James D. Cavalcoli

Decade-long bacterial community dynamics in cystic fibrosis airways

The structure and dynamics of bacterial communities in the airways of persons with cystic fibrosis (CF) remain largely unknown. We characterized the bacterial communities in 126 sputum samples representing serial collections spanning 8–9 y from six age-matched male CF patients. Sputum DNA was analyzed by bar-coded pyrosequencing of the V3–V5 hypervariable region of the 16S rRNA gene, defining 662 operational taxonomic units (OTUs) from >633,000 sequences. Bacterial community diversity decreased significantly over time in patients with typically progressive lung disease but remained relatively stable in patients with a mild lung disease phenotype. Antibiotic use, rather than patient age or lung function, was the primary driver of decreasing diversity. Interpatient variability in community structure exceeded intrapatient variability in serial samples. Antibiotic treatment was associated with pronounced shifts in community structure, but communities showed both short- and long-term resilience after antibiotic perturbation. There was a positive correlation between OTU occurrence and relative abundance, with a small number of persistent OTUs accounting for the greatest abundance. Significant changes in community structure, diversity, or total bacterial density at the time of pulmonary exacerbation were not observed. Despite decreasing community diversity in patients with progressive disease, total bacterial density remained relatively stable over time. These findings show the critical relationship between airway bacterial community structure, disease stage, and clinical state at the time of sample collection. These features are the key parameters with which to assess the complex ecology of the CF airway.

ConceptGen: a gene set enrichment and gene set relation mapping tool

MOTIVATION The elucidation of biological concepts enriched with differentially expressed genes has become an integral part of the analysis and interpretation of genomic data. Of additional importance is the ability to explore networks of relationships among previously defined biological concepts from diverse information sources, and to explore results visually from multiple perspectives. Accomplishing these tasks requires a unified framework for agglomeration of data from various genomic resources, novel visualizations, and user functionality. RESULTS We have developed ConceptGen, a web-based gene set enrichment and gene set relation mapping tool that is streamlined and simple to use. ConceptGen offers over 20,000 concepts comprising 14 different types of biological knowledge, including data not currently available in any other gene set enrichment or gene set relation mapping tool. We demonstrate the functionalities of ConceptGen using gene expression data modeling TGF-beta-induced epithelial-mesenchymal transition and metabolomics data comparing metastatic versus localized prostate cancers.

Michigan molecular interactions r2: from interacting proteins to pathways.

Molecular interaction data exists in a number of repositories, each with its own data format, molecule identifier and information coverage. Michigan molecular interactions (MiMI) assists scientists searching through this profusion of molecular interaction data. The original release of MiMI gathered data from well-known protein interaction databases, and deep merged this information while keeping track of provenance. Based on the feedback received from users, MiMI has been completely redesigned. This article describes the resulting MiMI Release 2 (MiMIr2). New functionality includes extension from proteins to genes and to pathways; identification of highlighted sentences in source publications; seamless two-way linkage with Cytoscape; query facilities based on MeSH/GO terms and other concepts; approximate graph matching to find relevant pathways; support for querying in bulk; and a user focus-group driven interface design. MiMI is part of the NIHs; National Center for Integrative Biomedical Informatics (NCIBI) and is publicly available at: http://mimi.ncibi.org.

Identification of Cross-Species Shared Transcriptional Networks of Diabetic Nephropathy in Human and Mouse Glomeruli

Murine models are valuable instruments in defining the pathogenesis of diabetic nephropathy (DN), but they only partially recapitulate disease manifestations of human DN, limiting their utility. To define the molecular similarities and differences between human and murine DN, we performed a cross-species comparison of glomerular transcriptional networks. Glomerular gene expression was profiled in patients with early type 2 DN and in three mouse models (streptozotocin DBA/2, C57BLKS db/db, and eNOS-deficient C57BLKS db/db mice). Species-specific transcriptional networks were generated and compared with a novel network-matching algorithm. Three shared human–mouse cross-species glomerular transcriptional networks containing 143 (Human-DBA STZ), 97 (Human-BKS db/db), and 162 (Human-BKS eNOS−/− db/db) gene nodes were generated. Shared nodes across all networks reflected established pathogenic mechanisms of diabetes complications, such as elements of Janus kinase (JAK)/signal transducer and activator of transcription (STAT) and vascular endothelial growth factor receptor (VEGFR) signaling pathways. In addition, novel pathways not previously associated with DN and cross-species gene nodes and pathways unique to each of the human–mouse networks were discovered. The human–mouse shared glomerular transcriptional networks will assist DN researchers in selecting mouse models most relevant to the human disease process of interest. Moreover, they will allow identification of new pathways shared between mice and humans.

Genome-Based Characterization of Two Prenylation Steps in the Assembly of the Stephacidin and Notoamide Anticancer Agents in a Marine-Derived Aspergillus sp.

Stephacidin and notoamide natural products belong to a group of prenylated indole alkaloids containing a core bicyclo[2.2.2]diazaoctane ring system. These bioactive fungal secondary metabolites have a range of unusual structural and stereochemical features but their biosynthesis has remained uncharacterized. Herein, we report the first biosynthetic gene cluster for this class of fungal alkaloids based on whole genome sequencing of a marine-derived Aspergillus sp. Two central pathway enzymes catalyzing both normal and reverse prenyltransfer reactions were characterized in detail. Our results establish the early steps for creation of the prenylated indole alkaloid structure and suggest a scheme for the biosynthesis of stephacidin and notoamide metabolites. The work provides the first genetic and biochemical insights for understanding the structural diversity of this important family of fungal alkaloids.

Community transcriptomic assembly reveals microbes that contribute to deep-sea carbon and nitrogen cycling.

The deep ocean is an important component of global biogeochemical cycles because it contains one of the largest pools of reactive carbon and nitrogen on earth. However, the microbial communities that drive deep-sea geochemistry are vastly unexplored. Metatranscriptomics offers new windows into these communities, but it has been hampered by reliance on genome databases for interpretation. We reconstructed the transcriptomes of microbial populations from Guaymas Basin, in the deep Gulf of California, through shotgun sequencing and de novo assembly of total community RNA. Many of the resulting messenger RNA (mRNA) contiguous sequences contain multiple genes, reflecting co-transcription of operons, including those from dominant members. Also prevalent were transcripts with only limited representation (2.8 times coverage) in a corresponding metagenome, including a considerable portion (1.2 Mb total assembled mRNA sequence) with similarity (96%) to a marine heterotroph, Alteromonas macleodii. This Alteromonas and euryarchaeal marine group II populations displayed abundant transcripts from amino-acid transporters, suggesting recycling of organic carbon and nitrogen from amino acids. Also among the most abundant mRNAs were catalytic subunits of the nitrite oxidoreductase complex and electron transfer components involved in nitrite oxidation. These and other novel genes are related to novel Nitrospirae and have limited representation in accompanying metagenomic data. High throughput sequencing of 16S ribosomal RNA (rRNA) genes and rRNA read counts confirmed that Nitrospirae are minor yet widespread members of deep-sea communities. These results implicate a novel bacterial group in deep-sea nitrite oxidation, the second step of nitrification. This study highlights metatranscriptomic assembly as a valuable approach to study microbial communities.

The IRE1α/XBP1s Pathway Is Essential for the Glucose Response and Protection of β Cells

Although glucose uniquely stimulates proinsulin biosynthesis in β cells, surprisingly little is known of the underlying mechanism(s). Here, we demonstrate that glucose activates the unfolded protein response transducer inositol-requiring enzyme 1 alpha (IRE1α) to initiate X-box-binding protein 1 (Xbp1) mRNA splicing in adult primary β cells. Using mRNA sequencing (mRNA-Seq), we show that unconventional Xbp1 mRNA splicing is required to increase and decrease the expression of several hundred mRNAs encoding functions that expand the protein secretory capacity for increased insulin production and protect from oxidative damage, respectively. At 2 wk after tamoxifen-mediated Ire1α deletion, mice develop hyperglycemia and hypoinsulinemia, due to defective β cell function that was exacerbated upon feeding and glucose stimulation. Although previous reports suggest IRE1α degrades insulin mRNAs, Ire1α deletion did not alter insulin mRNA expression either in the presence or absence of glucose stimulation. Instead, β cell failure upon Ire1α deletion was primarily due to reduced proinsulin mRNA translation primarily because of defective glucose-stimulated induction of a dozen genes required for the signal recognition particle (SRP), SRP receptors, the translocon, the signal peptidase complex, and over 100 other genes with many other intracellular functions. In contrast, Ire1α deletion in β cells increased the expression of over 300 mRNAs encoding functions that cause inflammation and oxidative stress, yet only a few of these accumulated during high glucose. Antioxidant treatment significantly reduced glucose intolerance and markers of inflammation and oxidative stress in mice with β cell-specific Ire1α deletion. The results demonstrate that glucose activates IRE1α-mediated Xbp1 splicing to expand the secretory capacity of the β cell for increased proinsulin synthesis and to limit oxidative stress that leads to β cell failure.

Genome-Wide Identification of Klebsiella pneumoniae Fitness Genes during Lung Infection

ABSTRACT Klebsiella pneumoniae is an urgent public health threat because of resistance to carbapenems, antibiotics of last resort against Gram-negative bacterial infections. Despite the fact that K. pneumoniae is a leading cause of pneumonia in hospitalized patients, the bacterial factors required to cause disease are poorly understood. Insertion site sequencing combines transposon mutagenesis with high-throughput sequencing to simultaneously screen thousands of insertion mutants for fitness defects during infection. Using the recently sequenced K. pneumoniae strain KPPR1 in a well-established mouse model of pneumonia, insertion site sequencing was performed on a pool of >25,000 transposon mutants. The relative fitness requirement of each gene was ranked based on the ratio of lung to inoculum read counts and concordance between insertions in the same gene. This analysis revealed over 300 mutants with at least a 2-fold fitness defect and 69 with defects ranging from 10- to >2,000-fold. Construction of 6 isogenic mutants for use in competitive infections with the wild type confirmed their requirement for lung fitness. Critical fitness genes included those for the synthesis of branched-chain and aromatic amino acids that are essential in mice and humans, the transcriptional elongation factor RfaH, and the copper efflux pump CopA. The majority of fitness genes were conserved among reference strains representative of diverse pathotypes. These results indicate that regulation of outer membrane components and synthesis of amino acids that are essential to its host are critical for K. pneumoniae fitness in the lung. IMPORTANCE Klebsiella pneumoniae is a bacterium that commonly causes pneumonia in patients after they are admitted to the hospital. K. pneumoniae is becoming resistant to all available antibiotics, and when these infections spread to the bloodstream, over half of patients die. Since currently available antibiotics are failing, we must discover new ways to treat these infections. In this study, we asked what genes the bacterium needs to cause an infection, since the proteins encoded by these genes could be targets for new antibiotics. We identified over 300 genes that K. pneumoniae requires to grow in a mouse model of pneumonia. Many of the genes that we identified are found in K. pneumoniae isolates from throughout the world, including antibiotic-resistant forms. If new antibiotics could be made against the proteins that these genes encode, they may be broadly effective against K. pneumoniae. Klebsiella pneumoniae is a bacterium that commonly causes pneumonia in patients after they are admitted to the hospital. K. pneumoniae is becoming resistant to all available antibiotics, and when these infections spread to the bloodstream, over half of patients die. Since currently available antibiotics are failing, we must discover new ways to treat these infections. In this study, we asked what genes the bacterium needs to cause an infection, since the proteins encoded by these genes could be targets for new antibiotics. We identified over 300 genes that K. pneumoniae requires to grow in a mouse model of pneumonia. Many of the genes that we identified are found in K. pneumoniae isolates from throughout the world, including antibiotic-resistant forms. If new antibiotics could be made against the proteins that these genes encode, they may be broadly effective against K. pneumoniae.

Regulation of the Human Endogenous Retrovirus K (HML-2) Transcriptome by the HIV-1 Tat Protein

ABSTRACT Approximately 8% of the human genome is made up of endogenous retroviral sequences. As the HIV-1 Tat protein activates the overall expression of the human endogenous retrovirus type K (HERV-K) (HML-2), we used next-generation sequencing to determine which of the 91 currently annotated HERV-K (HML-2) proviruses are regulated by Tat. Transcriptome sequencing of total RNA isolated from Tat- and vehicle-treated peripheral blood lymphocytes from a healthy donor showed that Tat significantly activates expression of 26 unique HERV-K (HML-2) proviruses, silences 12, and does not significantly alter the expression of the remaining proviruses. Quantitative reverse transcription-PCR validation of the sequencing data was performed on Tat-treated PBLs of seven donors using provirus-specific primers and corroborated the results with a substantial degree of quantitative similarity. IMPORTANCE The expression of HERV-K (HML-2) is tightly regulated but becomes markedly increased following infection with HIV-1, in part due to the HIV-1 Tat protein. The findings reported here demonstrate the complexity of the genome-wide regulation of HERV-K (HML-2) expression by Tat. This work also demonstrates that although HERV-K (HML-2) proviruses in the human genome are highly similar in terms of DNA sequence, modulation of the expression of specific proviruses in a given biological situation can be ascertained using next-generation sequencing and bioinformatics analysis.

Modeling complex genetic and environmental influences on comorbid bipolar disorder with tobacco use disorder

BackgroundComorbidity of psychiatric and substance use disorders represents a significant complication in the clinical course of both disorders. Bipolar Disorder (BD) is a psychiatric disorder characterized by severe mood swings, ranging from mania to depression, and up to a 70% rate of comorbid Tobacco Use Disorder (TUD). We found epidemiological evidence consistent with a common underlying etiology for BD and TUD, as well as evidence of both genetic and environmental influences on BD and TUD. Therefore, we hypothesized a common underlying genetic etiology, interacting with nicotine exposure, influencing susceptibility to both BD and TUD.MethodsUsing meta-analysis, we compared TUD rates for BD patients and the general population. We identified candidate genes showing statistically significant, replicated, evidence of association with both BD and TUD. We assessed commonality among these candidate genes and hypothesized broader, multi-gene network influences on the comorbidity. Using Fisher Exact tests we tested our hypothesized genetic networks for association with the comorbidity, then compared the inferences drawn with those derived from the commonality assessment. Finally, we prioritized candidate SNPs for validation.ResultsWe estimate risk for TUD among BD patients at 2.4 times that of the general population. We found three candidate genes associated with both BD and TUD (COMT, SLC6A3, and SLC6A4) and commonality analysis suggests that these genes interact in predisposing psychiatric and substance use disorders. We identified a 69 gene network that influences neurotransmitter signaling and shows significant over-representation of genes associated with BD and TUD, as well as genes differentially expressed with exposure to tobacco smoke. Twenty four of these genes are known drug targets.ConclusionsThis work highlights novel bioinformatics resources and demonstrates the effectiveness of using an integrated bioinformatics approach to improve our understanding of complex disease etiology. We illustrate the development and testing of hypotheses for a comorbidity predisposed by both genetic and environmental influences. Consistent with our hypothesis, the selected network models multiple interacting genetic influences on comorbid BD with TUD, as well as the environmental influence of nicotine. This network nominates candidate genes for validation and drug testing, and we offer a panel of SNPs prioritized for follow-up.