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Secondary metabolites are compounds not essential for an organism's development, but provide significant ecological and physiological benefits. These compounds have applications in medicine, biotechnology and agriculture. Their production is encoded in biosynthetic gene clusters (BGCs), groups of genes collectively directing their biosynthesis. The advent of metagenomics has allowed researchers to study BGCs directly from environmental samples, identifying numerous previously unknown BGCs encoding unprecedented chemistry. Here, we present the BGC Atlas (https://bgc-atlas.cs.uni-tuebingen.de), a web resource that facilitates the exploration and analysis of BGC diversity in metagenomes. The BGC Atlas identifies and clusters BGCs from publicly available datasets, offering a centralized database and a web interface for metadata-aware exploration of BGCs and gene cluster families (GCFs). We analyzed over 35 000 datasets from MGnify, identifying nearly 1.8 million BGCs, which were clustered into GCFs. The analysis showed that ribosomally synthesized and post-translationally modified peptides are the most abundant compound class, with most GCFs exhibiting high environmental specificity. We believe that our tool will enable researchers to easily explore and analyze the BGC diversity in environmental samples, significantly enhancing our understanding of bacterial secondary metabolites, and promote the identification of ecological and evolutionary factors shaping the biosynthetic potential of microbial communities.

Using automated genome analysis tools, it is often unclear to what degree genetic variability in homologous biosynthetic pathways relates to structural variation. This hampers strain prioritization and compound identification and can lead to overinterpretation of chemical diversity. Here, we assessed the metabolic potential of Nocardia, an underinvestigated actinobacterial genus that is known to comprise opportunistic human pathogens. Our analysis revealed a plethora of putative biosynthetic gene clusters of various classes, including polyketide, nonribosomal peptide, and terpenoid pathways. Furthermore, we used the highly conserved biosynthetic pathway for nocobactin-like siderophores to investigate how gene cluster differences correlate to structural differences in the produced compounds. Sequence similarity networks generated by BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) showed the presence of several distinct gene cluster families. Metabolic profiling of selected Nocardia strains using liquid chromatography-mass spectrometry (LC-MS) metabolomics data, nuclear magnetic resonance (NMR) spectroscopy, and GNPS (Global Natural Product Social molecular networking) revealed that nocobactin-like biosynthetic gene cluster (BGC) families above a BiG-SCAPE threshold of 70% can be assigned to distinct structural types of nocobactin-like siderophores.IMPORTANCE Our work emphasizes that Nocardia represent a prolific source for natural products rivaling better-characterized genera such as Streptomyces or Amycolatopsis Furthermore, we showed that large-scale analysis of biosynthetic gene clusters using similarity networks with high stringency allows the distinction and prediction of natural product structural variations. This will facilitate future genomics-driven drug discovery campaigns.

Obesity, characterized by the accumulation of excess fat, is a complex condition resulting from the combination of genetic and epigenetic factors. Recent studies have found correspondence between DNA methylation and cell differentiation, suggesting a role of the former in cell fate determination. There is a lack of comprehensive understanding concerning the underpinnings of preadipocyte differentiation, specifically when cells are undergoing terminal differentiation (TD). To gain insight into dynamic genome-wide methylation, 3T3 L1 preadipocyte cells were differentiated by a hormone cocktail. The genomic DNA was isolated from undifferentiated cells and 4 hours, 2 days postdifferentiated cells, and 15 days TD cells. We employed whole-genome bisulfite sequencing (WGBS) to ascertain global genomic DNA methylation alterations at single base resolution as preadipocyte cells differentiate. The genome-wide distribution of DNA methylation showed similar overall patterns in pre-, post-, and terminally differentiated adipocytes, according to WGBS analysis. DNA methylation decreases at 4 hours after differentiation initiation, followed by methylation gain as cells approach TD. Studies revealed novel differentially methylated regions (DMRs) associated with adipogenesis. DMR analysis suggested that though DNA methylation is global, noticeable changes are observed at specific sites known as "hotspots." Hotspots are genomic regions rich in transcription factor (TF) binding sites and exhibit methylation-dependent TF binding. Subsequent analysis indicated hotspots as part of DMRs. The gene expression profile of key adipogenic genes in differentiating adipocytes is context-dependent, as we found a direct and inverse relationship between promoter DNA methylation and gene expression. [ABSTRACT FROM AUTHOR]

Abstract Background Genome-wide gene expression profiling and detailed physiological investigation were used for understanding the molecular mechanism and physiological response of Gossypium herbaceum, which governs the adaptability of plants in drought conditions. Recently, microarray-based gene expression analysis is commonly used to decipher genes and genetic networks controlling the traits of interest. However, the results of such an analysis are often plagued due to a limited number of genes (probe sets) on microarrays. On the other hand, pyrosequencing of a transcriptome has the potential to detect rare as well as a large number of transcripts in the samples quantitatively. We used Affymetrix microarray as well as Roche's GS-FLX transcriptome sequencing for a comparative analysis of cotton transcriptome in leaf tissues under drought conditions. Results Fourteen accessions of Gossypium herbaceum were subjected to mannitol stress for preliminary screening; two accessions, namely Vagad and RAHS-14, were selected as being the most tolerant and most sensitive to osmotic stress, respectively. Affymetrix cotton arrays containing 24,045 probe sets and Roche's GS-FLX transcriptome sequencing of leaf tissue were used to analyze the gene expression profiling of Vagad and RAHS-14 under drought conditions. The analysis of physiological measurements and gene expression profiling showed that Vagad has the inherent ability to sense drought at a much earlier stage and to respond to it in a much more efficient manner than does RAHS-14. Gene Ontology (GO) studies showed that the phenyl propanoid pathway, pigment biosynthesis, polyketide biosynthesis, and other secondary metabolite pathways were enriched in Vagad under control and drought conditions as compared with RAHS-14. Similarly, GO analysis of transcriptome sequencing showed that the GO terms responses to various abiotic stresses were significantly higher in Vagad. Among the classes of transcription factors (TFs) uniquely expressed in both accessions, RAHS-14 showed the expression of ERF and WRKY families. The unique expression of ERFs in response to drought conditions reveals that RAHS-14 responds to drought by inducing senescence. This was further supported by transcriptome analysis which revealed that RAHS-14 responds to drought by inducing many transcripts related to senescence and cell death. Conclusion The comparative genome-wide gene expression profiling study of two accessions of G.herbaceum under drought stress deciphers the differential patterns of gene expression, including TFs and physiologically relevant processes. Our results indicate that drought tolerance observed in Vagad is not because of a single molecular reason but is rather due to several unique mechanisms which Vagad has developed as an adaptation strategy.