Statistical analysis of feature-based molecular networking results from non-targeted metabolomics data.

Feature-based molecular networking (FBMN) is a popular analysis approach for liquid chromatography-tandem mass spectrometry-based non-targeted metabolomics data. While processing liquid chromatography-tandem mass spectrometry data through FBMN is fairly streamlined, downstream data handling and statistical interrogation are often a key bottleneck. Especially users new to statistical analysis struggle to effectively handle and analyze complex data matrices.

UmetaFlow: an untargeted metabolomics workflow for high-throughput data processing and analysis.

Metabolomics experiments generate highly complex datasets, which are time and work-intensive, sometimes even error-prone if inspected manually. Therefore, new methods for automated, fast, reproducible, and accurate data processing and dereplication are required. Here, we present UmetaFlow, a computational workflow for untargeted metabolomics that combines algorithms for data pre-processing, spectral matching, molecular formula and structural predictions, and an integration to the GNPS workflows Feature-Based Molecular Networking and Ion Identity Molecular Networking for downstream analysis.

Activation and Identification of a Griseusin Cluster in sp. CA-256286 by Employing Transcriptional Regulators and Multi-Omics Methods.

are well-known producers of a range of different secondary metabolites, including antibiotics and other bioactive compounds. Recently, it has been demonstrated that "silent" biosynthetic gene clusters (BGCs) can be activated by heterologously expressing transcriptional regulators from other BGCs. Here, we have activated a silent BGC in sp.

Characterization and engineering of Streptomyces griseofuscus DSM 40191 as a potential host for heterologous expression of biosynthetic gene clusters.

Streptomyces griseofuscus DSM 40191 is a fast growing Streptomyces strain that remains largely underexplored as a heterologous host. Here, we report the genome mining of S. griseofuscus, followed by the detailed exploration of its phenotype, including the production of native secondary metabolites and ability to utilise carbon, nitrogen, sulphur and phosphorus sources.

Complete Genome Sequence of the Rare Actinobacterium sp. Strain CA-103260.

Here, we report the sequencing, assembly, and annotation of the genome of the rare actinobacterium sp. strain CA-103260. The genome of CA-103260 was sequenced using PacBio and Illumina technologies and it consists of a circular 11,609,901-bp chromosome.

Discovery and Characterization of Epemicins A and B, New 30-Membered Macrolides from sp. CA-103260.

Actinobacteria have been a rich source of novel, structurally complex natural products for many decades. Although the largest genus is , from which the majority of antibiotics in current and past clinical use were originally isolated, other less common genera also have the potential to produce a wealth of novel secondary metabolites. One example is the genus, which currently contains only five reported species.

Programmable polyketide biosynthesis platform for production of aromatic compounds in yeast.

To accelerate the shift to bio-based production and overcome complicated functional implementation of natural and artificial biosynthetic pathways to industry relevant organisms, development of new, versatile, bio-based production platforms is required. Here we present a novel yeast-based platform for biosynthesis of bacterial aromatic polyketides. The platform is based on a synthetic polyketide synthase system enabling a first demonstration of bacterial aromatic polyketide biosynthesis in a eukaryotic host.