Iron-regulated proteome and transcriptome of 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
Feb 01, 2016
Iron-regulatedproteome and transcriptome
of 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
IRON HOMEOSTASIS
Iron is essential to virtually all organisms, but poses problems of toxicity and poor solubility
Basic principles of iron homeostasis• There are essentially 5 strategies used by bacteria in the
management of iron:1)High-affinity iron transport enabling iron to be scavenged, in
various forms, from the surroundings.
2)Deposition of intracellular iron stores to provide a source of iron that can be drawn upon when external supplies are limited.
3)Employment of redox stress resistance systems (e.g. degradation of iron-induced reactive oxygen species and repair of redox stress-induced damage).
4)Control of iron consumption by down-regulating the expression of iron-containing proteins under iron-restricted conditions.
5)An over-arching iron-responsive regulatory system that co-ordinates the expression of the above iron homeostatic machinery according to iron availability.
Mechanism of Fur regulation
Andrews – FEMS Microbiology Reviews 27 (2003); Delany – Mol Microbiol 52 (2004)
High iron Low iron
NADH dehydrogenase subunits
NADH dehydrogenase subunits
ON OFF
iron-responsive repression of gene transcriptionHowever, recently also iron-responsive activation of gene transcription was discovered
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
Neisseria meningitidisObligate 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, chloramphenicol
Vaccine:purified polysaccharidesserogroups A, C, Y and W-135
lactoferrin
ferritintransferrin
hemoglobin
2 µM iron
Neisseria meningitidis – life cycle Iron availability in the human host
Experimental design – iron starvation
7 µM Fe(NO3)3
10 h
RNAmicroarray
Proteins2-D + MS
O/NRPMI2 h
100 µM Desferal10 h
RNAmicroarray
Proteins2-D + MS
Iron regulated
PROTEOMEI. LINHARTOVÁ, P. HALADA,
J. NOVOTNÁ, S. BEZOUŠKOVÁ, J. VOHRADSKÝ
+ Fe(NO3)3 + Desferal Image and data analysis
Mass Spectrometry
theor. 788 proteins theor. 962 proteins
4 7 6 11pI pI100
5
100
15
kDa kDa
DF set – 6 gelsFe set – 7 gels
362 protein spots analyzed46 spots in DF set31 spots in Fe set
DF set – 8 gelsFe set – 10 gels
238 protein spots analyzed67 spots in DF set11 spots in Fe set
114 spots were identified by MS64 unique proteins in DF set27 unique proteins in Fe set
Iron regulated
TRANSCRIPTOMEM. BASLER, I. LINHARTOVÁ
Cy3Cy5
Probe
Target: PCR products
Hybridization
Chip
+
Image processing
Data mining and visualization
+ Fe(NO3)3 + Desferal
N. meningitidis whole genome slide (Eurogentec) - 2194 ORFs
3 biological experiments8 whole genome slides
62 genes up-regulated in DF64 genes up-regulated in Fe
[email protected]@biomed.cas.cz
DATA ANALYSIS
scanning, image analysis, quality control, background subtraction,
normalization, data mining
Microarray Data Flow
Database
AGED
Database
Others…
Database
MAD
Raw Gene Expression Data
Normalized Data with Gene Annotation
Interpretation of Analysis Results
.tiff Image File
Gene Annotation
ScannerPrinter
Image Analysis
Normalization / Filtering
Expression Analysis
Scanning
Image analysisquality control
background subtraction
SpotFinderwww.tigr.org
Basic Steps from Image to Table
1. Image File Loading
2. Construct or Apply an Overlay Grid
3. ComputationsFind Spot Boundary and Area
Intensity Calculation
Background Calculation and Correction
4. Quality Control
5. Text File Output
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
NormalizationData mining, filtering
MIDASwww.tigr.org
Rwww.r-project.org
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!
4.5 5.0 5.5 6.0 6.5
-20
24
68
Intensity vs. expression ratio slide #6
Mean of Log10 intensities for both channels
Exp
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Histogram of expression ratios normalized data - slide #6
5146 spots
De
nsi
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-3 -2 -1 0 1 2 3
0.0
0.2
0.4
0.6
0.8
1.0
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
Distribution of intensity ratios for each gene
Finding Significant Genes by t-test
Average ratio is same
Not significantp-val > 0.01
Significantp-val < 0.01
RESULTS
Complementarity of proteome and transcriptome
199 genes regulated by iron
114 genes up-regulated in low iron85 genes up-regulated in high iron
73 18 108
91 genes found in
proteome126 genes found in
transcriptome
Identification of iron-activated and repressed Fur-dependent genes by transcriptome analysis of
Neisseria meningitidis group B Grifantini 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.
Overlap of PNAS and our data
• PNAS data are for N. m. B
• NMB to NMA conversion tableblastall -p blastp -d Nm_Z2491 -b1 -m8 -i MC58.txt -o NmB_in_NmA.txt
85 genes found in
proteome+ 1 not similar to NmA or NmB
117 genes found in
transcriptome
191 genes found by Siena group+ 40 not on EGT chip, + 4 more than once
62 1 77
245 (2)15
145
Correlation between our data and PNAS data39 genes
R2 = 0.7568
-4
-3
-2
-1
0
1
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3
-4 -3 -2 -1 0 1 2 3 4
Our data (Log2 expression ratio)
PN
AS
da
ta (
Lo
g2
exp
res
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n r
ati
o)
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!
Some what came out …
IRON HOMEOSTASIS
Iron is essential to virtually all organisms, but poses problems of toxicity and poor solubility
Basic principles of iron homeostasis• There are essentially 5 strategies used by bacteria in the
management of iron:1)High-affinity iron transport enabling iron to be scavenged, in
various forms, from the surroundings.
2)Deposition of intracellular iron stores to provide a source of iron that can be drawn upon when external supplies are limited.
3)Employment of redox stress resistance systems (e.g. degradation of iron-induced reactive oxygen species and repair of redox stress-induced damage).
4)Control of iron consumption by down-regulating the expression of iron-containing proteins under iron-restricted conditions.
5)An over-arching iron-responsive regulatory system that co-ordinates the expression of the above iron homeostatic machinery according to iron availability.
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
lactoferrin
ferritintransferrin
hemoglobin
2 µM iron
Iron sources in the human host
Iron acquisition mechanisms• Siderophore mediated
N. meningitidis utilize heterologous siderophores
• Receptor mediatedTransferrin 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.
7x
These results validate the experimental procedure!
5x
3x
5x
4x
3x
5x - LbpB
4x - LbpA
Iron acquisition system is up-regulated in low iron
Proteins up-regulated in low iron
Other iron acquisition system?
Method Reg Protein Name
Arrays 3.13 possible periplasmic protein
Arrays 6.50 putative integral membrane protein
Arrays 2.55 putative integral membrane protein
Arrays 1.91 putative membrane protein
Arrays 3.24 putative lipoprotein
Arrays 5.50 putative periplasmic protein
Arrays 5.24 putative periplasmic protein
Proteome 2.35 putative periplasmic protein
Arrays 1.87putative periplasmic hypothetical protein
Basic periplasmic proteins up in low iron
Protein name Reg MW pI
putative periplasmic protein -5.50 16427.6 11.0
putative periplasmic protein -5.24 31673.7 9.9
hypothetical protein NMA1073 -3.14 19533.4 10.9
major ferric iron binding protein -2.79 35841.9 10.2
Other periplasmic transporters?
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
Mechanism of Fur regulation
Andrews – FEMS Microbiology Reviews 27 (2003); Delany – Mol Microbiol 52 (2004)
High iron Low iron
NADH dehydrogenase subunits
NADH dehydrogenase subunits
ON OFF
iron-responsive repression of gene transcriptionHowever, recently also iron-responsive activation of gene transcription was discovered
Transcriptional regulators possibly involved regulation of iron homeostasis
Method +/- Reg Protein Name
Both DF 2.15 ferric uptake regulation protein
Arrays DF 2.68 putative transcriptional regulator
Arrays DF 2.02 putative transcriptional regulator
Proteome DF only DNA-binding response regulator
Proteome DF only Integration host factor alpha-subunit (IHF-alpha)
Arrays Fe 2.28 AsnC-family transcriptional regulator
Arrays Fe 2.53 putative transcriptional regulator
Arrays Fe 1.93 putative ATP-dependent RNA helicase
Arrays Fe 1.79 ribonuclease PH
Grifantini – PNAS, 2003; V. Scarlato (2003, J Bact) – Fur is autoregulated in Neisseria meningitidis
Iron can regulate gene expression in a Fur-independent manner for approx. 50 % of the up/down regulated genes.
• The generally accepted concept that iron homeostasis in bacteria is regulated by Fur may be an oversimplification.
• Is there a hierarchy of iron-dependent regulation by a cascade of transcriptional activators and/or repressors?
Transcriptional regulators possibly involved regulation of iron homeostasis
Masse – PNAS, 2002
Positive regulation by Fur in E. coliA small non-coding RNA (RyhB) acts as a Fur repressed negative
regulator of genes induced in presence of iron in E. coli.
III.IRON STORAGE
Deposition of intracellular iron in stores offers a source of iron that can be used when external supplies are limited
Proteins involved in iron storage• Free iron in presence of oxygen can form free
radicals which are toxic to the cell.• Storage of iron in nontoxic form is very important!• Two types of iron storage proteins have been
identified in bacteria:bacterioferritin - heme iron and nonheme ironferritin - only iron and not heme
• In presence of ironbfrA - up-regulated more than 11 timesbfrB - up-regulated nearly 8 times
• In presence of desferalputative ferredoxin - up-regulated 2.4 times
Andrews – FEMS Microbiology Reviews 27 (2003)
Bfr500 kDa, 2000-3000 iron atoms/24-mer
Dps250 kDa, 500 iron atoms/12-mer
Structures of iron storage proteins from E. coli
IV.IRON CONSUMPTIONControl of iron consumption by down-regulating the expression of iron-containing proteins under iron-
restricted conditions
CITRATE CYCLE
Fe
DF
The overlap of proteome and transcriptome data shows that
FumC substitutes for FumA during iron starvation
• In presence of iron– Neisseria express iron containing (Fe-S)fumarate hydratase class I (FumA)– up-regulated almost 2 times on level of RNA and FumA protein was found only in Fe set of gels.
• In presence of desferal– Neisseria express “iron free” isoenzymefumarate hydratase class II (FumC)– up-regulated almost 4 times on level of RNA and FumC protein was found only in DF set of gels.
Park – Journal of bacteriology, 1995
PROTEOSYNTHESIS
Proteins up-regulated in iron
Method Reg Protein Name
Arrays 1.73 30S ribosomal protein S18
Arrays 1.83 30S ribosomal protein S6
Arrays 1.80 50S ribosomal protein L27
Arrays 1.90 50S ribosomal protein L31
Arrays 1.82 putative additional 50S ribosomal protein L31
Proteome only 50S ribosomal protein L4
Proteome 2.06 50S ribosomal protein L9
Proteome 2.13 elongation factor G (EF-G)
Proteome only hypothetical protein NMA1094*
Proteome only translation elongation factor Tu
*Protein NMA1094 was annotated by TIGR as ribosomal 5S rRNA E-loop binding protein Ctc/L25/TL5
HYPOTHETICAL PROTEINS
Method Reg Protein Name
Proteome only conserved hypothetical protein
Proteome only hypothetical protein NMA1013
Arrays 7.89 hypothetical protein NMA0957
Arrays 6.00 hypothetical protein NMA0963
Arrays 5.55 hypothetical protein NMA1078
Arrays 3.39 hypothetical protein NMA1076
Arrays 3.14 hypothetical protein NMA1073
Arrays 2.92 hypothetical protein
Arrays 2.30 hypothetical protein
Proteome 2.19 conserved hypothetical protein
Arrays 2.10 hypothetical protein
Arrays 2.02 hypothetical protein NMA0482
Arrays 1.97 hypothetical protein NMA1070
Arrays 1.89 hypothetical protein
Arrays 1.89 hypothetical protein
Arrays 1.89 hypothetical protein NMA0401
Arrays 1.88 hypothetical protein NMA1220
Arrays 1.75 hypothetical protein NMA1067
Arrays 1.75 hypothetical protein NMA1071
Arrays 1.74 hypothetical protein NMA0565
Arrays 1.74 hypothetical protein NMA0737
Arrays 1.74 hypothetical protein NMA1484
Arrays 1.73 hypothetical protein NMA1072
Arrays 1.71 hypothetical protein NMA0787
Hypothetical proteins up in low iron
Hypothetical proteins up in high ironMethod Reg Protein Name
Proteome only conserved hypothetical protein
Proteome only conserved hypothetical protein
Proteome only hypothetical protein NMA1013
Proteome only hypothetical protein NMA1094
Arrays 3.25 hypothetical protein NMA0004
Arrays 3.20 hypothetical protein
Arrays 2.96 hypothetical protein NMA0013
Arrays 2.70 hypothetical protein
Arrays 2.08 hypothetical protein NMA0003
Arrays 1.90 hypothetical periplasmic protein
Arrays 1.87 outer membrane protein
Arrays 1.84 hypothetical protein
Arrays 1.81 hypothetical protein
Arrays 1.78putative periplasmic binding protein
Arrays 1.74 putative periplasmic protein
SUMMARY
Genes up-regulated at low-iron conditions 114 genes
• Transport and binding proteins
transferrin and lactoferrin binding proteins
TonB protein
siderophore receptor
ferric binding protein
ABC transporter
• Virulence factorspilins
opaD
• Transcriptional regulatorsferric uptake regulation protein
integration host factor (IHF)
hypothetical DNA binding proteins
putative regulators
• 15 putative membrane and periplasmic proteins
• 30 hypothetical proteins
Genes up-regulated at high-iron conditions 85 genes
• Iron storagebacterioferritins
• Energy metabolismelectron transport
• cytochromes
• NADH dehydrogenase
TCA cycle• fumarate hydratase
• aconitate hydratase
• citrate synthase
• Protein synthesisribosomal proteins
translation and elongation factors
• Transcriptional regulatorsAsnC-family transcriptional regulatorDNA binding proteinsputative regulatorsribonuclease
• 15 hypothetical proteins
Acknowledgments
Sponsors:AV ČRMBÚ AV ČRHHMI
Irena Linhartová
Petr Halada
Jana Novotná
Silvia Bezoušková
Jiří Vohradský
Radim Osička
Jaroslav Weiser
Peter Šebo