PRISE2: software for designing sequence-selective PCR primers and probes.

BackgroundPRISE2 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.ResultsPRISE2 has been tested on two very similar strains of the fungus Dactylella oviparasitica, and it was able to create highly selective primers and probes for each of them, demonstrating the ability to create useful sequence-selective assays.ConclusionsPRISE2 is a user-friendly, interactive software package that can be used to design high-quality selective primers for PCR experiments. In addition to choosing primers, users have an option to add a probe to any selected primer pair, enabling design of Taqman and other primer-probe based assays. PRISE2 can also be used to design probes for FISH and other hybridization-based assays

Clustering Scatter Plots Using Data Depth Measures.

Clustering is rapidly becoming a powerful data mining technique, and has been broadly applied to many domains such as bioinformatics and text mining. However, the existing methods can only deal with a data matrix of scalars. In this paper, we introduce a hierarchical clustering procedure that can handle a data matrix of scatter plots. To more accurately reflect the nature of data, we introduce a dissimilarity statistic based on "data depth" to measure the discrepancy between two bivariate distributions without oversimplifying the nature of the underlying pattern. We then combine hypothesis testing with hierarchical clustering to simultaneously cluster the rows and columns of the data matrix of scatter plots. We also propose novel painting metrics and construct heat maps to allow visualization of the clusters. We demonstrate the utility and power of our new clustering method through simulation studies and application to a microbe-host-interaction study

Improving probe set selection for microbial community analysis by leveraging taxonomic information of training sequences

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Results</p> <p>Gene sequences manifesting identical fingerprints with probes chosen by the new algorithm are more likely to be from the same taxonomic group than probes chosen by the previous algorithm. In cases where they are from different taxonomic groups, underlying DNA sequences of identical fingerprints are more similar to each other in probe sets made with the new versus the previous algorithm. Complete removal of large taxonomic groups from training data does not greatly decrease the ability of probe sets to distinguish those groups.</p> <p>Conclusions</p> <p>Probe sets made from the new algorithm create fingerprints that more reliably cluster into biologically meaningful groups. The method can readily distinguish microbial phylotypes that were excluded from the training sequences, suggesting novel microbes can also be detected.</p

High Levels of Oxidative Stress and Skin Microbiome are Critical for Initiation and Development of Chronic Wounds in Diabetic Mice.

A balanced redox state is critical for proper healing. Although human chronic wounds are characterized by high levels of oxidative stress (OS), whether OS levels are critical for chronic wound development is not known. For these studies, we used our chronic wound model in diabetic mice that has similar characteristics as human chronic wounds, including naturally developed biofilm. We hypothesize that OS levels in wound tissues are critical for chronic wound initiation and development. We show that increased OS levels in the wound correlate with increased chronicity. Moreover, without increased OS levels, biofilm taken from chronic wounds and placed in new excision wounds do not create chronic wounds. Similarly, high OS levels in the wound tissue in the absence of the skin microbiome do not lead to chronic wounds. These findings show that both high OS levels and bacteria are needed for chronic wound initiation and development. In conclusion, OS levels in the wound at time of injury are critical for biofilm formation and chronic wound development and may be a good predictor of the degree of wound chronicity. Treating such wounds might be accomplished by managing OS levels with antioxidants combined with manipulation of the skin microbiome after debridement

Functional diversity in resource use by fungi.

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

A metaproteomic approach to study human-microbial ecosystems at the mucosal luminal interface

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. © 2011 Li et al

Reprograming of gut microbiome energy metabolism by the FUT2 Crohn's disease risk polymorphism.

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

A screen of Crohn's disease-associated microbial metabolites identifies ascorbate as a novel metabolic inhibitor of activated human T cells.

Microbial metabolites are an emerging class of mediators influencing CD4+ T-cell function. To advance the understanding of direct causal microbial factors contributing to Crohn's disease, we screened 139 predicted Crohn's disease-associated microbial metabolites for their bioactivity on human CD4+ T-cell functions induced by disease-associated T helper 17 (Th17) polarizing conditions. We observed 15 metabolites with CD4+ T-cell bioactivity, 3 previously reported, and 12 unprecedented. A deeper investigation of the microbe-derived metabolite, ascorbate, revealed its selective inhibition on activated human CD4+ effector T cells, including IL-17A-, IL-4-, and IFNγ-producing cells. Mechanistic assessment suggested the apoptosis of activated human CD4+ T cells associated with selective inhibition of energy metabolism. These findings suggest a substantial rate of relevant T-cell bioactivity among Crohn's disease-associated microbial metabolites, and evidence for novel modes of bioactivity, including targeting of T-cell energy metabolism

An In Vitro Pipeline for Screening and Selection of Citrus-Associated Microbiota with Potential Anti-"Candidatus Liberibacter asiaticus" Properties.

Huanglongbing (HLB) is a destructive citrus disease that is lethal to all commercial citrus plants, making it the most serious citrus disease and one of the most serious plant diseases. Because of the severity of HLB and the paucity of effective control measures, we structured this study to encompass the entirety of the citrus microbiome and the chemistries associated with that microbial community. We describe the spatial niche diversity of bacteria and fungi associated with citrus roots, stems, and leaves using traditional microbial culturing integrated with culture-independent methods. Using the culturable sector of the citrus microbiome, we created a microbial repository using a high-throughput bulk culturing and microbial identification pipeline. We integrated an in vitro agar diffusion inhibition bioassay into our culturing pipeline that queried the repository for antimicrobial activity against Liberibacter crescens, a culturable surrogate for the nonculturable "Candidatus Liberibacter asiaticus" bacterium associated with HLB. We identified microbes with robust inhibitory activity against L. crescens that include the fungi Cladosporium cladosporioides and Epicoccum nigrum and bacterial species of Pantoea, Bacillus, and Curtobacterium Purified bioactive natural products with anti-"Ca. Liberibacter asiaticus" activity were identified from the fungus C. cladosporioides Bioassay-guided fractionation of an organic extract of C. cladosporioides yielded the natural products cladosporols A, C, and D as the active agents against L. crescens This work serves as a foundation for unraveling the complex chemistries associated with the citrus microbiome to begin to understand the functional roles of members of the microbiome, with the long-term goal of developing anti-"Ca Liberibacter asiaticus" bioinoculants that thrive in the citrus holosystem.IMPORTANCE Globally, citrus is threatened by huanglongbing (HLB), and the lack of effective control measures is a major concern of farmers, markets, and consumers. There is compelling evidence that plant health is a function of the activities of the plant's associated microbiome. Using Liberibacter crescens, a culturable surrogate for the unculturable HLB-associated bacterium "Candidatus Liberibacter asiaticus," we tested the hypothesis that members of the citrus microbiome produce potential anti-"Ca Liberibacter asiaticus" natural products with potential anti-"Ca Liberibacter asiaticus" activity. A subset of isolates obtained from the microbiome inhibited L. crescens growth in an agar diffusion inhibition assay. Further fractionation experiments linked the inhibitory activity of the fungus Cladosporium cladosporioides to the fungus-produced natural products cladosporols A, C, and D, demonstrating dose-dependent antagonism to L. crescens