Lezione 4 INFIAMMAZIONE

L’INFIAMMAZIONE
INFIAMMAZIONE = risposta protettiva
dei tessuti a stimoli endogeni o esogeni
che provocano danno.
Ha 2 obiettivi:
1. eliminare o contenere la causa del danno
2. riparazione dei tessuti danneggiati
Infiammazione: ACUTA e CRONICA
FLOGOSI ACUTA O ANGIOFLOGOSI
E' LA REAZIONE DEL MICROCIRCOLO
VASCOLARE CARATTERIZZATA DAL
MOVIMENTO DI FLUIDI E LEUCOCITI DAL
SANGUE AL TESSUTO EXTRAVASCOLARE.
CAUSE: CHIMICHE, FISICHE, BIOLOGICHE
MANIFESTAZIONI: RUBOR
TUMOR
DOLOR
CALOR
Le fasi dell infiammazione acuta
Edema
PMNs
Monociti/Macrofagi
RIPARAZIONE
à (fibroblasti)
Attivita
1
2
GIORNI
3
FENOMENI ALLA BASE DELLA ANGIOFLOGOSI:
1) IPEREMIA ATTIVA (ARTERIOLE, CAPILLARI,
VENULE)
-
VASODILATAZIONE DELLE ARTERIOLE
PRECAPILLARI E VASOCOSTRIZIONE DELLE
VENULE POSTCAPILLARI –aumento flusso sg. E’ dovuta
al rilascio di mediatori chimici vasoattivi (plasmatici o tessutali)
-
AUMENTO DELLA PERMEABILITA'
DELLA BARRIERA ENDOTELIALE; STASI
Filmato migrazione nel sito d infiammazione
LA FAGOCITOSI
INGLOBAMENTO
ATTACCO
Ossidasi
citoplasmatica
FORMAZIONE DEL
FAGOLISOSOMA E
DEGRANULAZIONE
Granulo
Formazione di
radicali
dell’ossigeno
e ipoclorito
Ossidasi
di membrana
Membran
MEDIATORI CHIMICI DELL’INFIAMMAZIONE
1. DERIVATI DAI SISTEMI POLIMOLECOLARI SOLUBILI
del plasma
Sistema del complemento
Sistema delle chinine
Sistema della coagulazione - fibrinolisi
2. DERIVATI DA CELLULE, durante o dopo il reclutamento. Sono
di tipo diverso:
PREFORMATI
Istamina
Serotonina
Ensimi lisosomiali
DI NUOVA SINTESI Prostaglandine
Leucotrieni
PAF (fattore attivante le
piastrine)
Radicali liberi
Ossido nitrico
Citochine
PATOGENESI PROCESSO INFIAMMATORIO
DANNO
Mediatori
chimici
1.  Modificazioni vascolari: vasodilatazione e aumentata
permeabilità endoteliale: iperemia attiva
2. Eventi cellulari: passaggio di leucociti nel compartimento
extravascolare (migrazione transendoteliale, fagocitosi, exocitosi)
Eliminazione
del danno
Risoluzione
Mancata eliminazione
del danno
Ascessualizzazione
Infiammazione
cronica
Guarigione
Cicatrizzazione/Rigenerazione
FLOGOSI CRONICA (ISTOFLOGOSI) – lunga durata (settimane,
mesi)
SCARSA O NULLA PARTECIPAZIONE VASCOLARE
SPESSO NON DIFENSIVA
CELLULARITA' PREVALENTEMENTE MONONUCLEATA (linfociti T e B, macrofagi)
DISTRUZIONE DEI TESSUTTI E GUARIGIONE PROCEDONO CONTEMPORANEAMENTE
ANGIOGENESI E FIBROSI
Cause:
- infezioni persistenti (es. TBC)
- prolungata esposizione a sostanze potenzialmente tossiche (es: silicosi,
aterosclerosi)
-
malattie autoimmuni
CARATTERISTICA: GRANULOMA = area focale di infiammazione cronica specifica caratterizzata da
macrofagi modificati.
Il granuloma
!
Le citochine
Le citochine sono polipeptidi prodotti in risposta a microbi e antigeni e hanno il
ruolo di mediare e regolare le risposte immuni e infiammatorie.
The cytokine network
Endotossiemia
• Riconoscimento di LPS da LBP/CD14 e Toll-like receptors
• Signaling via Toll Receptor 4
• Effetti LPS su cells infiammatorie:
1.
2.
3.
4.
5.
6.
Produzione di citochine
Mediatori derivati da fosfolipidi di membrana
Attivazione ed espressione di molecole adesive
Attivazione di neutrofili
Produzione di NO
Induzione di attività procoagulante
LPS
!
!
L’analisi dell’infiammazione sistemica nell’uomo basata su
approcci di systems biology
LETTERS
NATURE|Vol 437|13 October 2005
had a maximum of 35 genes. (3) Pathways of highly interconnected genes were
identified by statistical likelihood using the following equation:
!
f 21
X
CðG; iÞCðN 2 G; s 2 iÞ
Score ¼ 2log10 1 2
CðN; sÞ
i¼0
13.
14.
where N is the number of genes in the genomic network, of which G are focus
genes, for a pathway of s genes, f of which are focus genes. C(n,k) is the binomial
coefficient. (4) Pathways with a score greater than 4 (P , 0.0001) were
combined to form a composite network representing the underlying biology
of the process.
15.
16.
17.
Received 17 May; accepted 4 July 2005.
Published online 31 August 2005.
18.
1.
19.
LETTERS
Heller, R. A. et al. Discovery and analysis of inflammatory disease-related
genes using cDNA microarrays. Proc. Natl Acad. Sci. USA 94, 2150–-2155
(1997).
2. Golub, T. R. et al. Molecular classification of cancer: class discovery and class
prediction by gene expression monitoring. Science 286, 531–-537 (1999).
3. Alizadeh, A. A. et al. Distinct types of diffuse large B-cell lymphoma identified
by gene expression profiling. Nature 403, 503–-511 (2000).
4. Bittner, M. et al. Molecular classification of cutaneous malignant melanoma by
gene expression profiling. Nature 406, 536–-540 (2000).
5. Perou, C. M. et al. Molecular portraits of human breast tumours. Nature 406,
747–-752 (2000).
6. Coussens, L. M. & Werb, Z. Inflammation and cancer. Nature 420, 860–-867
(2002).
7. Ridker, P. M., Hennekens, C. H., Buring, J. E. & Rifai, N. C-reactive protein and
other markers of inflammation in the prediction of cardiovascular disease in
women. N. Engl. J. Med. 342, 836–-843 (2000).
8. Cheung, C. Y. et al. Induction of proinflammatory cytokines in human
macrophages by influenza A (H5N1) viruses: a mechanism for the unusual
severity of human disease? Lancet 360, 1831–-1837 (2002).
9. Bone, R. C. et al. Definitions for sepsis
2 and organ failure and guidelines for the 3
use of innovative therapies in sepsis. The ACCP/SCCM Consensus Conference
Committee. American College of Chest Physicians/Society of Critical Care
3
Medicine. Chest 101, 1644–-1655 (1992).
10. Fong, Y. M. et al. The acute splanchnic and peripheral tissue metabolic
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response
to endotoxin in humans. J. Clin. Invest.
11. Dinauer, M. C., Orkin, S. H., Brown, R., Jesaitis, A. J. & Parkos, C. A. The
glycoprotein encoded by the X-linked chronic granulomatous disease locus is a
component of the neutrophil cytochrome b complex. Nature 327, 717–-720
(1987).
12. Wolk, K., Docke, W. D., von Baehr, V., Volk, H. D. & Sabat, R. Impaired antigen
20.
21.
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presentation by human monocytes during endotoxin tolerance. Blood 96,
218–-223 (2000).
Wolk, K., Kunz, S., Crompton, N. E., Volk, H. D. & Sabat, R. Multiple
mechanisms of reduced major histocompatibility complex class II expression in
endotoxin tolerance. J. Biol. Chem. 278, 18030–-18036 (2003).
Nakagawa, T. et al. Cyclophilin D-dependent mitochondrial permeability
transition regulates some necrotic but not apoptotic cell death. Nature 434,
652–-658 (2005).
Baines, C. P. et al. Loss of cyclophilin D reveals a critical role for mitochondrial
permeability transition in cell death. Nature 434, 658–-662 (2005).
Buttgereit, F. & Brand, M. D. A hierarchy of ATP-consuming processes in
mammalian cells. Biochem. J. 312, 163–-167 (1995).
Crouser, E. D., Julian, M. W., Blaho, D. V. & Pfeiffer, D. R. Endotoxin-induced
mitochondrial damage correlates with impaired respiratory activity. Crit. Care
Med. 30, 276–-284 (2002).
Padfield, K. E. et al. Burn injury causes mitochondrial dysfunction in skeletal
muscle. Proc. Natl Acad. Sci. USA 102, 5368–-5373 (2005).
Brealey, D. et al. Association between mitochondrial dysfunction and severity
and outcome of septic shock. Lancet 360, 219–-223 (2002).
Fink, M. P. Cytopathic hypoxia. Mitochondrial dysfunction as a mechanism
contributing to organ dysfunction in sepsis. Crit. Care. Clin. 17, 219–-237 (2001).
Kalil, A. C. et al. Effects of drotrecogin alfa (activated) in human endotoxemia.
Shock 21, 222–-229 (2004).
Li, C. & Wong, W. H. Model-based analysis of oligonucleotide arrays:
expression index computation and outlier detection. Proc. Natl Acad. Sci. USA
98, 31–-36 (2001).
Tusher, V. G., Tibshirani, R. & Chu, G. Significance analysis of microarrays
applied to the ionizing radiation response. Proc. Natl Acad. Sci. USA 98,
5116–-5121 (2001).
Eisen, M. B., Spellman, P. T., Brown, P. O. & Botstein, D. Cluster analysis and
display of genome-wide expression patterns. Proc. Natl Acad. Sci. USA 95,
14863–-14868 (1998).
Vol 437|13 October 2005|doi:10.1038/nature03985
A network-based analysis of systemic inflammation
in humans
23.
24.
Supplementary Information is linked to the online version of the paper at
www.nature.com/nature.
3
Steve E. Calvano1*, Wenzhong Xiao *, Daniel R. Richards , J.Ramon
M. S.Felciano
Henryfor technical
V. Baker4,5,
Wilhelmy, A. Kumar,
MacMillan and A.,Abouhamze
assistance.
This work was supported6by an Injury and the Host Response to
6
5
Large ScaleCobb
Collaborative, Research
Program Award
from the
,
J.
Perren
S.
Kevin
Tschoeke
,
Raymond J. Cho3, Richard O. Chen , Bernard H. BrownsteinInflammation
National Institute of General Medical Sciences (to R.G.T.).
2
2
8
, Ronald
Davis
, Ronald
Carol Miller-Graziano , Lyle L. Moldawer , Michael N. Mindrinos
Author Information
Reprints andW.
permissions
information
is available at G. Tompkins ,
npg.nature.com/reprintsandpermissions. The authors declare competing
Injury
Large
Scale
Collaborative
Research
Stephen F. Lowry1 & the Inflammation and Host Response to
financial
interests: details
accompany
the paper
on www.nature.com/nature.
Correspondence and requests for materials should be addressed to R.W.D.
([email protected]).
Program†
Acknowledgements We thank S. M. Coyle for clinical assistance, and
Oligonucleotide and complementary
DNA microarrays are being
endotoxin activates innate immune responses and presents with
Inflammation and Host Response to Injury Large Scale Collaborative Research Program Paul E. Bankey , Timothy R. Billiar , David G.
10
Notably, there is an initial
used to subclassify histologically
similar
monitor
diseaseA. Choudhry
physiological
responses
duration
Casellatumours,
, Irshad H. Chaudry
, Mashkoor
, Charles Cooper
, Asitof
Debrief
, Constance
Elson ,. Bradley
Camp , George
1–5
,
Richard
L.
Gamelli
,
Celeste
Campbell-Finnerty
,
Nicole
S.
Gibran
,
Douglas
L.
Hayden
,
Brian
G.
Harbrecht
,
David
N.
Freeman
proinflammatory phase and a subsequent counterregulatory
phase,
progress, and individualize
treatment regimens . However,
Herndon , Jureta W. Horton , William J. Hubbard , John L. Hunt , Jeffrey Johnson , Matthew B. Klein , James A. Lederer , Tanya
extracting new biological
insight
fromV.high-throughput
genomic
with, resolution
of virtually
clinical
within 24 h.
, Ronald
Maier , John A. Mannick
, Philip H. Mason
Bruce A. McKinley
, Joseph P.all
Minei
, Ernestperturbations
E. Moore ,
Logvinenko
B. Nathens
Grant E. O’Keefe
G. Rahme ,cluster
Daniel G.and
Remick
, David A.component
Schoenfeld , Martin
Frederick
Moore , Avery
studies of human diseases
is a A.challenge,
limited
by ,difficulties
in, LaurenceK-means
principal
analyses were first used
Schwacha , Michael B. Shapiro , Geoffrey M. Silver , Richard D. Smith , John D. Storey , Mehmet Toner , H. Shaw Warren ,
recognizing and evaluating
relevant
biological processes from
to visualize the overall response to endotoxin administration. Figure
Michael A.
West
huge quantities of experimental data. Here we present a structured
1a reveals probe sets clustered by K-mean analysis, where each bin has
1
3
4
7
5
5
8
9
9
11
6
5
10
16
5
10
6
2
13
26
14
15
16
10
8
2
1
6
12
15
10
19
19
26
17
3
11
18
20
13
6
21
22
Scopo dell’applicazione: chiarire i meccanismi responsabili
della risposta infiammatoria sistemica a LPS nel contesto
di una guarigione completa
Questo studio NON può essere eseguito su cellule
Questo studio NON può essere eseguito su pazienti “veri” in
quanto i pazienti con endotossiemia hanno spesso patologie
pregresse oppure vanno incontro a trattamenti che alterano la
risposta infiammatoria
FASI DELL’APPLICAZIONE:
1.  Soggetti umani ed induzione dell’endotossiemia
2.  Dinamica della risposta genomica infiammatoria
3. Costruzione dell’interactoma
4. Il network dell’infiammazione sistemica
5. Analisi della dinamica delle pathways di geni coinvolti
6. Conclusioni sulla dinamica della risposta infiammatoria
sistemica transiente
1.  Soggetti umani ed induzione dell’endotossiemia
a.  Il modello dell’endotossiemia umana:
8 soggetti sani tra 18-40 anni sono stati divisi in 2 gruppi: controllo e
trattati con LPS 2ng/kg
b. Sampling del sangue (blood sampling):
I campioni di sangue sono stati ottenuti da ogni paziente a tempo 0,
e a 2h, 4h, 6h, 9h e 24h dopo l’infusione di LPS
c. Isolamento dei leucociti totali dal sangue ed estrazione del RNA
- Isolamento dei leucociti dopo la lisi dei globuli rossi
- Isolamento del RNA totale mediante kit Qigen
2. Dinamica della risposta genomica infiammatoria
Profili di espressione genica nei leucociti circolanti in risposta
all’endotossina
Risultati micorarrays:
- 5.093 probe sets variano in maniera
significativa in risposta a LPS
- sono stati identificati 3.714 geni
EntrezGeneID (http://
www.ncbi.nih.gov/Entrez/)
Il clustering dei probe sets
in 10 bins è stato effettuato con
K-means analysis utilizzando
Cluster e TreeView che
rappresentano due programmi
integrati per analizzare e visualizzare
risultati di esperimenti complessi
di microarrays.
Ogni bin rappresenta un
pattern temporale distinto
K-means clustering
The algorithm is composed of the following steps:
1.  Place K points into the space represented by the
objects that are being clustered. These points
represent initial group centroids.
2.  Assign each object to the group that has the closest
centroid.
3.  When all objects have been assigned, recalculate
the positions of the K centroids
4.  Repeat Steps 2 and 3 until the centroids no longer
move. This produces a separation of the objects
into groups from which the metric to be minimized
can be calculated.
2. Dinamica della risposta genomica infiammatoria
Risultati:
Più della metà dei geni presentano una
riduzione dell’espressione (bins 0-4)
Un gruppo ridotto mostra un aumento a
2h (bins 5, 6)
L’espressione degli altri geni aumenta
tardivamente (bins 7-9)
2. Dinamica della risposta genomica infiammatoria
3D plot del principal component dei probe sets significativi a vari
time points dopo la somministrazione di LPS
PRINCIPAL COMPONENT ANALYSIS per dati di microarays
Principal components analysis (PCA) is a statistical technique for
determining the key variables in a multidimensional data set that
explain the differences in the observations, and can be used to simplify
the analysis and visualization of multidimensional data sets. PCA
allows us to summarize the ways in which gene responses vary under
different conditions.
PCA is a method that reduces data dimensionality by performing a
covariance analysis between factors. As such, it is suitable for data sets in
multiple dimensions, such as a large experiment in gene expression.
3. Costruzione dell’interactoma
IL DATABASE
http://www.ingenuity.com/
Sono state utilizzate le informazioni fornite da Ingenuity Systems Inc. (a
pagamento!
2005: “The Ingenuity Pathways Knowledge Base (KB) is the largest curated
database of previously published findings on mammalian biology from the
public literature.”
The KB is constructed through the efforts of Ph.D.- level scientists who have
read the abstracts of every paper in the Ingenuity KB. These scientists
manually extracted the findings in the KB from the full text of >200,000
articles, including the abstract, text, tables, and figures. As of January 2005,
the KB includes information of more than 9,800 human (including the ~9,500
Reviewed and Validated Human RefSeqs, http://www.ncbi.nlm.nih.gov/entrez/
query.fcgi?CMD=search&DB=gene ), 7,900 mouse, and 5,000 rat genes.
3. Costruzione dell’interactoma
IL DATABASE
http://www.ingenuity.com/
Sono state utilizzate le informazioni fornite dal database di Ingenuity
Systems Inc. (a pagamento!
2005: “The Ingenuity Pathways Knowledge Base (KB) is the largest curated
database of previously published findings on mammalian biology from the
public literature.
The KB is constructed through the efforts of Ph.D.-level scientists who have
read the abstracts of every paper in the Ingenuity KB. These scientists
manually extracted the findings in the KB from the full text of >200,000
articles, including the abstract, text, tables, and figures.
As of January 2005, the KB includes information of more than 9,800 human
(including the ~9,500 Reviewed and Validated Human RefSeqs, http://
www.ncbi.nlm.nih.gov/entrez/query.fcgi?CMD=search&DB=gene ), 7,900
mouse, and 5,000 rat genes.”
3. Costruzione dell’interactoma
IL DATABASE
http://www.ingenuity.com/
2011: The Ingenuity Pathways Analysis (IPA) program is a software that
helps researchers model, analyze, and understand data derived from gene
expression, microRNA, and SNP microarrays; metabolomics, proteomics, and
RNA-Seq experiments; and small-scale experiments that generate gene and
chemical lists.
Network analysis was performed on molecular relationships involving
8,000 human orthologs (between human, mouse and rat, as defined by
Homologene, http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=homologene).
IPA® 9.0
Applications
•
•
•
•
•
Target Identification and Validation
Biomarker Discovery
Drug Mechanism of Action
Drug Mechanism of Toxicity
Disease Mechanisms
Experimental approaches supported
•
•
•
•
•
•
•
RNA-Seq
microarray
microRNA
mRNA
qPCR
proteomics
genotyping
Identifiers supported in IPA
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
Affymetrix (Exon/Gene
Expression, 3’ IVT Expression)
Affymetrix SNP ID (Genotyping)
Agilent (Gene Expression, microRNA)
Applied Biosystems
(Gene Expression, microRNA)
CAS Registry
CodeLink
dbSNP IDs (including Illumina
genotyping arrays with dbSNP ids)
Entrez Gene
Ensembl new
GenBank
GenPept
GI Number
HUGO Gene Symbol
Human Metabolome Database (HMDB)
Illumina (whole-genome
& microRNA arrays)
International Protein Index
KEGG ID
miRBase (mature)
PubChem CID
RefSeq
new
UCSC Human Isoform IDs (hg 18 & hg 19)
UniGene
UniProt/SwissProt Accession
IPA® is an all-in-one, web-based software application that enables you to analyze, integrate,
and understand data derived from gene expression, microRNA, and SNP microarrays; metabolomics,
proteomics, and RNA-Seq experiments; and small-scale experiments that generate gene and
chemical lists. With IPA you can search for targeted information on genes, proteins, chemicals,
and drugs, and build interactive models of your experimental systems. IPA’s data analysis and
search capabilities help you
understand the significance
of your data, specific target,
or candidate biomarker in the
context of larger biological or
chemical systems, backed by
the Ingenuity® Knowledge Base
of highly structured, detailrich biological and chemical
Findings.
Path Designer transforms networks
and pathways into publication quality
representations of biological systems.
Data Analysis & Interpretation
IPA’s Data Analysis and Interpretation unlocks the insights buried in experimental data by
quickly identifying relationships, mechanisms, functions, and pathways of relevance, allowing you
to move beyond statistical analysis to novel biological insights, testable hypotheses, and validation
experiments.
IPA Core Analysis delivers a rapid
assessment of the signaling and metabolic
pathways, molecular networks, and biological
processes that are most significantly perturbed
in a dataset of interest.
• Understand the relative impact of
changes in mRNA, microRNA, protein
or metabolite levels in the context
of well-characterized pathways.
• Identify the cellular and disease
phenotypes most significant to a
set of genes, and understand how
those genes impact that phenotype,
i.e. whether they increase or
decrease a biological process.
Species-specific identifiers
supported in IPA
•
•
•
•
Human
Mouse
Rat
Additional species supported
Identify pathways implicated by multiple
experimental platforms.
• Optimize visualization and biological context of analyses with Context and Network
Size parameters.
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HomoloGene is a system for automated detection of homologs among the annotated genes of
several completely sequenced eukaryotic genomes.
HomoloGene Release 65 Statistics
Initial numbers of genes from complete genomes, numbers of genes
placed in a homology group, and the numbers of groups for each
species.
Species
Number of Genes HomoloGene
Input Grouped
groups
*
Homo sapiens
18,981
18,431
19,943
Pan troglodytes
16,850
15,980
25,096
Canis familiaris
16,708
15,951
19,766
Bos taurus
18,180
16,224
22,049
Mus musculus
21,766
19,005
25,388
Rattus norvegicus
19,229
17,473
21,991
Gallus gallus
13,142
11,905
17,959
*
Danio rerio
21,084
14,067
26,690
*
Drosophila melanogaster
9,282
7,749
13,827
Anopheles gambiae
8,867
7,541
12,460
Caenorhabditis elegans
8,678
4,810
20,132*
Schizosaccharomyces pombe
3,225
2,935
5,043
Saccharomyces cerevisiae
4,851
4,370
5,880
Kluyveromyces lactis
4,459
4,382
5,335
Eremothecium gossypii
3,928
3,884
4,722
Magnaporthe grisea
7,330
6,399
12,832
*
Neurospora crassa
6,287
6,144
9,821
Arabidopsis thaliana
19,961
11,243
27,309*
Oryza sativa
17,276
10,627
26,887
Plasmodium falciparum
1,862
799
5,266
'*' indicates organisms where new genome annotation data is used in this
build.
Last updated on: Mon Feb 14 2011
We have recently adopted a new build procedure that makes use of
amino acid sequence searching (blastp) to find more distant
relationships, but the procedure still refers to the DNA sequence for
computation of some of the statistics. The matching strategy is guided
by the taxonomic tree such that more closely related organisms are
compared first. Moreover, HomoloGene entries now include paralogs
in addition to orthologs.
What's New
HomoloGene release 65
includes updated annotations
for the following species: Homo
sapiens (NCBI release 37.2),
Danio rerio (NCBI release 4.1),
Drosophila melanogaster (NCBI
release 9.3) Caenorhabditis
elegans (NCBI release 9.1),
Arabidopsis thaliana (NCBI
release 9.1).
Tip of The Day
Use [unigene id] in your search
query to restrict search results
to that particular unigene
cluster. e.g. Hs.15484[unigene
id].
[More Tips]
Related Resources
Entrez Genomes
A collection of complete genome
sequences that includes more than
1000 viruses and over hundred
microbes
Archaea
Bacteria
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Viruses
Books
3. Costruzione dell’interactoma
Esempio: il network del gene RELA estratto dal KB e visualizzato con IPA
1. Examining KB content for RELA (Suppl Figure 1)
Supplementary Figure 1 describes the network neighborhood surrounding a single gene, RELA.
To reproduce this network in IPA, please perform the following steps identified below. The
network neighborhood is derived from findings extracted from the public literature and stored in
the KB. Every gene interaction is supported by evidence from the underlying papers.
Gene
RELA
Neighboring Genes
150
Direct Interactions
619
Findings
7,118
Papers
847
the page to view the “Network Neighborhood Explorer” for
NF-kB = nuclear factor of kappa light chain gene enhancer in B-cells
7.
From
the
“Network
Neighborhood
Explorer”,
with
RELA
in
Rel/NFKB family includes REL (c-Rel) (MIM164910), RELA (RelA/p65) (MIM 164014), RELB
RELB
in the diagram
and and
click
on it.
Alternately,
select “RE
(RelB) (604758), NFKB1
(P105/p50)
(MIM 164011),
NFKB2
(p100/p52)
(MIM 164012).
NFKB is activated by
variety
of stimuli
cytokines, oxidant-free
inhaled
lista wide
on the
left.
RELBsuch
is as
highlighted
in blue, radicals,
as are the
edges
particles, ultraviolet irradiation, and bacterial or viral products. Inappropriate activation of NFRELA:
kappa-B has been linked
to inflammatory events associated with autoimmune arthritis, asthma,
septic shock, lung fibrosis, glomerulonephritis, atherosclerosis, and AIDS.
4. Il network dell’infiammazione sistemica
A. LA CELLULA INFIAMMATORIA VIRTUALE: la risposta
specifica dell’immunità innata
292 representative genes involved in inflammation and innate immunity. Genes for which the expression statistically increased from baseline
are coloured red, those for which expression decreased are shown in blue
4. Il network dell’infiammazione sistemica
B. Il network intracellulare della
risposta infiammatoria
generale cellulare
(formato da 1.556 geni)
5. Analisi della
dinamica delle
pathways di
geni coinvolti
Analisi delle pathways
dei geni rappresentativi
dell’immunità innata
nella cellula virtuale
5. Analisi della dinamica delle pathways di geni coinvolti
La cellula virtuale: Risultati
2-4h
Espressione massima di citochine e chemochine proinfiammatorie a
2-4h: TNFSF2 (TNFa), IL1alpha, IL1beta, CXCL1 (GROalpha),
CXCL2 (GRO-beta), CCL2 (MCP-1), CXCL8 (IL-8) and CXCL10,
molecole pro-infiammatorie come PTGS2 (sintesi di prostaglandine),
SOD2 formazione di ROS (reactive oxygen species) come H2O2
Espressione di fattori di trascrizione pro-infiammatori a 2-4h: membri
della famiglia di nuclear factor kappa/RelA (NFKB1, NFKB2, RELA
and RELB) e STAT
- Espressione di IKBKB (Inhibitor of nuclear factor kappa-B kinase
subunit beta) che inibisce la funzione dell’inibitore di NFKB
TNSF2 = Tumor necrosis factor ligand superfamily member 2 = TNFalpha
PTGS2 = Prostaglandin G/H synthase 2 = Cyclooxygenase-2
SOD2 = Superoxide dismutase [Mn], mitochondrial
5. Analisi della dinamica delle pathways di geni coinvolti
La cellula virtuale: Risultati
6h
-  Espressione di geni per STAT (signal transductor and activator of
transcription) e cAMP-response element-binding protein (CREB)
genes.
-  Espressione di geni per fattori di trascrizione che limitano la
risposta innata come per esempio suppressor of cytokine
signalling 3 (SOCS3).
-  Espressione di geni per citochine anti-infiammatorie: IL10
-  Riduzione dell’espressioni di geni pro-infiammatori upregolati a 4h
9h – Riduzione dei geni pro-infiammatori
24h – Ritorno ad uno stato simile alla fase iniziale (tempo 0)
5. Analisi della dinamica delle pathways di geni coinvolti
Il network intracellulare della
risposta infiammatoria
generale cellulare
(formato da 1.556 geni)
Blu = geni con ridotta espressione
Rosso = geni con aumentata espressione
to
A small
small amount
amount of
of
to produce
produce ATP,
ATP, which
which provides
provides energy
energy to
to power
power other
other cellular
cellular reactions.
reactions. A
The electron
transport
chain
(ETC)
in
mitochondria
ATP
glycolysis. In
In most
most
ATP is
is available
available from
from substrate-level
substrate-level phosphorylation,
phosphorylation, for
for example,
example, in
in glycolysis.
organisms
while only
only some
some
organisms the
the majority
majority of
of ATP
ATP is
is generated
generated in
in electron
electron transport
transport chains,
chains, while
[citation
needed]
obtain
obtain ATP
ATP by
by fermentation.
fermentation.[citation needed]
Electron transport chains in mitochondria
Most
products of
of the
the Krebs
Krebs
Most eukaryotic
eukaryotic cells
cells contain
contain mitochondria,
mitochondria, which
which produce
produce ATP
ATP from
from products
cycle, fatty acid oxidation, and amino acid oxidation. At the mitochondrial inner membrane,
electrons from NADH and succinate pass through the electron transport chain to oxygen, which
is reduced to water. The electron transport chain comprises an enzymatic series of electron
donors and acceptors. Each electron donor passes electrons to a more electronegative acceptor,
which in turn donates these electrons to another acceptor, a process that continues down the
series until electrons are passed to oxygen, the most electronegative and terminal electron
acceptor in the chain. Passage of electrons between donor and acceptor releases energy, which
is used to generate a proton gradient across the mitochondrial membrane by actively pumping
protons into the intermembrane space, producing a thermodynamic state that has the potential
to do work. A small percentage of electrons do not complete the whole series and instead
to produce ATP, which provides energy to
directly leak to oxygen, resulting in the formation of the free-radical superoxide, a highly
to produce ATP, which provides energy to power other cellular reactions. A small amount of ATP is available from substrate-level phosp
reactive molecule that contributes to oxidative stress and has been implicated in a number of organisms the majority of ATP is generated
ATP is available from substrate-level phosphorylation, for example, in glycolysis. In most
diseases and aging.
obtain ATP by fermentation.[citation needed]
organisms the majority of ATP is generated in electron transport chains, while only some
obtain ATP by fermentation.[citation needed]
Mitochondrial redox carriers
Electron transport chains in mitochondria
NAD = Nicotinamide adenine dinucleotide
UQ = ubiquinone
Electron transport chains in
Most eukaryotic cells contain mitochondria,
Most eukaryotic cells contain mitochondria, which produce ATP from products of the Krebs cycle, fatty acid oxidation, and amino acid o
cycle, fatty acid oxidation, and amino acid oxidation. At the mitochondrial inner membrane, electrons from NADH and succinate pass th
electrons from NADH and succinate pass through the electron transport chain to oxygen, whichis reduced to water. The electron transport c
donors and acceptors. Each electron donor p
is reduced to water. The electron transport chain comprises an enzymatic series of electron
donors and acceptors. Each electron donor passes electrons to a more electronegative acceptor, which in turn donates these electrons to ano
which in turn donates these electrons to another acceptor, a process that continues down the series until electrons are passed to oxygen,
acceptor in the chain. Passage of electrons b
series until electrons are passed to oxygen, the most electronegative and terminal electron
acceptor in the chain. Passage of electrons between donor and acceptor releases energy, which is used to generate a proton gradient across
isStylized
used torepresentation
generate a proton
gradient across the mitochondrial membrane by actively pumping protons into the intermembrane space, produ
of the ETC
protons into the intermembrane space, producing a thermodynamic state that has the potential to do work. A small percentage of electrons
directly leak to oxygen, resulting in the form
to
do work.
A small
percentage
of electrons
do not(black
complete
the whole
series
and
ETC
is instead
used to
Energy
obtained
through
the transfer
of electrons
arrows)
down the
reactive molecule that contributes to oxidati
directly
leak to(red
oxygen,
resulting
in the
formation ofmatrix
the free-radical
superoxide, a space,
highly
pump protons
arrows)
from the
mitochondrial
into the intermembrane
reactive
that contributes
oxidative
stresstheand
has been implicated
in a number
of diseases and aging.
(IMM)
creating molecule
an electrochemical
protontogradient
across
mitochondrial
inner membrane
diseases
called ". and
Thisaging.
electrochemical proton gradient allows ATP synthase (ATP-ase) to use the
flow of H+ through the enzyme back into the matrix to generate ATP from adenosine
Mitochondrial
carriersphosphate. Complex I (NADH coenzyme Q reductase;
diphosphate (ADP)redox
and inorganic
labeled I) accepts electrons from the Krebs cycle electron carrier nicotinamide adenine
Mitochondrial redox carriers
5. Analisi della dinamica delle pathways di geni coinvolti
Pathways che globalmente vanno incontro a soppressione dopo
stimolazione sistemica con LPS
Riduzione dei moduli implicati nella respirazione cellulare
Group 1
mitochondrial
respiratory
chain complex I
(NDUF genes)
Group 3
ATP synthase
complex (ATP5
genes).
NDUF = NADH Ubiquinone
oxidoreductase Fe-S
Group 2
mitochondrial
respiratory
chain complex
III (UQCR
genes).
UQCR = ubiquinol-cytochrome c
reductase
Group 4
pyruvate
dehydrogenase
complex.
5. Analisi della dinamica delle pathways di geni coinvolti
Riduzione di geni implicati nella diffusione di soluti attraverso le
membrane mitocondriali
Group 5
mitochondrial
permeability
transition pore
complex
Riduzione di moduli implicati nell’attività ribosomiale
Group 7
ribosomal
proteins (RPL,
RPS genes).
Group 6 Group
6, elongation
initiation factor
complex (EIF3
genes)
importanti
nella
traslazione.
d
b
5. Analisi della
dinamica delle pathways di geni coinvolti
Riduzione di moduli coinvolti nella pathway ubiquitin-proteasomes
Group 8
COP9
signallosome
(COPS genes).
f
Group 9
proteasome
(PSM genes).
e
Group e
subunits of the
anaphasepromoting
complex (E3
ubiquitin ligase)
The ubiquitination system functions in a wide
variety of cellular processes, including:
Antigen processing
Apoptosis
Biogenesis of organelles
Cell cycle and division
DNA transcription and repair
Differentiation and development
Immune response and inflammation
Neural and muscular degeneration
Morphogenesis of neural networks
Modulation of cell surface receptors, ion
channels and the secretory pathway
Response to stress and extracellular modulators
Ribosome biogenesis
Viral infection
a
c
5. Analisi della dinamica delle pathways di geni coinvolti
Attivazione di geni implicati nel danno ossidativo e mitosi
a
b
Groupc a .
superoxideproducing
phagocyte
NADPHoxidase.
d
b
d
e
Group d . tubulin-A
genes.
5. Analisi della dinamica delle pathways di geni coinvolti
a
e
c
Riduzione di geni implicati nell presentazione antigenica (MHC II) e
molecole di adesione implicate nel movimento cellulare (integrine)
d
b
Group a
members of the
MHC II
complex
e
f
f
Group f
Integrin chains
6. Conclusioni sulla dinamica della risposta infiammatoria
sistemica transiente
1. L’analisi della “cellula virtuale” evidenzia un’aumento
transiente a tempi brevi dell’espressione genica per molecole
con attività proinfiammatoria (citochine, chemochine, danno
ossidativo, fattori di trascrizione pro-infiammatori, TLRs). A
tempi più lunghi vengono attivati geni anti-infiammatori
2. L’analisi del network dell’infiammazione sistemica evidenzia
una disregolazione di moduli implicati in varie funzioni
cellulari nei leucociti umani: metabolismo energetico, sintesi
proteica e degradazione proteica in seguito ad endotossiemia
transiente
3. La soppressione di importanti moduli funzionali suggerisce
che i leucociti esposti a stimoli pro-infiammatori hanno
un’alterata capacità di rispondere a stimoli successivi
(toleranza dell’immunità innata)