Kristýna Boušová: Engineering new proteins

<p><strong>Jan Velecký is a&nbsp;researcher at the RECETOX center. In his dissertation, he focuses on machine learning methods for protein engineering. He works at the center within Loschmidt Laboratories, specifically on Stanislav Mazurenko's&nbsp;team. In the interview, he explains what protein engineering is about, why it is important to study protein solubility, and how machine learning can be crucial for human knowledge.</strong></p><div><div><h5><strong>How did you get into protein engineering?</strong></h5><p>Since childhood, I&nbsp;had a&nbsp;curious relationship with computers, which led me to a&nbsp;technical high school in Zlín, where I&nbsp;studied information technology. Then I&nbsp;continued at the Faculty of Information Technology at Brno University of Technology. After my bachelor's&nbsp;degree, I&nbsp;realized that I&nbsp;would like to combine computer science with something more tangible, not just living inside the computer. One option was bioinformatics, which I&nbsp;started to pursue during my master's&nbsp;studies. Even then, I&nbsp;began to focus on protein research, specifically choosing the topic of protein solubility for my diploma thesis. And that's&nbsp;what I&nbsp;still do.</p><h5><strong>Could you explain a&nbsp;bit about what protein engineering actually focuses on?</strong></h5><p>Protein engineering is, simply put, the design or modification of proteins. Sometimes we create completely new proteins, or more commonly, we modify existing ones. We often proceed based on mutations, i.e., targeted changes that a&nbsp;scientist makes in the protein. To be able to change and modify proteins purposefully, we first need to study them and find out how they work. In its early days, the field aimed at creating mutations that would "damage" the function of a&nbsp;protein. If we manage to disable the protein through mutation, we actually reveal which part of it is essential for its function. That's&nbsp;why protein engineering was initially dubbed protein terrorism.</p><h5><strong>How can I&nbsp;practically imagine such deliberate protein mutating?</strong></h5><p>A protein is a&nbsp;linear molecule, a&nbsp;chain of amino acids encoded by a&nbsp;gene. An organism produces it according to the gene and subsequently the protein folds, gaining a&nbsp;shape. The shape then determines the function of the protein. We don't need to know the shape, but we can play with the composition of amino acids. Typically, we replace an arbitrary amino acid with another. We have 20 types of amino acids, so I&nbsp;can, for example, put an alanine, which is very small and neutral, instead of a&nbsp;cysteine, making it ideal for our purposes. If the protein loses its function after such modification, we know that this cysteine is essential for its function or some key property.</p><h5><strong>Why do you focus on solubility particularly?</strong></h5><p>Solubility is one of the basic properties; it is crucial for producing new proteins. It determines whether it will be possible to produce the protein in sufficient quantity or quality and at an acceptable cost. It has direct implications in medicine and industry; drugs for stroke in development, for example, are protein-based, so are ingredients contained in washing detergents. Decent solubility is important for yield and thus more efficient production. I&nbsp;specifically deal with methods to estimate changes in protein solubility. This means that where we would usually need a&nbsp;person and material to measure solubility, we could use a&nbsp;computer and estimate solubility in silico, saving both money and time. For example, with the mentioned therapeutics for stroke, we could determine solubility in advance and avoid experiments that wouldn't make sense. To sum up, I&nbsp;try to measure and predict changes in protein properties, especially solubility, after introducing a&nbsp;mutation.</p><h5><strong>Do you have a&nbsp;personal connection to the field?</strong></h5><p>Bioinformatics interested me mainly because I&nbsp;saw its potential for the future; it simply seemed exciting to me. By choosing my then-teacher Jiří Hon, who was doing his doctorate at the faculty, as my diploma thesis supervisor at BUT, I&nbsp;also became part of the Loschmidt Laboratories, where I&nbsp;subsequently started working on my own doctorate under the supervision of Dr. Stanislav Mazurenko.</p><figure class="image"><img style="aspect-ratio:575/764;" src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/MUNI_Proteinovy_vedec_Jan_Velecky_Strojove_uceni_muze_zazarit_tam_kde_uz_lidska_predstavivost_nestaci_877b7af987.jpg" alt="MUNI: Protein scientist Jan Velecký: Machine learning can shine where human imagination falls short" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_MUNI_Proteinovy_vedec_Jan_Velecky_Strojove_uceni_muze_zazarit_tam_kde_uz_lidska_predstavivost_nestaci_877b7af987.jpg 117w," sizes="100vw" width="575" height="764"></figure><h5><strong>Can you explain a&nbsp;bit about what the Loschmidt Laboratories are?</strong></h5><p>The full name is the Loschmidt Laboratories of Protein Engineering, which is our main research focus. We are named after Johann Josef Loschmidt, a&nbsp;Bohemian-Austrian scientist of the 19th century, a&nbsp;founder of modern chemistry. We consist of four teams, two more theoretical, more focused on computational methods, and two experimental, working in the laboratory. What is specific about our work is that although we have specific protein targets we focus on, they serve more as case studies for the methods we create. We develop several software tools for protein engineers, biochemists, or clinical doctors to analyze or modify proteins for their applications. For example, one of our successful and widely used tools is EnzymeMiner, which can find more proteins with the desired function based on the well-studied protein. Thanks to it, we can recycle and use what nature has already invented in the course of evolution. Our work is mainly about developing methods and tools.</p><h5><strong>Where does your work fall within the focus of the Loschmidt Laboratories?</strong></h5><p>Researching solubility is about protein optimization. If we develop a&nbsp;new drug, but the yield is so low that it is not enough even for laboratory experiments, we can increase it thanks to protein engineering. I&nbsp;mentioned the drug for stroke; another good example is insulin, which had low solubility earlier and originally used to be derived from pigs, but today, we can produce it artificially in cells and then extract it, making it financially accessible. Solubility prediction is also important in diagnostics. Many diseases are caused by mutation in an individual's&nbsp;genetic code that significantly reduces the solubility of a&nbsp;particular protein. And since insoluble proteins can even be toxic, there is a&nbsp;potential use in personalized medicine too.</p><h5><strong>If I&nbsp;understand correctly, the role of IT in your field is primarily to save time and money. But does machine learning have any other specific advantages?</strong></h5><p>Certainly. Let's&nbsp;say that all the problems a&nbsp;person solves can be well managed if they are imaginable in two to four dimensions. However, once there are, say, a&nbsp;hundred dimensions, finding interdependencies and explaining the phenomena and behaviours that lead to them is definitely not trivial. This is where machine learning can shine, as it has no limitations in the possible number of dimensions it can think in and can find what is hidden from us.</p><h5><strong>How can you be sure that the information you obtain this way is reliable?</strong></h5><p>Naturally, we have methods to verify reliability. The basis is that we train the machine learning model from data with known outcomes. However, we do not show the model all the data we have. The data we keep aside then serves to test the model. Machine learning is also about experimentation. It's&nbsp;not like you design a&nbsp;model and it works straight on.</p><p>And thanks to today's&nbsp;availability of computational hardware, we are putting into practice what was previously unimaginable. After all, the cost per unit of computation has dropped a&nbsp;quadrillion times since the 1950s when the foundations of machine learning were laid.</p><h5><strong>Where is the field heading and what are its ambitions?</strong></h5><p>There is a&nbsp;whole array of unresolved problems. The latest major challenge solved was the protein structure prediction problem. Now we know what the shape of a&nbsp;protein molecule will be based on its genetic code. This is an important advancement because, as I&nbsp;said, the function depends on a&nbsp;shape. Thus, I&nbsp;think we will now see many problems in molecular biology solved in quick succession. If I&nbsp;were to put it on a&nbsp;timeline, we used to mutate proteins to find out how they work. Today, we are redesigning them. In the future, we will be ordinarily creating completely new proteins, supported not only by the development of machine learning but also by robotics and other high-throughput methods that will enable us to collect data for machine learning.</p><h5><strong>Do you think the development of AI could threaten some jobs in science?</strong></h5><p>In my opinion, the development of AI will improve the lives of scientists because it will make repetitive and boring work easier. I&nbsp;don't think AI is targeting any specific positions. Proofreaders and translators might be needed less. In other positions, it will actually increase efficiency and thus the amount of work completed. Someone who now characterizes five protein variants a&nbsp;week in the lab might one day do five thousand.</p><h5><strong>What are your personal vision and scientific ambitions?</strong></h5><p>I would like my work to advance the field of protein engineering so that the field can continue to build on it. Right now, I&nbsp;want to focus mainly on completing my doctorate. In the future, I&nbsp;would like to stay in research. However, I&nbsp;want to experiment a&nbsp;bit at the same time. It could be an experience from research in the commercial sphere or a&nbsp;voyage into a&nbsp;new domain where I&nbsp;could apply my machine-learning skills. Not stopping broadening my horizons.</p></div></div>

Protein scientist Jan Velecký: Machine learning can shine where human imagination falls short

<p><strong>Bohumil Kolář applies artificial intelligence in places where ordinary people can hardly imagine it. We talked about how AI makes work easier, how construction kit Mercur continues to inspire a hundred years after its creation, and beer cups whose meaning will blow your mind.</strong></p><p>I'm taking pictures of Bohumil with the computer. "<i>And now I'm going to take a picture of you with neural networks</i>," I say mischievously. "<i>Well, we have some graphic simulation, so I can send it to you</i>," Bohumil replies with hesitation. I can see that my sense of humor is off, so I'm getting insecure with the conversation. ChatGPT is now an integral part of my life, but what's behind it, I don't know. And Bohumil knows, he's an AI expert.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/TUL_CXI_Bohumil_Kolar_5cdb8ef8d0.jpg" alt="TUL CXI: Bohumil Kolář" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_TUL_CXI_Bohumil_Kolar_5cdb8ef8d0.jpg 231w," sizes="100vw" width="800" height="540"></p><h5><strong>Sometimes I'm lazy</strong></h5><p>And what does Bohumil use ChatGPT for? "<i>Sometimes I'm just lazy</i>," Bohumil admits. "<i>The AI saves me hours of reading</i>," he says with a guilty smile. "<i>Sometimes I copy a long text into ChatGPT and ask it to summarize it in two paragraphs. Why? Because I don't always have the desire or time to read anything longer than two pages</i>," he explains candidly.</p><p>Bohumil found out about the AI Specialist position at CXI TUL when he was looking for a job after school. "<i>For example, I was offered a job developing a cable car control system, which is not interesting for me. Then I found an offer from CXI TUL and I'm happy, I often learn new things. I enjoy challenges. For example, I am working on an AI application for laser calibration</i>," he shrugs. The aforementioned laser has many applications, for example from eye surgery, through brute force cutting to space research and defense systems.</p><h5><strong>It started with Mercur</strong></h5><p>Bohumil was a fan of the construction kit Merkur as a kid, but he was missing something to get the kit moving. So he became interested in electrical engineering. He soon discovered that there was always a need for a man to program everything. "<i>I'm not really a programmer, I've always been attracted to the interdisciplinary field, the connection with electrical engineering. Now, for example, I'm tackling business efficiency with artificial intelligence in the European Digital Innovation Hub, </i><a target="_blank" rel="noopener noreferrer" href="https://www.edih-northeast.cz/en/home/"><i>EDIH</i></a>."</p><h5><strong>Real problems, practical solutions</strong></h5><p>Businesses from across the spectrum of industries turn to Bohumil directly or attend training sessions where he shows them the possibilities of AI to streamline operations. "<i>For example, Škoda approached us about vibrodiagnostics. The brief was to see if we could predict when an engine would break down. My job was to teach AI to recognize the vibration of a balanced engine and detect deflections such as bearing float, unbalance, and so on. Based on this data, they can prevent failures and maintain production quality,</i>" Bohumil recounts.</p><h5><strong>Image analysis of wastewater</strong></h5><p>One of the most interesting contracts is the detection of problems at wastewater treatment plants. "<i>My job is to teach the program to recognize what a poorly working treatment plant looks like. For example, foaming water means an overgrowth of microorganisms. Color changes can indicate a different type of problem. Camera detection is fast and efficient, and you don't have to physically go around to all the treatment plants</i>," he says.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/TUL_CXI_Bohumil_Kolar_Umela_inteligence_otevira_nove_pracovni_moznosti_5386b28764.jpg" alt="TUL CXI: Bohumil Kolář (Artificial intelligence opens up new job opportunities)" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_TUL_CXI_Bohumil_Kolar_Umela_inteligence_otevira_nove_pracovni_moznosti_5386b28764.jpg 117w," sizes="100vw" width="1500" height="2000"></p><h5><strong>AI and Beer cups</strong></h5><p>And what does Bohumil have on his desk besides his computer? "<i>Lots of beer cups</i>," he laughs. One of his apps detects whether you have an honest pint in front of you or under measurement.</p><p>The audience immediately thinks: nice, but what is it good for? "<i>The same algorithm can detect a tank and guide a missile. Maybe in Ukraine,</i>" Bohumil answered laconically. It shows that even a seemingly innocent AI application can be a weapon.</p><h5><strong>Revolution</strong></h5><p>The rapid development of artificial intelligence is a challenge for Bohumil. "<i>The pace at which AI is growing is insane,</i>" he says. "<i>New algorithms and technologies are being created every day. Sometimes I must understand how a certain technology works, only to find out a year later that it's already outdated. The world's largest organizations are rapidly pushing the boundaries of AI. Guessing the direction of development and keeping track is a big challenge."</i></p><h5><strong>AI gives work</strong></h5><p>From engineering to natural sciences, Bohumil sees no limits to artificial intelligence. "<i>The only problem is the lack of data to train the models.</i>" Many people argue that AI is taking jobs. Bohumil sees it differently. “<i>Automation opens up opportunities for more work.</i>"</p><p>It is important to show that AI is a tool. "<i>It is not a threat. It depends on how we use it,</i>" concludes Bohumil.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/TUL_CXI_Bohumil_Kolar_Umela_inteligence_otevira_nove_pracovni_moznosti_2_e943a453a0.jpg" alt="TUL CXI: Bohumil Kolář (Artificial intelligence opens up new job opportunities)" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_TUL_CXI_Bohumil_Kolar_Umela_inteligence_otevira_nove_pracovni_moznosti_2_e943a453a0.jpg 117w," sizes="100vw" width="1500" height="2000"></p>

Bohumil Kolář: Artificial intelligence opens up new job opportunities

<p><strong>The growing influence of artificial intelligence brings with it huge energy demands, which in turn bring large-scale climate challenges. Ondřej Wojewoda from CEITEC BUT brings a revolutionary solution in his PhD thesis: using Mie resonances in dielectric materials, he has developed a method that enables efficient measurement of short spin waves using common laboratory equipment. Ondřej’s discovery brings a fundamental shift in the availability of spin wave research, which has the potential to become a key platform for energy-efficient data transmission and processing with applications in AI, but also in medicine and mechano-biology.</strong></p><p>Artificial Intelligence (AI) has experienced an extraordinary boom in recent years, and its potential to fundamentally change and streamline human activities is undeniable. A groundbreaking example of this development is the emergence of large-scale language models (LLMs) such as ChatGPT or Gemini. However, with their rise comes a major problem: the enormous energy consumption, which represents a significant obstacle to meeting global climate goals, especially in terms of water consumption – the problem being the heating, which necessitates the associated cooling of infrastructure, requiring up to a litre of water for just a few prompts.</p><p>One promising way to reduce the energy intensity of AI, especially LLM, is to move away from the classical von Neumann architecture to new technologies using wave&nbsp;systems. In this context, spin waves seem to be a promising candidate – they allow easy integration into existing technologies and provide natural nonlinearity, crucial for the proper functioning of AI (in current implementations, this function is provided by activation functions). However, the main challenge for implementing spin waves in functional chips is their miniaturization. Short spin waves with lengths below 400 nm can currently only be measured using synchrotrons, which is expensive, time consuming, and therefore slows down further development in this area.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/CEITEC_Spinove_vlny_jako_klic_k_udrzitelnejsi_AI_Ondrej_Wojewoda_prinasi_prulom_v_mereni_diky_vyuziti_Brillouinovy_spektroskopie_svetla_4_0c425482f7.jpg" alt="CEITEC: Spin waves as the key to more sustainable AI: Ondřej Wojewoda makes a breakthrough in measurement using Brillouin spectroscopy of light " srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_CEITEC_Spinove_vlny_jako_klic_k_udrzitelnejsi_AI_Ondrej_Wojewoda_prinasi_prulom_v_mereni_diky_vyuziti_Brillouinovy_spektroskopie_svetla_4_0c425482f7.jpg 156w," sizes="100vw" width="1080" height="1080"></p><p>Under the guidance of <a target="_blank" rel="noopener noreferrer" href="https://www.ceitec.eu/michal-urbanek-ph-d/u17142?page=publication">Michal Urbánek</a>, head of the CEITEC Nano research infrastructure, Ondřej Wojewoda has been working on this problem as part of his PhD together with his colleagues. In his PhD thesis, Ondřej developed a new methodology that addresses this problem by exploiting so-called Mie resonances in dielectric materials and allows these short spin waves to be measured using standard laboratory equipment called Brillouin Light Spectroscopy (BLS). This technique not only paves the way for the further development of spin waves as an energy-efficient technology for AI, but also finds applications in other fields. With the theoretical description and practical implementation of Mie resonances in Ondřej’s work, this technique has the potential to significantly contribute to advances in medical and mechano-biological applications, where BLS is currently experiencing a tremendous boom, for example, in the early diagnosis of eye defects.</p><p><i>“Spin waves (magnons) have the potential to be used as a new platform for data transmission and processing because they can reach wavelengths in the nanometer range and frequencies from hundreds of megahertz to units of terahertz. However, until now, it has only been possible to image spin waves with wavelengths below the diffraction limit of light using X-ray microscopy with large particle accelerators,”</i> says Ondřej, introducing the context of his work. In Europe, for example, synchrotron accelerators able to measure spin waves are only in two places – Berlin and Zurich. This limitation makes research and development of spin wave devices much slower as well as more expensive. With this in mind, during his PhD studies, Ondřej looked for ways to overcome this problem.</p><p><i>“By exploiting Mie resonances in dielectric structures, we can measure spin waves with comparable wavelengths using a standard optical setup designed for Brillouin light scattering microscopy measurements,”</i> says Ondřej. He studied the whole process on a silicon disk placed on a nickel-iron layer. The technique can be adapted to obtain resolution for wavelengths as short as 50 nm in the sample plane using an array of silicon strips with a subdiffraction period. In the last part of his thesis, Ondřej focused on the measurement of coherently excited spin waves, where he demonstrated phase resolution by measuring the dispersion relation of the spin waves.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/CEITEC_Spinove_vlny_jako_klic_k_udrzitelnejsi_AI_Ondrej_Wojewoda_prinasi_prulom_v_mereni_diky_vyuziti_Brillouinovy_spektroskopie_svetla_2_666d83dabc.jpeg" alt="CEITEC: Spin waves as the key to more sustainable AI: Ondřej Wojewoda makes a breakthrough in measurement using Brillouin spectroscopy of light " srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_CEITEC_Spinove_vlny_jako_klic_k_udrzitelnejsi_AI_Ondrej_Wojewoda_prinasi_prulom_v_mereni_diky_vyuziti_Brillouinovy_spektroskopie_svetla_2_666d83dabc.jpeg 208w," sizes="100vw" width="1600" height="1200"></p><p>How did Ondřej’s research actually proceed? When choosing the topic for his PhD, Ondřej saw the use of plasmonic resonances in Brillouin scattering as natural because Brillouin scattering is similar to Raman scattering, and in Raman scattering, plasmonic resonances are often used to amplify the signal.</p><p>However, since Ondřej and his colleagues were new to Brillouin scattering, they were unaware that several teams had been made to try a similar approach before, to no avail. On their first attempt, however, the team obtained excellent results, which, unfortunately, they were unable to repeat. <i>“Thanks to the advanced nanocharacterisation capabilities available at CEITEC Nano, we discovered that the samples we did not measure metal particles as we had originally planned, but instead, a silicon "mess" that has inadvertently fallen on our samples,”</i> explains Ondřej.</p><p>This discovery led Ondřej to create new silicon resonators with which he and his colleagues were the first to not only amplify the signal but also to extend the detection capabilities of Brillouin scattering to very small wavelengths below 50 nm. The results presented have the potential to fundamentally change the research paradigm in solid-state physics and mechano-biology.</p><p>Ondřej’s method is replicable, and similar results can now be achieved by teams around the world – all they need is a nanofabrication lab and an optical setup to measure Brillouin light scattering. This is a major advance; as we mentioned above, previously, scientists were only able to image spin waves at the nanometer level in synchrotron accelerators, which are space and cost intensive. Using the BLS to measure spin waves thus makes magnonics a much more competent field.</p><p>At the end of last year, Ondřej received the Hlávka Foundation Award for his outstanding academic achievements and exceptional contribution to the field of laser spectroscopy. The Hlávka Foundation, the oldest Czech foundation founded on 25 January 1904 by architect Josef Hlávka, supports science, literature, art, and gifted students at Czech universities. It awards the Josef Hlávka Prize to the best students, graduates and young scientists. Six students of Brno University of Technology received the Hlávka Foundation 2024 Prize, together with a financial reward, at the Lužany castle.</p><p>Ondřej Wojewoda continues to work at CEITEC BUT. Thanks to the Postdoc Individual Fellowship grant from GAČR, he is now preparing for a two-year postdoctoral fellowship at the prestigious Massachusetts Institute of Technology (MIT), where he intends to research non-reciprocal magnetic materials for use in microwave technology.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/CEITEC_Spinove_vlny_jako_klic_k_udrzitelnejsi_AI_Ondrej_Wojewoda_prinasi_prulom_v_mereni_diky_vyuziti_Brillouinovy_spektroskopie_svetla_3_a4fb59bd6c.jpeg" alt="CEITEC: Spin waves as the key to more sustainable AI: Ondřej Wojewoda makes a breakthrough in measurement using Brillouin spectroscopy of light " srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_CEITEC_Spinove_vlny_jako_klic_k_udrzitelnejsi_AI_Ondrej_Wojewoda_prinasi_prulom_v_mereni_diky_vyuziti_Brillouinovy_spektroskopie_svetla_3_a4fb59bd6c.jpeg 235w," sizes="100vw" width="1600" height="1067"></p>

Spin waves as the key to more sustainable AI: Ondřej Wojewoda makes a breakthrough in measurement using Brillouin spectroscopy of light 

<p><strong>Mushrooms – a fragrant forest treasure for some, a fascinating object of study for others. In this case, the connection between nature and science is entirely natural. What can you discover about a simple mushroom under a microscope or using chromatography? And how helpful is a scientific education when it comes to everyday mushroom hunting?&nbsp;</strong></p><p>We asked <strong>RNDr. Roman Kysilka, CSc.</strong>, who worked as a research specialist at the Czechoslovak Academy of Sciences and now works at <a target="_blank" rel="noopener noreferrer" href="https://watrex.com/?utm_source=labrulez&amp;utm_medium=propagace&amp;utm_campaign=labrulez_clanky"><strong>Watrex Prague</strong></a>. He walked us through not only his career, but also through the forest – both scientific and real.&nbsp;</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Watrex_19_6_uvod_1600_X900_4dca2a04b3.jpg" alt="Watrex Fig.1: RNDr. Roman Kysilka, CSc." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Watrex_19_6_uvod_1600_X900_4dca2a04b3.jpg 245w," sizes="100vw" width="3540" height="1875"></p><h4><strong>When and why did you decide to study natural sciences? Were you drawn to them as a child?</strong></h4><p>I got a chemistry experiment kit, I think it was called "Curious Chemist," around seventh grade, and I was immediately captivated by home experiments. I was also into electricity and experimented with that as well. In my early years of high school, I was still considering studying electrical engineering or chemistry. But chemistry won out, largely thanks to the chemistry olympiads I took part in regularly from elementary school. Through national competitions (later in high school), I met a lot of chemistry enthusiasts. And during training camps for the international olympiad, I got to know chemists from the Faculty of Science at Charles University – and that sealed the deal.</p><h4><strong>How did you first get into studying mushrooms? Was it by chance or intentional?</strong></h4><p>It was a coincidence. I did grow champignons when I was around twelve, but that had nothing to do with research – I was mostly curious about what my mom would cook with them. Between 1982 and 1984, I was working on my thesis, and my advisor, Prof. Karel Štulík, arranged for me to work in a chromatography lab in the Department of Experimental Mycology at the Institute of Microbiology of the Czechoslovak Academy of Sciences. And that’s where I first encountered mushrooms as a subject of scientific research.&nbsp;</p><h4><strong>What fascinated you most about mushrooms?&nbsp;</strong></h4><p>Mushrooms have been with humankind since ancient times. You might recall the phrase “mushrooms – meat of the poor.” The Aztecs used the word teonanácatl, which roughly translates as “meat of the gods” (later found to refer to mushrooms with psychoactive effects). Meat for both the poor and the gods – interesting, right? The diverse world of fungi – heterotrophic organisms with a vital role in nature – fascinated me from the start. And of course, there’s also the unexpected potential of the compounds mushrooms produce. Every year, hundreds of new, previously unknown chemical compounds – secondary metabolites – are isolated and described in scientific literature, with potential uses in medicine and other fields. You could say the world of fungi is still largely unexplored from a chemical standpoint.&nbsp;</p><h4><strong>You worked at the Czechoslovak Academy of Sciences from 1985–1991 – what exactly did you do there?&nbsp;</strong></h4><p>After returning from military service, I went back to the Institute of Microbiology, where I focused on research into psychoactive tryptamine derivatives in basidiomycetes for my dissertation. The list of substances later narrowed to psilocybin, psilocin, baeocystin, and bufotenin. I worked on developing analytical methods to detect these compounds in fruiting bodies and mycelium, designing chromatographic methods for semi-preparative scale isolation, conducting cultivation experiments with various Psilocybe species in the lab, and screening potentially psychoactive mushrooms for these compounds.&nbsp;</p><h4><strong>Do you recall a moment or discovery that left a strong impression on you?&nbsp;</strong></h4><p>Yes. Part of the research on magic mushrooms included experimental poisonings. In the late 1980s, together with Marta Semerdžieva, we completed (and later patented) a method for producing mushroom mycelium via submerged cultivation. We planned an intoxication experiment using this rather unappealing material. Based on HPLC analysis, we cooked a “mushroom” soup and began the experiment. However, the outcome was very different from what we expected – it was clear we had significantly overdosed the test subjects. That prompted a detailed review of the analytical method used to determine psilocybin and psilocin levels. We found that the critical step for accurate results was the sample preparation before HPLC analysis. With optimized extraction, we detected concentrations of active compounds several times higher than with previously published methods. Our article in Planta Medica is still cited today and occasionally discussed in forums about psychoactive substances.&nbsp;</p><h4><strong>What techniques were you using then – and what surprises you most about modern lab methods?&nbsp;</strong></h4><p>Our main analytical technique was HPLC. Mass spectrometry, which is standard today, was just a dream back then. The peak was using a UV-VIS diode-array detector or selective and sensitive amperometric detection. I find the current development of lab automation, the explosive growth of computing and mathematical modeling, and more recently, the use of artificial intelligence truly remarkable.</p><h4><strong>How did you transition from academia to Watrex Prague? What attracted you to the change?</strong></h4><p>In the early '90s, research projects at the Institute of Microbiology were being reorganized, and several colleagues I worked with left the institute. Around the same time, I got a job offer from Milan Minárik, who was founding <a target="_blank" rel="noopener noreferrer" href="https://watrex.com/?utm_source=labrulez&amp;utm_medium=propagace&amp;utm_campaign=labrulez_clanky"><strong>Watrex</strong></a> – a distributor for <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/companies/325"><strong>Waters</strong></a> chromatography systems. I had met Milan a few years earlier (through HPLC, of course), and the idea of working as an applications specialist in his private company was very appealing. It was a time of rapid private sector growth in Czechoslovakia, and I was excited to be a part of that.&nbsp;</p><h4><strong>You’ve studied mushrooms scientifically, but what about in the actual forest? Are you a mushroom picker?</strong></h4><p>I love picking mushrooms (their fruiting bodies), but I don’t have as much time for it as I’d like.&nbsp;</p><h4><strong>How much do you rely on your scientific knowledge when mushroom picking? Do you see mushrooms differently than the average picker?&nbsp;</strong></h4><p>Rather than scientific knowledge, I rely on experience from field excursions with the Institute of Microbiology, where I had the chance to learn mushroom identification from leading Czech mycologists. And unlike “typical pickers,” I often collect gilled mushrooms. My three-year-old granddaughter Anička might actually be able to name more bolete species than I can.</p><h4><strong>Does your knowledge of chemistry help with identifying lesser-known species?</strong></h4><p>No.&nbsp;</p><h4><strong>Do you have a favorite mushroom – either for eating or just because it’s interesting?&nbsp;</strong></h4><p>Aside from magic mushrooms, I have a soft spot for the fly agaric. Amanita muscaria, with its unmistakable red cap and white spots, has a rich and ancient history. Its story intersects with folk medicine and shamanism across many cultures, especially in the Northern Hemisphere. Another mushroom worth mentioning is the deadly Cortinarius orellanus. It grows in our region and can unfortunately be confused with some edible species. It contains the nephrotoxin orellanine, which is dangerous due to its delayed onset – symptoms can appear up to three weeks after ingestion, which makes treating the poisoning extremely difficult.&nbsp;</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Watrex_19_6_obr_2_02794e1777.jpg" alt="Watrex Fig.2: Illustrative photo of Amanita muscaria and Cortinarius orellanus" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Watrex_19_6_obr_2_02794e1777.jpg 245w," sizes="100vw" width="1600" height="839"></p><h4><strong>What can we learn about a mushroom in a laboratory — apart from whether it’s edible or not?&nbsp;</strong></h4><p>A mushroom, as a subject of laboratory study, can be analyzed taxonomically; we can identify substances that are toxicologically significant, search for new biologically active compounds, or use fungi as model organisms in genetic research. Their bioaccumulation capacity can help monitor unwanted substances in the environment. And I’m sure there are many other possibilities for scientific investigation in the lab.&nbsp;</p><h4><strong>Have you ever examined the presence of toxins, heavy metals, or pesticides? How common are they in mushrooms?&nbsp;</strong></h4><p>The ability of mushrooms to accumulate foreign substances is well documented and stems from the way they absorb nutrients from their surroundings. Their mycelium has a huge surface area and absorbs not only nutrients from the soil solution, but also unwanted substances, which may then accumulate in the fruiting bodies. I personally haven’t focused on bioaccumulation research in fungi — with one exception. After the Chernobyl nuclear disaster, we collected various mushroom species to monitor levels of Cesium-137.&nbsp;</p><h4><strong>What’s your opinion on identifying mushrooms using mobile apps?&nbsp;</strong></h4><p>If a mobile app serves as a replacement for a quality, well-illustrated mushroom atlas, I have no objections. However, I’d be very cautious when using various "identification keys." An amateur can easily overlook or misinterpret an important feature that differentiates an edible mushroom from an inedible or even poisonous one. That said, with the advancement of AI, things will surely improve :). As always — only collect mushrooms you can identify with absolute confidence!&nbsp;</p><h4><strong>What’s something every mushroom hunter should know — but often overlooks?</strong></h4><p>Where north is — and how to get back to the train station or their parked car.</p><h4><strong>Besides a knife, is there anything else you’d bring in your mushroom basket?&nbsp;</strong></h4><p>A camera. Mushrooms are incredibly photogenic. And if one doesn't end up in the basket, it can at least become a model for photography.&nbsp;</p><h4><strong>And finally: If you had to describe mushrooms in one word, what would it be?</strong></h4><p>Saprophytes. Without them, life on our planet would come to a halt.&nbsp;</p><p><i><strong>Many thanks to Roman Kysilka for such an open and inspiring conversation. It was a pleasure to explore his professional journey and the unique experiences that have shaped it. Roman currently works at </strong></i><a target="_blank" rel="noopener noreferrer" href="https://watrex.com/?utm_source=labrulez&amp;utm_medium=propagace&amp;utm_campaign=labrulez_clanky"><i><strong>Watrex Praha</strong></i></a><i><strong>, where his expertise and experience continue to make a valuable impact. We wish him all the best in his future professional and personal endeavors!</strong></i></p>

Are you scientifically prepared for the new mushroom-picking season?

<p><strong>In this insightful interview, David Oliva, General Manager of Organomation, sits down with Dr. David Hanigan, Associate Professor at the University of Nevada, Reno, to discuss cutting-edge PFAS research. Dr. Hanigan sheds light on efforts to break the "forever cycle" of PFAS by exploring thermal destruction processes and the challenges of ensuring complete elimination rather than creating more volatile forms. The conversation also touches on the standardized EPA methods, including EPA 1633, and the role of LC-MS in analyzing PFAS across various environmental matrices. Learn how this research aims to improve air and water quality through innovative environmental engineering approaches.</strong></p><h3><strong>Video Transcription</strong></h3><h5><strong>Interviewer: David, could you introduce yourself and your research focus?</strong></h5><p><strong>David Hanigan:</strong> I’m an associate professor at the University of Nevada, Reno. I’m trained as an environmental engineer, and today most of my work is aquatic and environmental chemistry. A big area is <strong>PFAS</strong>—<i>per- and polyfluoroalkyl substances</i>. Across drinking water, wastewater, and other media, we’re pretty good at <strong>separating and concentrating</strong> PFAS, but then what? You’ve created a concentrate and now need <strong>destruction</strong>. A major focus in my lab is understanding <strong>thermal processes</strong>—what happens during <strong>incineration</strong> and how to ensure PFAS aren’t simply transformed into smaller, more volatile PFAS and released. If they are formed, can <strong>air-pollution control devices</strong> capture and control those releases?</p><h5><strong>Interviewer: Is your work tied to standardized EPA methodologies?</strong></h5><p><strong>Dr. Hanigan:</strong> We use <strong>EPA Method 1633</strong> frequently—though not for gas-phase PFAS. 1633 is designed for <strong>aqueous, soil, and solid matrices</strong>. For <strong>gas-phase</strong> work, our setups are closer to <strong>OTM-45</strong> and <strong>OTM-50</strong> (<i>Other Test Methods</i>). That said, for most gas-phase experiments we <strong>measure online</strong>: rather than collecting with a canister as in OTM workflows, we route the <strong>furnace outlet directly to an FTIR</strong> and quantify in real time.</p><h5><strong>Interviewer: My background is drinking-water methods (533, 537, 1633). How do matrices affect method choice and prep?</strong></h5><p><strong>Dr. Hanigan:</strong> <strong>EPA 537</strong> is <strong>drinking water only</strong>—EPA really doesn’t intend it to be “modified 537 for wastewater.” Methods are matrix-specific. <strong>1633</strong> is broader and explicitly covers <strong>multiple matrices</strong> (e.g., wastewater and solids), so we use that when applicable.</p><h5><strong>Interviewer: You recently installed a new LC-MS. How’s it going, and how will you prep samples?</strong></h5><p><strong>Dr. Hanigan:</strong> Good! We brought on a part-time technician/research scientist with extensive LC-MS experience; he’s been going through manufacturer training. It’s great having a <strong>new instrument under warranty and service contract</strong>. For most PFAS work that falls within a defined method, we expect to use <strong>EPA 1633</strong>. We also analyze <strong>short-chain PFAS combustion byproducts</strong>—those may fall <strong>outside</strong> current EPA methods, so we’ll tailor workflows accordingly.</p><h5><strong>Interviewer: Anything you’d like readers to keep in mind about PFAS and destruction research?</strong></h5><p><strong>Dr. Hanigan:</strong> Think beyond removal. <strong>Concentration without destruction</strong> just moves PFAS around. We need to validate that <strong>thermal destruction</strong> actually <strong>minimizes formation</strong> of undesirable gas-phase PFAS and that <strong>downstream controls</strong> capture what’s produced. Our <strong>online FTIR</strong> approach helps reveal what’s really happening in the stack in <strong>real time</strong>.</p><h4><strong>Key takeaways</strong></h4><ul><li><strong>Removal isn’t enough:</strong> Concentrated PFAS require <strong>verified destruction</strong> pathways.</li><li><strong>Thermal processes under scrutiny:</strong> Incineration must avoid forming/releasing more volatile PFAS; <strong>air-pollution controls</strong> are critical.</li><li><strong>Method matters:</strong> <strong>EPA 537</strong> = drinking water only; <strong>EPA 1633</strong> = broader matrices (aqueous/soil/solids). <strong>OTM-45/50</strong> guide <strong>gas-phase</strong> sampling—but Hanigan’s team often measures <strong>online via FTIR</strong>.</li><li><strong>LC-MS readiness:</strong> New platform supports <strong>EPA 1633</strong> workflows and exploratory analysis of <strong>combustion byproducts</strong> outside current methods.</li></ul><blockquote><p><strong>This text has been automatically transcribed from a video presentation using AI technology. It may contain inaccuracies and is not guaranteed to be 100% correct.</strong></p></blockquote><blockquote><h4><strong>Concentrating on Chromatography Podcast</strong></h4><p>Dive into the frontiers of chromatography, mass spectrometry, and sample preparation with host David Oliva. Each episode features candid conversations with leading researchers, industry innovators, and passionate scientists who are shaping the future of analytical chemistry. From decoding PFAS detection challenges to exploring the latest in AI-assisted liquid chromatography, this show uncovers practical workflows, sustainability breakthroughs, and the real-world impact of separation science. Whether you’re a chromatographer, lab professional, or researcher you'll discover inspiring content!</p><p>You can find <strong>Concentrating on Chromatography Podcast </strong>in podcast apps:</p><ul><li><a target="_blank" rel="noopener noreferrer" href="https://open.spotify.com/show/1wZg67rCjoGju4yhqxI3tL"><strong>Spotify</strong></a></li><li><a target="_blank" rel="noopener noreferrer" href="https://podcasts.apple.com/tz/podcast/concentrating-on-chromatography/id1788429185"><strong>Apple podcast</strong></a></li><li><a target="_blank" rel="noopener noreferrer" href="https://podscan.fm/podcasts/concentrating-on-chromatography"><strong>podscan</strong></a></li></ul><p>and on <a target="_blank" rel="noopener noreferrer" href="https://www.youtube.com/@ChromatographyTalk/videos"><strong>YouTube channel</strong></a></p></blockquote>

Breaking the Forever Cycle: PFAS Destruction & EPA Methodologies with Dr. David Hanigan

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Akademie věd České republiky (AV ČR) vznikla v roce 1992 jako nástupce někdejší Československé akademie věd. V současnosti ji tvoří komplex 54 veřejných výzkumných institucí.

Akademie věd České republiky

Centrum je samostatným ústavem Přírodovědecké fakulty Masarykovy univerzity, který realizuje výzkum, vývoj, výuku a expertní činnost v oblasti znečištění prostředí toxickými látkami. Předmětem zájmu jsou především perzistentní organické polutanty (POPs), polární organické látky, toxické kovy a jejich specie, přírodní toxiny (cyanotoxiny).

RECETOX - Centrum pro výzkum toxických látek v prostředí

Je výzkumné centrum zaměřené na oblast živých věd, pokročilých materiálů a technologií.  Vznikl v roce 2011 na základech šesti významných brněnských univerzit a výzkumných institucí. Od doby jeho nedávného vzniku se daří budovat významné vědecké centrum, a již nyní se řadí mezi špičkové evropské instituce.

CEITEC

Ústav pro nanomateriály, pokročilé technologie a inovace Technické univerzity v Liberci, známý také jako CXI TUL, byl založen v roce 2009. Naším posláním je podporovat dlouhodobou vizi TUL v oblasti spolupráce s průmyslem a vytváření inovací.

CXI TUL

Společnost Organomation, založená v roce 1959, navrhuje a vyrábí vysoce kvalitní dusíkové koncentrátory a extrakční systémy. Jejich laboratorní přístroje, známé svou inovativností a odolností, se používají po celém světě pro efektivní přípravu vzorků a jsou doprovázeny silnou zákaznickou podporou.

Organomation

Watrex Praha je přední český výrobce a distributor systémů a příslušenství zejména pro kapalinovou chromatografii. Distribuujeme produkty mnoha chemických firem a máme vlastní řadu systémů za rozumnou cenu.

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