Characterization of ciliate diversity in bromeliad tank waters from the Brazilian Atlantic Forest.

Bromeliads are a diverse group of plants that includes many species whose individuals are capable of retaining water, forming habitats called phytotelmata. These habitats harbor a diversity of organisms including prokaryotes, unicellular eukaryotes, metazoans, and fungi. Among single-celled eukaryotic organisms, ciliates are generally the most abundant. In the present study, we used Illumina DNA sequencing to survey the eukaryotic communities, especially ciliates, inhabiting the tanks of the bromeliads Aechmea gamosepala and Vriesea platynema in the Atlantic Forest of southern Brazil. Filtered sequences were clustered into distinct OTUs using a 99% identity threshold, and then assigned to phylum and genus using a BLAST-based approach (implemented in QIIME) and the SILVA reference database. Both bromeliad species harbored very diverse eukaryotic communities, with Arthropoda and Ciliophora showing the highest abundance (as estimated by the number of sequence reads). The ciliate genus Tetrahymena was the most abundant among single-celled organisms, followed by apicomplexan gregarines and the ciliate genus Glaucoma. Another interesting finding was the presence and high abundance of Trypanosoma in these bromeliad tanks, demonstrating their occurrence in this type of environment. The results presented here demonstrate a hidden diversity of eukaryotes in bromeliad tank waters, opening up new avenues for their in-depth characterization.

Native California soils are selective reservoirs for multidrug-resistant bacteria.

Soil bacteria can exhibit extensive antibiotic resistomes and act as reservoirs of important antibiotic resistance traits. However, the geographic sources and evolutionary drivers of resistance traits are poorly understood in these natural settings. We investigated the prevalence, spatial structure and evolutionary drivers of multidrug resistance in natural populations of Bradyrhizobium, a cosmopolitan bacterial lineage that thrives in soil and aquatic systems as well as in plant and human hosts. We genotyped > 400 isolates from plant roots and soils across California and assayed 98 of them for resistance traits against 17 clinically relevant antibiotics. We investigated the geographic and phylogenetic structure of resistance traits, and analysed correlations of resistance with strain abundance, host infection capacity and in vitro fitness. We found: (i) multidrug resistance at all sites, (ii) subsets of resistance traits that are spatially structured and (iii) significant associations between resistance traits and increased strain abundance or host infection capacity. Our results highlight multiple selective factors that can result in the spread of resistance traits in native Bradyrhizobium populations.

Early childhood gut microbiomes show strong geographic differences among subjects at high risk for type 1 diabetes.

OBJECTIVE: Gut microbiome dysbiosis is associated with numerous diseases, including type 1 diabetes. This pilot study determines how geographical location affects the microbiome of infants at high risk for type 1 diabetes in a population of homogenous HLA class II genotypes. RESEARCH DESIGN AND METHODS: High-throughput 16S rRNA sequencing was performed on stool samples collected from 90 high-risk, nonautoimmune infants participating in The Environmental Determinants of Diabetes in the Young (TEDDY) study in the U.S., Germany, Sweden, and Finland. RESULTS: Study site-specific patterns of gut colonization share characteristics across continents. Finland and Colorado have a significantly lower bacterial diversity, while Sweden and Washington state are dominated by Bifidobacterium in early life. Bacterial community diversity over time is significantly different by geographical location. CONCLUSIONS: The microbiome of high-risk infants is associated with geographical location. Future studies aiming to identify the microbiome disease phenotype need to carefully consider the geographical origin of subjects.

Compromised gut microbiota networks in children with anti-islet cell autoimmunity.

The gut microbiome is suggested to play a role in the pathogenesis of autoimmune disorders such as type 1 diabetes. Evidence of anti-islet cell autoimmunity in type 1 diabetes appears in the first years of life; however, little is known regarding the establishment of the gut microbiome in early infancy. Here, we sought to determine whether differences were present in early composition of the gut microbiome in children in whom anti-islet cell autoimmunity developed. We investigated the microbiome of 298 stool samples prospectively taken up to age 3 years from 22 case children in whom anti-islet cell autoantibodies developed, and 22 matched control children who remained islet cell autoantibody-negative in follow-up. The microbiome changed markedly during the first year of life, and was further affected by breast-feeding, food introduction, and birth delivery mode. No differences between anti-islet cell autoantibody-positive and -negative children were found in bacterial diversity, microbial composition, or single-genus abundances. However, substantial alterations in microbial interaction networks were observed at age 0.5 and 2 years in the children in whom anti-islet cell autoantibodies developed. The findings underscore a role of the microbiome in the pathogenesis of anti-islet cell autoimmunity and type 1 diabetes.

Efficiency of partner choice and sanctions in Lotus is not altered by nitrogen fertilization.

Eukaryotic hosts must exhibit control mechanisms to select against ineffective bacterial symbionts. Hosts can minimize infection by less-effective symbionts (partner choice) and can divest of uncooperative bacteria after infection (sanctions). Yet, such host-control traits are predicted to be context dependent, especially if they are costly for hosts to express or maintain. Legumes form symbiosis with rhizobia that vary in symbiotic effectiveness (nitrogen fixation) and can enforce partner choice as well as sanctions. In nature, legumes acquire fixed nitrogen from both rhizobia and soils, and nitrogen deposition is rapidly enriching soils globally. If soil nitrogen is abundant, we predict host control to be downregulated, potentially allowing invasion of ineffective symbionts. We experimentally manipulated soil nitrogen to examine context dependence in host control. We co-inoculated Lotus strigosus from nitrogen depauperate soils with pairs of Bradyrhizobium strains that vary in symbiotic effectiveness and fertilized plants with either zero nitrogen or growth maximizing nitrogen. We found efficient partner choice and sanctions regardless of nitrogen fertilization, symbiotic partner combination or growth season. Strikingly, host control was efficient even when L. strigosus gained no significant benefit from rhizobial infection, suggesting that these traits are resilient to short-term changes in extrinsic nitrogen, whether natural or anthropogenic.

Interactions between specific phytoplankton and bacteria affect lake bacterial community succession.

Time-series observations and a phytoplankton manipulation experiment were combined to test the hypothesis that phytoplankton succession effects changes in bacterial community composition. Three humic lakes were sampled weekly May-August and correlations between relative abundances of specific phytoplankton and bacterial operational taxonomic units (OTUs) in each time series were determined. To experimentally characterize the influence of phytoplankton, bacteria from each lake were incubated with phytoplankton from one of the three lakes or no phytoplankton. Following incubation, variation in bacterial community composition explained by phytoplankton treatment increased 65%, while the variation explained by bacterial source decreased 64%. Free-living bacteria explained, on average, over 60% of the difference between phytoplankton and corresponding no-phytoplankton control treatments. Fourteen out of the 101 bacterial OTUs that exhibited positively correlated patterns of abundance with specific algal populations in time-series observations were enriched in mesocosms following incubation with phytoplankton, and one out of 59 negatively correlated bacterial OTUs was depleted in phytoplankton treatments. Bacterial genera enriched in mesocosms containing specific phytoplankton assemblages included Limnohabitans (clade betI-A), Bdellovibrio and Mitsuaria. These results suggest that effects of phytoplankton on certain bacterial populations, including bacteria tracking seasonal changes in algal-derived organic matter, result in correlations between algal and bacterial community dynamics.

Ca. Nitrososphaera and Bradyrhizobium are inversely correlated and related to agricultural practices in long-term field experiments.

Agricultural land management, such as fertilization, liming, and tillage affects soil properties, including pH, organic matter content, nitrification rates, and the microbial community. Three different study sites were used to identify microorganisms that correlate with agricultural land use and to determine which factors regulate the relative abundance of the microbial signatures of the agricultural land-use. The three sites included in this study are the Broadbalk Experiment at Rothamsted Research, UK, the Everglades Agricultural Area, Florida, USA, and the Kellogg Biological Station, Michigan, USA. The effects of agricultural management on the abundance and diversity of bacteria and archaea were determined using high throughput, barcoded 16S rRNA sequencing. In addition, the relative abundance of these organisms was correlated with soil features. Two groups of microorganisms involved in nitrogen cycle were highly correlated with land use at all three sites. The ammonia oxidizing-archaea, dominated by Ca. Nitrososphaera, were positively correlated with agriculture while a ubiquitous group of soil bacteria closely related to the diazotrophic symbiont, Bradyrhizobium, was negatively correlated with agricultural management. Analysis of successional plots showed that the abundance of ammonia oxidizing-archaea declined and the abundance of bradyrhizobia increased with time away from agriculture. This observation suggests that the effect of agriculture on the relative abundance of these genera is reversible. Soil pH and NH3 concentrations were positively correlated with archaeal abundance but negatively correlated with the abundance of Bradyrhizobium. The high correlations of Ca. Nitrososphaera and Bradyrhizobium abundances with agricultural management at three long-term experiments with different edaphoclimatic conditions allowed us to suggest these two genera as signature microorganisms for agricultural land use.

Characterization of the Relative Abundance of the Citrus Pathogen Ca. Liberibacter Asiaticus in the Microbiome of Its Insect Vector, Diaphorina citri, using High Throughput 16S rRNA Sequencing.

The relationship between the causal agent of Huanglongbing (HLB), Ca. Liberibacter asiaticus(Las), and the naturally occurring endosymbiotic community of its insect vector, the Asian citrus psyllid (ACP), Diaphorina citri, was studied. Variation was observed in the titer of Las within an ACP population feeding on the same material. The cause of this disparity is unknown, and has implications for Las transmission and the spread of HLB. This study utilizes culture independent methods to establish the relationship between the ACP's microbial community and Las acquisition. DNA from 21 psyllids was amplified using universal 16S rRNA primers with Illumina adaptor regions and a sample-specific 7- base identifier. These amplicons were then batch-sequenced on the Illumina platform. The resulting sequences were separated by the identifier, and compared to known sequences in a 16S rRNA database. The microbial communities of each psyllid were compared to determine whether a correlation exists between the ACP's endosymbionts and level of Las acquisition.ACPs were dominated by the same four bacterialgenera regardless of the abundance of Ca.Liberibacter. A combination of qPCR and Illumina sequencing was used to establish an infection gradient among the sampled ACPs. The Ca. Liberibacter titer within the insect was found to have a strong negative relationship with an endosymbiont residing in the syncytium of the mycetocyte and a positive relationship with Wolbachia. These correlations have implications in the acquisition of Las by the ACP as well as the activities of Las within this vector.

Gut microbiome metagenomics analysis suggests a functional model for the development of autoimmunity for type 1 diabetes.

Recent studies have suggested a bacterial role in the development of autoimmune disorders including type 1 diabetes (T1D). Over 30 billion nucleotide bases of Illumina shotgun metagenomic data were analyzed from stool samples collected from four pairs of matched T1D case-control subjects collected at the time of the development of T1D associated autoimmunity (i.e., autoantibodies). From these, approximately one million open reading frames were predicted and compared to the SEED protein database. Of the 3,849 functions identified in these samples, 144 and 797 were statistically more prevalent in cases and controls, respectively. Genes involved in carbohydrate metabolism, adhesions, motility, phages, prophages, sulfur metabolism, and stress responses were more abundant in cases while genes with roles in DNA and protein metabolism, aerobic respiration, and amino acid synthesis were more common in controls. These data suggest that increased adhesion and flagella synthesis in autoimmune subjects may be involved in triggering a T1D associated autoimmune response. Extensive differences in metabolic potential indicate that autoimmune subjects have a functionally aberrant microbiome. Mining 16S rRNA data from these datasets showed a higher proportion of butyrate-producing and mucin-degrading bacteria in controls compared to cases, while those bacteria that produce short chain fatty acids other than butyrate were higher in cases. Thus, a key rate-limiting step in butyrate synthesis is more abundant in controls. These data suggest that a consortium of lactate- and butyrate-producing bacteria in a healthy gut induce a sufficient amount of mucin synthesis to maintain gut integrity. In contrast, non-butyrate-producing lactate-utilizing bacteria prevent optimal mucin synthesis, as identified in autoimmune subjects.

Toward defining the autoimmune microbiome for type 1 diabetes.

Several studies have shown that gut bacteria have a role in diabetes in murine models. Specific bacteria have been correlated with the onset of diabetes in a rat model. However, it is unknown whether human intestinal microbes have a role in the development of autoimmunity that often leads to type 1 diabetes (T1D), an autoimmune disorder in which insulin-secreting pancreatic islet cells are destroyed. High-throughput, culture-independent approaches identified bacteria that correlate with the development of T1D-associated autoimmunity in young children who are at high genetic risk for this disorder. The level of bacterial diversity diminishes overtime in these autoimmune subjects relative to that of age-matched, genotype-matched, nonautoimmune individuals. A single species, Bacteroides ovatus, comprised nearly 24% of the total increase in the phylum Bacteroidetes in cases compared with controls. Conversely, another species in controls, represented by the human firmicute strain CO19, represented nearly 20% of the increase in Firmicutes compared with cases overtime. Three lines of evidence are presented that support the notion that, as healthy infants approach the toddler stage, their microbiomes become healthier and more stable, whereas, children who are destined for autoimmunity develop a microbiome that is less diverse and stable. Hence, the autoimmune microbiome for T1D may be distinctly different from that found in healthy children. These data also suggest bacterial markers for the early diagnosis of T1D. In addition, bacteria that negatively correlated with the autoimmune state may prove to be useful in the prevention of autoimmunity development in high-risk children.

PANGEA: pipeline for analysis of next generation amplicons.

High-throughput DNA sequencing can identify organisms and describe population structures in many environmental and clinical samples. Current technologies generate millions of reads in a single run, requiring extensive computational strategies to organize, analyze and interpret those sequences. A series of bioinformatics tools for high-throughput sequencing analysis, including pre-processing, clustering, database matching and classification, have been compiled into a pipeline called PANGEA. The PANGEA pipeline was written in Perl and can be run on Mac OSX, Windows or Linux. With PANGEA, sequences obtained directly from the sequencer can be processed quickly to provide the files needed for sequence identification by BLAST and for comparison of microbial communities. Two different sets of bacterial 16S rRNA sequences were used to show the efficiency of this workflow. The first set of 16S rRNA sequences is derived from various soils from Hawaii Volcanoes National Park. The second set is derived from stool samples collected from diabetes-resistant and diabetes-prone rats. The workflow described here allows the investigator to quickly assess libraries of sequences on personal computers with customized databases. PANGEA is provided for users as individual scripts for each step in the process or as a single script where all processes, except the chi(2) step, are joined into one program called the 'backbone'.