PRISE2 is a new software tool for designing sequence-selective PCR primers and probes. To achieve high level of selectivity, PRISE2 allows the user to specify a collection of target sequences that the primers are supposed to amplify, as well as non-target sequences that should not be amplified. The program emphasizes primer selectivity on the 3' end, which is crucial for selective amplification of conserved sequences such as rRNA genes. In PRISE2, users can specify desired properties of primers, including length, GC content, and others. They can interactively manipulate the list of candidate primers, to choose primer pairs that are best suited for their needs. A similar process is used to add probes to selected primer pairs. More advanced features include, for example, the capability to define a custom mismatch penalty function. PRISE2 is equipped with a graphical, user-friendly interface, and it runs on Windows, Macintosh or Linux machines.
Current high throughput sequencing (HTS) methods are limited in their ability to resolve bacteria at or below the genus level. While the impact of this limitation may be relatively minor in whole-community analyses, it constrains the use of HTS as a tool for identifying and examining individual bacteria of interest. The limited resolution is a consequence of both short read lengths and insufficient sequence variation within the commonly targeted variable regions of the small-subunit rRNA (SSU) gene. The goal of this work was to improve the resolving power of bacterial HTS. We developed an assay targeting the hypervariable rRNA internal transcribed spacer (ITS) region residing between the SSU and large-subunit (LSU) rRNA genes. Comparisons of the ITS region and two SSU regions using annotated bacterial genomes in GenBank showed much greater resolving power is possible with the ITS region. This report presents a new HTS method for analyzing bacterial composition with improved capabilities. The greater resolving power enabled by the ITS region arises from its high sequence variation across a wide range of bacterial taxa and an associated decrease in taxonomic heterogeneity within its OTUs. Although the method should be adaptable to any HTS platform, this report presents PCR primers, amplification parameters, and protocols for Illumina-based analyses.
Fucosyltransferase 2 (FUT2) is an enzyme that is responsible for the synthesis of the H antigen in body fluids and on the intestinal mucosa. The H antigen is an oligosaccharide moiety that acts as both an attachment site and carbon source for intestinal bacteria. Non-secretors, who are homozygous for the loss-of-function alleles of FUT2 gene (sese), have increased susceptibility to Crohn's disease (CD). To characterize the effect of FUT2 polymorphism on the mucosal ecosystem, we profiled the microbiome, meta-proteome and meta-metabolome of 75 endoscopic lavage samples from the cecum and sigmoid of 39 healthy subjects (12 SeSe, 18 Sese and 9 sese). Imputed metagenomic analysis revealed perturbations of energy metabolism in the microbiome of non-secretor and heterozygote individuals, notably the enrichment of carbohydrate and lipid metabolism, cofactor and vitamin metabolism and glycan biosynthesis and metabolism-related pathways, and the depletion of amino-acid biosynthesis and metabolism. Similar changes were observed in mice bearing the FUT2(-/-) genotype. Metabolomic analysis of human specimens revealed concordant as well as novel changes in the levels of several metabolites. Human metaproteomic analysis indicated that these functional changes were accompanied by sub-clinical levels of inflammation in the local intestinal mucosa. Therefore, the colonic microbiota of non-secretors is altered at both the compositional and functional levels, affecting the host mucosal state and potentially explaining the association of FUT2 genotype and CD susceptibility.
Next-generation sequencing coupled with metagenomics has led to the rapid growth of sequence databases and enabled a new branch of microbiology called comparative metagenomics. Comparative metagenomic analysis studies compositional patterns within and between different environments providing a deep insight into the structure and function of complex microbial communities. It is a fast growing field that requires the development of novel supervised learning techniques for addressing challenges associated with metagenomic data, e.g. sensitivity to the choice of sequence similarity cutoff used to define operational taxonomic units (OTUs), high dimensionality and sparsity of the data and so forth. On the other hand, the natural properties of microbial community data may provide useful information about the structure of the data. For example, similarity between species encoded by a phylogenetic tree captures the relationship between OTUs and may be useful for the analysis of complex microbial datasets where the diversity patterns comprise features at multiple taxonomic levels. Even though some of the challenges have been addressed by learning algorithms in the literature, none of the available methods take advantage of the inherent properties of metagenomic data.
Ataxia-telangiectasia is a genetic disorder associated with high incidence of B-cell lymphoma. Using an ataxia-telangiectasia mouse model, we compared lymphoma incidence in several isogenic mouse colonies harboring different bacterial communities, finding that intestinal microbiota are a major contributor to disease penetrance and latency, lifespan, molecular oxidative stress, and systemic leukocyte genotoxicity. High-throughput sequence analysis of rRNA genes identified mucosa-associated bacterial phylotypes that were colony-specific. Lactobacillus johnsonii, which was deficient in the more cancer-prone mouse colony, was causally tested for its capacity to confer reduced genotoxicity when restored by short-term oral transfer. This intervention decreased systemic genotoxicity, a response associated with reduced basal leukocytes and the cytokine-mediated inflammatory state, and mechanistically linked to the host cell biology of systemic genotoxicity. Our results suggest that intestinal microbiota are a potentially modifiable trait for translational intervention in individuals at risk for B-cell lymphoma, or for other diseases that are driven by genotoxicity or the molecular response to oxidative stress.
Abnormalities of the intestinal microbiota are implicated in the pathogenesis of Crohns disease (CD) and ulcerative colitis (UC), two spectra of inflammatory bowel disease (IBD). However, the high complexity and low inter-individual overlap of intestinal microbial composition are formidable barriers to identifying microbial taxa representing this dysbiosis. These difficulties might be overcome by an ecologic analytic strategy to identify modules of interacting bacteria (rather than individual bacteria) as quantitative reproducible features of microbial composition in normal and IBD mucosa. We sequenced 16S ribosomal RNA genes from 179 endoscopic lavage samples from different intestinal regions in 64 subjects (32 controls, 16 CD and 16 UC patients in clinical remission). CD and UC patients showed a reduction in phylogenetic diversity and shifts in microbial composition, comparable to previous studies using conventional mucosal biopsies. Analysis of weighted co-occurrence network revealed 5 microbial modules. These modules were unprecedented, as they were detectable in all individuals, and their composition and abundance was recapitulated in an independent, biopsy-based mucosal dataset 2 modules were associated with healthy, CD, or UC disease states. Imputed metagenome analysis indicated that these modules displayed distinct metabolic functionality, specifically the enrichment of oxidative response and glycan metabolism pathways relevant to host-pathogen interaction in the disease-associated modules. The highly preserved microbial modules accurately classified IBD status of individual patients during disease quiescence, suggesting that microbial dysbiosis in IBD may be an underlying disorder independent of disease activity. Microbial modules thus provide an integrative view of microbial ecology relevant to IBD.
Aberrant interactions between the host and the intestinal bacteria are thought to contribute to the pathogenesis of many digestive diseases. However, studying the complex ecosystem at the human mucosal-luminal interface (MLI) is challenging and requires an integrative systems biology approach. Therefore, we developed a novel method integrating lavage sampling of the human mucosal surface, high-throughput proteomics, and a unique suite of bioinformatic and statistical analyses. Shotgun proteomic analysis of secreted proteins recovered from the MLI confirmed the presence of both human and bacterial components. To profile the MLI metaproteome, we collected 205 mucosal lavage samples from 38 healthy subjects, and subjected them to high-throughput proteomics. The spectral data were subjected to a rigorous data processing pipeline to optimize suitability for quantitation and analysis, and then were evaluated using a set of biostatistical tools. Compared to the mucosal transcriptome, the MLI metaproteome was enriched for extracellular proteins involved in response to stimulus and immune system processes. Analysis of the metaproteome revealed significant individual-related as well as anatomic region-related (biogeographic) features. Quantitative shotgun proteomics established the identity and confirmed the biogeographic association of 49 proteins (including 3 functional protein networks) demarcating the proximal and distal colon. This robust and integrated proteomic approach is thus effective for identifying functional features of the human mucosal ecosystem, and a fresh understanding of the basic biology and disease processes at the MLI.
Population levels of microbial phylotypes can be examined using a hybridization-based method that utilizes a small set of computationally-designed DNA probes targeted to a gene common to all. Our previous algorithm attempts to select a set of probes such that each training sequence manifests a unique theoretical hybridization pattern (a binary fingerprint) to a probe set. It does so without taking into account similarity between training gene sequences or their putative taxonomic classifications, however. We present an improved algorithm for probe set selection that utilizes the available taxonomic information of training gene sequences and attempts to choose probes such that the resultant binary fingerprints cluster into real taxonomic groups.
Fungi influence nutrient cycling in terrestrial ecosystems, as they are major regulators of decomposition and soil respiration. However, little is known about the substrate preferences of individual fungal species outside of laboratory culture studies. If active fungi differ in their substrate preferences in situ, then changes in fungal diversity due to global change may dramatically influence nutrient cycling in ecosystems. To test the responses of individual fungal taxa to specific substrates, we used a nucleotide-analogue procedure in the boreal forest of Alaska (USA). Specifically, we added four organic N compounds commonly found in plant litter (arginine, glutamate, lignocellulose, and tannin-protein) to litterbags filled with decomposed leaf litter (black spruce and aspen) and assessed the responses of active fungal species using qPCR (quantitative polymerase chain reaction), oligonucleotide fingerprinting of rRNA genes, and sequencing. We also compared the sequences from our experiment with a concurrent warming experiment to see if active fungi that targeted more recalcitrant compounds would respond more positively to soil warming. We found that individual fungal taxa responded differently to substrate additions and that active fungal communities were different across litter types (spruce vs. aspen). Active fungi that targeted lignocellulose also responded positively to experimental warming. Additionally, resource-use patterns in different fungal taxa were genetically correlated, suggesting that it may be possible to predict the ecological function of active fungal communities based on genetic information. Together, these results imply that fungi are functionally diverse and that reductions in fungal diversity may have consequences for ecosystem functioning.
Two-class neutral zone classifiers were recently proposed for use in microbial community profiling applications. These classifiers allow a region of neutrality for cases where probe hybridization outcomes are too ambiguous to have adequate confidence in assigning a "binding" or "no binding" result. In this paper, we generalize the idea of neutral zone classifiers to an arbitrary number of classes and apply it to improve the process of microbial community profiling by considering a third class for the outcome of probe hybridization experiments, "partial binding." We introduce a family of class distributions that uses a mixture of Gaussian distributions as a model for a Box-Cox power transformation of the raw intensity measurements. Stratified cross-validation analyses are used to assess the efficacy of the proposed three-class neutral zone classifier. This article has supplementary material online.
Commensal bacteria play an important role in formation of the immune system, but the mechanisms involved are incompletely understood. In this study, we analyze CD1d-restricted invariant NKT (iNKT) cells in germfree mice and in two colonies of C57BL/6 mice termed conventional flora and restricted flora (RF), stably bearing commensal microbial communities of diverse but distinct composition. In germfree mice, iNKT cells were moderately reduced, suggesting that commensal microbiota were partially required for the antigenic drive in maintaining systemic iNKT cells. Surprisingly, even greater depletion of iNKT cell population occurred in RF mice. This was in part attributable to reduced RF levels of intestinal microbial taxa (Sphingomonas spp.) known to express antigenic glycosphingolipid products. However, memory and activated CD8(+) T cells were also expanded in RF mice, prompting us to test whether CD8(+) T cell activity might be further depleting iNKT cells. Indeed, iNKT cell numbers were restored in RF mice bearing the CD8alpha(-/-) genotype or in adult wild-type RF mice acutely depleted with anti-CD8 Ab. Moreover, iNKT cells were restored in RF mice bearing the Prf1(-/-) phenotype, a key component of cytolytic function. These findings indicate that commensal microbiota, through positive (antigenic drive) and negative (cytolytic depletion by CD8(+) T cells) mechanisms, profoundly shape the iNKT cell compartment. Because individuals greatly vary in the composition of their microbial communities, enteric microbiota may play an important epigenetic role in the striking differences in iNKT cell abundance in humans and therefore in their potential contribution to host immune status.
This study examined bacteria-immune interactions in a mouse model possessing microbiota-dependent immune regulatory features similar to those occurring in human atopy, colitis, and immune regulation. Associations between the abundance of several bacterial phylotypes and immunoregulatory target cell types were identified, suggesting that they may play a role in these phenotypes.
Replant diseases often occur when pome and stone fruits are grown in soil that had previously been planted with the same or similar plant species. They typically lead to reductions in plant growth, crop yield and production duration. In this project, greenhouse assays were used to identify a peach orchard soil that caused replant disease symptoms. Biocidal treatments of this soil led to growth increases of Nemaguard peach seedlings. In addition, plants grown in as little as 1% of the replant soil exhibited reduced plant growth. These results suggest that the disease etiology has a biological component. Analysis of roots from plants exhibiting various levels of replant disease symptoms showed little difference in the amounts of PCR-amplified bacterial or fungal rRNA genes. However, analysis using a stramenopile-selective PCR assay showed that rRNA genes from this taxon were generally more abundant in plants with the smallest top weights. Nucleotide sequence analysis of these genes identified several phylotypes belonging to Bacillariophyta, Chrysophyceae, Eustigmatophyceae, Labyrinthulida, Oomycetes, Phaeophyceae and Synurophyceae. Sequence-selective quantitative PCR assays targeting four of the most abundant phylotypes showed that both diatoms (Sellaphora spp.) and an oomycete (Pythium ultimum) were negatively associated with plant top weights.
Three Pochonia chlamydosporia var. chlamydosporia strains were isolated from a Meloidogyne incognita-suppressive soil, and then genetically characterized with multiple Pochonia-selective typing methods based on analysis of ß-tubulin, rRNA internal transcribed spacer (ITS), rRNA small subunit (SSU), and enterobacterial repetitive intergenic consensus (ERIC) PCR. All strains exhibited different patterns with the ERIC analysis. Strains 1 and 4 were similar with PCR analysis of ß-tubulin and ITS. The strains potential as biological control agents against root-knot nematodes were examined in greenhouse trials. All three P. chlamydosporia strains significantly reduced the numbers of nematode egg masses. When chlamydospores were used as inoculum, strain 4 reduced egg numbers on tomato roots by almost 50%, and showed effects on the numbers of J2 and on nematode-caused root-galling. A newly developed SSU-based PCR analysis differentiated strain 4 from the others, and could therefore potentially be used as a screening tool for identifying other effective biocontrol strains of P. chlamydosporia var. chlamydosporia.
A series of experiments were performed to examine the population dynamics of the sugarbeet cyst nematode, Heterodera schachtii, and the nematophagus fungus Dactylella oviparasitica. After two nematode generations, the population densities of H. schachtii were measured in relation to various initial infestation densities of both D. oviparasitica and H. schachtii. In general, higher initial population densities of D. oviparasitica were associated with lower final population densities of H. schachtii. Regression models showed that the initial densities of D. oviparasitica were only significant when predicting the final densities of H. schachtii J2 and eggs as well as fungal egg parasitism, while the initial densities of J2 were significant for all final H. schachtii population density measurements. We also showed that the densities of H. schachtii-associated D. oviparasitica fluctuate greatly, with rRNA gene numbers going from zero in most field-soil-collected cysts to an average of 4.24 x 10(8) in mature females isolated directly from root surfaces. Finally, phylogenetic analysis of rRNA genes suggested that D. oviparasitica belongs to a clade of nematophagous fungi that includes Arkansas Fungus strain L (ARF-L) and that these fungi are widely distributed. We anticipate that these findings will provide foundational data facilitating the development of more effective decision models for sugar beet planting.
Replant disease often occurs when certain crops are "replanted" in a soil that had previously supported the same or similar plant species. This disease typically leads to reductions in plant growth, crop yields, and production duration, and its etiology remains ill-defined. The objective of this study was to identify microorganisms associated with peach replant disease symptoms at a field location in California, USA. Soil samples were subjected to treatments to create various levels of replant disease symptoms. Clonal peach seedlings were grown in the treated soils in greenhouse trials. After 6 weeks, plant growth parameters were measured, and both culture and culture-independent analyses were performed to identify root-associated bacteria, fungi and stramenopiles.
Australian Subtropical White Syndrome (ASWS) is an infectious, temperature dependent disease of the subtropical coral Turbinaria mesenterina involving a hitherto unknown transmissible causative agent. This report describes significant changes in the coral associated bacterial community as the disease progresses from the apparently healthy tissue of ASWS affected coral colonies, to areas of the colony affected by ASWS lesions, to the dead coral skeleton exposed by ASWS. In an effort to better understand the potential roles of bacteria in the formation of disease lesions, the effect of antibacterials on the rate of lesion progression was tested, and both culture based and culture independent techniques were used to investigate the bacterial communities associated with colonies of T. mesenterina. Culture-independent analysis was performed using the Oligonucleotide Fingerprinting of Ribosomal Genes (OFRG) technique, which allowed a library of 8094 cloned bacterial 16S ribosomal genes to be analysed. Interestingly, the bacterial communities associated with both healthy and disease affected corals were very diverse and ASWS associated communities were not characterized by a single dominant organism. Treatment with antibacterials had a significant effect on the rate of progress of disease lesions (p = 0.006), suggesting that bacteria may play direct roles as the causative agents of ASWS. A number of potential aetiological agents of ASWS were identified in both the culture-based and culture-independent studies. In the culture-independent study an Alphaproteobacterium closely related to Roseovarius crassostreae, the apparent aetiological agent of juvenile oyster disease, was found to be significantly associated with disease lesions. In the culture-based study Vibrio harveyi was consistently associated with ASWS affected coral colonies and was not isolated from any healthy colonies. The differing results of the culture based and culture-independent studies highlight the importance of using both approaches in the investigation of microbial communities.
Improvements to oligonucleotide fingerprinting of rRNA genes (OFRG) were obtained by implementing polony microarray technology. OFRG is an array-based method for analyzing microbial community composition. Polonies are discrete clusters of DNA, produced by solid-phase PCR in hydrogels, and derived from individual, spatially isolated DNA molecules. The advantages of a polony-based OFRG method include higher throughput and reductions in the PCR-induced errors and compositional skew inherent in all other PCR-based community composition methods, including high-throughput sequencing of rRNA genes. Given the similarities between polony microarrays and certain aspects of sequencing methods such as the Illumina platform, we suggest that if concepts presented in this study were implemented in high-throughput sequencing protocols, a reduction of PCR-induced errors and compositional skew may be realized.
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