Design guidlines for tandem fluorescent timers

Almost 4 years ago, I wrote a post on tandem fluorescent timers (tFTs). The idea is to have two different fluorescent proteins fused together to the protein of interest. In the paper from 4 years ago, it was superfolder GFP (sfGFP) and mCherry. sfGFP matures very fast (within minutes) and mCherry  matures more slowly (t1/2 ~40min). The ratio beween green to red fluorescent signal indicates the percentage of new vs old proteins, thus acts as a “timer”.  This latests paper on tFTs from the same group of Michael Knop’s lab, found that analyzing tFTs might be more complicated due to some possible problems of this system.

Folding and maturation, or how to evolve your own GFP (part 2)

In part 1 I discussed the directed evolution of fast-folding GFPs. These were developed for specific purposes of improving the solubility, stability and folding of the protein. Now, I will discuss the maturation step and how it was measured for a variety of GFPs.

As mentioned in the first part, maturation is the final step in the transformation of GFP from a chain of amino acids to a fluorescent protein – the creation of the chromofore. The chromofore has a very long name (p-hydroxybenzylideneimidazolidone) which in wild type  GFP is formed from amino acids S65, Y66 and G67. In this process, the amide nitrogen of G67 backbone performs a nucleophilic attack on the carbonyl carbon of S65. Oxidation with atmospheric O₂ and dehydration reactions create the imidazolinone ring, which is conjugated to the side chain of Y66.

In most papers that measure GFP maturation, the authors do not distinguish folding from maturation. In many cases, the experiments involve complete denaturation of the protein in vitro (e.g. by urea or guanidinium chloride) and then measuring fluorescence following re-folding. In vivo, it would be difficult to assess folding kinetics (because you do not really have an exact time zero for when the protein is being translated).  [In our lab, we are trying to develop a system to visualize translation in vivo in real time by imaging techniques.  If it works, it would be useful for determining exact folding & maturation rates in vivo of a single fluorescent protein].

In any case, it is easier to measure the kinetics of the maturation step, both in vivo and in vitro, simply by removing and adding oxygen. I mentioned in part 1 that this is how the maturation rate of GFP-S65 was calculated in vivo.  A new paper from 2011 from the lab of Funatsu analyzed the maturation rates of several GFPs in vitro. Their idea was simple – using a commercial kit, the performed in vitro transcription-translation reaction of the FPs at anaerobic conditions (they added catalase and glucose oxidase to get 0.1mg/l of oxygen). They then stopped the reaction and added oxygen, then followed fluorescence.

The proteins they assayed were: wild-type GFP, GFP-S65T, GFP-S65T/S147P, EGFP, sfGFP, Emerald, GFPm, GFPmut2, GFPmut3, sgGFP, “cycle 3”(a.k.a GFPuv), frGFP (a.k.a GFPuv3), GFPuv4 and 5 and two yellow FPs: EYFP and Venus..

Their results are interesting. As expected, the S65T mutation improved the maturation rate by 3.2 fold. However, EGFP matured only 20% faster than the S65T alone. The S65T/S147P is a variant that is stable under a range of temperatures. This mutant matured faster than EGFP, at a rate 40% faster than S65T alone. GFPmut2 and GFPmut3 (S65G/S72A) both showed a 7-fold faster maturation than WT GFP (>2-fold the S65T alone). sgGFP (SuperGloGFP, F64L/S65C/I167T, from Qbiogene) showed improved maturation rate compared to S65T (70%  faster).  Emerald, which contains 4 mutations on top of the EGFP mutations showed only a slight increase in maturation rate (similar to S65T/S147P). “cycle 3” was only slightly better than WT GFP, frGFP (which is cycle 3 +EGFP mutations combined) showed a maturation rate which was 10% less than EGFP.  Addition of the I167T mutation to create GFPuv5 increased the maturation rate by ~70% (just like in sgGFP).

Most interesting is the super-folder GFP (sfGFP), which showed a maturation rate of only 2.3-fold over the WT (that is ~70% of that of S65T). Thus, though this protein may be more stable and may fold very fast compared to other variants, the important step of maturation is the slowest among all variants tested (except the WT). Since folding assays measure fluorescence as the output for a mature protein, it means that the folding step (prior to maturation) is much faster than previously appreciated.

GFPm is a weird case.  GFPm, developed by David Tirrell, is a variant with mutations from cycle 3 and GFPmut3. However, Tirrell tried something unique –  to replace the leucines in the protein with 5,5,5- tri-fluoroleucine (tfl). The fluoreinated form proved to be insoluble, and fluorescent of the cells (E. coli) was 500-fold less than the regular protein. They then went on with mutagenesis, developing new variants which were brighter (up to 650-fold over GFPm). Personally, I do not understand how this can be of much use, since using tfl will probably have major effects on every aspect of cell biology we are interested in. Anyway, the maturation rate of GFPm (not fluoreinated) is itself pretty high – almost 3-fold over S65T and is actually the fastest maturing GFP variant tested. Oddly, they do not discuss this result anywhere in the text. Perhaps there is a technical issue they wanted to avoid?

Last but not least, the two YFPs showed maturation rates which are similar to WT GFP (Venus) or ~2.3-fold better (EYFP).

So how does all this information help us?

First, if we know which mutations enhance maturation and which slow it down, we can design faster-maturing proteins.

Second, we can use this data to estimate translation or translocation rates in vivo. However, we should remember that the data obtained in vitro (at 37C) does not neccessarily agree with actual maturation rates in vivo in every cell type. for instance, yeast or fly grow in colder temperatures which may affect maturation. Oxygen levels in tissue culture dish are differnt than in entire animals, and also differnt in differnt organs.  Also, if the GFP is fused to another protein, it may also affect folding as we learned in part 1, as well as maturation. Finally, the in vitro environment in the tube lacks many biomolecules (proteins other than used for translation, small molecules, ions, oxidizing molecules, antioxidants etc) which can affect oxygen availability in the immediate environment of the newly translated GFP.

Third, we can use such data to design cool experiments. So… stay tuned for part 3, which I will dedicate to biological timers.

Iizuka R, Yamagishi-Shirasaki M, & Funatsu T (2011). Kinetic study of de novo chromophore maturation of fluorescent proteins. Analytical biochemistry, 414 (2), 173-8 PMID: 21459075
Yoo TH, Link AJ, & Tirrell DA (2007). Evolution of a fluorinated green fluorescent protein. Proceedings of the National Academy of Sciences of the United States of America, 104 (35), 13887-90 PMID: 17717085