Identifying metabolites by integrating metabolome databases with mass spectrometry cheminformatics.

Novel metabolites distinct from canonical pathways can be identified through the integration of three cheminformatics tools: BinVestigate, which queries the BinBase gas chromatography-mass spectrometry (GC-MS) metabolome database to match unknowns with biological metadata across over 110,000 samples; MS-DIAL 2.0, a software tool for chromatographic deconvolution of high-resolution GC-MS or liquid chromatography-mass spectrometry (LC-MS); and MS-FINDER 2.0, a structure-elucidation program that uses a combination of 14 metabolome databases in addition to an enzyme promiscuity library. We showcase our workflow by annotating N-methyl-uridine monophosphate (UMP), lysomonogalactosyl-monopalmitin, N-methylalanine, and two propofol derivatives

Editing of the urease gene by CRISPR-Cas in the diatom Thalassiosira pseudonana

Background: CRISPR-Cas is a recent and powerful addition to the molecular toolbox which allows programmable genome editing. It has been used to modify genes in a wide variety of organisms, but only two alga to date. Here we present a methodology to edit the genome of Thalassiosira pseudonana, a model centric diatom with both ecological significance and high biotechnological potential, using CRISPR-Cas. Results: A single construct was assembled using Golden Gate cloning. Two sgRNAs were used to introduce a precise 37 nt deletion early in the coding region of the urease gene. A high percentage of bi-allelic mutations (≤61.5%) were observed in clones with the CRISPR-Cas construct. Growth of bi-allelic mutants in urea led to a significant reduction in growth rate and cell size compared to growth in nitrate. Conclusions: CRISPR-Cas can precisely and efficiently edit the genome of T. pseudonana. The use of Golden Gate cloning to assemble CRISPR-Cas constructs gives additional flexibility to the CRISPR-Cas method and facilitates modifications to target alternative genes or species