Analysis of Copper Homeostasis Pathways in Cryptococcus ...

Report 4 Downloads 59 Views
Analysis of Copper Homeostasis Pathways in Cryptococcus neoformans via Microarray and Bioinformatic Characterization of a cuf1- Strain

Jeramia J. Ory King’s College Department of Biology 133 North River Street Wilkes-Barre, PA 18711 [email protected]

Shannon E. Ellis, Nicholas A. Attanasio, Salvador A. Sapienza, Alexander J. Kish and Jeramia J. Ory* King’s College, Wilkes-Barre, PA 18711; and The Commonwealth Medical College, Scranton, PA 18503 Copper homeostasis in C. neoformans •  Copper is a known cofactor for CNLAC1, the laccase that produces melanin in C. neoformans. (1) •  CUF1(MAC1) is a Quantitative Trait Gene for monokaryotic fruiting, melanin production, and growth at 39°. (2) •  Cuf1p appears to be the major regulator of copper levels in the cell, enhancing transcription of the copper transporter CTR4 in response to copper starvation. •  Interruption of CUF1 results in avirulent cells that are unable to respond to many environmental stressors, including high copper tolerance. (3)

Questions •  What is the consensus sequence for Copper Sensing Elements in C. neoformans? •  Are any other sequences conserved upstream of copper transporters? •  Using whole genome transcription analysis of a cuf1- strain, can we identify upstream sequences common to either a low copper or high copper response?

Complete repression of CTR4 expression requires all potential CuSE sites Reporter  ac*vity   +  Cu  

-­‐  Cu  

Fold   induc*on  

pCTR4  

-­‐  

++  

~300  

pCTR4-­‐2  

+  

+++  

~135  

pCTR4-­‐1  

-­‐  

+  

~20  

pCTR4-­‐0  

-­‐  

-­‐  

0  

Reporter gene (gusA) activity from constructs designed to test copper response of regions upstream of the CTR4 gene. Green arrows are potential CuSE sequences, blue arrows are potential iron regulation sequences. The entire upstream sequence is required to generate expression enhancement on the same scale seen in the RT-PCR experiments (pCTR4 construct). Greater raw expression than native is possible by generating a construct which repeats bases -150 to -350 (pCTR4-2 construct), although complete repression is not possible using copper alone. The presence of potential iron regulation motifs suggests that complete repression of pCTR4-2 may be possible using a combination of copper and iron. Fold induction and relative expression are taken from (4). +Cu = 25 µM CuSO4 + 1mM ascorbic acid. -Cu = 100 µM bathocuproeine disulphonate

Motif analysis reveals few copper sensitive genes contain upstream CuSE-like elements

Expression profile of the cuf1- strain grown in low copper indicates metabolic stress

C. neoformans var grubii C. neoformans var neoformans

GOMO Orthology predictions

2.8e-029

unknown

2.5e-003

vacuolar protein catabolic process response to abiotic stimulus oxidation reduction

6.3e-002

chromatin modification

3.5e+004

RNA polymerase II transcription factor activity

Wild type (JEC21) and cuf1- strains of C. neoformans were grown overnight at 30° in YPD with 0µM, 10µM or 100 µM CuSO4 added. Cells were harvested, RNA extracted, and whole genome microarray hybridizations conducted. All conditions were competitively hybridized against JEC21 grown in YPD (0µM added copper). Cluster analysis using kmeans and Self Organizing Maps (9) was performed in order to find groups of genes regulated similarly to the copper transporter CTR4. 1000 base pairs upstream and 200 base pairs downstream of genes regulated similarly to CTR4 were downloaded from Regulatory Sequence Analysis Tools (10; 11) and submitted to the MEME (Multiple EM for Motif Elicitation) server (12) to find upstream sequences that were significantly represented in the data set. Conserved motifs were then submitted to the GOMO (Gene Ontology for Motifs) server (13; 14) to elucidate ontological predictions based on S. cerevisiae upstream sequences. Top:

CTR4 upstream topology varies by serotype

MEME e-value

Cuf1p may activate ubiquitin dependent degradation in response to toxic copper levels

Cluster analysis using k-means and Self Organizing Maps was performed as before in order to find groups of genes with enhanced expression in higher copper levels in JEC21 cells, but not in cuf1- cells. The genes discovered suggest that C. neoformans may degrade Ctr4p via ubiquitin mediated pathways in a manner similar to Ctr1p degradation in S. cerevisiae. (15; 16) Top:

Consensus sequences found by MEME, their color in the Bottom figure, the significance of the hit and the top Biological Process (BP) or Molecular Function (MF) ontology predictions

Genes displaying the regulation pattern of higher expression in wild type and little to no expression in the cuf1- strain. Sites are colored as before. Genes involved in protein degradation are highlighted in green.

Bottom: Sequences found by MEME, their color in the Top figure, the significance of the hit and the top Biological Process (BP) or Molecular Function (MF) ontology predictions

Bottom: Genes regulated in a similar pattern to CTR4 across all conditions tested and their corresponding upstream regions. Hits to the motifs discovered by MEME are colored according to the scheme above, and the height of the bar is proportional to the p-value of the hit. Hits to the potential iron regulatory sequence (5’AAkGGCkCaT-3’) are colored in light cyan. C0, C10 & C100 = cuf1- strain grown in 0 µM, 10 µM and 100 µM added copper. J10 & J100 = JEC21 grown in 10 µM & 100 µM added copper. Due to competitive hybridization techniques, all samples were compared to JEC21 grown in 0 µM added copper, so there is no J0 condition.

Graphical representation of the upstream regions of the CTR4 gene. Green triangles are potential Copper Sensing Elements (CuSE), containing the sequence 5’-GCTG-3’. Blue triangles are sequences overrepresented upstream of all copper transporters in C. neoformans, similar to sequences found upstream of S. cerevisiae FRA1 (5’AAkGGCkCaT-3’)

MEME e-value

GOMO Orthology predictions

2.8e-029

vacuolar protein catabolic process transcription regulator activity

2.5e-003

vacuolar protein catabolic process oxidoreductase activity

Conclusions CTR4 expression magnitude varies by serotype 1.00

p = 0.08

p = 0.002

-1.00 -2.00 -3.00 -4.00 -5.00 -6.00

log(2) expression, relative to YPD

0.00

Microarray expression profile of the cuf1- strain grown in low copper (YPD) indicates numerous genes are differentially expressed in comparison to wild type. Using a cut off of two-fold change in expression compared to wild type and a qvalue < 0.05 reported by Significance Analysis of Microarrays (5), 243 genes demonstrate increased expression in the mutant, while 259 show decreased expression. A list of significantly expressed genes was loaded into KegArray, and KEGG Pathway as well as KEGG BRITE (6-8) was searched to characterize the metabolic response of the cuf1- strain to low copper. The expression profiles indicate the mutant has shifted to mobilize glucose stores, and may be unable to efficiently undergo oxidative phosphorylation. Top:

Expression ratios of all genes, comparing cuf1- expression to wild type (JEC21) expression in YPD with no added copper

Bottom: Individual genes differentially expressed between mutant and wild type, organized by molecular function. Green = expression is lower in cuf1- mutant. Red = Expression is higher in cuf1- mutant.

Pathway TCA  Cycle  

CNA00510/Citrate  Synthase  

CND02620/Aconitase  

CNB01730/Oxoglutarate   Dehydrogenase  

CNA07260/Succinate-­‐CoA  Ligase  

Sugar   metabolism  

CNE02630/glucan  1,4-­‐alpha-­‐ glucosidase  

CNJ00590/Glycogen  Synthase  

CNB00720/Glycogen   Synthase  Kinase  

Structural   polysaccharide  

CNE03150/cellulase  

 CNA05300/chiPn  synthase  6  

CNC00050/chiPn  synthase  

CNE03240/chiPn  synthase  

CNB03210/alpha-­‐1,2-­‐ mannosyltransferase  

-7.00 -8.00

YPD

5 µM Cu

50 µM Cu

CTR4 expression, as determined via RT-PCR. Values are shown as fold change difference from expression levels in YPD after normalization to cyclophillin expression using ΔΔCt analysis. Green bars represent var neoformans expression, Red var grubii. Error bars represent standard deviation of reactions run in triplicate. p-value is calculated using an unpaired t-test.

Gene/Enzyme CNB04090/Isocitrate   Dehydrogenase  

•  Many genes in the cuf1- strain are differentially regulated in low copper compared to wild type, but most appear to be part of a secondary response to copper starvation. •  A CuSE-like sequence is found upstream of genes regulated similarly to CTR4 (5’-YTGCTKCT-3’), but it is not the primary regulator. •  The most common motif found upstream of copper sensitive genes is a purine rich sequence of no homology to known transcription factor binding sites. •  The cuf1- strain is unable to activate a small set of genes in response to higher copper levels, the function of which suggests the copper toxicity response in C. neoformans involves targeted endocytic degradation of Ctr4p, similar to the response in S. cerevisiae. References 1.  2.  3.  4.  5.  6.  7.  8.  9.  10.  11.  12.  13.  14.  15.  16. 

Salas SD, Bennett JE, Kwon-Chung KJ, Perfect JR, Williamson PR. Effect of the laccase gene CNLAC1, on virulence of Cryptococcus neoformans. J Exp Med 1996 Aug.;184(2):377-386. Lin X, Huang JC, Mitchell TG, Heitman J. Virulence attributes and hyphal growth of C. neoformans are quantitative traits and the MATalpha allele enhances filamentation. PLoS Genet 2006 Nov.;2(11):e187. Waterman SR, Hacham M, Hu G, Zhu X, Park Y, Shin S, Panepinto J, Valyi-Nagy T, Beam C, Husain S, Singh N, Williamson PR. Role of a CUF1/CTR4 copper regulatory axis in the virulence of Cryptococcus neoformans. J Clin Invest 2007 Mar.;117(3):794-802. Ory JJ, Griffith CL, Doering TL. An efficiently regulated promoter system for Cryptococcus neoformans utilizing the CTR4 promoter. Yeast 2004 Aug.;21(11):919-926. Tusher VG, Tibshirani R, Chu G. Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci USA 2001 Apr.;98(9):5116-5121. Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res 2000 Jan.;28(1):27-30. Kanehisa M, Goto S, Hattori M, Aoki-Kinoshita KF, Itoh M, Kawashima S, Katayama T, Araki M, Hirakawa M. From genomics to chemical genomics: new developments in KEGG. Nucleic Acids Res 2006 Jan.; 34(Database issue):D354-7. Kanehisa M, Goto S, Furumichi M, Tanabe M, Hirakawa M. KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Res 2010 Jan.;38(Database issue):D355-60. de Hoon MJL, Imoto S, Nolan J, Miyano S. Open source clustering software. Bioinformatics 2004 Jun.;20(9):1453-1454. van Helden J. Regulatory sequence analysis tools. Nucleic Acids Res 2003 Jul.;31(13):3593-3596. Thomas-Chollier M, Sand O, Turatsinze JV, Janky R, Defrance M, Vervisch E, Brohee S, van Helden J. RSAT: regulatory sequence analysis tools. Nucleic Acids Res 2008 May;36(Web Server):W119-W127. Bailey TL, Elkan C. Fitting a mixture model by expectation maximization to discover motifs in biopolymers. In: Second International Conference on Intelligent Systems for Molecular Biology. Stanford, CA: [no date] p. 28-36. Buske FA, Boden M, Bauer DC, Bailey TL. Assigning roles to DNA regulatory motifs using comparative genomics. Bioinformatics 2010 Mar.;26(7):860-866. Boden M, Bailey TL. Associating transcription factor-binding site motifs with target GO terms and target genes. Nucleic Acids Res 2008 May;36(12):4108-4117. Wu X, Sinani D, Kim H, Lee J. Copper Transport Activity of Yeast Ctr1 Is Down-regulated via Its C Terminus in Response to Excess Copper. Journal of Biological Chemistry 2008 Dec.;284(7):4112-4122. Liu J, Sitaram A, Burd CG. Regulation of copper-dependent endocytosis and vacuolar degradation of the yeast copper transporter, Ctr1p, by the Rsp5 ubiquitin ligase. Traffic 2007 Oct.;8(10):1375-1384.

Recommend Documents