Anaerobic oxidation of ethane by archaea from a marine hydrocarbon seep.

Ethane is the second most abundant component of natural gas in addition to methane, and-similar to methane-is chemically unreactive. The biological consumption of ethane under anoxic conditions was suggested by geochemical profiles at marine hydrocarbon seeps1-3, and through ethane-dependent sulfate reduction in slurries4-7. Nevertheless, the microorganisms and reactions that catalyse this process have to date remained unknown8. Here we describe ethane-oxidizing archaea that were obtained by specific enrichment over ten years, and analyse these archaea using phylogeny-based fluorescence analyses, proteogenomics and metabolite studies. The co-culture, which oxidized ethane completely while reducing sulfate to sulfide, was dominated by an archaeon that we name 'Candidatus Argoarchaeum ethanivorans'; other members were sulfate-reducing Deltaproteobacteria. The genome of Ca. Argoarchaeum contains all of the genes that are necessary for a functional methyl-coenzyme M reductase, and all subunits were detected in protein extracts. Accordingly, ethyl-coenzyme M (ethyl-CoM) was identified as an intermediate by liquid chromatography-tandem mass spectrometry. This indicated that Ca. Argoarchaeum initiates ethane oxidation by ethyl-CoM formation, analogous to the recently described butane activation by 'Candidatus Syntrophoarchaeum'9. Proteogenomics further suggests that oxidation of intermediary acetyl-CoA to CO2 occurs through the oxidative Wood-Ljungdahl pathway. The identification of an archaeon that uses ethane (C2H6) fills a gap in our knowledge of microorganisms that specifically oxidize members of the homologous alkane series (CnH2n+2) without oxygen. Detection of phylogenetic and functional gene markers related to those of Ca. Argoarchaeum at deep-sea gas seeps10-12 suggests that archaea that are able to oxidize ethane through ethyl-CoM are widespread members of the local communities fostered by venting gaseous alkanes around these seeps.

Yolk-Shell Hierarchical Pore Au@MOF Nanostructures: Efficient Gas Capture and Enrichment for Advanced Breath Analysis.

Surface-enhanced Raman scattering (SERS) offers a promising, cost-effective alternative for the rapid, sensitive, and quantitative analysis of potential biomarkers in exhaled gases, which is crucial for early disease diagnosis. However, a major challenge in SERS is the effective detection of gaseous analytes, primarily due to difficulties in enriching and capturing them within the substrate's "hotspot" regions. This study introduces an advanced gas sensor combining mesoporous gold (MesoAu) and metal-organic frameworks (MOFs), exhibiting high sensitivity and rapid detection capabilities. The MesoAu provides abundant active sites and interconnected mesopores, facilitating the diffusion of analytes for detection. A ZIF-8 shell enveloping MesoAu further enriches target molecules, significantly enhancing sensitivity. A proof-of-concept experiment demonstrated a detection limit of 0.32 ppb for gaseous benzaldehyde, indicating promising prospects for the rapid diagnosis of early stage lung cancer. This research also pioneers a novel approach for constructing hierarchical plasmonic nanostructures with immense potential in gas sensing.

Molecular Dynamics Simulations of Native Protein Charging via Proton Transfer during Electrospray Ionization with Grotthuss Diffuse H3O.

Unraveling the mechanism by which native proteins are charged through electrospray ionization (ESI) has been the focus of considerable research because observable charge states can be correlated to biophysical characteristics, such as protein folding and, thus, solution conformation. Difficulties in characterizing electrosprayed droplets have catalyzed the use of molecular dynamics (MD) to provide insights into the mechanisms by which proteins are charged and transferred to the gas phase. However, prior MD studies have utilized metal ions, primarily Na+, as charge carriers, even though proteins are primarily detected as protonated ions in the mass spectra. Here, we propose a modified MD protocol for simulating discrete Grotthuss diffuse H3O+ that is capable of dynamically altering amino-acid protonation states to model electrospray charging and gaseous ion formation of model proteins, ubiquitin, and myoglobin. Application of the protocol to the evaporation of acidic droplets enables a molecular perspective of H3O+ coordination and proton transfer to/from proteins, which is unfeasible with the metal charge carriers used in previous MD studies of ESI. Our protocol recreates experimentally observed charge-state distributions and supports the charge residue model (CRM) as the dominant mechanism of native protein ionization during ESI. Additionally, our results suggest that protonation is highly specific to individual residues and is correlated to the formation of localized hydrated regions on the protein surface as droplets desolvate. Considering the use of discrete H3O+ instead of Na+, the developed protocol is a necessary step toward developing a more comprehensive model of protein ionization during ESI.

Structural Elucidation of Ubiquitin via Gas-Phase Ion/Ion Cross-Linking Reactions Using Sodium-Cationized Reagents Coupled with Infrared Multiphoton Dissociation.

Accurate structural determination of proteins is critical to understanding their biological functions and the impact of structural disruption on disease progression. Gas-phase cross-linking mass spectrometry (XL-MS) via ion/ion reactions between multiply charged protein cations and singly charged cross-linker anions has previously been developed to obtain low-resolution structural information on proteins. This method significantly shortens experimental time relative to conventional solution-phase XL-MS but has several technical limitations: (1) the singly deprotonated N-hydroxysulfosuccinimide (sulfo-NHS)-based cross-linker anions are restricted to attachment at neutral amine groups of basic amino acid residues and (2) analyzing terminal cross-linked fragment ions is insufficient to unambiguously localize sites of linker attachment. Herein, we demonstrate enhanced structural information for alcohol-denatured A-state ubiquitin obtained from an alternative gas-phase XL-MS approach. Briefly, singly sodiated ethylene glycol bis(sulfosuccinimidyl succinate) (sulfo-EGS) cross-linker anions enable covalent cross-linking at both ammonium and amine groups. Additionally, covalently modified internal fragment ions, along with terminal b-/y-type counterparts, improve the determination of linker attachment sites. Molecular dynamics simulations validate experimentally obtained gas-phase conformations of denatured ubiquitin. This method has identified four cross-linking sites across 8+ ubiquitin, including two new sites in the N-terminal region of the protein that were originally inaccessible in prior gas-phase XL approaches. The two N-terminal cross-linking sites suggest that the N-terminal half of ubiquitin is more compact in gas-phase conformations. By comparison, the two C-terminal linker sites indicate the signature transformation of this region of the protein from a native to a denatured conformation. Overall, the results suggest that the solution-phase secondary structures of the A-state ubiquitin are conserved in the gas phase. This method also provides sufficient sensitivity to differentiate between two gas-phase conformers of the same charge state with subtle structural variations.

Image Sensing of Gaseous Acetone Using Secondary Alcohol Dehydrogenase-Immobilized Mesh for Exhaled Air.

Human-borne acetone is a potent marker of lipid metabolism. Here, an enzyme immobilization method for secondary alcohol dehydrogenase (S-ADH), which is suitable for highly sensitive and selective biosensing of acetone, was developed, and then its applicability was demonstrated for spatiotemporal imaging of concentration distribution. After various investigations, S-ADH-immobilized meshes could be prepared with less than 5% variation by cross-linking S-ADH with glutaraldehyde on a cotton mesh at 40 °C for 15 min. Furthermore, high activity was obtained by adjusting the concentration of the coenzyme nicotinamide adenine dinucleotide (NADH) solution added to the S-ADH-immobilized mesh to 500 µM and the solvent to a potassium phosphate buffer solution at pH 6.5. The gas imaging system using the S-ADH-immobilized mesh was able to image the decrease in NADH fluorescence (ex 340 nm, fl 490 nm) caused by the catalytic reaction of S-ADH and the acetone distribution in the concentration range of 0.1-10 ppm-v, including the breath concentration of healthy people at rest. The exhaled breath of two healthy subjects at 6 h of fasting was quantified as 377 and 673 ppb-v, which were consistent with the values quantified by gas chromatography-mass spectrometry.

Codelivery of Dual Gases with Metal-Organic Supramolecular Cage-Based Microenvironment-Responsive Nanomedicine for Atherosclerosis Therapy.

Atherosclerosis (AS) is a common cause of coronary heart disease and stroke. The delivery of exogenous H2S and in situ production of O2 within atherosclerotic plaques can help suppress inflammatory cell infiltration and alleviate disease progression. However, the uncontrolled release of gas donors hinders achieving effective drug concentrations and causes toxic effects. Herein, diallyl trisulfide (DATS)-loaded metal-organic cage (MOC)-68-doped MnO2 nanoparticles are developed as a microenvironment-responsive nanodrug with the capacity for the in situ co-delivery of H2S and O2 to inflammatory cells within plaques. This nanomedicine exhibited excellent monodispersity and stability and protected DATS from degradation in the circulation. In vitro studies showed that the nanomedicine reduced macrophage polarization toward an inflammatory phenotype and inhibited the formation of foam cells, while suppressing the expression of NOD-like receptor thermal protein domain associated protein 3 (NLRP3) and interleukin-1ß. In a mouse model of ApoE-/- genotype, the nanomedicine reduces the plaque burden, inflammatory infiltration, and hypoxic conditions within the plaques. Furthermore, the treatment process and therapeutic effects can be monitored by magnetic resonance image (MRI), in real time upon Mn2+ release from the acidic- and H2O2- microenvironment-responsive MnO2 nanoparticles. The DATS-loaded MOC-68-doped MnO2-based nanodrug holds great promise as a novel theranostic platform for AS.

Oxygen-Evolving Radiotherapy-Radiodynamic Therapy Synergized with NO Gas Therapy by Cerium-Based Rare-Earth Metal-Porphyrin Framework.

The efficacy of traditional radiotherapy (RT) has been severely limited by its significant side effects, as well as tumor hypoxia. Here, the nanoscale cerium (Ce)-based metaloxo clusters (Ce(IV)6)-porphyrin (meso-tetra (4-carboxyphenyl) porphyrin, TCPP) framework loaded with L-arginine (LA) (denoted as LA@Ce(IV)6-TCPP) is developed to serve as a multifarious radio enhancer to heighten X-ray absorption and energy transfer accompanied by O2/NO generation for hypoxia-improved RT-radiodynamic therapy (RDT) and gas therapy. Within tumor cells, LA@Ce(IV)6-TCPP will first react with endogenous H2O2 and inducible NO synthase (iNOS) to produce O2 and NO to respectively increase the oxygen supply and reduce oxygen consumption, thus alleviating tumor hypoxia. Then upon X-ray irradiation, LA@Ce(IV)6-TCPP can significantly enhance hydroxyl radical (•OH) generation from Ce(IV)6 metaloxo clusters for RT and synchronously facilitate singlet oxygen (1O2) generation from adjacently-coordinated TCPP for RDT. Moreover, both the •OH and 1O2 can further react with NO to generate more toxic peroxynitrite anions (ONOO-) to inhibit tumor growth for gas therapy. Benefitting from the alleviation of tumor hypoxia and intensified RT-RDT synergized with gas therapy, LA@Ce(IV)6-TCPP elicited superior anticancer outcomes. This work provides an effective RT strategy by using low doses of X-rays to intensify tumor suppression yet reduce systemic toxicity.

A closer look at high-energy X-ray-induced bubble formation during soft tissue imaging.

Improving the scalability of tissue imaging throughput with bright, coherent X-rays requires identifying and mitigating artifacts resulting from the interactions between X-rays and matter. At synchrotron sources, long-term imaging of soft tissues in solution can result in gas bubble formation or cavitation, which dramatically compromises image quality and integrity of the samples. By combining in-line phase-contrast imaging with gas chromatography in real time, we were able to track the onset and evolution of high-energy X-ray-induced gas bubbles in ethanol-embedded soft tissue samples for tens of minutes (two to three times the typical scan times). We demonstrate quantitatively that vacuum degassing of the sample during preparation can significantly delay bubble formation, offering up to a twofold improvement in dose tolerance, depending on the tissue type. However, once nucleated, bubble growth is faster in degassed than undegassed samples, indicating their distinct metastable states at bubble onset. Gas chromatography analysis shows increased solvent vaporization concurrent with bubble formation, yet the quantities of dissolved gasses remain unchanged. By coupling features extracted from the radiographs with computational analysis of bubble characteristics, we uncover dose-controlled kinetics and nucleation site-specific growth. These hallmark signatures provide quantitative constraints on the driving mechanisms of bubble formation and growth. Overall, the observations highlight bubble formation as a critical yet often overlooked hurdle in upscaling X-ray imaging for biological tissues and soft materials and we offer an empirical foundation for their understanding and imaging protocol optimization. More importantly, our approaches establish a top-down scheme to decipher the complex, multiscale radiation-matter interactions in these applications.

Gas Evolution as a Tool to Study Reaction Kinetics Under Biomimetic Conditions.

The field of bioorthogonal chemistry is rapidly growing, presenting successful applications of organic and transition metal-catalysed reactions in cells and living systems (in vivo). The development of such reactions typically proceeds through many iterative steps focused on biocompatibility and fast reaction kinetics to ensure product formation. However, obtaining kinetic data, even under simulated biological (biomimetic) conditions, remains a challenge due to substantial concentrations of salts and biomolecules hampering the use of typically employed solution-phase analytical techniques. In this study, we explored the suitability of gas evolution as a probe to study kinetics under biomimetic conditions. As proof of concept, we show that the progress of two transition metal-catalysed bioorthogonal chemical reactions can be accurately monitored, regardless of the complexity of the medium. As such, we introduce a protocol to gain more insight into the performance of a catalytic system under biomimetic conditions to further progress iterative catalyst development for in vivo applications.

Radiation-Induced Molecular Processes in DNA: A Perspective on Gas-Phase Interaction Studies.

Studying the direct effects of DNA irradiation is essential for understanding the impact of radiation on biological systems. Gas-phase interactions are especially well suited to uncover the molecular mechanisms underlying these direct effects. Only relatively recently, isolated DNA oligonucleotides were irradiated by ionizing particles such as VUV or X-ray photons or ion beams, and ionic products were analyzed by mass spectrometry. This article provides a comprehensive review of primarily experimental investigations in this field over the past decade, emphasizing the description of processes such as ionization, fragmentation, charge and hydrogen transfer triggered by photoabsorption or ion collision, and the recent progress made thanks to specific atomic photoabsorption. Then, we outline ongoing experimental developments notably involving ion-mobility spectrometry, crossed beams or time-resolved measurements. The discussion extends to potential research directions for the future.

Gas Delivery Relevant to Human Health using Porous Materials.

Gases are essential for various applications relevant to human health, including in medicine, biomedical imaging, and pharmaceutical synthesis. However, gases are significantly more challenging to safely handle than liquids and solids. Herein, we review the use of porous materials, such as metal-organic frameworks (MOFs), zeolites, and silicas, to adsorb medicinally relevant gases and facilitate their handling as solids. Specific topics include the use of MOFs and zeolites to deliver H2S for therapeutic applications, 129Xe for magnetic resonance imaging, O2 for the treatment of cancer and hypoxia, and various gases for use in organic synthesis. This Perspective aims to bring together the organic, inorganic, medicinal, and materials chemistry communities to inspire the design of next-generation porous materials for the storage and delivery of medicinally relevant gases.

Toward Lung Ventilation Imaging Using Hyperpolarized Diethyl Ether Gas Contrast Agent.

Hyperpolarized 129Xe gas was FDA-approved as an inhalable contrast agent for magnetic resonance imaging of a wide range of pulmonary diseases in December 2022. Despite the remarkable success in clinical research settings, the widespread clinical translation of HP 129Xe gas faces two critical challenges: the high cost of the relatively low-throughput hyperpolarization equipment and the lack of 129Xe imaging capability on clinical MRI scanners, which have narrow-bandwidth electronics designed only for proton (1H) imaging. To solve this translational grand challenge of gaseous hyperpolarized MRI contrast agents, here we demonstrate the utility of batch-mode production of proton-hyperpolarized diethyl ether gas via heterogeneous pairwise addition of parahydrogen to ethyl vinyl ether. An approximately 0.1-liter bolus of hyperpolarized diethyl ether gas was produced in 1 second and injected in excised rabbit lungs. Lung ventilation imaging was performed using sub-second 2D MRI with up to 2×2 mm2 in-plane resolution using a clinical 0.35 T MRI scanner without any modifications. This feasibility demonstration paves the way for the use of inhalable diethyl ether as a gaseous contrast agent for pulmonary MRI applications using any clinical MRI scanner.

Gas-Responsive and Gas-Releasing Polymer Assemblies.

In order to explore the unique physiological roles of gas signaling molecules and gasotransmitters in vivo, chemists have engineered a variety of gas-responsive polymers that can monitor their changes in cellular milieu, and gas-releasing polymers that can orchestrate the release of gases. These have advanced their potential applications in the field of bio-imaging, nanodelivery, and theranostics. Since these polymers are of different chain structures and properties, the morphology of their assemblies will manifest distinct transitions after responding to gas or releasing gas. In this review, we summarize the fundamental design rationale of gas-responsive and gas-releasing polymers in structure and their controlled transition in self-assembled morphology and function, as well as present some perspectives in this prosperous field. Emerging challenges faced for the future research are also discussed.

Gas-Phase Functionalization of Phytoglycogen Nanoparticles and the Role of Reagent Structure in the Formation of Self-Limiting Hydrophobic Shells.

A suite of acyl chloride structural isomers (C6H11OCl) was used to effect gas-phase esterification of starch-based phytoglycogen nanoparticles (PhG NPs). The surface degree of substitution (DS) was quantified using X-ray photoelectron spectroscopy, while the overall DS was quantified using 1H NMR spectroscopy. Gas-phase modification initiates at the NP surface, with the extent of surface and overall esterification determined by both the reaction time and the steric footprint of the acyl chloride reagent. The less sterically hindered acyl chlorides diffuse fully into the NP interior, while the branched isomers are restricted to the near-surface region and form self-limiting hydrophobic shells, with shell thicknesses decreasing with increasing steric footprint. These differences in substitution were also reflected in the solubility of the NPs, with water solubility systematically decreasing with increasing DS. The ability to separately control both the surface and overall degree of functionalization and thereby form thin hydrophobic shells has significant implications for the development of polysaccharide-based biopolymers as nanocarrier delivery systems.

High-precision Helicobacter pylori infection diagnosis using a dual-element multimodal gas sensor array.

Helicobacter pylori (H. pylori) is a globally widespread bacterial infection. Early diagnosis of this infection is vital for public and individual health. Prevalent diagnosis methods like the isotope 13C or 14C labelled urea breath test (UBT) are not convenient and may do harm to the human body. The use of cross-response gas sensor arrays (GSAs) is an alternative way for label-free detection of metabolite changes in exhaled breath (EB). However, conventional GSAs are complex to prepare, lack reliability, and fail to discriminate subtle changes in EB due to the use of numerous sensing elements and single dimensional signal. This work presents a dual-element multimodal GSA empowered with multimodal sensing signals including conductance (G), capacitance (C), and dissipation factor (DF) to improve the ability for gas recognition and H. pylori-infection diagnosis. Sensitized by poly(diallyldimethylammonium chloride) (PDDA) and the metal-organic framework material NH2-UiO66, the dual-element graphene oxide (GO)-composite GSAs exhibited a high specific surface area and abundant adsorption sites, resulting in high sensitivity, repeatability, and fast response/recovery speed in all three signals. The multimodal sensing signals with rich sensing features allowed the GSA to detect various physicochemical properties of gas analytes, such as charge transfer and polarization ability, enhancing the sensing capabilities for gas discrimination. The dual-element GSA could differentiate different typical standard gases and non-dehumidified EB samples, demonstrating the advantages in EB analysis. In a case-control clinical study on 52 clinical EB samples, the diagnosis model based on the multimodal GSA achieved an accuracy of 94.1%, a sensitivity of 100%, and a specificity of 90.9% for diagnosing H. pylori infection, offering a promising strategy for developing an accurate, non-invasive and label-free method for disease diagnosis.

Solution and gaseous phase sensing of formaldehyde with economical triphenylmethane based sensors: a tool to estimate formaldehyde content in stored fish samples.

The use of formalin to preserve raw food items such as fish, meat, vegetables etc. is very commonly practiced in the present day. Also, formaldehyde (FA), which is the main constituent of formalin solution, is known to cause serious health issues on exposure. Considering the ill effects of formaldehyde, herein we report synthesis of highly sensitive triphenylmethane based formaldehyde (FA) sensors from a single step reaction of inexpensive reagents namely 4-hydroxy benzaldehyde and 2,6-dimethyl phenol. The synthetic method also provides highly pure product in bulk quantity. The analytical activity of the triphenylmethane sensor 1 with a limit of detection (LOD) value of 2.31 × 10-6 M for FA was significantly enhanced through induced deprotonation and thereafter a LOD value of 1.82 × 10-8 M could be achieved. To the best of our knowledge, the LOD value of the deprotonated form (sensor 2) for FA was superior to those of all the FA optical sensors reported so far. The mechanism of sensing was demonstrated by 1H-NMR titration and recording mass spectra before and after addition of FA to a solution of sensor 2. Both sensor 1 and sensor 2 exhibit quenching in emission upon addition of FA. A fluorescence study also demonstrates enhancement in analytical activity of the sensor upon induced deprotonation. Then the sensor was effectively immobilized into a hydrophilic and biocompatible starch-PVA polymer matrix which enabled detection of FA in a 100% aqueous system reversibly. Again, quick and effective sensing of FA in real food samples (stored fish) with the help of a computational application was demonstrated. The sensors have significant practical applicability as they effectively detect FA in real food samples qualitatively and quantitatively.

Molecular Gas-Phase Conformational Ensembles.

Accurately determining the global minima of a molecular structure is important in diverse scientific fields, including drug design, materials science, and chemical synthesis. Conformational search engines serve as valuable tools for exploring the extensive conformational space of molecules and for identifying energetically favorable conformations. In this study, we present a comparison of Auto3D, CREST, Balloon, and ETKDG (from RDKit), which are freely available conformational search engines, to evaluate their effectiveness in locating global minima. These engines employ distinct methodologies, including machine learning (ML) potential-based, semiempirical, and force field-based approaches. To validate these methods, we propose the use of collisional cross-section (CCS) values obtained from ion mobility-mass spectrometry studies. We hypothesize that experimental gas-phase CCS values can provide experimental evidence that we likely have the global minimum for a given molecule. To facilitate this effort, we used our gas-phase conformation library (GPCL) which currently consists of the full ensembles of 20 small molecules and can be used by the community to validate any conformational search engine. Further members of the GPCL can be readily created for any molecule of interest using our standard workflow used to compute CCS values, expanding the ability of the GPCL in validation exercises. These innovative validation techniques enhance our understanding of the conformational landscape and provide valuable insights into the performance of conformational generation engines. Our findings shed light on the strengths and limitations of each search engine, enabling informed decisions for their utilization in various scientific fields, where accurate molecular structure determination is crucial for understanding biological activity and designing targeted interventions. By facilitating the identification of reliable conformations, this study significantly contributes to enhancing the efficiency and accuracy of molecular structure determination, with particular focus on metabolite structure elucidation. The findings of this research also provide valuable insights for developing effective workflows for predicting the structures of unknown compounds with high precision.

Prediction of Vacuum Ultraviolet/Ultraviolet Gas-Phase Absorption Spectra Using Molecular Feature Representations and Machine Learning.

Ultraviolet (UV) absorption spectroscopy is a widely used tool for quantitative and qualitative analyses of chemical compounds. In the gas phase, vacuum UV (VUV) and UV absorption spectra are specific and diagnostic for many small molecules. An accurate prediction of VUV/UV absorption spectra can aid the characterization of new or unknown molecules in areas such as fuels, forensics, and pharmaceutical research. An alternative to quantum chemical spectral prediction is the use of artificial intelligence. Here, different molecular feature representation techniques were used and developed to encode chemical structures for testing three machine learning models to predict gas-phase VUV/UV absorption spectra. Structure data files (.sdf) and VUV/UV absorption spectra for 1397 volatile and semivolatile chemical compounds were used to train and test the models. New molecular features (termed ABOCH) were introduced to better capture pi-bonding, aromaticity, and halogenation. The incorporation of these new features benefited spectral prediction and demonstrated superior performance compared to computationally intensive molecular-based deep learning methods. Of the machine learning methods, the use of a Random Forest regressor returned the best accuracy score with the shortest training time. The developed machine learning prediction model also outperformed spectral predictions based on the time-dependent density functional theory.

CHARMM36 All-Atom Gas Model for Lipid Nanobubble Simulation.

Lipid nanobubbles with different gas cores may integrate the biocompatibility of lipids, powerful physicochemical properties of nanobubbles, and therapeutic effects of gas molecules, which thus promote enormous biomedical applications such as ultrasound molecular imaging, gene/drug delivery, and gas therapy. In order for further more precise applications, the exact molecular mechanisms for the interactions between lipid nanobubbles and biological systems should be studied. Molecular dynamics (MD) simulation provides a powerful computational tool for this purpose. However, previous state-of-the-art MD simulations of free gas nanobubble/lipid nanobubble employed the vacuum as their gas cores, which is not suitable for studying the interactions between functional lipid nanobubbles and biological systems and revealing the biological roles of gas molecules. Hence, in this work, we developed and optimized the CHARMM36 all-atom gas parameters for six gases including N2, O2, H2, CO, CO2, and SO2, which accurately reproduced the gas density at different pressures as well as the spontaneous formation of gas nanobubbles. Subsequent applications of these gas parameters for lipid nanobubble simulations also reproduced the self-assembly process of the lipid nanobubble. We further developed a Python script to generate all-atom lipid nanobubble simulation systems, which was proven to be efficient for all-atom MD simulations of lipid nanobubbles and to be able to capture the exact dynamics of gas molecules at the gas-lipid and lipid-water interfaces of the lipid nanobubble. In summary, the all-atom gas models proposed in this work are suitable for simulating free gas nanobubbles and lipid nanobubbles, which are supposed to overcome the shortcomings of previous state-of-the-art MD simulations with the vacuum replacing the gas core and play key roles in revealing the molecular-level interactions between lipid nanobubbles and biological systems.

Gas-sensing riboceptors.

Understanding how cells sense gases or gaseous solutes is a fundamental question in biology and is pivotal for the evolution of molecular and organismal life. In numerous organisms, gases can diffuse into cells, be transported, generated, and sensed. Controlling gases in the cellular environment is essential to prevent cellular and molecular damage due to interactions with gas-dependent free radicals. Consequently, the mechanisms governing acute gas sensing are evolutionarily conserved and have been experimentally elucidated in various organisms. However, the scientific literature on direct gas sensing is largely based on hemoprotein-based gasoreceptors (or sensors). As RNA-based G-quadruplex (G4) structures can also bind to heme, I propose that some ribozymes can act as gas-sensing riboceptors (ribonucleic acid receptors). Additionally, I present a few other ideas for non-heme metal ion- or metal cluster-based gas-sensing riboceptors. Studying riboceptors can help understand the evolutionary origins of cellular and gasocrine signaling.