Stimulation, Monitoring, and Analysis of Pathway Dynamics by Metabolic Profiling in the Aromatic Amino Acid Pathway
Using a concerted approach of biochemical standard preparation, analytical access via LC‐MS/MS, glucose pulse, metabolic profiling, and statistical data analysis, the metabolism dynamics in the aromatic amino acid pathway has been stimulated, monitored, and analyzed in different tyrosine‐auxotrophic...
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description | Using a concerted approach of biochemical standard preparation, analytical access via LC‐MS/MS, glucose pulse, metabolic profiling, and statistical data analysis, the metabolism dynamics in the aromatic amino acid pathway has been stimulated, monitored, and analyzed in different tyrosine‐auxotrophic l‐phenylalanine‐producing Escherichia coli strains. During the observation window from –4 s (before) up to 27 s after the glucose pulse, the dynamics of the first five enzymatic reactions in the aromatic amino acid pathway was observed by measuring intracellular concentrations of 3‐deoxy‐d‐arabino‐heptulosonate 7‐phosphate DAH(P), 3‐dehydroquinate (3‐DHQ), 3‐dehydroshikimate (3‐DHS), shikimate 3‐phosphate (S3P), and shikimate (SHI), together with the pathway precursors phosphoenolpyruvate (PEP) and P5P, the lumped pentose phosphate pool as an alternative to the nondetectable erythrose 4‐phosphate (E4P). Provided that a sufficient fortification of the carbon flux into the pathway of interest is ensured, respective metabolism dynamics can be observed. On the basis of the intracellular pool measurements, the standardized pool velocities were calculated, and a simple, data‐driven criterion‐called “pool efflux capacity” (PEC)‐is derived. Despite its simplifying system description, the criterion managed to identify the well‐known AroB limitation in the E. coli strain A (genotype Δ( pheA tyrA aroF)/pJF119EH aroFfbr pheAfbr amp) and it also succeeded to identify AroL and AroA (in strain B, genotype Δ( pheA tyrA aroF)/pJF119EH aroFfbr pheAfbr aroB amp) as promising metabolic engineering targets to alleviate respective flux control in subsequent l‐Phe producing strains. Furthermore, using of a simple correlation analysis, the reconstruction of the metabolite sequence of the observed pathway was enabled. The results underline the necessity to extend the focus of glucose pulse experiments by studying not only the central metabolism but also anabolic pathways. |
doi_str_mv | 10.1021/bp0498746 |
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During the observation window from –4 s (before) up to 27 s after the glucose pulse, the dynamics of the first five enzymatic reactions in the aromatic amino acid pathway was observed by measuring intracellular concentrations of 3‐deoxy‐d‐arabino‐heptulosonate 7‐phosphate DAH(P), 3‐dehydroquinate (3‐DHQ), 3‐dehydroshikimate (3‐DHS), shikimate 3‐phosphate (S3P), and shikimate (SHI), together with the pathway precursors phosphoenolpyruvate (PEP) and P5P, the lumped pentose phosphate pool as an alternative to the nondetectable erythrose 4‐phosphate (E4P). Provided that a sufficient fortification of the carbon flux into the pathway of interest is ensured, respective metabolism dynamics can be observed. On the basis of the intracellular pool measurements, the standardized pool velocities were calculated, and a simple, data‐driven criterion‐called “pool efflux capacity” (PEC)‐is derived. Despite its simplifying system description, the criterion managed to identify the well‐known AroB limitation in the E. coli strain A (genotype Δ( pheA tyrA aroF)/pJF119EH aroFfbr pheAfbr amp) and it also succeeded to identify AroL and AroA (in strain B, genotype Δ( pheA tyrA aroF)/pJF119EH aroFfbr pheAfbr aroB amp) as promising metabolic engineering targets to alleviate respective flux control in subsequent l‐Phe producing strains. Furthermore, using of a simple correlation analysis, the reconstruction of the metabolite sequence of the observed pathway was enabled. 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A.</creatorcontrib><creatorcontrib>Takors, R.</creatorcontrib><title>Stimulation, Monitoring, and Analysis of Pathway Dynamics by Metabolic Profiling in the Aromatic Amino Acid Pathway</title><title>Biotechnology progress</title><addtitle>Biotechnol Progress</addtitle><description>Using a concerted approach of biochemical standard preparation, analytical access via LC‐MS/MS, glucose pulse, metabolic profiling, and statistical data analysis, the metabolism dynamics in the aromatic amino acid pathway has been stimulated, monitored, and analyzed in different tyrosine‐auxotrophic l‐phenylalanine‐producing Escherichia coli strains. During the observation window from –4 s (before) up to 27 s after the glucose pulse, the dynamics of the first five enzymatic reactions in the aromatic amino acid pathway was observed by measuring intracellular concentrations of 3‐deoxy‐d‐arabino‐heptulosonate 7‐phosphate DAH(P), 3‐dehydroquinate (3‐DHQ), 3‐dehydroshikimate (3‐DHS), shikimate 3‐phosphate (S3P), and shikimate (SHI), together with the pathway precursors phosphoenolpyruvate (PEP) and P5P, the lumped pentose phosphate pool as an alternative to the nondetectable erythrose 4‐phosphate (E4P). Provided that a sufficient fortification of the carbon flux into the pathway of interest is ensured, respective metabolism dynamics can be observed. On the basis of the intracellular pool measurements, the standardized pool velocities were calculated, and a simple, data‐driven criterion‐called “pool efflux capacity” (PEC)‐is derived. Despite its simplifying system description, the criterion managed to identify the well‐known AroB limitation in the E. coli strain A (genotype Δ( pheA tyrA aroF)/pJF119EH aroFfbr pheAfbr amp) and it also succeeded to identify AroL and AroA (in strain B, genotype Δ( pheA tyrA aroF)/pJF119EH aroFfbr pheAfbr aroB amp) as promising metabolic engineering targets to alleviate respective flux control in subsequent l‐Phe producing strains. Furthermore, using of a simple correlation analysis, the reconstruction of the metabolite sequence of the observed pathway was enabled. The results underline the necessity to extend the focus of glucose pulse experiments by studying not only the central metabolism but also anabolic pathways.</description><subject>Amino acids</subject><subject>Amino Acids, Aromatic - biosynthesis</subject><subject>Aromatic compounds</subject><subject>Biological and medical sciences</subject><subject>Biotechnology</subject><subject>Chromatography, Liquid - methods</subject><subject>Computer Simulation</subject><subject>Escherichia coli - metabolism</subject><subject>Escherichia coli Proteins - metabolism</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Gene Expression Profiling - methods</subject><subject>Gene Expression Regulation, Bacterial - physiology</subject><subject>Glucose - metabolism</subject><subject>Kinetics</subject><subject>Mass Spectrometry - methods</subject><subject>Mass spectroscopy</subject><subject>Mathematical models</subject><subject>Metabolism</subject><subject>Models, Biological</subject><subject>Multienzyme Complexes - metabolism</subject><subject>Phenylalanine - biosynthesis</subject><subject>Q1</subject><subject>Signal Transduction - physiology</subject><subject>Statistical analysis</subject><issn>8756-7938</issn><issn>1520-6033</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2004</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kc1u1DAUhS0EotMpC14AeQMIqQH_JHa8DC3TIk3LUIpYWo7jUFPHHuyM2rx9jWaYrmB1Jd_vnKvjA8BLjN5jRPCHdo1KUfOSPQEzXBFUMETpUzCrecUKLmh9AA5T-oUQqhEjz8EBrqq8EmQG0rfRDhunRhv8MbwI3o4hWv_zGCrfwcYrNyWbYOjhSo03d2qCp5NXg9UJthO8MKNqg7MarmLorctCaD0cbwxsYhiyq4bNYH2AjbbdX4sj8KxXLpkXuzkH3xefrk_Oi-WXs88nzbLQpeCs6HtlWK9rorgxoq1bgnHO2GNM82uJmeDcaEaqjuZcFIuyrIjqOkFFXQtU0zl4u_Vdx_B7Y9IoB5u0cU55EzZJZjNMOOJlJt_8l2QcVxyVKIPvtqCOIaVoermOdlBxkhjJP13IfReZfbUz3bSD6R7J3edn4PUOUEkr10fltU2PHKOkZLm-OcBb7s46M_37ovx4vbraHy-2GptGc7_XqHibw1BeyR-XZ3Jx_nWxvCJECvoASrWuGA</recordid><startdate>20041101</startdate><enddate>20041101</enddate><creator>Oldiges, M.</creator><creator>Kunze, M.</creator><creator>Degenring, D.</creator><creator>Sprenger, G. A.</creator><creator>Takors, R.</creator><general>American Chemical Society</general><general>American Institute of Chemical Engineers</general><scope>BSCLL</scope><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20041101</creationdate><title>Stimulation, Monitoring, and Analysis of Pathway Dynamics by Metabolic Profiling in the Aromatic Amino Acid Pathway</title><author>Oldiges, M. ; Kunze, M. ; Degenring, D. ; Sprenger, G. A. ; Takors, R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4976-ffae6fc82a7ee9b8b211746f113fc8416977ec625d30803194452add939889083</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Amino acids</topic><topic>Amino Acids, Aromatic - biosynthesis</topic><topic>Aromatic compounds</topic><topic>Biological and medical sciences</topic><topic>Biotechnology</topic><topic>Chromatography, Liquid - methods</topic><topic>Computer Simulation</topic><topic>Escherichia coli - metabolism</topic><topic>Escherichia coli Proteins - metabolism</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>Gene Expression Profiling - methods</topic><topic>Gene Expression Regulation, Bacterial - physiology</topic><topic>Glucose - metabolism</topic><topic>Kinetics</topic><topic>Mass Spectrometry - methods</topic><topic>Mass spectroscopy</topic><topic>Mathematical models</topic><topic>Metabolism</topic><topic>Models, Biological</topic><topic>Multienzyme Complexes - metabolism</topic><topic>Phenylalanine - biosynthesis</topic><topic>Q1</topic><topic>Signal Transduction - physiology</topic><topic>Statistical analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Oldiges, M.</creatorcontrib><creatorcontrib>Kunze, M.</creatorcontrib><creatorcontrib>Degenring, D.</creatorcontrib><creatorcontrib>Sprenger, G. A.</creatorcontrib><creatorcontrib>Takors, R.</creatorcontrib><collection>Istex</collection><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Biotechnology progress</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Oldiges, M.</au><au>Kunze, M.</au><au>Degenring, D.</au><au>Sprenger, G. A.</au><au>Takors, R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Stimulation, Monitoring, and Analysis of Pathway Dynamics by Metabolic Profiling in the Aromatic Amino Acid Pathway</atitle><jtitle>Biotechnology progress</jtitle><addtitle>Biotechnol Progress</addtitle><date>2004-11-01</date><risdate>2004</risdate><volume>20</volume><issue>6</issue><spage>1623</spage><epage>1633</epage><pages>1623-1633</pages><issn>8756-7938</issn><eissn>1520-6033</eissn><coden>BIPRET</coden><abstract>Using a concerted approach of biochemical standard preparation, analytical access via LC‐MS/MS, glucose pulse, metabolic profiling, and statistical data analysis, the metabolism dynamics in the aromatic amino acid pathway has been stimulated, monitored, and analyzed in different tyrosine‐auxotrophic l‐phenylalanine‐producing Escherichia coli strains. During the observation window from –4 s (before) up to 27 s after the glucose pulse, the dynamics of the first five enzymatic reactions in the aromatic amino acid pathway was observed by measuring intracellular concentrations of 3‐deoxy‐d‐arabino‐heptulosonate 7‐phosphate DAH(P), 3‐dehydroquinate (3‐DHQ), 3‐dehydroshikimate (3‐DHS), shikimate 3‐phosphate (S3P), and shikimate (SHI), together with the pathway precursors phosphoenolpyruvate (PEP) and P5P, the lumped pentose phosphate pool as an alternative to the nondetectable erythrose 4‐phosphate (E4P). Provided that a sufficient fortification of the carbon flux into the pathway of interest is ensured, respective metabolism dynamics can be observed. On the basis of the intracellular pool measurements, the standardized pool velocities were calculated, and a simple, data‐driven criterion‐called “pool efflux capacity” (PEC)‐is derived. Despite its simplifying system description, the criterion managed to identify the well‐known AroB limitation in the E. coli strain A (genotype Δ( pheA tyrA aroF)/pJF119EH aroFfbr pheAfbr amp) and it also succeeded to identify AroL and AroA (in strain B, genotype Δ( pheA tyrA aroF)/pJF119EH aroFfbr pheAfbr aroB amp) as promising metabolic engineering targets to alleviate respective flux control in subsequent l‐Phe producing strains. Furthermore, using of a simple correlation analysis, the reconstruction of the metabolite sequence of the observed pathway was enabled. The results underline the necessity to extend the focus of glucose pulse experiments by studying not only the central metabolism but also anabolic pathways.</abstract><cop>USA</cop><pub>American Chemical Society</pub><pmid>15575692</pmid><doi>10.1021/bp0498746</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Amino acids Amino Acids, Aromatic - biosynthesis Aromatic compounds Biological and medical sciences Biotechnology Chromatography, Liquid - methods Computer Simulation Escherichia coli - metabolism Escherichia coli Proteins - metabolism Fundamental and applied biological sciences. Psychology Gene Expression Profiling - methods Gene Expression Regulation, Bacterial - physiology Glucose - metabolism Kinetics Mass Spectrometry - methods Mass spectroscopy Mathematical models Metabolism Models, Biological Multienzyme Complexes - metabolism Phenylalanine - biosynthesis Q1 Signal Transduction - physiology Statistical analysis |
title | Stimulation, Monitoring, and Analysis of Pathway Dynamics by Metabolic Profiling in the Aromatic Amino Acid Pathway |
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