Microbial Diagnostic Microarray (MDMs) Microbial Diagnostic Microarray (MDMs) IZSA&M IZSA&M

Yersinia, Salmonella, ListeriaYersinia, Salmonella, Listeria

Obiettivo 1Obiettivo 1: : Metodo

• Differenziare il genere e la specie di Differenziare il genere e la specie di appartenenza degli organismi patogeniappartenenza degli organismi patogeni

• Evidenziare la presenza dei geni di Evidenziare la presenza dei geni di virulenza nel patogenovirulenza nel patogeno

Una multipurpose platform: un unico test

18/03/09

MDMs IZSA&M MDMs IZSA&M Yersinia, Salmonella, ListeriaYersinia, Salmonella, Listeria

Microbial Diagnostic Microarray (MDMs)

Sequenze di oligonucleotidi 35, 50 e 70 mer

Identificazione di specie Housekeeping genes

PatogeniGeni di virulenza

MDMs IZSA&MMDMs IZSA&MSalmonellaSalmonella

Teoricamente 47 Serovars di Salmonella entericaSalmonella enterica

subsp. entericasubsp. enterica305 Virulence genes

Chromosome encoded Plasmid encoded

MDMs IZSA&MMDMs IZSA&MSalmonellaSalmonella

                                                                                                                 

                                                                                                                   

Chen et al. 2005: VFDB: a reference database for bacterial virulence factors.

Yang et al. 2008: VFDB 2008 release: an enhanced web-based resource for comparative pathogenomics

http://zdsys.chgb.org.cn/VFs/main.htm

MDMs IZSA&MMDMs IZSA&MYersiniaYersinia

Teoricamente 12 species of Yersinia 3 serotypes of Yersinia enterocolitica O:3, Yersinia enterocolitica O:3,

O:8, O:9O:8, O:9 195 Virulence genes of Y.enterocolitica

Chromosome encoded Plasmid encoded

Sequenced  Y. enterocolitica  8081 (biotype 1B) serotype O:8 has

1 chromosome 1 plasmid

MDMs IZSA&MMDMs IZSA&MListeriaListeria

Teoricamente 6 species of Listeria 4 serovars of Listeria monocytogenesListeria monocytogenes 21 Virulence genes of Listeria monocytogenes

MDMs IZSA&MMDMs IZSA&MHousekeeping genesHousekeeping genes

Per l’identificazione di specie vengono interrogati 2 o più

“Housekeeping genes” Classificazione Primers universali.

Housekeeping genesHousekeeping genes Universali In condizioni di crescita specifica il gene non

deve mutare per adattarsi (not show any adaptive mutation to specific growth conditions)

non deve trasferirsi in modo orizzontale

MDMs IZSA&MMDMs IZSA&MHousekeeping genesHousekeeping genes

16SrRNA (presente in abbondanza) Regioni variabili vengono usate per la

distinzione http://rdp.cme.msu.edu/http://rdp.cme.msu.edu/ hsp60, groEl or Chaperonins sono presenti

in eukaryotes e prokaryotes http://cpndb.cbr.nrc.ca/http://cpndb.cbr.nrc.ca/

gyrB, DNA gyrase rpoB, DNA-directed RNA polymerase

MDMs IZSA&MMDMs IZSA&MDesignDesignElenco Target

Dei Geni

InformazioniSequenze

DatabaseGenomich

e NCBI

PATRICERIC

NMPDRExPASy

OligoPicker Blast

Dedicated PC1 ghz

1 gig RAM

Desk Top PC500 mhz

512 meg RAM

Selected Unique Sequences

SEQUENCES

1° seq. evaluation 2° seq. evaluation

MDMs IZSA&MMDMs IZSA&MDesignDesign

Primary Sequence EvaluationPrimary Sequence EvaluationOligoPicker

Secondary Sequence EvaluationSecondary Sequence EvaluationNCBI-BlastPATRICERICExPASyNMPDR

MDMs IZSA&MMDMs IZSA&MDesignDesign

Sequenze scelte GC content range = 40%-60% Reject 4 or more contiguous bases of G or C

(2ndary Structure) Reject palindromic-hairpin sequences greater than

7 bases (2ndary Structure)http://www.bioinfo.rpi.edu/applications/hybrid/quikfold.phttp://www.bioinfo.rpi.edu/applications/hybrid/quikfold.phphp

Reject known splice site sequences Accepted if Calculated Tm = ΔT < 10-15 C No more than 75% homology within the target

region of non-target genes No more than 14 contiguous base pairs with non-

target genes.

MDMs IZSA&MMDMs IZSA&MDesignDesign

Numero di sequenze bersaglio SalmonellaSalmonella

521 YersiniaYersinia

317 ListeriaListeria

137 Numero di spots senza i controlli

positivi, negativi e blanks ((521+317+137)x4)= 3900 spots

MDMs IZSA&MMDMs IZSA&MDesignDesign

http://euler.bri.nrc.ca/bridna5/http://euler.bri.nrc.ca/bridna5/

Layout-view

Positive control 1.4 green

Negative control 4.3 pinkBlank 4.3

Estrarre e purificare DNA

Quantificare DNA (500 ng or >)

Amplificazione DNA • random primers

• fluorocrome (Cy3, Cy5)

Purificare e quantificare DNA amplificato (1 цg)Calcolare % incorporation (2-12) accetabile

http://www.pangloss.com/seidel/Protocols/percent_inc.htmlhttp://www.pangloss.com/seidel/Protocols/percent_inc.html

NanodropNanodrop

QUIAprepQUIAprep

Bioprime CGH Labeling Bioprime CGH Labeling ModuleModule

QUIAprep & QUIAprep & NanodropNanodrop

Ibridare

MDMs IZSA&MMDMs IZSA&MOutputOutput

Fluorescenza in numeri.BEGIN DATAIndex Array Row Array ColumnSpot Row Spot ColumnName ID X Y Diameter F Pixels B Pixels Footprint Flags Ch1 MedianCh1 Mean Ch1 SD

1 1 1 1 1 cjfly70 5435 6915 160 176 124 14 3 2248 2389 ########2 1 1 1 2 ch170 5639 6913 150 155 124 14 3 2095 2230 1259.803 1 1 1 3 cjfliq70 5834 6913 150 155 124 12 3 2543 2733 ########4 1 1 1 4 cfva50 6014 6906 150 153 124 16 3 2252 2525 1427.745 1 1 2 1 cjfly70 5442 7091 120 95 180 16 3 2624 2601 1328.896 1 1 2 2 ch170 5627 7098 130 113 180 4 3 2177 2337 1155.987 1 1 2 3 cjfliq70 5834 7105 140 130 124 5 3 2507 2798 ########8 1 1 2 4 cfva50 6009 7108 150 151 124 21 3 2087 2243 ########9 1 1 3 1 cjkpsd70 5435 7306 130 115 180 6 3 3295 3383 ########

10 1 1 3 2 cirp70 5633 7312 120 95 180 11 3 2652 2812 ########11 1 1 3 3 cjiama70 5823 7307 120 96 180 8 3 2743 2764 ########12 1 1 3 4 chorp70 6011 7304 130 114 180 18 3 2607 2727 ########13 1 1 4 1 cjkpsd70 5444 7496 140 133 124 15 3 2996 3022 ########14 1 1 4 2 cirp70 5639 7513 140 133 124 14 3 2891 3076 1573.6015 1 1 4 3 cjiama70 5823 7499 100 63 180 7 3 3536 3852 ########16 1 1 4 4 chorp70 6017 7508 130 113 180 13 3 2208 2340 ########17 1 1 5 1 cjptmb70 5482 7738 100 64 180 62 3 2685 3542 3545.6118 1 1 5 2 cjcdtb70 5626 7700 130 113 180 4 3 3870 4067 1574.7419 1 1 5 3 cjpfla70 5826 7708 150 156 124 7 3 2572 2730 ########20 1 1 5 4 cjcadf70 6015 7704 140 131 124 14 3 2094 2152 1110.6821 1 1 6 1 cjptmb70 5432 7904 140 133 124 3 3 3569 3721 ########22 1 1 6 2 cjcdtb70 5606 7903 120 96 180 23 1 2948 3053 ########23 1 1 6 3 cjpfla70 5817 7896 120 97 180 13 3 2801 3103 ########24 1 1 6 4 cjcadf70 6012 7893 120 96 180 19 3 2338 2462 1340.7625 1 1 7 1 cjvirb270 5441 8097 130 113 180 12 3 3727 4214 ########26 1 1 7 2 cj1136 5630 8111 140 135 124 9 3 3051 3214 1547.6627 1 1 7 3 cjvirb4 5821 8102 130 113 180 8 3 3022 3364 1764.6728 1 1 7 4 cjciab70 6008 8119 100 65 180 28 3 2460 2777 ########29 1 1 8 1 cjvirb270 5454 8292 140 133 124 25 3 2899 2899 1365.8730 1 1 8 2 cj1136 5627 8293 130 113 180 9 3 3250 3421 1586.9331 1 1 8 3 cjvirb4 5817 8302 140 135 124 12 3 2634 2940 ########32 1 1 8 4 cjciab70 6030 8305 150 154 124 3 3 65535 60852 11010.1233 1 1 9 1 csrr35 5473 8491 200 282 56 44 3 1772 2091 ########34 1 1 9 2 cj1430 5633 8494 130 116 180 7 3 2731 2799 1177.6735 1 1 9 3 cmrp70 5830 8493 150 153 124 8 3 3098 3237 1445.6236 1 1 9 4 cj1426 6017 8502 160 178 124 12 3 2777 3057 ########37 1 1 10 1 csrr35 5464 8688 120 96 180 37 1 1606 1734 1038.7338 1 1 10 2 cj1430 5621 8705 140 131 124 9 3 5048 5171 1955.6239 1 1 10 3 cmrp70 5819 8696 140 133 124 11 3 2448 2688 ########40 1 1 10 4 cj1426 6014 8685 160 174 124 23 3 3045 3313 ########41 1 1 11 1 hcd170 5443 8910 120 95 180 15 3 2694 2957 ########42 1 1 11 2 cj1436 5642 8894 140 132 124 14 3 2846 3109 1578.8843 1 1 11 3 csprp70 5832 8911 140 135 124 9 3 4113 4346 1924.8944 1 1 11 4 cj1433 6017 8899 120 95 180 13 1 3079 3173 ########45 1 1 12 1 hcd170 5435 9101 140 131 124 5 3 2254 2374 ########46 1 1 12 2 cj1436 5623 9104 140 132 124 6 3 2940 3181 1503.7547 1 1 12 3 csprp70 5828 9098 140 135 124 4 3 3174 3424 1546.6148 1 1 12 4 cj1433 6015 9102 140 133 124 14 3 2996 3243 1582.8649 1 1 13 1 sf31570 5443 9305 130 115 180 13 3 2654 2836 ########50 1 1 13 2 cjflge270 5633 9295 130 115 180 7 3 2715 2946 ########51 1 1 13 3 hpy270 5833 9296 130 116 180 6 3 2886 2965 1407.6452 1 1 13 4 cjflgc70 6030 9304 130 111 180 1 3 3381 3588 ########53 1 1 14 1 sf31570 5436 9490 130 111 180 13 3 2548 2673 1393.6054 1 1 14 2 cjflge270 5626 9503 140 131 124 4 3 2409 2716 ########55 1 1 14 3 hpy270 5828 9492 130 111 180 9 3 2959 3081 1312.9656 1 1 14 4 cjflgc70 6021 9500 130 112 180 8 3 2873 3122 1418.6857 1 1 15 1 Arab 5438 9698 150 152 124 8 3 2318 2486 ########58 1 1 15 2 cjflhA70 5631 9698 130 113 180 4 3 2421 2577 1325.7159 1 1 15 3 gfp50 5836 9706 140 131 124 6 3 2531 2673 ########60 1 1 15 4 cjflgh70 6019 9692 130 113 180 14 3 2586 2515 1268.83

MDMs IZSA&MMDMs IZSA&M

Obiettivo 2Obiettivo 2: : Automazione Creazione di un database con risultati

in .txt dei ceppi ATCC/NCTC/DSMZ e ceppi di campo

Applicazione di algoritmi statistici che forniranno un risultato dai dati numerici

Cluster analysis Principle component analysis altro

Applicazione di “Learning algorithms” per dare un nome con un valore P

MDMs IZSA&MMDMs IZSA&MDatabaseDatabase

Creazione del database DatabaseDatabase

http://candida.bri.nrc.ca/italy/index.cfmhttp://candida.bri.nrc.ca/italy/index.cfm Permetterà di comparare i profili di

fluorescenza inter e intra specie mediante Hierarchical clustering analysis

Con Java TreeView http://jtreeview.sourceforge.net/http://jtreeview.sourceforge.net/

Characterisation of the genetic diversity of Brucella by multilocus sequencingAdrian M Whatmore*, Lorraine L Perrett and Alastair P MacMillan

R= 0.8566R= 0.7895 R= 0.9304

988 genes 460 genes

MDMs IZSA&MMDMs IZSA&MCluster AnalysisCluster Analysis

Interspecies

MDMs IZSA&MMDMs IZSA&MCluster AnalysisCluster Analysis

55 different different biovarsbiovars of Brucella abortus of Brucella abortusBrucella abortus biovar 2, 4, 7, 5, 9 (in replicate)

22 5555777744 4422 99 99

MDMs IZSA&MMDMs IZSA&M

“ “Learning algorithms”GeneSpring GX