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Kakhkhorov, S. A.

Publications and source records attributed to Kakhkhorov, S. A..

3 recordsLinked to original sources

Untargeted metabolomics reveals farming practice- and cultivar-driven modulations of pea (Pisum sativum L.) seed metabolome

This work presents untargeted LC-MS-based metabolome of ten cultivars of peas grown at three field sites following different agricultural practices. More than 1,200 metabolite features were detected in methanolic extracts of pea seed flours. Of these, nearly 300 features were identified using mass spectral libraries and advanced computational tools. Approximately 40 metabolites were found to be associated with location effect, independent of cultivar type. Organically grown pea samples showed lower level of the main pea triterpene glycoside soyasaponin I and higher levels of nitrogen-abundant amino acids indicating increased nitrogen availability in soil. More than 100 metabolites were associated with the location-independent cultivar effect. Two cultivars resistant to downy mildew and pea wilt, Akooma and Greenway, showed the most distinct metabolome with greater levels of polyunsaturated fatty acids and lipid oxidation products known to give beany off-flavors. The most commonly cultivated pea variety, Ingrid, had significantly lower levels or was completely devoid of hydroxycinnamic acid amides such as caffeoyl, feruloyl, and coumaroyl aspartates that were present in all other cultivars. Three chloroauxin metabolites, reported here for the first time, were identified through molecular networking within GNPS platform and propagation of annotation from a computationally predicted indole-3-acetic acid catabolite. Overall, the results indicate biochemical adaptation of pea plants to location or agricultural practice as reflected in their seed metabolome.

plant biology↗

A Universal Language for Finding Mass Spectrometry Data Patterns

Even though raw mass spectrometry data is information rich, the vast majority of the data is underutilized. The ability to interrogate these rich datasets is handicapped by the limited capability and flexibility of existing software. We introduce the Mass Spec Query Language (MassQL) that addresses these issues by enabling an expressive set of mass spectrometry patterns to be queried directly from raw data. MassQL is an open-source mass spectrometry query language for flexible and mass spectrometer manufacturer-independent mining of MS data. We envision the flexibility, scalability, and ease of use of MassQL will empower the mass spectrometry community to take fuller advantage of their mass spectrometry data and accelerate discoveries.

bioinformatics↗

Open Access Repository-Scale Propagated Nearest Neighbor Suspect Spectral Library for Untargeted Metabolomics

Despite the increasing availability of tandem mass spectrometry (MS/MS) community spectral libraries for untargeted metabolomics over the past decade, the majority of acquired MS/MS spectra remain uninterpreted. To further aid in interpreting unannotated spectra, we created a nearest neighbor suspect spectral library, consisting of 87,916 annotated MS/MS spectra derived from hundreds of millions of public MS/MS spectra. Annotations were propagated based on structural relationships to reference molecules using MS/MS-based spectrum alignment. We demonstrate the broad relevance of the nearest neighbor suspect spectral library through representative examples of propagation-based annotation of acylcarnitines, bacterial and plant natural products, and drug metabolism. Our results also highlight how the library can help to better understand an Alzheimers brain phenotype. The nearest neighbor suspect spectral library is openly available through the GNPS platform to help investigators hypothesize candidate structures for unknown MS/MS spectra in untargeted metabolomics data.

bioinformatics↗