Native mass spectrometry-based metabolomics identifies metal-binding compounds

Aron, Allegra T.; Petras, Daniel; Schmid, Robin; Gauglitz, Julia M.; Büttel, Isabell; Antelo, Luís T.; Zhi, Hui; Nuccio, Sean Paul; Saak, Christina C.; Malarney, Kien P.; Thines, Eckhard; Dutton, Rachel J.; Aluwihare, Lihini I.; Raffatellu, Manuela; Dorrestein, Pieter C.

doi:10.1038/s41557-021-00803-1

Cited by 35 publications

(32 citation statements)

References 91 publications

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“…lata is highly variable and could explain the broad differences in pathogenicity reported in several studies [ 6 , 87 – 89 ]. Future screens using untargeted metabolomics and the development of novel metabolomic methods [ 90 ] will be needed to confirm the diversity of metabolites produced, and how these compounds correlate with differences in pathogenicity and lifestyle of this species.…”

Section: Resultsmentioning

confidence: 99%

Population genomics of the grapevine pathogen Eutypa lata reveals evidence for population expansion and intraspecific differences in secondary metabolite gene clusters

et al. 2022

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Eutypa dieback of grapevine is an important disease caused by the generalist Ascomycete fungus Eutypa lata. Despite the relevance of this species to the global wine industry, its genomic diversity remains unknown, with only a single publicly available genome assembly. Whole-genome sequencing and comparative genomics was performed on forty Australian E. lata isolates to understand the genome evolution, adaptation, population size and structure of these isolates. Phylogenetic and linkage disequilibrium decay analyses provided evidence of extensive gene flow through sexual recombination between isolates obtained from different geographic locations and hosts. Investigation of the genetic diversity of these isolates suggested rapid population expansion, likely as a consequence of the recent growth of the Australian wine industry. Genomic regions affected by selective sweeps were shown to be enriched for genes associated with secondary metabolite clusters and included genes encoding proteins with a role in nutrient acquisition, degradation of host cell wall and metal and drug resistance, suggesting recent adaptation to both abiotic factors and potentially host genotypes. Genome synteny analysis using long-read genome assemblies showed significant intraspecific genomic plasticity with extensive chromosomal rearrangements impacting the secondary metabolite production potential of this species. Finally, k-mer based GWAS analysis identified a potential locus associated with mycelia recovery in canes of Vitis vinifera that will require further investigations.

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Section: Resultsmentioning

confidence: 99%

Population genomics of the grapevine pathogen Eutypa lata reveals evidence for population expansion and intraspecific differences in secondary metabolite gene clusters

et al. 2022

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“…Most importantly, the chromatographic dimension is also essential for the unambiguous linking of binding information to MS/MS features which facilitates dereplication and downstream structure elucidation. Online Postcolumn complex formation by addition of metal binding partner has been used, to study carbohydrates 67 and siderophores 68 , respectively, which we here expand to protein targets as binding partners. Initial tests with 12 proteins showed the accessibility of a wide range of protein targets by native metabolomics (Supplementary Fig.…”

Section: Discussionmentioning

confidence: 99%

Native metabolomics identifies the rivulariapeptolide family of protease inhibitors

et al. 2022

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The identity and biological activity of most metabolites still remain unknown. A bottleneck in the exploration of metabolite structures and pharmaceutical activities is the compound purification needed for bioactivity assignments and downstream structure elucidation. To enable bioactivity-focused compound identification from complex mixtures, we develop a scalable native metabolomics approach that integrates non-targeted liquid chromatography tandem mass spectrometry and detection of protein binding via native mass spectrometry. A native metabolomics screen for protease inhibitors from an environmental cyanobacteria community reveals 30 chymotrypsin-binding cyclodepsipeptides. Guided by the native metabolomics results, we select and purify five of these compounds for full structure elucidation via tandem mass spectrometry, chemical derivatization, and nuclear magnetic resonance spectroscopy as well as evaluation of their biological activities. These results identify rivulariapeptolides as a family of serine protease inhibitors with nanomolar potency, highlighting native metabolomics as a promising approach for drug discovery, chemical ecology, and chemical biology studies.

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“…Metal ions are certain atom compounds that usually form cations that have (a) positive electric charge(s). Metal ions play pivotal roles in protein structure, function, regulation, and stability [ 1 , 2 ]. Common metal ions include zinc (Zn 2+ ), calcium (Ca 2+ ), magnesium (Mg 2+ ), manganese (Mn 2+ ), iron (Fe 3+ or Fe 2+ ), copper (Cu 2+ ), cobalt (Co 2+ ), sodium (Na + ), potassium (K + ), and nickel (Ni 2+ ) ions.…”

Section: Introductionmentioning

confidence: 99%

A Comprehensive Review of Computation-Based Metal-Binding Prediction Approaches at the Residue Level

Zhou

Liang

et al. 2022

BioMed Research International

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Clear evidence has shown that metal ions strongly connect and delicately tune the dynamic homeostasis in living bodies. They have been proved to be associated with protein structure, stability, regulation, and function. Even small changes in the concentration of metal ions can shift their effects from natural beneficial functions to harmful. This leads to degenerative diseases, malignant tumors, and cancers. Accurate characterizations and predictions of metalloproteins at the residue level promise informative clues to the investigation of intrinsic mechanisms of protein-metal ion interactions. Compared to biophysical or biochemical wet-lab technologies, computational methods provide open web interfaces of high-resolution databases and high-throughput predictors for efficient investigation of metal-binding residues. This review surveys and details 18 public databases of metal-protein binding. We collect a comprehensive set of 44 computation-based methods and classify them into four categories, namely, learning-, docking-, template-, and meta-based methods. We analyze the benchmark datasets, assessment criteria, feature construction, and algorithms. We also compare several methods on two benchmark testing datasets and include a discussion about currently publicly available predictive tools. Finally, we summarize the challenges and underlying limitations of the current studies and propose several prospective directions concerning the future development of the related databases and methods.

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Native mass spectrometry-based metabolomics identifies metal-binding compounds

Cited by 35 publications

References 91 publications

Population genomics of the grapevine pathogen Eutypa lata reveals evidence for population expansion and intraspecific differences in secondary metabolite gene clusters

Population genomics of the grapevine pathogen Eutypa lata reveals evidence for population expansion and intraspecific differences in secondary metabolite gene clusters

Native metabolomics identifies the rivulariapeptolide family of protease inhibitors

A Comprehensive Review of Computation-Based Metal-Binding Prediction Approaches at the Residue Level

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