Dataset Information

An Integrated Approach to Protein Discovery and Detection From Complex Biofluids.

ABSTRACT: Ovarian cancer, a leading cause of cancer-related deaths among women, has been notoriously difficult to screen for and diagnose early, as early detection significantly improves survival. Researchers and clinicians seek routinely usable and noninvasive screening methods; however, available methods (i.e., biomarker screening) lack desirable sensitivity/specificity. The most fatal form, high-grade serous ovarian cancer, often originate in the fallopian tube; therefore, sampling from the vaginal environment provides more proximal sources for tumor detection. To address these shortcomings and leverage proximal sampling, we developed an untargeted mass spectrometry microprotein profiling method and identified cystatin A, which was validated in an animal model. To overcome the limits of detection inherent to mass spectrometry, we demonstrated that cystatin A is present at 100 pM concentrations using a label-free microtoroid resonator and translated our workflow to patient-derived clinical samples, highlighting the potential utility of early stage detection where biomarker levels would be low.

SUBMITTER: Luu GT

PROVIDER: S-EPMC10388710 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature

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An Integrated Approach to Protein Discovery and Detection From Complex Biofluids.

Luu Gordon T GT Ge Chang C Tang Yisha Y Li Kailiang K Cologna Stephanie M SM Godwin Andrew K AK Burdette Joanna E JE Su Judith J Sanchez Laura M LM

Molecular & cellular proteomics : MCP 20230609 7

Ovarian cancer, a leading cause of cancer-related deaths among women, has been notoriously difficult to screen for and diagnose early, as early detection significantly improves survival. Researchers and clinicians seek routinely usable and noninvasive screening methods; however, available methods (i.e., biomarker screening) lack desirable sensitivity/specificity. The most fatal form, high-grade serous ovarian cancer, often originate in the fallopian tube; therefore, sampling from the vaginal env ...[more]

PMID: 37301378

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Project description:Microbiome research offers promising insights into the impact of microorganisms on biological systems. Metaproteomics, the study of microbial proteins at the community level, integrates genomic, transcriptomic, and proteomic data to determine the taxonomic and functional state of a microbiome. However, standard metaproteomics software is subject to several limitations, commonly supporting only spectral counts, emphasizing exploratory analysis rather than hypothesis testing and rarely offering the ability to analyze the interaction of function and taxonomy - that is, which taxa are responsible for different processes.Here we present metaQuantome, a novel, multifaceted software suite that analyzes the state of a microbiome by leveraging complex taxonomic and functional hierarchies to summarize peptide-level quantitative information, emphasizing label-free intensity-based methods. For experiments with multiple experimental conditions, metaQuantome offers differential abundance analysis, principal components analysis, and clustered heat map visualizations, as well as exploratory analysis for a single sample or experimental condition. We benchmark metaQuantome analysis against standard methods, using two previously published datasets: (1) an artificially assembled microbial community dataset (taxonomy benchmarking) and (2) a dataset with a range of recombinant human proteins spiked into an Escherichia coli background (functional benchmarking). Furthermore, we demonstrate the use of metaQuantome on a previously published human oral microbiome dataset.In both the taxonomic and functional benchmarking analyses, metaQuantome quantified taxonomic and functional terms more accurately than standard summarization-based methods. We use the oral microbiome dataset to demonstrate metaQuantome's ability to produce publication-quality figures and elucidate biological processes of the oral microbiome. metaQuantome enables advanced investigation of metaproteomic datasets, which should be broadly applicable to microbiome-related research. In the interest of accessible, flexible, and reproducible analysis, metaQuantome is open source and available on the command line and in Galaxy.

Dataset Information

An Integrated Approach to Protein Discovery and Detection From Complex Biofluids.

Publications

An Integrated Approach to Protein Discovery and Detection From Complex Biofluids.

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