Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

Non-targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) is a widely used tool for metabolomics analysis, enabling the detection and annotation of small molecules in complex environmental samples. Data-dependent acquisition (DDA) of product ion spectra is thereby currently one of the most frequently applied data acquisition strategies. The optimization of DDA parameters is central to ensuring high spectral quality, coverage, and number of compound annotations. Here, we evaluated the influence of 10 central DDA settings of the Q Exactive mass spectrometer on natural organic matter samples from ocean, river, and soil environments. After data analysis with classical and feature-based molecular networking using MZmine and GNPS, we compared the total number of network nodes, multivariate clustering, and spectrum quality-related metrics such as annotation and singleton rates, MS/MS placement, and coverage. Our results show that , , and are the most critical parameters, whereas , , and had moderate and , , and minor effects. The insights into the data acquisition ergonomics of the Q Exactive platform presented here can guide new users and provide them with initial method parameters, some of which may also be transferable to other sample types and MS platforms.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10469366PMC
http://dx.doi.org/10.1021/acs.analchem.3c01202DOI Listing

Publication Analysis

Top Keywords

molecular networking
8
environmental samples
8
exactive platform
8
data acquisition
8
evaluation data-dependent
4
data-dependent ms/ms
4
acquisition
4
ms/ms acquisition
4
parameters
4
acquisition parameters
4

Similar Publications

Integrative profiling of lung cancer biomarkers EGFR, ALK, KRAS, and PD-1 with emphasis on nanomaterials-assisted immunomodulation and targeted therapy.

Front Immunol

September 2025

Department of Thoracic Surgery, Shenzhen People's Hospital (The First Affiliated Hospital, Southern University of Science and Technology; The Second Clinical Medical College, Jinan University), Shenzhen, Guangdong, China.

Background: Lung cancer remains the leading cause of cancer-related mortality globally, primarily due to late-stage diagnosis, molecular heterogeneity, and therapy resistance. Key biomarkers such as EGFR, ALK, KRAS, and PD-1 have revolutionized precision oncology; however, comprehensive structural and clinical validation of these targets is crucial to enhance therapeutic efficacy.

Methods: Protein sequences for EGFR, ALK, KRAS, and PD-1 were retrieved from UniProt and modeled using SWISS-MODEL to generate high-confidence 3D structures.

View Article and Find Full Text PDF

Isoform-specific expression patterns have been linked to stress-related psychiatric disorders such as major depressive disorder (MDD). To further explore their involvement, we constructed co-expression networks using total gene expression (TE) and isoform ratio (IR) data from affected ( = 210, 81% with depressive symptoms) and unaffected ( = 95) individuals. Networks were validated using advanced graph generation methods.

View Article and Find Full Text PDF

Purpose: This study aimed to conduct functional proteomics across breast cancer subtypes with bioinformatics analyses.

Methods: Candidate proteins were identified using nanoscale liquid chromatography with tandem mass spectrometry (NanoLC-MS/MS) from core needle biopsy samples of early stage (0-III) breast cancers, followed by external validation with public domain gene-expression datasets (TCGA TARGET GTEx and TCGA BRCA).

Results: Seventeen proteins demonstrated significantly differential expression and protein-protein interaction (PPI) found the strong networks including COL2A1, COL11A1, COL6A1, COL6A2, THBS1 and LUM.

View Article and Find Full Text PDF

Unravelling the molecular network structure of biohybrid hydrogels.

Mater Today Bio

October 2025

Leibniz Institute of Polymer Research Dresden, Division Polymer Biomaterials Science, Max Bergmann Center of Biomaterials Dresden, 01069, Dresden, Germany.

Glycosaminoglycan-based biohybrid hydrogels represent a powerful class of cell-instructive materials with proven potential in tissue engineering and regenerative medicine. Their biomedical functionality relies on a nanoscale polymer network that standard microscopy techniques cannot resolve. Here, we introduce an advanced analytical approach that integrates transmission electron microscopy, X-ray scattering, and computer simulations to directly and quantitatively characterize the nanoscale molecular network structure of these hydrogels.

View Article and Find Full Text PDF

modulates presynaptic Ca1.3 Ca channel function in inner hair cells (IHCs) and is required for indefatigable synaptic sound encoding. Biallelic variants in are associated with non-syndromic hearing loss (DFNB93).

View Article and Find Full Text PDF