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Genomics and metabolomics are widely used to explore specialized metabolite diversity. The Paired Omics Data Platform is a community initiative to systematically document links between metabolome and (meta)genome data, aiding identification of natural product biosynthetic origins and metabolite structures.

A thiazole-containing cyclic depsipeptide with 11 amino acid residues, named pagoamide A (1), was isolated from laboratory cultures of a marine Chlorophyte, Derbesia sp. This green algal sample was collected from America Samoa, and pagoamide A was isolated using guidance by MS/MS-based molecular networking. Cultures were grown in a light- and temperature-controlled environment and harvested after several months of growth. The planar structure of pagoamide A (1) was characterized by detailed 1D and 2D NMR experiments along with MS and UV analysis. The absolute configurations of its amino acid residues were determined by advanced Marfey's analysis following chemical hydrolysis and hydrazinolysis reactions. Two of the residues in pagoamide A (1), phenylalanine and serine, each occurred twice in the molecule, once in the d- and once in the l-configuration. The biosynthetic origin of pagoamide A (1) was considered in light of other natural products investigations with coenocytic green algae.

This report describes the first application of the novel NMR-based machine learning tool "Small Molecule Accurate Recognition Technology" (SMART 2.0) for mixture analysis and subsequent accelerated discovery and characterization of new natural products. The concept was applied to the extract of a filamentous marine cyanobacterium known to be a prolific producer of cytotoxic natural products. This environmental Symploca extract was roughly fractionated, and then prioritized and guided by cancer cell cytotoxicity, NMR-based SMART 2.0, and MS2-based molecular networking. This led to the isolation and rapid identification of a new chimeric swinholide-like macrolide, symplocolide A, as well as the annotation of swinholide A, samholides A-I, and several new derivatives. The planar structure of symplocolide A was confirmed to be a structural hybrid between swinholide A and luminaolide B by 1D/2D NMR and LC-MS2 analysis. A second example applies SMART 2.0 to the characterization of structurally novel cyclic peptides, and compares this approach to the recently appearing "atomic sort" method. This study exemplifies the revolutionary potential of combined traditional and deep learning-assisted analytical approaches to overcome longstanding challenges in natural products drug discovery.

INTRODUCTION:Urinary biomarkers are being developed to detect bladder cancer recurrence/progression in patients with non-muscle-invasive bladder cancer (NMIBC). We conducted a questionnaire-based study to determine what diagnostic accuracy and cost would such test(s) need for both patients and urologic oncologists to comfortably forgo surveillance cystoscopy in favour of these tests. METHODS:Surveys were administered to NMIBC patients at followup cystoscopy visit and to physician members of the Society of Urologic Oncology. Participants were questioned about acceptable false-negative (FN) rates and costs for such alternatives, in addition to demographics that could influence chosen error rates and costs. RESULTS:A total of 137 patient and 51 urologic oncologist responses were obtained. Seventy-seven percent of patients were not comfortable with urinary biomarker(s) alternatives to repeat cystoscopy, with a further 14% willing to accept such alternatives only if the FN rate were 0.5% or lower. Seventy-five percent of urologic oncologists were comfortable with an alternative urinary biomarker test(s), with 37% and 33% willing to accept FN rates of 5% and 1%, respectively. Forty-seven percent of patients were not willing to pay out-of-pocket for such tests, while 61% of urologic oncologists felt that a price range of $100-500 would be reasonable. CONCLUSIONS:This is the first survey evaluating patient and urologic oncologist perspectives on acceptable error rates and costs for urinary biomarker alternatives to surveillance cystoscopy for patients with NMIBC. Despite potential responder bias, this study suggests that urinary biomarker(s) will require sensitivity equivalent to that of cystoscopy in order to completely replace it in surveillance of patients with NMIBC.

Genome sequencing of microorganisms has revealed a greatly increased capacity for natural products biosynthesis than was previously recognized from compound isolation efforts alone. Hence, new methods are needed for the discovery and description of this hidden secondary metabolite potential. Here we show that provision of heavy nitrogen 15N-nitrate to marine cyanobacterial cultures followed by single-filament MALDI analysis over a period of days was highly effective in identifying a new natural product with an exceptionally high nitrogen content. The compound, named cryptomaldamide, was subsequently isolated using MS to guide the purification process, and its structure determined by 2D NMR and other spectroscopic and chromatographic methods. Bioinformatic analysis of the draft genome sequence identified a 28.7 kB gene cluster that putatively encodes for cryptomaldamide biosynthesis. Notably, an amidinotransferase is proposed to initiate the biosynthetic process by transferring an amidino group from arginine to serine to produce the first residue to be incorporated by the hybrid NRPS-PKS pathway. The maldiisotopic approach presented here is thus demonstrated to provide an orthogonal method by which to discover novel chemical diversity from Nature.

Cyanobacteria are major sources of oxygen, nitrogen, and carbon in nature. In addition to the importance of their primary metabolism, some cyanobacteria are prolific producers of unique and bioactive secondary metabolites. Chemical investigations of the cyanobacterial genus Moorea have resulted in the isolation of over 190 compounds in the last two decades. However, preliminary genomic analysis has suggested that genome-guided approaches can enable the discovery of novel compounds from even well-studied Moorea strains, highlighting the importance of obtaining complete genomes. We report a complete genome of a filamentous tropical marine cyanobacterium, Moorea producens PAL, which reveals that about one-fifth of its genome is devoted to production of secondary metabolites, an impressive four times the cyanobacterial average. Moreover, possession of the complete PAL genome has allowed improvement to the assembly of three other Moorea draft genomes. Comparative genomics revealed that they are remarkably similar to one another, despite their differences in geography, morphology, and secondary metabolite profiles. Gene cluster networking highlights that this genus is distinctive among cyanobacteria, not only in the number of secondary metabolite pathways but also in the content of many pathways, which are potentially distinct from all other bacterial gene clusters to date. These findings portend that future genome-guided secondary metabolite discovery and isolation efforts should be highly productive.

The high species richness of tropical forests has long been recognized, yet there remains substantial uncertainty regarding the actual number of tropical tree species. Using a pantropical tree inventory database from closed canopy forests, consisting of 657,630 trees belonging to 11,371 species, we use a fitted value of Fisher's alpha and an approximate pantropical stem total to estimate the minimum number of tropical forest tree species to fall between ∼ 40,000 and ∼ 53,000, i.e., at the high end of previous estimates. Contrary to common assumption, the Indo-Pacific region was found to be as species-rich as the Neotropics, with both regions having a minimum of ∼ 19,000-25,000 tree species. Continental Africa is relatively depauperate with a minimum of ∼ 4,500-6,000 tree species. Very few species are shared among the African, American, and the Indo-Pacific regions. We provide a methodological framework for estimating species richness in trees that may help refine species richness estimates of tree-dependent taxa.

BackgroundIn Brazil little is known about adverse reactions during donation and the donor characteristics that may be associated with such events. Donors are offered snacks and fluids before donating and are required to consume a light meal after donation. For these reasons the frequency of reactions may be different than those observed in other countries.Study design and methodsA cross-sectional study was conducted of eligible whole blood donors at three large blood centers located in Brazil between July 2007 and December 2009. Vasovagal reactions (VVRs) along with donor demographic and biometric data were collected. Reactions were defined as any presyncopal or syncopal event during the donation process. Multivariable logistic regression was performed to identify predictors of VVRs.ResultsOf 724,861 donor presentations, 16,129 (2.2%) VVRs were recorded. Rates varied substantially between the three centers: 53, 290, and 381 per 10,000 donations in Recife, São Paulo, and Belo Horizonte, respectively. Although the reaction rates varied, the donor characteristics associated with VVRs were similar (younger age [18-29 years], replacement donors, first-time donors, low estimated blood volume [EBV]). In multivariable analysis controlling for differences between the donor populations in each city younger age, first-time donor status, and lower EBV were the factors most associated with reactions.ConclusionFactors associated with VVRs in other locations are also evident in Brazil. The difference in VVR rates between the three centers might be due to different procedures for identifying and reporting the reactions. Potential interventions to reduce the risk of reactions in Brazil should be considered.

BackgroundIn Brazil little is known about adverse reactions during donation and the donor characteristics that may be associated with such events. Donors are offered snacks and fluids before donating and are required to consume a light meal after donation. For these reasons the frequency of reactions may be different than those observed in other countries.Study design and methodsA cross-sectional study was conducted of eligible whole blood donors at three large blood centers located in Brazil between July 2007 and December 2009. Vasovagal reactions (VVRs) along with donor demographic and biometric data were collected. Reactions were defined as any presyncopal or syncopal event during the donation process. Multivariable logistic regression was performed to identify predictors of VVRs.ResultsOf 724,861 donor presentations, 16,129 (2.2%) VVRs were recorded. Rates varied substantially between the three centers: 53, 290, and 381 per 10,000 donations in Recife, São Paulo, and Belo Horizonte, respectively. Although the reaction rates varied, the donor characteristics associated with VVRs were similar (younger age [18-29 years], replacement donors, first-time donors, low estimated blood volume [EBV]). In multivariable analysis controlling for differences between the donor populations in each city younger age, first-time donor status, and lower EBV were the factors most associated with reactions.ConclusionFactors associated with VVRs in other locations are also evident in Brazil. The difference in VVR rates between the three centers might be due to different procedures for identifying and reporting the reactions. Potential interventions to reduce the risk of reactions in Brazil should be considered.

IntroductionTo understand which signalling pathways become deregulated in breast cancer, it is necessary to identify functionally significant gene expression patterns in the stem, progenitor, transit amplifying and differentiated cells of the mammary epithelium. We have previously used the markers 33A10, CD24 and Sca-1 to identify mouse mammary epithelial cell subpopulations. We now investigate the relationship between cells expressing these markers and use gene expression microarray analysis to identify genes differentially expressed in the cell populations.MethodsFreshly isolated primary mouse mammary epithelial cells were separated on the basis of staining with the 33A10 antibody and an alpha-Sca-1 antibody. The populations identified were profiled using gene expression microarray analysis. Gene expression patterns were confirmed on normal mouse and human mammary epithelial subpopulations and were examined in a panel of breast cancer samples and cell lines.ResultsAnalysis of the separated populations demonstrated that Sca-1- 33A10High stained cells were estrogen receptor alpha (Esr1)- luminal epithelial cells, whereas Sca-1+ 33A10Low/- stained cells were a mix of nonepithelial cells and Esr1+ epithelial cells. Analysis of the gene expression data identified the gene Rgs2 (regulator of G-protein signalling 2) as being highly expressed in the Sca-1- 33A10Low/- population, which included myoepithelial/basal cells. RGS2 has previously been described as a regulator of angiotensin II receptor signalling. Gene expression analysis by quantitative real-time RT-PCR of cells separated on the basis of CD24 and Sca-1 expression confirmed that Rgs2 was more highly expressed in mouse myoepithelial/basal mammary cells than luminal cells. This expression pattern was conserved in normal human breast cells. Functional analysis demonstrated RGS2 to be a modulator of oxytocin receptor signalling. The potential significance of RGS2 expression in breast cancer was demonstrated by semi-quantitative RT-PCR analysis, data mining and quantitative real-time RT-PCR approaches, which showed that RGS2 was expressed in the majority of solid breast cancers at much higher levels than in normal human mammary cells.ConclusionMolecular analysis of prospectively isolated mammary epithelial cells identified RGS2 as a modulator of oxytocin receptor signalling, which is highly expressed in the myoepithelial cells. The RGS2 gene, but not the oxytocin receptor, was also shown to be over-expressed in the majority of breast cancers, identifying the product of this gene, or the pathway(s) it regulates, as potentially significant therapeutic targets.

IntroductionTo understand which signalling pathways become deregulated in breast cancer, it is necessary to identify functionally significant gene expression patterns in the stem, progenitor, transit amplifying and differentiated cells of the mammary epithelium. We have previously used the markers 33A10, CD24 and Sca-1 to identify mouse mammary epithelial cell subpopulations. We now investigate the relationship between cells expressing these markers and use gene expression microarray analysis to identify genes differentially expressed in the cell populations.MethodsFreshly isolated primary mouse mammary epithelial cells were separated on the basis of staining with the 33A10 antibody and an alpha-Sca-1 antibody. The populations identified were profiled using gene expression microarray analysis. Gene expression patterns were confirmed on normal mouse and human mammary epithelial subpopulations and were examined in a panel of breast cancer samples and cell lines.ResultsAnalysis of the separated populations demonstrated that Sca-1- 33A10High stained cells were estrogen receptor alpha (Esr1)- luminal epithelial cells, whereas Sca-1+ 33A10Low/- stained cells were a mix of nonepithelial cells and Esr1+ epithelial cells. Analysis of the gene expression data identified the gene Rgs2 (regulator of G-protein signalling 2) as being highly expressed in the Sca-1- 33A10Low/- population, which included myoepithelial/basal cells. RGS2 has previously been described as a regulator of angiotensin II receptor signalling. Gene expression analysis by quantitative real-time RT-PCR of cells separated on the basis of CD24 and Sca-1 expression confirmed that Rgs2 was more highly expressed in mouse myoepithelial/basal mammary cells than luminal cells. This expression pattern was conserved in normal human breast cells. Functional analysis demonstrated RGS2 to be a modulator of oxytocin receptor signalling. The potential significance of RGS2 expression in breast cancer was demonstrated by semi-quantitative RT-PCR analysis, data mining and quantitative real-time RT-PCR approaches, which showed that RGS2 was expressed in the majority of solid breast cancers at much higher levels than in normal human mammary cells.ConclusionMolecular analysis of prospectively isolated mammary epithelial cells identified RGS2 as a modulator of oxytocin receptor signalling, which is highly expressed in the myoepithelial cells. The RGS2 gene, but not the oxytocin receptor, was also shown to be over-expressed in the majority of breast cancers, identifying the product of this gene, or the pathway(s) it regulates, as potentially significant therapeutic targets.

IntroductionDiverse microarray and sequencing technologies have been widely used to characterise the molecular changes in malignant epithelial cells in breast cancers. Such gene expression studies to identify markers and targets in tumour cells are, however, compromised by the cellular heterogeneity of solid breast tumours and by the lack of appropriate counterparts representing normal breast epithelial cells.MethodsMalignant neoplastic epithelial cells from primary breast cancers and luminal and myoepithelial cells isolated from normal human breast tissue were isolated by immunomagnetic separation methods. Pools of RNA from highly enriched preparations of these cell types were subjected to expression profiling using massively parallel signature sequencing (MPSS) and four different genome wide microarray platforms. Functional related transcripts of the differential tumour epithelial transcriptome were used for gene set enrichment analysis to identify enrichment of luminal and myoepithelial type genes. Clinical pathological validation of a small number of genes was performed on tissue microarrays.ResultsMPSS identified 6,553 differentially expressed genes between the pool of normal luminal cells and that of primary tumours substantially enriched for epithelial cells, of which 98% were represented and 60% were confirmed by microarray profiling. Significant expression level changes between these two samples detected only by microarray technology were shown by 4,149 transcripts, resulting in a combined differential tumour epithelial transcriptome of 8,051 genes. Microarray gene signatures identified a comprehensive list of 907 and 955 transcripts whose expression differed between luminal epithelial cells and myoepithelial cells, respectively. Functional annotation and gene set enrichment analysis highlighted a group of genes related to skeletal development that were associated with the myoepithelial/basal cells and upregulated in the tumour sample. One of the most highly overexpressed genes in this category, that encoding periostin, was analysed immunohistochemically on breast cancer tissue microarrays and its expression in neoplastic cells correlated with poor outcome in a cohort of poor prognosis estrogen receptor-positive tumours.ConclusionUsing highly enriched cell populations in combination with multiplatform gene expression profiling studies, a comprehensive analysis of molecular changes between the normal and malignant breast tissue was established. This study provides a basis for the identification of novel and potentially important targets for diagnosis, prognosis and therapy in breast cancer.

IntroductionDiverse microarray and sequencing technologies have been widely used to characterise the molecular changes in malignant epithelial cells in breast cancers. Such gene expression studies to identify markers and targets in tumour cells are, however, compromised by the cellular heterogeneity of solid breast tumours and by the lack of appropriate counterparts representing normal breast epithelial cells.MethodsMalignant neoplastic epithelial cells from primary breast cancers and luminal and myoepithelial cells isolated from normal human breast tissue were isolated by immunomagnetic separation methods. Pools of RNA from highly enriched preparations of these cell types were subjected to expression profiling using massively parallel signature sequencing (MPSS) and four different genome wide microarray platforms. Functional related transcripts of the differential tumour epithelial transcriptome were used for gene set enrichment analysis to identify enrichment of luminal and myoepithelial type genes. Clinical pathological validation of a small number of genes was performed on tissue microarrays.ResultsMPSS identified 6,553 differentially expressed genes between the pool of normal luminal cells and that of primary tumours substantially enriched for epithelial cells, of which 98% were represented and 60% were confirmed by microarray profiling. Significant expression level changes between these two samples detected only by microarray technology were shown by 4,149 transcripts, resulting in a combined differential tumour epithelial transcriptome of 8,051 genes. Microarray gene signatures identified a comprehensive list of 907 and 955 transcripts whose expression differed between luminal epithelial cells and myoepithelial cells, respectively. Functional annotation and gene set enrichment analysis highlighted a group of genes related to skeletal development that were associated with the myoepithelial/basal cells and upregulated in the tumour sample. One of the most highly overexpressed genes in this category, that encoding periostin, was analysed immunohistochemically on breast cancer tissue microarrays and its expression in neoplastic cells correlated with poor outcome in a cohort of poor prognosis estrogen receptor-positive tumours.ConclusionUsing highly enriched cell populations in combination with multiplatform gene expression profiling studies, a comprehensive analysis of molecular changes between the normal and malignant breast tissue was established. This study provides a basis for the identification of novel and potentially important targets for diagnosis, prognosis and therapy in breast cancer.