Biology subjects

Deutsch, S.

Publications and source records attributed to Deutsch, S..

8 recordsLinked to original sources

bioRxiv2025

NTX250: A Modular mRNA-Based Immunotherapy Platform for HPV-Associated Cancers with Broad Applicability.

Infection with high-risk human papillomavirus (HPV) is a key driver of multiple HPV-associated malignancies, including cervical intraepithelial neoplasia (CIN), oropharyngeal, head and neck, and anogenital cancers. Despite the high efficacy of prophylactic HPV vaccines, a substantial population remains at ongoing risk due to issues related to vaccine accessibility, awareness, or personal choice. Current treatments, such as the loop electrosurgical excision procedure (LEEP), address lesions but do not eliminate persistent HPV infection and are associated with potential complications. Moreover, individuals treated for HPV-related disease are at increased risk for subsequent HPV-associated malignancies. These factors underscore an urgent need for effective, non-invasive therapeutic strategies capable of targeting and eradicating persistent HPV infections. Here we introduce NTX250, an innovative mRNA-based therapeutic platform designed to deliver HPV type 16 (HPV16) E6-E7 antigens, combined with immunomodulators human interleukin-12 (IL-12) p70 and engineered human LIGHT (LIGHT). The mRNAs are co-delivered via lipid and ionizable peptoid nanoparticles referred to as Nutshell formulation for intralesional administration. Our preclinical evaluation demonstrates that localized delivery of NTX250 in HPV16-transformed tumor-bearing models results in complete tumor regression and the induction of durable, antigen-specific immune memory. Moreover, this modular mRNA nanoparticle approach combining tumor-specific antigens and immunomodulators is adaptable beyond HPV, with potential applications targeting neoepitopes or other tumor-associated antigens, thus offering a versatile platform for immunotherapy across a broad range of indications. These findings highlight the potential of this strategy as a broadly applicable, non-surgical immunotherapeutic capable of inducing robust and specific anti-tumor responses.

immunology↗

bioRxiv2025

An application-specific approach to modelling the probability of unsuccessful initial attack on wildfires in Victoria, Australia

BackgroundInitial attack refers to the first firefighting actions undertaken at a newly reported fire, with the intention to control the fires spread. When multiple ignitions are reported and resources constrained, decisions need to be made about triaging fires for an escalated response. AimsWe developed empirical initial attack models for grass and forest fires for the specific purpose of triaging fires, and evaluated the models relative to their intended application. MethodsWe used a recently developed dataset of spreading fires and tested three statistical modelling techniques to model the probability of unsuccessful initial attack. Model performance was evaluated with case studies, including major fire episodes. Key resultsThe models showed limited skill overall. The best performance was observed for lightning-ignited forest fires in remote areas, but performance was not adequate to support implementation on days with extreme fire behaviour. ConclusionsOur approach did not yield suitable models for operational triage of fires, because there are many on-the-ground factors that influence the success of initial attack, and they are difficult to capture as data. ImplicationsThis study shows the importance of developing and testing empirical models relative to their intended application. It also demonstrates the significance of unmeasured bottlenecks in wildfire suppression on initial attack outcome. Summary text for Table of ContentsThis study develops models to aid operational staff in triaging fires for an escalated response. We determined that model performance was not suitable for this use case. We found that using both modelling visualisations and case studies were fundamental in assessing the models applicability for operations.

ecology↗

bioRxiv2025

Deciphering the altered conformational states of bifunctional thaumarchaeal crotonyl-CoA hydratase and 3-hydroxypropionyl-CoA dehydratase from Nitrosopumilus maritimus

The thaumarchaeal 3-hydroxypropionate/4-hydroxybutyrate (3HP/4HB) cycle represents one of the most efficient mechanisms for CO2 fixation discovered to date. Within this cycle, the enzyme encoded by Nmar_1308 from Nitrosopumilus maritimus SCM1 plays a crucial role due to its dual functionality as both a crotonyl-CoA hydratase (CCAH) and a 3-hydroxypropionyl-CoA dehydratase (3HPD). Although the importance of a bifunctional enzyme for lowering the cost of biosynthesis, the details of structural dynamics are still missing. Here, in addition to our cryogenic temperature structures, we determined the first ambient temperature structures of the Nmar_1308 protein by Serial Femtosecond X-ray Crystallography (SFX). The determined structures capture previously unobserved conformational dynamics of the Nmar_1308 protein, providing invaluable information for future synthetic biology applications.

biochemistry↗

bioRxiv2021

Structural Insights into Bifunctional Thaumarchaeal Crotonyl-CoA Hydratase and 3-Hydroxypropionyl-CoA Dehydratase from Nitrosopumilus maritimus

The ammonia-oxidizing thaumarchaeal 3-hydroxypropionate/4-hydroxybutyrate (3HP/4HB) cycle is one of the most energy-efficient CO2 fixation cycles discovered thus far. The protein encoded by Nmar_1308 (from Nitrosopumilus maritimus SCM1) is a promiscuous enzyme that catalyzes two essential reactions within the thaumarchaeal 3HP/4HB cycle, functioning as both a crotonyl-CoA hydratase (CCAH) and 3- hydroxypropionyl-CoA dehydratase (3HPD). In performing both hydratase and dehydratase activities, Nmar_1308 reduces the total number of enzymes necessary for CO2 fixation in Thaumarchaeota, reducing the overall cost for biosynthesis. Here, we present the first high-resolution crystal structure of this bifunctional enzyme with key catalytic residues in the thaumarchaeal 3HP/4HB pathway.

biochemistry↗

bioRxiv2021

Jetlag Expectations, not Circadian Parameters, Predict Jetlag Symptom Severity in Travelers

After a flight across multiple time zones, most people show a transient state of circadian misalignment causing temporary malaise known as jetlag disorder. The severity of the elicited symptoms is postulated to depend mostly on circadian factors such as the number of time zones crossed and the direction of travel. Here, we examined the influence of prior expectation on symptom severity, compared to said "classic" determinants, in order to gauge potential psychosocial effects in jetlag disorder. To this end, we monitored jetlag symptoms in travel-inexperienced individuals (n=90, 18-37y) via detailed questionnaires twice daily for one week before and after flights crossing >3 time zones. We found pronounced differences in individual symptom load that could be grouped into 4 basic symptom trajectories. Both traditional and newly devised metrics of jetlag symptom intensity and duration (accounting for individual symptom trajectories) recapitulated previous results of jetlag prevalence at about 50-60% as well as general symptom dynamics. Surprisingly, however, regression models showed very low predictive power for any of the jetlag outcomes. The classic circadian determinants, including number of time zones crossed and direction of travel, exhibited little to no link with jetlag symptom intensity and duration. Only expectation emerged as a parameter with systematic, albeit small, predictive value. These results suggest expectation as a relevant factor in jetlag experience - hinting at potential placebo effects and new treatment options. Our findings also caution against jetlag recommendations based on circadian principles but insufficient evidence linking circadian re-synchronization dynamics with ensuing symptom intensity and duration. Significance StatementJetlag disorder afflicts millions of travelers each year - a nuisance on holiday trips but also a danger in safety and performance-critical operations. For effective prevention and treatment, it is critical to understand what influences jetlag severity, i.e. jetlag symptom intensity and duration. In contrast to what guidelines state, in our study, we did not find that symptom severity could be explained by the number of time zones crossed or travel direction. Rather, travelers expectations about how long and strongly they will suffer from jetlag symptoms was the only factor systematically predicting jetlag severity. If this holds true not only for subjective but also objective symptoms, we need to revisit assumptions about how circadian desynchronization relates to experienced jetlag symptoms.

neuroscience↗

bioRxiv2019

A plant host enables the heterologous production and combinatorial study of fungal lignin-degrading enzymes

Lignin has significant potential as an abundant and renewable source for commodity chemicals yet remains vastly underutilized. Efforts towards engineering a biochemical route to the valorization of lignin are currently limited by the lack of a suitable heterologous host for the production of lignin-degrading enzymes. Here, we show that expression of fungal genes in Nicotiana benthamiana enables production of members from seven major classes of enzymes associated with lignin degradation (23 of 35 tested) in soluble form for direct use in lignin activity assays. We combinatorially characterized a subset of these enzymes in the context of model lignin dimer oxidation, revealing that fine-tuned coupling of peroxide-generators to peroxidases results in more extensive C-C bond cleavage compared to direct addition of peroxide. Comparison of peroxidase isoform activity revealed that the extent of C-C bond cleavage depends on peroxidase identity, suggesting that peroxidases are individually specialized in the context of lignin oxidation. We anticipate the use of N. benthamiana as a platform to rapidly produce a diverse array of fungal lignin-degrading enzymes will facilitate a better understanding of their concerted role in nature and unlock their potential for lignin valorization, including within the plant host itself.

bioengineering↗

bioRxiv2019

Coupled inter-subunit dynamics enable the fastest CO2-fixation by reductive carboxylases

Enoyl-CoA carboxylases/reductases (ECRs) belong to the most efficient CO2-fixing enzymes described to date. However, the molecular mechanisms underlying ECRs extraordinary catalytic activity on the level of the protein assembly remain elusive. Here we used a combination of ambient temperature X-ray Free Electron Laser (XFEL) and cryogenic synchrotron experiments to study the structural organization of the ECR from Kitasatospora setae. K. setae ECR is a homo-tetramer that differentiates into a dimer of dimers of open- and closed-form subunits in the catalytically active state. Using molecular dynamics simulations and structure-based mutagenesis, we show that catalysis is synchronized in K. setae ECR across the pair of two dimers. This conformational coupling of catalytic domains is conferred by individual amino acids to achieve high CO2-fixation rates. Our results provide unprecedented insights into the dynamic organization and synchronized inter- and intra-subunit communications of this remarkably efficient CO2-fixing enzyme during catalysis. Significance StatementFixation of CO2 offers real potential for reaching negative CO2 emissions in bioenergy, and bioproduct utilization. The capture and conversion of atmospheric CO2 remains a challenging task. Existing biological systems can be exploited and optimized for this use. Bacterial enoyl-CoA carboxylases/reductases (ECRs) encompass the fastest CO2-fixing enzymes found in nature to date. However, the mechanisms underlying ECRs extraordinary catalytic activity remain elusive. Our structural, computational, and biochemical results elucidate the dynamic structural organization of the ECR complex and describe how coupled motions of catalytic domains in the ECR tetramer drive carboxylation. This mechanistic understanding is critical for engineering highly efficient CO2-fixing biocatalysts for bioenergy and bioproduct applications.

biophysics↗

bioRxiv2017

MAGI: A Bayesian-like method for metabolite, annotation, and gene integration

Metabolomics is a widely used technology for obtaining direct measures of metabolic activities from diverse biological systems. However, ambiguous metabolite identifications are a common challenge and biochemical interpretation is often limited by incomplete and inaccurate genome-based predictions of enzyme activities (i.e. gene annotations). Metabolite, Annotation, and Gene Integration (MAGI) generates a metabolite-gene association score using a biochemical reaction network. This is calculated by a method that emphasizes consensus between metabolites and genes via biochemical reactions. To demonstrate the potential of this method, we applied MAGI to integrate sequence data and metabolomics data collected from Streptomyces coelicolor A3(2), an extensively characterized bacterium that produces diverse secondary metabolites. Our findings suggest that coupling metabolomics and genomics data by scoring consensus between the two increases the quality of both metabolite identifications and gene annotations in this organism. MAGI also made biochemical predictions for poorly annotated genes that were consistent with the extensive literature on this important organism. This limited analysis suggests that using metabolomics data has the potential to improve annotations in sequenced organisms and also provides testable hypotheses for specific biochemical functions. MAGI is freely available for academic use both as an online tool at https://magi.nersc.gov and with source code available at https://github.com/biorack/magi.

bioinformatics↗