Variations in microbiome composition of sewer biofilms due to ferrous and ferric iron dosing

During transport of wastewater in force mains, sulphide and possibly methane formation take place due to prokaryotic activity. Sulphide has several detrimental effects and addition of ferrous or ferric iron for abatement by precipitation is commonly applied. Precipitation stoichiometry and efficiency of this process have been investigated in detail. However, it is largely unknown how ferrous and ferric iron influence prokaryotic populations of sewer biofilms. The microbiomes of iron-treated force main biofilms were, together with an untreated control, examined by sequencing of the 16S rDNA V3+ V4 regions. Differences in distribution and abundance of several bacterial and archaeal genera were observed, indicating that treatment with ferrous and ferric iron for sulphide abatement differentially changed sewer force main microbiomes. Furthermore, differences at the functional level (KEGG orthologs, KOs) indicate that ferrous and ferric iron treatment possibly can decrease methane formation, whereas functions related to dissimilatory sulphate reduction seemed unaffected

Local diversity of heathland Cercozoa explored by in-depth sequencing

Cercozoa are abundant free-living soil protozoa and quantitatively important in soil food webs; yet, targeted high-throughput sequencing (HTS) has not yet been applied to this group. Here we describe the development of a targeted assay to explore Cercozoa using HTS, and we apply this assay to measure Cercozoan community response to drought in a Danish climate manipulation experiment (two sites exposed to artificial drought, two unexposed). Based on a comparison of the hypervariable regions of the 18S ribosomal DNA of 193 named Cercozoa, we concluded that the V4 region is the most suitable for group-specific diversity analysis. We then designed a set of highly specific primers (encompassing ~270 bp) for 454 sequencing. The primers captured all major cercozoan groups; and >95% of the obtained sequences were from Cercozoa. From 443 350 high-quality short reads (>300 bp), we recovered 1585 operational taxonomic units defined by >95% V4 sequence similarity. Taxonomic annotation by phylogeny enabled us to assign >95% of our reads to order level and ~85% to genus level despite the presence of a large, hitherto unknown diversity. Over 40% of the annotated sequences were assigned to Glissomonad genera, whereas the most common individually named genus was the euglyphid Trinema. Cercozoan diversity was largely resilient to drought, although we observed a community composition shift towards fewer testate amoebae

Microbial diversity and putative opportunistic pathogens in dishwasher biofilm communities

Extreme habitats are not only limited to natural environments, but also exist in manmade systems, for instance, household appliances such as dishwashers. Limiting factors, such as high temperatures, high and low pHs, high NaCl concentrations, presence of detergents, and shear force from water during washing cycles, define microbial survival in this extreme system. Fungal and bacterial diversity in biofilms isolated from rubber seals of 24 different household dishwashers was investigated using next-generation sequencing. Bacterial genera such as Pseudomonas, Escherichia, and Acinetobacter, known to include opportunistic pathogens, were represented in most samples. The most frequently encountered fungal genera in these samples belonged to Candida, Cryptococcus, and Rhodotorula, also known to include opportunistic pathogenic representatives. This study showed how specific conditions of the dishwashers impact the abundance of microbial groups and investigated the interkingdom and intrakingdom interactions that shape these biofilms. The age, usage frequency, and hardness of incoming tap water of dishwashers had significant impact on bacterial and fungal community compositions. Representatives of Candida spp. were found at the highest prevalence (100%) in all dishwashers and are assumed to be one of the first colonizers in recently purchased dishwashers. Pairwise correlations in tested microbiomes showed that certain bacterial groups cooccur, as did the fungal groups. In mixed bacterial-fungal biofilms, early adhesion, contact, and interactions were vital in the process of biofilm formation, where mixed complexes of bacteria and fungi could provide a preliminary biogenic structure for the establishment of these biofilms. IMPORTANCE Worldwide demand for household appliances, such as dishwashers and washing machines, is increasing, as is the number of immunocompromised individuals. The harsh conditions in household dishwashers should prevent the growth of most microorganisms. However, our research shows that persisting polyextremotolerant groups of microorganisms in household appliances are well established under these unfavorable conditions and supported by the biofilm mode of growth. The significance of our research is in identifying the microbial composition of biofilms formed on dishwasher rubber seals, how diverse abiotic conditions affect microbiota, and which key microbial members were represented in early colonization and contamination of dishwashers, as these appliances can present a source of domestic cross-contamination that leads to broader medical impacts

Whole-genome sequence of <i>Pseudomonas fluorescens</i> EK007-RG4, a promising biocontrol agent against a broad range of bacteria, including the fire blight bacterium <i>Erwinia amylovora</i>

Here, we report the first draft whole-genome sequence of Pseudomonas fluorescens strain EK007-RG4, which was isolated from the phylloplane of a pear tree. P. fluorescens EK007-RG4 displays strong antagonism against Erwinia amylovora, the causal agent for fire blight disease, in addition to several other pathogenic and non-pathogenic bacteria

Warming, shading and a moth outbreak reduce tundra carbon sink strength dramatically by changing plant cover and soil microbial activity

Abstract Future increases in temperature and cloud cover will alter plant growth and decomposition of the large carbon pools stored in Arctic soils. A better understanding of interactions between above- and belowground processes and communities of plants and microorganisms is essential for predicting Arctic ecosystem responses to climate change. We measured ecosystem CO2 fluxes during the growing season for seven years in a dwarf-shrub tundra in West Greenland manipulated with warming and shading and experiencing a natural larvae outbreak. Vegetation composition, soil fungal community composition, microbial activity, and nutrient availability were analyzed after six years of treatment. Warming and shading altered the plant community, reduced plant CO2 uptake, and changed fungal community composition. Ecosystem carbon accumulation decreased during the growing season by 61% in shaded plots and 51% in warmed plots. Also, plant recovery was reduced in both manipulations following the larvae outbreak during the fifth treatment year. The reduced plant recovery in manipulated plots following the larvae outbreak suggests that climate change may increase tundra ecosystem sensitivity to disturbances. Also, plant community changes mediated via reduced light and reduced water availability due to increased temperature can strongly lower the carbon sink strength of tundra ecosystems

Community structure of the metabolically active rumen bacterial and archaeal communities of dairy cows over the transition period

Dairy cows experience dramatic changes in host physiology from gestation to lactation period and dietary switch from high-forage prepartum diet to high-concentrate postpartum diet over the transition period (parturition +/- three weeks). Understanding the community structure and activity of the rumen microbiota and its associative patterns over the transition period may provide insight for e.g. improving animal health and production. In the present study, rumen samples from ten primiparous Holstein dairy cows were collected over seven weeks spanning the transition period. Total RNA was extracted from the rumen samples and cDNA thereof was subsequently used for characterizing the metabolically active bacterial (16S rRNA transcript amplicon sequencing) and archaeal (qPCR, T-RFLP and mcrA and 16S rRNA transcript amplicon sequencing) communities. The metabolically active bacterial community was dominated by three phyla, showing significant changes in relative abundance range over the transition period: Firmicutes (from prepartum 57% to postpartum 35%), Bacteroidetes (from prepartum 22% to postpartum 18%) and Proteobacteria (from prepartum 7% to postpartum 32%). For the archaea, qPCR analysis of 16S rRNA transcript number, revealed a significant prepartum to postpartum increase in Methanobacteriales, in accordance with an observed increase (from prepartum 80% to postpartum 89%) in relative abundance of 16S rRNA transcript amplicons allocated to this order. On the other hand, a significant prepartum to postpartum decrease (from 15% to 2%) was observed in relative abundance of Methanomassiliicoccales 16S rRNA transcripts. In contrast to qPCR analysis of the 16S rRNA transcripts, quantification of mcrA transcripts revealed no change in total abundance of metabolically active methanogens over the transition period. According to T-RFLP analysis of the mcrA transcripts, two Methanobacteriales genera, Methanobrevibacter and Methanosphaera (represented by the T-RFs 39 and 267 bp), represented more than 70% of the metabolically active methanogens, showing no significant changes over the transition period; minor T-RFs, likely to represent members of the order Methanomassiliicoccales and with a relative abundance below 5% in total, decreased significantly over the transition period. In accordance with the T-RFLP analysis, the mcrA transcript amplicon sequencing revealed Methanobacteriales to cover 99% of the total reads, dominated by the genera Methanobrevibacter (75%) and Methanosphaera (24%), whereas the Methanomassiliicoccales order covered only 0.2% of the total reads. In conclusion, the present study showed that the structure of the metabolically active bacterial and archaeal rumen communities changed over the transition period, likely in response to the dramatic changes in physiology and nutritional factors like dry matter intake and feed composition. It should be noted however that for the methanogens, the observed community changes were influenced by the analyzed gene (mcrA or 16S rRNA)

Large-scale benchmarking reveals false discoveries and count transformation sensitivity in 16S rRNA gene amplicon data analysis methods used in microbiome studies

BACKGROUND: There is an immense scientific interest in the human microbiome and its effects on human physiology, health, and disease. A common approach for examining bacterial communities is high-throughput sequencing of 16S rRNA gene hypervariable regions, aggregating sequence-similar amplicons into operational taxonomic units (OTUs). Strategies for detecting differential relative abundance of OTUs between sample conditions include classical statistical approaches as well as a plethora of newer methods, many borrowing from the related field of RNA-seq analysis. This effort is complicated by unique data characteristics, including sparsity, sequencing depth variation, and nonconformity of read counts to theoretical distributions, which is often exacerbated by exploratory and/or unbalanced study designs. Here, we assess the robustness of available methods for (1) inference in differential relative abundance analysis and (2) beta-diversity-based sample separation, using a rigorous benchmarking framework based on large clinical 16S microbiome datasets from different sources. RESULTS: Running more than 380,000 full differential relative abundance tests on real datasets with permuted case/control assignments and in silico-spiked OTUs, we identify large differences in method performance on a range of parameters, including false positive rates, sensitivity to sparsity and case/control balances, and spike-in retrieval rate. In large datasets, methods with the highest false positive rates also tend to have the best detection power. For beta-diversity-based sample separation, we show that library size normalization has very little effect and that the distance metric is the most important factor in terms of separation power. CONCLUSIONS: Our results, generalizable to datasets from different sequencing platforms, demonstrate how the choice of method considerably affects analysis outcome. Here, we give recommendations for tools that exhibit low false positive rates, have good retrieval power across effect sizes and case/control proportions, and have low sparsity bias. Result output from some commonly used methods should be interpreted with caution. We provide an easily extensible framework for benchmarking of new methods and future microbiome datasets. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40168-016-0208-8) contains supplementary material, which is available to authorized users