Untargeted Identification of Alkyne-Containing Natural Products Using Ruthenium-Catalyzed Azide Alkyne Cycloaddition Reactions Coupled to LC-MS/MS

Abstract

Alkyne-containing natural products have been identified from plants, insects, algae, fungi, and bacteria. This class of natural products has been characterized as having a variety of biological activities. Polyynes are a subclass of acetylenic natural products that contain conjugated alkynes and are underrepresented in natural product databases due to the fact that they decompose during purification. Here we report a workflow that utilizes alkyne azide cycloaddition (AAC) reactions followed by LC-MS/MS analysis to identify acetylenic natural products. In this report, we demonstrate that alkyne azide cycloaddition reactions with p-bromobenzyl azide result in p-bromobenzyl-substituted triazole products that fragment to a common brominated tropylium ion. We were able to identify a synthetic alkyne spiked into the extract of Anabaena sp. PCC 7120 at a concentration of 10 μg/mL after optimization of MS/MS conditions. We then successfully identified the known natural product fischerellin A in the extract of Fischerella muscicola PCC 9339. Lastly, we identified the recently identified natural products protegenins A and C from Pseudomonas protegens Pf-5 through a combination of genome mining and RuAAC reactions. This is the first report of RuAAC reactions to detect acetylenic natural products. We also compare CuAAC and RuAAC reactions and find that CuAAC reactions produce fewer byproducts compared to RuAAC but is limited to terminal-alkyne-containing compounds. In contrast, RuAAC is capable of identification of both terminal and internal acetylenic natural products, but byproducts need to be eliminated from analysis by creation of an exclusion list. We believe that both CuAAC and RuAAC reactions coupled to LC-MS/MS represent a method for the untargeted identification of acetylenic natural products, but each method has strengths and weaknesses.

Structures and Biosynthesis of Caryoynencins, Unstable Bacterial Polyynes from Pseudomonas protegens Recombinant Expressing the cayG Gene

“…Protegenin A ( 6 ) was also discovered from P. protegens strains CHA0 and Pf-5 by Mullins et al , They renamed 6 to protegencin A. The BGC for protegenins ( proA − H ) was simple compared with those for cepacins and collimonins (Figures B and S1).…”

Investigation of Kinetic, Equilibrium, and Thermodynamic Modeling of Perfluorooctanoic Acid (PFOA) Adsorption in the Presence of Natural Organic Matter (NOM) by Dielectric Barrier Discharge Plasma-Modified Granular Activated Carbon (GAC)

“…Therefore, CPRW was prepared in the form of total solid and total suspended solid for FTIR analysis of NOM-TS and NOM-TSS, respectively. This characteristic is evident in the NOM-TS FTIR spectrum (Figure 6a) from CPRW, where the peak at 3292 cm −1 is assigned to the O-H stretching of the hydroxylic group which is common in NOM [68]. The absorbance peak at 2108 cm −1 , representing C≡C stretching vibrations (non-polar), suggests the presence of alkyne groups.…”

New azodyrecins identified by a genome mining-directed reactivity-based screening

“…HRMS showed that compound 8 possesses two additional hydrogens compared to 2 and 5, while compounds 9 and 10 possess two additional hydrogens compared to compounds 3 and 6. These data, together with 2D NMR spectra showed that compounds 8, 9, and 10 were azodyrecin derivatives with saturated alkyl side chains, which were named azodyrecin E (8), azodyrecin F (9), and azodyrecin G (10), respectively (Figure S3, Supporting Information File 1). Although azodyrecins characteristically possess branched alkyl side chains, compound 10 is the only azodyrecin analog with a straight alkyl chain.…”

“…The reactions usually facilitate the subsequent isolation process of the target molecules. This strategy has been successfully applied for detecting a range of peculiar functional groups, such as ureido [ 7 ], isocyanide [ 8 ], and alkyne [ 9 – 10 ]. A combination of reactivity-based screening and genome-based prioritization would allow the prediction of the producer of natural products with the functional groups of interest, leading to a higher rate of hits.…”