Oxydifficidin, a potent Neisseria gonorrhoeae antibiotic due to DedA assisted uptake and ribosomal protein RplL sensitivity.

Gonorrhea, which is caused by Neisseria gonorrhoeae, is the second most prevalent sexually transmitted infection worldwide. The increasing appearance of isolates that are resistant to approved therapeutics raises the concern that gonorrhea may become untreatable. Here, we serendipitously identified oxydifficidin as a potent N. gonorrhoeae antibiotic through the observation of a Bacillus amyloliquefaciens contaminant in a lawn of N. gonorrhoeae. Oxydifficidin is active against both wild-type and multidrug-resistant N. gonorrhoeae. It's potent activity results from a combination of DedA-assisted uptake into the cytoplasm and the presence of an oxydifficidin-sensitive ribosomal protein L7/L12 (RplL). Our data indicates that oxydifficidin binds to the ribosome at a site that is distinct from other antibiotics and that L7/L12 is uniquely associated with its mode of action. This study opens a potential new avenue for addressing antibiotic resistant gonorrhea and underscores the possibility of identifying overlooked natural products from cultured bacteria, particularly those with activity against previously understudied pathogens.

Functional Multigenomic Screening of Human-Associated Bacteria for NF-κB-Inducing Bioactive Effectors.

The effect of the microbiota on its human host is driven, at least in part, by small-molecule and protein effectors it produces. Here, we report on the use of functional multigenomic screening to identify microbiota-encoded effectors. In this study, genomic DNA from 116 human-associated bacteria was cloned en masse, and the resulting multigenomic library was screened using a nuclear factor-κB reporter (NF-κB) assay. Functional multigenomics builds on the concept of functional metagenomics but takes advantage of increasing advances in cultivating and sequencing human-associated bacteria. Effector genes found to confer NF-κB-inducing activity to Escherichia coli encode proteins in four general categories: cell wall hydrolases, membrane transporters, lipopolysaccharide biosynthetic enzymes, and proteins of unknown function. The compact nature of multigenomic libraries, which results from the ability to normalize input DNA ratios, should simplify screening of libraries using diverse heterologous hosts and reporter assays, increasing the rate of discovery of novel effector genes.IMPORTANCE Human-associated bacteria are thought to encode bioactive small molecules and proteins that play an intimate role in human health and disease. Here, we report on the creation and functional screening of a multigenomic library constructed using genomic DNA from 116 bacteria found at diverse sites across the human body. Individual clones were screened for genes capable of conferring NF-κB-inducing activity to Escherichia coli NF-κB is a useful reporter for a range of cellular processes related to immunity, pathogenesis, and inflammation. Compared to the screening of metagenomic libraries, the ability to normalize input DNA ratios when constructing a multigenomic library should facilitate the more efficient examination of commensal bacteria for diverse bioactivities. Multigenomic screening takes advantage of the growing available resources in culturing and sequencing the human microbiota and generates starting points for more in-depth studies on the mechanisms by which commensal bacteria interact with their human host.

Uncovering the biosynthetic potential of rare metagenomic DNA using co-occurrence network analysis of targeted sequences.

Sequencing of DNA extracted from environmental samples can provide key insights into the biosynthetic potential of uncultured bacteria. However, the high complexity of soil metagenomes, which can contain thousands of bacterial species per gram of soil, imposes significant challenges to explore secondary metabolites potentially produced by rare members of the soil microbiome. Here, we develop a targeted sequencing workflow termed CONKAT-seq (co-occurrence network analysis of targeted sequences) that detects physically clustered biosynthetic domains, a hallmark of bacterial secondary metabolism. Following targeted amplification of conserved biosynthetic domains in a highly partitioned metagenomic library, CONKAT-seq evaluates amplicon co-occurrence patterns across library subpools to identify chromosomally clustered domains. We show that a single soil sample can contain more than a thousand uncharacterized biosynthetic gene clusters, most of which originate from low frequency genomes which are practically inaccessible through untargeted sequencing. CONKAT-seq allows scalable exploration of largely untapped biosynthetic diversity across multiple soils, and can guide the discovery of novel secondary metabolites from rare members of the soil microbiome.

Cadasides, Calcium-Dependent Acidic Lipopeptides from the Soil Metagenome That Are Active against Multidrug-Resistant Bacteria.

The growing threat of antibiotic resistance necessitates the discovery of antibiotics that are active against resistant pathogens. Calcium-dependent antibiotics are a small family of structurally diverse acidic lipopeptides assembled by nonribosomal peptide synthetases (NRPSs) that are known to display various modes of action against antibiotic-resistant pathogens. Here we use NRPS adenylation (AD) domain sequencing to guide the identification, recovery, and cloning of the cde biosynthetic gene cluster from a soil metagenome. Heterologous expression of the cde biosynthetic gene cluster led to the production of cadasides A (1) and B (2), a subfamily of acidic lipopeptides that is distinct from previously characterized calcium-dependent antibiotics in terms of both overall structure and acidic residue rich peptide core. The cadasides inhibit the growth of multidrug-resistant Gram-positive pathogens by disrupting cell wall biosynthesis in the presence of high concentrations of calcium. Interestingly, sequencing of AD domains from diverse soils revealed that sequences predicted to arise from cadaside-like gene clusters are predominantly found in soils containing high levels of calcium carbonate.

Corrigendum: Commensal bacteria make GPCR ligands that mimic human signalling molecules.

This corrects the article DOI: 10.1038/nature23874.

An Optimized Synthetic-Bioinformatic Natural Product Antibiotic Sterilizes Multidrug-Resistant Acinetobacter baumannii-Infected Wounds.

The antibiotic paenimucillin A was originally identified using a culture-independent synthetic-bioinformatic natural product (syn-BNP) discovery approach. Here we report on a bioinformatics-guided survey of paenimucillin A analogs that led to the discovery of paenimucillin C. Paenimucillin C inhibits the growth of multidrug-resistant (MDR) Acinetobacter baumannii clinical isolates, as well as other Gram-negative bacterial pathogens. In a rat cutaneous wound model, it completely sterilized MDR A. baumannii wound infections with no sign of rebound. Mechanistic studies point to a membrane-associated mode of action that results in leakage of intracellular contents. IMPORTANCE Natural product-inspired antibiotics have saved millions of lives and played a critical role in modern medicine. However, the emergence of drug-resistant pathogens is outpacing the rate at which new clinically useful antibiotics are being discovered. The lack of a means to combat infections caused by multidrug-resistant (MDR) Acinetobacter baumannii is of particular concern. The sharp increase in cases of MDR A. baumannii infections in recent years prompted the CDC (https://www.cdc.gov/drugresistance/biggest_threats.html) and WHO (http://www.who.int/medicines/publications/global-priority-list-antibiotic-resistant-bacteria/en/) to list this pathogen as a "serious threat" and "critical pathogen," respectively. Here we report a new antibiotic, paenimucillin C, active against Gram-negative bacterial pathogens, including many clinical isolates of MDR A. baumannii strains. Mechanistic studies point to membrane disruption leading to leakage of intracellular contents as its antibacterial mode of action. Paenimucillin C sterilizes MDR A. baumannii infections in a rat cutaneous wound model with no sign of rebound infection, providing a potential new therapeutic regimen.

Bacterial natural product biosynthetic domain composition in soil correlates with changes in latitude on a continent-wide scale.

Although bacterial bioactive metabolites have been one of the most prolific sources of lead structures for the development of small-molecule therapeutics, very little is known about the environmental factors associated with changes in secondary metabolism across natural environments. Large-scale sequencing of environmental microbiomes has the potential to shed light on the richness of bacterial biosynthetic diversity hidden in the environment, how it varies from one environment to the next, and what environmental factors correlate with changes in biosynthetic diversity. In this study, the sequencing of PCR amplicons generated using primers targeting either ketosynthase domains from polyketide biosynthesis or adenylation domains from nonribosomal peptide biosynthesis was used to assess biosynthetic domain composition and richness in soils collected across the Australian continent. Using environmental variables collected at each soil site, we looked for environmental factors that correlated with either high overall domain richness or changes in the domain composition. Among the environmental variables we measured, changes in biosynthetic domain composition correlate most closely with changes in latitude and to a lesser extent changes in pH. Although it is unclear at this time the exact mix of factors that may drive the relationship between biosynthetic domain composition and latitude, from a practical perspective the identification of a latitudinal basis for differences in soil metagenome biosynthetic domain compositions should help guide future natural product discovery efforts.

Identification of biosynthetic gene clusters from metagenomic libraries using PPTase complementation in a Streptomyces host.

The majority of environmental bacteria are not readily cultured in the lab, leaving the natural products they make inaccessible using culture-dependent discovery methods. Cloning and heterologous expression of DNA extracted from environmental samples (environmental DNA, eDNA) provides a means of circumventing this discovery bottleneck. To facilitate the identification of clones containing biosynthetic gene clusters, we developed a model heterologous expression reporter strain Streptomyces albus::bpsA ΔPPTase. This strain carries a 4΄-phosphopantetheinyl transferase (PPTase)-dependent blue pigment synthase A gene, bpsA, in a PPTase deletion background. eDNA clones that express a functional PPTase restore production of the blue pigment, indigoidine. As PPTase genes often occur in biosynthetic gene clusters (BGCs), indigoidine production can be used to identify eDNA clones containing BGCs. We screened a soil eDNA library hosted in S. albus::bpsA ΔPPTase and identified clones containing non-ribosomal peptide synthetase (NRPS), polyketide synthase (PKS) and mixed NRPS/PKS biosynthetic gene clusters. One NRPS gene cluster was shown to confer the production of myxochelin A to S. albus::bpsA ΔPPTase.

Commensal bacteria make GPCR ligands that mimic human signalling molecules.

Commensal bacteria are believed to have important roles in human health. The mechanisms by which they affect mammalian physiology remain poorly understood, but bacterial metabolites are likely to be key components of host interactions. Here we use bioinformatics and synthetic biology to mine the human microbiota for N-acyl amides that interact with G-protein-coupled receptors (GPCRs). We found that N-acyl amide synthase genes are enriched in gastrointestinal bacteria and the lipids that they encode interact with GPCRs that regulate gastrointestinal tract physiology. Mouse and cell-based models demonstrate that commensal GPR119 agonists regulate metabolic hormones and glucose homeostasis as efficiently as human ligands, although future studies are needed to define their potential physiological role in humans. Our results suggest that chemical mimicry of eukaryotic signalling molecules may be common among commensal bacteria and that manipulation of microbiota genes encoding metabolites that elicit host cellular responses represents a possible small-molecule therapeutic modality (microbiome-biosynthetic gene therapy).

Antimicrobials Inspired by Nonribosomal Peptide Synthetase Gene Clusters.

Bacterial culture broth extracts have been the starting point for the development of numerous therapeutics. However, only a small fraction of bacterial biosynthetic diversity is accessible using this strategy. Here, we apply a discovery approach that bypasses the culturing step entirely by bioinformatically predicting small molecule structures from the primary sequences of the biosynthetic gene clusters. These structures are then chemically synthesized to give synthetic-bioinformatic natural products (syn-BNPs). Using this approach, we screened syn-BNPs inspired by nonribosomal peptide synthetases against microbial pathogens, and discovered an antibiotic for which no resistance could be identified and an antifungal agent with activity against diverse fungal pathogens.

Urban park soil microbiomes are a rich reservoir of natural product biosynthetic diversity.

Numerous therapeutically relevant small molecules have been identified from the screening of natural products (NPs) produced by environmental bacteria. These discovery efforts have principally focused on culturing bacteria from natural environments rich in biodiversity. We sought to assess the biosynthetic capacity of urban soil environments using a phylogenetic analysis of conserved NP biosynthetic genes amplified directly from DNA isolated from New York City park soils. By sequencing genes involved in the biosynthesis of nonribosomal peptides and polyketides, we found that urban park soil microbiomes are both rich in biosynthetic diversity and distinct from nonurban samples in their biosynthetic gene composition. A comparison of sequences derived from New York City parks to genes involved in the biosynthesis of biomedically important NPs produced by bacteria originally collected from natural environments around the world suggests that bacteria producing these same families of clinically important antibiotics, antifungals, and anticancer agents are actually present in the soils of New York City. The identification of new bacterial NPs often centers on the systematic exploration of bacteria present in natural environments. Here, we find that the soil microbiomes found in large cities likely hold similar promise as rich unexplored sources of clinically relevant NPs.

RNASeq analysis reveals biological processes governing the clinical behaviour of endometrioid and serous endometrial cancers.

BACKGROUND: Endometrial carcinoma comprises a group of tumours with distinct histologic and molecular features and clinical behaviour. Here, we sought to define the biological processes that govern the clinical behaviour of endometrial cancers. METHODS: Sixteen prototype genes representative of different biological processes that would likely play a role in endometrial and other hormone-driven cancers were defined. RNA-sequencing gene expression data from 323 endometrial cancers from The Cancer Genome Atlas (TCGA) were used to determine the transcription module of each prototype gene. The expression of prototype genes and modules and their association with outcome was assessed in univariate and multivariate survival analyses. The association of MSH6 expression with outcome was validated in an independent cohort of 243 primary endometrial cancers using immunohistochemistry. RESULTS: We observed that the clinical behaviour of endometrial cancers as a group was associated with hormone receptor signalling, PI3K pathway signalling and DNA mismatch repair processes. When analysed separately, in endometrioid carcinomas, hormone receptor, PI3K and DNA mismatch repair modules were significantly associated with outcome in univariate analysis, whereas the clinical behaviour of serous cancers was likely governed by apoptosis and Wnt signalling. Multivariate survival analysis revealed that MSH6 gene expression was associated with outcome of endometrial cancer patients independently from traditional prognostic clinicopathologic parameters, which was confirmed in an independent cohort at the protein level. CONCLUSION: Endometrioid and serous endometrial cancers are underpinned by distinct molecular pathways. MSH6 expression levels may be associated with outcome in endometrial cancers as a group.

DNA Copy Number Aberrations, and Human Papillomavirus Status in Penile Carcinoma. Clinico-Pathological Correlations and Potential Driver Genes.

Penile squamous cell carcinoma is a rare disease, in which somatic genetic aberrations have yet to be characterized. We hypothesized that gene copy aberrations might correlate with human papillomavirus status and clinico-pathological features. We sought to determine the spectrum of gene copy number aberrations in a large series of PSCCs and to define their correlations with human papillomavirus, histopathological subtype, and tumor grade, stage and lymph node status. Seventy formalin-fixed, paraffin embedded penile squamous cell carcinomas were centrally reviewed by expert uropathologists. DNA was extracted from micro-dissected samples, subjected to PCR-based human papillomavirus assessment and genotyping (INNO-LiPA human papillomavirus Genotyping Extra Assay) and microarray-based comparative genomic hybridization using a 32K Bacterial Artificial Chromosome array platform. Sixty-four samples yielded interpretable results. Recurrent gains were observed in chromosomes 1p13.3-q44 (88%), 3p12.3-q29 (86%), 5p15.33-p11 (67%) and 8p12-q24.3 (84%). Amplifications of 5p15.33-p11 and 11p14.1-p12 were found in seven (11%) and four (6%) cases, respectively. Losses were observed in chromosomes 2q33-q37.3 (86%), 3p26.3-q11.1 (83%) and 11q12.2-q25 (81%). Although many losses and gains were similar throughout the cohort, there were small significant differences observed at specific loci, between human papillomavirus positive and negative tumors, between tumor types, and tumor grade and nodal status. These results demonstrate that despite the diversity of genetic aberrations in penile squamous cell carcinomas, there are significant correlations between the clinico-pathological data and the genetic changes that may play a role in disease natural history and progression and highlight potential driver genes, which may feature in molecular pathways for existing therapeutic agents.

RNA:DNA hybrids in the human genome have distinctive nucleotide characteristics, chromatin composition, and transcriptional relationships.

BACKGROUND: RNA:DNA hybrids represent a non-canonical nucleic acid structure that has been associated with a range of human diseases and potential transcriptional regulatory functions. Mapping of RNA:DNA hybrids in human cells reveals them to have a number of characteristics that give insights into their functions. RESULTS: We find RNA:DNA hybrids to occupy millions of base pairs in the human genome. A directional sequencing approach shows the RNA component of the RNA:DNA hybrid to be purine-rich, indicating a thermodynamic contribution to their in vivo stability. The RNA:DNA hybrids are enriched at loci with decreased DNA methylation and increased DNase hypersensitivity, and within larger domains with characteristics of heterochromatin formation, indicating potential transcriptional regulatory properties. Mass spectrometry studies of chromatin at RNA:DNA hybrids shows the presence of the ILF2 and ILF3 transcription factors, supporting a model of certain transcription factors binding preferentially to the RNA:DNA conformation. CONCLUSIONS: Overall, there is little to indicate a dependence for RNA:DNA hybrids forming co-transcriptionally, with results from the ribosomal DNA repeat unit instead supporting the intriguing model of RNA generating these structures in trans. The results of the study indicate heterogeneous functions of these genomic elements and new insights into their formation and stability in vivo.

Comparative analysis of genome maintenance genes in naked mole rat, mouse, and human.

Genome maintenance (GM) is an essential defense system against aging and cancer, as both are characterized by increased genome instability. Here, we compared the copy number variation and mutation rate of 518 GM-associated genes in the naked mole rat (NMR), mouse, and human genomes. GM genes appeared to be strongly conserved, with copy number variation in only four genes. Interestingly, we found NMR to have a higher copy number of CEBPG, a regulator of DNA repair, and TINF2, a protector of telomere integrity. NMR, as well as human, was also found to have a lower rate of germline nucleotide substitution than the mouse. Together, the data suggest that the long-lived NMR, as well as human, has more robust GM than mouse and identifies new targets for the analysis of the exceptional longevity of the NMR.

Artificial neural network inference (ANNI): a study on gene-gene interaction for biomarkers in childhood sarcomas.

OBJECTIVE: To model the potential interaction between previously identified biomarkers in children sarcomas using artificial neural network inference (ANNI). METHOD: To concisely demonstrate the biological interactions between correlated genes in an interaction network map, only 2 types of sarcomas in the children small round blue cell tumors (SRBCTs) dataset are discussed in this paper. A backpropagation neural network was used to model the potential interaction between genes. The prediction weights and signal directions were used to model the strengths of the interaction signals and the direction of the interaction link between genes. The ANN model was validated using Monte Carlo cross-validation to minimize the risk of over-fitting and to optimize generalization ability of the model. RESULTS: Strong connection links on certain genes (TNNT1 and FNDC5 in rhabdomyosarcoma (RMS); FCGRT and OLFM1 in Ewing's sarcoma (EWS)) suggested their potency as central hubs in the interconnection of genes with different functionalities. The results showed that the RMS patients in this dataset are likely to be congenital and at low risk of cardiomyopathy development. The EWS patients are likely to be complicated by EWS-FLI fusion and deficiency in various signaling pathways, including Wnt, Fas/Rho and intracellular oxygen. CONCLUSIONS: The ANN network inference approach and the examination of identified genes in the published literature within the context of the disease highlights the substantial influence of certain genes in sarcomas.

Mosaic epigenetic dysregulation of ectodermal cells in autism spectrum disorder.

DNA mutational events are increasingly being identified in autism spectrum disorder (ASD), but the potential additional role of dysregulation of the epigenome in the pathogenesis of the condition remains unclear. The epigenome is of interest as a possible mediator of environmental effects during development, encoding a cellular memory reflected by altered function of progeny cells. Advanced maternal age (AMA) is associated with an increased risk of having a child with ASD for reasons that are not understood. To explore whether AMA involves covert aneuploidy or epigenetic dysregulation leading to ASD in the offspring, we tested a homogeneous ectodermal cell type from 47 individuals with ASD compared with 48 typically developing (TD) controls born to mothers of ≥35 years, using a quantitative genome-wide DNA methylation assay. We show that DNA methylation patterns are dysregulated in ectodermal cells in these individuals, having accounted for confounding effects due to subject age, sex and ancestral haplotype. We did not find mosaic aneuploidy or copy number variability to occur at differentially-methylated regions in these subjects. Of note, the loci with distinctive DNA methylation were found at genes expressed in the brain and encoding protein products significantly enriched for interactions with those produced by known ASD-causing genes, representing a perturbation by epigenomic dysregulation of the same networks compromised by DNA mutational mechanisms. The results indicate the presence of a mosaic subpopulation of epigenetically-dysregulated, ectodermally-derived cells in subjects with ASD. The epigenetic dysregulation observed in these ASD subjects born to older mothers may be associated with aging parental gametes, environmental influences during embryogenesis or could be the consequence of mutations of the chromatin regulatory genes increasingly implicated in ASD. The results indicate that epigenetic dysregulatory mechanisms may complement and interact with DNA mutations in the pathogenesis of the disorder.

Predictive performance of microarray gene signatures: impact of tumor heterogeneity and multiple mechanisms of drug resistance.

Gene signatures have failed to predict responses to breast cancer therapy in patients to date. In this study, we used bioinformatic methods to explore the hypothesis that the existence of multiple drug resistance mechanisms in different patients may limit the power of gene signatures to predict responses to therapy. In addition, we explored whether substratification of resistant cases could improve performance. Gene expression profiles from 1,550 breast cancers analyzed with the same microarray platform were retrieved from publicly available sources. Gene expression changes were introduced in cases defined as sensitive or resistant to a hypothetical therapy. In the resistant group, up to five different mechanisms of drug resistance causing distinct or overlapping gene expression changes were generated bioinformatically, and their impact on sensitivity, specificity, and predictive values of the signatures was investigated. We found that increasing the number of resistance mechanisms corresponding to different gene expression changes weakened the performance of the predictive signatures generated, even if the resistance-induced changes in gene expression were sufficiently strong and informative. Performance was also affected by cohort composition and the proportion of sensitive versus resistant cases or resistant cases that were mechanistically distinct. It was possible to improve response prediction by substratifying chemotherapy-resistant cases from actual datasets (non-bioinformatically perturbed datasets) and by using outliers to model multiple resistance mechanisms. Our work supports the hypothesis that the presence of multiple resistance mechanisms in a given therapy in patients limits the ability of gene signatures to make clinically useful predictions.

DACH1: its role as a classifier of long term good prognosis in luminal breast cancer.

BACKGROUND: Oestrogen receptor (ER) positive (luminal) tumours account for the largest proportion of females with breast cancer. Theirs is a heterogeneous disease presenting clinical challenges in managing their treatment. Three main biological luminal groups have been identified but clinically these can be distilled into two prognostic groups in which Luminal A are accorded good prognosis and Luminal B correlate with poor prognosis. Further biomarkers are needed to attain classification consensus. Machine learning approaches like Artificial Neural Networks (ANNs) have been used for classification and identification of biomarkers in breast cancer using high throughput data. In this study, we have used an artificial neural network (ANN) approach to identify DACH1 as a candidate luminal marker and its role in predicting clinical outcome in breast cancer is assessed. MATERIALS AND METHODS: A reiterative ANN approach incorporating a network inferencing algorithm was used to identify ER-associated biomarkers in a publically available cDNA microarray dataset. DACH1 was identified in having a strong influence on ER associated markers and a positive association with ER. Its clinical relevance in predicting breast cancer specific survival was investigated by statistically assessing protein expression levels after immunohistochemistry in a series of unselected breast cancers, formatted as a tissue microarray. RESULTS: Strong nuclear DACH1 staining is more prevalent in tubular and lobular breast cancer. Its expression correlated with ER-alpha positive tumours expressing PgR, epithelial cytokeratins (CK)18/19 and 'luminal-like' markers of good prognosis including FOXA1 and RERG (p<0.05). DACH1 is increased in patients showing longer cancer specific survival and disease free interval and reduced metastasis formation (p<0.001). Nuclear DACH1 showed a negative association with markers of aggressive growth and poor prognosis. CONCLUSION: Nuclear DACH1 expression appears to be a Luminal A biomarker predictive of good prognosis, but is not independent of clinical stage, tumour size, NPI status or systemic therapy.

SubNet: a Java application for subnetwork extraction.

SUMMARY: The extraction of targeted subnetworks is a powerful way to identify functional modules and pathways within complex networks. Here, we present SubNet, a Java-based stand-alone program for extracting subnetworks, given a basal network and a set of selected nodes. Designed with a graphical user-friendly interface, SubNet combines four different extraction methods, which offer the possibility to interrogate a biological network according to the question investigated. Of note, we developed a method based on the highly successful Google PageRank algorithm to extract the subnetwork using the node centrality metric, to which possible node weights of the selected genes can be incorporated. AVAILABILITY: http://www.zdzlab.org/1/subnet.html