Few tools exist in
natural products discovery to integrate biological
screening and untargeted mass spectrometry data at the library scale.
Previously, we reported Compound Activity Mapping as a strategy for
predicting compound bioactivity profiles directly from primary screening
results on extract libraries. We now present NP Analyst, an open online
platform for Compound Activity Mapping that accepts bioassay data
of almost any type, and is compatible with mass spectrometry data
from major instrument manufacturers via the mzML format. In addition,
NP Analyst will accept processed mass spectrometry data from the MZmine
2 and GNPS open-source platforms, making it a versatile tool for integration
with existing discovery workflows. We demonstrate the utility of this
new tool for both the dereplication of known compounds and the discovery
of novel bioactive natural products using a challenging low-resolution
antimicrobial bioassay data set. This new platform is available at
.
Unicellular phototrophic algae can form massive blooms with up to millions of individual cells per milliliter in freshwater and marine ecosystems. Despite the temporal dominance of bloom formers many algal species can co-exist and compete for nutrients and space, creating a complex and diverse community. While microscopy and single cell genomics can address the taxonomic inventory, the cellular metabolome has yet to be thoroughly explored to determine the physiological status of microalgae. This might, however, provide a key to understand the observed species diversity in the homogeneous environment. Here, we introduce an effective, rapid and versatile method to analyze living single cells from aqueous substrata with laser-desorption/ionization mass spectrometry (LDI-MS) using a simple and inexpensive matrix-free support. The cells deposited on a cultivation-medium wetted support are analyzed with minimal disturbance as they remain in their natural viable state until their disruption during LDI-MS. Metabolites desorbed from single cells are analyzed on High-Resolution Mass Spectrometry (HR-MS) using the Orbitrap FT-MS technology to fingerprint cellular chemistry. This live single-cell mass spectrometry (LSC-MS) allows assessing the physiological status and strain-specifics of different microalgae, including marine diatoms and freshwater chlorophytes, at the single-cell level. We further report a reliable and robust data treatment pipeline to perform multivariate statistics on the replicated LSC-MS data. Comparing single cell MS spectra from natural phytoplankton samples and from laboratory strains allows the identification and discrimination of inter and intra-specific metabolic variability and thereby has promising applications in addressing highly complex phytoplankton communities. Notably, the herein described matrix-free live-single-cell LDI-HR-MS approach enables monitoring dynamics of the plankton and might explain why key-players survive, thrive, avoid selective feeding or pathogenic virus and bacteria, while others are overcome and die.
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