Iron-regulated proteome and transcriptome of Neisseria meningitidis

1. Iron-regulatedproteome and transcriptomeof Neisseria meningitidis M. BASLER, I. LINHARTOVÁ, P. HALADA,J. NOVOTNÁ, S. BEZOUŠKOVÁ, R. OSIČKA,J. WEISER, J. VOHRADSKÝ and P. ŠEBO Institute of Microbiology of the Czech Academy of Sciences, Prague

2. IRON HOMEOSTASIS Iron is essential to virtually all organisms, but poses problems of toxicity and poor solubility

3. Basic principles of iron homeostasis • There are essentially 5 strategies used by bacteria in the management of iron: • High-affinity iron transport enabling iron to be scavenged, in various forms, from the surroundings. • Deposition of intracellular iron stores to provide a source of iron that can be drawn upon when external supplies are limited. • Employment of redox stress resistance systems (e.g. degradation of iron-induced reactive oxygen species and repair of redox stress-induced damage). • Control of iron consumption by down-regulating the expression of iron-containing proteins under iron-restricted conditions. • An over-arching iron-responsive regulatory system that co-ordinates the expression of the above iron homeostatic machinery according to iron availability.

4. High iron Low iron Mechanism of Fur regulation However, recently also iron-responsive activation of gene transcription was discovered iron-responsive repression of gene transcription ON OFF NADH dehydrogenase subunits NADH dehydrogenase subunits Andrews – FEMS Microbiology Reviews 27 (2003); Delany – Mol Microbiol 52 (2004)

5. Gene expression in N. meningitidisunder iron starvation • In human body more than 99,9% of iron is bound to transport (transferrin, lactoferrin) and storage proteins (ferritin, heme-containing compounds) • For invasion and proliferation bacteria need to induce specific pathways capable of scavenging iron from the host • Low iron concentration tells the pathogen it is inside the host • Several Neisseria virulence genes are iron-regulated

6. Neisseria meningitidis Obligate human commensal gram-negative bacterium colonizing the nasopharynx of about 10% of healthy subjects. Risk factors: upper respiratory infection, immunodeficiency, age Risk groups:military recruits, refugees, contacts of patients Treatment (7 to 14 days):intravenous penicillin or cephalosporins, chloramphenicolVaccine:purified polysaccharidesserogroups A, C, Y and W-135

7. Neisseria meningitidis – life cycleIron availability in the human host lactoferrin 2 µM iron transferrin hemoglobin ferritin

8. Experimental design – iron starvation Proteins2-D + MS RNAmicroarray 7 µM Fe(NO3)310 h O/N Proteins2-D + MS RPMI2 h RNAmicroarray 100µM Desferal10 h

9. Iron regulatedPROTEOME I. LINHARTOVÁ, P. HALADA,J. NOVOTNÁ, S. BEZOUŠKOVÁ, J. VOHRADSKÝ

10. + Fe(NO3)3 + Desferal Image and data analysis Mass Spectrometry

11. theor. 788 proteins theor. 962 proteins 4 pI 7 6 pI 11 100 100 kDa kDa 5 15 DF set – 6 gels Fe set – 7 gels 362 protein spots analyzed 46 spots in DF set 31 spots in Fe set DF set – 8 gels Fe set – 10 gels 238 protein spots analyzed 67 spots in DF set 11 spots in Fe set 114 spots were identified by MS64 unique proteins in DF set27 unique proteins in Fe set

12. Iron regulatedTRANSCRIPTOME M. BASLER, I. LINHARTOVÁ

13. + Fe(NO3)3 + Desferal Chip Target: PCR products Cy3 Cy5 + Probe Data mining and visualization Hybridization Image processing

14. N. meningitidis whole genome slide (Eurogentec) - 2194 ORFs 3 biological experiments 8 whole genome slides 62 genes up-regulated in DF64 genes up-regulated in Fe

15. sebo@biomed.cas.cz basler@biomed.cas.cz

16. DATA ANALYSIS scanning, image analysis, quality control, background subtraction, normalization, data mining

17. Database AGED Database Others… Database MAD Printer Scanner .tiff Image File Image Analysis Microarray Data Flow Raw Gene Expression Data Gene Annotation Normalization / Filtering Normalized Data with Gene Annotation Expression Analysis Interpretation of Analysis Results

18. Scanning

21. Image analysisquality controlbackground subtraction SpotFinder www.tigr.org

22. Basic Steps from Image to Table 1. Image File Loading 2. Construct or Apply an Overlay Grid 3. Computations • Find Spot Boundary and Area • Intensity Calculation • Background Calculation and Correction 4. Quality Control 5. Text File Output

25. Applying an Overlay Grid • What does it accomplish? • The grid cells set a boundary for the spot finding algorithms. • The grid cells also define an area for background correction. Area inside contour is used for spot intensity calculation Area outside contour is used for local background calculation Reported “Intensity” = Integral – BKG * A

26. NormalizationData mining, filtering MIDAS www.tigr.org R www.r-project.org

27. Why is normalization important? • There are many sources of experimental variation: • During preparation – mRNA extraction, labeling • During manufacture of array – amount of spotted DNA • During hybridization – amount of sample applied, amount of target hybridized • After hybridization – optical measurements, label intensity, scanner • Proper normalization is needed before ratios from different chips are compared!

30. Data mining • Visualization and control (R) • Filtering (MS Excel, R) • One sample t-test • mean of Log2 ratios for all replicates • mean is not equal to 0 • p-val < 0.01 • Expression ratio > 1.7x • Clustering • KEGG GENES Database • PubMed

31. Finding Significant Genes by t-test Distribution of intensity ratios for each gene Not significant p-val > 0.01 Average ratio is same Significant p-val < 0.01

32. RESULTS

33. Complementarity of proteome and transcriptome199genes regulated by iron 73 18 108 91 genes found inproteome 126 genes found in transcriptome 114genes up-regulated inlow iron85genes up-regulated inhigh iron

34. Identification of iron-activated and repressed Fur-dependent genes by transcriptome analysis of Neisseria meningitidis group BGrifantini et al., PNAS, August 5, 2003 • After iron addition to an iron-depleted bacterial culture 153 genes were up-regulated and 80 were down-regulated • Only 50% of the iron-regulated genes were found to contain Fur-binding consensus sequences in their promoter regions. • Different growth conditions. N. meningitidis MC58 cultures were grown in chemically defined medium with 12.5 µM desferal (iron-depleted) for 3 h. After this adaptation to iron starvation, half of the culture was supplemented with 100 µM ferric nitrate, and growth continued for a 5-h period.

35. Overlap of PNAS and our data • PNAS data are for N. m. B • NMB to NMA conversion table • blastall -p blastp -d Nm_Z2491-b1 -m8 -i MC58.txt -o NmB_in_NmA.txt

36. 145 5 (2) 24 15 62 1 77 191 genes found by Siena group+ 40 not on EGT chip, + 4 more than once 85 genes found inproteome + 1 not similar to NmA or NmB 117 genes found in transcriptome

38. Conclusions for combined results • There is more iron-regulated genes than expected! Up to about 300. • In a single type of experiment we and the Siena group found 10x more genes regulated by iron concentration than before the entire scientific community in 40 years!

39. Some what came out …

40. IRON HOMEOSTASIS Iron is essential to virtually all organisms, but poses problems of toxicity and poor solubility

41. Basic principles of iron homeostasis • There are essentially 5 strategies used by bacteria in the management of iron: • High-affinity iron transport enabling iron to be scavenged, in various forms, from the surroundings. • Deposition of intracellular iron stores to provide a source of iron that can be drawn upon when external supplies are limited. • Employment of redox stress resistance systems (e.g. degradation of iron-induced reactive oxygen species and repair of redox stress-induced damage). • Control of iron consumption by down-regulating the expression of iron-containing proteins under iron-restricted conditions. • An over-arching iron-responsive regulatory system that co-ordinates the expression of the above iron homeostatic machinery according to iron availability.

42. I.TRANSPORT OF IRON High-affinity iron transport systems allowing acquisition in various forms from the environment are vital to all commensal and pathogenic bacteria

43. Iron sources in the human host lactoferrin 2 µM iron transferrin hemoglobin ferritin

44. Iron acquisition mechanisms • Siderophore mediated • N. meningitidis utilize heterologous siderophores • Receptor mediated • Transferrin and lactoferrin receptors • Hemoglobin receptor • Haptoglobin-hemoglobin receptor • Siderophores and hemophores are taken into the cell whole. • Host carrier proteins are not transported into the cell. Iron and heme must be stripped away prior to transport.

45. Iron acquisition system is up-regulated in low iron 4x - LbpA 5x - LbpB 7x 5x 3x 3x 5x 4x These results validate the experimental procedure!

46. Proteins up-regulated in low iron Other iron acquisition system?

47. Basic periplasmic proteins up in low iron Other periplasmic transporters?

48. II.REGULATORY SYSTEMS An over-arching iron-responsive regulatory system thatco-ordinates the expression of the iron homeostatic machinery according to iron availability is the Fur system

49. High iron Low iron Mechanism of Fur regulation However, recently also iron-responsive activation of gene transcription was discovered iron-responsive repression of gene transcription ON OFF NADH dehydrogenase subunits NADH dehydrogenase subunits Andrews – FEMS Microbiology Reviews 27 (2003); Delany – Mol Microbiol 52 (2004)

50. Transcriptional regulators possibly involved regulation of iron homeostasis Iron can regulate gene expression in a Fur-independent manner for approx. 50 % of the up/down regulated genes. Grifantini – PNAS, 2003; V. Scarlato (2003, J Bact) – Fur is autoregulated in Neisseria meningitidis