Microbial mechanisms for CO2 and CH4 emissions in Robinia pseudoacacia forests along a North-South transect in the Loess Plateau.

Forest soil microbes play a crucial role in regulating atmospheric-soil carbon fluxes. Environmental heterogeneity across forest types and regions may lead to differences in soil CO2 and CH4 emissions. However, the microbial mechanisms underlying these emission variations are currently unclear. In this study, we measured CO2 and CH4 emissions of Robinia pseudoacacia forests along a north-south transect in the Loess Plateau. Using metagenomic sequencing, we investigated the structural and functional profiles of soil carbon cycling microbial communities. Results indicated that the forest CO2 emissions of Robinia pseudoacacia was significantly higher in the north region than in the south region, while the CH4 emission was oppositely. This is mainly attributed to changes in gene abundance driven by soil pH and moisture in participating carbon degradation and methane oxidation processes across different forest regions. The gene differences in carbon fixation processes between regions primarily stem from the Calvin cycle, where the abundance of rbcL, rbcS, and prkB genes dominates microbial carbon fixation in forest soils. Random forest models revealed key genes involved in predicting forest soil CO2 emissions, including SGA1 and amyA for starch decomposition, TYR for lignin decomposition, chitinase for chitin decomposition, and pectinesterase for pectin decomposition. Microbial functional characterization revealed that interregional differences in CH4 emissions during methane metabolism may originate from methane oxidation processes, and the associated gene abundances (glyA, ppc, and pmoB) were key genes for predicting CH4 emissions from forest soils. Our results provide new insights into the microbial mechanisms of CO2 and CH4 emissions from forest soils, which will be crucial for accurate prediction of the forest soil carbon cycle in the future.

Bacterial outer membrane vesicles increase polymyxin resistance in Pseudomonas aeruginosa while inhibiting its quorum sensing.

The persistent emergence of multidrug-resistant bacterial pathogens is leading to a decline in the therapeutic efficacy of antibiotics, with Pseudomonas aeruginosa (P. aeruginosa) emerging as a notable threat. We investigated the antibiotic resistance and quorum sensing (QS) system of P. aeruginosa, with a particular focused on outer membrane vesicles (OMVs) and polymyxin B as the last line of antibiotic defense. Our findings indicate that OMVs increase the resistance of P. aeruginosa to polymyxin B. The overall gene transcription levels within P. aeruginosa also reveal that OMVs can reduce the efficacy of polymyxin B. However, both OMVs and sublethal concentrations of polymyxin B suppressed the transcription levels of genes associated with the QS system. Furthermore, OMVs and polymyxin B acted in concert on the QS system of P. aeruginosa to produce a more potent inhibitory effect. This suppression was evidenced by a decrease in the secretion of virulence factors, impaired bacterial motility, and a notable decline in the ability to form biofilms. These results reveal that OMVs enhance the resistance of P. aeruginosa to polymyxin B, yet they collaborate with polymyxin B to inhibit the QS system. Our research contribute to a deeper understanding of the resistance mechanisms of P. aeruginosa in the environment, and provide new insights into the reduction of bacterial infections caused by P. aeruginosa through the QS system.

Fe-Mn binary oxides improve the methanogenic performance and reduce the environmental health risks associated with antibiotic resistance genes during anaerobic digestion.

Increasing evidence indicates that metal oxides can improve the methanogenic performance during anaerobic digestion (AD) of piggery wastewater. However, the impacts of composite metal oxides on the methanogenic performance and risk of antibiotic resistance gene (ARG) transmission during AD are not fully understood. In this study, different concentrations of Fe-Mn binary oxides (FMBO at 0, 250, 500, and 1000 mg/L) were added to AD to explore the effects of FMBO on the process. The methane yield was 7825.1 mL under FMBO at 250 mg/L, 35.2% higher than that with FMBO at 0 mg/L. PICRUSt2 functional predictions showed that FMBO promoted the oxidation of acetate and propionate, and the production of methane from the substrate, as well as increasing the abundances of most methanogens and genes encoding related enzymes. Furthermore, under FMBO at 250 mg/L, the relative abundances of 14 ARGs (excluding tetC and sul2) and four mobile gene elements (MGEs) decreased by 24.7% and 55.8%, respectively. Most of the changes in the abundances of ARGs were explained by microorganisms, especially Bacteroidetes (51.20%), followed by MGEs (11.98%). Thus, the methanogenic performance of AD improved and the risk of horizontal ARG transfer decreased with FMBO, especially at 250 mg/L.

Urea fertilization increased CO2 and CH4 emissions by enhancing C-cycling genes in semi-arid grasslands.

Global climate change is predicted to increase exogenous N input into terrestrial ecosystems, leading to significant changes in soil C-cycling. However, it remains largely unknown how these changes affect soil C-cycling, especially in semi-arid grasslands, which are one of the most vulnerable ecosystems. Here, based on a 3-year field study involving N additions (0, 25, 50, and 100 kg ha-1 yr-1 of urea) in a semi-arid grassland on the Loess Plateau, we investigated the impact of urea fertilization on plant characteristics, soil properties, CO2 and CH4 emissions, and microbial C cycling genes. The compositions of genes involved in C cycling, including C fixation, degradation, methanogenesis, and methane oxidation, were determined using metagenomics analysis. We found that N enrichment increased both above- and belowground biomasses and soil organic C content, but this positive effect was weakened when excessive N was input (N100). N enrichment also altered the C-cycling processes by modifying C-cycle-related genes, specifically stimulating the Calvin cycle C-fixation process, which led to an increase in the relative abundance of cbbS, prkB, and cbbL genes. However, it had no significant effect on the Reductive citrate cycle and 3-hydroxypropionate bi-cycle. N enrichment led to higher soil CO2 and CH4 emissions compared to treatments without added N. This increase showed significant correlations with C degradation genes (bglA, per, and lpo), methanogenesis genes (mch, ftr, and mcr), methane oxidation genes (pmoA, pmoB, and pmoC), and the abundance of microbial taxa harboring these genes. Microbial C-cycling genes were primarily influenced by N-induced changes in soil properties. Specifically, reduced soil pH largely explained the alterations in methane metabolism, while elevated available N levels were mainly responsible for the shift in C fixation and C degradation genes. Our results suggest that soil N enrichment enhances microbial C-cycling processes and soil CO2 and CH4 emissions in semi-arid ecosystems, which contributes to more accurate predictions of ecosystem C-cycling under future climate change.

Effect of aridity on the ß-diversity of alpine soil potential diazotrophs: insights into community assembly and co-occurrence patterns.

Microbial diversity plays a vital role in the maintenance of ecosystem functions. However, the current understanding of mechanisms that shape microbial diversity along environmental gradients at broad spatial scales is relatively limited, especially for specific functional groups, such as potential diazotrophs. Here, we conducted an aridity-gradient transect survey from 60 sites across the Tibetan Plateau, the largest alpine ecosystem of the planet, to investigate the ecological processes (e.g., local species pools, community assembly processes, and co-occurrence patterns) that underlie the ß-diversity of alpine soil potential diazotrophic communities. We found that aridity strongly and negatively affected the abundance, richness, and ß-diversity of soil diazotrophs. Diazotrophs displayed a distance-decay pattern along the aridity gradient, with organisms living in lower aridity habitats having a stronger distance-decay pattern. Arid habitats had lower co-occurrence complexity, including the number of edges and vertices, the average degree, and the number of keystone taxa, as compared with humid habitats. Local species pools explained limited variations in potential diazotrophic ß-diversity. In contrast, co-occurrence patterns and stochastic processes (e.g., dispersal limitation and ecological drift) played a significant role in regulating potential diazotrophic ß-diversity. The relative importance of stochastic processes and co-occurrence patterns changed with increasing aridity, with stochastic processes weakening whereas that of co-occurrence patterns enhancing. The genera Geobacter and Paenibacillus were identified as keystone taxa of co-occurrence patterns that are associated with ß-diversity. In summary, aridity affects the co-occurrence patterns and community assembly by regulating soil and vegetation characteristics and ultimately shapes the ß-diversity of potential diazotrophs. These findings highlight the importance of co-occurrence patterns in structuring microbial diversity and advance the current understanding of mechanisms that drive belowground communities.IMPORTANCERecent studies have shown that community assembly processes and species pools are the main drivers of ß-diversity in grassland microbial communities. However, co-occurrence patterns can also drive ß-diversity formation by influencing the dispersal and migration of species, the importance of which has not been reported in previous studies. Assessing the impact of co-occurrence patterns on ß-diversity is important for understanding the mechanisms of diversity formation. Our study highlights the influence of microbial co-occurrence patterns on ß-diversity and combines the drivers of community ß-diversity with drought variation, revealing that drought indirectly affects ß-diversity by influencing diazotrophic co-occurrence patterns and community assembly.

Metagenomic binning analyses of swine manure composting reveal mechanism of nitrogen cycle amendment using kaolin.

The efficient control of nitrogen loss in composting and the enhancement of product quality have become prominent concerns in current research. The positive role of varying concentrations kaolin in reducing nitrogen loss during composting was revealed using metagenomic binning combined with reverse transcription quantitative polymerase chain reaction. The results indicated that the addition of 0.5 % kaolin significantly (P < 0.05) up-regulated the expression of nosZ and nifH on day 35, while concurrently reducing norB abundance, resulting in a reduction of NH3 and N2O emissions by 61.4 % and 17.5 %, respectively. Notably, this study represents the first investigation into the co-occurrence of nitrogen functional genes and heavy metal resistance genes within metagenomic assembly genomes during composting. Emerging evidence indicates that kaolin effectively impedes the binding of Cu/Zn to nirK and nosZ gene reductases through passivation. This study offers a novel approach to enhance compost quality and waste material utilization.

Constant advance replicas method for locating minimum energy paths and transition states.

The chain-of-states (CoS) constant advance replicas (CAR) method and its climbing image variant (CI-CAR) for locating minimum energy paths (MEPs) and transition states are reported. The CAR algorithm applies the Lagrange multiplier method for imposing holonomic constraints on a chain-of-replicas, aiming to maintain equal mass-weighted/scaled root-mean-square (RMS) distances between the adjacent replicas by removing the sliding-down displacements contributed by the potential gradients during path optimization. Two contextual regularization schemes with clear geometrical interpretations are implemented to jointly promote high convergence and numerical robustness of the CAR algorithm. We show that the constrained reaction path can be solved normally within 5 steps of Lagrange multiplier updates with remarkably high numerical precision via the CAR approach. The efficacy of the CAR methods is demonstrated by testing on multiple analytical, classical, and quantum mechanical transition paths: the Müller potential, the alanine dipeptide isomerization, the helix unwinding of the VIVITLVMLKKK 12-mer peptide, and the Baker set of reactions. We also explore the potential of applying adaptive momentum (AdaM) optimizers for locating optimal transition paths under complex conformational changes. Most importantly, we discuss extensively the differences and connections between our newly proposed CAR methods and several related methods, with focuses on the reaction path with holonomic constraints (RPCons) approach of Brokaw et al. [J. Chem. Theory Comput. 2009, 5 (8), 2050-2061] and the state-of-the-art string method (SM) of E et al. [J. Chem. Phys. 2007, 126 (16), 164103]. The CAR approach represents a latest update to the general theoretical framework of reaction path finding algorithms in the two-ended CoS regime.

Reductions in abundances of intracellular and extracellular antibiotic resistance genes by SiO2 nanoparticles during composting driven by mobile genetic elements.

Applying exogenous additives during the aerobic composting of livestock manure is effective for slowing down the spread of antibiotic resistance genes (ARGs) in the environment. Nanomaterials have received much attention because only low amounts need to be added and they have a high capacity for adsorbing pollutants. Intracellular ARGs (i-ARGs) and extracellular ARGs (e-ARGs) comprise the resistome in livestock manure but the effects of nanomaterials on the fates of these different fractions during composting are still unclear. Thus, we investigated the effects of adding SiO2 nanoparticles (SiO2NPs) at four levels (0 (CK), 0.5 (L), 1 (M), and 2 g/kg (H)) on i-ARGs, e-ARGs, and the bacterial community during composting. The results showed that i-ARGs represented the main fraction of ARGs during aerobic composting of swine manure, and their abundance was lowest under M. Compared with CK, M increased the removal rates of i-ARGs and e-ARGs by 17.9% and 100%, respectively. SiO2NPs enhanced the competition between ARGs hosts and non-hosts. M optimized the bacterial community by reducing the abundances of co-hosts (Clostridium_sensu_stricto_1, Terrisporobacter, and Turicibacter) of i-ARGs and e-ARGs (by 96.0% and 99.3%, respectively) and killing 49.9% of antibiotic-resistant bacteria. Horizontal gene transfer dominated by mobile genetic elements (MGEs) played a key role in the changes in the abundances of ARGs. i-intI1 and e-Tn916/1545 were key MGEs related closely to ARGs, and the maximum decreases of 52.8% and 100%, respectively, occurred under M, which mainly explained the decreased abundances of i-ARGs and e-ARGs. Our findings provide new insights into the distribution and main drivers of i-ARGs and e-ARGs, as well as demonstrating the possibility of adding 1 g/kg SiO2NPs to reduce the propagation of ARGs.

Metagenomic insights into dietary remodeling of gut microbiota and antibiotic resistome in meat rabbits.

The gut microbiota is a repository of antibiotic resistance genes (ARGs), which may affect the health of humans and animals. The intestinal flora is affected by many factors but it is unclear how the intestinal microflora and antibiotic resistome in rabbits might change under dietary intervention. Feeding with lettuce led to the amplification and transfer of exogenous ARGs in the intestinal flora, but there were no significant differences when fed lettuces grown with different manure types. For example, the lsaC of lettuce fed with bovine, chicken and pig manure without adding organic fertilizer increased by 0.143, 0.151, 0.179 and 0.169 logs respectively after 4 weeks, and the efrB also increased by 0.074, 0.068, 0.079 and 0.106 logs respectively. Network analysis showed that Clostridium_ sensu_ stricto_ 18 was a potential host of type 6 virulence factor genes (VFGs). Mantel analysis showed that ARGs were directly influenced by mobile genetic elements (MGEs) and VFGs. Thus, feeding rabbits lettuce grown with different manure types contribute to the transmission of ARGs by remodeling the intestinal microenvironment. In addition, diet may affect exogenous ARGs to change the intestinal antibiotic resistome and possibly threaten health.

Profiles and key drivers of bacteria/phage co-mediated antibiotic resistance genes during swine manure composting amended with humic acid.

Phages can promote the spread of antibiotic resistance genes (ARGs) in agricultural environments through transduction. However, studies on phage-mediated ARG profiles during composting have not been performed. This study investigated the effects of adding humic acid (HA) on the abundances of bacteria/phage co-mediated ARGs (b/pARGs) during swine manure composting and the key factors that affected the transmission of b/pARGs. The results showed that the addition of 5 % HA during composting could effectively reduce the absolute abundances of b/pARGs, inhibit the proliferation of pathogenic microorganisms (e.g., Corynebacterium and Streptococcus) that carried ARGs, and ultimately affect the fate of b/pARGs in the composting process by regulating key environmental factors to change the abundance of co-host bacteria. Overall, the findings of this study provided new information for understanding the main driving factors affecting the b/pARGs profile and provided a reference for the prevention and control of ARGs pollution during composting.

Response characteristics of denitrifying bacteria and denitrifying functional genes to woody peat during pig manure composting.

This study aimed to explore the impacts of adding different proportions of woody peat (WP) (0%(CK), 5%(T1), and 15%(T2)) on denitrification during composting. The results demonstrated that compared with CK, T1 and T2 increased the total Kjeldahl nitrogen content (8% and 14%, respectively) and reduced the nitrate nitrogen (7% and 23%) content after composting. After composting, the abundances of nirK and nirS decreased by 4-9% and 33-35% under T1 and T2, respectively. Adding 15% WP reduced the abundances of key denitrifying bacteria such as Pseudomonas, Pusillimonas, Achromobacter, and Rhizobiales by 5-90%. The main factors that affected denitrification genes were the carbon content, nitrogen form (nitrite nitrogen and ammonium nitrogen), and denitrifying bacteria community. In summary, adding 15% WP has the best ability to reduce nitrogen loss by decreasing the abundances of denitrifying bacteria and denitrifying functional genes, thereby improving the agricultural value of composting products.

Reversing ferroptosis resistance by MOFs through regulation intracellular redox homeostasis.

As a non-apoptotic cell death form, ferroptosis offers an alternative approach to overcome cancer chemotherapy resistance. However, accumulating evidence indicates cancer cells can develop ferroptosis resistance by evolving antioxidative defense mechanisms. To address this issue, we prepared a Buthionine-(S,R)-sulfoximine (BSO) loaded metal organic framework (MOF) of BSO-MOF-HA (BMH) with the combination effect of boosting oxidative damage and inhibiting antioxidative defense. MOF nanoparticle was constructed by the photosensitizer of [4,4,4,4-(porphine-5,10,15,20-tetrayl) tetrakis (benzoic acid)] (TCPP) and the metal ion of Zr6, which was further decorated with hyaluronic acid (HA) in order to impart active targeting to CD44 receptors overexpressed cancer cells. BMH exhibited a negative charge and spherical shape with average particle size about 162.5 nm. BMH was found to restore the susceptibility of 4T1 cells to ferroptosis under irradiation. This was attributed to the combination of photodynamic therapy (PDT) and γ-glutamylcysteine synthetase inhibitor of BSO, shifting the redox balance to oxidative stress. Enhanced ferroptosis also induced the release of damage associated molecular patterns (DAMPs) to maturate dendritic cells and activated T lymphocytes, leading to superior anti-tumor performance in vivo. Taken together, our findings demonstrated that boosting oxidative damage with photosensitizer serves as an effective strategy to reverse ferroptosis resistance.

Unveiling the structural features that regulate carbapenem deacylation in KPC-2 through QM/MM and interpretable machine learning.

Resistance to carbapenem ß-lactams presents major clinical and economical challenges for the treatment of pathogen infections. The fast hydrolysis of carbapenems by carbapenemase-producing bacterial strains enables the effective deactivation of carbapenem antibiotics. In this study, we aim to unravel the structural features that distinguish the notable deacylation activity of carbapenemases. The deacylation reactions between imipenem (IPM) and the KPC-2 class A serine-based ß-lactamases (ASßLs) are modeled with combined quantum mechanical/molecular mechanical (QM/MM) minimum energy pathway (MEP) calculations and interpretable machine-learning (ML) methods. We first applied a dual-level computational protocol to achieve fast sampling of QM/MM MEPs. A tree-based ensemble ML model was employed to learn the MEP activation barriers from the conformational features of the KPC-2/IPM active site. The barrier-predicting model was then unboxed using the Shapley additive explanation (SHAP) importance attribution methods to derive mechanistic insights, which were also verified by additional QM/MM wavefunction analysis. Essentially, we show that potential hydrogen bonding interactions of the general base and the tautomerization states of the carbapenem pyrroline ring could concertedly regulate the activation barrier of KPC-2/IPM deacylation. Nonetheless, we demonstrate the efficacy of interpretable ML to assist the analysis of QM/MM simulation data for robust extraction of human-interpretable mechanistic insights.

Exploring the mechanism associated with methane emissions during composting: Inoculation with lignocellulose-degrading microorganisms.

Inoculation with microorganisms is an effective strategy for improving traditional composting processes. This study explored the effects of inoculation with lignocellulose-degrading microorganisms (LDM) on the degradation of organic matter (OM), methane (CH4) emissions, and the microbial community (bacteria and methanogens) during composting. The results showed that LDM accelerated the degradation of OM (including the lignocellulose fraction) and increased the CH4 releases in the later thermophilic and cooling stages during composting. At the ending of composting, LDM increased the CH4 emissions by 38.6% compared with the control. Moreover, LDM significantly increased the abundances of members of the bacterial and methanogenic community during the later thermophilic period (P < 0.05). In addition, LDM promoted the growth and activity of major bacterial genera (e.g., Ureibacillus) with the ability to degrade macromolecular OM, as well as affecting key methanogens (e.g., Methanocorpusculum) in the composting system. Network analysis and variance partitioning analysis indicated that OM and temperature were the main factors that affected the bacterial and methanogen community structures. Structural equation modeling demonstrated that the higher CH4 emissions under LDM were related to the growth of methanogens, which was facilitated by the anaerobic environment produced by large amounts of CO2. Thus, aerobic conditions should be improved during the end of the thermophilic and cooling composting period when inoculating with lignocellulose-degrading microorganisms in order to reduce CH4 emissions.

Assessments of Variational Autoencoder in Protein Conformation Exploration.

Molecular dynamics (MD) simulations have been extensively used to study protein dynamics and subsequently functions. However, MD simulations are often insufficient to explore adequate conformational space for protein functions within reachable timescales. Accordingly, many enhanced sampling methods, including variational autoencoder (VAE) based methods, have been developed to address this issue. The purpose of this study is to evaluate the feasibility of using VAE to assist in the exploration of protein conformational landscapes. Using three modeling systems, we showed that VAE could capture high-level hidden information which distinguishes protein conformations. These models could also be used to generate new physically plausible protein conformations for direct sampling in favorable conformational spaces. We also found that VAE worked better in interpolation than extrapolation and increasing latent space dimension could lead to a trade-off between performances and complexities.

Self-amplified ROS production from fatty acid oxidation enhanced tumor immunotherapy by atorvastatin/PD-L1 siRNA lipopeptide nanoplexes.

Despite the important role of reactive oxygen species (ROS) in battling cancer, ROS production with current approaches has been severely limited by the deficiency of oxy-substrates in tumor microenvironment. Herein, an atorvastatin (Ato)-catalytic self-amplified approach was utilized for sustainable ROS production and enhancing anti-tumor efficacy of PD-L1 silencing. A C18-pArg8-ss-pHis10 lipopeptide based self-assembled nanoplexes was developed to co-encapsulate AMP-activated protein kinase (AMPK) activator of Ato and PD-L1 siRNA. Efficient delivery of payloads was achieved because of the acidic pH triggered the protonation of pHis10, disulfide-bond exposure for cleavage and subsequent cytosolic translocation. Ato was found to activate AMPK, boosting the highly restrained mitochondrial fatty acid oxidation (FAO) in cancer cells for ROS production. The ROS derived from FAO further activated AMPK, creating a positive-feedback mechanism of sustainable ROS production. The self-amplified ROS production from cellular mitochondrial FAO was maintained by the sufficient intracellular fatty acid substrates arising from the dysregulated lipid metabolism and Ato inhibited triglyceride synthesis in cancer cells. The excessive ROS level was found to successfully induce immunogenic cell death effect, boosting the anti-tumor efficacy of PD-L1 silencing. Overall, the Ato catalyzed self-amplified ROS production has been demonstrated as a promising alternative for cancer therapy.

Mechanistic Insights into Enzyme Catalysis from Explaining Machine-Learned Quantum Mechanical and Molecular Mechanical Minimum Energy Pathways.

With the increasing popularity of machine learning (ML) applications, the demand for explainable artificial intelligence techniques to explain ML models developed for computational chemistry has also emerged. In this study, we present the development of the Boltzmann-weighted cumulative integrated gradients (BCIG) approach for effective explanation of mechanistic insights into ML models trained on high-level quantum mechanical and molecular mechanical (QM/MM) minimum energy pathways. Using the acylation reactions of the Toho-1 ß-lactamase and two antibiotics (ampicillin and cefalexin) as the model systems, we show that the BCIG approach could quantitatively attribute the energetic contribution in one system and the relative reactivity of individual steps across different systems to specific chemical processes such as the bond making/breaking and proton transfers. The proposed BCIG contribution attribution method quantifies chemistry-interpretable insights in terms of contributions from each elementary chemical process, which is in agreement with the validating QM/MM calculations and our intuitive mechanistic understandings of the model reactions.

Mechanism associated with the positive effect of nanocellulose on nitrogen retention in a manure composting system.

Additives can play important roles in effectively inhibiting nitrogen losses during livestock manure composting due to the activities of microbes. This study investigated the effects of adding nanocellulose at 300 mg/kg, 600 mg/kg, and 900 mg/kg (NC900) on nitrogen conversion, nitrogen conversion functional genes, and related microorganisms during composting. The results showed that compared with the control, nanocellulose hindered the ammoniation reaction. In addition, NC900 promoted nitrification, interfered with the denitrification process, and reduced the abundance of the nirK gene, thereby increasing the nitrate nitrogen content and decreasing ammonia spillover. NC900 promoted nitrogen fixation by increasing the abundance of members of Rhizobiales, which play important roles in nitrogen fixation. In general, compared with the control, NC900 improved the retention of nitrogen by controlling ammonia emissions. The results obtained in this study demonstrate that nanocellulose can be applied in the treatment of organic solid waste and agricultural production.

Effects and microbial mechanisms of phosphogypsum and medical stone on organic matter degradation and methane emissions during swine manure composting.

The degradation of organic matter (OM) and CH4 emissions during composting greatly influence the composting efficiency and greenhouse effect. This study evaluated the effects of adding phosphogypsum (PPG) and medical stone (MS) on OM breakdown, CH4 emissions, and their underlying mechanisms. MS accelerated the breakdown of OM in the early composting stage, whereas PPG increased it in the cooling and maturation periods. At the ending of composting, humification was also significantly promoted by PPG and MS (P < 0.05). Moreover, MS and PPG reduced CH4 emissions by 27.64% and 23.12%, respectively, and significantly inhibited the activities of methanogens in terms of their abundance (mcrA) and composition (dominant genera such as Methanobrevibacter, Methanocorpusculum, and Methanothermus) (P < 0.05). Interestingly, MS enhanced the activity of enzymes and bacterial metabolism related to OM degradation in the early composting stage, whereas PPG promoted them during the cooling and maturity stages. MS and PPG inhibited the activities of enzymes related to CH4 release during the cooling and maturity stages. Therefore, PPG and MS may have influenced OM degradation and CH4 releases during composting via changes in bacterial metabolism and enzyme activity levels. PPG and MS could have altered the activities of methanogens to influence the transformation of carbon and CH4 emissions according to network analysis and partial least-squares path modeling analysis. These findings provide insights at the molecular level into the effects of adding PPG and MS on OM degradation and CH4 emissions during composting, thereby facilitating the application of PPG and MS in composting systems.

Allosteric control of ACE2 peptidase domain dynamics.

The Angiotensin Converting Enzyme 2 (ACE2) assists the regulation of blood pressure and is the main target of the coronaviruses responsible for SARS and COVID19. The catalytic function of ACE2 relies on the opening and closing motion of its peptidase domain (PD). In this study, we investigated the possibility of allosterically controlling the ACE2 PD functional dynamics. After confirming that ACE2 PD binding site opening-closing motion is dominant in characterizing its conformational landscape, we observed that few mutations in the viral receptor binding domain fragments were able to impart different effects on the binding site opening of ACE2 PD. This showed that binding to the solvent exposed area of ACE2 PD can effectively alter the conformational profile of the protein, and thus likely its catalytic function. Using a targeted machine learning model and relative entropy-based statistical analysis, we proposed the mechanism for the allosteric perturbation that regulates the ACE2 PD binding site dynamics at atomistic level. The key residues and the source of the allosteric regulation of ACE PD dynamics are also presented.