Project description:This was a 1500+ sample run taken in both positive and negative mode. This submission is just for the positive data.
These are fungal extracts grown by the Cichewicz Lab, prepared by Thillini P, and run on the McCall Lab Q Exactive Plus for the joint Natural Product libraries building grant.
These samples had previously had malaria docking on them. at this point of the study, the results of the docking are kept blind for data analysis.
Project description:negative data from the malaria extract run. postive done in separate job
These are fungal extracts from the natural product library R01. Previous malaria docking already done on samples.
Project description:Dichloromethane (DCM) extracts of aerial parts and roots of Waltheria indica analyzed in UHPLC-MS/MS in positive ionization mode. .raw, .mzML and MzMine2 processed files(spectra .mgf and feature table .csv) are available.
References:
Cretton, Sylvian, Stéphane Dorsaz, Antonio Azzollini, Quentin Favre-Godal, Laurence Marcourt, Samad Nejad Ebrahimi, Francine Voinesco, et al. 2016. “Antifungal Quinoline Alkaloids from Waltheria Indica.” Journal of Natural Products 79 (2): 300–307.
Cretton, S., L. Breant, L. Pourrez, C. Ambuehl, L. Marcourt, S. N. Ebrahimi, M. Hamburger, et al. 2014. “Antitrypanosomal Quinoline Alkaloids from the Roots of Waltheria Indica.” Journal of Natural Products 77 (10): 2304–11.
Project description:Data independent acquisition-mass spectrometry (DIA-MS) coupled with liquid chromatography is a promising approach for rapid, automatic sampling of MS/MS data in untargeted metabolomics. However, wide isolation windows in DIA-MS generate MS/MS spectra containing a mixed population of fragment ions together with their precursor ions. This precursor-fragment ion map in a comprehensive MS/MS spectral library is crucial for relative quantification of fragment ions uniquely representative of each precursor ion. However, existing reference libraries are not sufficient for this purpose since the fragmentation patterns of small molecules can vary in different instrument setups. Here we developed a bioinformatics workflow called MetaboDIA to build customized MS/MS spectral libraries using a user's own data dependent acquisition (DDA) data and to perform MS/MS-based quantification with DIA data, thus complementing conventional MS1-based quantification. MetaboDIA also allows users to build a spectral library directly from DIA data in studies of a large sample size. Using a marine algae data set, we show that quantification of fragment ions extracted with a customized MS/MS library can provide as reliable quantitative data as the direct quantification of precursor ions based on MS1 data. To test its applicability in complex samples, we applied MetaboDIA to a clinical serum metabolomics data set, where we built a DDA-based spectral library containing consensus spectra for 1829 compounds. We performed fragment ion quantification using DIA data using this library, yielding sensitive differential expression analysis. </br></br> Serum metabolome of 40 age-related macular degeneration patients and 20 control samples was analyzed using untargeted mass spectrometry. We used data dependent acquisition data to build a MS/MS spectral assay library for more than 1,000 compounds and performed targeted extraction of MS2 ion chromatograms from data independent acquisition analysis.
Project description:Here we found Rosa roxburghii fruit extracts effectively increase TERT expression and telomerase activity in cultured human mesenchymal stem cells. Both Rosa roxburghii fruit extracts by freeze drying and spray drying methods increase the activity of telomerase. Rosa roxburghii fruit freeze drying extracts is able to reduce reactive oxygen species levels, enhance SOD activity and resistance to oxidative stress, and reduce DNA damage caused by oxidative stress or radiation. Rosa roxburghii fruit extracts promoted cell proliferation, improved senescent cell morphology, delayed replicative cellular senescence, attenuated cell cycle supressors and alleviated the senescence-associated secretory phenotype. Transcriptome and metabolic profilings found that Rosa roxburghii fruit extract promote cell proliferation and DNA repair pathways, decreased triglycerides as well. Overall, we provided a theoretical basis for the application of Rosa roxburghii fruit as an anti-aging natural product.
Project description:As the importance of transcriptional variation and regulation for Plasmodium becomes more apparent, advances for non-falciparum species are hindered by our reliance on natural infections to study parasite biology. Untargeted transcriptomic research is also complicated by low parasite densities and high proportions of human genetic material, highlighting the need for optimized sample processing protocols. In this study, we used a P. knowlesi culture diluted in whole blood as a mock P. vivax natural infection to compare white blood cell, rRNA-, and globin depletion methods and RNA-seq library preparation kits to create an optimized protocol for low-volume sample processing.
Project description:Plants sense light and temperature changes to regulate flowering time. The expression of the florigen gene, FLOWERING LOCUS T (FT), peaks in the morning during spring, a different pattern than we observe in the lab. Providing our lab growth conditions with a red/far-red light ratio similar to open field conditions and average natural temperature oscillation is sufficient to mimic the FT expression and flowering time in natural long days. Here, we use RNA-seq to identify and understand the molecular differences between natural growth conditions, conventional lab growth conditions, and supplemented lab growth conditions that mimic natural conditions. Non-NIH grant(s): Grant ID: NSF 1656076 Grant title: Exploring Seasonal Flowering Mechanisms Affiliation: University of Washington Name: Takato Imaizumi
Project description:<p>Large-scale metabolite annotation is a challenge in liquid chromatogram-mass spectrometry (LC-MS)-based untargeted metabolomics. Here, we develop a metabolic reaction network (MRN)-based recursive algorithm (MetDNA) that expands metabolite annotations without the need for a comprehensive standard spectral library. MetDNA is based on the rationale that seed metabolites and their reaction-paired neighbors tend to share structural similarities resulting in similar MS2 spectra. MetDNA characterizes initial seed metabolites using a small library of MS2 spectra, and utilizes their experimental MS2 spectra as surrogate spectra to annotate their reaction-paired neighbor metabolites, which subsequently serve as the basis for recursive analysis. Using different LC-MS platforms, data acquisition methods, and biological samples, we showcase the utility and versatility of MetDNA and demonstrate that about 2000 metabolites can cumulatively be annotated from one experiment. Our results demonstrate that MetDNA substantially expands metabolite annotation, enabling quantitative assessment of metabolic pathways and facilitating integrative multi-omics analysis.</p><p><br></p><p><strong>Aging mouse liver positive mode</strong> is reported in <a href='https://www.ebi.ac.uk/metabolights/MTBLS601' rel='noopener noreferrer' target='_blank'><strong>MTBLS601</strong></a>.</p><p><strong>Aging mouse liver negative mode</strong> is reported in <a href='https://www.ebi.ac.uk/metabolights/MTBLS606' rel='noopener noreferrer' target='_blank'><strong>MTBLS606</strong></a>.</p><p><strong>Aging fruit fly positive mode</strong> is reported in <a href='https://www.ebi.ac.uk/metabolights/MTBLS612' rel='noopener noreferrer' target='_blank'><strong>MTBLS612</strong></a>.</p><p><strong>Aging fruit fly negative mode</strong> is reported in <a href='https://www.ebi.ac.uk/metabolights/MTBLS615' rel='noopener noreferrer' target='_blank'><strong>MTBLS615</strong></a>.</p>