Category: Chemistry

Researchers at North Carolina State University have developed a stretchable strain sensor that has an unprecedented combination of sensitivity and range, allowing it to detect even minor changes in strain with greater range of motion than previous technologies. The researchers demonstrated the sensor’s utility by creating new health monitoring and human-machine interface devices.

Their research paper, “Highly Sensitive, Stretchable, and Robust Strain Sensor Based on Crack Propagation and Opening,” is published in the journal ACS Applied Materials & Interfaces.

Strain is a measurement of how much a material deforms from its original length. For example, if you stretched a rubber band to twice its original length, its strain would be 100%.

“And measuring strain is useful in many applications, such as devices that measure blood pressure and technologies that track physical movement,” says Yong Zhu, corresponding author of a paper on the work and the Andrew A. Adams Distinguished Professor of Mechanical and Aerospace Engineering at NC State.

“But to date there’s been a trade-off. Strain sensors that are sensitive—capable of detecting small deformations—cannot be stretched very far. On the other hand, sensors that can be stretched to greater lengths are typically not very sensitive. The new sensor we’ve developed is both sensitive and capable of withstanding significant deformation,” says Zhu. “An additional feature is that the sensor is highly robust even when over-strained, meaning it is unlikely to break when the applied strain accidently exceeds the sensing range.”

The new sensor consists of a silver nanowire network embedded in an elastic polymer. The polymer features a pattern of parallel cuts of a uniform depth, alternating from either side of the material: one cut from the left, followed by one from the right, followed by one from the left, and so on.

“This feature—the patterned cuts—is what enables a greater range of deformation without sacrificing sensitivity,” says Shuang Wu, who is first author of the paper and a recent Ph.D. graduate at NC State.

The sensor measures strain by measuring changes in electrical resistance. As the material stretches, resistance increases. The cuts in the surface of the sensor are perpendicular to the direction that it is stretched. This does two things. First, the cuts allow the sensor to deform significantly. Because the cuts in the surface pull open, creating a zigzag pattern, the material can withstand substantial deformation without reaching the breaking point. Second, when the cuts pull open, this forces the electrical signal to travel further, traveling up and down the zigzag.

“To demonstrate the sensitivity of the new sensors, we used them to create new wearable blood pressure devices,” Zhu says. “And to demonstrate how far the sensors can be deformed, we created a wearable device for monitoring motion in a person’s back, which has utility for physical therapy.”

“We have also demonstrated a human-machine interface,” Wu says. “Specifically, we used the sensor to create a three-dimensional touch controller that can be used to control a video game.”

“The sensor can be easily incorporated into existing wearable materials such as fabrics and athletic tapes, convenient for practical applications,” Zhu says. “And all of this is just scratching the surface. We think there will be a range of additional applications as we continue working with this technology.”

The paper was co-authored by Katherine Moody, a Ph.D. student at NC State; and by Abhiroop Kollipara, a former undergraduate at NC State.

More information: Shuang Wu et al, Highly Sensitive, Stretchable, and Robust Strain Sensor Based on Crack Propagation and Opening, ACS Applied Materials & Interfaces (2022). DOI: 10.1021/acsami.2c16741

Journal information: ACS Applied Materials and Interfaces 

Provided by North Carolina State University 

Ammonia (NH3) is an important fertilizer and chemical for human society; however, its production by the traditional Haber-Bosch process consumes substantial fossil fuel energy and produces massive carbon dioxide emissions. Powered by renewable energy, electrocatalytic reduction of nitrogen (N2) to NH3 under eco-friendly and mild conditions provides a highly attractive solution for carbon neutrality.

Despite recent significant progress, electrocatalytic nitrogen reduction reaction (eNRR) still suffers from limited selectivity and activity. This is due to the super-stability of N≡N triple bond. Theoretical and experimental efforts have demonstrated that the electrocatalysts always face a significant challenge to effectively activate N2 and accomplish the first protonation of N2 to form NNH* in the rate-determining step (RDS).

One strategy to break the above limitation of eNRR is to involve multi-reaction sites in catalytic reactions, just like the catalytically active sites in talented metalloenzymes. For instance, in Fe nitrogenase, the S atom adjacent to the Fe center functions as a co-catalytic site to bind protons (H), which electrostatically activates the N2 molecule adsorbed by the Fe center to the optimum state and provides H for the hydrogenation of N2.

Such a close collaboration between the metal center and its coordination atoms enables the nitrogenase to achieve ultrahigh activity and selectivity. Therefore, one can expect that the synergetic work of multiple catalytic sites on the catalyst surface can significantly enhance the activity and selectivity of eNRR.

Recently, a research team led by Prof. Tao Ling from Tianjin University, China, proposed to realize a synergetic work of multi-reaction sites to overcome the limitation of sustainable NH3 production. Herein, using ruthenium-sulfur-carbon (Ru-S-C) catalyst as a prototype, the researchers showed that the Ru/S dual-site cooperated to catalyze eNRR at ambient conditions.

With the combination of theoretical calculations, in situ Raman spectroscopy, and experimental observation, the researchers demonstrated that such Ru/S dual-site cooperation greatly facilitated the activation and first protonation of N2 in the rate-determining step of eNRR. As a result, Ru-S-C catalyst exhibited significantly enhanced eNRR performance compared with the routine Ru-N-C catalyst via a single-site catalytic mechanism.

The specifically designed dual-site collaborative catalytic mechanism could offer new opportunities for advancing sustainable NH3 production.

The results were published in Chinese Journal of Catalysis..

More information: Liujing Yang et al, Dual-site collaboration boosts electrochemical nitrogen reduction on Ru-S-C single-atom catalyst, Chinese Journal of Catalysis (2022). DOI: 10.1016/S1872-2067(22)64136-6

Provided by Chinese Academy of Sciences

Researchers have developed a transparent temperature sensor capable of precisely and quickly measuring temperature changes caused by light. This technology is expected to contribute to the advancement of various applied bio devices that rely on sensitive temperature changes.

The photothermal effect using plasmonic nanomaterials has recently been widely proposed in various bio-application fields, such as brain nerve stimulation, drug delivery, cancer treatment, and ultra-high-speed PCR due to its unique heating properties using light. However, measuring temperature changes by photothermal phenomena still relies on an indirect and slow measurement method using a thermal imaging camera, leading to the limitation that it is not suitable for local temperature measurement at the level of a single cell, which changes rapidly at the level of several milliseconds to tens of micrometers.

Due to the absence of precise information on temperature changes, photothermal effect technology has raised concerns about the understanding of biological changes and stable clinical application resulting from precise temperature changes, despite the spreading effect of its application.

Accordingly, the joint research team, which included Professor Kang Hong-gi of the Department of Electrical Engineering and Computer Science at DGIST and Dr. Chung Seung-jun of the Soft Hybrid Materials Research Center at KIST, developed a temperature sensor technology that can measure even rapid temperature changes in less than a few milliseconds by using the thermoelectric effect, in which a voltage signal is generated by rapid charge transfer triggered by a difference in temperature.

In particular, the team established a direct photothermal phenomenon measurement technology with reduced interference by light utilizing an organic thermoelectric layer of transparent PEDOT:PSS, a conductive polymer suitable for storing charges.

The 50-nanometer thin PEDOT:PSS thermoelectric sensor secures high transparency at 97% on average in the visible light zone and can be directly applied to the area of photothermal phenomenon, minimizing light interference for various photothermal bioengineering and medical applications. In addition, since a low-temperature solution process could be used for the polymer thermoelectric material used, it was prepared using an inkjet printing process, which is simpler to manufacture than a general semiconductor process, with a high degree of design freedom thus giving it an advantage in the printing process.

The transparent thermoelectric temperature sensor technology developed through this study can be used to understand the mechanism of the optical neural interface for controlling brain activity using light, which has recently been known broadly through optogenetics. It is a key technology in that it can be utilized to analyze the principles in treating cancer cells with local high heat. In addition, it is expected that it can be applied to next-generation semiconductor technologies, such as wearable devices, transparent display devices, and analysis of local deterioration of power semiconductors, based on the principle of powerless operation.

DGIST Department of Electrical Engineering and Computer Science Professor Kang Hong-gi said, “It is significant in that we proposed a technology that directly and precisely measures the photothermal effect, the biggest advantage of which is rapid generation of local heat,” and added, “We look forward to the possibility of in-depth bioengineering analysis and biomedical application by combining it with various bio-electronic chips through micro-semiconductor processes in the future.”

The study was published online in Materials Horizons,

More information: Junhee Lee et al, High temporal resolution transparent thermoelectric temperature sensors for photothermal effect sensing, Materials Horizons (2022). DOI: 10.1039/D2MH00813K

Journal information: Materials Horizons 

Provided by DGIST (Daegu Gyeongbuk Institute of Science and Technology)

Real-world technology is often foretold by science fiction. In 1927, characters in the film Metropolis made video calls to each other. Star Trek creator Gene Roddenberry hung flat-screen color monitors on the walls of the Enterprise decades before we did the same in our living rooms.

The most obvious examples of technology in science fiction tend to focus on artificial intelligence, communication and transport. But futuristic chemistry is embraced by sci-fi writers too. For example, a central feature of Aldous Huxley’s 1932 novel Brave New World is a chemical antidepressant.

In recent years we’ve seen incredible leaps in chemical technologies—to the point where, as a chemist, I’m frequently reminded of some of my favorite fiction while reading about the latest big developments.

A plastic world

While environmental issues are a common thread in science fiction, not many deal with the blight of plastics. An exception is the 1972 novel Mutant 59: The Plastic Eaters. This story, featuring a bacteria that digests plastic, would have seemed far fetched a few years ago. After all, plastics have only been around for 80 years or so, which hardly seems long enough for nature to evolve a mechanism to eat them.

Yet plastics are carbon-based compounds, in many ways similar to natural polymers such as collagen (in animals), cellulose (in plants) and bee waxes. Over eons, bacteria and fungi have evolved many biochemical tools to scavenge the carbon from every dead organism.

So maybe it shouldn’t have been a surprise when, in 2016, scientists sifting through a recycling plant in Kyoto, Japan discovered a bacteria literally feeding on plastic bottles. Since then, several other research groups have isolated the digestive enzymes involved and engineered them to be more efficient. The hope is we can use these modified natural systems to clean up our plastic mess.

The most recent attempts to do so have a distinctly futuristic feel. A group in Austin, Texas fed the digestive enzymes’ structure into a neural network. This artificial intelligence predicted the best parts of the enzyme to tweak to increase its efficiency. With the AI’s advice, the group produced an enzyme that completely degraded a plastic punnet in just a couple of days.

Chemical engineers are already developing large-scale recycling plants using bacteria. The bacteria in Mutant 59 was also engineered in a lab—but let’s hope the parallel stops there. In the novel, the bacteria escapes and causes devastation as it rips through our world, rotting the plastic infrastructure that holds society together.

Dishing up science fiction

From William Gibson’s Neuromancer to the Expanse series, vat-grown meat is a common trope of science fiction. Characters are rarely content with the results, frequently complaining about how synthetic meat is a poor substitute for the real thing.

Many fake meats already line our supermarket shelves, but most are formed from plant-based ingredients blended to mimic the taste and texture of flesh. As a vegetarian, I actually quite enjoy them. But they are easily distinguishable from the real meat of my memories.

Growing meat in a vat is a different affair. It is more like brewing, but using animal cells instead of yeast. The process needs people with a good understanding of cell biology, nutritional chemistry and chemical engineering to work.

The process begins by growing a dense broth of cells. The mix of nutrients within the vat is changed, triggering the cells to differentiate into tissue types—muscle, connective tissue, fat cells. Finally, the cells coalesce into something resembling a pulp of meat, which is harvested and processed into your nuggets, burgers and such like. The advantage, of course, is that you get something with the texture, taste and nutritional content of meat, but without the slaughter.

Back in 2013, the first edible burger made this way cost $300,000. Nine years later, costs have plummeted and investors have in poured billions of dollars. The industry is poised to start selling its products, and is just waiting for the regulatory frameworks to be put in place. Singapore led the way in approving cultured meat in 2021, the US Food and Drug Administration recently gave its seal of approval, and UK and EU regulators are not far behind.

A word of caution

However, sometimes aspirations of real-world science struggle to progress from their fictional inspiration. In 2003 Elizabeth Holmes, aged only 19, founded Theranos. Ten years later, the company was worth $10 billion.

Holmes raised the funds with her promise to deliver a revolutionary technology that could deliver cheap, rapid diagnostics from just a drop of blood. The idea seemed closer to the medical scanners in Star Trek sickbays than anything in reality. And it turned out the promises made by Holmes were criminally over-inflated, earning her an 11-year prison sentence for fraud.

The Theranos story may have set back investors’ confidence in plausible applications for the lab-on-a-chip technologies that Holmes championed. But we are actually quite familiar with them already, in the form of COVID lateral flow tests. An even more extraordinary, real example reminded me of the almost-instant DNA sequencing depicted in the 1997 film Gattaca.

Early in 2022 at Stanford University, a small group of researchers sequenced an entire human genome in just over five minutes. Contrast that to the 13 years it took to sequence the first human genome, published in 2003. This could help speed up rare disease diagnosis from years to hours.

These astounding leaps forward in diagnostics, recycling and food are just a few areas of chemistry that were once considered science fiction. Many others—such as high-density batteries allowing quicker and fewer charges, atmospheric cleaning technology to remove C0₂ from the air, and 3D “printed” personalized medication—are also under development. Let’s just hope the dystopias so often depicted in science fiction don’t emerge alongside the technologies they describe.

Provided by The Conversation 

This article is republished from The Conversation under a Creative Commons license. Read the original article.

While conducting an otherwise straightforward investigation into the assembly mechanism of calcium-phosphate clusters, researchers at UC Santa Barbara and New York University (NYU) made a surprising discovery: Phosphate ions in water have a curious habit of spontaneously alternating between their commonly encountered hydrated state and a mysterious, previously unreported ‘dark’ state.

This recently uncovered behavior, they say, has implications for understanding the role of phosphate species in biocatalysis, cellular energy balance and the formation of biomaterials. Their findings are published in the Proceedings of the National Academy of Sciences

“Phosphate is everywhere,” said UCSB chemistry professor Songi Han, one of the authors of a paper in the Proceedings of the National Academy of Sciences. The ion consists of one phosphorus atom surrounded by four oxygen atoms. “It’s in our blood and in our serum,” Han continued. “It’s in every biologist’s buffer, it’s on our DNA and RNA.” It’s also a structural component of our bones and cell membranes, she added.

When bound with calcium, phosphates form small, molecular clusters on their way toward forming mineral deposits in cells and bone. That’s what Han and collaborators Matthew Helgeson at UCSB and Alexej Jerschow at NYU were preparing to study and characterize, in hopes of uncovering quantum behaviors in symmetric phosphate clusters proposed by UCSB physics professor Matthew Fisher. But first, the researchers had to set up control experiments, which involved scans of phosphate ions in the absence of calcium via nuclear magnetic resonance (NMR) spectroscopy and cryogenic transmission electron microscopy (cryo-TEM).

But as the UCSB and NYU students on the project were collecting reference data, which involved the naturally occurring isotope phosphorus 31 in aqueous solutions at varying concentrations and temperatures, their results didn’t match up with expectations. For instance, Han said, the line that represents the spectrum for 31P during NMR scans is supposed to narrow with increasing temperatures.

“The reason is, as you go to higher temperatures, the molecules tumble faster,” she explained. Typically, this rapid molecular motion would average out the anisotropic interactions, or interactions that are dependent on the relative orientations of these small molecules. The result would be a narrowing of resonances measured by the NMR instrument.

“We were expecting a phosphorus NMR signal, which is a simple one, with a peak that narrows with higher temperatures,” she said. “Surprisingly, though, we measured spectra that were broadening, doing the complete opposite of what we expected.”

This counterintuitive result set the team on a new path, following experiment after experiment to determine its molecular-level cause. The conclusion, after a year of eliminating one hypothesis after another? Phosphate ions were forming clusters under a wide range of biological conditions—clusters that were evading direct spectroscopic detection, which is likely why they had not been observed before. Furthermore, the measurements suggested these ions were alternating between a visible “free” state and a dark “assembled” state, hence the broadening of the signal instead of a sharp peak.

Additionally, as the temperature increased, the number of these assembled states was also increasing, another temperature-dependent behavior, according to co-lead author Mesopotamia Nowotarski.

“The conclusion from those experiments was that the phosphates are dehydrating and that allows them to come closer together,” she said. At lower temperatures, the vast majority of these phosphates in solution cling to water molecules that form a protective water coat around them. This hydrated state is typically assumed when considering how phosphate behaves in biological systems.

But at higher temperatures, Nowotarski explained, they shed their water shields, allowing them to stick to each other. This concept was confirmed by NMR experiments that probed the phosphate water shell, and further validated by analysis of cryo-TEM images to identify the existence of clusters, as well as modeling the energetics of phosphate assembly by co-lead author Joshua Straub.

These dynamic phosphate assemblies and hydration shells have important implications for biology and biochemistry, according to the researchers. Phosphate, said chemical engineer Matthew Helgeson, is a commonly understood “currency” used in biological systems to store and consume energy through conversion into adenosine triphosphate (ATP) and adenosine diphosphate (ADP).

“If hydrated phosphate, ADP and ATP represent small ‘bills’ of currency, this new discovery suggests that these smaller currencies can exchange with much larger denominations—say $100—which may have very different interactions with biochemical processes than currently known mechanisms,” he said.

Also, many biomolecular components include phosphate groups that may, similarly, form clusters. Hence, the finding that these phosphates can spontaneously assemble might shed some light on other fundamental biological processes such as biomineralization—how shells and skeletons form, as well as protein interactions.

“We also tested a range of phosphates, including those incorporated into the ATP molecule, and they all appear to show the same phenomenon, and we achieved quantitative analysis for these assemblies,” said co-lead author Jiaqi Lu.

This once overlooked process could also be significant in the realms of cell signaling, metabolism and disease processes such as Alzheimer’s disease, where the attachment of a phosphate group, or phosphorylation, to the protein tau in our brain is commonly found in neurofibrillary tangles—a hallmark of neurodegeneration. Having seen and studied this assembly behavior, the team is now digging deeper, with studies on the effect of pH on phosphate assembly, genetic translation and modified protein assembly, as well as their original work on calcium phosphate assembly.

“It really changes the way we think about the role of phosphate groups that we typically don’t consider a driver of molecular assembly,” Han said.

More information: Joshua S. Straub et al, Phosphates form spectroscopically dark state assemblies in common aqueous solutions, Proceedings of the National Academy of Sciences (2022). DOI: 10.1073/pnas.2206765120

Journal information: Proceedings of the National Academy of Sciences 

Provided by University of California – Santa Barbara 

X-ray diffraction (XRD) is an experimental technique to discern the atomic structure of a material by irradiating it with X-rays at different angles. Essentially, the intensity of the reflected X-rays becomes high at specific irradiation angles, producing a pattern of diffraction peaks. An XRD serves as a fingerprint for a material since each substance produces a unique pattern.

In research and development, changes in XRDs are used to identify the positions and amounts of additional elements that need to be added to fine-tune a material to help enhance a desired functional property, say, energy storage efficiency in batteries.

However, the peak changes in XRDs are barely discernible to humans. This makes ascertaining the features and relevance of different peaks for material characterization difficult. To this end, a group of Japanese researchers, led by Professor Ryo Maezono from the Japan Advanced Institute of Science and Technology (JAIST), applied a Deep Learning technique called “auto-encoder” to the problem to find hidden regularities in XRDs that could help accelerate the development of new functional materials.

The research team also included Associate Professor Kenta Hongo and Assistant Professor Kousuke Nakano from JAIST. Their work has been published in Advanced Theory and Simulations.

Explaining the fundamentals of the auto-encoder technique, Prof. Maezono says, “The auto-encoder technique captures data features by expressing them as points on a two-dimensional plane (feature space). Based on their scatter, the points get grouped to coarse-grain information. The auto-encoder compresses the data dimension and can efficiently capture the multifaceted XRD pattern analysis in a two-dimensional plane.”

Using a neural network, the researchers applied the auto-encoder to 150 XRD patterns of magnetic alloys with different concentrations. In the feature space, each XRD is projected to a single point. These points form clusters, in which similar materials with similar constituent concentrations are placed closer together. Thus, the distance between the points in the feature space allows the estimation of the concentration of any given sample alloy. This also permits the fine-tuning of alloys by indirectly identifying the XRD peaks that change when new elements are added to an alloy or its constituent element ratios are altered.

The researchers further proposed a novel application of the feature space. When a peak of interest is masked on the original XRD pattern, the point on the feature space shifts. The extent of the shift helps distinguish how relevant a peak is to capturing the properties of a material. Using this technique, the researchers were able to identify which peak is actually relevant to be watched out for estimating the amount of doping etc.—something that could not have been predicted by a human but was revealed using Deep Learning.

The researchers also proposed the application of the auto-encoder for the generation of artificial XRD patterns by interpolating existing ones to handle tiny changes in alloy compositions. The approach would generate plausible datasets, avoiding computationally expensive ab initio simulations.

“The results of this research are not limited to XRD peak patterns. Rather, they provide a general Deep Learning technique that can be used to extract features from material science data. Its framework can find hidden regularity in nature that is not identifiable by humans and is expected to serve as a powerful tool for theorem discovery through data science,” says Prof. Maezono.

The application of the described auto-encoder could accelerate the development of high efficiency, low cost, and low environmental impact materials, ushering in a new era of Deep Learning-based materials science research.

More information: Keishu Utimula et al, Feature Space of XRD Patterns Constructed by an Autoencoder, Advanced Theory and Simulations (2022). DOI: 10.1002/adts.202200613

Provided by Japan Advanced Institute of Science and Technology

Researchers at the U.S. Department of Energy’s (DOE) Institute for Cooperative Upcycling of Plastics (iCOUP) have developed a new method for recycling high-density polyethylene (HDPE).

Using a novel catalytic approach, scientists at DOE’s Argonne National Laboratory and Cornell University converted post-consumer HDPE plastic into a fully recyclable and potentially biodegradable material with the same mechanical and thermal properties of the starting single-use plastic. Their paper describing the results was published December 16 in the Journal of the American Chemical Society.

HDPE is ubiquitous in single-use applications because it is strong, flexible, long-lasting and inexpensive. But the ways we produce and dispose of HDPE pose serious threats to our own health and that of our planet.

Many HDPE products are produced from fossil fuels, and most post-consumer HDPE is either incinerated, dumped in landfills or lost in the environment. When it is recycled with current methods, the quality of the material degrades.

This new approach could reduce carbon emission and pollution associated with HDPE by using waste plastic as untapped feedstock and transforming it into a new material that can be recycled repeatedly without loss of quality.

Current HDPE recycling approaches yield materials with inferior properties. The team’s alternative approach uses a series of catalysts to cleave the polymer chains into shorter pieces that contain reactive groups at the ends. The smaller pieces can then be put back together to form new products of equal value. The end groups have the added benefit of making the new plastic easier to decompose, both in the lab and in nature.

More information: Alejandra Arroyave et al, Catalytic Chemical Recycling of Post-Consumer Polyethylene, Journal of the American Chemical Society (2022). DOI: 10.1021/jacs.2c11949

Journal information: Journal of the American Chemical Society 

Provided by Argonne National Laboratory 

One of the major obstacles that those conducting research on carbohydrates are constantly working to overcome is the limited array of tools available to decipher the role of sugars. As a workaround, most researchers utilize lectins (sugar-binding proteins) isolated from plants or fungi, but they are large, with weak binding, and they are limited in their specificity and in the scope of sugars that they detect.

In a new study published in ACS Chemical Biology, researchers in Professor Barbara Imperiali’s group have developed a platform to address this shortcoming.

“The challenge with polymers of carbohydrates is that their biosynthesis is not template-driven,” says Imperiali, the senior author of the study and a professor in the departments of Chemistry and Biology. “Biology, medicine, and biotechnology have been fueled by technological advancements for proteins and nucleic acids. The carbohydrate field lags terribly behind and is desperately seeking tools.”

Identifying carbohydrate-binding proteins

Biosynthesizing carbohydrates requires every link between individual sugar molecules to be made by a particular enzyme, and there’s no ready way to decipher the structures and sequences of complex carbohydrates. Antibodies to carbohydrates can be generated, but doing so is challenging, expensive, and results in a molecule that is far larger than what is really needed for the research.

An ideal resource for this field plagued with limited mechanisms would be discovery of binding proteins, of limited size, that recognize small chunks of carbohydrates to piece together a structure by using those binders, or methods to detect and identify particular carbohydrates within complicated structures.

The authors of this study used directed evolution and clever screen design to identify carbohydrate-binding proteins from proteins that have absolutely no ability to bind carbohydrates at all. Their findings lay the groundwork for identifying carbohydrate-binding proteins with diverse and programmable specificity.

Streamlining for collaboration

This advance will allow researchers to go after a user-defined sugar target without being limited by what a lectin does, or challenged by the abilities of generating antibodies. These results could serve to inspire future collaborations with engineering communities to maximize the efficiency of glycobiology’s yeast surface display pipeline. As it is, this pipeline works well for proteins, but sugars are far more difficult targets and require the pipeline to be modified.

In terms of future applications, the potential for this innovation ranges from diagnostic to, in the longer term, therapeutic, and paves the way for collaborations with researchers at MIT and beyond. For example, chemistry Professor Laura Kiessling’s research group works with Mycobacterium tuberculosis (Mtb), which has an unusual cell wall composition with unique, distinct, and exclusive sugars. Using this method, a binder could potentially be evolved to that particular feature on Mtb.

Chemical engineering Professor Hadley Sikes develops paper-based diagnostic tools where the binding partner for a particular epitope or marker is laid down, and with the use of this discovery, in the longer term, a lateral flow assay device could be developed.

Laying the groundwork for future solutions

In cancer, certain sugars are overrepresented on cell surfaces, so theoretically, researchers can utilize this finding, which is also amenable to labeling, to develop a tool out of the evolved glycan binder for detection.

This discovery also stands to contribute significantly to improving cell imaging. Researchers can modify binders with a fluorophore using a simple ligation strategy, and can then choose the best fluorophore for tissue or cell imaging. The Kiessling group, for example, could apply small protein binders labeled with fluorophore to detect bacterial sugars to initiate fluorescence-activated cell sorting to probe a complex mixture of microbes.

This could in turn be used to determine how a patient’s microbiome has been disturbed. It also has the potential to screen the microbiome of a patient’s mouth or their upper or lower gastrointestinal tract to read out the imbalance within the community using these types of reagents. In the more distant future, the binders could potentially have therapeutic purposes like clearing the gastrointestinal tract or mouth of a particular bacterium based on the sugars that the bacterium displays.

More information: Elizabeth M. Ward et al, Engineered Glycan-Binding Proteins for Recognition of the Thomsen–Friedenreich Antigen and Structurally Related Disaccharides, ACS Chemical Biology (2022). DOI: 10.1021/acschembio.2c00683

Journal information: ACS Chemical Biology 

Provided by Massachusetts Institute of Technology 

Coal tar, once considered waste, has become a huge treasure trove because hundreds of compounds can be isolated from it. Most of these compounds tend to be aromatic hydrocarbons, polycyclic aromatic hydrocarbons, and heterocyclic compounds.

Carbazole and anthracene, two aromatic hydrocarbon components contained in coal tar, are used as essential organic intermediates to synthesize various carbazole derivatives and anthraquinones. The effective separation of carbazole and anthracene takes advantage of their different solubility in solvents. In this process, solvent screening and performance optimization are essential, and their optimization mainly follows the principle of trial and error. Thus, it is necessary to use a versatile detection technique for understanding this separation process on the molecular level.

N,N-Dimethylformamide (DMF) has been developed as an efficient solvent for carbazole and anthracene separation due to the high solubility of carbazole in DMF; moreover, researchers have found that the separation of carbazole and anthracene may benefit from an intermolecular hydrogen bond between carbazole and DMF. However, there was no detailed study concerning the interaction mechanism between carbazole/anthracene and a solvent capable of hydrogen bonding. It is important to use a versatile detection technique for analyzing hydrogen bond interaction, and hence to explain the interaction mechanism between carbazole/anthracene and DMF via hydrogen bonding on the molecular level.

Recently, the group of Yan Qiao, a professor of the State Key Laboratory of Coal Conversion, Institute of Coal Chemistry, CAS, studied the intermolecular interaction mechanism between DMF and carbazole/anthracene by various advanced liquid state NMR techniques. They observed that the N-H chemical shift of carbazole changed significantly in 1H NMR titration and VT-NMR experiments, indicating strong intermolecular hydrogen bonds between carbazole and DMF, which was further supported by the decrease in molecular self-diffusion coefficients (D) of both carbazole and DMF according to diffusion-ordered spectroscopy (DOSY) measurements.

Moreover, the Nuclear Overhauser Effect Spectroscopy (NOESY) experiment revealed that the distance between the aldehydic hydrogen of DMF and the N-H of carbazole was smaller than 5 Å. Accordingly, an intermolecular hydrogen bond between carbazole and DMF in the form of C=O···H-N was proposed.

“Solvent screening is still lacking theoretical guidance, with most work on the basis of ‘like dissolves like’ and lacks direct spectroscopic evidence,” Qiao said, “Our research helps researchers to understand the interaction mechanism between carbazole/anthracene and DMF in this process from the molecular and even atomic levels. It will also guide the further expansion of alternative solvent media and optimization of separation processes, and play an important role in promoting the development of coal tar separation industry.”

This research is published in the journal Industrial Chemistry & Materials.

More information: Hui Cao et al, Understanding the interaction mechanism of carbazole/anthracene with N,N-dimethylformamide: NMR study substantiated carbazole separation, Industrial Chemistry & Materials (2022). DOI: 10.1039/D2IM00020B

Provided by Institute of Process Engineering, Chinese Academy of Sciences

Genetic information encoded in genomic DNA is transcribed to mRNAs and then the codons on mRNA are decoded by transfer RNAs (tRNAs) during protein synthesis. tRNAs deliver amino acids to ribosomes and proteins are synthesized from the amino acids on the ribosomes according to the decoded genetic information. Therefore, tRNA plays a key role during the translation of genetic information.

tRNAs contain numerous modified nucleosides, which regulate the accuracy and efficiency of protein synthesis. Modified nucleosides in tRNA are synthesized by tRNA modification enzymes. Therefore, unveiling the mechanisms by which tRNA modification enzymes selectively recognize substrate tRNAs from non-substrate RNAs; the when, where, and how many tRNAs are being modified by the modification enzymes, is of crucial importance to understand the protein synthesis machinery.

Addressing these key questions is, however, challenging due to the lack of a high-throughput technique that identifies the characteristic properties of tRNA modification enzymes.

To overcome this issue, Drs. Yamagami and Hori at Ehime University applied next-generation DNA sequencing technology to functional analyses of tRNA modification enzymes and developed a new high-throughput assay method, “tRNA-MaP.”

The tRNA-MaP technique can rapidly screen an RNA pool consisting of more than 5,000 RNA species and identify the substrate tRNAs of the target tRNA modification enzyme(s) with comparative sensitivity to already-established methods. By tRNA-MaP, in combination with protein orthology analyses, the researchers predicted numerous natural modifications in Geobacillus stearothermophilus tRNAs.

Furthermore, they analyzed the substrate recognition mechanism of G. stearothermophilus tRNA m¹A22 methyltransferase (TrmK), which methylates adenosine at position 22 to 1-methyladenosine (m¹A22) in tRNA, using tRNA-Map. Mutation profiling has revealed that TrmK selects a subset of tRNAs for the substrate.

Using 240 variants of G. stearothermophilus tRNA^Leu transcripts, the researchers found that U8, A14, G15, G18, G19, U55, Purine57 and A58 are important for the methylation by TrmK. In addition, based on the recognition sites in tRNA and the crystal structure of TrmK, a docking model between TrmK and tRNA has been constructed.

This study, now published in the Journal of Biological Chemistry, revealed that tRNA-Map is applicable for the analysis of the tRNA modification enzyme. Notably, because tRNA-Map can analyze any RNA molecular species from any organism, even DNA molecules, tRNA-Map can be used for analysis of all nucleic acid-related proteins except for tRNA modification enzymes. Thus, tRNA-Map can accelerate the integrative understanding of the flow of genetic information.

More information: Ryota Yamagami et al, Application of mutational profiling: New functional analyses reveal the tRNA recognition mechanism of tRNA m1A22 methyltransferase, Journal of Biological Chemistry (2022). DOI: 10.1016/j.jbc.2022.102759

Journal information: Journal of Biological Chemistry 

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