[Advances of gut-on-a-chip for exploring host-microbe interactions].

The human gut is a complex ecosystem harboring rich microbes that play a key role in the nutrient absorption, drug metabolism, and immune responses. With the continuous development of microfluidics and organ-on-a-chip, gut-on-a-chip has become a powerful tool for modeling host-microbe interactions. The chip is able to mimic the complex physiological environment of the human gut in vitro, providing a unique platform for studying host-microbe interactions. Firstly, we introduce the physiological characteristics of the human gut. Secondly, we comprehensively summarize the advantages of the microfluidic chip in vitro recapitulating the intestinal system by integrating microenvironmental factors, such as complex cell components, dynamic fluids, oxygen gradients, and mechanical mechanics. Thirdly, we expound the key performance indicators for evaluating the construction performance of gut-on-a-chip. In addition, we review the progress of gut-on-a-chip models in the research on gut microecology, disease modeling, and drug evaluation. Finally, we highlight the challenges and prospects in the applications of the emerging technology. The above is summarized with a view to informing the application of gut-on-a-chip for indepth studies of gut microbe-host interactions.

Effects of four potent entomopathogenic fungal isolates on the survival and performance of Telenomus remus, an egg parasitoid of fall armyworm.

Fall armyworm (FAW), Spodoptera frugiperda is a generalist pest known to feed on more than 300 plant species, including major staple crops such as rice, maize and sorghum. Biological control of FAW using a combination of a major indigenous egg parasitoid Telenomus remus and entomopathogenic fungi was explored in this study. Metarhizium anisopliae strains (ICIPE 7, ICIPE 41, and ICIPE 78) and Beauveria bassiana ICIPE 621 which demonstrated effectiveness to combat the pest, were evaluated through direct and indirect fungal infection to assess their pathogenicity and virulence against T. remus adults, S. frugiperda eggs and their effects on T. remus parasitism rates. Metarhizium anisopliae ICIPE 7 and ICIPE 78 exhibited the highest virulence against T. remus adults with LT50 values >2 days. ICIPE 7 induced the highest T. remus mortality rate (81.40 ± 4.17%) following direct infection with dry conidia. Direct fungal infection also had a significant impact on parasitoid emergence, with the highest emergence rate recorded in the M. anisopliae ICIPE 7 treatment (42.50 ± 5.55%), compared to the control ± (83.25 ± 5.94%). In the indirect infection, the highest concentration of 1 x 109 conidia ml-1 of ICIPE 78 induced the highest mortality (100 ± 0.00%) of T. remus adults, and the highest mortality (51.25%) of FAW eggs, whereas the least FAW egg mortality (15.25%) was recorded in the lowest concentration 1 x 105 conidia ml-1 of ICIPE 41. The number of parasitoids that emerged and their sex ratios were not affected by the different fungal strain concentrations except in ICIPE 7 at high dose. This study showed that potential combination of both M. anisopliae and B. bassiana with T. remus parasitoid can effectively suppress FAW populations.

Phosphorus availability influences disease-suppressive soil microbiome through plant-microbe interactions.

BACKGROUND: Soil nutrient status and soil-borne diseases are pivotal factors impacting modern intensive agricultural production. The interplay among plants, soil microbiome, and nutrient regimes in agroecosystems is essential for developing effective disease management. However, the influence of nutrient availability on soil-borne disease suppression and associated plant-microbe interactions remains to be fully explored. T his study aims to elucidate the mechanistic understanding of nutrient impacts on disease suppression, using phosphorous as a target nutrient. RESULTS: A 6-year field trial involving monocropping of tomatoes with varied fertilizer manipulations demonstrated that phosphorus availability is a key factor driving the control of bacterial wilt disease caused by Ralstonia solanacearum. Subsequent greenhouse experiments were then conducted to delve into the underlying mechanisms of this phenomenon by varying phosphorus availability for tomatoes challenged with the pathogen. Results showed that the alleviation of phosphorus stress promoted the disease-suppressive capacity of the rhizosphere microbiome, but not that of the bulk soil microbiome. This appears to be an extension of the plant trade-off between investment in disease defense mechanisms versus phosphorus acquisition. Adequate phosphorus levels were associated with elevated secretion of root metabolites such as L-tryptophan, methoxyindoleacetic acid, O-phosphorylethanolamine, or mangiferin, increasing the relative density of microbial biocontrol populations such as Chryseobacterium in the rhizosphere. On the other hand, phosphorus deficiency triggered an alternate defense strategy, via root metabolites like blumenol A or quercetin to form symbiosis with arbuscular mycorrhizal fungi, which facilitated phosphorus acquisition as well. CONCLUSION: Overall, our study shows how phosphorus availability can influence the disease suppression capability of the soil microbiome through plant-microbial interactions. These findings highlight the importance of optimizing nutrient regimes to enhance disease suppression, facilitating targeted crop management and boosting agricultural productivity. Video Abstract.

Biotic interactions, evolutionary forces and the pan-plant specialized metabolism.

Plant specialized metabolism has a complex evolutionary history. Some aspects are conserved across the green lineage, but many metabolites are unique to certain lineages. The network of specialized metabolism continuously diversified, simplified or reshaped during the evolution of streptophytes. Many routes of pan-plant specialized metabolism are involved in plant defence. Biotic interactions are recalled as major drivers of lineage-specific metabolomic diversification. However, the consequences of this diversity of specialized metabolism in the context of plant terrestrialization and land plant diversification into the major lineages of bryophytes, lycophytes, ferns, gymnosperms and angiosperms remain only little explored. Overall, this hampers conclusions on the evolutionary scenarios that shaped specialized metabolism. Recent efforts have brought forth new streptophyte model systems, an increase in genetically accessible species from distinct major plant lineages, and new functional data from a diversity of land plants on specialized metabolic pathways. In this review, we will integrate the recent data on the evolution of the plant immune system with the molecular data of specialized metabolism and its recognition. Based on this we will provide a contextual framework of the pan-plant specialized metabolism, the evolutionary aspects that shape it and the impact on adaptation to the terrestrial environment.This article is part of the theme issue 'The evolution of plant metabolism'.

Dose Effect of Polyethylene Microplastics Derived from Commercial Resins on Soil Properties, Bacterial Communities, and Enzymatic Activity.

Soils are the largest reservoir of microplastics (MPs) on earth. Since MPs can remain in soils for a very long time, their effects are magnified. In this study, different concentrations of polyethylene (PE) MPs derived from commercial resins (0%, 1%, 7%, and 14%, represented as MP_0, MP_1, MP_7, and MP_14) were added to soils to assess the changes in the soils' chemical properties, enzyme activities, and bacterial communities during a 70-day incubation period. The results show that PE MP treatments with low concentrations differed from other treatments in terms of exchangeable Ca and Mg, whereas at high concentrations, the pH and availability of phosphate ions differed. Fluorescein diacetate (FDA), acid phosphatase (ACP), and N-acetyl-ß-d-glucosaminidase (NAG) enzyme activities exhibited a dose-related trend with the addition of the PE MPs; however, the average FDA and ACP activities were significantly affected only by MP_14. Changes in the microbial communities were observed at both the phylum and family levels with all PE MP treatments. It was revealed that even a low dosage of PE MPs in soils can affect the functional microbes, and a greater impact is observed on those that can survive in polluted environments with limited resources.

Decoding the Gut Microbiome in Companion Animals: Impacts and Innovations.

The changing notion of "companion animals" and their increasing global status as family members underscores the dynamic interaction between gut microbiota and host health. This review provides a comprehensive understanding of the intricate microbial ecology within companion animals required to maintain overall health and prevent disease. Exploration of specific diseases and syndromes linked to gut microbiome alterations (dysbiosis), such as inflammatory bowel disease, obesity, and neurological conditions like epilepsy, are highlighted. In addition, this review provides an analysis of the various factors that impact the abundance of the gut microbiome like age, breed, habitual diet, and microbe-targeted interventions, such as probiotics. Detection methods including PCR-based algorithms, fluorescence in situ hybridisation, and 16S rRNA gene sequencing are reviewed, along with their limitations and the need for future advancements. Prospects for longitudinal investigations, functional dynamics exploration, and accurate identification of microbial signatures associated with specific health problems offer promising directions for future research. In summary, it is an attempt to provide a deeper insight into the orchestration of multiple microbial species shaping the health of companion animals and possible species-specific differences.

The Role of Salicylic, Jasmonic Acid and Ethylene in the Development of the Resistance/Susceptibility of Wheat to the SnTox1-Producing Isolate of the Pathogenic Fungus Stagonospora nodorum (Berk.).

The SnTox1 effector is a virulence factor of the fungal pathogen Stagonospora nodorum (Berk.), which interacts with the host susceptibility gene Snn1 in a gene-for-gene manner and causes necrosis on the leaves of sensitive wheat genotypes. It is known that salicylic acid (SA), jasmonic acid (JA) and ethylene are the key phytohormones involved in plant immunity. To date, effectors of various pathogens have been discovered that can manipulate plant hormonal pathways and even use hormone crosstalk to promote disease development. However, the role of SnTox1 in manipulating hormonal pathways has not been studied in detail. We studied the redox status and the expression of twelve genes of hormonal pathways and two MAPK genes in six bread wheat cultivars sensitive and insensitive to SnTox1 with or without treatment by SA, JA and ethephon (ethylene-releasing agent) during infection with the SnTox1-producing isolate S. nodorum 1SP. The results showed that SnTox1 controls the antagonism between the SA and JA/ethylene signaling pathways. The SA pathway was involved in the development of susceptibility, and the JA/ethylene pathways were involved in the development of wheat plants resistance to the Sn1SP isolate in the presence of a SnTox1-Snn1 interaction. SnTox1 hijacked the SA pathway to suppress catalase activity, increase hydrogen peroxide content and induce necrosis formation; it simultaneously suppresses the JA and ethylene hormonal pathways by SA. To do this, SnTox1 reprogrammed the expression of the MAPK genes TaMRK3 and TaMRK6 and the TF genes TaWRKY13, TaEIN3 and TaWRKY53b. This study provides new data on the role of SnTox1 in manipulating hormonal pathways and on the role of SA, JA and ethylene in the pathosystem wheat S. nodorum.

Microbe-drug association prediction model based on graph convolution and attention networks.

The human microbiome plays a key role in drug development and precision medicine, but understanding its complex interactions with drugs remains a challenge. Identifying microbe-drug associations not only enhances our understanding of their mechanisms but also aids in drug discovery and repurposing. Traditional experiments are expensive and time-consuming, making computational methods for predicting microbe-drug associations a new trend. Currently, computational methods specifically designed for this task are still scarce. Therefore, to address the shortcomings of traditional experimental methods in predicting potential microbe-drug associations, this paper proposes a new prediction model named GCNATMDA. The model combines two deep learning models, Graph Convolutional Network and Graph Attention Network, and aims to reveal potential relationships between microbes and drugs by learning related features. Thus improve the efficiency and accuracy of prediction. We first integrated the microbe-drug association matrix from the existing dataset, and then combined the calculated microbe-drug characteristic matrix as the model input. The GCN module is used to dig deeper into the potential characterization of microbes and drugs, while the GAT module further learns the more complex interactions between them and generates the corresponding score matrix. The experimental results show that the GCNATMDA model achieves 96.59% and 93.01% in AUC and AUPR evaluation indexes, respectively, which is significantly better than the existing prediction models. In addition, the reliability of the prediction results is verified by a series of experiments.

Posttranslational modifications: an emerging functional layer of diet-host-microbe interactions.

The microbiome plays a vital role in human health, with changes in its composition impacting various aspects of the body. Posttranslational modification (PTM) regulates protein activity by attaching chemical groups to amino acids in an enzymatic or non-enzymatic manner. PTMs offer fast and dynamic regulation of protein expression and can be influenced by specific dietary components that induce PTM events in gut microbiomes and their hosts. PTMs on microbiome proteins have been found to contribute to host-microbe interactions. For example, in Escherichia coli, S-sulfhydration of tryptophanase regulates uremic toxin production and chronic kidney disease in mice. On a broader microbial scale, the microbiomes of patients with inflammatory bowel disease exhibit distinct PTM patterns in their metaproteomes. Moreover, pathogens and commensals can alter host PTM profiles through protein secretion and diet-regulated metabolic shifts. The emerging field of metaPTMomics focuses on understanding PTM profiles in the microbiota, their association with lifestyle factors like diet, and their functional effects on host-microbe interactions.

In situ deposition of nanobodies by an engineered commensal microbe promotes survival in a mouse model of enterohemorrhagic E. coli.

Engineered smart microbes that deliver therapeutic payloads are emerging as treatment modalities, particularly for diseases with links to the gastrointestinal tract. Enterohemorrhagic Escherichia coli (EHEC) is a causative agent of potentially lethal hemolytic uremic syndrome. Given concerns that antibiotic treatment increases EHEC production of Shiga toxin (Stx), which is responsible for systemic disease, novel remedies are needed. EHEC encodes a type III secretion system (T3SS) that injects Tir into enterocytes. Tir inserts into the host cell membrane, exposing an extracellular domain that subsequently binds intimin, one of its outer membrane proteins, triggering the formation of attaching and effacing (A/E) lesions that promote EHEC mucosal colonization. Citrobacter rodentium (Cr), a natural A/E mouse pathogen, similarly requires Tir and intimin for its pathogenesis. Mice infected with Cr(ΦStx2dact), a variant lysogenized with an EHEC-derived phage that produces Stx2dact, develop intestinal A/E lesions and toxin-dependent disease. Stx2a is more closely associated with human disease. By developing an efficient approach to seamlessly modify the C. rodentium genome, we generated Cr_Tir-MEHEC(ΦStx2a), a variant that expresses Stx2a and the EHEC extracellular Tir domain. We found that mouse precolonization with HS-PROT3EcT-TD4, a human commensal E. coli strain (E. coli HS) engineered to efficiently secrete an anti-EHEC Tir nanobody, delayed bacterial colonization and improved survival after challenge with Cr_Tir-MEHEC(ΦStx2a). This study suggests that commensal E. coli engineered to deliver payloads that block essential virulence determinants can be developed as a new means to prevent and potentially treat infections including those due to antibiotic resistant microbes.

ANS-SCMC: A matrix completion method based on adaptive neighbourhood similarity and sparse constraints for predicting microbe-disease associations.

The use of matrix completion methods to predict the association between microbes and diseases can effectively improve treatment efficiency. However, the similarity measures used in the existing methods are often influenced by various factors such as neighbourhood size, choice of similarity metric, or multiple parameters for similarity fusion, making it challenging. Additionally, matrix completion is currently limited by the sparsity of the initial association matrix, which restricts its predictive performance. To address these problems, we propose a matrix completion method based on adaptive neighbourhood similarity and sparse constraints (ANS-SCMC) for predict microbe-disease potential associations. Adaptive neighbourhood similarity learning dynamically uses the decomposition results as effective information for the next learning iteration by simultaneously performing local manifold structure learning and decomposition. This approach effectively preserves fine local structure information and avoids the influence of weight parameters directly involved in similarity measurement. Additionally, the sparse constraint-based matrix completion approach can better handle the sparsity challenge in the association matrix. Finally, the algorithm we proposed has achieved significantly higher predictive performance in the validation compared to several commonly used prediction methods proposed to date. Furthermore, in the case study, the prediction algorithm achieved an accuracy of up to 80% for the top 10 microbes associated with type 1 diabetes and 100% for Crohn's disease respectively.

CMFHMDA: a prediction framework for human disease-microbe associations based on cross-domain matrix factorization.

Predicting associations between microbes and diseases opens up new avenues for developing diagnostic, preventive, and therapeutic strategies. Given that laboratory-based biological tests to verify these associations are often time-consuming and expensive, there is a critical need for innovative computational frameworks to predict new microbe-disease associations. In this work, we introduce a novel prediction algorithm called Predicting Human Disease-Microbe Associations using Cross-Domain Matrix Factorization (CMFHMDA). Initially, we calculate the composite similarity of diseases and the Gaussian interaction profile similarity of microbes. We then apply the Weighted K Nearest Known Neighbors (WKNKN) algorithm to refine the microbe-disease association matrix. Our CMFHMDA model is subsequently developed by integrating the network data of both microbes and diseases to predict potential associations. The key innovations of this method include using the WKNKN algorithm to preprocess missing values in the association matrix and incorporating cross-domain information from microbes and diseases into the CMFHMDA model. To validate CMFHMDA, we employed three different cross-validation techniques to evaluate the model's accuracy. The results indicate that the CMFHMDA model achieved Area Under the Receiver Operating Characteristic Curve scores of 0.9172, 0.8551, and 0.9351$\pm $0.0052 in global Leave-One-Out Cross-Validation (LOOCV), local LOOCV, and five-fold CV, respectively. Furthermore, many predicted associations have been confirmed by published experimental studies, establishing CMFHMDA as an effective tool for predicting potential disease-associated microbes.

Intergenerational neurotoxicity of polystyrene nanoplastics in offspring mice is mediated by dysfunctional microbe-gut-brain axis.

Nanoplastics (NPs) are ubiquitous in daily life, posing potential risks to the environment and human. While their negative effects on parental organisms have been extensively studied, intergenerational effects are still in the early stages of investigation. Here, we aimed to investigate the impact of maternal exposure to an environmentally relevant level of polystyrene NPs (PSNPs, 100 nm) during gestation and lactation (∼32 days, 50 µg/mouse/day) on neurotoxicity mediated by the microbe-gut-brain axis in offspring mice. Maternal PSNPs exposure significantly increased brain TNF-α level and microglia by 1.43 and 1.48 folds respectively, compared to control, accompanied by nuclear pyknosis and cell vacuolization in cortex and hippocampus. Targeted neurotransmitter metabolomics analysis revealed dysregulation in dopamine and serotonin metabolism. Specifically, dopamine levels increased significantly from 0.007 ng/L to 0.015 ng/L, while N-acetylseroton and 3,4-dihydroxyphenylacetic acid decreased significantly from 0.002 and 0.929 ng/L to 0.001 and 0.680 ng/L, respectively. Through a combination of 16S rRNA sequencing and biochemical analysis, we discovered that maternal PSNPs exposure led to a depletion of anti-inflammatory bacteria and an enrichment of pro-inflammatory bacteria resulting in intestinal barrier damage, elevated levels of lipopolysaccharide in blood, and subsequent activation of neuroinflammation. Meanwhile, gut bacteria dysbiosis interfered with communication between gut and brain by dysregulating neurotransmitter synthesis, as evidenced by significant associations between neurotransmitter-related bacteria (Akkermansia, Family_XIII_AD3011_group, Lachnoclostridium) and dopamine/serotonin related metabolites. Furthermore, transcriptional alterations in dopamine and serotonin related pathways were observed in the enteric nervous system, suggesting abnormal signal transduction from gut to brain contributes to neurotoxicity. This study provides new insights into NPs-induced neurotoxicity within the context of microbe-gut-brain axis and highlights the risk of cerebral dysfunction in offspring with maternal NPs exposure.

Long-term grazing reduces soil fungal network complexity but enhances plant-soil microbe network connectivity in a semi-arid grassland.

Grazing plays a significant role in shaping both aboveground vegetation and belowground microbial communities in arid and semi-arid grasslands, which in turn affects ecosystem functions and sustainability. Therefore, it was essential to implement effective grazing management practices to preserve ecological balance and support sustainable development in these delicate environments. To optimize the traditional continuous grazing policy, we conducted a 10-year seasonal grazing experiment with five treatments in a typical grassland in northern China: no grazing (NG), continuous summer grazing (CG), and three seasonal grazing treatments (G57 in May and July, G68 in June and August, and G79 in July and September). Our study found that although grazing reduced plant community biomass, G68 treatment maintained high plant height and community diversity (P < 0.05). Grazing did not affect soil bacterial and archaeal alpha diversity, but CG treatment reduced soil fungal diversity (P < 0.05). CG reduced the archaeal network's vertices (which represent microbial taxa, OTUs) and connections (ecological interactions between taxa), but seasonal grazing increased its complexity. Furthermore, grazing did not change bacterial networks but enhanced cross-domain interactions (relationships between different biological groups) of plant-soil fungi and plant-soil archaea. Overall, we used the Mantel test to find that soil microbial diversity was positively correlated with soil physicochemical properties rather than plant community characteristics after grazing. These findings are beneficial for the optimization of sustainable grassland management policies and the protection of plant and soil biodiversity.

Microbiome-Mucosal Immunity Nexus: Driving Forces in Respiratory Disease Progression.

The importance of the complex interplay between the microbiome and mucosal immunity, particularly within the respiratory tract, has gained significant attention due to its potential implications for the severity and progression of lung diseases. Therefore, this review summarizes the specific interactions through which the respiratory tract-specific microbiome influences mucosal immunity and ultimately impacts respiratory health. Furthermore, we discuss how the microbiome affects mucosal immunity, considering tissue-specific variations, and its capacity in respiratory diseases containing asthma, chronic obstructive pulmonary disease, and lung cancer. Additionally, we investigate the external factors which affect the relationship between respiratory microbiome and mucosal immune responses. By exploring these intricate interactions, this review provides valuable insights into the potential for microbiome-based interventions to modulate mucosal immunity and alleviate the severity of respiratory diseases.

New Approaches to Plant Pathogen Detection and Disease Diagnosis.

Detecting plant pathogens and diagnosing diseases are critical components of successful pest management. These key areas have undergone significant advancements driven by breakthroughs in molecular biology and remote sensing technologies within the realm of precision agriculture. Notably, nucleic acid amplification techniques, with recent emphasis on sequencing procedures, particularly next-generation sequencing, have enabled improved DNA or RNA amplification detection protocols that now enable previously unthinkable strategies aimed at dissecting plant microbiota, including the disease-causing components. Simultaneously, the domain of remote sensing has seen the emergence of cutting-edge imaging sensor technologies and the integration of powerful computational tools, such as machine learning. These innovations enable spectral analysis of foliar symptoms and specific pathogen-induced alterations, making imaging spectroscopy and thermal imaging fundamental tools for large-scale disease surveillance and monitoring. These technologies contribute significantly to understanding the temporal and spatial dynamics of plant diseases.

The hindgut microbiota of coconut rhinoceros beetles (Oryctes rhinoceros) in relation to their geographical populations.

The coconut rhinoceros beetle (CRB, Oryctes rhinoceros) is a palm tree pest capable of rapidly expanding its population in new territories. Previous studies identified a digestive symbiosis between CRB and its gut microbes. However, no research compared the genetic variation of CRBs with their hindgut microbiota on a global scale. This study aims to investigate the genetic divergence of CRB and the compositional variation of CRB's microbiota across different geographical locations, and explore the association between them and their predicted functional profiles and environmental data. The research reveals a distinct and consistent microbial community within local populations, but it varies across different geographical populations. The microbial functional profiles linked to the production of digestive enzymes, including cellulases and ligninases, are nonetheless globally conserved. This suggests that CRBs employ specific mechanisms to select and maintain microbes with functional benefits, contributing to host adaptability, stress tolerance, and fitness. The CRB microbial communities did not appear to recapitulate the genetic variation of their hosts. Rather than depend on obligate symbionts, CRBs seem to establish similar digestive associations with whatever environmentally acquired microbes are available wherever they are, aiding them in successfully establishing after invading a new location.IMPORTANCECoconut rhinoceros beetles (CRBs) are notorious pests on Arecaceae plants, posing destructive threats to countries highly reliant on coconut, oil palm, and date palm as economic crops. In the last century, CRBs have rapidly expanded their presence to territories that were once free of these beetles. The United States, for instance, has officially designated CRBs as invasive and alien pests. Given their remarkable ability to swiftly adapt to new environments, their gut microbes may play a crucial role in this process. While the microbiota of CRBs vary depending on geographical location, these beetles consistently exhibit a functionally identical digestive association with locally acquired microbes. This underscores the significance of CRB-microbe association in shaping the adaptive strategies of this agricultural pest.

Effect of dietary live microbe intake on the prevalence and mortality risks of depression and suicidal ideation in adults: Evidence from a nationwide population-based study.

BACKGROUND: Gut microbial dysbiosis has been implicated in the pathogenesis of depression. Dietary interventions offer promising microbial-targeted therapeutics for depression. However, limited evidence exists regarding the associations between dietary live microbe intake and the prevalence of depression, as well as its impact on mortality risks. METHODS: This study included 28,133 participants from the U.S. National Health and Nutrition Examination Survey (2005-2018), and ascertained their underlying causes of death. Weighted logistic regression was utilized to assess the relationships between live microbe intake and risks of depression and suicidal ideation. Independent and joint associations between live microbe and mortality outcomes were evaluated using multivariable Cox regression and Kaplan-Meier survival curves to calculate relative risks. RESULTS: In the fully adjusted model, participants with high dietary live microbe intake had a significantly lower prevalence of depression (OR = 0.727, 95%CI: 0.627,0.844) and suicidal ideation (OR = 0.778, 95%CI: 0.648,0.935) than those with low intake. The multivariable-adjusted HRs for individuals in the G1 were 1.217 (95%CI, 1.081, 1.370) for all-cause mortality and 1.307 (95%CI, 1.029,1.661) for cardiovascular disease mortality, compared to participants in the G3. Kaplan-Meier survival analysis revealed that cumulative hazard of cardiovascular mortality was progressively lower among participants with depression in the G3 than those without depression. CONCLUSIONS: Higher live microbe intake was associated with a lower prevalence of depression and suicidal ideation, and was linked to significantly decreased risks of all-cause and cardiovascular mortality. Further larger prospective studies are essential to verify the health effects of live microbes, and personalized dietary recommendations are necessary.

Exploring the relationship between live microbe intake and obesity prevalence in adults.

Obesity has become a global health problem. In recent years, the influence of dietary microbes in the obese population has attracted the attention of scholars. Our study aimed to investigate the link between live microbe intake and obesity in adults. Participants (aged over 20 years) for this study were from the 1999-2018 National Health and Nutrition Examination Survey (NHANES). Participants were categorised into low, medium and high dietary live microbe intake groups. Linear regression was used to analyse the link between live microbe intake and body mass index (BMI) and waist circumference (WC). Logistic regression was used to analyse the link between live microbe intake and obesity and abdominal obesity prevalence. Restricted cubic spline curves (RCS) were used to check whether there was a non-linear relationship between live microbe intake and obesity. A total of 42,749 participants were included in this study and the number of obese reached 15,463. We found that live microbe intake was negatively linked to BMI and WC. In models adjusted for all confounders, the high live microbe intake group had lower obesity (OR = 0.812, 95%CI: 0.754-0.873) and abdominal obesity prevalence (OR = 0.851, 95%CI: 0.785-0.923) than the lowest intake group. Upon further quantification of live microbe intake, we found similar results. RCS analyses showed that live microbe intake was nonlinearly negatively correlated with BMI, WC, obesity, and abdominal obesity prevalence (P for non-linearity < 0.05). This study preliminarily reveals a negative link between live microbe intake and obesity in adults.

Plant Pattern recognition receptors: Exploring their evolution, diversification, and spatiotemporal regulation.

Plant genomes possess hundreds of candidate surface localized receptors capable of recognizing microbial components or modified-self molecules. Surface-localized pattern recognition receptors (PRRs) can recognize proteins, peptides, or structural microbial components as nonself, triggering complex signaling pathways leading to defense. PRRs possess diverse extracellular domains capable of recognizing epitopes, lipids, glycans and polysaccharides. Recent work highlights advances in our understanding of the diversity and evolution of PRRs recognizing pathogen components. We also discuss PRR functional diversification, pathogen strategies to evade detection, and the role of tissue and age-related resistance for effective plant defense.