Peripheral blood cellular dynamics of rheumatoid arthritis treatment informs about efficacy of response to disease modifying drugs.

Rheumatoid arthritis (RA) is an autoimmune disease characterized by systemic inflammation and is mediated by multiple immune cell types. In this work, we aimed to determine the relevance of changes in cell proportions in peripheral blood mononuclear cells (PBMCs) during the development of disease and following treatment. Samples from healthy blood donors, newly diagnosed RA patients, and established RA patients that had an inadequate response to MTX and were about to start tumor necrosis factor inhibitors (TNFi) treatment were collected before and after 3 months of treatment. We used in parallel a computational deconvolution approach based on RNA expression and flow cytometry to determine the relative cell-type frequencies. Cell-type frequencies from deconvolution of gene expression indicate that monocytes (both classical and non-classical) and CD4+ cells (Th1 and Th2) were increased in RA patients compared to controls, while NK cells and B cells (naïve and mature) were significantly decreased in RA patients. Treatment with MTX caused a decrease in B cells (memory and plasma cell), and a decrease in CD4 Th cells (Th1 and Th17), while treatment with TNFi resulted in a significant increase in the population of B cells. Characterization of the RNA expression patterns found that most of the differentially expressed genes in RA subjects after treatment can be explained by changes in cell frequencies (98% and 74% respectively for MTX and TNFi).

Predictive metabolomic profiling of microbial communities using amplicon or metagenomic sequences.

Microbial community metabolomics, particularly in the human gut, are beginning to provide a new route to identify functions and ecology disrupted in disease. However, these data can be costly and difficult to obtain at scale, while amplicon or shotgun metagenomic sequencing data are readily available for populations of many thousands. Here, we describe a computational approach to predict potentially unobserved metabolites in new microbial communities, given a model trained on paired metabolomes and metagenomes from the environment of interest. Focusing on two independent human gut microbiome datasets, we demonstrate that our framework successfully recovers community metabolic trends for more than 50% of associated metabolites. Similar accuracy is maintained using amplicon profiles of coral-associated, murine gut, and human vaginal microbiomes. We also provide an expected performance score to guide application of the model in new samples. Our results thus demonstrate that this 'predictive metabolomic' approach can aid in experimental design and provide useful insights into the thousands of community profiles for which only metagenomes are currently available.

Author Correction: Gut microbiome structure and metabolic activity in inflammatory bowel disease.

In the Supplementary Tables 2, 4 and 6 originally published with this Article, the authors mistakenly included sample identifiers in the form of UMCGs rather than UMCG IBDs in the validation cohort; this has now been amended.

Gut microbiome structure and metabolic activity in inflammatory bowel disease.

The inflammatory bowel diseases (IBDs), which include Crohn's disease (CD) and ulcerative colitis (UC), are multifactorial chronic conditions of the gastrointestinal tract. While IBD has been associated with dramatic changes in the gut microbiota, changes in the gut metabolome-the molecular interface between host and microbiota-are less well understood. To address this gap, we performed untargeted metabolomic and shotgun metagenomic profiling of cross-sectional stool samples from discovery (n = 155) and validation (n = 65) cohorts of CD, UC and non-IBD control patients. Metabolomic and metagenomic profiles were broadly correlated with faecal calprotectin levels (a measure of gut inflammation). Across >8,000 measured metabolite features, we identified chemicals and chemical classes that were differentially abundant in IBD, including enrichments for sphingolipids and bile acids, and depletions for triacylglycerols and tetrapyrroles. While > 50% of differentially abundant metabolite features were uncharacterized, many could be assigned putative roles through metabolomic 'guilt by association' (covariation with known metabolites). Differentially abundant species and functions from the metagenomic profiles reflected adaptation to oxidative stress in the IBD gut, and were individually consistent with previous findings. Integrating these data, however, we identified 122 robust associations between differentially abundant species and well-characterized differentially abundant metabolites, indicating possible mechanistic relationships that are perturbed in IBD. Finally, we found that metabolome- and metagenome-based classifiers of IBD status were highly accurate and, like the vast majority of individual trends, generalized well to the independent validation cohort. Our findings thus provide an improved understanding of perturbations of the microbiome-metabolome interface in IBD, including identification of many potential diagnostic and therapeutic targets.

A role for bacterial urease in gut dysbiosis and Crohn's disease.

Gut dysbiosis during inflammatory bowel disease involves alterations in the gut microbiota associated with inflammation of the host gut. We used a combination of shotgun metagenomic sequencing and metabolomics to analyze fecal samples from pediatric patients with Crohn's disease and found an association between disease severity, gut dysbiosis, and bacterial production of free amino acids. Nitrogen flux studies using 15N in mice showed that activity of bacterial urease, an enzyme that releases ammonia by hydrolysis of host urea, led to the transfer of murine host-derived nitrogen to the gut microbiota where it was used for amino acid synthesis. Inoculation of a conventional murine host (pretreated with antibiotics and polyethylene glycol) with commensal Escherichia coli engineered to express urease led to dysbiosis of the gut microbiota, resulting in a predominance of Proteobacteria species. This was associated with a worsening of immune-mediated colitis in these animals. A potential role for altered urease expression and nitrogen flux in the development of gut dysbiosis suggests that bacterial urease may be a potential therapeutic target for inflammatory bowel diseases.

Not so simple, not so subtle: the interspecies competition between Bacillus simplex and Bacillus subtilis and its impact on the evolution of biofilms.

Bacillus subtilis biofilms have a fundamental role in shaping the soil ecosystem. During this process, they unavoidably interact with neighbour bacterial species. We studied the interspecies interactions between biofilms of the soil-residing bacteria B. subtilis and related Bacillus species. We found that proximity between the biofilms triggered recruitment of motile B. subtilis cells, which engulfed the competing Bacillus simplex colony. Upon interaction, B. subtilis secreted surfactin and cannibalism toxins, at concentrations that were inert to B. subtilis itself, which eliminated the B. simplex colony, as well as colonies of Bacillus toyonensis. Surfactin toxicity was correlated with the presence of short carbon-tail length isomers, and synergistic with the cannibalism toxins. Importantly, during biofilm development and interspecies interactions a subpopulation in B. subtilis biofilm lost its native plasmid, leading to increased virulence against the competing Bacillus species. Overall, these findings indicate that genetic programs and traits that have little effect on biofilm development when each species is grown in isolation have a dramatic impact when different bacterial species interact.

Growth dynamics of gut microbiota in health and disease inferred from single metagenomic samples.

Metagenomic sequencing increased our understanding of the role of the microbiome in health and disease, yet it only provides a snapshot of a highly dynamic ecosystem. Here, we show that the pattern of metagenomic sequencing read coverage for different microbial genomes contains a single trough and a single peak, the latter coinciding with the bacterial origin of replication. Furthermore, the ratio of sequencing coverage between the peak and trough provides a quantitative measure of a species' growth rate. We demonstrate this in vitro and in vivo, under different growth conditions, and in complex bacterial communities. For several bacterial species, peak-to-trough coverage ratios, but not relative abundances, correlated with the manifestation of inflammatory bowel disease and type II diabetes.

Sequencing and beyond: integrating molecular 'omics' for microbial community profiling.

High-throughput DNA sequencing has proven invaluable for investigating diverse environmental and host-associated microbial communities. In this Review, we discuss emerging strategies for microbial community analysis that complement and expand traditional metagenomic profiling. These include novel DNA sequencing strategies for identifying strain-level microbial variation and community temporal dynamics; measuring multiple 'omic' data types that better capture community functional activity, such as transcriptomics, proteomics and metabolomics; and combining multiple forms of omic data in an integrated framework. We highlight studies in which the 'multi-omics' approach has led to improved mechanistic models of microbial community structure and function.

Identification and characterization of a highly motile and antibiotic refractory subpopulation involved in the expansion of swarming colonies of Paenibacillus vortex.

Bacteria often use sophisticated cooperative behaviours, such as the development of complex colonies, elaborate biofilms and advanced dispersal strategies, to cope with the harsh and variable conditions of natural habitats, including the presence of antibiotics. Paenibacillus vortex uses swarming motility and cell-to-cell communication to form complex, structured colonies. The modular organization of P. vortex colony has been found to facilitate its dispersal on agar surfaces. The current study reveals that the complex structure of the colony is generated by the coexistence and transition between two morphotypes--'builders' and 'explorers'--with distinct functions in colony formation. Here, we focused on the explorers, which are highly motile and spearhead colonial expansion. Explorers are characterized by high expression levels of flagellar genes, such as flagellin (hag), motA, fliI, flgK and sigD, hyperflagellation, decrease in ATP (adenosine-5'-triphosphate) levels, and increased resistance to antibiotics. Their tolerance to many antibiotics gives them the advantage of translocation through antibiotics-containing areas. This work gives new insights on the importance of cell differentiation and task distribution in colony morphogenesis and adaptation to antibiotics.

Genome sequence of the pattern-forming social bacterium Paenibacillus dendritiformis C454 chiral morphotype.

Paenibacillus dendritiformis is a Gram-positive, soil-dwelling, spore-forming social microorganism. An intriguing collective faculty of this strain is manifested by its ability to switch between different morphotypes, such as the branching (T) and the chiral (C) morphotypes. Here we report the 6.3-Mb draft genome sequence of the P. dendritiformis C454 chiral morphotype.

Genome sequence of the pattern forming Paenibacillus vortex bacterium reveals potential for thriving in complex environments.

BACKGROUND: The pattern-forming bacterium Paenibacillus vortex is notable for its advanced social behavior, which is reflected in development of colonies with highly intricate architectures. Prior to this study, only two other Paenibacillus species (Paenibacillus sp. JDR-2 and Paenibacillus larvae) have been sequenced. However, no genomic data is available on the Paenibacillus species with pattern-forming and complex social motility. Here we report the de novo genome sequence of this Gram-positive, soil-dwelling, sporulating bacterium. RESULTS: The complete P. vortex genome was sequenced by a hybrid approach using 454 Life Sciences and Illumina, achieving a total of 289× coverage, with 99.8% sequence identity between the two methods. The sequencing results were validated using a custom designed Agilent microarray expression chip which represented the coding and the non-coding regions. Analysis of the P. vortex genome revealed 6,437 open reading frames (ORFs) and 73 non-coding RNA genes. Comparative genomic analysis with 500 complete bacterial genomes revealed exceptionally high number of two-component system (TCS) genes, transcription factors (TFs), transport and defense related genes. Additionally, we have identified genes involved in the production of antimicrobial compounds and extracellular degrading enzymes. CONCLUSIONS: These findings suggest that P. vortex has advanced faculties to perceive and react to a wide range of signaling molecules and environmental conditions, which could be associated with its ability to reconfigure and replicate complex colony architectures. Additionally, P. vortex is likely to serve as a rich source of genes important for agricultural, medical and industrial applications and it has the potential to advance the study of social microbiology within Gram-positive bacteria.

GeneCards Version 3: the human gene integrator.

GeneCards (www.genecards.org) is a comprehensive, authoritative compendium of annotative information about human genes, widely used for nearly 15 years. Its gene-centric content is automatically mined and integrated from over 80 digital sources, resulting in a web-based deep-linked card for each of >73,000 human gene entries, encompassing the following categories: protein coding, pseudogene, RNA gene, genetic locus, cluster and uncategorized. We now introduce GeneCards Version 3, featuring a speedy and sophisticated search engine and a revamped, technologically enabling infrastructure, catering to the expanding needs of biomedical researchers. A key focus is on gene-set analyses, which leverage GeneCards' unique wealth of combinatorial annotations. These include the GeneALaCart batch query facility, which tabulates user-selected annotations for multiple genes and GeneDecks, which identifies similar genes with shared annotations, and finds set-shared annotations by descriptor enrichment analysis. Such set-centric features address a host of applications, including microarray data analysis, cross-database annotation mapping and gene-disorder associations for drug targeting. We highlight the new Version 3 database architecture, its multi-faceted search engine, and its semi-automated quality assurance system. Data enhancements include an expanded visualization of gene expression patterns in normal and cancer tissues, an integrated alternative splicing pattern display, and augmented multi-source SNPs and pathways sections. GeneCards now provides direct links to gene-related research reagents such as antibodies, recombinant proteins, DNA clones and inhibitory RNAs and features gene-related drugs and compounds lists. We also portray the GeneCards Inferred Functionality Score annotation landscape tool for scoring a gene's functional information status. Finally, we delineate examples of applications and collaborations that have benefited from the GeneCards suite. Database URL: www.genecards.org.

Lethal protein produced in response to competition between sibling bacterial colonies.

Sibling Paenibacillus dendritiformis bacterial colonies grown on low-nutrient agar medium mutually inhibit growth through secretion of a lethal factor. Analysis of secretions reveals the presence of subtilisin (a protease) and a 12 kDa protein, termed sibling lethal factor (Slf). Purified subtilisin promotes the growth and expansion of P. dendritiformis colonies, whereas Slf is lethal and lyses P. dendritiformis cells in culture. Slf is encoded by a gene belonging to a large family of bacterial genes of unknown function, and the gene is predicted to encode a protein of approximately 20 kDa, termed dendritiformis sibling bacteriocin. The 20 kDa recombinant protein was produced and found to be inactive, but exposure to subtilisin resulted in cleavage to the active, 12 kDa form. The experimental results, combined with mathematical modeling, show that subtilisin serves to regulate growth of the colony. Below a threshold concentration, subtilisin promotes colony growth and expansion. However, once it exceeds a threshold, as occurs at the interface between competing colonies, Slf is then secreted into the medium to rapidly reduce cell density by lysis of the bacterial cells. The presence of genes encoding homologs of dendritiformis sibling bacteriocin in other bacterial species suggests that this mechanism for self-regulation of colony growth might not be limited to P. dendritiformis.