Newcastle University Drylab/19 May 2008

Mark
Carried out the Blast analysis of the different agrC groups. There are very small differences between the agrC protein sequences in Staphylococcus aureus, however the differences are much greater between Staphylococcus aureus species and other Staph species, namely epidermis and haemolyticus. As a result the agrC protein could well be used as a receptor for the agrD receptor proteins.

The alignment for agrD contains group I, III and IV agrD peptides. The alignment for the sensory protein in agrC contains three peptides from agrC and two from Staphylococcus haemolyticus and Staphylococcus epidermis. The differences mentioned above are documented.

Have started looking at Listeria monocytogenes. It is a gram-positive human pathogenic bacterium and the cause of listeriosis a serious infection characterized by high mortality rates in immunocompromised individuals and pregnant women. It is often involved in food poisoning and although rare results in a mortality rate of over 25% compared to Salmonella which only has a mortality rate of 1%. The bacteria uses a similar two-component system to Staphylococcus aureus for its quorum sensing signalling system, the agr system.

I am now going to blast the genomic sequence data I have found on the agr system for Listeria. The results for the Listeria agrC protein are promising as it is distincly different to any agrC present in any other species (including importantly Staphylococcus aureus). The result is similar for the agrD protein. The results are listed below:

I am now moving on to look at the neural network training data, and to incorporate some noise into the network. I want to use multiple instances and inputs to map to a single output, and see how the network trains the data. Using the Emergent software I created 8 inputs, 25 hidden layer nodes and mapped it all to a single output. As specified the data was extremely noisy as the graphical output showed. I specified first 10 batches, and then 50 batches each to run through until the error reached zero. This enables the demonstration of network learning. As the network learns, the length of time and the number of epoch required to run through the data to reach zero is significantly reduced, even in a network filled with noisy data.

Megan
Continue looking into biological concept (in particular S. pneumoniae)

Morgan
Switched over to some user-friendliness stuff after being frustrated at the deletion button. Rr! Got the status bar to repaint when the message is updated. Looking into tooltips too, because of WB Todo build #17.

While I'm at it, I might as well write down my thoughts.

I have an identifier for each part on the drawing panel, because while there is only 1 gfp protein (THERE IS ONLY ONE), there may be multiple instances of such, the Drawing Identifier (DID). I need to also represent them in the truth table in the behaviour panel. So the name of the instance has to be unique on the drawing panel, and then the name in the truth table can be linked back to the instance, which can be linked back to the part by the separate Part Identifier(PID) (provided to me by the Parts/Constraints repositories).

Right now, the palette is generated by the Parts Repository as an ordinary JTree. The nodes that can be dragged are PaletteTreeNodes extending DefaultTreeNode, which are special purely because they also store the general type of part they are (promoter, etc). In the future, theoretically this will maybe be the PID, which can be used to look up the type of part they are and therefore define the icon used.

In ElementTransferHandler, the PaletteTreeNodes are turned into Elements, which are the primary drawing type. Elements store the type of part, and the position on the drawing panel, the connectivity, the PID, and the DID, which is generated based on the human-readable name of the part. Numbers are appended based on whether the named part already exists in the DrawingPanel. In the future, they will also be human-modifiable.

The Elements are then passed on to the DrawingPanel (DP), which takes them in and turns them into DrawingElements. The reason for this transformation is so that the same basic graph (List) can be shared across multiple DrawingPanels. DrawingElement is a wrapper for Element, but it also allows the Drawing Panel to set the border and the color of the element, coloring it differently for different DP's. Like, for the Build panel and the Behaviour panel.

Nina
Today I will be working backwards to identify gram-positive bacteria that have well characterized quorum sensing systems (QSS). This should be a more efficient way of finding a suitable peptide.

List of Bacteria with well characterized QSS

Streptococcus pneumoniae - currently being looked at by Megan

Streptoccoccus mutans and gordonii - cause dental plaque and sub-acute endocarditis. Possibly not severe enough for us to use?

 Bacillus subtillis  - not pathogenic

 Lactococcus lactis  - not pathogenic. Used in dairy products.

Staphylococcus aureus - currently being looked at by Mark

 Pseudomonas aeruginosa  - Gram-negative

 Carnobacterium piscicola  - not pathogenic but releases a bacteriocin inhibiting QSS of Listeria monocytogene (approved and already looked at by Mark).

 Yersinia enterocoliticia  - Gram negative!!

 Lactobacillus sake  - not pathogenic (used in fermented sausages) Note to self... a lot of gram-negative well characterized QSS..annoying. What if I focus search to only G+ve disease causing bacteria? Another note to self... I cannot consider any of the bacteria which solely adopt the LuxS QSS (such as Clostridium difficile) since autoinducer emitted is the same for many bacteria and would not serve as a suitable protein to target. (Lerat et al., 2004).

Streptococcus pyogenes- myositis, toxic shock syndrome, puerperal fever, pharyngitis, cellulitis, rhematic fever etc..

Streptococcus agalactiae - important human pathogen..meningistis, pneumonia, sepsis and major cause of infections in new borns.

Bacillus cereus - Food pathogen particularly in rice. Has a Plc-PapR quorum sensing system.

Conclusion

Bacillus cereus, Streptococcus agalactiae and Streptococcus pyogenes all serve as extra pathogenic bacteria which we can detect in addition to ''Staph. aureus, Streptococcus pneumoniae and Listeria monocytogene''. They all have very well characterized quorum sensing systems and peptides which we can detect.