ArticleNPJ systems biology and applications2016
Integrating highly quantitative proteomics and genome-scale metabolic modeling to study pH adaptation in the human pathogen
Article in NPJ systems biology and applications, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Model-driven analysis reveals oxidative stress adaptation enabling efficient energy utilization in a Crabtree-negative Saccharomyces cerevisiae.Scientific reports · 2026Article
- Genome-scale metabolic model-guided systematic framework for designing customized live biotherapeutic products.NPJ systems biology and applications · 2025Review
- Insights into ecology, pathogenesis, and biofilm formation ofMicrobiology and molecular biology reviews : MMBR · 2025Review
- Proteome profiling of Campylobacter jejuni 81-176 at 37 °C and 42 °C by label-free mass spectrometry.BMC microbiology · 2024Article
- Differences of protein expression in enterococcus faecalis biofilm during resistance to environmental pressures.Technology and health care : official journal of the European Society for Engineering and Medicine · 2024Article
- Applications of genome-scale metabolic models to investigate microbial metabolic adaptations in response to genetic or environmental perturbations.Briefings in bioinformatics · 2023Review
- Parameter inference for enzyme and temperature constrained genome-scale models.Scientific reports · 2023Article
- Antibiotic Resistance Diagnosis in ESKAPE Pathogens-A Review on Proteomic Perspective.Diagnostics (Basel, Switzerland) · 2023Review
- Variations in protein expression associated with oral cancer.Technology and health care : official journal of the European Society for Engineering and Medicine · 2023Article
- Expanding the search for small-molecule antibacterials by multidimensional profiling.Nature chemical biology · 2022Review
- All Driven by Energy Demand? Integrative Comparison of Metabolism of Enterococcus faecalis Wildtype and a Glutamine Synthase Mutant.Microbiology spectrum · 2022Article
- Toward modeling metabolic state from single-cell transcriptomics.Molecular metabolism · 2022Review
- Inspecting the Solution Space of Genome-Scale Metabolic Models.Metabolites · 2022Article
- Advances in experimental and computational methodologies for the study of microbial-surface interactions at different omics levels.Frontiers in microbiology · 2022Review
- Path to improving the life cycle and quality of genome-scale models of metabolism.Cell systems · 2021Review
- Review
- Article
- Biomedical applications of genome-scale metabolic network reconstructions of human pathogens.Current opinion in biotechnology · 2018Review
- Systems biology of lactic acid bacteria: For food and thought.Current opinion in systems biology · 2017Review
- More than just a gut feeling: constraint-based genome-scale metabolic models for predicting functions of human intestinal microbes.Microbiome · 2017Review
Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genome-scale metabolic models represent the entirety of metabolic reactions of an organism based on the annotation of the respective genome. These models commonly allow all reactions to proceed concurrently, disregarding the fact that at no point all proteins will be present in a cell. The metabolic reaction space can be constrained to a more physiological state using experimentally obtained information on enzyme abundances. However, high-quality, genome-wide protein measurements have been challenging and typically transcript abundances have been used as a surrogate for protein measurements. With recent developments in mass spectrometry-based proteomics, exemplified by SWATH-MS, the acquisition of highly quantitative proteome-wide data at reasonable throughput has come within reach. Here we present methodology to integrate such proteome-wide data into genome-scale models. We applied this methodology to study cellular changes in
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.