Multigenerational Adaptation Can Enhance the Pathogen Resistance of Plants via Changes in Rhizosphere Microbial Community Assembly.

Plants withstand pathogen attacks by recruiting beneficial bacteria to the rhizosphere and passing their legacy on to the next generation. However, the underlying mechanisms involved in this process remain unclear. In our study, we combined microbiomic and transcriptomic analyses to reveal how the rhizosphere microbiome assembled through multiple generations and defense-related genes expressed in Arabidopsis thaliana under pathogen attack stress. Our results showed that continuous exposure to the pathogen Pseudomonas syringae pv tomato DC3000 led to improved growth and increased disease resistance in a third generation of rps2 mutant Arabidopsis thaliana. It could be attributed to the enrichment of specific rhizosphere bacteria, such as Bacillus and Bacteroides. Pathways associated with plant immunity and growth in A. thaliana, such as MAPK signaling pathways, phytohormone signal transduction, ABC transporter proteins, and flavonoid biosynthesis, were activated under the influence of rhizosphere bacterial communities. Our findings provide a scientific basis for explaining the relationship between beneficial microbes and defense-related gene expression. Understanding microbial communities and the mechanisms involved in plant responses to disease can contribute to better plant management and reduction of pesticide use.

Combined effects of azoxystrobin and oxytetracycline on rhizosphere microbiota of Arabidopsis thaliana.

The rhizosphere is one of the key determinants of plant health and productivity. Mixtures of pesticides are commonly used in intensified agriculture. However, the combined mechanisms underlying their impacts on soil microbiota remain unknown. The present study revealed that the rhizosphere microbiota was more sensitive to azoxystrobin and oxytetracycline, two commonly used pesticides, than was the microbiota present in bulk soil. Moreover, the rhizosphere microbiota enhanced network complexity and stability and increased carbohydrate metabolism and xenobiotic biodegradation as well as the expression of metabolic genes involved in defence against pesticide stress. Co-exposure to azoxystrobin and oxytetracycline had antagonistic effects on Arabidopsis thaliana growth and soil microbial variation by recruiting organic-degrading bacteria and regulating ABC transporters to reduce pesticide uptake. Our study explored the composition and function of soil microorganisms through amplicon sequencing and metagenomic approaches, providing comprehensive insights into the synergistic effect of plants and rhizosphere microbiota on pesticides and contributing to our understanding of the ecological risks associated with pesticide use.

Geographic patterns of microbial traits of river basins in China.

River microbiotas contribute to critical geochemical processes and ecological functions of rivers but are sensitive to variations of environmental drivers. Understanding the geographic pattern of river microbial traits in biogeochemical processes can provide important insights into river health. Many studies have characterized river microbial traits in specific situations, but the geographic patterns of these traits and environmental drivers at a large scale are unknown. We reanalyzed 4505 raw 16S rRNA sequences samples for microbiota from river basins in China. The results indicated differences in the diversity, composition, and structure of microbiotas across diverse river basins. Microbial diversity and functional potential in the river basins decreased over time in northern China and increased in southern China due to niche differentiation, e.g., the Yangtze River basin was the healthiest ecosystem. River microbiotas were mainly involved in the cycling of carbon and nitrogen in the river ecosystems and participated in potential organic metabolic functions. Anthropogenic pollutants discharge was the most critical environmental driver for the microbial traits, e.g., antibiotic discharge, followed by climate change. The prediction by machine-learning models indicated that the continuous discharge of antibiotics and climate change led to high ecological risks for the rivers. Our study provides guidelines for improving the health of river ecosystems and for the formulation of strategies to restore the rivers.

The mechanism of different cyanobacterial responses to glyphosate.

Glyphosate, the most extensively used herbicide globally, has raised ecotoxicological concerns because it can be transported into the aquatic environment and cause adverse effects on the aquatic system. However, the functional mechanism of glyphosate on cyanobacteria are not completely disentangled. In this study, we selected six common cyanobacteria to evaluate glyphosate effects on cyanobacterial growth in monoculture experiment. Results showed that the growth of five tested cyanobacterial species were promoted under different degrees, and only Pseudanabaena was inhibited by glyphosate. In the phylogenetic tree based on gene sequences of 5-enol-pyruvylshikimate-3-phosphate synthase (EPSPS), a target for glyphosate, we found that the position of Pseudanabaena is the closest to plant, which was sensitive to glyphosate, thereby explaining the inhibitory effect of Pseudanabaena following glyphosate exposure. The primary degraded metabolites or analogs did not induce cyanobacterial growth, laterally demonstrating that glyphosate was used as a source of phosphorus to accelerate cyanobacterial growth because phosphorus levels increased in the medium of glyphosate treatment. Overall, this study provides a better understanding of the influence of glyphosate on the composition of aquatic microbiota and explains the mechanism of cyanobacterial response to glyphosate.

Development of a machine-learning model to identify the impacts of pesticides characteristics on soil microbial communities from high-throughput sequencing data.

High-throughput sequencing (HTS) of soil environmental DNA provides an advanced insight into the effects of pesticides on soil microbial systems. However, the association between the properties of the pesticide and its ecological impact remains methodically challenging. Risks associated with pesticide use can be minimized if pesticides with optimal structural traits were applied. For this purpose, we merged the 20 independent HTS studies, to reveal that pesticides significantly reduced beneficial bacteria associated with soil and plant immunity, enhanced the human pathogen and weaken the soil's ecological stability. Through the machine-learning approach, correlating these impacts with the physicochemical properties of the pesticides yielded a random forest model with good predictive capabilities. The models revealed that physical pesticide properties such as the dissociation constant (pKa), the molecular weight and water solubility, determined the ecological impact of pesticides to a large extent. Moreover, this study identified that eco-friendly pesticides should possess a value of pKa > 5 and a molecular weight in the range of 200-300 g/mol, which were found to be conducive to bacteria related to plant immunity promotion and exerted the lowest fluctuation of human opportunistic pathogen and keystone species. This guides the design of pesticides for which the impacts on soil biota are minimized.

Response of microbial antibiotic resistance to pesticides: An emerging health threat.

The spread of microbial antibiotic resistance has seriously threatened public health globally. Non-antibiotic stressors have significantly contributed to the evolution of bacterial antibiotic resistance. Although numerous studies have been conducted on the potential risk of pesticide pollution for bacterial antibiotic resistance, a systematic review of these concerns is still lacking. In the present study, we elaborate the mechanism underlying the effects of pesticides on bacterial antibiotic resistance acquisition as well as the propagation of antimicrobial resistance. Pesticide stress enhanced the acquisition of antibiotic resistance in bacteria via various mechanisms, including the activation of efflux pumps, inhibition of outer membrane pores for resistance to antibiotics, and gene mutation induction. Horizontal gene transfer is a major mechanism whereby pesticides influence the transmission of antibiotic resistance genes (ARGs) in bacteria. Pesticides promoted the conjugation transfer of ARGs by increasing cell membrane permeability and increased the proportion of bacterial mobile gene elements, which facilitate the spread of ARGs. This review can improve our understanding regarding the pesticide-induced generation and spread of ARGs and antibiotic resistant bacteria. Moreover, it can be applied to reduce the ecological risks of ARGs in the future.

Development of a Potentially New Algaecide for Controlling Harmful Cyanobacteria Blooms Which is Ecologically Safe and Selective.

Harmful cyanobacterial blooms (HCBs) caused by Microcystis aeruginosa are of great concern as they negatively affect the aquatic environment and human health. Chemical methods could rapidly eradicate HCBs and have been used for many decades. However, many chemical reagents are not recommended to eliminate HCBs in the long term, given the possible destructive and toxic effects of the chemicals employed on non-target aquatic organisms. We developed a new algaecide, 2-((1,3,4-thiadiazol-2-yl)thio)-N-(4-chlorophenyl) acetamide (Q2), to control harmful cyanobacteria while being environmentally friendly and selective. In our study, Q2 effectively inhibited cyanobacterial growth, especially of M. aeruginosa, but did not affect eukaryotic algae in test concentrations. A critical mechanism was revealed by transcriptome and metagenomic results showing that Q2 affects multiple cellular targets of cyanobacteria for HCB control, including the destruction of organelles, damage in the photosynthesis center, as well as inhibition of gas vesicle growth, and these changes can be highly relevant to the decrease of quorum-sensing functional KEGG pathways. Furthermore, Q2 did not affect the microbial composition and could recover the disrupted aquatic functional pathways in a short period. This is different from the impact on ecosystem functioning of the traditionally used harmful algaecide diuron. All these results verified that Q2 could be friendly to the aquatic environment, providing a new directional choice in managing HCBs in the future.

Strain-boosted hyperoxic graphene oxide efficiently loading and improving performances of microcystinase.

Harmful Microcystis blooms (HMBs) and microcystins (MCs) that are produced by Microcystis seriously threaten water ecosystems and human health. This study demonstrates an eco-friendly strategy for simultaneous removal of MCs and HMBs by adopting unique hyperoxic graphene oxides (HGOs) as carrier and pure microcystinase A (PMlrA) as connecting bridge to form stable HGOs@MlrA composite. After oxidation, HGOs yield inherent structural strain effects for boosting the immobilization of MlrA by material characterization and density functional theory calculations. HGO5 exhibits higher loading capacities for crude MlrA (1,559 mg·g-1) and pure MlrA (1,659 mg·g-1). Moreover, the performances of HGO5@MlrA composite, including the capability of removing MCs and HMBs, the ecological and human safety compared to MlrA or HGO5 treatment alone, have been studied. These results indicate that HGO5 can be used as a promising candidate material to effectively improve the application potential of MlrA in the simultaneous removal of MCs and HMBs.

Compare the performance of multiple binary classification models in microbial high-throughput sequencing datasets.

The development of machine learning and deep learning provided solutions for predicting microbiota response on environmental change based on microbial high-throughput sequencing. However, there were few studies specifically clarifying the performance and practical of two types of binary classification models to find a better algorithm for the microbiota data analysis. Here, for the first time, we evaluated the performance, accuracy and running time of the binary classification models built by three machine learning methods - random forest (RF), support vector machine (SVM), logistic regression (LR), and one deep learning method - back propagation neural network (BPNN). The built models were based on the microbiota datasets that removed low-quality variables and solved the class imbalance problem. Additionally, we optimized the models by tuning. Our study demonstrated that dataset pre-processing was a necessary process for model construction. Among these 4 binary classification models, BPNN and RF were the most suitable methods for constructing microbiota binary classification models. Using these 4 models to predict multiple microbial datasets, BPNN showed the highest accuracy and the most robust performance, while the RF method was ranked second. We also constructed the optimal models by adjusting the epochs of BPNN and the n_estimators of RF for six times. The evaluation related to performances of models provided a road map for the application of artificial intelligence to assess microbial ecology.

Machine learning predicts ecological risks of nanoparticles to soil microbial communities.

With the rapid development of nanotechnology in agriculture, there is increasing urgency to assess the impacts of nanoparticles (NPs) on the soil environment. This study merged raw high-throughput sequencing (HTS) data sets generated from 365 soil samples to reveal the potential ecological effects of NPs on soil microbial community by means of metadata analysis and machine learning methods. Metadata analysis showed that treatment with nanoparticles did not have a significant impact on the alpha diversity of the microbial community, but significantly altered the beta diversity. Unfortunately, the abundance of several beneficial bacteria, such as Dyella, Methylophilus, Streptomyces, which promote the growth of plants, and improve pathogenic resistance, was reduced under the addition of synthetic nanoparticles. Furthermore, metadata demonstrated that nanoparticles treatment weakened the biosynthesis ability of cofactors, carriers, and vitamins, and enhanced the degradation ability of aromatic compounds, amino acids, etc. This is unfavorable for the performance of soil functions. Besides the soil heterogeneity, machine learning uncovered that a) the exposure time of nanoparticles was the most important factor to reshape the soil microbial community, and b) long-term exposure decreased the diversity of microbial community and the abundance of beneficial bacteria. This study is the first to use a machine learning model and metadata analysis to investigate the relationship between the properties of nanoparticles and the hazards to the soil microbial community from a macro perspective. This guides the rational use of nanoparticles for which the impacts on soil microbiota are minimized.

Phyllosphere Microorganisms: Sources, Drivers, and Their Interactions with Plant Hosts.

The leaves of plants are colonized by various microorganisms. In comparison to the rhizosphere, less is known about the characteristics and ecological functions of phyllosphere microorganisms. Phyllosphere microorganisms mainly originate from soil, air, and seeds. The composition of phyllosphere microorganisms is mainly affected by ecological and abiotic factors. Phyllosphere microorganisms execute multiple ecological functions by influencing leaf functions and longevity, seed mass, fruit development, and homeostasis of host growth. A plant can respond to phyllosphere microorganisms by secondary metabolite secretion and its immune system. Meanwhile, phyllosphere microorganisms play an important role in ecological stability and environmental safety assessment. However, as a result of the instability of the phyllosphere environment and the poor cultivability of phyllosphere microorganisms in the current research, there are still many limitations, such as the lack of insight into the mechanisms of plant-microorganism interactions, the roles of phyllosphere microorganisms in plant growth processes, the responses of phyllosphere microorganisms to plant metabolites, etc. This review summarizes the latest progress made in the research of the phyllosphere in recent years. This is beneficial for deepening our understanding of phyllosphere microorganisms and promoting the research of plant-atmosphere interactions, plant pathogens, and plant biological control.

Effects of chiral herbicide dichlorprop on Arabidopsis thaliana metabolic profile and its implications for microbial communities in the phyllosphere.

Dichlorprop (2-(2,4-dichlorophenoxy) propionic acid, DCPP), a commonly used herbicide for weed control, can be residually detected in soil. It is still unclear whether chiral DCPP exerts an enantioselective adverse effect on plant metabolism and the microbial community of the phyllosphere. In this study, we selected Arabidopsis thaliana as a model plant to explore the effects of R- and S-DCPP enantiomers on plant physiological activities, metabolism, and associated changes in the phyllosphere microbial community. Results indicated that the fresh weight of plants decreased by 37.6% after R-DCPP treatment, whereas it increased by 7.6% after S-DCPP treatment. The R-DCPP enantiomer also caused stronger disturbance to leaf morphology, mesophyll cell structure, and leaf metabolites compared with S-DCPP. GC-MS analysis of DCPP-treated Arabidopsis leaves pointed out a differential profile mostly in carbohydrates, organic acids, and fatty acids, between S-DCPP and R-DCPP treatments. The diversity of phyllospheric microorganisms decreased and the stability of microbial community in the phyllosphere increased after R-DCPP treatment, whereas the opposite result was detected after S-DCPP exposure. The correlation analysis revealed that chiral herbicides may affect microbial communities in the phyllosphere by influencing leaf metabolism, while sugars and terpenoids were considered the main factors in reshaping the microbial community structure in the phyllosphere. Our study provides a new perspective for evaluating the effect of residual DCPP enantiomers on plant physiology and corresponding phyllosphere microorganism changes via the regulation of leaf metabolism, and clarifies the ecological risk of DCPP enantiomer application in agriculture.

Leaf metabolic influence of glyphosate and nanotubes on the Arabidopsis thaliana phyllosphere.

Chemical exposure can indirectly affect leaf microbiota communities, but the mechanism driving this phenomenon remains largely unknown. Results revealed that the co-exposure of glyphosate and multi-carbon nanotubes (CNTs) caused a synergistic inhibitory effect on the growth and metabolism of Arabidopsis thaliana shoots. However, only a slight inhibitory effect was induced by nanotubes or glyphosate alone at the tested concentrations. Several intermediate metabolites of nitrogen metabolism and fatty acid synthesis pathways were upregulated under the combined treatment, which increased the amount of energy required to alleviate the disruption caused by the combined treatment. Additionally, compared with the two individual treatments, the glyphosate/nanotube combination treatment induced greater fluctuations in the phyllosphere bacterial community members with low abundance (relative abundance (RA) <1%) at both the family and genus levels, and among these bacteria some plant growth promotion and nutrient supplement related bacteria were markable increased. Strikingly, strong correlations between phyllosphere bacterial diversity and metabolites suggested a potential role of leaf metabolism, particularly nitrogen and carbohydrate metabolism, in restricting the range of leaf microbial taxa. These correlations between phyllosphere bacterial diversity and leaf metabolism will improve our understanding of plant-microbe interactions and the extent of their drivers of variation and the underlying causes of variability in bacterial community composition.

Synergetic toxicity of silver nanoparticle and glyphosate on wheat (Triticum aestivum L.).

Silver nanoparticles (AgNPs) are one of the most commonly used nanomaterials in industrial and agricultural production. Glyphosate is a broad-spectrum systemic herbicide, which mainly acts in the phloem of weeds that compete with crop growth and is widely used in agriculture. This study investigated the interactive effects of AgNPs and glyphosate on the physiological morphology, gene transcription, and rhizosphere microorganisms of wheat. Our results demonstrated that wheat growth, and the structure and diversity of rhizosphere microorganisms were slightly influenced by AgNPs and glyphosate single treatment at the test concentration. However, AgNPs and glyphosate (Gly) combined treatment (AgNPs + Gly) strongly inhibited wheat growth and influenced gene transcription. In total, 955, 601, and 1336 genes were determined to be differentially expressed in AgNPs, glyphosate, and combined treatment, respectively. According to KEGG analysis, the combined groups induced an antioxidant response by upregulating the transcription of phenylpropanoid biosynthesis-related genes. In addition, more energy was needed, and disrupted cell membrane was shown in the combined treatment, which displayed in the upregulation of sucrose, starch, and lipid synthesis. Moreover, the relative abundance of Bradyrhizobium, Devosia, Kribbella, Sphingopyxis (nitrogen-fixing bacteria), and Streptomyces (plant growth-promoting bacteria) in soil microbiota were decreased, implicated that nitrogen fixation and some beneficial substance secretions were inhibited by the combined treatment. This study emphasized that the synergetic effects of AgNPs and glyphosate exerted a negative impact on wheat growth.

Phyllosphere bacterial assemblage is affected by plant genotypes and growth stages.

The interaction between plants and microorganisms directly affects plant health and sustainable agricultural development. Leaves represent a wide-area habitat populated by a variety of microorganisms, whose impact on host environmental adaptability could influence plant growth and function. The driving factors for phyllosphere microbiota assemblage are the focus of current research. Here, we investigated the effect of growth stage (i.e., bolting, flowering, and maturation) and genotype of Arabidopsis thaliana (wild-type and the two photosynthetic mutants ndf4 and pgr5) on the composition of phyllosphere microbiota. Our results show that species abundance varied significantly between the three genotypes at different growth stages, whereas species richness and evenness varied only for ndf4. The leaf surface shared a core microbiota dominated by Proteobacteria, Actinobacteria, Bacteroidetes, and Firmicutes in all tested growth stages and genotypes. Phyllosphere specificity varied more with respect to growth stage than to genotype. In summary, both the growth stage and genotype of A. thaliana are crucial in shaping phyllosphere bacterial composition, with the former being a stronger driver. Our findings provide a novel for investigating whether the host properties influence the phyllosphere community and favor healthy development of plants.

Effect of electroacupuncture on postoperative cognitive dysfunction for patients undergoing total knee arthroplasty: A protocol for systematic review and meta-analysis of randomized controlled trials.

BACKGROUND: Electroacupuncture is increasingly used in rehabilitation for postoperative cognitive dysfunction (POCD), but relevant evidence remains unclear for patients receiving total knee arthroplasty (TKA). METHODS: The databases research of PubMed, EMBASE, CINAHL, and China National Knowledge Infrastructure (CNKI) will be conducted from inception to December 31, 2020. The relevant randomized controlled trials (RCTs) from data will be screened one by one. The remaining studies that meet the inclusion criteria will be extracted and analyzed using RevMan V.5.3 software. Paired 2 reviewers will assess quality of the included studies and publication bias by using the Cochrane Collaboration risk of bias tool, and Egger test and Begg test respectively. And grading of recommendations assessment, development and evaluation (GRADE) will be used to estimate the quality of evidence. RESULTS: In this study, we will analyze the effect of electroacupuncture on Mini-Mental State Examination (MMSE), interleukin 1ß (IL-1ß), tumor necrosis factor-α (TNF-α), S100-ß protein, and adverse events for patients with TKA. CONCLUSION: Our findings will provide evidence for the effectiveness of electroacupuncture on the treatment and prevention of POCD for TKA patients. REGISTRATION NUMBER: Available at: https://osf.io/azyt9 (DOI number: 10.17605/OSF.IO/AZYT9).

Synergistic effects of glyphosate and multiwall carbon nanotubes on Arabidopsis thaliana physiology and metabolism.

Agricultural chemicals have the potential to become pollutants that adversely affect plant growth. Interactions between these compounds are likely, but potential synergies are under-researched. Multiwall carbon nanotubes are increasingly finding novel uses in agriculture, as delivery mechanisms and as slow-release fertilizers. There is potential for nanotubes to interact with other agricultural chemicals in unpredictable ways. To investigate this possibility, we examined interactions with glyphosate, a widely used herbicide that is also attracting increasing concern over its potential for non-target effects. Here we examined potential synergistic effects on hydroponically grown Arabidopsis thaliana. Single treatments did not affect plant growth significantly, or did only mildly. However, combined treatment significantly affected both plant root and shoot growth. High-level content of malondialdehyde and up-regulated of metabolic antioxidant molecules in plant indicated that combined group caused the strong oxidative damage, while the decreased of antioxidant enzyme activities indicated an imbalance between reactive oxygen species (ROS)and the antioxidant defense system due to the continuously generated ROS. Besides, several intermediate metabolites of unsaturated fatty acids synthesis pathways were up-regulated in combined treatment, which clarified that combined group changed membrane components. The increase of intermediate metabolites in combined group also reflected more energy consumption in the repairment of the disrupt of combined treatment. The synergistic effect observed was attributed to the accumulation of glyphosate resulting from permeability and transportability of the carbon nanotubes. Overall, the risk of nanotube-herbicide interaction suggests a caution use of nanotubes in agricultural applications.

Metabolomic modulations in a freshwater microbial community exposed to the fungicide azoxystrobin.

An effective broad-spectrum fungicide, azoxystrobin (AZ), has been widely detected in aquatic ecosystems, potentially affecting the growth of aquatic microorganisms. In the present study, the eukaryotic alga Monoraphidium sp. and the cyanobacterium Pseudanabaena sp. were exposed to AZ for 7 days. Our results showed that 0.2-0.5 mg/L concentrations of AZ slightly inhibited the growth of Monoraphidium sp. but stimulated Pseudanabaena sp. growth. Meanwhile, AZ treatment effectively increased the secretion of total organic carbon (TOC) in the culture media of the two species, and this phenomenon was also found in a freshwater microcosm experiment (containing the natural microbial community). We attempted to assess the effect of AZ on the function of aquatic microbial communities through metabolomic analysis and further explore the potential risks of this compound. The metabonomic profiles of the microcosm indicated that the most varied metabolites after AZ treatment were related to the citrate cycle (TCA), fatty acid biosynthesis and purine metabolism. We thereby inferred that the microbial community increased extracellular secretions by adjusting metabolic pathways, which might be a stress response to reduce AZ toxicity. Our results provide an important theoretical basis for further study of fungicide stress responses in aquatic microcosm microbial communities, as well as a good start for further explorations of AZ detoxification mechanisms, which will be valuable for the evaluation of AZ environmental risk.

Enantioselective effects of imazethapyr residues on Arabidopsis thaliana metabolic profile and phyllosphere microbial communities.

Imazethapyr (IM) is a widely used acetolactate synthase-inhibiting chiral herbicide. It has long-term residuals that may be absorbed by the human body through the edible parts of plants, such as vegetable leaves or fruits. Here, we selected a model plant, Arabidopsis thaliana, to determine the effects of R-IM and S-IM on its leaf structure, photosynthetic efficiency, and metabolites, as well as the structures of microorganisms in the phyllosphere, after 7 days of exposure. Our results indicated enantiomeric differences in plant growth between R-IM and S-IM; 133 µg/kg R-IM showed heavier inhibition of photosynthetic efficiency and greater changes to subcellular structure than S-IM. R-IM and S-IM also had different effects on metabolism and leaf microorganisms. S-IM mainly increased lipid compounds and decreased amino acids, while R-IM increased sugar accumulation. The relative abundance of Moraxellaceae human pathogenic bacteria was increased by R-IM treatment, indicating that R-IM treatment may increase leaf surface pathogenic bacteria. Our research provides a new perspective for evaluating the harmfulness of pesticide residues in soil, phyllosphere microbiome changes via the regulation of plant metabolism, and induced pathogenic bacterial accumulation risks.

Offspring toxicity of silver nanoparticles to Arabidopsis thaliana flowering and floral development.

Many studies have considered silver nanoparticles (AgNPs) cytotoxicity to mammalian and human cell lines and plant growth. However, only few studies considered toxic effects of AgNPs on plant offspring, especially on flowering. Arabidopsis thaliana was treated with 12.5 mg/kg AgNPs employing parental-(P-AgNPs) and offspring-generation (O-AgNPs) exposure to study the effects of AgNPs on flowering and floral development. Exposure to P-AgNPs was found to significantly decrease petal and pollen viability and subsequently reduced pod production. The inhibition of A. thaliana vegetative growth caused by P-AgNPs exposure was transferred to offspring and even became more severe in the O-AgNPs group. Further, the transcription of genes related to flowering and floral organ development in P-AgNPs and O-Con plants was downregulated by approximately 10-40% compared to the transcription in P-Con plants and showed a stronger decrease in the O-AgNPs group to 30-50% of that in the P-AgNPs group. This resulted in a delay in flowering of 4, 3 and 8 days in P-AgNPs, O-Con and O-AgNPs plants, respectively. Our research shows that the negative effects on floral development can be transferred to the offspring in A. thaliana, which may have significant implications with regard to the risks posed by NPs to food safety and security.