Effect of sequence level mutations on transcription, translation, and noise

One of the main biological questions explored when DNA sequencing first became a practical laboratory technique was how the nucletides in a gene's promoter and ribosomal binding site define the gene's interactions with transcription factors and the ribosome translation apparatus. At least in prokaryotes, these interactions largely determine the levels of transcript and protein available for each gene, and thus provide the crucial information of how a genome regulates itself.

This early work resulted in many of the promoter analysis tools that are still widely used today. In particular, the promoters were often analyzed in terms of information content, and this information content was visualized using sequence logos. These sequence logos are still the most popular way to display DNA binding sites. I'm not sure why this field tappered off a little. My guess is that the people in this field had maxed out the information that was affordably obtainable with the available technologies.

But as most biotech loving biologists know, the times are a changin in biotech, and we have new sequencing technologies that enable drastically larger sequencing studies to be undertaken. Importantly, we are faced with several quite-different sequencing methods (unlike the previous era in sequencing biotech which was almost exclusively driven by ABI's advances in Sanger sequencing). I think with these new technologies coming online, it's time we dusted off our promoters and start figuring out how they work.

What we still must learn about promoters

For several promoters (ideally for all promoters), we need to exhaustively determine how base-pair changes in the promoter lead to changes in the amount of transcription and translation. We must determine this information across time, so we can also determine the rates of transcription and translation. Finally, we must determine these values at the level of single-cells, so that we can also obtain information about the noise inherent in each promoter sequence.

In the early 90s, these type of analyses were at least partially undertaken with populations of cells and 100-200 promoter mutations. Now we must study several promoters, with millions of different mutations for each promoter, and with multiple single-cell replicates of each mutation so we can estimate noise.

What is this new level of promoter knowledge good for?

We need to understand to what extent it is possible to build a computational model to predict translation and transcription from sequence alone. Such a model could act like a molecular biologist's version of Hardy-Weinberg equilibrium. That is if a promoter does not fit the model, it would suggest that there is some additional regulation (e.g. small RNA) that is not explained by the binding of transcription factors and the ribosome. In addition, the ability to screen vast numbers of promoter variants could be of huge value to forward biological engineering. Synthetic biologists often tune their human created networks using directed evolution. While directed evolution is a very powerful and massively parallel way to optimize a genetic system, the human that created the system in the first place has limited control over the final result. For example, it may be that the network evolved to generate ethanol from cellulose is extremely noise and could be made more efficient by fine-tuning the promoters in a more intelligent design.

An idea for a massively parallel method to determine the effect of sequence level mutations on transcription, translation, and noise

I think the tools are already available to determine the effect of sequence level mutations on transcription, translation, and noise in single-cells. One approach I've thought about is shown in the figure on the right (click to see an easier to read/print pdf version of the figure). The idea takes a cell-in-emulsion approach (see Directed evolution of polymerase function by compartmentalized self-replication) and combines it with the polony sequencing method pioneered in the Church lab (see Accurate multiplex polony sequencing of an evolved bacterial genome).

The first step (top right) is to synthesize a known promoter with a large number of random nucleotides. This is very similar to the method used by Stormo's lab many years ago (see Quantitative analysis of ribosome binding sites in E.coli), except that with modern sequencing methods we can drastically increase the number of random sites that we explore. A GFP reporter is placed directly after the promoter so that we can measure the amount of protein generated. Since, the vast majority of mutations will probably result in little to no expression, it may be useful to also add a bactericidal antibiotic resistance gene after the GFP to provide an easy way to get rid of unproductive promoters (for some studies, you would probably not want to remove these low output promoters).

The second step (top left) is to take a dynal bead and attach a primer to amplify the promoter, a second primer to amplify the GFP sequence, and an anti-GFP antibody.

Next the bead and the bacteria a placed together into an emulsion. In the emulsion solution, we also need to include reverse primers for the promoter and GFP sequence, reverse transcriptase, and PCR reagents. You would need to mess around a little with the dilutions and concentrations of beads and cells to maximize the case where you have only one bead and one cell in each emulsion.

Now we have the cells isolated into separate chambers, and we have one bead with the bacteria. This bead will provide the source of our future information read out. Also remember that by synthesizing our promoters with N's, we actually have generated a huge library of different promoters. So that each emulsion will have a different variant of our promoter. We then lyse the cells. I'm not sure of the best way to lyse the cell. But in the figure, I just assumed we used extreme heat. Because of the next step, it may be wise to use a gentler method to lyse them, such as placing a protein that will cause cell lysis (e.g. lysozyme or ccdB) on a promoter that is heat inducible, so you'd only need to heat the cells up to 42C rather than 95C. Once the cells are lysed, the GFP expressed from the synthetic promoter should diffuse around the emulsion until they meet and bind the antiGFP attached to our dynal bead.

We've got the protein on our bead, now we need to attach the DNA. Since one of the things we want to measure is transcript concentration which is mRNA, we need to do a reverse transcription reaction. Reverse transcriptase is not very heat stable, which is why I stressed above that we might want to lyse our cells more gently than by heating them to 95C. However, Superscript III from Invitrogen is pretty heat stable, so that might be worth a shot too. Since we include a reverse primer to our GFP sequence into the emulsion, we should have a fairly specific reverse transcription.

Finally, we need to attach the DNA to our bead, we can do so by running a multiplex PCR reaction for a few cycles. Since the forward primers are on the dynal bead, the PCR reaction results in the DNA being stuck to the bead.

And now for the fun part, let's measure protein concentration, transcript concentration, and determine the promoter sequence for our single cells (bottom row of the figure). To do this we lay our beads out on a microscope slide or some type of microfluidic device. We can measure the protein concentration directly as GFP fluorescence. Next we measure the transcript concentration as the amount of GFP cDNA attached to the bead. For increased accuracy, we might want to measure this concentration using cycled PCR reactions (like qPCR on a microscope). The concentration of the promoter sequence and GFP sequence attached to the bead can be measured in each round using two different molecular beacons. The concentration of promoter sequence can be used to normalize the concentration of the transcript (i.e. to try and remove artifacts due to the variance in emulsion sizes, emulsion PCR efficiency, and to remove the background transcript value that is due to amplification from the DNA rather than cDNA sequence). This bead based DNA quantitation can borrow some ideas from the BEAMing method (see BEAMing: single-molecule PCR on microparticles in water-in-oil emulsions).
Now that we've measured protein concentration and transcript concentration, it is time to determine the promoter sequence responsible for these concentrations. In some ways, this is the most difficult step. But in practice, it may be the easiest step, as the polony sequencing method does exactly that.

With the size of the beads and the massively parallel nature of this protocol, it should be possible to have the same sequence appear multiple times, allowing the estimation of noise for the tested promoters.

Again, I haven't tried any of this stuff, and I'm not sure it'll work. I just wanted to throw the idea out there in case someone else is thinking about this problem too.

Open questions with this idea

1. how quantitative is emulsion PCR and how is noise influenced by the size of the emulsion
1. can we increase quantitative accuracy of our mRNA concentration by running very few emulsion cycles and then running a microscope based qPCR on our bead
   
2. how strongly does the GFP bind to our bead (e.g. when we break the emulsions, can GFP move from one bead to the next? we can test this by using mCherry in one sample, GFP in another, and then breaking the emulsions together to see if any beads have both proteins attached)
   
3. Is crowding on the bead going to cause problems; that bead has a lot on it. does this bias our results in unpredictable ways?
4. there are a lot of steps. long protocols can lead to excess experimenter derived error and slow the techniques adoption
   

Mutations, gene passing, and the evolution of gut microbes

The gut is a particularly interesting niche for evolution because things change there so rapidly. You eat a undercooked hamburger from a poorly butchered cow and all of a sudden your intestine is full of E. coli O157:H7, you've got the worst stomach ache of your life, and you have bloody diarrhea. But this doesn't just create an difficult life for you, this also causes a great deal of confusion for the bacteria that were happily living in your intestine. Before the O157:H7 invaders arrived, your normal intestine residents (i.e. your normal flora) were grabbing the food you didn't eat and passing on the some of the benefits to you. Now all of a sudden the flow rate through your intestine is much faster. Perhaps the normal flora are having trouble staying attached to your intestinal lining? A new food source, blood, has arrived from the E. coli O157:H7 that so rudely invaded your intestine. And most of your intestines normal residents are probably not optimized to eat blood.

Now let's assume you were misdiagnosed and the doctor gave you antibiotics to get rid of the new E. coli O157:H7 residents in your intestine (unfortunately, the current best treatment for O157:H7 is to wait a week or two for it to go away). Now, the bacteria in your intestine are being bombarded by these antibiotic chemicals that kill off most of them.

So how do bacteria survive, and often thrive, in such a complicated environment?

1. they are tiny so lots of them can live in a small space; their large number allows for diversity; and diversity is largely why they survive drastic changes in their environment - only a few diverse individuals of a particular species need to survive each in order for the species to remain a resident of the normal flora
   
2. the different species trade DNA in the gut; this means that if one type of bacteria in the gut develops resistance to a particular antibiotic, another type of bacteria can develop resistance more easily, because they can just obtain the important piece of DNA from the bacteria that already figured out how to survive

Point 1 above deals with mutations and selective pressure. Point 2, the gene-exchanging idea, deals with a phenomenon called horizontal gene transfer. However, it's not clear how often any of these things happen, or if they occur more often in some situations than others (e.g. is there more horizontal gene transfer when there is a strong selecting force like an antibiotic). Mutations and selective pressure has been studied for quite a while in the lab (see the NY Times article "Fast-Reproducing Microbes Provide a Window on Natural Selection") with pretty interesting results. But I think its time we moved these evolution studies into more complicated environments like the gut. We also need to further explore the extent to which horizontal gene transfer plays a role in these organisms' survival and adaptation, because previous studies (as far as I know) have focused more on the mutations in cultures of a single bacteria put under some sort of selective pressure.

Here's what I propose:

Inoculate a gnotobiotic mouse with N species of bacteria (probably make N = low = 2-4; also make the species diverse: one Firmicute, one Bacteroidetes, and one Archaea). You should probably place things under selective pressure to push the organisms in different directions. For example, give the mouse diets that have few of the nutrients necessary for the gut residents, or add one antibiotic resistant strain of bacteria and give the mouse a weak but constant dose of the antibiotic (to see how long / if the bacteria horizontally pass on the gene).

Now pass on the microbial residents to new mice (either the children of the inoculated mouse or another germ-free mouse; both would be interesting). This passing could be done by mixing a little feces in their food, but it would probably just happen naturally if you put them in the same cage for a few days. Now at set times in each mouse's life take a feces sample to be sequenced at a later date (might as well delay sequencing as long as possible, since the stuff gets so much cheaper with time). Then sequence the frozen samples to see the extent of the mutations and gene transfers over time and in different selective environments and genetic backgrounds of mice. The sequencing will also show how the proportions of the normal flora change over time.

The problem with this experiment is that it would take several years of work, and you'd always need to be careful to pass on the flora before the mouse died. But according to that NYTimes article I linked to above, most of the action in the single-species studies occurred at the beginning, so even the early results might yield some interesting insights into gut ecology and evolution.

Live imaging of host-microbe interactions

Two photon excitation microscopy allows imaging of living tissue up to a depth of one millimeter. Karel Svoboda has used this to amazing effect to study neurons in mice. I wonder if it would be possible to apply a similar approach to study host-microbe interactions in real time. The idea would be to create a few strains of fluorescently labeled bacteria (or make a fusion protein or U. Alon style fluorescent promoter of a key protein or two) and watch them interact in real time with the gut of a mouse after you feed or inject the mouse with different drugs.

Questions:

1. how thick is the intestinal lining (i.e. is it greater than 1mm?)
2. how easy it is to do surgery on the mouse to get to the intestine?
3. how easy is it to sew the mouse back up and have sorta a ready-access flap into the intestine like Svoboda does with the mouse neurons?
4. how much will it alter the physiology of the mouse to have an open wound near the intestine?

2-photon links



Update Dec 2, 2007
Jost Enninga, Philippe Sansonetti and Regis Tournebize wrote an excellent review that covers this idea and much more (as is always the case, this idea has already be worked on to some extent, though never in the context of an intestine as far as I know).

Roundtrip explorations of bacterial infection: from single cells to the entire host and back.
Trends in Microbiology, Nov 2007
doi:10.1016/j.tim.2007.10.006

Do microbes directly sense host hormones?

Microbes have been living inside vertebrates for a long time now. They and their hosts are constantly interacting. I think it is not clear however on how many scales they interact. For sure the host has things an acidic stomach and bile secretions (which is like a detergent) to keep the microbe populations from growing outta control. The innate immune system also has plenty of peptides that have antimicrobial properties. For every host combatant action, there
must be a subsequent microbe response for the microbe to survive (e.g. E. coli can export detergent-like bile molecules to survive in intestine). But is it known if bacteria can respond to general non-combatant host properties like the presence of hormones circulating about?

For sure if you have a big boast in adrenaline the bacteria populations will be stimulated, but this could occur simply as a side effect to the host's response to the hormone. I want to know if bacteria can directly sense any hormones. What about leptin? Work in Gordon lab at WashU suggests that low leptin might send a signal to the microbiota to become more efficient at extracting calories from food. I'd like to know if this or any other hormonal signals are directly sensed by the microbial community.

Could try running microarrays of microbes in the presence/absence of different hormones.

(see Nature News & Views article "Obesity and gut flora", Bajzer M and Seeley RJ and the two articles from the Gordon lab in the same issue "An obesity-associated gut microbiome with increased capacity for energy harvest" and "Human gut microbes associated with obesity").