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Harwood, T. V.

Publications and source records attributed to Harwood, T. V..

3 recordsLinked to original sources

Insights into the role of root exudates in bacteriophage infection dynamics

Bacteriophages impact soil bacteria through lysis, altering the availability of organic carbon and plant nutrients. However, the magnitude of nutrient uptake by plants from lysed bacteria remains unknown, partly because this process is challenging to investigate in the field. In this study, we extend ecosystem fabrication (EcoFAB 2.0) approaches to study plant-bacteria-phage interactions by comparing the impact of phage-lysed and uninfected 15N-labeled bacterial necromass on plant nitrogen acquisition and rhizosphere exometabolites composition. We show that grass Brachypodium distachyon derives some nitrogen from amino acids in uninfected Pseudomonas putida necromass but not from virocell necromass. Additionally, the bacterial necromass elicits the formation of rhizosphere exometabolites, some of which (guanosine), alongside tested aromatic acids (p-coumaric and benzoic acid), show distinct effects on bacteriophage-induced lysis when tested in vitro. The study highlights the dynamic feedback between bacterial necromass and plants and suggests that root exudate metabolites can impact bacteriophage infection dynamics.

plant biology↗

plantMASST - Community-driven chemotaxonomic digitization of plants

Understanding the distribution of hundreds of thousands of plant metabolites across the plant kingdom presents a challenge. To address this, we curated publicly available LC-MS/MS data from 19,075 plant extracts and developed the plantMASST reference database encompassing 246 botanical families, 1,469 genera, and 2,793 species. This taxonomically focused database facilitates the exploration of plant-derived molecules using tandem mass spectrometry (MS/MS) spectra. This tool will aid in drug discovery, biosynthesis, (chemo)taxonomy, and the evolutionary ecology of herbivore interactions.

plant biology↗

BLINK: Ultrafast tandem mass spectrometry cosine similarity scoring

SummaryMetabolomics has a long history of using cosine similarity to match experimental tandem mass spectra to databases for compound identification. Here we introduce the Blur-and-Link (BLINK) approach for scoring cosine similarity. BLINK calculates substantially equivalent cosine similarity scores (>99% identification agreement) over 1000 times faster than commonly used loop-based implementations by bypassing fragment alignment and simultaneously scoring all pairs of spectra using sparse matrix operations. This performance improvement can enable calculations to be performed that would typically be limited by time and available computational resources. Availability and ImplementationBLINK is implemented in Python3 and is published under a modified open source license. Code and license are available on Github: https://github.com/biorack/blink

bioinformatics↗