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GNPS - Refactoring the cryptic streptophenazine biosynthetic gene cluster unites phenazine, polyketide, and nonribosomal peptide biochemistry (for Figure S3)

ABSTRACT: mzMXL files used to create Figure S3, related to Figures 2 and 3

INSTRUMENT(S): 6530 Accurate-Mass Q-TOF (Agilent instrument)

ORGANISM(S): Streptomyces (ncbitaxon:1883)

SUBMITTER: Bradley S. Moore

PROVIDER: MSV000083082 | GNPS | Mon Oct 29 15:51:00 GMT 2018

REPOSITORIES: GNPS

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GNPS - Refactoring the cryptic streptophenazine biosynthetic gene cluster unites phenazine, polyketide, and nonribosomal peptide biochemistry

Project description:mxXML files used to generate Figure 3 and Figure S4

2018-10-29 | MSV000083081 | GNPS

Quantitative Proteome Remodeling Characterization of Two Human Reference Pluripotent Stem Cell Lines During Neurogenesis and Cardiomyogenesis

Project description:Supporting raw MS data for paper (doi: 10.1002/pmic.202100246) by Nam K.H. et al, titled "Quantitative Proteome Remodeling Characterization of Two Human Reference Pluripotent Stem Cell Lines During Neurogenesis and Cardiomyogenesis". Index of RAW files uploaded: - Related to Figure 1 (KN97-120: whole proteome (Unimod: 35; 2016; 4)). - Related to Figure 2 (KN121-126: phospho proteome (Unimod: 35; 21; 2016; 4)) - Related to Figures 3 and 4 (KN205-228: whole proteome (Unimod: 35; 2016; 4))

2022-02-14 | MSV000088833 | MassIVE

Analysis of botanicals and botanical supplements by LC-MS/MS-based molecular networking: approaches for annotating plant metabolites and authentication

Project description:These data are LC-MS/MS files associated with the journal article (title above). Files represent botanical or supplement extracts and species and plant parts are designated in file titles. Additionally chromatography fractions are also identified as is a file for the standards used in the analysis (aloin A/B, echinacoside, berberine, withaferin A, 23-epi-26-deoxyactein). These files were used to create figures 2-6 and all supplementary networking figures.

2022-02-22 | MSV000088895 | MassIVE

Strain dropouts reveal interactions that govern the metabolic output of gut microbiome

Project description:Folder 1 (CsCh_Dropouts_Chow) includes the raw MS data of the strain-dropout study on the Chow diet, related to Figures 3, 4 and 7 Folder 2 (hCom_Hum_Conv_BAs) includes the raw MS data of the reproducibility study for hCom1a-colonized mice, related to Figure 1 and S7

2023-04-20 | MSV000091763 | MassIVE

EMpire: Deep isoform level integration of the transcriptome, translatome, and proteome

Project description:In this study, we make used of mRNA-seq and its ability to reliably quantify isoforms, integrating this data with ribosome profiling and LC-MS/MS, to assign ribosome footprints and peptides at the isoform level. We leverage the principle that most cell types, and even tissues, predominantly express a single principal isoform to set isoform-level mRNA-seq quantifications as priors to guide and improve allocation of footprints or peptides to isoforms. Through tightly integrated mRNAseq, ribosome footprinting and/or LC-MS/MS proteomics we demonstrate that a principal isoform can be identified in over 80% of gene products in homogenous HEK293 cell culture and over 70% of proteins detected in complex human brain tissue. Defining isoforms in experiments with matched RNA-seq and translatomic/proteomic data increases the functional relevance of such datasets and will further broaden our understanding of multi-level control of gene expression. In this PRIDE submission you will find the raw files for the HEK293 cell proteomics. Files for the human brain proteomics can be found at PXD005445. We have also uploaded a zip file that contains the input files for our HEK293 cell analysis, and the isoform level output files – there is a separate folder within the zip files for these. The data used to create the manuscript figures is in the Rdata file. Code for assigning peptides and footprints to isoforms can be found on Github here: https://github.com/rkitchen/EMpire

2018-08-21 | PXD008693 | Pride

Whole genome CRISPR screens in SC-islet grafts under allogeneic rejection (Hu. Mice) [CRISPR]

Project description:A whole genome screen using a CRISPR lentivirus library (Doench et al., 2016) was performed. The Brunello CRISPR library consists of a pool of 76,441 human targeting guide RNAs (gRNA) and 1000 control gRNAs [non-targeting (NT) or intergenic], in a lentiviral vector that expresses Cas9. The pooled library targets 19,114 human genes, most of them by four gRNA per gene. To avoid multiple different gRNA in cells and a nonspecific effect on the screen results (Doench, 2018), a low infection lentivirus titer (multiplicity of infection that is <1) was used. Library transduced cells (LT SC-islets) were allowed at least 10 days for CRISPR editing, before transplantation to the NSG-MHCnull mouse model, where PBMCs were injected to half of the cohort (hPi mice: n=6, control mice: n=6) (Figures 3A). hPi mice retained levels of circulating T cells throughout the experiment (Figures S3A and S3B). Graft function and subsequent failure due to human PBMC injection was assessed (Figures 3B and S3C). When hPi graft failure was confirmed, 10 weeks after PBMC injection (Figure 3B), both control and hPi grafts were recovered from kidney sites, genomic DNA (gDNA) was extracted, and gRNA regions were amplified by PCR for Illumina sequencing.

2022-09-01 | GSE200085 | GEO

30 synthetic peptide fragments of proteins from the human microbiota

Project description:The peptides shown in Table 2 and Supplementary Table S3 were found in MS/MS spectra search against the HuMiProt90 database and validated several times — both in silico and by comparison with the spectra of synthetic peptides. The in silico approach included machine learning used by Scaffold 4 software to validate identifications based on the target-decoy approach (FDR 0.56% by PSM), as well as filtering homologous sequences among known human proteins, taking into account possible single amino acid polymorphism. The key stage of validation was the production of 30 synthetic peptides identified as fragments of proteins from the human microbiota. Identification, de novo or by searching against databases, cannot serve as the ultimate stage of investigation because it contains some deliberately incorrect identifications. Figure 2B demonstrates an example of spectrum comparison for a sequence identified in the plasma/serum and a synthetic peptide. Similar pairs of spectra for all 30 peptides are shown in Supplementary Figures S1. The correlation between the mass spectra of blood plasma/serum samples and the spectra of synthetic peptides is not less than 0.7 (for 23 peptides, the correlation is more than 0.8).

2024-06-14 | PXD027675 | Pride

GNPS Analysis of botanicals and botanical supplements by LC-MS/MS-based molecular networking: approaches for annotating plant metabolites and authentication

2022-02-22 | MSV000088895 | GNPS

In situ synthesis of peptide microarrays - shadow mask design [1]

Project description:A computer program was used to create random amino acid sequences based on and restricted by physical shadow masks which will be used for lithography-based synthesis of peptides. The output from this algorithm was used to create peptides that were synthesized by Sigma Aldrich, and printed onto glass slides. The arrays contained 384 peptides printed in duplicate for each of 4 different mask designs. 52 different monoclonal antibodies were incubated on these microarrays and analyzed for their propensity to bind the peptides created from each mask set. The diversity of binding served as a proxy for the 'randomness' of these peptides, and provided information about how many masks are needed to truly generate random sequence peptides.

2014-01-16 | GSE49217 | GEO

TARGET-seq: novel method for single-cell mutational analysis and parallel RNA-sequencing [validation in cell lines; Figure 2 and Figure S3]

Project description:TARGET-seq: novel method for single-cell mutational analysis and parallel RNA-sequencing [validation in cell lines; Figure 2 and Figure S3]

| PRJNA415204 | ENA

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