Field of Science

Planning the GTA work

My goal for the rest of my time in Andrew Lang's GTA lab  is to gather data that constrains estimates of the efficiency of GTA transduction.  I have lots of ideas but they're not very well organized, and I keep getting distracted by the minutiae of GTA biology (and our general ignorance of same).  So this post is an attempt to get a sensible plan written out.

The bottom line for efficiency is how many transductants are generated for each cell that produces GTA and then dies. This depends on many factors, so I'm going to try to break down the steps and evaluate their limitations.

Here are some of the questions I'd like to know the answers to.  (Some of these questions overlap with others, and some of them are addressed by data we already have.)

  1. How many functional GTA particles does a cell produce under 'normal' conditions?  
  2. Are lots of defective particles produced too?
  3. Do individual cells of 'overproducer' mutants produce more GTA particles than normal cells, or is overproduction due only to more cells being producers? 
  4. How stable are GTA particles in the cultures where they are produced?
  5. How stable are GTA particles in more dilute solutions?
  6. Do GTA particles bind to free capsule or to cell-envelope components released by lysed cells?
  7. Do cells in producer cultures bind the GTA particles produced by other cells and take up ands recombine their DNA? 
  8. How good are recipient cells at finding GTA particles when cells and particles are scarce?
  9. Do cells die if they are exposed to too high a concentration of GTA particles?
Experiments I'm going to do:
  1. Measure stability of GTA titers in culture filtrates stored at room temperature.
  2. Measure growth of wildtype and overproducer strains by plating dilutions and counting colonies, in addition to measuring culture density by its turbidity.  At the same time measure accumulation of GTA (see this post and this post).
  3. Compete an overproducer mutant against its isogenic parent during growth under GTA-producing conditions, to estimate the cost of GTA production.  This is especially important since my most recent growth curves don't show much difference between ovverproducer and wildtype strains.  This requires that one strain carry an antibiotic resistance marker the other lacks, so I'm using GTA to transfer a kanamycin-resistance marker from a derivative of the 'wildtype' strain into its overproducer sibling.  Then I can do the competition both ways, starting with the kanR overproducer at low frequency in a background of kanS wildtype cells, or starting with the kanR wildtype at low frequency in a background of kanS overproducer.  I have all these strains now (just confirming that the kanR overproducer does overproduce GTA), so I can start the experiment as soon as I grow up the cultures.  I should also Do a complete growthtiter the amounts fo GTA produced, since the goal is to get the ration of GTA produced to cells died.
  4. Do the same competitions, but between an overproducer and a no-GTA mutant, or between wildtype and no-GTA mutant
  5. Add marked GTA to a producer culture (to multiple different producer cultures) to see how efficiently the cells take up  GTA.  The producer strains are all rifR, so this needs a GTA prep carrying a different marker.  I've made a GTA filtrate that transduces kanR, but this transduction is very inefficient compared to rifR, no doubt partly because the kanR is a big insertion, not a point mutation.
  6. To get an independent antibiotic resistance point mutation, I've just started selecting for a spontaneous mutation giving resistance to streptomycin, by plating GTA-producer strains on streptomycin plates.  Mutations giving strR are common and this selection has been successful for R. capsulatus in the past.
  7. Do a GTA-producer time course analysis that distinguishes between GTA production and GTA accumulation.  Experiments to date have just assayed the amount of GTA in the culture at different times, and there are unexplained peculiarities about the results (see this post: http://rrresearch.fieldofscience.com/2018/06/summary-of-r-capsulatus-bioscreen.html)

Scheduling complication:  I'm here until August 12, but I'll be tied up with visitors for part of the time, next week and for the last two weeks of July.  Because R. capsulatus grows slowly, I need to wait two days to see the result of each experiment.  

I could do the first 'quick-and-dirty' version of the competition experiment now, starting the cell mixtures tomorrow (Friday) morning and growing them for only 24 or 48 hr, taking time point samples at t=0, t=24 and t=48 (Sunday morning).  Then I could count the colonies on Tuesday morning.  Will I also measure the amount of GTA in each mixture, by its ability to transduce rifR and kanR?

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