Evaluation of scoring functions and peptide exposure by fractionation
Ontology highlight
ABSTRACT: Evaluation of sensitivity and accuracy of widely used scoring functions Sequest, MaxQuant, Peaks, and Byonic. Spectra from E. coli were matched to human sequences, and human spectra from K052 cells were matched to A. loki sequences to determine specificity of matching and FDR estimation. A subsampling analysis of SCX-RP fractionation was performed.
Project description:Mass spectrometry remains an important method for analysis of modified nucleosides ubiquitously present in cellular RNAs, in particular for ribosomal and transfer RNAs that play crucial roles in mRNA translation and decoding. Furthermore, modifications have effect on the lifetimes of nucleic acids in plasma and cells and are consequently incorporated into RNA therapeutics. To provide an analytical tool for sequence characterization of modified RNAs, we developed Pytheas, an open-source software package for automated analysis of tandem MS data for RNA. This dataset contains the 95 MS/MS spectra of 3-14 nts-long oligomers, used for the training and validation of Pytheas' scoring function.
Project description:To improve identification of canonical and non-canonical protein isoforms, we introduced ProteomeGenerator, a framework for reference-guided and de novo proteogenomic database generation from transcriptomic sequencing dataset. The proteomic databases output by ProteomeGenerator contain only proteins encoded by actively transcribed genes, and includes sample-specific protein isoforms resulting from non-canonical transcription and mRNA editing. We applied this workflow to the proteogenomic analysis of spliceosome-defective K052 SRSF2(P95H) cells, demonstrating high-confidence identification of proteins isoforms arising from intron inclusion and non-canonical splicing, as well as improved overall estimation of false-discovery rate from the focused database assembled by ProteomeGenerator.
Project description:The Immunoscore is a method to quantify the immune cell infiltration within cancers to predict the disease prognosis. Previous immune profiling approaches relied on limited immune markers to establish patients’ tumor immunity. However, immune cells exhibit a higher-level complexity that is typically not obtained by the conventional immunohistochemistry methods. Herein, we present a spatially variant immune infiltration score, termed as SpatialVizScore, to quantify immune cells infiltration within lung tumor samples using multiplex protein imaging data. Imaging mass cytometry (IMC) was used to target 26 markers in tumors to identify stromal, immune, and cancer cell states within 26 human tissues from lung cancer patients. Unsupervised clustering methods dissected the spatial infiltration of cells in tissue using the high-dimensional analysis of 16 immune markers and other cancer and stroma enriched labels to profile alterations in the tumors’ immune infiltration patterns. Spatially resolved maps of distinct tumors determined the spatial proximity and neighborhoods of immune-cancer cell pairs. These SpatialVizScore maps provided a ranking of patients’ tumors consisting of immune inflamed, immune suppressed, and immune cold states, demonstrating the tumor’s immune continuum assigned to three distinct infiltration score ranges. Several inflammatory and suppressive immune markers were used to establish the cell-based scoring schemes at the single-cell and pixel-level, depicting the cellular spectra in diverse lung tissues. Thus, SpatialVizScore is an emerging quantitative method to deeply study tumor immunology in cancer tissues.
Project description:Cell-type biomarkers are useful in stem cell manufacture to monitor cell purification, cell quantity, and quality. However, the study on cell-type marker, specifically for stem cell manufacture, is limited. The emerging questions are which RNA transcripts can serve as biomarkers during stem cell culture, and what method can efficiently and accurately discover these biomarkers. We developed a scoring function system to identify small RNA (smRNA) biomarkers with RNA-seq data. We applied the method to two data sets, one for extracellular smRNAs and the other for intracellular smRNAs. To get the RNA-seq data from intracellular smRNAs, we cultured four types of cells: human embryo stem cells (H9), neural stem cells (NSC), hESC-derived endothelial cells (EC) and conducted small RNA-seq to their intracellular smRNAs. Using these data, we identified a set of smRNAs as candidates of biomarkers for different types of cells.
Project description:PirB is an inhibitory cell surface receptor particularly prominent on myeloid cells. PirB curtails the phenotypes of activated macrophages during inflammation or tumorigenesis, but its functions in macrophage homeostasis are obscure. To elucidate PirB-related functions in macrophages at steady-state, we generated and compared single-cell RNA-sequencing (scRNAseq) datasets obtained from myeloid cell subsets of wild type (WT) and PirB-deficient knockout (PirB KO) mice. To facilitate this analysis, we developed a novel approach to clustering parameter optimization called “Cluster Similarity Scoring and Distinction Index” (CaSSiDI). Our application of CaSSiDI in this study has revealed previously unknown roles for PirB in myeloid cell populations. In particular, we have discovered homeostatic functions for PirB that are related to Cebpb expression in distinct macrophage subsets. Our results establish the utility of CaSSiDI for single-cell assay analyses and the determination of optimal clustering parameters.
Project description:The proteome of the anaerobic bacterium Dehalococcoides mccartyi strain CBDB1 from the phylum Chloroflexi was investigated. D. mccartyi strain CBDB1 is a model organism for organohalide respiration where halogenated organic compounds serve as terminal electron acceptors. A wide range of halogenated organic compounds have been shown to be dehalogenated by the strain CBDB1. Therefore, D. mccartyi strain CBDB1 is a promising candidate for bioremediation application. Proteomic analysis of cultures grown with hexachlorobenzene as only electron acceptor resulted in identification of 8,491 distinct peptides which represents 1,023 proteins. A coverage of 70% of the 1,458 annotated proteins for strain CBDB1 was achieved. In addition, a spectral library was created from the annotated spectra. By using proteogenomics, 18 previously not annotated peptides were identified which contribute to four proteins previously not annotated and corrections in length of eight protein coding sequences.
Project description:The purpose of this study is to develop a new severity scoring tool for Low Anterior Resection Syndrome (LARS) drawing on the international consensus criteria for LARS as well as opinions of patients with lived-experience of LARS.