Zrusso Biol 368 week 11

From OpenWetWare
Revision as of 16:59, 9 November 2011 by Zeb Russo (talk | contribs) (→‎Outline)
Jump to navigationJump to search

Journal Club Prep

[Microarray Data]

[Journal Article]

Unknown Terms

  1. Mode of Action - The individual steps and processes by which a drug works. [1]
  2. Cationic - Of or relating to an ion or group of ions having a positive charge and characteristically moving toward the negative electrode in electrolysis. [2]
  3. Morbidity - a state of injury, sickness or disease. [3]
  4. Putative - Commonly believed or deemed to be the case; accepted by supposition rather than as a result of proof. [4]
  5. Tropoelastin - A water-soluble molecule with a molecular weight of approximately 72,000 daltons. Multiple tropoelastin molecules covalently bind together with crosslinks to form the protein elastin. [5]
  6. Stimulon - In cell biology a stimulon is a collection of genes (which may be in operons and regulons) under regulation by the same stimulus. [6]
  7. Attenuate - Reduce the force, effect, or value of [7]
  8. Anabolism - The synthesis in living organisms of more complex substances (e.g., living tissue) from simpler ones together with the storage of energy [8]
  9. Canonical - conforming to orthodox or recognized rules. [9]
  10. Antiporter - An antiporter (also called exchanger or counter-transporter) is an integral membrane protein which is involved in secondary active transport of two or more different molecules or ions (i.e. solutes) across a phospholipid membrane such as the plasma membrane in opposite directions. [10]

Outline

  • Background
    • Methicillin Resistant Staphylococcus aureus (MRSA) is a major cause of morbidity and mortality
      • strains resistant to existing treatments continually emerge and community-associated MRSA is a major global problem
      • development of new and unique prevention and treatment strategies is very important
    • Antimicrobial peptides (AMPs) are a potential source of new and unique antibiotics that may be developed to combat resistant bacteria such as MRSA
      • Almost all living creatures as part of their innate defenses produce AMPs and over 800 have been described
      • Ranalexin is a cationic 20 amino acid peptide that has potent activity against Gram-positive bacteria in vitro, particularly Staphylococcus aureus, so offers therapeutic potential against staphylococcal infections, including MRSA.
    • Transcriptome and proteome profiling offers powerful new approach for studying antimicrobial inhibitory action due to the fact that they reflect modulation of particular cellular functions, and provide a signature of the type of stress imposed
      • Transcriptome and proteome were integrated with a functional association network that modeled 95% of all pathways for MRSA-252
    • Twenty-two novel MRSA virulence factors and novel complementary killing mechanisms for the antimicrobial peptide ranalexin, including effects at the cell wall as well as evidence supporting involvement of the VraRS two-component system in cationic peptide resistance and FtsH was proposed as a candidate drug target, and a role was inferred for PhoU-mediated persister formation in S. aureus drug tolerance were discovered
  • Results & Discussion
    • Ranalexin elicits significant changes in transcript and protein levels
    • 20 μg/ml was discovered to be a sublethal concentration of ranalexin that impaired but not abolished growth of MRSA-252
    • Microarrays identified 95 upregulated and 105 downregulated genes (>two-fold difference, p<0.05)
    • iTRAQ LC-MS/MS with ProQuant identified 56 upregulated and 15 downregulated genes (>two-fold difference, p<0.05)
    • No inconsistencies observed between transcriptome and proteome
    • overlap in Gene Ontology (GO) annotation was observed but very little direct overlap at gene level which is not uncommon for transcriptome and proteome integration
      • GO-based functional profiling identified 290 significantly (p<0.05) enriched terms which shows complexity of effect of Ranalexin on MRSA-252
    • Figure 1 shows MRSA growth in sublethal Ranalexin concentration compared to control as well as colony counts
    • Functional association network was built to give a model of global gene function
      • contained information from GO annotations, STRING scores, KEGG pathways
      • final network contained 2,494 genes and 19,076 connections
      • false positive rate (FPR) no greater than 3%, which is similar to estimated value of functional association prior (4.7%) which indicates that a significant fraction of the false positives may be genuine functional relationships previously undiscovered.
      • node pair degree connectivity and network degree and clustering coefficients show a hierarchical structure with modularity.
        • normal protein interaction networks are far less modular, this networks more closely resembles a metabolic network
      • network was clustered into 597 putative functional modules using MCL algorithm
        • transcriptome and proteome profiles were mapped onto the network and checked for significance
      • eleven modules were found to be enriched in genes that displayed significant differences in expression in MRSA-252 cultures exposed to Ranalexin.
        • 5 upregulated and 6 downregulated
        • 58 genes outside these hubs were classified as intermodular hubs which link subnetworks and are putatively important regulators of the system
      • Figure 2 shows the normalized probability of network degree pairs.
        • the darker the area, the more likely the connection between two genes isn’t random
        • lower left is genes with few connections, upper right is genes with many connections
      • Table 1 is a list of all the modules that showed a response to Ranalexin
        • ’+’ indicate upregulation and ‘-‘ indicate down regulation
        • fraction in the ‘altered gene set’ column indicates number of genes that were altered in a module and the remaining genes that were unaltered in the module
        • unaltered genes seen in ‘additional genes’ column’
      • Downregulated genes impacted virulence
        • all 6 ESAT-6 secretion system components which are central to MRSA pathogenicity, were downregulated
          • 5 of these genes were in a highly significant module with the sixth sharing connections with 10/12 genes in the module
          • two other uncharacterized genes also downregulated and analysis found them to be related to membrane permease and virulence associated families.
          • the seven other genes in this module fits a predicted operon structure and so may be co-regulated with the ESAT-6 system
        • two other downregulated modules were associated with high-affinity metal ion transport, which is crucial for establishment of infection
        • another module contained 12 genes annotated with virulence functions and largely implicated in colonizationand immune-modulation. All 16 genes in this module were known or predicted to encode cell wall anchored or transmembrane proteins
        • a fully downregulated module of 3 genes was completely uncharacterized but only connected to ESAT-6 as seen in Figure 3
        • Prediction of additional virulence factors was done by mapping GO term ‘pathogenesis’ onto network.
        • Above analysis indicates Ranalexin restricts S. aureus MRSA-252 pathogenicity, including the ESAT-6 system, and inferred twenty-two novel virulence factors.
      • Figure 3 shows ESAT-6 module as well as the new genes discovered to share in ESAT-6
      • Table 2 shows all the modules that are believed to be significant in virulence
        • all these were not upregulated with Ranalexin, underlined ID’s were downregulated and those in bold are possible new virulence factors

Powerpoint Presentation

Links for Biol 368

Biol 368 Homepage

Zeb Russo's Homepage

Class Journals

Class Journal Week 1

Class Journal Week 2

Class Journal Week 3

Class Journal Week 4

Class Journal Week 5

Class Journal Week 6

Class Journal Week 7

Class Journal Week 8

Class Journal Week 9

Class Journal Week 10

Class Journal Week 11

Class Journal Week 12

Class Journal Week 14

Weekly Journals

Week 2 Journal Entry

Week 3 Journal Entry

Week 4 Journal Entry

Week 5 Journal Entry

Week 6 Journal Entry

Week 7 Journal Entry

Week 8 Journal Entry

Week 9 Journal Entry

Week 10 Journal Entry

Week 11 Journal Entry

Week 12 Journal Entry

Week 14 Journal Entry

Assignment Pages

BIOL368/F11:Week 7

BIOL368/F11:Week 8

BIOL368/F11:Week 9

BIOL368/F11:Week 10

BIOL368/F11:Week 11

BIOL368/F11:Week 12

BIOL368/F11:Week 14