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Abstract
In Drosophila, the GAL4/UAS/GAL80 repressible binary expression system is widely used to manipulate or mark tissues of interest. However, complex biological systems often require distinct transgenic manipulations of different cell populations. For this purpose, we recently developed the Q system, a second repressible binary expression system. We describe here the basic steps for performing a variety of Q system experiments in vivo. These include how to generate and use Q system reagents to express effector transgenes in tissues of interest, how to use the Q system in conjunction with the GAL4 system to generate intersectional expression patterns that precisely limit which tissues will be experimentally manipulated and how to use the Q system to perform mosaic analysis. The protocol described here can be adapted to a wide range of experimental designs.
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Affiliation(s)
- Christopher J Potter
- The Solomon H. Snyder Department of Neuroscience, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
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Tang X, Dong W, Griffith J, Nilsen R, Matthes A, Cheng KB, Reeves J, Schuttler HB, Case ME, Arnold J, Logan DA. Systems biology of the qa gene cluster in Neurospora crassa. PLoS One 2011; 6:e20671. [PMID: 21695121 PMCID: PMC3114802 DOI: 10.1371/journal.pone.0020671] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2010] [Accepted: 05/10/2011] [Indexed: 11/18/2022] Open
Abstract
An ensemble of genetic networks that describe how the model fungal system, Neurospora crassa, utilizes quinic acid (QA) as a sole carbon source has been identified previously. A genetic network for QA metabolism involves the genes, qa-1F and qa-1S, that encode a transcriptional activator and repressor, respectively and structural genes, qa-2, qa-3, qa-4, qa-x, and qa-y. By a series of 4 separate and independent, model-guided, microarray experiments a total of 50 genes are identified as QA-responsive and hypothesized to be under QA-1F control and/or the control of a second QA-responsive transcription factor (NCU03643) both in the fungal binuclear Zn(II)2Cys6 cluster family. QA-1F regulation is not sufficient to explain the quantitative variation in expression profiles of the 50 QA-responsive genes. QA-responsive genes include genes with products in 8 mutually connected metabolic pathways with 7 of them one step removed from the tricarboxylic (TCA) Cycle and with 7 of them one step removed from glycolysis: (1) starch and sucrose metabolism; (2) glycolysis/glucanogenesis; (3) TCA Cycle; (4) butanoate metabolism; (5) pyruvate metabolism; (6) aromatic amino acid and QA metabolism; (7) valine, leucine, and isoleucine degradation; and (8) transport of sugars and amino acids. Gene products both in aromatic amino acid and QA metabolism and transport show an immediate response to shift to QA, while genes with products in the remaining 7 metabolic modules generally show a delayed response to shift to QA. The additional QA-responsive cutinase transcription factor-1β (NCU03643) is found to have a delayed response to shift to QA. The series of microarray experiments are used to expand the previously identified genetic network describing the qa gene cluster to include all 50 QA-responsive genes including the second transcription factor (NCU03643). These studies illustrate new methodologies from systems biology to guide model-driven discoveries about a core metabolic network involving carbon and amino acid metabolism in N. crassa.
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Affiliation(s)
- Xiaojia Tang
- Department of Physics and Astronomy, University of Georgia, Athens, Georgia, United States of America
- Statistics Department, University of Georgia, Athens, Georgia, United States of America
| | - Wubei Dong
- Genetics Department, University of Georgia, Athens, Georgia, United States of America
| | - James Griffith
- Genetics Department, University of Georgia, Athens, Georgia, United States of America
- College of Agricultural and Environmental Sciences, University of Georgia, Athens, Georgia, United States of America
| | - Roger Nilsen
- Genetics Department, University of Georgia, Athens, Georgia, United States of America
| | - Allison Matthes
- Genetics Department, University of Georgia, Athens, Georgia, United States of America
| | - Kevin B. Cheng
- Genetics Department, University of Georgia, Athens, Georgia, United States of America
| | - Jaxk Reeves
- Statistics Department, University of Georgia, Athens, Georgia, United States of America
| | - H.-Bernd Schuttler
- Department of Physics and Astronomy, University of Georgia, Athens, Georgia, United States of America
| | - Mary E. Case
- Genetics Department, University of Georgia, Athens, Georgia, United States of America
| | - Jonathan Arnold
- Genetics Department, University of Georgia, Athens, Georgia, United States of America
- * E-mail:
| | - David A. Logan
- Department of Biological Sciences, Clark Atlanta University, Atlanta, Georgia, United States of America
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Geever RF, Huiet L, Baum JA, Tyler BM, Patel VB, Rutledge BJ, Case ME, Giles NH. DNA sequence, organization and regulation of the qa gene cluster of Neurospora crassa. J Mol Biol 1989; 207:15-34. [PMID: 2525625 DOI: 10.1016/0022-2836(89)90438-5] [Citation(s) in RCA: 141] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
In Neurospora, five structural and two regulatory genes mediate the initial events in quinate/shikimate metabolism as a carbon source. These genes are clustered in an 18 x 10(3) base-pair region as a contiguous array. The qa genes are induced by quinic acid and are coordinately controlled at the transcriptional level by the positive and negative regulators, qa-1F and qa-1S, respectively. The DNA sequence of the entire qa gene cluster has been determined and transcripts for each gene have been mapped. The qa genes are transcribed in divergent pairs and two types of transcripts are associated with each gene: basal level transcripts that initiate mainly from upstream regions and are independent of qa regulatory gene control, and inducible transcripts that initiate downstream from basal transcripts and are dependent on qa-1F binding to a 16 base-pair sequence. We discuss how both types of transcription relate to the organization of the qa genes as a cluster and how this may impose constraints on gene dispersal.
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Affiliation(s)
- R F Geever
- Department of Genetics, University of Georgia, Athens 30602
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Lockington R, Scazzocchio C, Sequeval D, Mathieu M, Felenbok B. Regulation of alcR, the positive regulatory gene of the ethanol utilization regulon of Aspergillus nidulans. Mol Microbiol 1987; 1:275-81. [PMID: 2834622 DOI: 10.1111/j.1365-2958.1987.tb01933.x] [Citation(s) in RCA: 67] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
The alcR positive control gene is necessary for the expression of both alcA (coding for alcohol dehydrogenase ADH I), and aldA (coding for aldehyde dehydrogenase, AldDH) in Aspergillus nidulans. Using a cloned alcR probe and Northern blots analysis we show that: (1) alcR itself is inducible; (2) alcR inducibility depends on the expression of the alcR gene itself; and (3) alcR is subject to carbon catabolite repression and its expression is controlled by the negatively acting creA wide specificity gene. The repression of alcR is sufficient to explain the carbon catabolite repression of ADH I and AldDH.
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Affiliation(s)
- R Lockington
- Institut de Microbiologie, Université Paris-Sud, Orsay, France
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Abstract
Recombinant DNA technology enables the creation of well-defined alterations in the genetic material of an organism. Methods to manipulate recombinant DNA in the filamentous fungi (a group of microorganisms that includes species of academic as well as commercial interest) have recently been developed. This has been the result of adaptation of procedures successfully employed in the manipulation of other microorganisms. There are a number of similarities in the behavior of recombinant DNA in different fungi, but a number of differences have also been observed between the filamentous and the nonfilamentous fungi. Such differences include the ability to identify DNA replication origins and the host range of expression of fungal genes.
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