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Fighting Antibiotic Resistance with Peptide Cocktails

Fighting Antibiotic Resistance with Peptide Cocktails

22 July, 2024

 

Antibiotics are crucial in modern medicine, but their widespread use has led to antibiotic-resistant bacteria, posing a serious public health threat. A new study highlights the potential of random antimicrobial peptide mixtures to significantly reduce the risk of resistance evolution compared to single peptides. These findings support the development of new antimicrobial strategies, emphasizing the need for innovative solutions to outpace bacterial resistance and safeguard public health.

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Antibiotics are essential tools in modern medicine, regularly used to treat bacterial infections and prevent infections during surgery. However, the widespread use of antibiotics has led to many bacteria developing resistance, posing a significant threat to public health. A recent study published in PLOS Biology, led by Prof. Zvi Hayouka from the Institute of Biochemistry Food science and Nutrition at the Faculty of Agriculture, Food and Environment at the Hebrew University of Jerusalem, and Prof. Jens Rolff from the Freie Universität Berlin, along with postdoctoral fellow Dr. Bernardo Antunes, who was affiliated with both Hebrew University and Freie Universität Berlin, highlights the urgent need for new strategies to control bacterial infections due to the growing threat of antibiotic-resistant pathogens. Proper antibiotic use, quick diagnostics, and careful development of new antimicrobial agents, ideally less likely to select for resistance than current antibiotics, are crucial.

Antibiotic resistance is emerging as a pressing global health challenge. While individuals themselves do not become resistant to antibiotics, the bacteria causing infections can develop this resistance, leading to more difficult-to-treat illnesses. Recent data from the World Health Organization highlights the severity of this issue, with some countries reporting resistance rates as high as 42% for certain common bacterial strains. In the United States, the Centers for Disease Control and Prevention estimates that over 2 million antibiotic-resistant infections occur annually, underscoring the urgency of addressing this crisis.

The study explored whether newly developed random antimicrobial peptide mixtures can significantly reduce the risk of resistance evolution compared to single sequence antimicrobial peptides. The research team used the ESKAPE pathogen Pseudomonas aeruginosa, a model gram-negative bacterium, known for its challenging infections due to inherent resistance to many drug classes and its ability to form biofilms.

Pseudomonas aeruginosa was experimentally evolved in the presence of antimicrobial peptides or random antimicrobial peptide mixtures to assess resistance evolution and cross-resistance between treatments. The study also examined the fitness costs of resistance on bacterial growth and used whole-genome sequencing to identify mutations responsible for resistance. Additionally, changes in the pharmacodynamics of the evolved bacterial strains were analyzed.

The findings suggest that random antimicrobial peptide mixtures pose a much lower risk of resistance evolution compared to single antimicrobial peptides and mostly prevent cross-resistance to other treatments while maintaining or improving drug sensitivity. Prof. Zvi Hayouka emphasized the significance of their work, stating, "The growing threat of antibiotic-resistant bacteria demands innovative solutions. Our research on random antimicrobial peptide mixtures presents a promising approach to outpace bacterial resistance, offering a viable alternative to traditional antibiotics and safeguarding public health."

This research suggests that Pseudomonas aeruginosa can detect these antimicrobial agents but cannot develop effective resistance within 4 weeks in vitro. Additionally, these antimicrobial peptide cocktails are affordable to synthesize and have proven to be non-toxic and non-hemolytic in a mouse model with strong efficacy profiles in several mouse model of human pathogenic bacterial infection model.

The findings advocate for the use of random antimicrobial peptide cocktails over single peptides, as resistance developed in vitro against single peptides. Despite some antibiotics, like Teixobactin, initially being deemed "resistance-proof," this was later disproven, necessitating caution even with the promising results for the random peptide mixture . Further research should explore the interaction of these random peptide mixtures with the host immune system. Employing peptides that synergize with the host response could diminish dosage requirements and side effects. This approach could be a cost-effective method to reduce bacterial loads and prevent resistance.

“It will still be quite some time before we are ready for practical applications,” says Prof. Jens Rolff. “Still, our current work demonstrates the potential that these combinations have when it comes to reducing antimicrobial resistance.”

Alongside their active research, Prof. Zvi Hayouka has co-founded a company, in partnership with Hebrew University's technology transfer company, Yissum, dedicated to addressing antibiotic resistance through innovative solutions Pepticore (https://tarominnovative.com/projects/pepticore/). The company aims to develop and commercialize new antimicrobial agents less likely to select for resistance. Their approach includes using different combinations of antibiotics and exploring mixtures made up of millions of molecules to inhibit resistance. This initiative is crucial, as antibiotic-resistant pathogens are estimated to cause approximately 5 million deaths annually. Despite advances in diagnostics and prudent antibiotic prescribing, developing new drugs remains essential to combat increasingly resistant bacteria.

The research paper titled “The evolution of antimicrobial peptide resistance in Pseudomonas aeruginosa is severely constrained by random peptide mixtures” is now available in PLOS Biology and can be accessed at https://doi.org/10.1371/journal.pbio.3002692.

Researchers:

Bernardo Antunes1,2, Caroline Zanchi1, Paul R. Johnston1,3,4, Bar Maron2, Christopher Witzany5, Roland R. Regoes5, Zvi Hayouka2, Jens Rolff1,3

Institution:

  1. Freie Universita¨ t Berlin, Evolutionary Biology
  2. Institute of Biochemistry, Food Science and Nutrition, The Hebrew University of Jerusalem
  3. Berlin Centre for Genomics in Biodiversity Research
  4. University of St. Andrews, School of Medicine
  5. Institute of Integrative Biology, ETH Zurich

Funding

Freie Universität Berlin and The Hebrew University of Jerusalem Joint Berlin-Jerusalem Post-Doctoral Fellowship Program

The Hebrew University of Jerusalem is Israel's premier academic and research institution. Serving over 23,000 students from 80 countries, the University produces nearly 40% of Israel’s civilian scientific research and has received over 11,000 patents. Faculty and alumni of the Hebrew University have won eight Nobel Prizes and a Fields Medal. For more information about the Hebrew University, please visit http://new.huji.ac.il/en. 

About Yissum

Yissum is the technology transfer company of the Hebrew University of Jerusalem. Founded in 1964, Yissum serves as a bridge between cutting-edge academic research and a global community of entrepreneurs, investors, and industry. Yissum’s mission is to benefit society by converting extraordinary innovations and transformational technologies into commercial solutions that address our most urgent global challenges. The company has registered more than 11,680 patents globally, licensed over 1,160 technologies, and has spun out over 260 companies. Yissum’s business partners span the globe. For further information please visit www.yissum.co.il.

 

 

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New Study Shows How Organic Molecules Impact Gold Nanoparticles

New Study Shows How Organic Molecules Impact Gold Nanoparticles

17 July, 2024

 

A new study shows how organic molecules greatly influence the redox potential of gold nanoparticles, with differences up to 71 mV. Using experiments and computer simulations, the study highlights the important role of capping agents in controlling the nanoparticles' electrochemical properties and also identifies how kinetic effects impact these interactions. These findings have practical uses in areas like nanoparticle dispersion, monitoring ligand exchange, and advancements in fields such as catalysis, electronics, and drug delivery, showing the potential for customizing nanoparticle behavior for specific applications.

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A recent study led by Prof. Daniel Mandler with Prof. Roi Baer and Dr. Hadassah Elgavi Sinai and a team at Hebrew University, published in the Journal of the American Chemical Society, reveals how organic molecules affect the behavior of tiny gold particles absorbed on surfaces. Their research deepens our understanding of how these nanoparticles absorbed on surfaces interact with their surroundings, offering important insights for various uses. The research was conducted jointly by PhD student Din Zelikovich, who carried out very careful experiments and MSc student Pavel Savchenko, who conducted the theoretical calculations.

The study found that different molecules, like 2- and 4-mercaptobenzoic acid, can cause gold nanoparticles to have significantly different electrical properties, with differences up to 71 Mv (millivolts). This highlights how crucial these molecules are in determining how nanoparticles behave.

Using advanced computer simulations and experiments, the collaboration between the experimental and theoretical teams showed that some molecules stick to gold surfaces in predictable ways, matching what they saw experimentally. However, they also found that the kinetics, namely, the rate the nanoparticles are oxidized adds more complexity to how they interact.

For instance, they discovered that gold nanoparticles stabilized by 4-mercaptobenzoic acid reacted twice as quickly as those with citrate. This finding, backed by scientific theories, shows just how much the right molecule can change how these nanoparticles act.

Prof. Daniel Mandler emphasized the significance of the research, stating, "Our study demonstrates the profound impact that capping agents have on the redox properties of nanoparticles. This understanding allows us to fine-tune nanoparticle behavior for specific applications, potentially leading to significant impact in fields ranging from catalysis to drug delivery."

As the scientific community continues to explore the intricate world of nanoparticles, this research contributes valuable knowledge to the field of nanoparticle chemistry. By shedding light on the complex interactions between nanoparticles and their capping agents, this study opens new avenues for designing and optimizing nanoparticles for a wide range of applications, promising exciting developments in nanotechnology in the years to come.

The research paper titled “The Effect of the Capping Agents of Nanoparticles on Their Redox Potential” is now available in the Journal of the American Chemical Society and can be accessed at https://pubs.acs.org/doi/10.1021/jacs.4c02524#

Researchers:

Pavel Savchenko1, Din Zelikovich2, Hadassah Elgavi Sinai1, Roi Baer1, Daniel Mandler2

Institutions:

  1. Fritz Haber Research Center for Molecular Dynamics and Institute of Chemistry, The Hebrew University of Jerusalem
  2. Institute of Chemistry, The Hebrew University of Jerusalem

Illustration

Title: Understanding how nanoparticles interact with organic molecules

Credit: Din Zelikovich (PhD student), Pavel Savchenko (MSc student) and Hadassah Elgavi Sinai (Senior Researcher).

 

The Hebrew University of Jerusalem is Israel's premier academic and research institution. Serving over 23,000 students from 80 countries, the University produces nearly 40% of Israel’s civilian scientific research and has received over 11,000 patents. Faculty and alumni of the Hebrew University have won eight Nobel Prizes and a Fields Medal. For more information about the Hebrew University, please visit http://new.huji.ac.il/en. 

 

 

 

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Predicting Bitterness in Foods Using Mass Spectrometry

Predicting Bitterness in Foods Using Mass Spectrometry

14 July, 2024

 

BitterMasS, a novel tool utilizing mass spectrometry, promises a revolutionary leap in predicting bitterness in compounds. Developed through interdisciplinary collaboration, it offers enhanced precision and efficiency compared to traditional methods, with wide-ranging applications in food science, pharmaceuticals, and beyond. BitterMasS not only accelerates taste perception research but also holds potential for transforming food processing, health discoveries, and safety monitoring, marking a significant advancement in taste prediction and compound screening technologies.

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Introducing BitterMasS, a pioneering tool developed by a team led by Phd student Evgenii Ziaikin and Prof. Masha Niv from Hebrew University and Dr. Edisson Tello and Prof. Devin Peterson from Ohio State University. BitterMasS harnesses the power of mass spectrometry to predict bitterness in compounds without requiring prior knowledge of their chemical structures. This advancement marks a significant departure from traditional methods that relied on structural data, which only covers a small fraction of the metabolome.

Bitterness, a fundamental taste modality potentially related to toxic substances, has long intrigued scientists and food experts alike. Today, an innovating study promises to revolutionize how bitterness is understood and managed in foods and beverages.

Using a dataset of over 5,400 experimental mass spectra of bitter and non-bitter compounds, BitterMasS achieved remarkable precision and recall rates in internal tests. For external validation, the tool demonstrated robust performance, accurately identifying bitter compounds without structural information. These findings underscore BitterMasS potential to streamline compound screening processes in food science, pharmaceuticals, and beyond.

"BitterMasS represents a critical shift in taste prediction," said Prof. Masha Niv, lead researcher. "By leveraging mass spectrometry data, we can now predict bitterness directly and efficiently, opening doors to new discoveries in health-promoting compounds and enhanced food processing techniques."

Researchers envision BitterMasS as a versatile tool capable of monitoring bitterness changes over time, providing critical insights into food quality and safety. This innovative approach also offers practical applications in drug development and metabolomics. 

In summary, BitterMasS stands as a testament to the power of interdisciplinary collaboration and technological innovation in advancing our understanding of taste. Its implications extend far beyond the lab, potentially reshaping how we perceive and utilize bitter compounds in various industries.

The research paper titled “BitterMasS: Predicting Bitterness from Mass Spectra” is now available in the Journal of Agricultural and Food Chemistry and can be accessed at https://www.webofscience.com/wos/woscc/full-record/WOS:001226287400001 

DOI 10.1021/acs.jafc.3c09767

Researchers:

Evgenii Ziaikin1, Eddison Tellow2, Devin G. Peterson2, Masha Y. Niv1

Institutions:

1. Hebrew University Jerusalem, Institute of Biochemistry Food & Nutrition, Robert H Smith Faculty of Agriculture, Food & Environment

2. Ohio State University, College of Food Agriculture and Environmental Sciences

The Hebrew University of Jerusalem is Israel's premier academic and research institution. Serving over 23,000 students from 80 countries, the University produces nearly 40% of Israel’s civilian scientific research and has received over 11,000 patents. Faculty and alumni of the Hebrew University have won eight Nobel Prizes and a Fields Medal. For more information about the Hebrew University, please visit http://new.huji.ac.il/en. 

 

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Enhancing Quantum Technology Performance Tenfold

Enhancing Quantum Technology Performance Tenfold

10 July, 2024

 

Researchers have developed a new method to significantly enhance quantum technology performance by using the cross-correlation of two noise sources to extend coherence time, improve control fidelity, and increase sensitivity for high-frequency sensing. This innovative strategy addresses key challenges in quantum systems, offering a tenfold increase in stability and paving the way for more reliable and versatile quantum devices.

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Researchers have made a significant breakthrough in quantum technology by developing a novel method that dramatically improves the stability and performance of quantum systems. This pioneering work addresses the longstanding challenges of decoherence and imperfect control, paving the way for more reliable and sensitive quantum devices.

Quantum technologies, including quantum computers and sensors, hold immense potential for revolutionizing various fields such as computing, cryptography, and medical imaging. However, their development has been hampered by the detrimental effects of noise, which can disrupt quantum states and lead to errors.

Many traditional approaches to mitigating noise in quantum systems primarily focus on temporal autocorrelation, which examines how noise behaves over time. While effective to some extent, these methods fall short when other types of noise correlations are present.

The research was conducted by experts in quantum physics, PhD. student Alon Salhov under the guidance of Prof. Alex Retzker from Hebrew University, PhD. student Qingyun Cao under the guidance of Prof. Fedor Jelezko and Dr. Genko Genov from Ulm University and Prof. Jianming Cai from Huazhong University of Science and Technology. They have introduced an innovative strategy that leverages the cross-correlation between two noise sources. By exploiting the destructive interference of cross-correlated noise, the team has managed to significantly extend the coherence time of quantum states, improve control fidelity, and enhance sensitivity for high-frequency quantum sensing.

Key achievements of this new strategy include:

Tenfold Increase in Coherence Time: The duration for which quantum information remains intact is extended ten times longer compared to previous methods.

Improved Control Fidelity: Enhanced precision in manipulating quantum systems leads to more accurate and reliable operations.

Superior Sensitivity: The ability to detect high-frequency signals surpasses the current state-of-the-art, enabling new applications in quantum sensing.

Alon Salhov said, "Our innovative approach extends our toolbox for protecting quantum systems from noise. By focusing on the interplay between multiple noise sources, we've unlocked unprecedented levels of performance, bringing us closer to the practical implementation of quantum technologies."

This advancement not only marks a significant leap in the field of quantum research but also holds promise for a wide range of applications. Industries that rely on highly sensitive measurements, such as healthcare, stand to benefit enormously from these improvements.

The study titled “Protecting Quantum Information via Destructive Interference of Correlated Noise” is now available in Physical Review Letters and can be openly accessed at https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.132.223601

Researchers:

Alon Salhov1, Qingyun Cao2,3, Jianming Cai3, Alex Retzker1,4, Fedor Jelezko2, and Genko Genov2

Institutions:

1. Racah Institute of Physics, The Hebrew University of Jerusalem

2. Institute for Quantum Optics, Ulm University, Germany

3. School of Physics, International Joint Laboratory on Quantum Sensing and Quantum Metrology, Huazhong University of Science and Technology, China

4. AWS Center for Quantum Computing, USA

Funding

Clore Israel Foundation Scholars Programme, the Israeli Council for Higher Education, and the Milner Foundation. This work was funded by the German Federal Ministry of Research (BMBF) by future cluster QSENS and projects DE-Brill (No. 13N16207), SPINNING, DIAQNOS (No. 13N16463), quNV2.0 (No. 13N16707), QR. X and Quamapolis (No. 13N15375), DLR via project QUASIMODO (No. 50WM2170), Deutsche Forschungsgemeinschaft (DFG) via Projects No. 386028944, No. 445243414, and No. 387073854, and Excellence Cluster POLiS European Union’s HORIZON Europe program via projects QuMicro (No. 101046911), SPINUS (No. 101135699), CQuENS (No. 101135359), QCIRCLE (No. 101059999) and FLORIN (No. 101086142), European Research Council (ERC) via Synergy grant HyperQ (No. 856432) and Carl-Zeiss-Stiftung via the Center of Integrated Quantum Science and technology (IQST) and project Utrasens-Vir. A. R. acknowledges the support of European Research Council grant QRES, Project No. 770929, Quantera grant MfQDS, Israel Science Foundation and the Schwartzmann university chair. J. M. acknowledges the National Natural Science Foundation of China (Grants No. 12161141011).

Pictures credit - the authors of the paper.

Image 1)

Title: Enhanced Quantum Memory and Sensitivity by Interfering Noise

Description:

Schematic representation of destructive interference of cross-correlated noise, control sequences and experimental setup. 

Detailed description (from the paper):

(a) The qubit is subjected to environmental noise δ(t). Applying a resonant drive with Rabi frequency Ω1 creates a protected dressed qubit which decoheres mainly due to ε1(t) - the amplitude noise in Ω1. Applying a second drive with modulation frequency eΩ1, Rabi frequency Ω2 and amplitude fluctuations ε2(t), reduces decoherence due to ε1(t). 

(b) If the cross-correlation, c, of ε1(t) and ε2(t) is nonzero, a detuning eΩ1 = Ω1 + c Ω2 2/Ω1 tilts the effective-drive axis and induces a destructive interference of the cross-correlated noise, resulting in a doubly-dressed qubit with a longer coherence time. 

(c) Measurement sequences for standard and correlated double drive (DD) protocols. (d) Experimental setup and level

scheme of the NV center

Image 2)

Title: Enhanced Quantum Memory and Sensitivity by Interfering Noise

Description: A Bloch-sphere of a qubit subjected to cross-correlated noise (blue and red). The method destructively interferes this noise, resulting in superior performance.

The Hebrew University of Jerusalem is Israel’s premier academic and research institution. With over 25,000 students from 90 countries, it is a hub for advancing scientific knowledge and holds a significant role in Israel’s civilian scientific research output, accounting for nearly 40% of it and has registered over 11,000 patents. The university’s faculty and alumni have earned eight Nobel Prizes and a Fields Medal, underscoring their contributions to ground-breaking discoveries. In the global arena, the Hebrew University ranks 86th according to the Shanghai Ranking. To learn more about the university’s academic programs, research initiatives, and achievements, visit the official website at http://new.huji.ac.il/en

 

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Revolutionizing Disease Classification and Identifying Hidden Disease Patterns

Revolutionizing Disease Classification and Identifying Hidden Disease Patterns

9 July, 2024

 

Researchers have developed a machine learning approach to identify potential subtypes in diseases, significantly enhancing disease classification and treatment strategies. The model, which achieved an 89.4% ROC AUC, uncovered 515 previously unannotated disease subtypes, demonstrating the potential for more precise and personalized medical treatments.

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Researchers from the Hebrew University of Jerusalem have developed a machine learning approach to identify potential subtypes in diseases, significantly enhancing the field of disease classification and treatment strategies. The study, led by PhD student Dan Ofer and Prof. Michal Linial from the Department of Biological Chemistry at The Life Science Institute at Hebrew University, marks a significant advancement in the use of artificial intelligence in medical research.

Distinguishing diseases into distinct subtypes is pivotal for accurate study and effective treatment strategies. The Open Targets Platform integrates biomedical, genetic, and biochemical datasets to support disease ontologies, classifications, and potential gene targets. However, many disease annotations remain incomplete, often necessitating extensive expert medical input. This challenge is especially significant for rare and orphan diseases, where resources are limited.

The research introduces a novel machine learning approach to identify diseases with potential subtypes. Utilizing the extensive database of approximately 23,000 diseases documented in the Open Targets Platform, they derived new features to predict diseases with subtypes using direct evidence. Machine learning models were then applied to analyze feature importance and evaluate predictive performance, uncovering both known and novel disease subtypes.

The model achieved an impressive 89.4% ROC Area Under the Receiver Operating Characteristic Curve in identifying known disease subtypes. The integration of pre-trained deep-learning language models further enhanced the model's performance. Notably, the research identified 515 disease candidates predicted to possess previously unannotated subtypes, paving the way for new insights into disease classification.

"This project demonstrates the incredible potential of machine learning in expanding our understanding of complex diseases," said Dan Ofer. "By leveraging advanced models, we can uncover patterns and subtypes that were previously hidden, ultimately contributing to more precise and personalized treatments."

This innovative methodology enables a robust and scalable approach for improving knowledge-based annotations and provides a comprehensive assessment of disease ontology tiers. "We are excited about the potential of our machine learning approach to revolutionize disease classification," said Prof. Michal Linial. "Our findings can significantly contribute to personalized medicine, offering new avenues for therapeutic development."

The research paper titled “Automated annotation of disease subtypes” is now available in Journal of Biomedical Informatics and can be accessed at https://doi.org/10.1016/j.jbi.2024.104650.

Researchers:

Dan Ofer, Michal Linial

Institution:

Department of Biological Chemistry, The Life Science Institute, The Hebrew University of Jerusalem, Israel

The Hebrew University of Jerusalem is Israel's premier academic and research institution. Serving over 23,000 students from 80 countries, the University produces nearly 40% of Israel’s civilian scientific research and has received over 11,000 patents. Faculty and alumni of the Hebrew University have won eight Nobel Prizes and a Fields Medal. For more information about the Hebrew University, please visit http://new.huji.ac.il/en. 

 

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Ozone's Influence on Exoplanetary Climate – New Study

Ozone's Influence on Exoplanetary Climate – New Study

9 May, 2024

 

In the quest for life beyond our solar system, a new study delves into the atmospheric dynamics of planet Proxima Centauri b, illuminating ozone's pivotal role in shaping planetary climates. This research signifies a significant leap forward in our understanding of habitable exoplanets.