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MGH-PGA Genomic Analysis of Stress and Inflammation: Pseudomonas aeruginosa Infection

MGH-PGA Genomic Analysis of Stress and Inflammation: Pseudomonas aeruginosa Infection. Nicole T. Liberati, Dan G. Lee, Jacinto M. Villanueva and Frederick M. Ausubel Department of Molecular Biology Massachusetts General Hospital. Carolyn Cannon, Fadie Coleman, Mike Kowalski

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MGH-PGA Genomic Analysis of Stress and Inflammation: Pseudomonas aeruginosa Infection

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  1. MGH-PGA Genomic Analysis of Stress and Inflammation: Pseudomonas aeruginosa Infection Nicole T. Liberati, Dan G. Lee, Jacinto M. Villanueva and Frederick M. Ausubel Department of Molecular Biology Massachusetts General Hospital Carolyn Cannon, Fadie Coleman, Mike Kowalski Jeff Lyczak, Martin Lee, Gloria Meluleni, and Gerald Pier Channing Laboratory Brigham and Women’s Hospital

  2. Ausubel/Pier PGA Project

  3. Contents of Slide Show: Section I: Background Information on Multi Host Pathogenesis System Section II: Background Information on Screening Methodology and Rationale for Constructing the Uni-Gene Library Section III: Progress Report on Uni-Gene Library Construction and Detailed Methodology Section IV: Development of a Linux MySQL Uni-Gene Library Relational Database Section V: CF Mouse Oropharynx Colonization Model

  4. Section I Background Information on Multi-Host Pathogenesis System

  5. Pseudomonas aeruginosa • Gram-negative rod • Found throughout the environment in soil, water and plants • Opportunistic human pathogen: - Nosocomial pulmonary infections - Immune compromised patients (chemotherapy/burns) - 85% of adult CF patients suffer from chronic pulmonary P. aeruginosa infections

  6. P. aeruginosa Strain PA14 P. aeruginosa Multi-Host Pathogenesis System Humans Mice Plants Nematodes Insects

  7. P. aeruginosa Kills C. elegans and Colonizes the C. elegans Intestine 100 P. aeruginosa E. coli 80 60 % Nematodes Killed 40 20 0 0 20 40 60 80 Hours of Feeding on P. aeruginosa strain PA14

  8. P. aeruginosa Kills Galleria mellonella (Wax Moth Caterpillar) Larvae; LD50 = 1

  9. Section II Background Information on Screening Methodology and Rationale for Constructing the Uni-Gene Library

  10. PA14 Identification of P. aeruginosa Virulence Factors by Screening “UniGene” Library for Mutants that do not Kill Wax Moth Caterpillars or Nematodes Random Transposon Mutagenesis Sequence Insertion Sites and Identify a Non-Redundant “Unigene” Set Screen Unigene Set for Mutants that Do Not Kill C. elegans or Wax Moths Test Mutants that Do Not Kill C. elegans in CF Mouse Model

  11. 6 Mb Generation of Transposon Insertion Mutations Transposase E. Coli Transposon: Kanr PA14 Select for insertions with Kanamycin

  12. Unigene Library: A collection of P. aeruginosa strains containing a disruption in each non-essential open reading frame (ORF) in the P. aeruginosa genome Wild type Mutant #1 Mutant #2

  13. ~6 Mb Unigene Library Size 6 Mb genome (S. cerevisiae) 4800 non-essential genes 5 fold saturation 24,000 insertions Recovery failure 30,400 insertions

  14. ~6 Mb Selection of Unigene Library Mutants 30,400 insertions Approximately 5 hits per ORF: Choose the most 5’ disruption within the actual coding sequence ~4800 catalogued Unigene mutants

  15. Advantages of Unigene Library Screening Mutation previously identified Limited number of mutants to screen (4800) Non-redundant mutations Built-in confirmation of the involvement of known pathways. Easy to confirm the importance of the mutated gene using other mutant alleles.

  16. Section III Progress Report on Uni-Gene Library Construction and Detailed Methodology

  17. Generation of Unigene Library of Transposon Insertions in Non-Essential Genes Pick ~30,000 colonies with Qbot into bar-coded 96- well plates containing media + selective antibiotics Grow overnight 25 ml for arbitrary (ARB) PCR reactions Add glycerol to 15% Divide into 3 plates: 384-well (Master copy) 384-well (Duplicate copy) 96-well (Working copy)

  18. Current Status of the Unigene Library 48 x 96 (4608) mutants created. 60% of the insertion sites identified. Insertion site identification protocol optimized. (1152 mutants created and identified in 2.5 weeks) 3) Accompanying database is operational. Quality assurance testing is in progress.

  19. Library Construction: Mutagenesis/Plating TnPhoA: Kanr/Neor E. Coli PA14 LB + Irgasan + Neomycin (3,000-5,000 colonies)

  20. Library Construction: Colony Picking/Culture • Inoculate 250 µL • LB + Irgasan [50 µg/mL] • Kanamycin [200 µg/mL]* • Grow 40 hrs at 37°C • (no shaking)

  21. Library Construction: Biomek-Automated Liquid Manipulation -80°C Storage -20°C Storage Culture (wor) (280 µL) 70 µL Working (wor) Add glycerol Mix and Seal Supernatant (sup) Master (mas) Duplicate (dup)

  22. Library Construction: Bar Coding B Side: Human Readable A Side: Unique ID# PA14_PhoA_100_xxx wor sup mas dup ar1 ar2 seq

  23. LEGEND Genomic DNA Transposon Transposon-specific Primer Arbitrary PCR Primers Library Construction: Arbitrary PCR to Amplify Sequence Adjacent to Transposon Insertion 3 2 1 1 2 1st PCR Reaction 2nd PCR Reaction PCR Cleanup and Sequencing

  24. Library Construction: Details of ARB1 PCR Supernatant (sup) Thaw, 99°C/6 min., pellet 3K/5 min. 3µL supnt Temporary Storage -20°C Arb PCR 1 (ar1) Arb PCR 1

  25. Library Construction: Details of ARB2 PCR ar1 5µL Temporary Storage -20°C Arb2 PCR (ar2) ARB2 PCR

  26. Library Construction: PCR Cleanup: EXOSAP-IT

  27. Library Construction: PCR Cleanup ar2 7µL Temporary Storage -20°C Sequencing plate (seq) + ExoSAP-IT 15’ at 37°C 15’ at 80°C

  28. Library Construction: Sequencing seq Add Sequencing primer to a [final] of 5 ng/µL and Seal Send to DNA Core for Sequencing (Store at 4°C)

  29. Example of High Quality Sequence TnPhoA Sequence Length + Mixed + TnPhoA = Sequence Success Index

  30. Example of Low Quality Sequence TnPhoA

  31. Optimization of [Taq] in Sequencing Reactions Sequencing Success Index

  32. Unigene Library Mutant Identification Optimized for: • Taq Manufacturer • Roche vs. Promega vs. Prepared Master Mixes • Final Taq Concentration • 1.25 U sufficient • PCR Master Mix Preparations • Fresh Master Mixes vs Stored (4°C) Master Mix • Hybaid vs. MJ Research PCR Machines • PCR Cleanup Protocol • ExoSAP-IT vs. Clontech NucleoSpin

  33. Relevant Background Sequence: Template Independent Genomic Sequence 3 2 1 Template-Specific Tn/Genomic Sequence 1 2 3 No Sequence 3 2 A Template-Independent Genomic Sequence 2

  34. High Quality Sequence (cont’d) NNNNNNNNN ARB PRIMER Sequence

  35. Trouble Shooting: Buried ARB Sequence NNNNNNNNN ARB PRIMER Sequence High Quality Sequence

  36. Relevant Background Sequence: Buried ARB Primer Sequence 1 3 2 1 1 2 2 3 2 1 1 1 2 2 +

  37. Library Construction:Time Line for 4608 colonies (48 sup plates) Time 3 days 2 days 1 day 10 days ? 16+ days Mutagenesis/growth on Qbot plate Qbot picking/growth in 96 well culture plate Biomek ARB1/ARB2 Reactions/PCR Cleanup/Seq prep Sequencing Total For 7 sets of 48 plates: 114 days

  38. P. aeruginosa PA14 Virulence-Related Factors Involved in Mammalian Pathogenesis Identified in Non-Vertebrate Hosts Category # Genes Regulators 6 gacA, gacS, algU, plcR, ptsP, lasR Membrane Protein 1 aefA Biosynthetic Enzymes 3 phzB, hrpM, fabF Modifying Enzyme 1 dsbA Multi-Drug Transport 2 mexA, mtrR Type III Secretion 1 pscD Helicases 2 phoL, lhr Unknown Proteins 16 ?

  39. Section IV Development of a Linux MySQL Uni-Gene Library Relational Database

  40. Unigene Library: Overview of Bioinformatics Catalog each sample in relational database Retrieve DNA sequence for each sample Process DNA sequence to remove low-quality and contaminant sequences (i.e. - vector) • BLAST searches to distinguish: • Pseudomonas sequence vs. contaminants. • PA01 vs. PA14 sequences. • BLAST searches to identify: • Disrupted ORF. • Coding sequence vs. putative promoter disruption.

  41. What will the MySQL Database Do? • Store/catalog all of the data. • Process DNA sequences and perform BLAST searches. • Display the results and allow for user queries.

  42. How will the Database Store the Data? • The data will be stored in a relational database. • Individual tables can be thought of as separate Excel spreadsheets with rows and columns. • The tables are connected to each other via specified relationships.

  43. How will the Database Store the Data? • Tables will be populated (i.e. - individual cells in the table will be filled with entries) as plates, samples, and/or data are generated. • Data entry into the Database will be “restricted” to parallel the creation of the physical library. • Order of different types of inputs is restricted. • Prevent duplicate entries.

  44. How will the Database Store the Data? • The Database will store organizational information: • Date created. • Created by. • Storage locations. • Bacterial strain. • Mutagen/Transposon used. • The Database will store experimental data: • DNA sequences obtained by PCR. • Location of insertion with respect to PAO1 genome. • Identity of PAO1 ORF disrupted. • Phenotypic data?

  45. Plate ProcessPlateLink PlateID ExecutionID PlateType PlateID InOrOut ProcessExecution ExecutionID ProcessType

  46. Plate ProcessPlateLink ProcessExecution PlateID ExecutionID ExecutionID PlateType PlateID ProcessType InOrOut Protocol PlateSample Mutant RawSequence MutID SampleID RawSeqID PlateID Library MutantID Well Position ChromatPath MutantID Sequence

  47. Chromatogram Phred Raw Sequence Quality Scores Trimmed Sequence How will the Database Analyze the Data?

  48. Processed Sequence Trimmed Sequence How will the Database Analyze the Data? Remove transposon, vector, and/or other contaminant sequences. BLAST PAO1 genome BLAST PAO1 annotated ORFs

  49. How will the Database Analyze the Data? • Other BLAST searches that can be performed in the future: • Internal BLAST against the contents of the database to identify siblings vs. adjacent independent insertions. • BLAST against other public databases to determine gene identity of ORFs not found in PAO1.

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