What Can You Learn from Watching Single Molecules?
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NobeliumChemistryMedical historyMoleculeController (control theory)Lecture/ConferenceMeeting/Interview
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ChemistryNobeliumMoleculeBiophysicsInositolphosphat-Synthase <myo-Inositol-1-phosphat-Synthase>Emission spectrumMotion (physics)Cell (biology)Polycyclische AromatenBase (chemistry)SpectroscopyMethyl iodidePhysical chemistryExplosionMedical historyAreaBase (chemistry)Intergranular corrosionCell (biology)MoleculeLecture/ConferenceComputer animation
00:58
NobeliumMortality rateInsulinMoleculeVakuumverpackungQuantum chemistryLecture/Conference
01:24
Quantum chemistryMoleculeElectronAtomNobeliumAdamantaneMoleculeElectronAtomSense DistrictNobeliumLecture/Conference
02:03
MoleculeSpectroscopyEmission spectrumLebensmittelfarbstoffLoamMoleculeEmission spectrumMeatHost (biology)StereoselectivityConjugated systemIce frontSpectroscopyQuartzZunderbeständigkeitAbsorption spectroscopyCryogenicsÜbergangszustandLecture/ConferenceComputer animation
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LebensmittelfarbstoffEmission spectrumSpectroscopyMoleculeFreies MolekülDeath by burningElectronOrigin of replicationActive siteZunderbeständigkeitHost (biology)CryogenicsWhitewaterColourantSpectral lineBearing (mechanical)Emission spectrumHomogeneous (chemistry)FunnelLecture/Conference
03:53
LebensmittelfarbstoffMoleculeEmission spectrumWhitewaterSpectroscopyFreies MolekülInflammationNobeliumOrigin of replicationElectronMoleculeGlättung <Oberflächenbehandlung>Emission spectrumZunderbeständigkeitSeafloor spreadingComputer animationLecture/Conference
04:20
Plasminogen human-AktivatorMoleculeEmission spectrumÜbergangszustandSpectroscopyFreies MolekülLebensmittelfarbstoffGlättung <Oberflächenbehandlung>WhitewaterUraniumPhysical chemistryZunderbeständigkeitEmission spectrumChemical structurePenicillinSpectroscopyResonance (chemistry)MoleculeWalkingFunnelComputer animationLecture/Conference
05:14
NobeliumFluorescencePenicillinMoleculeCryogenicsWalkingLecture/Conference
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FluorescenceEmission spectrumMolekulardynamikHost (biology)MoleculeEnzymkinetikMoleculeSystemic therapyResonance (chemistry)Sea levelCrystallographic defectQuartzFluorescenceSingulettzustandController (control theory)CryogenicsMolekulardynamik
06:45
U.S. Securities and Exchange CommissionEmission spectrumEnzymkinetikFluorescenceMolekulardynamikHost (biology)MoleculeLocus (genetics)Mineral explorationGreen fluorescent proteinSchmidt reactionProteinIon transporterResonance (chemistry)LactitolCryogenicsMoleculeBase (chemistry)Mineral explorationController (control theory)WalkingMolekulardynamikProteinFluorescenceMuscle relaxantIsotopenmarkierung
07:47
Green fluorescent proteinSchmidt reactionOrganisches MolekülProteinMoleculeIon transporterFluorescenceProteinCell (biology)NucleotideOligonucleotideMoleculeStuffingLecture/ConferenceComputer animation
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Green fluorescent proteinOrganisches MolekülProteinMoleculeIon transporterSchmidt reactionInfiltrationsanästhesieCell (biology)Major histocompatibility complexFluorescenceMoleculeCryogenicsStereoselectivitySea levelCell membraneLipideIsotopenmarkierungCholesterolGreen fluorescent proteinCell (biology)Spontaneous combustionOctane ratingWalkingLecture/ConferenceMeeting/Interview
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FluorescenceNana (manga)Green fluorescent proteinEmission spectrumMoleculeBlue cheeseGreen fluorescent proteinController (control theory)ChromophorPatentGenotypeProteinComputer animation
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NobeliumNobeliumIce frontMoleculePhysical chemistrySymptomLecture/Conference
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Inclusion (mineral)Nondestructive testingIcing (food)Serum (blood)NobeliumCell (biology)ProteinToughnessLecture/Conference
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Wine tasting descriptorsWine tasting descriptorsChemical structureProteinIsotopenmarkierungGreen fluorescent proteinLecture/Conference
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WalkingSunscreenWine tasting descriptors
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IngredientFreies MolekülMoleculeSeafloor spreadingMoleculeFunctional groupLecture/Conference
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IngredientMoleculeFreies MolekülNobeliumConcentrateDipol <1,3->Reaction mechanismFunctional groupSense DistrictFluorescenceIsotopenmarkierungController (control theory)ChemistryChemical structureMoleculeWursthülleEmission spectrumActivity (UML)
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IngredientMoleculeFreies MolekülMalerfarbeSolutionReaction mechanismConcentrateBranch (computer science)Controller (control theory)Reaction mechanismMoleculeReducing agentGreen fluorescent proteinChemical structureActivity (UML)ChemistrySample (material)Body weightMeat analogueIonenbindungLecture/ConferenceMeeting/InterviewComputer animation
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Methyl iodideMoleculeChemical structureReaction mechanismEmission spectrumLecture/Conference
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Chemical structurePermacultureBioavailabilityCell (biology)Wine tasting descriptorsGesundheitsstörungProteinPilot experimentChemical structureSpectrinAtomclusterInclusion (mineral)Einschlusskörper
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Chemical structureBioavailabilityPermacultureCell (biology)Optische AktivitätHelixBreed standardMoleculeChemical structureSurface scienceFunctional groupHelixSeafloor spreadingColourantNucleic acid double helixPhase (waves)
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NobeliumMoleculeMolekulardynamikSolutionLebensmittelfarbstoffCell (biology)PolymerGalactoseLocus (genetics)ThreonineBaker's yeastMoleculeFunctional groupSystemic therapyAnimal trappingMolekulardynamikSolutionBaker's yeastDipol <1,3->Locus (genetics)DNS-SyntheseCeratonia siliquaLecture/ConferenceComputer animation
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Locus (genetics)GalactoseBaker's yeastNondestructive testingGreen fluorescent proteinCell (biology)ChromatinMolekulardynamikLocus (genetics)IsotopenmarkierungNucleic acid double helixGesundheitsstörungMoleculeGeneChromatinMolekulardynamikCommon landOceanIon channelChemical structureLecture/Conference
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NobeliumLocus (genetics)Can (band)Chemical structureMoleculeMotion (physics)MolekulardynamikMolecular beamSurface scienceStuffingLecture/ConferenceMeeting/Interview
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IsotopenmarkierungMolekulardynamikSolutionMoleculeElectrical mobilityEmission spectrumMolekulardynamikAnimal trappingPotenz <Homöopathie>Surface scienceSolutionElectrical mobilityEmission spectrumMoleculeEnzymkinetikWine tasting descriptorsElectronic cigarette
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MolekulardynamikMoleculeEmission spectrumIsotopenmarkierungSolutionElectrical mobilityMoleculeAnimal trappingSet (abstract data type)Multiprotein complexComputer animation
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MolekulardynamikMoleculeEmission spectrumIsotopenmarkierungSolutionElectrical mobilityThylakoidNobeliumProcess (computing)PigmentThermoformingPhotosynthesisProteinOligomereHerzfrequenzvariabilitätAnimal trappingMoleculeCHARGE syndromeComputer animation
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MoleculeMolekulardynamikSolutionEmission spectrumIsotopenmarkierungElectrical mobilityPigmentDNS-SyntheseOligomereMoleculeDNS-SyntheseHybridisierung <Chemie>HexamereSense DistrictProcess (computing)CHARGE syndromeWalkingMachinabilityBasenpaarungAmount of substanceElectrical mobilityBinding energyAnimal trapping
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Electric currentPolyethylenterephthalatePhantom <Medizin>GasolineNobeliumMethyl iodideMoleculeMemory-EffektMoleculeAmount of substanceLecture/ConferenceComputer animation
Transcript: English(auto-generated)
00:14
Well, thank you very much for the introduction. It's a great pleasure to be here. And what I'd like to do today is to briefly describe
00:21
the history of single molecule optical studies, especially imaging and photo control, and then talk about some of the neat things you can do with single molecules, in addition to the ones that were just described, very beautifully by Stefan Hell. So let's look at a real quick roadmap. Really, I'm talking about a story of physical chemistry, ultra-sensitive detection, and industrial basic research.
00:44
Some years ago, three decades ago, having unexpected effects, spanning a number of areas of science. So this will involve sort of telling you a little bit about that early history, and then talk about super resolution with single molecules and cells. Also talk about what else we can learn from single molecules by themselves.
01:04
So what I would like for you to do now is to turn your mind back to the middle of the 1980s, when there was beautiful work going on to look at single ions in vacuum. That was very inspiring to me. The question was, can we see single molecules? But there was a bit of a problem.
01:22
Erwin Schrodinger, one of the great founders of quantum mechanics, said in 1952 that we never experiment with just one electron or atom or small molecule. So this is a bit of a problem. A lot of people thought it was impossible to detect a single molecule. And what this really means for you today, I just want to give you a little signpost that helps you remember what you want to think about this.
01:44
Beware when Nobel laureates say something cannot be done. In the sense that almost all the things that he said that could not be done have been done, single atoms, single electrons, and even now single molecules. So it's a great sort of incentive to prove these people wrong.
02:03
Nevertheless, to explain how the earlier experiments were done, we have to look a little bit at spectroscopy of molecules. Let's think of this molecule, terilene, in a transparent host crystal of peritrophinol. And because of its conjugation, it has an optical absorption in the visible. So here's an absorption spectrum
02:21
and on the wavelength scale here. It's broad due to vibrations and so on. So let's cool it now to low temperatures. So this was the thing that we were thinking about back in the 60s, 70s, and 80s and so on. You cooled this to low temperatures, flipped the axis in the other direction, and this first electronic transition now seems to have four copies because it's become so narrow
02:42
that the individual positions in the host lattice, there's four different inequivalent sites, so you see four different origins, electronic origins. So notice now here the scale is getting far narrower in wavelength space or frequency space, whatever units you like. Now, so thinking about these kinds
03:01
of optical absorption lines at low temperatures, let's think about just one of these for a moment. It turns out that when I was at IBM in the middle of the 1980s, we were trying to use that kind of absorption line for optical storage. The idea was to store data in the color of the wavelength at which a spectral hole was written.
03:21
It turns out it's an inhomogeneously broadened line, and you can make marks in that inhomogeneous line. In various ways that I can't really describe quickly here, I'll just tell you that you can do it at low temperatures. And working at this great industrial research lab, it was a very wonderful environment because not only were we looking at this technology,
03:40
we could also ask questions about its fundamental limits, what will be the signal to noise and so on. So asking one of those questions kind of led to the first experiment. So it sounds a little bit esoteric, but bear with me for a moment. Here's that same spectrum I just showed you, okay, that electronic origin of absorption for nalpenicine in paratrofenol,
04:00
a different molecule but related, similar. It's about one wave number or 30,000 megahertz in width. And the question that we asked, is this completely smooth? Is this just a smooth Gaussian spectrum? Let's spread it out, look at the peak of it, spread it out in a much, much finer frequency scale and see what's there. And so in 1987, we did that experiment and we found this.
04:23
Oh, you say that's just some noise. No, this is not noise. This is actually repeatable spectral structure. You measure it one time and measure it again and you see the same lumpity dump, okay, across the spectrum. And now the scale is just a few hundred megahertz. Okay, this was 30,000 megahertz. So what's really exciting about this
04:42
is that it hadn't been seen and it is a spectral structure that's coming directly from the discreteness of the molecular absorption. Scales is the square root of the number of molecules in resonance. And this, because we observed this, we then realized a key point that it's possible to detect a single molecule
05:00
because we only have to work the square root of n times harder. So that's what happened in 1989 with Lothar Khador. We used a laser frequency modulation spectroscopy and detected the absorption from a single molecule of penicillin and periturfennel. It's this structure right here in the middle. And then a year later, a very important additional step occurred from Michel Orie in France.
05:22
He also detected the absorption of a single molecule of penicillin and periturfennel, but he did it by detecting the emitted fluorescence. And that method is actually, gives you a little bit better signal to noise and it's what we all use today. So the low temperature single molecule regime began. And in the 90s, many amazing things were observed.
05:42
Here's a few surprises that occurred. I'm just gonna show you now some spectra that are repetitive, the same spectral region, and you see a single molecule absorption there measured by fluorescence. And it's doing something crazy. It's jumping around. It's moving in frequency space, even at 1.2 degrees Kelvin, even in a crystal.
06:00
And we were excited and surprised because you're in a new regime and in fact, it's fairly reasonable to believe you might see certain surprises. And this turns out to be due to host dynamics, that the two level systems in the crystal due to some defects were actually causing the changes in the local environment, which shifted the molecule back and forth.
06:22
And if you just set the laser at a fixed frequency, you see then the molecule will be in resonance and out of resonance, in resonance and out of resonance due to the effect that I just showed you here. And so the molecules were blinking way back there in the very first experiments in the early 90s, 1991. Now, another surprise occurred.
06:41
You could also, for a different molecule here, demonstration, we can look at a single molecule multiple times and then bring the laser into resonance and it disappears. That means it goes somewhere else in frequency space. Wait a little bit, comes back to the same frequency. Then you can drive it away again, comes back. So we also saw optical control of these molecules
07:00
at low temperatures. So those two things, blinking optical control, you can just keep into your mind, but the important point here is that even in this industrial research environment, when you can explore fundamental basic science, surprises can occur and important discoveries. Moreover, since we started detecting single molecules, we were in this wonderful regime
07:21
where we peeled back the ensemble average. We didn't have to always measure millions or billions of molecules at the same time. We can measure them one by one and ask if there's any hidden heterogeneity and also watch their individual dynamics, their individual time-dependent state changes. Then the field jumped to room temperature in the mid-90s with important steps by many pioneers
07:43
and it was shown very quickly that you could detect single molecules at room temperature as well. We're still pumping a molecule from a ground state to an excited state and after relaxation, collecting this emitted fluorescence. These one nanometer objects were being used as labels. You can imagine attaching them to a protein of interest
08:01
or an oligo or nucleotide and looking at it in a cell if you like. And just remember how the experiments are done at room temperature. Effectively, we focus a laser down to a diffraction-limited spot, so it can't be smaller than lambda over two NA as Stefan pointed out. But if you dilute the molecules, you make them be far enough apart,
08:21
then you would pump only one and the emitted light, assuming backgrounds are well-controlled, is coming from that single molecule. Notice how different this room temperature experiment is from the low temperature where we had spectral selectivity to distinguish the different molecules. And so this early work at room temperatures
08:41
was very exciting as well. Here's an example from a cell problem where these are single molecules in the membrane of the cell. And what are they doing? They're dancing around, all right? This is just a regular movie at regular rates, regular frame rates, and I still love it even though it's very old. You can see them moving, okay? So that's being affected by cholesterol
09:01
and the lipids in the membrane. Lots of beautiful science can come from measuring the positions. You see them also turning off. That's the photobleaching effect, a single-step photobleaching, proving they're single molecules. You also might even see some of them coming back on at different times. So all of those features kind of are characteristic of the wonderful things we can do now
09:20
with these sort of ultimate emitters at the single-molecule level. So now also in the 90s, 1997 in particular, we decided to prove or find out if we could detect a single copy of green fluorescent protein because that was so important in terms of a label in the biological community,
09:41
pioneered by Roger Chen and Chalfie and Shimomura and others that you heard about yesterday. And this experiment involved looking at a mutant that was at a slightly better wavelength just for technical reasons. And indeed, Rob Dixon in my lab was able to see single copies of GFP. But it's a new regime again.
10:01
This GFP mutant was not only visible, it also blinked. That is, it would be on, on, on, on and then off and then on and then off in a wonderful random pattern which is saying that we're collecting emitted light but sometimes the molecule will go into a dark state and then can come back spontaneously and start emitting again due to changes in the local environment
10:22
and the chromophore and so on. But we also found that you could radiate the molecules for an even longer time and they would essentially stop completely but a little bit of blue light could turn them on again from a long-lived dark state. So you could restore the molecules from a dark state. Again, blinking and photo control were around
10:42
and available. And this became a sort of an industry of experts on mutations created much, much better switchable fluorescent proteins and so on. Now, note at the time though, notice there's a patent listed here. We thought this was gonna be interesting for optical storage because I came from IBM at that time.
11:02
People were thinking about storing data but just the ability of having this ultimate object to turn on and off was, you know, fascinating from the very beginning. So another little signpost, when you're exploring a new regime, it's important to remember you cannot predict in advance if there are surprises that are going to occur. And this is why we have to have
11:20
basic fundamental science. These may seem esoteric at first but in fact later those new things that were surprises could lead to unexpected and planned applications. So that's gonna be the story of super resolution with single molecules for the Nobel Prize. But before I talk about that, let me just point out and ask you this particularly strange question
11:41
since you think I may be going crazy here at this time. What is almost as good as being picked for a Nobel Prize? So you can ask yourself, what is he talking about? Well, you know, marrying my wife, my first child, those sort of things are way up there. But, and then here's a Nobel Prize just below that and then just below that, what would you have?
12:03
Well, for me the answer is being picked by Milhouse on The Simpsons. So believe it or not, in 2010, 26 September 2010, four years before the Nobel Prize, episode one, season 22, you can look it up but don't do it now. Here's the story, the family,
12:22
the Simpsons are waking up in the middle of the night and they're saying, ugh, why do we have to get up so early and so on? And they drag into the living room, sit on the couch in front of the TV and Homer Simpson says, because we gotta watch the Nobel Prize announcements. So they have a betting pool, and here's the betting pool, here's the different people, okay,
12:41
the different family members, here's physics, chemistry, economics, and so on, and right here in the middle is my name. So, this is wonderful, right?
13:01
But notes, notes, these people are really good. Here's Ben Ferenga, okay? They picked him too. Here's Bing Tolbstrom, here's the economics winner. So they got three in this one little bingo card, so to speak. Anyway, of course the Nobel Prize is talking about
13:23
circumventing the optical diffraction limit by various techniques, and Stefan talked about sted and other beautiful schemes, but let's just think about it from sort of the biologist's point of view. Here's a cell, a bacterial cell, really small, and inside it there's many proteins that have been labeled, one particular class of proteins
13:41
labeled with a fluorescent protein, and so you know you can't see any structure if you just buy the most expensive microscope, conventional microscope, that is, you just see this big blurry image, that's because the individual emitters, even though they're so tiny, they look larger, and according to the Abe diffraction limit, pointed out in the late 1800s.
14:02
So the point of super resolution microscopy is that you can take this image and turn it into that image. That's a big step, okay? Even though this is only a factor of five, so to speak, it's a huge step. It's not 15%, 50%, or a factor of two or whatever. This happens to be a factor of five, and there's also factors of 10 and so on.
14:21
It's a huge jump, and it's very exciting, but it's also technically important that we look closely at all of the techniques that we use to make sure that there's full validation of every image. But anyway, I think you all know roughly how this works, because Stefan already introduced it. But the key points that I wanna mention,
14:42
we've got this point spread function, this spot from a single molecule, kind of like a mountain, and you basically walk up to the top of the mountain and read the coordinates, okay, using your GPS. But we really do that by taking advantage of the fact that there's a shape to the spot, and we use that shape and fit the,
15:02
spread out on multiple pixels of a detector, and fit it to find the position of an estimator function, like a Gaussian function. Now this is an estimation problem, and there's all sorts of interesting mathematics that can be used to describe how well it's done, and so on, so that's just one of the issues that we think about, and we've actually invented some ways
15:24
to make sure that even if the molecule has a dipole emission pattern, that it will not cause any error in the position if you use proper filtering, optical filtering of the light. But the other key requirement is this active control of the emitting concentration.
15:40
I like to sort of state it that way in a chemical sense. We have to use some method that makes sure that the emitting concentration is very small in any frame. And so in the case of trying to see a detailed structure like this, fluorescent labels are attached. If you let them all emit at the same time, you just get the blurry fuzzball,
16:01
but if you use this a switching mechanism or an on-off control mechanism, blinking or photoactivation or other mechanisms, then you can make sure using these mechanisms to push all the molecules into a dark state except a few so that only a few are visible in the image, and then you can fit each one of them
16:20
and find their positions. You can't control a specific molecule, but you can only force the average concentration to be low. And it randomly, later, if you do it again, you'll get different molecules on randomly, and this random sampling eventually gives you lots of samples on the structure which will give you the super-resolution information.
16:42
So this is the PALM idea that Eric Betzig talked about first in April 2006. All these other acronyms appeared later, STORM, F-PALM, PAINT, D-STORM, GSDEM, BLINK, and so on, wonderful acronyms, but they're all talking about different mechanisms for controlling the molecules. And so there's beautiful chemistry here,
17:02
photochemistry, how to make sure the molecules have fully dark states or quite dark states, and we tend to be able to do that. You can break bonds, you can do lots of interesting things, but you can also drive molecules into various dark states that are available due to, let's say, reduction mechanisms.
17:20
So we used that YFP, yellow fluorescent protein photo control, to demonstrate this, but left off the acronym on that paper. So of course, you know, that's not a good idea, right? You always gotta have an acronym. So to rectify that problem, here's one that's mechanism-independent, single molecule active control microscopy, or SMACM.
17:43
Okay, good, see, there's still some by your way. But now, suppose you wanna explain this to your grandmother or something like that. How can you explain this thing? Well, here's a way to do it. Think about fireflies. Imagine, and here's the story,
18:00
it's an approximate analogy, not perfect. You wanna see the branches of a tree at night, and it's dark, you can't see the branches of the tree. So what you'd like to do is to have a way to find out where they are, so you can place fireflies all along the branches of the tree. Just place fireflies all along the branches. And then you just watch what happens and take a movie.
18:21
And so they will be, the fireflies come on randomly and slowly at different positions. Each time one is on, you see where it is on your little camera and measure exactly where it is. And this works even if things are a little bit fuzzy or if there's a little bit of fog or things like that. But nevertheless, you get all these positions from the blinking fireflies, and then you just show them all at once
18:41
and you see the whole structure. So maybe that helps explain to some broader audience. And doing this with molecules looks just like that almost. Here's a cell, here's the single molecules in a single frame. This is using the on-off blinking mechanisms of de-storm, storm, and so on. And there's little tiny white spots on this side
19:01
that you may not be able to see, but they're the positions of all those molecules. The next frame of the movie, since they're blinking, different ones are on. More spots, more spots, more spots. And then of course, if you look at the whole movie, then the beautiful structure at high resolution appears beyond the diffraction limit. So not too different from those fireflies.
19:22
And of course, the method has been applied to a huge number of situations. So I can't possibly review all of that. Here's a few examples out of hundreds. Here's this beautiful banding pattern in axons of spectrin and also actin, seen by the Zhuang lab. Here's fascinating clusters of this Brouche pilot protein
19:42
in the synaptic active zone. Here's the Huntington aggregates that are part of the source of Huntington's disease. Not only big inclusion bodies, but very tiny little fibrils below the diffraction limit. And here's the bacteria thing again. Now we're looking at the structure of the stalk,
20:01
which is below the diffraction limit, and looking at the surface. I just want to say that there's lots of ways to apply this in bacteria, because they're already close to the diffraction limit. So it's like a new world of being able to see new shapes, structures, and other things inside the bacteria. What else can we do with these single molecules?
20:20
Well, since we have them as emitters in a microscope, we can also play with the light inside the microscope. And one way to play is to change the behavior of the microscope, change the fundamental response of the microscope to a point emitter, from just being a single point of light on the camera to let's say, how about two spots on the camera?
20:41
But if you do that in a certain way, those two spots actually revolve around one another, depending upon the z position of the emitter. This is called the double helix point spread function that came out of work in the Piston Lab, which we recognized we could use for 3D and with single molecules.
21:02
So the double helix point spread function, you can see why we call it a double helix if you think about it along the z-axis. It's like a double helix. But that's not the only point spread function. In fact, there's a raft of new ones. My students have been so creative, a corkscrew, a bisected, a quadrated. These are all produced by a phase mask
21:23
that's placed inside the microscope in the Fourier plane, a transmissive phase mask, a tetrapod, and so on. But even using the double helix in two colors and so on, now you get three-dimensional images that lets you see structures inside as well as reference structures outside and so on.
21:40
This business of playing with the light from molecules is really electromagnetic fields and it's sort of quite beautiful. And in particular, you can do really crazy things. You can even make a single emitter look like a happy face. So here's that. Here's a few single emitters, all right? And there's no phase mask, nothing changing the response to the microscope.
22:02
But if you turn on this phase mask designed by Matt Lu, then you see each one is a happy face and as you move them up and down in Z on the other side of focus, unhappy face. All right, so lots of fun with single molecules. But what else can you do? Well, remember these little ultimate emitters?
22:21
Well, you can just watch them move or change color, spectra, or orientation using measurements of the dipole orientation and do that in many interesting systems or you can trap them in solution using a feedback technique and watch their dynamics as they change as a function of time. So let's just quick examples of these two.
22:42
Here's one. This is from Mikael Backlund who actually is in the audience. The problem here is to look at DNA loci in yeast. So in yeast, you can, for example, label the gal locus with a red emitter and the other copy of the gal locus with a green emitter and then do two color double helix.
23:01
So here's the green channel, here's the red channel, and you can see that these two lobes are turning because those molecules are moving in X, Y, and Z. That's what happens when you see the two lobes turn. And so that leads to beautiful data that provides nice time dependence of relative motions of interesting objects under different conditions.
23:23
Here, the problem was to see what happens when you activate or deactivate this gene and again, without the details. The correlations between these two locations were higher in the repressed condition of this particular gene. And there was also a great deal
23:41
of global chromatin dynamics, which you can see with your eyes, the fluctuations in the positions. So that's one example of tracking which can be used in many contexts. So please remember, if you're trying to measure a detailed structure, it takes some time to do that but by the single molecule methods. STED methods can be somewhat faster but since it takes a little time,
24:02
make sure you're using a static structure. You're observing something that's not changing too much if you wanna get the details of a structure. But if you just go to this single emitter limit or a single molecule limit, then you can watch motions essentially as fast as you can get photons out of the molecule.
24:20
Great. And it's very exciting, by the way, to see these new schemes from Stefan where he's also using these patterned pumping beams to get much more information from those single molecules and observe them faster. But what about other kinds of dynamics and what about molecules that don't like to be tied down on a surface
24:41
but they may have fascinating dynamics. So we've been using this new device called the AbleTrap, an anti-brownian electric kinetic trap for some years. And really it's a microfluidic device where you wanna watch a single molecule in solution but you keep it in the middle of the trap using electrokinetic forces,
25:02
voltages that are applied at some distance away and if you change the direction of these forces in response to the brownian kicks of the molecule, then you can keep it in the middle for a long time. And while you're doing this, you can measure the brightness, how many photons per second, lifetime, excited state lifetimes, spectrum of the molecule, polarization or anisotropy of the molecule.
25:23
You can measure even diffusion coefficients in some new work and the mobility of the molecule without allowing it to diffuse. So fascinating new developments and these last two were enabled by another person in the audience, Trinh Hoang. One of the things that Trinh did in his work,
25:42
not just measuring D and mu but showed the power of this multivariate measurement of the single molecule behaviors. So let me explain what I'm showing here. Remember I trapped a molecule in this special trap and for every molecule that comes into the trap, we can measure all these parameters. What's its brightness? What's its polarization?
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What's its spectrum? What's its lifetime? And so these single black spots correspond to one molecule that had come through the trap. All the other spots come from all the other molecules that have subsequently later come through the trap. So we observe very quickly that there's a whole set of states of a complex molecule like this.
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This is a monomer of a antenna protein from photosynthesis and you see that there are different forms corresponding to behaviors of the different pigments and in fact photobleaching or quenching processes that get turned on in the various pigments. So multiple variables let you figure out what's going on
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with the molecule in the trap as it changes with time. This business of measuring D and mu also can be used for other fascinating studies. Here's measuring the size and charge of molecules. This happens to be a trimeric aloficosyanin molecule and if you just have trimers,
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then their D and mu measurements scatter around this little region. But if you have trimers that can fall apart into monomers, you see both the pairs of D and mu that correspond to the trimer as well as the monomer. So this is on the fly, calling whether a molecule is a trimer or a monomer. And you can imagine using this to look at oligomer distributions
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in an equilibrium sort of situation or one that you might even have perturbed. This is just because measuring two variables, mu and D, do a much better job of allowing you to distinguish between these different oligomers. And then another thing you can do is sense charges and diffusion coefficient changes.
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Here's using the same idea to sense single DNA hybridization and binding, unbinding events. Because if you have DNA getting ready to hybridize, single strands becoming a double strand, then when they combine, they'll be larger, so D will be lower, but they have more charges, so mu will be higher. D and mu are anti-correlated
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and you can see this beautiful data from Tranagan, from this AbleTrap machine. So I think there's still lots to do with single molecules. It just depends upon your ingenuity and your ideas about new things to do with them. So let me end with a few quick lessons for you and your friends. Of course, you wanna find your passion
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and we're very happy if science is your passion. But it's very essential, right, because you have to be determined, persistent, and methodical, always applying the scientific method, always looking for validation, always making sure that what you report is really correct. That's essential for our field. Keep your eyes open for surprises. Always do that. If something behaves strangely,
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well, make sure you're not making a mistake, of course. But then if it's really strange and you're sure it's right, it could be a great discovery. Failure happens a lot. Experiments don't work all the time. That's a great opportunity to learn something. Think of it that way, always as a learning experience. What is it that I didn't quite know that caused this to fail? And then that's much more of a positive step.
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And of course, we're always asking how things work, but I want you to encourage your daughters and sons and family members and so on to keep asking how things work throughout your life. We have such fascinating things in our world today, and people sort of use this supercomputer that's in your pocket and think nothing about how it really works.
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So this, of course, requires us to push beyond conventional wisdom. And finally, science provides this rational and predictive way to understand our world. In the times of anti-science and so forth, various threats to science, we study science and believe in it, in a sense, because we know it can be predictive.
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It can tell you what's gonna happen next. And that's essential to understand our world and our future. I wanna thank my past students and so on and all these agencies that support our work. And of course, we're the guacamole team, right? One molecule is one guacamole, one over avocados number of moles.
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So thank you very much for your attention.