Tag Archives: GFP

FISEB 2014 meeting -day 1

FISEB meeting happens every three years, and it includes participants from 28 different experimental biology societies in Israel. It is the best meeting to learn about biological-medical research performed in Israel at all fields and doctrines.

4 days, 8-10 parallel sessions, hundreds of lectures, >1000 posters, >2200 participants.

The first day started by a plenary lecture by Aryeh Warshel, Nobel lauret. He is really far from my field, and his lecture was very much confusing to me. But he has nice cartoons :-) The bottom line – enzymes are able to catalyze reactions due to electrostatic connections that are maintained stable (unlike in water).

From the afternoon sessions, I chose “signaling pathways & networks”. Relevant to this blog:

Yoav Henis from Tel-Aviv Uni. talked about oligomerization of TGF-beta receptors. he used a method he calls “co-patching”, which is essentially IF with two different antibodies for two receptor subunits. homodimerization will yield single color “patch” whereas heterodimerization will yield an overlap of both colors (co-patch). He then looked at the % of co-patch with different receptor subunits with/without ligand, or with mutants.

Maya Schulinder from Weizmann Institute talked about the contacts between mitochondria and other organelles (ER, vacuole) in yeast. These contacts are important for lipid metabolism. She new about the mito-ER contact but found there must be a second contact (bypass mechanism). She used an interesting screen method to find the bypass mechanism to the mito-ER contact: she expressed one of the contact protein as a GFP fusion. She expected that if the bypass mechanism and the mito-ER contact “share the load” of lipid metabolism, then deletion of the bypass will increase the number of the mito-ER contacts to compensate. Using automation, she imaged 6200 deletion mutants (from the yeast deletion library) each expressing this GFP fusion. As expected, she found 4 candidates which turned out to be very interesting.

Roni Seger from Weizmann showed that targeting the nuclear localization signal of ERK can be a novel cure for certain pathologies, including certain types of cancer.

On the other hand, Maya Zigler from the Hebrew Uni. suggested another new idea to cure cancer – by inducing the surrounding immune cells to destroy the tumor.

Ido Amit from Weizmann as well told us that we may not really know all the different types of cells that exist. What most people do, particularly in immunology, is rely on one or two known “markers” and use FACS or other methods to sort the cells based on these markers. However, some of the markers overlap. and there may be cells for which we do not have any markers and they “disappear” in the crowd of unsorted cells. or, the could be further sub-types we do not know about. So he approached the problem in an unbiased way – he took all the cells in the spleen, and did single cell RNA seq to individual cells from the spleen. Thus, each cell type has several hundred/thousand “markers” based on gene expression profiles. Not only did this method agree with the common FACS sorting markers, but he identified several sub-types unknown before.  Expect his paper this month in Science. His paper just got published in Science.

Finally, Yaron Shav-tal from Bar-Ilan Uni. used the MS2 system to study how perturbing the signaling pathway of serum stimulation affects transcription of beta-actin gene. As per usual – very neat job and interesting results.

High res imaging of DNA double strand breaks: Clearing the nucleus or marking the spot

DNA can be damaged in many ways. Consequently, there are numerous mechanisms to repair it. It is a fascinating field full of innovative concepts (“DNA repair” was my favorite course during my undergrad studies).  Double strand breaks (DSBs) are considered the most genotoxic, which is why many DNA damaging drugs and treatments intended to treat cancer are intended to create DSBs. On the other hand, DSBs can lead to chromosome translocations which can promote cancer, and can actually be viewed as a hallmark of cancer cells. DSBs also occur naturally during recombination events at Meiosis, and are important intermediates in immune system development.

DSBs are recognized by repair complexes that act to mark and repair the damage. Though the sequence of event has been studied biochemically, knowledge on the in vivo temporal and spatial arrangement has been limited due to lack of good high-res methods to visualize DSBs and repair proteins at DBS sites.

Two papers recently published take two different approaches to get  high-resolution images of events at DSBs.

The first paper, from Stephen Jackson’s lab, implemented a simple method to reduce the background fluorescence in the nucleus, thus increasing the signal/noise ratio. They study the non-homologous end joining (NHEJ) process which initiates with the Ku complex recognizing the DSB, followed by recruitment of the DNA dependent protein kinase (DNA-PK) and ending with ligation by XRCC4. DNA-PK phosphorylates the histone H2AX near DSB (gamma-H2AX). This is a known marker for DSB.

They used laser illumination to create a streak of DSB, and immunofluorescence (IF) against gamma-H2AX and Ku. They used a buffer called CSK that is known to release soluble proteins, thus removing background. Though the gamma-H2AX appears as a clear streak, Ku is all over the nucleus. Ku is also an RNA binding protein. So they added an RNase to the CSK wash. Miraculously, only DNA-bound Ku was now visible.

Look at the image – it looks amazing!

Hi-res image of Ku at DSB

Addition of RNase to the CSK buffer during IF allows for high-resolution imaging of DNA repair proteins. Source: Britton et al (2013) JCB vol 202(3):579-595.

Using this simple upgrade to the protocol, which removed most of the background, and combined with 3D structured illumination (3D-SIM) super resolution microscopy*, they were able to study co-localization (here’s a video), measure distances and study composition of different components of the repair complex. They also used Ku foci count to asses the effect of different drugs on DSBs repair efficiency.

I found this paper important mostly because  this simple improvement in their protocol yielded a vast improvement in imaging. This technique could be useful for studying many other nuclear processes which involve proteins that associate with both DNA and RNA (e.g. transcription complexes).

The second paper, from Tom Misteli’s lab, took a very different approach. They wanted to see sites of chromosomal translocations  following DSBs. First, instead of getting random, or multiple DSBs using drugs, radiation or laser (as in Jackson’s paper), they introduced restriction sites for the rare-cutting IsceI restriction enzyme. One site, on chromosome 7, was surrounded by multiple repeats (256) of the LacO sequence. Other sites, on chromosomes 1 & 10, were surrounded by 96 TetO repeats. The LacO and TetO arrays can be viewed by fusion of GFP to the Lac repressor (which binds LacO) and mCherry to the Tet repressor which binds TetO. Thus, each potential DSB site is marked by a fluorescent array in distinct colors. Expression of ISceI enzyme from a plasmid induces DSB. They then followed the temporal position of the green and red spots, until they get co-localization of the colors – meaning chromosomal translocation has occurred.

Time-Lapse microscopy of cells after transfection with ISceI enzyme, showing the translocation of two distinct sites (marked by GFP and mCherry) into a co-localized spot. Source: Roukus et al. (2013) Science vol 341:660-664.

Time-Lapse microscopy of cells after transfection with ISceI enzyme, showing the translocation of two distinct sites (marked by GFP and mCherry) into a co-localized spot. Source: Roukus et al. (2013) Science vol 341:660-664.

Like in Jackson’s paper, they used this system to look at temporal and spatial events, including recruitment of proteins (tagged with a third color: BFP), and to study the effect of different mechanisms that perturb the DSB repair machinery.

In conclusion: both approaches yielded beautiful and informative images about DSBs behavior and repair. Jackson’s method has a more global and immediate application, since it can be used to study other nuclear processes. Misteli’s system requires a lot of “genetic engineering” but can provide a more precise temporal resolution (since it enables live-cell imaging, unlike Jackson’s modified IF which only uses fixed cells). Misteli’s method can also provide insight into specificity (studying DSBs at specific genomic locations). These arrays can also be used to study chromosome dynamics (i.e. movements within the nucleus, during cell division, or transport of specific genomic regions during transcription induction e.g. to the nuclear pore complex). I am actually using such an array myself, to mark the location of my gene of interest.

* 3D-SIM uses laser light that passes through an optical grating. A series of images created by these striped patterns, generated at high spatial frequency, can then be processed by a computer algorithm into a high resolution imaging. See ref. below for more details.

ResearchBlogging.orgBritton S, Coates J, & Jackson SP (2013). A new method for high-resolution imaging of Ku foci to decipher mechanisms of DNA double-strand break repair. The Journal of cell biology, 202 (3), 579-95 PMID: 23897892
Roukos V, Voss TC, Schmidt CK, Lee S, Wangsa D, & Misteli T (2013). Spatial dynamics of chromosome translocations in living cells. Science (New York, N.Y.), 341 (6146), 660-4 PMID: 23929981
Schermelleh L, Heintzmann R, & Leonhardt H (2010). A guide to super-resolution fluorescence microscopy. The Journal of cell biology, 190 (2), 165-75 PMID: 20643879

Green Fluorescent sushi

Fluorescent proteins have been isolated from invertebrate species only, until now.  A group of researchers from Japan isolated a green fluorescent protein from the freshwater eel called Unagi (yes, the same Unagi used for sushi).

The protein, named UnaG, is smaller than GFP (139 amino acids compared to 237 of GFP), excited at 498nm (after bilirubin binding) and emits light at 527nm.

UnaG is a green fluorescent protein found in eel muscle. Source: Kumagai et al. (2013) Cell 153(7):1602-1611

UnaG is a green fluorescent protein found in eel muscle. Source: Kumagai et al. (2013) Cell 153(7):1602-1611

UnaG, glows in green upon noncovalent binding to bilirubin - a membrane permeable heme metabolite.  This is a major advantage, since this mechanism can be utilized as a fluorescent switch: add bilirubin–> get fluorescence; remove bilirubin–>remove fluorescent.

This unique characteristic of UnaG prompted the researchers to develop a sensitive assay to measure bilirubin levels in blood serum – a known biomarker for several human diseases. Their assay sensitivity is 100-fold better than current clinical assays, they claim.

Another big advantage of this protein is that its fluorescence is independent of oxygen (unlike GFP-based FPs).  UnaG can therefore be used under anaerobic conditions.

UnaG fluorescence depends on bilirubin, but not on oxygen. Source: Kumagai et al. (2013) Cell 153(7):1602-1611

UnaG fluorescence depends on bilirubin, but not on oxygen. Source: Kumagai et al. (2013) Cell 153(7):1602-1611

The biological role of UnaG is still unknown, but it is suggested to have a function in oxidative stress.

I think that this is just the opening shot for the search for more vertebrate fluorescent proteins…

Read a research highlight from Nature Methods.

Unagi, from “Friends”:

ResearchBlogging.orgKumagai A, Ando R, Miyatake H, Greimel P, Kobayashi T, Hirabayashi Y, Shimogori T, & Miyawaki A (2013). A bilirubin-inducible fluorescent protein from eel muscle. Cell, 153 (7), 1602-11 PMID: 23768684

Cells reach out their “hands” to create new limbs

Communication between cells takes many forms. There could be communication by sending out microvesicles with important messages inside, by sending out free molecules (like hormones) or by special structures (e.g. synapses).

Sonic hedgehog (SHH) is a signaling protein that is important for the development of vertebrate limbs. It was thought to be release from a small group of cells at the posterior end of the limb bud, and is recognized by receptors on cells a long distance away.

Not this Sonic Hedgehog… (image taken from http://sonic.wikia.com)

A new paper publish in Nature from Maria Barna’s lab shows that SHH actually remains bound on the external side of the cells that produce it. The cells simply send very long thin protrusions (here named filopodia) that reach all the way to similar filopodia of the receiving cells.

I think that not only the story is very novel and interesting, but the images are very pretty.

Several “technical” issues:

In order to study the SHH signaling in live chick embryos, they designed a custom made live in ovo microscopy system: a temperature controlled plate; on it an egg container chamber, and an objective that is dipping into the yoke.

They show that standard fixation methods (e.g formaldehyde) destroy these filopodia. Also, a volume marker (in this case sfGFP) that just fills the cytoplasm does not give a strong enough signal to detect these filopodia (possibly since they are very thin, and packed with actin filaments  and other proteins, so there’s very little free volume left).

So, they used palmitoylated fluorescent proteins, pmeGFP (green) and pmKate2 (red) that target them to the plasma membrane. This enabled them to visualize these very thin and long filopodia. Here’s a video movie from their paper.

They use a variety of cytoskeletal proteins fused to EGFP or to mKate2 to learn about the structure of these filopodia. Their conclusion is that these structures contain only a specialized form of actin filaments.

They show beautifully that SHH (fused to EGFP) travels to the tip of these filopodia:

They used a split GFP technology to show that SHH is actually found on the outside of the cell membrane.  In split GFP, two fusion proteins are produced, each one is fused to “half” of a GFP protein (its not exactly half but let not go into that now). If the two fused proteins are in close proximity, the two halves associate to produce an GFP that fluoresce irreversibly. The two separate halves do no fluoresce. So one half was fused to SHH and the other was anchored to the extracellular leaflet of the plasma membrane, and when both were expressed, they got green fluorescence.

In total – a very nice and pretty paper.
ResearchBlogging.orgSanders TA, Llagostera E, & Barna M (2013). Specialized filopodia direct long-range transport of SHH during vertebrate tissue patterning. Nature, 497 (7451), 628-32 PMID: 23624372

New and improved – the next generation of GFP?

A new and improved green fluorescent protein, named mNeonGreen, was developed.

It was engineered from a Yellow fluorescent protein (LanYFP) that was isolated from the cephalochordate Branchiostoma lanceolatum. Therefore, LanYFP is genetically unrelated to the commonly used Aequorea victoria GFP.

LanYFP has a high quantum yield (0.95) and extinction coefficient (~150,000 M−1 cm−1) – making it a very bright protein.  LanYFP is a tetramer – not useful for most applications.

Directed evolution to make it a monomer produced the new, monomeric protein, mNeonGreen. The ex/em of mNeonGreen is slightly shifted to the yellow compared to EGFP (509/516 compared to 488/509), making it a better choice to separate from CFP emission.

Though slightly less brighter than its parent protein LanYFP, mNeonGFP is 2-3 times brighter than EGFP and actually brighter than most green & yellow proteins.

Another great advantage of this new protein is that is it fast folding – the authors claim it is <10 min at 37C. This is fairly close to the superfolder GFP.

It is also very photostable (comparable to EGFP), performs well as a fusion construct at N & C termini many tested proteins, performs 4-times better that EGFP in stochastic single-molecule superresolution imaging and is a better FRET partner (both as acceptor and donor) than other proteins.

mNeonGreen fused to histone H2B shows the different stages of the chromosomes during cell division. Source: Shaner et al., (2013) Nature Methods 10:407-409.

mNeonGreen fused to histone H2B shows the different stages of the chromosomes during cell division. Source: Shaner et al., (2013) Nature Methods 10:407-409.

In short, this may very well be the “next generation” of fluorescent proteins. It has all the good qualities, and seems to have none of the bad ones. It performs better than most, if not all fluorescent proteins in every tested parameter.

Only its name is rather plain. I would call it something like wonderGFP or GreenLantern (hey, it even has the Lan from the animal they developed it from).

(Update: see here for details on how to get your hands on this protein).

ResearchBlogging.orgShaner NC, Lambert GG, Chammas A, Ni Y, Cranfill PJ, Baird MA, Sell BR, Allen JR, Day RN, Israelsson M, Davidson MW, & Wang J (2013). A bright monomeric green fluorescent protein derived from Branchiostoma lanceolatum. Nature methods, 10, 407-409 PMID: 23524392

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.

ResearchBlogging.orgIizuka 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

Folding and maturation, or how to evolve your own GFP (part 1)

GFP is one of the most widely used proteins in research. Its usefulness has advanced our understanding of biology in huge leaps forward. One of the greatest advantages of GFP is that the chromophore is formed in an autocatalytyic manner, no need for an enzyme or cofactor assistance. All that is required is atmospheric oxygen.

GFP has sort of a barrel shape, with the chromophore inside. The chromophore is formed from residues serine 65 (S65), tyrosine 66 (Y66) and glycine 67 (G67). The process of creating the structure of the protein is called folding, whereas the process of creating the chromophore is termed maturation. Maturation occurs after the protein folds to near native conformation.

However, the natural, wild type, GFP is not the best tool. It is rather dim and not very stable at 37°C  (Since the jellyfish lives at low temperatures). Also, it matures rather slowly. Early on, a mutation was introduced, S65T, that increased the brightness of the GFP and also shifted its excitation peak (from a major peak at 395 and a minor at 475, to a single major peak at 488).  In vivo, it was shown that maturation of GFP-S65T takes 27 minutes (this was measured by expressing GFP in E. coli bacteria under anaerobic conditions, then supplementing the bacteria with O2. Therefore, they only measured the last few steps of the maturation process). EGFP, the most common variant used in research labs, contains a second mutation, F64L. This mutation stabilizes the protein at 37°C and was suggested to increase the maturation rate.

Over the years, GFP has been a subject for further “directed evolution” to achieve required traits like different colors, brightness, pH stability and photostability, oligomerization state, as well as folding and maturation.

Why do we care about folding and maturation?

Well, GFP is often fused to other proteins. In some cases, that protein is misfolding, or folding slowly. This can affect the folding of GFP. This is particularly true when expressing fused proteins in E. coli, where in many cases the ectopically expressed protein is aggregating in inclusion bodies. Since GFP itself has a slight tendency to dimerize, any aggregation of the fusion protein may amplify the dimerization of the GFP. Thus, it would be advantageous to have a better folding GFP, with a lower tendency to dimerize.

As to maturation, having a fast-maturing GFP would be very beneficial for studies of translation, or translation-coupled localization.  Because, if the GFP takes 20-30 minutes to mature after it is being translated, we cannot really say what happened and where was the GFP or any fused protein, in that time.

Our story begins in 1996, when the lab of Willem Stemmer tried to improve GFP by a technique called DNA shuffling. Their goal was to improve whole cell fluorescent in E. coli cells expressing GFP. After three cycles of DNA shuffling, and selection based on fluorescence intensity with UV excitation, they isolated a clone (named simply ‘GFP cycle 3’) which showed 45-fold increased fluorescence compared to the then commercial Clontech pGFP. However, the spectral characteristics were unchanged, and the maturation rate (T1/2 = 95min at 37°C in whole cells) also seemed unchanged).  Mutations found in GFP cycle 3 compared to their starting GFP showed that three hydrophobic amino acids were replaced by hydrophilic amino acids. Thus, the improved fluorescence is probably due to reduction in protein aggregation by the hydrophobic surfaces, and increased solubility of the GFP.

CHO cells expressing wt GFP (A) or GFP cycle 3 (B). Source: Crameri et al. (1996) Nat. Biotech. 14:315.

Ten years later, the superfolder GFP (sfGFP) was engineered by the lab of Geoffrey Waldo for the particular purpose of creating a protein with less tendency to misfold when fused to poorly folded proteins in E. coli.

How was this protein engineered?

They started with a folding reporter GFP  (frGFP) which contained the cycle 3 & EGFP mutations.

They fused frGFP to a poorly folding protein, H subunit ferritin, which is insoluble when expressed in E. coli. After several rounds of mutagenesis and screening for fluorescence, they obtained the highly fluorescent sfGFP which bears six new mutations.  Ferritin-sfGFP was found to be 50-fold more fluorescent than the starting fusion protein. When expressed alone, cells expressing sfGFP were twice as bright as with frGFP. Importantly, the excitation & emission spectra , QY and EC were similar in both proteins.

Measuring the folding rate was done by first denaturing the proteins with urea. Then washing the urea and measuring the time it takes the GFP variant to regain fluorescence.  This method actually measures folding and maturation and this should be taken into account. In any case, though both proteins showed 95% yield within 4 minutes, sfGFP showed a 3.5-fold faster initial rate. sfGFP also tolerated higher urea levels, and showed better fluorescence with a bunch of different fused proteins with different characteristics (expression level, solubility etc…).

fusion of frGFP or sfGFP to 18 differnt proteins shows sfGFP much brighter in all cases. 0.125s, 1s: exposure time. below the images of the bacteria are Western blot images of the fusion proteins. Source: Pedelacq et al. (2006). Nat. Biotech. 24(1):79

They found that the most contributing mutation to the folding  kinetics and stability is the S30R mutation. The change from an oxygen group (that forms a hydrogen bond with E17) to a positively charged side chain mediates an electrostatically charged network of the β-barrel which seems to create a global stability to the structure. A second mutation, Y39N, slightly changes the angle of the backbone, and allows a hydrogen bond with D36, further stabilizing the structure. The other four mutations slightly contribute to the stability.

Although sfGFP seems to fold fast (though no comparison to EGFP was made in this paper), the assays here did not really differentiate folding from maturation.

A year later, the group of David Liu used sfGFP  in an effort to create a new GFP protein that is highly soluble. In order to do that, they replaced multiple neutral amino acids on the outer side of the protein with either positively or negatively charged amino acids to produce super-charged GFP variants GFP(+36) and GFP(-30) [compared to the net charge of sfGFP which is (-7) or GFP which is (-8)]. This scGFP was highly soluble, and also highly resistant to denaturing, even by boiling to protein at 100°C. The spectral characteristics of the scGFPs remained similar to those of GFP and sfGFP indicating that the structure of the outside “barrel” does not affect the chromophore features inside the barrel.

In 2008, Fisher & DeLisa produced yet another variant of GFP called superfast GFP. By exploiting the cell’s protein secretion quality control mechanisms, they screened for new super folding variants. The secretion mechanism exports unfolded proteins to the periplasm of E. coli. In the periplasm, GFP is apparently non-fluorescent. If the protein folds fast enough, the quality control mechanism prevents its export and the protein remains in the cytoplasm.  Their starting GFP was GFPmut2, a variant that was previously optimized for FACS analysis, harboring the mutations S65A/V68L/S72A. Following several round of selection, they isolated a clone which they named superfast GFP. Based on their analysis (using guanidinium chloride (GdnCl) to unfold the proteins and then diluting the GdnCl to refold the proteins, the T1/2 for superfast GFP refolding (resumed fluorescence) was 11 minutes, compared to 33 min (GFPmut2), 20min (sfGFP) and 73min (frGFP).

Graph showing folding of GFP proteins over time. black: square – frGFP; circle – sfGFP; triangle – GFPmut2. open circle – superfast GFP; triangle, square – two other mutants. Source: Fisher AC & DeLisa MP. (2008). PLoS One. 3(6):e2351.

So, far we discussed fast folding GFP proteins. However, the methods to measure folding of these proteins do not discriminate folding from maturation.  Furthermore, the in vitro results do not necessarily represent the in vivo folding rates (i.e. 11 min in vitro does not mean 11 min in vivo).

In the next post I will discuss the issue of maturation.

ResearchBlogging.orgCrameri A, Whitehorn EA, Tate E, & Stemmer WP (1996). Improved green fluorescent protein by molecular evolution using DNA shuffling. Nature biotechnology, 14 (3), 315-9 PMID: 9630892
Pédelacq JD, Cabantous S, Tran T, Terwilliger TC, & Waldo GS (2006). Engineering and characterization of a superfolder green fluorescent protein. Nature biotechnology, 24 (1), 79-88 PMID: 16369541
Lawrence MS, Phillips KJ, & Liu DR (2007). Supercharging proteins can impart unusual resilience. Journal of the American Chemical Society, 129 (33), 10110-2 PMID: 17665911
Fisher AC, & DeLisa MP (2008). Laboratory evolution of fast-folding green fluorescent protein using secretory pathway quality control. PloS one, 3 (6) PMID: 18545653