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Article: The RegA regulon exhibits variability in response to altered growth conditions and differs markedly between

Schindel, Heidi S / Bauer, Carl E

2016 Volume 2, Issue 10, Page(s) e000081

Abstract: The RegB/RegA two-component system ... ...

Abstract	The RegB/RegA two-component system from
MeSH term(s)	Bacterial Proteins/genetics ; Gene Expression Regulation, Bacterial/genetics ; Regulon/genetics ; Rhodobacter/genetics ; Rhodobacter capsulatus ; Rhodobacter sphaeroides ; Species Specificity
Chemical Substances	Bacterial Proteins
Language	English
Publishing date	2016-10-21
Publishing country	England
Document type	Journal Article
ZDB-ID	2835258-0
ISSN	2057-5858
ISSN	2057-5858
DOI	10.1099/mgen.0.000081
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Article ; Online: The plastid genome as a chassis for synthetic biology-enabled metabolic engineering: players in gene expression.

Schindel, Heidi S / Piatek, Agnieszka A / Stewart, C Neal / Lenaghan, Scott C

Plant cell reports

2018 Volume 37, Issue 10, Page(s) 1419–1429

Abstract: Owing to its small size, prokaryotic-like molecular genetics, and potential for very high transgene expression, the plastid genome (plastome) is an attractive plant synthetic biology chassis for metabolic engineering. The plastome exists as a homogenous, ...

Abstract	Owing to its small size, prokaryotic-like molecular genetics, and potential for very high transgene expression, the plastid genome (plastome) is an attractive plant synthetic biology chassis for metabolic engineering. The plastome exists as a homogenous, compact, multicopy genome within multiple-specialized differentiated plastid compartments. Because of this multiplicity, transgenes can be highly expressed. For coordinated gene expression, it is the prokaryotic molecular genetics that is an especially attractive feature. Multiple genes in a metabolic pathway can be expressed in a series of operons, which are regulated at the transcriptional and translational levels with cross talk from the plant's nuclear genome. Key features of each regulatory level are reviewed, as well as some examples of plastome-enabled metabolic engineering. We also speculate about the transformative future of plastid-based synthetic biology to enable metabolic engineering in plants as well as the problems that must be solved before routine plastome-enabled synthetic circuits can be installed.
MeSH term(s)	3' Untranslated Regions ; 5' Untranslated Regions ; Gene Expression Regulation ; Genome, Plant ; Genome, Plastid ; Metabolic Engineering/methods ; Promoter Regions, Genetic ; Synthetic Biology/methods ; Transgenes
Chemical Substances	3' Untranslated Regions ; 5' Untranslated Regions
Language	English
Publishing date	2018-07-23
Publishing country	Germany
Document type	Journal Article ; Review
ZDB-ID	8397-5
ISSN	1432-203X ; 0721-085X ; 0721-7714
ISSN (online)	1432-203X
ISSN	0721-085X ; 0721-7714
DOI	10.1007/s00299-018-2323-4
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Article ; Online: Characterization of a Glycyl Radical Enzyme Bacterial Microcompartment Pathway in

Schindel, Heidi S / Karty, Jonathan A / McKinlay, James B / Bauer, Carl E

Journal of bacteriology

2019 Volume 201, Issue 5

Abstract: Bacterial microcompartments (BMCs) are large (∼100-nm) protein shells that encapsulate enzymes, their substrates, and cofactors for the purposes of increasing metabolic reaction efficiency and protecting cells from toxic intermediates. The best-studied ... ...

Abstract	Bacterial microcompartments (BMCs) are large (∼100-nm) protein shells that encapsulate enzymes, their substrates, and cofactors for the purposes of increasing metabolic reaction efficiency and protecting cells from toxic intermediates. The best-studied microcompartment is the carbon-fixing carboxysome that encapsulates ribulose-1,5-bisphosphate carboxylase and carbonic anhydrase. Other well-known BMCs include the Pdu and Eut BMCs, which metabolize 1,2-propanediol and ethanolamine, respectively, with vitamin B
MeSH term(s)	1-Propanol/metabolism ; Aldehydes/metabolism ; Anaerobiosis ; Bacterial Proteins/genetics ; Bacterial Proteins/metabolism ; Biotransformation ; Chromatography, High Pressure Liquid ; Computational Biology ; Darkness ; Mass Spectrometry ; Metabolic Networks and Pathways/genetics ; Multigene Family ; Propionates/metabolism ; Propylene Glycol/metabolism ; Rhodobacter capsulatus/enzymology ; Rhodobacter capsulatus/genetics ; Rhodobacter capsulatus/metabolism
Chemical Substances	Aldehydes ; Bacterial Proteins ; Propionates ; Propylene Glycol (6DC9Q167V3) ; 1-Propanol (96F264O9SV) ; propionaldehyde (AMJ2B4M67V)
Language	English
Publishing date	2019-02-11
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	2968-3
ISSN	1098-5530 ; 0021-9193
ISSN (online)	1098-5530
ISSN	0021-9193
DOI	10.1128/JB.00343-18
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Article: The plastid genome as a chassis for synthetic biology-enabled metabolic engineering: players in gene expression

Schindel, Heidi S / Agnieszka A. Piatek / C. Neal Stewart Jr / Scott C. Lenaghan

Plant cell reports. 2018 Oct., v. 37, no. 10

2018

Abstract	Owing to its small size, prokaryotic-like molecular genetics, and potential for very high transgene expression, the plastid genome (plastome) is an attractive plant synthetic biology chassis for metabolic engineering. The plastome exists as a homogenous, compact, multicopy genome within multiple-specialized differentiated plastid compartments. Because of this multiplicity, transgenes can be highly expressed. For coordinated gene expression, it is the prokaryotic molecular genetics that is an especially attractive feature. Multiple genes in a metabolic pathway can be expressed in a series of operons, which are regulated at the transcriptional and translational levels with cross talk from the plant’s nuclear genome. Key features of each regulatory level are reviewed, as well as some examples of plastome-enabled metabolic engineering. We also speculate about the transformative future of plastid-based synthetic biology to enable metabolic engineering in plants as well as the problems that must be solved before routine plastome-enabled synthetic circuits can be installed.
Keywords	biochemical pathways ; gene expression ; metabolic engineering ; nuclear genome ; operon ; plastid genome ; synthetic biology ; transcription (genetics) ; transgenes
Language	English
Dates of publication	2018-10
Size	p. 1419-1429.
Publishing place	Springer Berlin Heidelberg
Document type	Article
Note	Review
ZDB-ID	8397-5
ISSN	1432-203X ; 0721-085X ; 0721-7714
ISSN (online)	1432-203X
ISSN	0721-085X ; 0721-7714
DOI	10.1007/s00299-018-2323-4
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Article ; Online: Machine-learning from Pseudomonas putida KT2440 transcriptomes reveals its transcriptional regulatory network.

Lim, Hyun Gyu / Rychel, Kevin / Sastry, Anand V / Bentley, Gayle J / Mueller, Joshua / Schindel, Heidi S / Larsen, Peter E / Laible, Philip D / Guss, Adam M / Niu, Wei / Johnson, Christopher W / Beckham, Gregg T / Feist, Adam M / Palsson, Bernhard O

Metabolic engineering

2022 Volume 72, Page(s) 297–310

Abstract: Bacterial gene expression is orchestrated by numerous transcription factors (TFs). Elucidating how gene expression is regulated is fundamental to understanding bacterial physiology and engineering it for practical use. In this study, a machine-learning ... ...

Abstract	Bacterial gene expression is orchestrated by numerous transcription factors (TFs). Elucidating how gene expression is regulated is fundamental to understanding bacterial physiology and engineering it for practical use. In this study, a machine-learning approach was applied to uncover the genome-scale transcriptional regulatory network (TRN) in Pseudomonas putida KT2440, an important organism for bioproduction. We performed independent component analysis of a compendium of 321 high-quality gene expression profiles, which were previously published or newly generated in this study. We identified 84 groups of independently modulated genes (iModulons) that explain 75.7% of the total variance in the compendium. With these iModulons, we (i) expand our understanding of the regulatory functions of 39 iModulon associated TFs (e.g., HexR, Zur) by systematic comparison with 1993 previously reported TF-gene interactions; (ii) outline transcriptional changes after the transition from the exponential growth to stationary phases; (iii) capture group of genes required for utilizing diverse carbon sources and increased stationary response with slower growth rates; (iv) unveil multiple evolutionary strategies of transcriptome reallocation to achieve fast growth rates; and (v) define an osmotic stimulon, which includes the Type VI secretion system, as coordination of multiple iModulon activity changes. Taken together, this study provides the first quantitative genome-scale TRN for P. putida KT2440 and a basis for a comprehensive understanding of its complex transcriptome changes in a variety of physiological states.
MeSH term(s)	Gene Expression Regulation, Bacterial ; Gene Regulatory Networks ; Machine Learning ; Pseudomonas putida/genetics ; Pseudomonas putida/metabolism ; Transcription Factors/genetics ; Transcription Factors/metabolism ; Transcriptome
Chemical Substances	Transcription Factors
Language	English
Publishing date	2022-04-27
Publishing country	Belgium
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S. ; Research Support, Non-U.S. Gov't
ZDB-ID	1470383-x
ISSN	1096-7184 ; 1096-7176
ISSN (online)	1096-7184
ISSN	1096-7176
DOI	10.1016/j.ymben.2022.04.004
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Article: Machine-learning from Pseudomonas putida KT2440 transcriptomes reveals its transcriptional regulatory network

Lim, Hyun Gyu / Rychel, Kevin / Sastry, Anand V. / Bentley, Gayle J. / Mueller, Joshua / Schindel, Heidi S. / Larsen, Peter E. / Laible, Philip D. / Guss, Adam M. / Niu, Wei / Johnson, Christopher W. / Beckham, Gregg T. / Feist, Adam M. / Palsson, Bernhard O.

Metabolic engineering. 2022 July, v. 72

2022

Abstract	Bacterial gene expression is orchestrated by numerous transcription factors (TFs). Elucidating how gene expression is regulated is fundamental to understanding bacterial physiology and engineering it for practical use. In this study, a machine-learning approach was applied to uncover the genome-scale transcriptional regulatory network (TRN) in Pseudomonas putida KT2440, an important organism for bioproduction. We performed independent component analysis of a compendium of 321 high-quality gene expression profiles, which were previously published or newly generated in this study. We identified 84 groups of independently modulated genes (iModulons) that explain 75.7% of the total variance in the compendium. With these iModulons, we (i) expand our understanding of the regulatory functions of 39 iModulon associated TFs (e.g., HexR, Zur) by systematic comparison with 1993 previously reported TF-gene interactions; (ii) outline transcriptional changes after the transition from the exponential growth to stationary phases; (iii) capture group of genes required for utilizing diverse carbon sources and increased stationary response with slower growth rates; (iv) unveil multiple evolutionary strategies of transcriptome reallocation to achieve fast growth rates; and (v) define an osmotic stimulon, which includes the Type VI secretion system, as coordination of multiple iModulon activity changes. Taken together, this study provides the first quantitative genome-scale TRN for P. putida KT2440 and a basis for a comprehensive understanding of its complex transcriptome changes in a variety of physiological states.
Keywords	Pseudomonas putida ; artificial intelligence ; carbon ; gene expression ; independent component analysis ; microbial physiology ; transcription (genetics) ; transcriptome ; type VI secretion system ; variance
Language	English
Dates of publication	2022-07
Size	p. 297-310.
Publishing place	Elsevier Inc.
Document type	Article
ZDB-ID	1470383-x
ISSN	1096-7184 ; 1096-7176
ISSN (online)	1096-7184
ISSN	1096-7176
DOI	10.1016/j.ymben.2022.04.004
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Article ; Online: Corrigendum to "Engineering glucose metabolism for enhanced muconic acid production in Pseudomonas putida KT2440" [Metab. Eng. 59 (2020) 64-75].

Bentley, Gayle J / Narayanan, Niju / Jha, Ramesh K / Salvachúa, Davinia / Elmore, Joshua R / Peabody, George L / Black, Brenna A / Ramirez, Kelsey / De Capite, Annette / Michener, William E / Werner, Allison Z / Klingeman, Dawn M / Schindel, Heidi S / Nelson, Robert / Foust, Lindsey / Guss, Adam M / Dale, Taraka / Johnson, Christopher W / Beckham, Gregg T

Metabolic engineering

2022 Volume 72, Page(s) 66–67

Language	English
Publishing date	2022-03-01
Publishing country	Belgium
Document type	Journal Article ; Published Erratum
ZDB-ID	1470383-x
ISSN	1096-7184 ; 1096-7176
ISSN (online)	1096-7184
ISSN	1096-7176
DOI	10.1016/j.ymben.2022.02.006
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Article: Engineering glucose metabolism for enhanced muconic acid production in Pseudomonas putida KT2440

International Metabolic Engineering Society Metabolic engineering. 2020 May, v. 59

2020

Abstract: Pseudomonas putida KT2440 has received increasing attention as an important biocatalyst for the conversion of diverse carbon sources to multiple products, including the olefinic diacid, cis,cis-muconic acid (muconate). P. putida has been previously ... ...

Abstract	Pseudomonas putida KT2440 has received increasing attention as an important biocatalyst for the conversion of diverse carbon sources to multiple products, including the olefinic diacid, cis,cis-muconic acid (muconate). P. putida has been previously engineered to produce muconate from glucose; however, periplasmic oxidation of glucose causes substantial 2-ketogluconate accumulation, reducing product yield and selectivity. Deletion of the glucose dehydrogenase gene (gcd) prevents 2-ketogluconate accumulation, but dramatically slows growth and muconate production. In this work, we employed adaptive laboratory evolution to improve muconate production in strains incapable of producing 2-ketogluconate. Growth-based selection improved growth, but reduced muconate titer. A new muconate-responsive biosensor was therefore developed to enable muconate-based screening using fluorescence activated cell sorting. Sorted clones demonstrated both improved growth and muconate production. Mutations identified by whole genome resequencing of these isolates indicated that glucose metabolism may be dysregulated in strains lacking gcd. Using this information, we used targeted engineering to recapitulate improvements achieved by evolution. Deletion of the transcriptional repressor gene hexR improved strain growth and increased the muconate production rate, and the impact of this deletion was investigated using transcriptomics. The genes gntZ and gacS were also disrupted in several evolved clones, and deletion of these genes further improved strain growth and muconate production. Together, these targets provide a suite of modifications that improve glucose conversion to muconate by P. putida in the context of gcd deletion. Prior to this work, our engineered strain lacking gcd generated 7.0 g/L muconate at a productivity of 0.07 g/L/h and a 38% yield (mol/mol) in a fed-batch bioreactor. Here, the resulting strain with the deletion of hexR, gntZ, and gacS achieved 22.0 g/L at 0.21 g/L/h and a 35.6% yield (mol/mol) from glucose in similar conditions. These strategies enabled enhanced muconic acid production and may also improve production of other target molecules from glucose in P. putida.
Keywords	Pseudomonas putida ; biocatalysts ; bioreactors ; biosensors ; carbon ; clones ; enzymes ; flow cytometry ; genes ; glucose ; metabolic engineering ; metabolism ; mutation ; oxidation ; repressor proteins ; screening ; sequence analysis ; transcriptomics
Language	English
Dates of publication	2020-05
Size	p. 64-75.
Publishing place	Elsevier Inc.
Document type	Article
ZDB-ID	1470383-x
ISSN	1096-7184 ; 1096-7176
ISSN (online)	1096-7184
ISSN	1096-7176
DOI	10.1016/j.ymben.2020.01.001
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Article ; Online: Engineering glucose metabolism for enhanced muconic acid production in Pseudomonas putida KT2440.

Metabolic engineering

2020 Volume 59, Page(s) 64–75

Abstract	Pseudomonas putida KT2440 has received increasing attention as an important biocatalyst for the conversion of diverse carbon sources to multiple products, including the olefinic diacid, cis,cis-muconic acid (muconate). P. putida has been previously engineered to produce muconate from glucose; however, periplasmic oxidation of glucose causes substantial 2-ketogluconate accumulation, reducing product yield and selectivity. Deletion of the glucose dehydrogenase gene (gcd) prevents 2-ketogluconate accumulation, but dramatically slows growth and muconate production. In this work, we employed adaptive laboratory evolution to improve muconate production in strains incapable of producing 2-ketogluconate. Growth-based selection improved growth, but reduced muconate titer. A new muconate-responsive biosensor was therefore developed to enable muconate-based screening using fluorescence activated cell sorting. Sorted clones demonstrated both improved growth and muconate production. Mutations identified by whole genome resequencing of these isolates indicated that glucose metabolism may be dysregulated in strains lacking gcd. Using this information, we used targeted engineering to recapitulate improvements achieved by evolution. Deletion of the transcriptional repressor gene hexR improved strain growth and increased the muconate production rate, and the impact of this deletion was investigated using transcriptomics. The genes gntZ and gacS were also disrupted in several evolved clones, and deletion of these genes further improved strain growth and muconate production. Together, these targets provide a suite of modifications that improve glucose conversion to muconate by P. putida in the context of gcd deletion. Prior to this work, our engineered strain lacking gcd generated 7.0 g/L muconate at a productivity of 0.07 g/L/h and a 38% yield (mol/mol) in a fed-batch bioreactor. Here, the resulting strain with the deletion of hexR, gntZ, and gacS achieved 22.0 g/L at 0.21 g/L/h and a 35.6% yield (mol/mol) from glucose in similar conditions. These strategies enabled enhanced muconic acid production and may also improve production of other target molecules from glucose in P. putida.
MeSH term(s)	Glucose/metabolism ; Metabolic Engineering ; Pseudomonas putida/genetics ; Pseudomonas putida/metabolism ; Sorbic Acid/analogs & derivatives ; Sorbic Acid/metabolism
Chemical Substances	muconic acid (3KD92ZL2KH) ; Glucose (IY9XDZ35W2) ; Sorbic Acid (X045WJ989B)
Language	English
Publishing date	2020-01-10
Publishing country	Belgium
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	1470383-x
ISSN	1096-7184 ; 1096-7176
ISSN (online)	1096-7184
ISSN	1096-7176
DOI	10.1016/j.ymben.2020.01.001
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