The early prognostic value of the 1-4-day BCM/PA trend after admission in neurocritical patients.

The purpose of this study was to investigate early stage dynamic changes in relevant indicators in neurocritical patients to identify biomarkers that can predict a poor prognosis at an early stage (1-4 days after admission). This study retrospectively collected clinical data, inflammatory indicators, and nutritional indicators from 77 patients at the neurology intensive care unit. The 3-month modified Rankin scale score was used as the outcome indicator. A linear mixed model was used to analyze changes in inflammatory indicators and nutritional indicators in neurocritical patients over time from 1-4 days after admission. Logistic regression was used to determine the independent risk factors for a poor prognosis in neurocritical patients and to construct a predictive model. The predictive efficacy of the model was verified using leave-one-out cross-validation and decision curve analysis methods. The analysis results showed that 1-4 days after admission, the inflammatory indicators of white blood cell and absolute monocyte counts and the nutritional indicators of body cell mass(BCM), fat-free mass, body cell mass/phase angle (BCM/PA), intracellular water, extracellular water, and skeletal muscle index increased overall, while the nutritional indicators of albumin and visceral fat area decreased overall. The logistic multivariate regression model showed that the Charlson comorbidity index (CCI) (odds ratio (OR) = 2.526, 95% CI [1.202, 5.308]), hemoglobin (Hb)(on admission)-Hb(min) (OR = 1.049, 95% CI [1.015, 1.083), BCM(on admission) (OR = 0.794, 95% CI [0.662, 0.952]), and the change in BCM/PA 1-4 days after admission (OR = 1.157, 95% CI [1.070, 1.252]) were independent risk factors for a poor prognosis in neurocritical patients. The predictive analysis showed that the predictive power of Model 1 with BCM/PA (area under the curve (AUC) = 0.95, 95% CI (0.90, 0.99)) was 93%, 65%, 141%, and 133% higher than that of Model 2 without BCM/PA, the CCI, the APACHE II score, and the NRS2002 score (all P < 0.05), respectively. The CCI, Hb(on admission)-Hb(min), BCM(on admission), and an increase in BCM/PA 1-4 days after admission were independently associated with a poor prognosis in neurocritical patients. Of these variables, BCM/PA may be a valid indicator for early stage prediction of a poor prognosis in neurocritical patients.

Single-cell exploration of active phosphate-solubilizing bacteria across diverse soil matrices for sustainable phosphorus management.

Phosphate-solubilizing bacteria (PSB) are crucial for enhancing phosphorus bioavailability and regulating phosphorus transformation processes. However, the in situ phosphorus-solubilizing activity and the link between phenotypes and genotypes for PSB remain unidentified. Here we employed single-cell Raman spectroscopy combined with heavy water to discern and quantify soil active PSB. Our results reveal that PSB abundance and in situ activity differed significantly between soil types and fertilization treatments. Inorganic fertilizer input was the key driver for active PSB distribution. Targeted single-cell sorting and metagenomic sequencing of active PSB uncovered several low-abundance genera that are easily overlooked within bulk soil microbiota. We elucidate the underlying functional genes and metabolic pathway, and the interplay between phosphorus and carbon cycling involved in high phosphorus solubilization activity. Our study provides a single-cell approach to exploring PSB from native environments, enabling the development of a microbial solution for the efficient agronomic use of phosphorus and mitigating the phosphorus crisis.

Combined metabolomics and proteomics to reveal the mechanism of S. oneidensis MR-1 degradation malathion enhanced by FeO/C.

Iron oxide @ biochar (FeO/C) promotes bacterial growth and facilitates electron transfer, thereby effectively promoting malathion degradation by Shewanella oneidensis MR-1 (S. oneidensis MR-1). This study elucidated the underlying mechanism of FeO/C-enhanced malathion degradation by S. oneidensis MR-1 through a combination of metabolomics and proteomics analysis. The kinetic fitting results from the degradation experiment indicated that 0.1 g/L FeO/C exerted the most significant enhancement effect on malathion degradation by S. oneidensis MR-1. Observations from Scanning Electron Microscopy and Laser Scanning Confocal Microscopy, along with physiological and biochemical analysis, showed that FeO/C enhanced the growth and oxidative response of S. oneidensis MR-1 under malathion stress. In addition, metabolomics and proteomics analysis revealed an increase in certain electron transfer related metabolites, such as coenzymes, and the upregulation of proteins, including coenzyme A, sdhD, and petC. Overall, spectroscopic analysis suggested that Fe2+, which was reduced from Fe3+ by S. oneidensis MR-1 in FeO/C, promoted electron transfer in S. oneidensis MR-1 to enhance the degradation of malathion. This study offers enhanced strategies for efficient removal of malathion contaminants.

Predictive value of the random forest model based on bioelectrical impedance analysis parameter trajectories for short-term prognosis in stroke patients.

BACKGROUND: The short-term prognosis of stroke patients is mainly influenced by the severity of the primary disease at admission and the trend of disease development during the acute phase (1-7 days after admission). OBJECTIVE: The aim of this study is to explore the relationship between the bioelectrical impedance analysis (BIA) parameter trajectories during the acute phase of stroke patients and their short-term prognosis, and to investigate the predictive value of the prediction model constructed using BIA parameter trajectories and clinical indicators at admission for short-term prognosis in stroke patients. METHODS: A total of 162 stroke patients were prospectively enrolled, and their clinical indicators at admission and BIA parameters during the first 1-7 days of admission were collected. A Group-Based Trajectory Model (GBTM) was employed to identify different subgroups of longitudinal trajectories of BIA parameters during the first 1-7 days of admission in stroke patients. The random forest algorithm was applied to screen BIA parameter trajectories and clinical indicators with predictive value, construct prediction models, and perform model comparisons. The outcome measure was the Modified Rankin Scale (mRS) score at discharge. RESULTS: PA in BIA parameters can be divided into four separate trajectory groups. The incidence of poor prognosis (mRS: 4-6) at discharge was significantly higher in the "Low PA Rapid Decline Group" (85.0%) than in the "High PA Stable Group " (33.3%) and in the "Medium PA Slow Decline Group "(29.5%) (all P < 0.05). In-hospital mortality was the highest in the "Low PA Rapid Decline Group" (60%) compared with the remaining trajectory groups (P < 0.05). Compared with the prediction model with only clinical indicators (Model 1), the prediction model with PA trajectories (Model 2) demonstrated higher predictive accuracy and efficacy. The area under the receiver operating characteristic curve (AUC) of Model 2 was 0.909 [95% CI 0.863, 0.956], integrated discrimination improvement index (IDI), 0.035 (P < 0.001), and net reclassification improvement (NRI), 0.175 (P = 0.031). CONCLUSION: PA trajectories during the first 1-7 days of admission are associated with the short-term prognosis of stroke patients. PA trajectories have additional value in predicting the short-term prognosis of stroke patients.

Association of bioimpedance analysis parameters trajectories with clinical outcomes in neurocritical patients.

Background and objective: Neurocritical patients often experience uncontrolled high catabolic metabolism state during the acuta phase of the disease. The complex interactions of neuroendocrine, inflammation, and immune system lead to massive protein breakdown and changes in body composition. Bioelectrical impedance analysis (BIA) evaluates the content and proportions of body components based on the principles of bioelectricity. Its parameters reflect the overall health status of the body and the integrity of cellular structure and function, playing an important role in assessing the disease status and predicting prognosis of such patients. This study explored the association of BIA parameters trajectories with clinical outcomes in neurocritical patients. Methods: This study prospectively collected BIA parameters of 127 neurocritical patients in the Department of Neurology admitted to the NICU for the first 1-7 days. All these patients were adults (≥18 years old) experiencing their first onset of illness and were in the acute phase of the disease. The group-based trajectory modeling (GBTM), which aims to identify individuals following similar developmental trajectories, was used to identify potential subgroups of individuals based on BIA parameters. The short-term prognosis of patients in each trajectory group with variations in phase angle (PA) and extracellular water/total body water (ECW/TBW) over time was differentially analyzed, and the logistic regression model was used to analyze the relationship between potential trajectory groups of PA and ECW/TBW and the short-term prognosis of neurocritical patients. The outcome was Glasgow Outcome Scale (GOS) score at discharge. Results: Four PA trajectories and four ECW/TBW trajectories were detected respectively in neurocritical patients. Among them, compared with the other latent subgroups, the "Low PA rapidly decreasing subgroup" and the "High ECW/TBW slowly rising subgroup" had higher incidences of adverse outcomes at discharge (GOS:1-3), in-hospital mortality, and length of neurology intensive care unit stay (all P < 0.05). After correcting for potential confounders, compared with the "Low PA rapidly decreasing subgroup", the risk of adverse outcome (GOS:1-3) was lower in the other three PA trajectories, with OR values of 0.0003, 0.0004, and 0.003 respectively (all P < 0.05). Compared with the "High ECW/TBW slowly rising subgroup", the risk of adverse outcome (GOS:1-3) was lower in the other three ECW/TBW trajectories, with OR values of 0.013, 0.035 and 0.038 respectively (all P < 0.05). Conclusion: Latent PA trajectories and latent ECW/TBW trajectories during 1-7 days after admission were associated with the clinical outcomes of neurocritical patients. The risk of adverse outcomes was highest in the "Low PA rapidly decreasing subgroup" and the "High ECW/TBW slowly rising subgroup". These results reflected the overall health status and nutritional condition of neurocritical patients at the onset of the disease, and demonstrated the dynamic change process in body composition caused by the inflammatory response during the acute phase of the disease. This provided a reference basis for the observation and prognostic evaluation of such patients.

Metabolic potential of Nitrososphaera-associated clades.

Soil ammonia-oxidizing archaea (AOA) play a crucial role in converting ammonia to nitrite, thereby mobilizing reactive nitrogen species into their soluble form, with a significant impact on nitrogen losses from terrestrial soils. Yet, our knowledge regarding their diversity and functions remains limited. In this study, we reconstructed 97 high-quality AOA metagenome-assembled genomes (MAGs) from 180 soil samples collected in Central Germany during 2014-2019 summers. These MAGs were affiliated with the order Nitrososphaerales and clustered into four family-level clades (NS-α/γ/δ/ε). Among these MAGs, 75 belonged to the most abundant but least understood δ-clade. Within the δ-clade, the amoA genes in three MAGs from neutral soils showed a 99.5% similarity to the fosmid clone 54d9, which has served as representative of the δ-clade for the past two decades since even today no cultivated representatives are available. Seventy-two MAGs constituted a distinct δ sub-clade, and their abundance and expression activity were more than twice that of other MAGs in slightly acidic soils. Unlike the less abundant clades (α, γ, and ε), the δ-MAGs possessed multiple highly expressed intracellular and extracellular carbohydrate-active enzymes responsible for carbohydrate binding (CBM32) and degradation (GH5), along with highly expressed genes involved in ammonia oxidation. Together, these results suggest metabolic versatility of uncultured soil AOA and a potential mixotrophic or chemolithoheterotrophic lifestyle among 54d9-like AOA.

HBB as a Novel Biomarker for the Diagnosis and Monitoring of Lung Cancer Regulates Cell Proliferation via ERK1/2 Pathway.

Objective: Recent studies have revealed that hemoglobin beta (HBB) plays an important role not only in blood disorders but also in malignancies. The aim of this study is to investigate the clinical significance, diagnostic value, and biological function of HBB in lung cancer. Methods: HBB expression was examined in lung cancer tissues and plasma samples using quantitative real-time polymerase chain reaction, and its relationship with clinical pathological characteristics was analyzed. Receiver operating characteristic (ROC) curves were constructed to evaluate the diagnostic value of HBB in lung cancer. The proliferation of A549 and SPCA1 cells was analyzed using a cell counting kit-8 assay and protein expressions were detected by western blot. Results: The expressions of HBB were found to be down-regulated in both lung cancer tissues and plasma samples. Notably, plasma HBB levels were significantly elevated in postoperative samples when compared to their preoperative counterparts. Across 66 cases of lung cancer tissues, a correlation was observed between HBB levels and both gender and tumor, node, metastasis staging. ROC curve analysis further confirmed the high diagnostic potential of HBB expression in lung cancer. Moreover, the combination of HBB and carcinoembryonic antigen (CEA) had greater significance than HBB or CEA alone in the diagnosis of lung cancer. Knocking out or overexpressing HBB could affect lung cancer cell proliferation through the ERK1/2 signaling pathway. Conclusion: HBB can serve as a novel biomarker for the diagnosis and monitoring of lung cancer, regulating cell proliferation via the ERK1/2 pathway and playing a pivotal role in the oncogenesis and progression of the disease.

Structure-based design of pan-coronavirus inhibitors targeting host cathepsin L and calpain-1.

Respiratory disease caused by coronavirus infection remains a global health crisis. Although several SARS-CoV-2-specific vaccines and direct-acting antivirals are available, their efficacy on emerging coronaviruses in the future, including SARS-CoV-2 variants, might be compromised. Host-targeting antivirals provide preventive and therapeutic strategies to overcome resistance and manage future outbreak of emerging coronaviruses. Cathepsin L (CTSL) and calpain-1 (CAPN1) are host cysteine proteases which play crucial roles in coronaviral entrance into cells and infection-related immune response. Here, two peptidomimetic α-ketoamide compounds, 14a and 14b, were identified as potent dual target inhibitors against CTSL and CAPN1. The X-ray crystal structures of human CTSL and CAPN1 in complex with 14a and 14b revealed the covalent binding of α-ketoamide groups of 14a and 14b to C25 of CTSL and C115 of CAPN1. Both showed potent and broad-spectrum anticoronaviral activities in vitro, and it is worth noting that they exhibited low nanomolar potency against SARS-CoV-2 and its variants of concern (VOCs) with EC50 values ranging from 0.80 to 161.7 nM in various cells. Preliminary mechanistic exploration indicated that they exhibited anticoronaviral activity through blocking viral entrance. Moreover, 14a and 14b exhibited good oral pharmacokinetic properties in mice, rats and dogs, and favorable safety in mice. In addition, both 14a and 14b treatments demonstrated potent antiviral potency against SARS-CoV-2 XBB 1.16 variant infection in a K18-hACE2 transgenic mouse model. And 14b also showed effective antiviral activity against HCoV-OC43 infection in a mouse model with a final survival rate of 60%. Further evaluation showed that 14a and 14b exhibited excellent anti-inflammatory effects in Raw 264.7 mouse macrophages and in mice with acute pneumonia. Taken together, these results suggested that 14a and 14b are promising drug candidates, providing novel insight into developing pan-coronavirus inhibitors with antiviral and anti-inflammatory properties.

Interaction of tetracycline and copper co-intake in inducing antibiotic resistance genes and potential pathogens in mouse gut.

The widespread use of copper and tetracycline as growth promoters in the breeding industry poses a potential threat to environmental health. Nevertheless, to the best of our knowledge, the potential adverse effects of copper and tetracycline on the gut microbiota remain unknown. Herein, mice were fed different concentrations of copper and/or tetracycline for 6 weeks to simulate real life-like exposure in the breeding industry. Following the exposure, antibiotic resistance genes (ARGs), potential pathogens, and other pathogenic factors were analyzed in mouse feces. The co-exposure of copper with tetracycline significantly increased the abundance of ARGs and enriched more potential pathogens in the gut of the co-treated mice. Copper and/or tetracycline exposure increased the abundance of bacteria carrying either ARGs, metal resistance genes, or virulence factors, contributing to the widespread dissemination of potentially harmful genes posing a severe risk to public health. Our study provides insights into the effects of copper and tetracycline exposure on the gut resistome and potential pathogens, and our findings can help reduce the risks associated with antibiotic resistance under the One Health framework.

Niche differentiation and biogeography of Bathyarchaeia in paddy soil ecosystems: a case study in eastern China.

Bathyarchaeia (formerly Bathyarchaeota) is a group of highly abundant archaeal communities that play important roles in global biogeochemical cycling. Bathyarchaeia is predominantly found in sediments and hot springs. However, their presence in arable soils is relatively limited. In this study, we aimed to investigate the spatial distributions and diversity of Bathyarchaeia in paddy soils across eastern China, which is a major rice production region. The relative abundance of Bathyarchaeia among total archaea ranged from 3 to 68% in paddy soils, and Bathy-6 was the dominant subgroup among the Bathyarchaeia (70-80% of all sequences). Bathyarchaeia showed higher migration ability and wider niche width based on the neutral and null model simulations. Bathy-6 was primarily assembled by deterministic processes. Soil pH and C/N ratio were identified as key factors influencing the Bathyarchaeia composition, whereas C/N ratio and mean annual temperature influenced the relative abundance of Bathyarchaeia. Network analysis showed that specific Bathyarchaeia taxa occupied keystone positions in the archaeal community and co-occurred with some methanogenic archaea, including Methanosarcina and Methanobacteria, and ammonia-oxidizing archaea belonging to Nitrososphaeria. This study provides important insights into the biogeography and niche differentiation of Bathyarchaeia particularly in paddy soil ecosystems.

Analysis of the Genomic Sequences and Metabolites of Bacillus velezensis YA215.

Discovering more novel antimicrobial compounds has become a keen research problem. In this study, YA215 genome was sequenced by the Illumina HiSeq + PacBio sequencing platform. Genome assembly was performed by Unicycler software and the gene clusters responsible for secondary metabolite biosynthesis were predicted by antiSMASH. The genome comprised 3976514 bp and had a 46.56% G + C content. 3809 coding DNA sequences, 27 rRNAs, 86 tRNAs genes, and 79 sRNA were predicted. Strain YA215 was re-identified as Bacillus velezensis based on ANI and OrthoANI analysis. In the COG database, 23 functional groups from 3090 annotations were predicted. In the GO database, 2654 annotations were predicted. 2486 KEGG annotations linked 41 metabolic pathways. Glycosyl transferases, polysaccharide lyases, auxiliary activities, glycoside hydrolases, carbohydrate esterases, and carbohydrate-binding modules were predicted among the 127 annotations in the CAZy database. AntiSMASH analysis predicted that B. velezensis YA215 boasted 13 gene clusters involved in synthesis of antimicrobial secondary metabolites including surfactin, fengycin, macrolactin H, bacillaene, difficidin, bacillibactin, bacilysin, and plantazolicin. Three of the gene clusters (gene cluster 5, gene cluster 9, and gene cluster 10) have the potential to synthesize unknown compounds. The research underscore the considerable potential of secondary metabolites, identified in the genomic composition of B. velezensis YA215, as versatile antibacterial agents with a broad spectrum of activity against pathogenic bacteria.

Comprehensive insights into the differences of fungal communities at taxonomic and functional levels in stony coral Acropora intermedia under a natural bleaching event.

Previous studies have reported the correlations between bacterial communities and coral bleaching, but the knowledge of fungal roles in coral bleaching is still limited. In this study, the taxonomic and functional diversities of fungi in unbleached, partly bleached and bleached stony coral Acropora intermedia were investigated through the ITS-rRNA gene next-generation sequencing. An unexpected diversity of successfully classified fungi (a total of 167 fungal genera) was revealed in this study, and the partly bleached coral samples gained the highest fungal diversity, followed by bleached and unbleached coral samples. Among these fungi, 122 genera (nearly 73.2%) were rarely found in corals in previous studies, such as Calostoma and Morchella, which gave us a more comprehensive understanding of coral-associated fungi. Positively correlated fungal genera (Calostoma, Corticium, Derxomyces, Fusicolla, Penicillium and Vishniacozyma) and negative correlated fungal genera (Blastobotrys, Exophiala and Dacryopinax) with the coral bleaching were both detected. It was found that a series of fungal genera, dominant by Apiotrichum, a source of opportunistic infections, was significantly enriched; while another fungal group majoring in Fusicolla, a probiotic fungus, was distinctly depressed in the bleached coral. It was also noteworthy that the abundance of pathogenic fungi, including Fusarium, Didymella and Trichosporon showed a rising trend; while the saprotrophic fungi, including Tricladium, Botryotrichum and Scleropezicula demostrated a declining trend as the bleaching deteriorating. The rising of pathogenic fungi and the declining of saprotrophic fungi revealed the basic rules of fungal community transitions in the coral bleaching, but the mechanism of coral-associated fungal interactions still lacks further investigation. Overall, this is an investigation focused on the differences of fungal communities at taxonomic and functional levels in stony coral A. intermedia under different bleaching statuses, which provides a better comprehension of the correlations between fungal communities and the coral bleaching.

Time-shifted expression of acetoclastic and methylotrophic methanogenesis by a single Methanosarcina genomospecies predominates the methanogen dynamics in Philippine rice field soil.

BACKGROUND: The final step in the anaerobic decomposition of biopolymers is methanogenesis. Rice field soils are a major anthropogenic source of methane, with straw commonly used as a fertilizer in rice farming. Here, we aimed to decipher the structural and functional responses of the methanogenic community to rice straw addition during an extended anoxic incubation (120 days) of Philippine paddy soil. The research combined process measurements, quantitative real-time PCR and RT-PCR of particular biomarkers (16S rRNA, mcrA), and meta-omics (environmental genomics and transcriptomics). RESULTS: The analysis methods collectively revealed two major bacterial and methanogenic activity phases: early (days 7 to 21) and late (days 28 to 60) community responses, separated by a significant transient decline in microbial gene and transcript abundances and CH4 production rate. The two methanogenic activity phases corresponded to the greatest rRNA and mRNA abundances of the Methanosarcinaceae but differed in the methanogenic pathways expressed. While three genetically distinct Methanosarcina populations contributed to acetoclastic methanogenesis during the early activity phase, the late activity phase was defined by methylotrophic methanogenesis performed by a single Methanosarcina genomospecies. Closely related to Methanosarcina sp. MSH10X1, mapping of environmental transcripts onto metagenome-assembled genomes (MAGs) and population-specific reference genomes revealed this genomospecies as the key player in acetoclastic and methylotrophic methanogenesis. The anaerobic food web was driven by a complex bacterial community, with Geobacteraceae and Peptococcaceae being putative candidates for a functional interplay with Methanosarcina. Members of the Methanocellaceae were the key players in hydrogenotrophic methanogenesis, while the acetoclastic activity of Methanotrichaceae members was detectable only during the very late community response. CONCLUSIONS: The predominant but time-shifted expression of acetoclastic and methylotrophic methanogenesis by a single Methanosarcina genomospecies represents a novel finding that expands our hitherto knowledge of the methanogenic pathways being highly expressed in paddy soils. Video Abstract.

Machine learning for detecting Wilson's disease by amplitude of low-frequency fluctuation.

Wilson's disease (WD) is a genetic disorder with the A7P7B gene mutations. It is difficult to diagnose in clinic. The purpose of this study was to confirm whether amplitude of low-frequency fluctuations (ALFF) is one of the potential biomarkers for the diagnosis of WD. The study enrolled 30 healthy controls (HCs) and 37 WD patients (WDs) to obtain their resting-state functional magnetic resonance imaging (rs-fMRI) data. ALFF was obtained through preprocessing of the rs-fMRI data. To distinguish between patients with WDs and HCs, four clusters with abnormal ALFF-z values were identified through between-group comparisons. Based on these clusters, three machine learning models were developed, including Random Forest (RF), Support Vector Machine (SVM), and Logistic Regression (LR). Abnormal ALFF z-values were also combined with volume information, clinical variables, and imaging features to develop machine learning models. There were 4 clusters where the ALFF z-values of the WDs were significantly higher than that of the HCs. Cluster1 was in the cerebellar region, Cluster2 was in the left caudate nucleus, Cluster3 was in the bilateral thalamus, and Cluster4 was in the right caudate nucleus. In the training set and test set, the models trained with Cluster2, Cluster3, and Cluster4 achieved area of curve (AUC) greater than 0.80. In the Delong test, only the AUC values of models trained with Cluster4 exhibited statistical significance. The AUC values of the Logit model (P = 0.04) and RF model (P = 0.04) were significantly higher than those of the SVM model. In the test set, the LR model and RF model trained with Cluster3 had high specificity, sensitivity, and accuracy. By conducting the Delong test, we discovered that there was no statistically significant inter-group difference in AUC values between the model that integrates multi-modal information and the model before fusion. The LR models trained with multimodal information and Cluster 4, as well as the LR and RF models trained with multimodal information and Cluster 3, have demonstrated high accuracy, specificity, and sensitivity. Overall, these findings suggest that using ALFF based on the thalamus or caudate nucleus as markers can effectively differentiate between WDs and HCs. The fusion of multimodal information did not significantly improve the classification performance of the models before fusion.

Released dsDNA-triggered inflammasomes serve as intestinal radioprotective targets.

Objectives: Intestinal mucositis is the major side effect during abdominal or pelvic radiotherapy, but the underlying immunogen remains to be further characterised and few radioprotective agents are available. This study investigated the role of dsDNA-triggered inflammasomes in intestinal mucositis during radiotherapy. Methods: Pro-inflammatory cytokines were detected by ELISA. Radiation-induced intestinal injury in mice was analyzed by means of survival curves, body weight, HE staining of intestines, and intestinal barrier integrity. Western blot, immunofluorescence staining, co-immunoprecipitation assay and flow cytometry were used to investigate the regulatory role of dsDNA on inflammasomes. Results: Here, we show that a high level of IL-1ß and IL-18 is associated with diarrhoea in colorectal cancer (CRC) patients during radiotherapy, which accounts for intestinal radiotoxicity. Subsequently, we found that the dose-dependently released dsDNA from the intestinal epithelial cells (IECs) serves as the potential immunogenic molecule for radiation-induced intestinal mucositis. Our results further indicate that the released dsDNA transfers into the macrophages in an HMGB1/RAGE-dependent manner and then triggers absent in melanoma 2 (AIM2) inflammasome activation and the IL-1ß and IL-18 secretion. Finally, we show that the FDA-approved disulfiram (DSF), a newly identified inflammasome inhibitor, could mitigate intestinal radiotoxicity by controlling inflammasome. Conclusion: These findings indicate that the extracellular self-dsDNA released from the irradiated IECs is a potential immunogen to stimulate immune cells and trigger the subsequent intestinal mucositis, while blunting the dsDNA-triggered inflammasome in macrophages may represent an exciting therapeutic strategy for side effects control during abdominal radiotherapy.

Metagenomic insights into genetic factors driving bacterial niche differentiation between bulk and rhizosphere soils.

Cellular motility is crucial for effective colonization of the rhizosphere, but it is not yet clear whether bacterial motility is particularly linked to other genetic traits. Here, we applied genome-resolved metagenomics and phylogenomics to investigate the ecological significance of cellular motility for niche differentiation and the links between the genetic makeup of motile bacteria and rhizosphere colonization within a four-decade maize field experiment. Indeed, highly diverse sets of genes encoding cellular motility, including chemotaxis, flagellar assembly and motility proteins, and utilization of polymeric carbon were the important predictors of bacterial niche differentiation between bulk and rhizosphere soils. This is well exemplified by metagenome-assembled genomes encoding high motility capacity (hmc_MAGs). Their collective abundance was, on average, sixfold higher in rhizosphere soil than in bulk soil. All bulk-soil-derived MAGs showed low motility capacities (lmc). The hmc_MAGs were highly enriched in beneficial traits involved in carbohydrate utilization, assimilatory (nasA) and dissimilatory (nirBD) nitrate reduction, inorganic phosphate solubilization (gcd), and organic phosphate mineralization (phoD). Belonging to the families Sphingomonadaceae, Burkholderiaceae and Steroidobacteraceae, the hmc_MAGs showed a ninefold greater enrichment in these traits than proteobacterial lmc_MAGs and a twofold greater enrichment than 264 genomes publicly available for the above three families, thereby substantiating that a specific rhizosphere effect acted on the microbes represented by the hmc_MAGs. The particular link between the genetic capacities for high cellular motility and increased carbohydrate depolymerization as the key determinant for plant-selected rhizosphere colonization was further substantiated by the analysis of public bulk-rhizosphere soil metagenomes retrieved from wheat and cucumber field sites.

Harnessing biological nitrogen fixation in plant leaves.

The importance of biological nitrogen fixation (BNF) in securing food production for the growing world population with minimal environmental cost has been increasingly acknowledged. Leaf surfaces are one of the biggest microbial habitats on Earth, harboring diverse free-living N2-fixers. These microbes inhabit the epiphytic and endophytic phyllosphere and contribute significantly to plant N supply and growth. Here, we summarize the contribution of phyllosphere-BNF to global N cycling, evaluate the diversity of leaf-associated N2-fixers across plant hosts and ecosystems, illustrate the ecological adaptation of N2-fixers to the phyllosphere, and identify the environmental factors driving BNF. Finally, we discuss potential BNF engineering strategies to improve the nitrogen uptake in plant leaves and thus sustainable food production.

Global biogeographic distribution of Bathyarchaeota in paddy soils.

Bathyarchaeota, known as key participants of global elements cycling, is highly abundant and diverse in the sedimentary environments. Bathyarchaeota has been the research spotlight on sedimentary microbiology; however, its distribution in arable soils is far from understanding. Paddy soil is a habitat similar to freshwater sediments, while the distribution and composition of Bathyarchaeota in paddy soils have largely been overlooked. In this study, we collected 342 in situ paddy soil sequencing data worldwide to illuminate the distribution patterns of Bathyarchaeota and explore their potential ecological functions in paddy soils. The results showed that Bathyarchaeota is the dominant archaeal lineage, and Bathy-6 is the most predominant subgroup in paddy soils. Based on random forest analysis and construction of a multivariate regression tree, the mean annual precipitation and mean annual temperature are identified as the factors significantly influencing the abundance and composition of Bathyarchaeota in paddy soils. Bathy-6 was abundant in temperate environments, while other subgroups were more abundant in sites with higher rainfall. There are highly frequent associations between Bathyarchaeota and methanogens and ammonia-oxidizing archaea. The interactions between Bathyarchaeota and microorganisms involved in carbon and nitrogen metabolism imply a potential syntrophy between these microorganisms, suggesting that members of Bathyarchaeota could be important participants of geochemical cycle in paddy soils. These results shed light on the ecological lifestyle of Bathyarchaeota in paddy soils, and provide some baseline for further understanding Bathyarchaeota in arable soils. IMPORTANCE Bathyarchaeota, the dominant archaeal lineage in sedimentary environments, has been the spotlight of microbial research due to its vital role in carbon cycling. Although Bathyarchaeota has been also detected in paddy soils worldwide, its distribution in this environment has not yet been investigated. In this study, we conducted a global scale meta-analysis and found that Bathyarchaeota is also the dominant archaeal lineage in paddy soils with significant regional abundance differences. Bathy-6 is the most predominant subgroup in paddy soils, which differs from sediments. Furthermore, Bathyarchaeota are highly associated with methanogens and ammonia-oxidizing archaea, suggesting that they may be involved in the carbon and nitrogen cycle in paddy soil. These interactions provide insight into the ecological functions of Bathyarchaeota in paddy soils, which will be the foundation of future studies regarding the geochemical cycle in arable soils and global climate change.