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Author(s): Louis J. Cohen; Daria Esterhazy; Seong-Hwan Kim; Christophe Lemetre; Rhiannon R. Aguilar; Emma A. Gordon; Amanda J. Pickard; Justin R. Cross; Ana B. Emiliano; Sun M. Han; John Chu; [...]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

We have used proteomic fingerprinting to investigate diagnosis of Alzheimer's disease (AD). Samples of lumbar cerebrospinal fluid (CSF) from clinically-diagnosed AD cases (n = 33), age-matched controls (n = 20), and mild cognitive impairment (MCI) patients (n = 10) were used to obtain proteomic profiles, followed by bioinformatic analysis that generated a set of potential biomarkers in CSF samples that could discriminate AD cases from controls. The identity of the biomarker ions was determined using mass spectroscopy. The panel of seven peptide biomarker ions was able to discriminate AD patients from controls with a median accuracy of 95% (sensitivity 85%, specificity 97%). When this model was applied to an independent blind dataset from MCI patients, the intensity of signals was intermediate between the control and AD patients implying that these markers could potentially predict patients with early neurodegenerative disease. The panel were identified, in order of predictive ability, as SPARC-like 1 protein, fibrinogen alpha chain precursor, amyloid-β, apolipoprotein E precursor, serum albumin precursor, keratin type I cytoskeletal 9, and tetranectin. The 7 ion ANN model was further validated using an independent cohort of samples, where the model was able to classify AD cases from controls with median accuracy of 84.5% (sensitivity 93.3%, specificity 75.7%). Validation by immunoassay was performed on the top three identified markers using the discovery samples and an independent sample cohort which was from postmortem confirmed AD patients (n = 17). [ABSTRACT FROM AUTHOR]

A correction to the article "SubNet: a Java application for subnetwork extraction" that was published in the 2013 issue is presented.

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. [ABSTRACT FROM AUTHOR]

Gonorrhea, which is caused by Neisseria gonorrhoeae , is the second most reported 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., Competing Interests: Competing Interest Statement: The authors declare no competing financial interests.

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., (Copyright © 2019 Estrela et al.)

Technological achievements have always contributed to the advancement of biomedical research. It has never been more so than in recent times, when the development and application of innovative cutting-edge technologies have transformed biology into a data-rich quantitative science. This stunning revolution in biology primarily ensued from the emergence of microarrays over two decades ago. The completion of whole-genome sequencing projects and the advance in microarray manufacturing technologies enabled the development of tiling microarrays, which gave unprecedented genomic coverage. Since their first description, several types of application of tiling arrays have emerged, each aiming to tackle a different biological problem. Although numerous algorithms have already been developed to analyze microarray data, new method development is still needed not only for better performance but also for integration of available microarray data sets, which without doubt constitute one of the largest collections of biological data ever generated. In this chapter we first introduce the principles behind the emergence and the development of tiling microarrays, and then discuss with some examples how they are used to investigate different biological problems.

Purpose: To advance our understanding of mechanisms involved in tumor progression/regression, a CT26 colorectal mouse model treated intra-tumorally with DISC-herpes simplex virus as immunotherapy was used in the discovery and validation phases to investigate and ultimately identify biomarkers correlating with the failure to respond to immunotherapy., Experimental Design: For the discovery phase, serum protein/peptide profiles of a retrospective sample collection (total n=70) were analyzed using MALDI-TOF-MS combined with artificial neural networks. Following identification of the key predictive peptides using ESI-MS/MS, validation of the identified proteins was carried out on serum and tissues collected in an independent sample set (total n=60)., Results: Artificial neural network analysis resulted in four discriminatory peaks with an accuracy of 86%, sensitivity of 90% and specificity of 81% between the progressor/regressor groups. Three of the identified discriminatory markers were upregulated and demonstrated a positive correlation with tumor progression following DISC-herpes simplex virus therapy. Immunovalidation studies corroborated the MALDI-TOF-MS findings. Immunohistochemistry revealed that serum amyloid A-1 and serum amyloid P produced in the liver localized intracellularly in CT26 tumor tissue., Conclusions: MALDI-TOF-MS and BI analysis of the serum proteome of tumor-bearer mice undergoing immunotherapy, identified biomarkers associating with "failure to respond" and biological arrays confirmed these findings., (Copyright © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Introduction: Breast cancer is a heterogeneous disease encompassing a number of phenotypically diverse tumours. Expression levels of the oestrogen, progesterone and HER2/neu receptors which characterize clinically distinct breast tumours have been shown to change during disease progression and in response to systemic therapies. Mi(cro)RNAs play critical roles in diverse biological processes and are aberrantly expressed in several human neoplasms including breast cancer, where they function as regulators of tumour behaviour and progression. The aims of this study were to identify miRNA signatures that accurately predict the oestrogen receptor (ER), progesterone receptor (PR) and HER2/neu receptor status of breast cancer patients to provide insight into the regulation of breast cancer phenotypes and progression., Methods: Expression profiling of 453 miRNAs was performed in 29 early-stage breast cancer specimens. miRNA signatures associated with ER, PR and HER2/neu status were generated using artificial neural networks (ANN), and expression of specific miRNAs was validated using RQ-PCR., Results: Stepwise ANN analysis identified predictive miRNA signatures corresponding with oestrogen (miR-342, miR-299, miR-217, miR-190, miR-135b, miR-218), progesterone (miR-520g, miR-377, miR-527-518a, miR-520f-520c) and HER2/neu (miR-520d, miR-181c, miR-302c, miR-376b, miR-30e) receptor status. MiR-342 and miR-520g expression was further analysed in 95 breast tumours. MiR-342 expression was highest in ER and HER2/neu-positive luminal B tumours and lowest in triple-negative tumours. MiR-520g expression was elevated in ER and PR-negative tumours., Conclusions: This study demonstrates that ANN analysis reliably identifies biologically relevant miRNAs associated with specific breast cancer phenotypes. The association of specific miRNAs with ER, PR and HER2/neu status indicates a role for these miRNAs in disease classification of breast cancer. Decreased expression of miR-342 in the therapeutically challenging triple-negative breast tumours, increased miR-342 expression in the luminal B tumours, and downregulated miR-520g in ER and PR-positive tumours indicates that not only is dysregulated miRNA expression a marker for poorer prognosis breast cancer, but that it could also present an attractive target for therapeutic intervention.