Professor Dr. Werner Mantele is the Professor of Biophysics at Goethe University and Frankfurt University. With over 30 years of experience with spectroscopy, Dr. Mantele is an internationally-recognized expert in the analysis and detection of molecules.
Within his work, Dr. Mantele explores fundamental aspects of protein structure function, correlation and protein analysis by four-year transform infrared spectroscopy. In this interview, Dr. Mantele discusses infrared spectroscopy and its uses in biochemistry, biology and medicine, including its advantages, disadvantages and real-world applications.
Dr. Suja Sukumaran is a Senior Application Scientist at Thermo Fisher Scientific. Dr. Sukumaran has over ten years of experience in analytical instrumentation, Molecular Biology, Protein and Lipid Biochemistry, and discusses the analysis of powdered samples using an MCT detector and via multi-bounce ATR.
In ths interview they outline the fundanmental aspects of protein structure-function coreelation and protein analysis by Fourier Transform Infrared (FTIR) spectroscopy.
Please introduce yourselves and describe your roles at Thermo Fisher Scientific?
Dr. Werner Mantele: My name is Professor Dr. Werner Mantele, Professor of Biophysics at Goethe University. A large portion of my work addresses the fundamental aspects of protein structure function, correlation and protein analysis by four-year transform infrared spectroscopy. I am a Professor of Biophysics at Frankfurt University and also the CSO of a startup that we founded six years ago that works to get products out of basic research on infrared spectroscopy.
Dr. Suja Sukumaran: My name is Dr. Suja Sukumaran, the Senior Application Scientist at Thermo Fisher Scientific. My work encompasses the above, including the use of an FTIR spectrometer and microscope and presenting examples of protein analysis.
Please outline a brief history of Infrared Spectroscopy for us?
Dr. Werner Mantele: Infrared spectroscopy is an established technique, which is now approximately 200 years old. If you look at history, you can see that the infrared was discovered around 1800: so-called ultra-red parts beyond the visible light by William Herrschel, a German immigrating to London, and it gradually became a method for molecular analysis mostly entering chemistry.
Until the 70s, this was essentially a method used in chemistry labs for the identification of compounds and characterization of simple molecules. The limitation of the technique has always been clear. But when Fourier transforming for spectroscopy entered the field in the late 70s, infrared spectroscopy became more interesting for biochemistry and even later on for medicine. It developed from the first tabletop devices requiring a few square meters of optical table area to a handheld instrument that is now in use.
A second improvement came around the turn of the century, namely around 1995: the first quantum cascade lasers as infrared sources were developed, which was a big step forward because it overcame some limitations of infrared spectroscopy, such as very low power from thermal sources. Meanwhile, the quantum cascade lasers became a reliable infrared source.
Why did it take so long before infrared spectroscopy entered biochemistry, biology, and medicine?
First of all, the spectral range is around 2-20 micrometers. In that range, we have water as a strong absorber at several points of the spectrum, which makes its application in IR spectroscopy and biologically difficult. It is important to keep in mind that we have photons in the infrared with very low energy, just about around the thermal energy KT. The problem is thermal sources – heated rods, glow bars, and so on. Thermal sources have a low brilliance, so the inherent problem of IR spectroscopy was always that the number of photons was very low.
Dispersive instruments require long scanning times: the first infrared spectra that I took as a diploma student in the mid-70s took hours. You could easily start scanning a spectrum, make a coffee, have a meal, and then come back and receive the spectrum. That became a lot different and faster in between.
The other problem was at the beginning of IR bio spectroscopy, new sampling techniques for biological macromolecules, membranes or cells were available. Now, that has completely changed. First of all, we have compact infrared instruments which work on the Fourier transform principles, interesting sample interfaces, the so-called attenuated total reflection technique with easy sample access. Those either operate for very small sample volumes, like a drop of blood, or even flow cells for bioprocess analysis. Today, the sampling side is also simple and established.
Could you please outline the second type of infrared source?
Dr. Werner Mantele: As I said, we have a second sort of infrared source, namely quantum cascade lasers. These are powerful, compact tunable light sources with lots of photons, which eliminate one of the problems of our spectroscopy. We have both tunable lasers and laser arrays with lots of wavelengths, which makes spectroscopy an easy issue.
At the same time, sampling techniques have actually focused more on biological samples. Classical sampling is a transmission sample with simple optics and where flow systems are possible. Path lengths are very short to absorb water. Sampling is a bit complicated. Cluttering can appear if you have particles in your sample. Certainly, this technique does not work in vivo. Some colleagues apply reflectance techniques where you shine infrared light onto the sample and collect the backscattered light.
This is an easy technique, but the penetration depth is unclear and covers only a few micrometers. It is its small sample volumes that allow flow cells to be made. The problem is that it worked with an evanescent wave with a penetration depth typically shorter than one wavelength, so in the order of five micrometers, which can be limiting.
Photoacoustic techniques are a lesser-known but extremely convenient for biological samples, especially for working in vivo. This is where you use a microphone to detect the sound wave generated by an absorption process. This is established well for gases and can also be used for liquids. There is also a photon thermal technique, which is linear and has a strong penetration depth of approximately a tenth of a millimeter – with the possibility to do depth profiling for skin, for example.
What are we going to see in infrared spectroscopy?
This is returning back to very simple principles. Infrared spectroscopy sees changes of dipole moments with nuclear motions. This can reveal changes in bond lengths, bond angles, bond polarization of protonation reactions of salvation and the formation and breaking of hydrogen bonds. The spectral range we have to consider is from approximately two to approximately 20 microns, 5,000 to 500 wave numbers. Within that range, a smaller region – approximately 5 – 10 micrometers – is most relevant for biological samples.
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What are the advantages and disadvantages of infrared spectroscopy?
Infrared spectroscopy uses small photon energies, which means you do not have unwanted photon reactions. For example, you are not at risk of the damage that could happen with fluorescent spectroscopy. The photon flow is moderate.
If you design the experiment correctly, you do not have heating of the sample. Sample quantities are also very small. That has been an enormous development, and you do not need high purity. For those that do time resolve spectroscopy, the intrinsic time resolution of infrared spectroscopy is one vibration cycle, meaning a few picoseconds.
However, there are also some disadvantages. For instance, infrared spectroscopy does not have selectivity for individual bonds, meaning that contributions from all parts of a protein, for example, will overlap.
As I mentioned already, you have a background absorption of water, meaning that you have to design specific sample forms. For example, for proteins, the peptide bond has a number of normal vibrations that are well characterized; MIA and MIB, which are the NH stretching modes. Then there is a nomenclature which has I to VII. This numbering determines the vibration type and among those, the most important one is the amide one absorbing around 16 to 700 wave numbers. That is an almost-pure CO stretching mode.
Dr. Werner Mantele: We will see that this is probably an easy way to characterize proteins. This amide one mode depends on the geometry and the secondary structure. And that information goes back to the 1950s. There is a paper that was published in Nature in 1950 based on the structure of synthetic polypeptides. This was the first report that the NH group and the CO group of the polypeptide backbone form a structure that can be probed by infrared spectroscopy and used as a sensitive probe for secondary structure.
What is notable about secondary structure elements when examined from about 1700 to 1600 wave numbers?
Dr. Werner Mantele: If you look at a small range in infrared spectroscopy from about 1700 to 1600 wave numbers, you have secondary structure elements that absorb differently. You find regions where you have an unordered structure that is on the top. You have regions where you have beta sheet absorbances, alpha-helix absorbances. And you can see that these absorbances are slightly different in H2 and D2.
It is clear because hydrogen or deuterium is involved there, which changes vibrational frequencies. If you analyze that Specter Range very carefully, you can actually get information on secondary structure.
Could you give an example?
Dr. Werner Mantele: On a particular image, for instance, we have a specific range around 1610 to 1615 wave numbers, which is characteristic for accurate aggregated proteins or, for example, amyloid fibrous. These are typical values; the positions of these secondary structures vary with the length. The problem of analyzing these is that the half widths of the mode are large, the modes are partially overlapping, and the assignment of transitions between secondary structures can be difficult because of that.
However, generally speaking, you have an ordered structure, alpha-helix and beta sheet in different regions, and you can use that like a fingerprint of sector structure for the characterization of the secondary structure of proteins for the influence of mutations, which will show up in that range for protein stability and protein folding, unfolding, and misfolding.
It is an easy, fast, and simple routine. It can be very precise if you are looking for changes in secondary structure, but the problem is bends are overlapping and hardly separated.
Where does a certain secondary structure begin and where does it end?
Dr. Werner Mantele: I will not give a detailed analysis of protein secretary structure, but I will pick up one point here, namely, the attractive application of direct following of protein folding. This is a possibility where you can determine melting points by infrared spectroscopy or see how folding and unfolding an aggregation or misfolding happen. I will pick out one small protein for this example.
This small protein, called Tendamistat, has about 74 amino acids; and eight kilos of molecular weight. This protein normally inhibits the enzyme Alpha-amylase. It has three prolines. If you do infrared spectroscopy in that special range, 1700 to 1600 wave numbers, from these proteins, and if you start at moderate temperatures of approximately 20 centigrade, you see the clear pattern of a beta sheet structure according to the X-Ray structure of the protein. If you then warm up the protein to about 40, 50, 60, 70, 80 centigrade, you will see how the beta sheet pattern disappears, and a clear random coil structure appears.
The transition is about 80 centigrade. That is fully reversible for the intact protein. If you cool down, the shape of the curve moves back to a clear, beta sheet structure, in contrast to the second experiment where we have replaced the three prolines with alanine at these positions. If you do the same experiment again, it starts with an unfolding: suddenly, there is an aggregation – this is indicated by the clear pattern for aggregated proteins in the infrared. This experiment is quick and offers a lot of information. If you do the heating up with a temperature jump from a laser, the experiment can be done in milliseconds or microseconds.
Making the switch now to biomedical applications, could you briefly outline some biomedical applications of infrared spectroscopy?
Dr. Werner Mantele: The main applications include the analysis of blood by infrared spectroscopy and non-invasive glucose measurement by infrared spectroscopy. This is termed biomedical spectroscopy, and there is enormous potential in that for clinical applications, portable apps and for home use.
First of all, the mid-infrared fingerprint of molecules in body fluids is key. All constituents of blood, urine, saliva, and so on, if they are of a molecular type, have a clear infrared pattern in the range of about 5 to 10 micrometers. This is the so-called fingerprint range, and that pattern can be used for identification and quantitative characterization – for example, in a sensor.
The basic principle is thus that you record an infrared spectrum of a blood sample, for example, urine samples, sweat, saliva. The analysis takes one to two minutes. It is suitable for a point of care and bedside applications. The sample quantities are very low, so we end up with a drop of blood, for example, from your fingertip. This method does not require any reagents; it does not require a recalibration procedure because of reagent change. The amount of potential infectious waste is extremely low, namely, acute tip to wipe clean the interface. It can use either FTIR instruments or quantum cascade lasers and is developed for handheld devices. The present analysis of a double blood sample, for example, can yield up to 12 medical parameters, relevant medical parameters.
However, with simple modifications of the sample interface, you can also use it for urine samples or dialysis fluid. Finally, the costs are low: it is just the investment on the device, but there are no longer any consumables.
Could you outline how the system works?
Dr. Werner Mantele: First of all, it uses a compact FTIR instrument. It is a few centimeters in size. Then, it needs a carefully designed mathematical procedure and a carefully selected calibration sample group. The user just chooses the best possible reference. In our case, it was the clinical lab of Frankfurt University. In the case of full blood samples, we have based the analysis of blood on about 2000 reference samples of full blood and plasma in the case of dialysis fluid.
The system has an automatic loading hemolysis and cleaning system. It is adapted to clinical routines and has clinically relevant simple user software because it is intended for medical doctors.
What it uses is mathematical procedures for calibration and validation strategies. Those are multiple variant analysis, colorimetry, and even deep learning procedures. How it works, principally, is that the user takes a correlation between a clinical reference value of a certain parameter with values being in the red range. So, potentially, the interest and the normal range, and you plot that versus the parameter derived from infrared spectroscopy. Now, once calibration has been done in this way, you take an unknown sample and you get the clinically relevant value: which, for example, could be the blood glucose value determined noninvasively.
How can the parameters be determined?
Dr. Werner Mantele: If we carry on from the previous question, we can state that at least eight parameters in practice, can be determined at clinical precision. All parameters are derived within less than a minute for taking a spectrum and about 20 seconds’ calculation time from a single drop of blood, and they are all at clinical precision.
Those blood parameters have been investigated in a range that covers the full clinical need, and the error is within the limits of what is expected for laboratory chemistry, except in the case of Immunoglobulin. This is a platform technology for different medical applications. We have tested it in the university clinics in Frankfurt for point of care analysis in a project which is called Patient Blood Management. We have a patent on urine measurements for the flow system, basically, an ATR system with a flow cell coupled to a urinal for immediate urine analysis. It’s used for real-time monitoring of hemodialysis for the flow cell.
Last but not least, it is applied for the blood analysis of small laboratory animals because the technology requires only a drop, whereas clinical laboratories are used for the blood analysis of small animals. They typically need more blood than the small animal can give without suffering.
What are some examples of real measurements in vivo using infrared spectroscopy?
Dr. Werner Mantele: One example which is relevant for many people in the world today is its use for diabetes patients. In 2019, about 463 million people worldwide lived with diabetes, and unfortunately, this number will continue to increase. The International Diabetes Federation estimates that by 2045, this will be close to 500 million people. Diabetes is increasing in all regions of the world: rapidly in the United States, and rapidly in the Middle East. In Europe, the increase is not as swift but is growing nonetheless and is truly a global pandemic that will not go away on its own.
What does a diabetes patient typically do to monitor or manage their disease, and how can the portfolio at Thermo Fisher Scientific help?
Dr. Werner Mantele: It is well-known that diabetes cannot be cured, but the disease can be managed. This means that a diabetes patient measures blood glucose levels several times a day by pricking, typically the finger, using an electrochemical sensor, building a test strip, and this sensor fits into a little device. This device, after one or two minutes, gives the blood glucose measurement.
The problem is that these test strips are costly, especially if you want to do several measurements a day, and they have a limited shelf time. Meanwhile, some continuously measuring minimally invasive sensors are tiny needles that go into your tissue and stay there for a week or two.
Of course, the issue currently is that too many people worldwide cannot afford those continuous measuring sensors, and thus, they have to rely on the test strips. Typically, the test measurements are not frequent enough, and measurements take place on average about 1.5 times per day and not more.
Now, our concept is to use infrared spectroscopy. The fluid that we focus on is not blood, but it is interstitial fluid or skin fluid. It is a liquid that surrounds cells, skin and muscle, and it is more than a minimal amount. It is twice the volume of blood. That liquid typically appears on the skin after shallow scratches or appears in a modified blister. It is a matrix of water ions, albumin, glucose, and phosphate.
Glucose in interstitial fluid represents about 90% of blood glucose, and if blood glucose changes, the ups and downs of blood glucose show up with very little delay in interstitial fluid. Our portfolio allows for the targeting of interstitial fluid in the skin with spectroscopy.
How does targeting of interstitial fluid in the skin with spectroscopy allow for a non-invasive glucose measurement?
Dr. Werner Mantele: First of all, we use the infrared fingerprint of glucose. These are glucose spectra in water at concentrations relevant for diabetes patients. The lower limit corresponds to 50 milligrams per deciliter, which is hypoglycemic for diabetes patients. The next limit is 100 milligrams per deciliter, which is normal glucose. And the top limit is 500 milligrams per deciliter for hyperglycemic situations, which is also of interest for diabetes patients. Those peaks arise from CO and OH bonds of the glucose molecule. This pattern is so characteristic that it can be termed a glucose fingerprint in the mid-infrared.
We make use of that fingerprint in the infrared using a laser system. You have to send infrared light into the tissue. Infrared radiation at 10 micrometers penetrates about 60 to 100 micrometers. We do not have the opportunity to use transmission measurements, but we can use photothermal or photoacoustic technologies to detect the absorbance process here.
How are photothermal or photoacoustic technologies used to detect the absorbance process?
Dr. Werner Mantele: In our setup, we use an internal reflection element. We use an infrared beam – called a pump beam – from a quantum cascade laser that shines lights through this crystal into skin. The beam penetrates about 100 micrometers of skin. If you select the glucose-specific wavelengths for this pump beam, glucose molecules in the skin’s interstitial fluid will absorb the infrared beam. As a consequence of absorption, they deposit a tiny amount of heat in these layers, which are warmed up by absorption just by a few millikelvin. The user doesn’t feel it.
Now, this warming up of the skin layers at that depth shows up at the surface and is transferred into that internal reflection element.
What happens in the internal reflection element?
Dr. Werner Mantele: This tiny warming up generates a so-called temporary thermal lens. A temporary thermal lens is something that you know from everyday experience. If you drive in the summertime on an asphalt road, and the sun burns on the asphalt, you see that the air directly in contact with the asphalt has different optical properties. It changes the optics, and you may see a mirage effect because of that. And that is exactly a thermal lens.
We use a second laser beam, which is called ProBeam, which is a simple red laser diode that we send through the thermal lens. It is deflected on the thermal lens, and the deflection is detected by a position that is sensitive to the diode.
This deflection is proportional to the absorbed radiation to the pump laser power, which we can control, and it is dependent on the change of the refractive index with the temperature of the internal reflection element. It is IR detection by visible light, which allows for the non-invasive measurement of glucose.
It is possible to use infrared spectroscopy for blood glucose measurement without any invasive procedure. It is precise enough to be used by diabetes patients. Its accuracy corresponds to commercially available glucometers. That was published both last year and this year in the Journal of Diabetes Science and Technology.
Suja, could you please provide an outline of your work regarding experimental aspects of protein analysis?
Dr. Suja Sukumaran: My work focuses on the analysis of proteins in FTIR, as well as establishing how protein analysis can be used for applications in food, technology, and research. We need to think about protein structure, stability, and aggregation. In analyzing samples in FTIR, there are two key sampling techniques that we have to remember. One is transmission, for which we can use transmission cells which are very small path links. We can also use protein solutions that are in H2O or D2O-based buffers. What we will do today is look ATR, and we will use both multi-bounce ATR as well as single-bounce ATR.
Multi-bounce ATR – as well as the single-bounce ATRs – is one of the more popular methods for analysis nowadays because of its ease of use, ease of cleaning, and the opportunity to regain the sample after the experiment is completed.
Which detector should be used in this type of experiment?
In the situation outlined below, an MCT detector should be used, especially if you are working with proteins at very low concentrations.
An MCT detector, which is a liquid nitrogen cooled detector, is much more sensitive than the DTGS detector and much faster as well. There are, therefore, options for the user to use the MCT and DTGS. The collect tab will tell where we can set the parameters for the number of scans and the resolution to other key parameters, which is based on what samples are being measured and what end goal you have. If you are considering samples that are very dilute, you will want to go much higher in scan numbers.
Why is the resolution parameter important?
Dr. Suja Sukumaran: The resolution parameter is important because if you are planning to do a secondary structure evaluation or look at peak shifts and peaks that are very close to each other, and you want to resolve them properly, you may want to use a resolution of two. For general use, you can also use a resolution of four. For higher resolutions, the time required to make a collection will also be higher. The number of scans is also critical here because there will be experiments where you are looking for very small differences between the same protein sample. You definitely want to go higher in the number of scans so that your signal to noise is really good.
How is the background measured?
Dr. Suja Sukumaran: Within the OMNIC software, the user can just click on this button that says “Click Background,” and it will start the background measurement. Once the background measurement is completed, the user is ready for either their sample or the buffer measurements just by themselves. All the user needs is ten microliters of my buffer or the sample. To start the measurement, simply click “Collect Sample.”
When it comes to the measurement of buffer and protein, the next step would be to subtract the buffer. To subtract the buffer, all we have to do is click on the “Select all” button and then, under “Process”, click on “Subtract”.
Now, we have to use the amide I region for our peak resolution or for peak fitting to get the second to restructure.
For that, we just select the amide I region. And all we have to do is go to the analyze button and click on peak resolve. In peak resolve, once we have selected the peaks and we have described the noise levels, all we need to do is click on the thick peaks button. This will run quite a few iterations to fit the peaks into the spectrum by itself. Once the peak fitting is done, all we need to do is click on the button so that it just adds it into a new window.
We can also look at the peaks and the peak areas as well. By just looking at the peaks, you can start to see the various peak areas that the software has come up with. You can add and delete certain peaks as and when required.
How can the proteins be analyzed using a multi bounce ATR?
When we want to analyze proteins that are in water-based buffers, we need to collect a buffer spectrum. We need to collect the protein spectrum, especially if we are going to do this at different temperatures also; we definitely will have to collect the buffers at different temperatures, as well as the protein at different temperatures.
Then, we subtract the buffer from the protein spectrum, and then the subtracted protein spectra with the amide I region between 1,700 to 1,600 is used for the peak result or the peak fitting function.
More information can be obtained under the Omnic training videos on our website.
There is a second way to analyze this and that is using the BioTools PROTA-3S software. Using the software, you can do multiple spectra at the same time, but this software is also more geared towards transmission analysis. If you have samples where you are doing multiple samples in transmission, you can use the PROTA-3S software for analysis of secondary structure as well.
Can you talk us through the applicability of these features?
One of the most commonplace examples of this kind of protein secondary structure determination is when we think about powdered food. Whey, rice, milk protein and pea protein are all materials that are made up of complex mixtures of carbohydrates, proteins, and lipids. However, it is simple and straightforward to analyze them: this can be done in a single bounce ATR.
It is very powerful to use a PCA-based analysis of these powders for classification and discrimination analysis.
When I have the sample, all I need to do is take a small scoop of it and put it on the ATR crystal (assuming the background has been completed). Once you have a powdered sample or so, it is important to use the pressure tower that is right in there so that the sample is in proper contact with the ATR crystal by itself. Then simply click “Collect Sample,” and the collection begins.
What can be observed in the analysis of the results from similar powdered samples?
We have analyzed milk protein, pea protein, rice protein, and whey protein from different vendors, as well as from different lots that were analyzed, and they were analyzed repeatedly.
Upon inspection, even the same type of protein from different vendors showed subtle differences. The spectrum was then further processed using PCA analysis. What we observed was that each of the proteins would separate out into its own little principle component regions.
The advantage of this is that the next time a certain type of protein sample from a particular vendor arrives, they can compare it to this particular model and say, “Oh, so this one is much closer to the G1 group” or “This is very similar to the milk protein group that we saw in the A2 type”, or so on.
What is the Rheonaut, and how is rheology related to food and beverages?
A Rheonaut is an instrument where rheology is coupled with FTIR spectroscopy. We want to know about viscosity and about the elasticity of the material. We want to know about the viscosity of things like chocolate syrup, as well as the elasticity of materials like marshmallows.
We knew we needed to couple two techniques: the first studying the physical properties of materials, like food powders, especially proteins, and then the second is the FTIR spectroscopy. That resulted in the instrument called the Rheonaut.
If we look at the Rheonaut, it is made up of three main components. One is the FTIR, the other one is the HAAKE MARS rheometer by itself, and then there is the interface between the FITR and the rheometer. Within this interface, the key component is the diamond ATR, which is built under the steel plate of the rheometer by itself.
How does the user load the sample into the steel plate?
The whey protein, for instance, is loaded right into the steel pedestal. Underneath, there is also the diamond ATR crystal. The RheoWin software controls the temperature ramps, but it also communicates with the Omnic software. In this maneuver, we are collecting rheological property and the changes in the FTIR peaks using the FTIR. The temperatures are controlled right on the pedestal when the plates make contact.
When the temperature ramps up and cools down is over. At the end of the experiment, the liquid material we loaded in has become this nice gel-like material that is also flexible and can fold. At the same time, there are significant changes in the amide I and II peaks, which indicates that there is some aggregation of protein that has happened as there is a downshift in the peak position, as well as a change in the intensity of the material.
When you actually begin in the solution state, the whey protein is in a nice folded state. It unfolds as the temperature ramps up, resulting in aggregation and the development of the whole gelation process.
What were the important findings from this study?
We can use protein secondary structure, folding and aggregation studies for many different application types, and we can perform these using transmission.
Finally, we observed that we could do this with ATR: both single bounce and multi bounce ATR. We also learned that we could use the power of FTIR spectroscopy and combine it with PCA analysis to create some really powerful discriminate models to do some nice QC techniques. We can also use hyphenated techniques, like the Rheo-IR, and other things like the TGA-IR or GC-IR to understand various physical and chemical properties of everyday materials.
About Werner Mäntele, PhD
Prof. Dr. Werner Mäntele is a professor of biophysics at the Goethe University in Frankfurt am Main. He has over 30 years of experience with spectroscopy and is an recognized expert in analyzing and detecting molecules like glucose and protein. Currently, Prof. Dr. Mäntele is the chief scientific officer in DiaMonTech, a medical device company based on the concept of “photothermal detection”, which Prof. Dr. Mäntele and his team developed.
About Suja Sukumaran, PhD
Dr. Suja Sukumaran earned her PhD in Biophysics from Johann Wolfgang Goethe University, Germany, as part of the international Max Planck research School. She is the co-inventor of US PATENTS on ‘MspA Nanopores and related methods’ licensed to Illumina Inc. Her experience and expertise is in Molecular Spectroscopy, Visible and fluorescence Imaging, protein and lipid biochemistry. Her current research interests are AI for protein folding , microplastics and recycling.
About Thermo Fisher Scientific – Materials & Structural Analysis
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