene category were evenly distributed. Functional gene composition varied significantly at most medium and broad spatial scales, and the PCNM analyses indicated that 14-20% of the variation in total and major functional gene categories could be attributed primarily to relatively broad-scale spatial effects that were consistent with broad-scale variation in soil pH and total nitrogen. The combination of variance partitioning and multi-scales analysis indicated that spatial distance effects contributed 12% to variation in functional gene composition,whereas environmental factors contributed only 3%. This relatively strong influence of spatial as compared to environmental variation in determining functional gene distributions contrasts sharply with typical microbial phylotype/species-based biogeographical patterns in the Arctic and elsewhere. Our results suggest that the distributions of soil functional genes cannot be predicted from phylogenetic distributions because spatial factors associated with historical contingencies are relatively important determinants of their biogeography.
Project description:In analogy to proteins, the function of RNA depends on its structure and dynamics, which are encoded in the linear sequence. While there are numerous methods for computational prediction of protein 3D structure from sequence, there have been very few such methods for RNA. This review discusses template-based and template-free approaches for macromolecular structure prediction, with special emphasis on comparison between the already tried-and-tested methods for protein structure modeling and the very recently developed "protein-like" modeling methods for RNA. We highlight analogies between many successful methods for modeling of these two types of biological macromolecules and argue that RNA 3D structure can be modeled using "protein-like" methodology. We also highlight the areas where the differences between RNA and proteins require the development of RNA-specific solutions.
Project description:In Arctic regions, thawing permafrost soils are projected to release 50 to 250 Gt of carbon by 2100. This data is mostly derived from carbon-rich wetlands, although 71% of this carbon pool is stored in faster-thawing mineral soils, where ecosystems close to the outer boundaries of permafrost regions are especially vulnerable. Although extensive data exists from currently thawing sites and short-term thawing experiments, investigations of the long-term changes following final thaw and co-occurring drainage are scarce. Here we show ecosystem changes at two comparable tussock tundra sites with distinct permafrost thaw histories, representing 15 and 25 years of natural drainage, that resulted in a 10-fold decrease in CH4 emissions (3.2 ± 2.2 vs. 0.3 ± 0.4 mg C-CH4 m-2 day-1 ), while CO2 emissions were comparable. These data extend the time perspective from earlier studies based on short-term experimental drainage. The overall microbial community structures did not differ significantly between sites, although the drier top soils at the most advanced site led to a loss of methanogens and their syntrophic partners in surface layers while the abundance of methanotrophs remained unchanged. The resulting deeper aeration zones likely increased CH4 oxidation due to the longer residence time of CH4 in the oxidation zone, while the observed loss of aerenchyma plants reduced CH4 diffusion from deeper soil layers directly to the atmosphere. Our findings highlight the importance of including hydrological, vegetation and microbial specific responses when studying long-term effects of climate change on CH4 emissions and underscores the need for data from different soil types and thaw histories.