Chemically informed analyses of metabolomics mass spectrometry data with Qemistree.

Untargeted mass spectrometry is employed to detect small molecules in complex biospecimens, generating data that are difficult to interpret. We developed Qemistree, a data exploration strategy based on the hierarchical organization of molecular fingerprints predicted from fragmentation spectra. Qemistree allows mass spectrometry data to be represented in the context of sample metadata and chemical ontologies. By expressing molecular relationships as a tree, we can apply ecological tools that are designed to analyze and visualize the relatedness of DNA sequences to metabolomics data. Here we demonstrate the use of tree-guided data exploration tools to compare metabolomics samples across different experimental conditions such as chromatographic shifts. Additionally, we leverage a tree representation to visualize chemical diversity in a heterogeneous collection of samples. The Qemistree software pipeline is freely available to the microbiome and metabolomics communities in the form of a QIIME2 plugin, and a global natural products social molecular networking workflow.

Tiny Earth: A Big Idea for STEM Education and Antibiotic Discovery.

The world faces two seemingly unrelated challenges-a shortfall in the STEM workforce and increasing antibiotic resistance among bacterial pathogens. We address these two challenges with Tiny Earth, an undergraduate research course that excites students about science and creates a pipeline for antibiotic discovery.

Draft Genome Sequence of Micromonospora sp. Strain WMMA1996, a Marine Sponge-Associated Bacterium.

Micromonospora sp. strain WMMA1996 was isolated in 2013 off the coast of the Florida Keys, United States, from a marine sponge as part of bacterial coculture-based drug discovery initiatives. Analysis of the ∼6.44-Mb genome reveals this microbe's potential role in the discovery of new drugs.