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MetabolomicsGrowth Substrate and Prophage Induction Collectively Influence Metabolite and Lipid Profiles in a Marine Bacterium

Bacterial growth substrates influence a variety of biological functions, including the biosynthesis and regulation of lipid intermediates. The extent of this rewiring is not well understood nor has it been considered in the context of virally-infected cells. Here, we use a one-host-two-temperate ...

2022-08-04 | MTBLS5345 | MetaboLights
MetabolomicsDeep functional analysis of synII, a 770 kb synthetic yeast chromosome
Here we report the design, construction and characterization of a 770 Kb synthetic yeast chromosome II (synII). With the UPLC-MS method, we demonstrated synII maintains a nearly wild-type phenotype and fitness despite hundreds of designer editing to it. Our phenomics, transcriptomics, proteomics dat...
2016-10-13 | MTBLS296 | MetaboLights
ModelsShannon2004_VentricularMyocyte
This a model from the article: A mathematical treatment of integrated Ca dynamics within the ventricular myocyte. Shannon TR, Wang F, Puglisi J, Weber C, Bers DM. Biophys J. 15347581 , doi: 10.1529/biophysj.104.047449 Abst...
2005-01-01 | MODEL7914464799 | BioModels
Metabolomicsmetabolomics Analysis in Cecal Samples
Targeted LC/MS Metabolomics. Cecal contents were lyophilized overnight and approximately 2.5-5 mg was homogenized in 250 µL of 50% acidified acetonitrile (0.3% formic acid) for targeted LC/MS/MS metabolomics (acylcarnitines, amino acids, organic acids, nucleotides, and CoAs) according to validated, ...
2026-06-19 | MTBLS14783 | MetaboLights
ProteomicsAutomation of a CRISPRi platform for enhanced isoprenol production in Pseudomonas putida [DBTL6]
Recent advances in genome engineering technologies have significantly enhanced the ability to perturb microbial metabolic networks. Despite this progress, many bioproduction efforts struggle to parse complex metabolic datasets (e.g., -omics) within the constraints of the traditional design-build-tes...
ORGANISM(S): Pseudomonas putida KT2440 
2025-09-19 | PXD063746 | Pride
Machine learning Saf Isoprenol Jbei Laboratory automation Crispri 
ProteomicsAutomation of a CRISPRi platform for enhanced isoprenol production in Pseudomonas putida [DBTL3]
Recent advances in genome engineering technologies have significantly enhanced the ability to perturb microbial metabolic networks. Despite this progress, many bioproduction efforts struggle to parse complex metabolic datasets (e.g., -omics) within the constraints of the traditional design-build-tes...
ORGANISM(S): Pseudomonas putida KT2440 
2025-09-19 | PXD063740 | Pride
Machine learning Saf Isoprenol Jbei Laboratory automation Crispri 
ProteomicsAutomation of a CRISPRi platform for enhanced isoprenol production in Pseudomonas putida [DBTL5]
Recent advances in genome engineering technologies have significantly enhanced the ability to perturb microbial metabolic networks. Despite this progress, many bioproduction efforts struggle to parse complex metabolic datasets (e.g., -omics) within the constraints of the traditional design-build-tes...
ORGANISM(S): Pseudomonas putida KT2440 
2025-09-19 | PXD063744 | Pride
Machine learning Saf Isoprenol Jbei Laboratory automation Crispri 
ProteomicsAutomation of a CRISPRi platform for enhanced isoprenol production in Pseudomonas putida [DBTL4]
Recent advances in genome engineering technologies have significantly enhanced the ability to perturb microbial metabolic networks. Despite this progress, many bioproduction efforts struggle to parse complex metabolic datasets (e.g., -omics) within the constraints of the traditional design-build-tes...
ORGANISM(S): Pseudomonas putida KT2440 
2025-09-19 | PXD063743 | Pride
Machine learning Saf Isoprenol Jbei Laboratory automation Crispri 
ProteomicsAutomation of a CRISPRi platform for enhanced isoprenol production in Pseudomonas putida [DBTL2]
Recent advances in genome engineering technologies have significantly enhanced the ability to perturb microbial metabolic networks. Despite this progress, many bioproduction efforts struggle to parse complex metabolic datasets (e.g., -omics) within the constraints of the traditional design-build-tes...
ORGANISM(S): Pseudomonas putida KT2440 
2025-09-19 | PXD063738 | Pride
Machine learning Saf Isoprenol Jbei Laboratory automation Crispri 
ProteomicsAutomation of a CRISPRi platform for enhanced isoprenol production in Pseudomonas putida [DBTL1]
Recent advances in genome engineering technologies have significantly enhanced the ability to perturb microbial metabolic networks. Despite this progress, many bioproduction efforts struggle to parse complex metabolic datasets (e.g., -omics) within the constraints of the traditional design-build-tes...
ORGANISM(S): Pseudomonas putida KT2440 
2025-09-19 | PXD063737 | Pride
Machine learning Saf Isoprenol Jbei Laboratory automation Crispri 
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