Structural insights into RNA cleavage by a novel family of bacterial RNases.

Processing of RNA is a key regulatory mechanism for all living systems. Escherichia coli protein YicC belongs to the well-conserved YicC family and has been identified as a novel ribonuclease. Here, we report a 2.8-Å-resolution crystal structure of the E. coli YicC apo protein and a 3.2-Å-cryo-EM structure of YicC bound to an RNA substrate. The apo YicC forms a dimer of trimers with a large open channel. In the RNA-bound form, the top trimer of YicC rotates nearly 70° and closes the RNA substrate inside the cavity to form a clamshell-pearl conformation that resembles no other known RNases. The structural information combined with mass spectrometry and biochemical data identified cleavage on the upstream side of an RNA hairpin. Mutagenesis studies demonstrated that the previously uncharacterized domain, DUF1732, is critical in both RNA binding and catalysis. These studies shed light on the mechanism of the previously unexplored YicC RNase family.

Mechanistic Insights into Micelle-Enhanced Nanofiltration for Heavy Metal Removal: Transformation of Ion Transport and Fouling Phenomena.

Toxic heavy metals are widely present in typical scenarios, such as mines and electroplating wastewater, presenting significant risks to biological and environmental safety. Membrane processes encounter a challenge in effectively intercepting heavy metals due to their small hydration radius. This research showcases the high efficiency of micelle-enhanced nanofiltration (MENF) in removing heavy metals. At the critical micelle concentration, sodium dodecyl sulfate demonstrated a high removal of Cu2+, Ni2+, Zn2+, and Cd2+ while maintaining substantial potential for complexation of heavy metals. The formation of micelles and the bonding of heavy metals with surfactants bolstered the resistance of heavy metal ions to transmembrane transport. The presence of heavy metals in ionic form in wastewater facilitated their complexation with surfactants or micelles. Notably, the valence state and concentration of interfering ions in the environment could slightly influence the removal of heavy metals by MENF. Additionally, MENF displayed remarkable antifouling properties. The loose gel layer created by surfactant molecules and the micelle enhanced the membrane permeability and reduced the scaling tendency of heavy metals. This study contributes to an improved understanding of the mechanisms involved in heavy metal rejection by using MENF.

Treatment of diabetic foot with moxibustion: Clinical evidence from meta-analysis.

To assess the efficacy of moxibustion for diabetic foot, and compile the findings of randomised clinical trials. China National Knowledge Infrastructure Database, Medicine, WanFang Database, Embase, Chinese Scientific Journal Database and Web of Science were from the establishment to January, 2024 were searched. Randomised controlled trials, which evaluated the effects of moxibustion were included. A total of 12 randomised controlled trials involving 1196 patients were included. According to the pooled results of this meta-analysis, effective rate (relative risk 1.16, 95% confidence intervals, CI [1.11, 1.22]), healing time (mean difference [MD] -6.27, 95% CI [-8.68, -3.86]), wound area (MD 3.46, 95% CI [0.84, 6.09]), and ankle brachial index (MD 0.14, 95% CI [0.03, 0.24]) were statistically significant compared to the control group. This study suggests that moxibustion treatment has the potential for improving symptoms of diabetic foot. However, future in-depth research on the benefits and harms of moxibustion for the diabetic foot is needed before it can be accepted as an evidence-based treatment.

Genome-Wide Characterization of DNase I-Hypersensitive Sites and Cold Response Regulatory Landscapes in Grasses.

Deep sequencing of DNase-I treated chromatin (DNase-seq) can be used to identify DNase I-hypersensitive sites (DHSs) and facilitates genome-scale mining of de novo cis-regulatory DNA elements. Here, we adapted DNase-seq to generate genome-wide maps of DHSs using control and cold-treated leaf, stem, and root tissues of three widely studied grass species: Brachypodium distachyon, foxtail millet (Setaria italica), and sorghum (Sorghum bicolor). Functional validation demonstrated that 12 of 15 DHSs drove reporter gene expression in transiently transgenic B. distachyon protoplasts. DHSs under both normal and cold treatment substantially differed among tissues and species. Intriguingly, the putative DHS-derived transcription factors (TFs) are largely colocated among tissues and species and include 17 ubiquitous motifs covering all grass taxa and all tissues examined in this study. This feature allowed us to reconstruct a regulatory network that responds to cold stress. Ethylene-responsive TFs SHINE3, ERF2, and ERF9 occurred frequently in cold feedback loops in the tissues examined, pointing to their possible roles in the regulatory network. Overall, we provide experimental annotation of 322,713 DHSs and 93 derived cold-response TF binding motifs in multiple grasses, which could serve as a valuable resource for elucidating the transcriptional networks that function in the cold-stress response and other physiological processes.

Prediction and Validation of Mouse Meiosis-Essential Genes Based on Spermatogenesis Proteome Dynamics.

The molecular mechanism associated with mammalian meiosis has yet to be fully explored, and one of the main reasons for this lack of exploration is that some meiosis-essential genes are still unknown. The profiling of gene expression during spermatogenesis has been performed in previous studies, yet few studies have aimed to find new functional genes. Since there is a huge gap between the number of genes that are able to be quantified and the number of genes that can be characterized by phenotype screening in one assay, an efficient method to rank quantified genes according to phenotypic relevance is of great importance. We proposed to rank genes by the probability of their function in mammalian meiosis based on global protein abundance using machine learning. Here, nine types of germ cells focusing on continual substages of meiosis prophase I were isolated, and the corresponding proteomes were quantified by high-resolution MS. By combining meiotic labels annotated from the mouse genomics informatics mouse knockout database and the spermatogenesis proteomics dataset, a supervised machine learning package, FuncProFinder (https://github.com/sjq111/FuncProFinder), was developed to rank meiosis-essential candidates. Of the candidates whose functions were unannotated, four of 10 genes with the top prediction scores, Zcwpw1, Tesmin, 1700102P08Rik, and Kctd19, were validated as meiosis-essential genes by knockout mouse models. Therefore, mammalian meiosis-essential genes could be efficiently predicted based on the protein abundance dataset, which provides a paradigm for other functional gene mining from a related abundance dataset.

Molecular basis for histone N-terminal methylation by NRMT1.

NRMT1 is an N-terminal methyltransferase that methylates histone CENP-A as well as nonhistone substrates. Here, we report the crystal structure of human NRMT1 bound to CENP-A peptide at 1.3 Å. NRMT1 adopts a core methyltransferase fold that resembles DOT1L and PRMT but not SET domain family histone methyltransferases. Key substrate recognition and catalytic residues were identified by mutagenesis studies. Histone peptide profiling revealed that human NRMT1 is highly selective to human CENP-A and fruit fly H2B, which share a common "Xaa-Pro-Lys/Arg" motif. These results, along with a 1.5 Å costructure of human NRMT1 bound to the fruit fly H2B peptide, underscore the importance of the NRMT1 recognition motif.

Facile synthesis of a novel BaSnO3/MXene nanocomposite by electrostatic self-assembly for efficient photodegradation of 4-nitrophenol.

Photocatalysis is regarded as one of the most effective strategies for the removal of the toxic organic pollutants from aqueous solutions. However, a lack of the efficient photocatalysts prevents the widespread practical application. Herein, the electrostatic self-assembly method has been designed for facile synthesis of a novel BaSnO3/PDDA/MXene (BSO/P/MX) nanocomposite as high efficient photocatalyst. In this nanocomposite, the BaSnO3 (BSO), poly (dimethyl-diallylammonium chloride) (PDDA) and MXene (Ti3C2Tx) act as the active species, structure stabilizer and efficient electron transfer medium, respectively. Due to the strong synergy of the nanocomposite, the electron-transferring ability as well as the charge separation efficiency is boosted and thus high catalytic activity achieves towards the photodegradation of 4-nitrophenol. The superior degradation rate of 98.8% and a rate constant K of 0.09113 min-1 have been realized within 75 min of ultraviolet (UV) light irradiation over the BSO/P/MX-8% catalyst. This as-prepared nanocomposite with the excellent catalytic activity can be employed as a promising photocatalyst for treating the organic pollutants from aqueous solutions.

Prevalence of infectious keratitis in Central China.

BACKGROUND: The baseline data pertaining to the national epidemiological survey of infectious keratitis remain scarce in China, and currently there is no corneal blindness control strategy developed by the nation. METHODS: Geographically defined cluster sampling was used to randomly select a cross-section of residents from representative urban and rural populations in Hubei Province. Participants were selected from village registers, followed by door-to-door household visits. The assessment items included a structured interview, visual acuity testing, external eye examination, and anterior segment examination using slit lamp. Causes and sequelae of corneal disease were identified according to uniform customized protocol. RESULTS: The prevalence of presenting corneal diseases was 0.8% (211/26 305), while the prevalence of infectious keratitis was 0.148% (39/26 305). The prevalences of viral, bacterial, and fungal keratitis were 0.065, 0.068, and 0.015%, respectively. There were no significant differences found between the prevalences of viral (accounting for 43.6%) and bacterial (accounting for 46.2%) corneal ulcers. cases of Acanthamoeba keratitis were not found. Infectious keratitis was the leading cause of corneal blindness (85.7%), and the prevalence of blindness in at least one eye resulting from infected corneas was 0.091% (95% CI: 0.067-0.127%). CONCLUSIONS: Viral and bacterial mechanisms constitute the most important risk factors for infectious corneal ulcers in Central China. To reduce the rate and severity of infectious keratitis, he public health care policy should be focused on designing cost-effective strategies and operational programs for the prevention and prompt treatment of infectious corneal ulcers.

Glutathione-gated potassium efflux as a mechanism of active biofilm detachment.

Biofilm detachment often has detrimental effects such as pipe obstruction and infection, yet the detachment mechanisms underlying dispersal remain largely unknown. In this study, a stress response mechanism known as glutathione-gated potassium efflux (GGKE) was evaluated as an active detachment mechanism in the dispersal of Pseudomonas aeruginosa biofilms. N-ethylmaleimide (NEM) was used to activate potassium efflux proteins (Kef) associated with the GGKE pathway. This stress response mechanism was hypothesized to lead to altered cation concentration, which can potentially affect polymer bridging in biofilms, and ultimately cause biofilm detachment. Results showed the activation of GGKE by NEM exposure caused biofilm detachment without inducing a measurable change in viability, and detached biomass concentration and composition were dependent on NEM concentration. More detached biomass was observed with higher concentrations of NEM, with a trend of increasing polymer detachment. The detachment was likely resulting from a weakened biofilm structural integrity induced by bridge denaturing from GGKE activation. This study is important in understanding biofilm detachment from engineered systems such as membrane aerated bioreactors.

Dielectric Barrier Discharge (DBD) enhanced Fenton process for landfill leachate nanofiltration: Organic matter removal and membrane fouling alleviation.

This study investigated a sustainable approach through dielectric barrier discharge (DBD) enhanced Fenton technology coupling nanofiltration (NF) process for landfill leachate treatment. The DBD/Fe(II)/H2O2 system exhibited significant synergistic effects, removing 55.07 % of TOC and 53.79 % of UV254 within 60 min, respectively. Additionally, the DBD/Fe(II)/H2O2 system demonstrated exceptional performance in removing fluorescent substances and large molecular organic compounds, thereby reducing the formation of cake layer on the nanofiltration membrane. Moreover, membrane flux increased by 2.34 times, with reversible and irreversible resistances decreasing by 75.79 % and 81.55 %, respectively. Quenching experiments revealed ·OH as the primary active species for perfluorooctanoic acid (PFOA) degradation in the DBD/Fe(II)/H2O2 process. The degradation pathway of PFOA was also elucidated via capillary electrophoresis-quadrupole time-of-flight mass spectrometry analysis. Correlation analysis indicated that TOC and EEM were the primary fouling factors. Lastly, through an assessment of energy consumption, economic costs, and carbon dioxide emissions, the advantages and practical application potential of the DBD/Fe(II)/H2O2 system were demonstrated. In summary, the DBD/Fe(II)/H2O2 system emerges as a feasible strategy for NF pretreatment, holding immense potential for treating landfill leachate.

Morphology Control of Zr-Based Luminescent Metal-Organic Frameworks for Aflatoxin B1 Detection.

Metal-organic frameworks (MOFs) have gained significant prominence as sensing materials owing to their unique properties. However, understanding the correlation between the morphology, properties, and sensing performance in these MOF-based sensors remains a challenge, limiting their applications and potential for improvement. In this study, Zr-MOF was chosen as an ideal model to explore the impact of the MOF morphology on the sensing performance, given its remarkable stability and structural variability. Three luminescent MOFs (namely rod-like Zr-LMOF, prismoid-like Zr-LMOF, and ellipsoid-like Zr-LMOF) were synthesized by adjusting the quantities of the benzoic acid and the reaction time. More importantly, the sensing performance of these Zr-LMOFs in response to aflatoxin B1 (AFB1) was thoroughly examined. Notably, the ellipsoid-like Zr-LMOF exhibited significantly higher sensitivity compared to other Zr-LMOFs, attributed to its large specific surface area and pore volume. Additionally, an in-depth investigation into the detection mechanism of AFB1 by Zr-LMOFs was conducted. Building upon these insights, a ratiometric fluorescence sensor was developed by coordinating Eu3+ with ellipsoid-like Zr-LMOF, achieving a remarkably lower detection limit of 2.82 nM for AFB1. This study contributes to an improved comprehension of the relationship between the MOF morphology and the sensing characteristics while presenting an effective approach for AFB1 detection.

Contrast-Enhanced Mammography Radiomics Analysis for Preoperative Prediction of Breast Cancer Molecular Subtypes.

BACKGROUND: Predicting breast cancer molecular subtypes can help guide individualised clinical treatment of patients who need the rational preoperative treatment. This study aimed to investigate the efficacy of preoperative prediction of breast cancer molecular subtypes by contrast-enhanced mammography (CEM) radiomic features. METHODS: This retrospective two-centre study included women with breast cancer who underwent CEM preoperatively between August 2016 and May 2022. We included 356 patients with 386 lesions, which were grouped into training (n = 162), internal test (n = 160) and external test sets (n = 64). Radiomics features were extracted from low-energy (LE) images and recombined (RC) images and selected. Three dichotomous tasks were established according to postoperative immunohistochemical results: Luminal vs. non-Luminal, human epidermal growth factor receptor (HER2)-enriched vs. non-HER2-enriched, and triple-negative breast cancer (TNBC) vs. non-TNBC. For each dichotomous task, the LE, RC, and LE+RC radiomics models were built by the support vector machine classifier. The prediction performance of the models was assessed by the area under the receiver operating characteristic curve (AUC). Then, the accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were calculated for the models. DeLong's test was utilised to compare the AUCs. RESULTS: Radiomics models based on CEM are valuable for predicting breast cancer molecular subtypes. The LE+RC model achieved the best performance in the test set. The LE+RC model predicted Luminal, HER2-enriched, and TNBC subtypes with AUCs of 0.93, 0.89, and 0.87 in the internal test set and 0.82, 0.83, and 0.69 in the external test set, respectively. In addition, the LE model performed more satisfactorily than the RC model. CONCLUSION: CEM radiomics features can effectively predict breast cancer molecular subtypes preoperatively, and the LE+RC model has the best predictive performance.

A dual-signal aptasensor based on cascade amplification for ultrasensitive detection of aflatoxin B1.

Aflatoxin B1 (AFB1) is considered as a serious carcinogenic mycotoxin that was widely detected in grains and foods, and its sensitive analysis is of key importance to avoid the health threats for consumers. In this study, a dual-signal aptasensor based on cascade of entropy-driven strand displacement reaction (ESDR) and linear rolling circle amplification (LRCA) was fabricated for ultrasensitive determination of AFB1. At the sensing system, the complementary strand would be released after the aptamer combined with AFB1, which will bring about the functional domains exposed, triggering the subsequent ESDR. Meanwhile, the two strands that were outputted by ESDR would incur the downstream LRCA reaction to produce a pair of long strands to assist in the generation of fluorescence and absorbance signals. Under the optimized conditions, the proposed aptasensor could achieve excellent sensitivity (limit of detection, 0.427 pg/mL) with satisfactory accuracy (recoveries, 92.8-107.9 %; RSD, 2.4-5.0 %), mainly ascribed to the cascade amplification. Importantly, owing to the flexibility design of nucleic acid primer, this analytical method can be applied in monitoring various hazardous substances according to the specific requirements. Our strategy provides some novel insights at signal amplification for rapid detection of AFB1 and other targets.

Characterization, Structure, and Inhibition of the Human Succinyl-CoA:glutarate-CoA Transferase, a Putative Genetic Modifier of Glutaric Aciduria Type 1.

Glutaric Aciduria Type 1 (GA1) is a serious inborn error of metabolism with no pharmacological treatments. A novel strategy to treat this disease is to divert the toxic biochemical intermediates to less toxic or nontoxic metabolites. Here, we report a putative novel target, succinyl-CoA:glutarate-CoA transferase (SUGCT), which we hypothesize suppresses the GA1 metabolic phenotype through decreasing glutaryl-CoA and the derived 3-hydroxyglutaric acid. SUGCT is a type III CoA transferase that uses succinyl-CoA and glutaric acid as substrates. We report the structure of SUGCT, develop enzyme- and cell-based assays, and identify valsartan and losartan carboxylic acid as inhibitors of the enzyme in a high-throughput screen of FDA-approved compounds. The cocrystal structure of SUGCT with losartan carboxylic acid revealed a novel pocket in the active site and further validated the high-throughput screening approach. These results may form the basis for the future development of new pharmacological intervention to treat GA1.

Characterization, structure and inhibition of the human succinyl-CoA:glutarate-CoA transferase, a genetic modifier of glutaric aciduria type 1.

Glutaric Aciduria Type 1 (GA1) is a serious inborn error of metabolism with no pharmacological treatments. A novel strategy to treat this disease is to divert the toxic biochemical intermediates to less toxic or non-toxic metabolites. Here, we report a novel target, SUGCT, which we hypothesize suppresses the GA1 metabolic phenotype through decreasing glutaryl-CoA. We report the structure of SUGCT, the first eukaryotic structure of a type III CoA transferase, develop a high-throughput enzyme assay and a cell-based assay, and identify valsartan and losartan carboxylic acid as inhibitors of the enzyme validating the screening approach. These results may form the basis for future development of new pharmacological intervention to treat GA1.

ALKBH5-mediated m6A modification of IL-11 drives macrophage-to-myofibroblast transition and pathological cardiac fibrosis in mice.

Cardiac macrophage contributes to the development of cardiac fibrosis, but factors that regulate cardiac macrophages transition and activation during this process remains elusive. Here we show, by single-cell transcriptomics, lineage tracing and parabiosis, that cardiac macrophages from circulating monocytes preferentially commit to macrophage-to-myofibroblast transition (MMT) under angiotensin II (Ang II)-induced hypertension, with accompanying increased expression of the RNA N6-methyladenosine demethylases, ALKBH5. Meanwhile, macrophage-specific knockout of ALKBH5 inhibits Ang II-induced MMT, and subsequently ameliorates cardiac fibrosis and dysfunction. Mechanistically, RNA immunoprecipitation sequencing identifies interlukin-11 (IL-11) mRNA as a target for ALKBH5-mediated m6A demethylation, leading to increased IL-11 mRNA stability and protein levels. By contrast, overexpression of IL11 in circulating macrophages reverses the phenotype in ALKBH5-deficient mice and macrophage. Lastly, targeted delivery of ALKBH5 or IL-11 receptor α (IL11RA1) siRNA to monocytes/macrophages attenuates MMT and cardiac fibrosis under hypertensive stress. Our results thus suggest that the ALKBH5/IL-11/IL11RA1/MMT axis alters cardiac macrophage and contributes to hypertensive cardiac fibrosis and dysfunction in mice, and thereby identify potential targets for cardiac fibrosis therapy in patients.

Facile synthesis of Ag/ZIF-8@ZIF-67 as an electrochemical sensing platform for sensitive detection of halonitrophenols in drinking water.

Halonitrophenols (HNPs) are an emerging type of aromatic disinfection byproduct, with detected concentrations of ∼nmol L-1 in source water and drinking water. Currently, there are no standard methods for identifying HNPs, and most of the reported methods are time-consuming and equipment-dependent. A core-shell metal-organic framework (MOF) based electrochemical sensor (Ag/ZIF-8@ZIF-67) capable of detecting 2,6-dichloro-4-nitrophenol (2,6-DCNP) is reported in this study. The electrochemical sensor obtains the concentration of 2,6-DCNP by detecting the peak current passing through the sensor. In this sensor, Ag nanoparticles (AgNPs) play a key role in electrochemical sensing by reducing nitro groups via electron transfer, and porous structure with a large surface area is offered by ZIF-8@ZIF-67. The cyclic voltammetry (CV) response of Ag/ZIF-8@ZIF-67 was found to be approximately 1.75 times and 2.23 times greater than that of Ag/ZIF-8 and Ag/ZIF-67, respectively, suggesting an ideal synergistic effect of the core-shell structures. The Ag/ZIF-8@ZIF-67 sensor exhibited exceptional sensitivity to 2,6-DCNP, exhibiting a broad linear response range (R2 = 0.992) from 240 nmol L-1 to 288 µmol L-1 and a low detection limit of 20 nmol L-1. Furthermore, the sensor exhibited good anti-interference for isomers and common distractors in water, excellent stability and reproducibility, and high recovery in actual water samples. Our reported sensor gives a novel strategy for sensitive, selective, and in situ detection of 2,6-DCNP in practical analysis.

Profiling regulatory T lymphocytes within the tumor microenvironment of breast cancer via radiomics.

OBJECTIVE: To generate an image-driven biomarker (Rad_score) to predict tumor-infiltrating regulatory T lymphocytes (Treg) in breast cancer (BC). METHODS: Overall, 928 BC patients were enrolled from the Cancer Genome Atlas (TCGA) for survival analysis; MRI (n = 71 and n = 30 in the training and validation sets, respectively) from the Cancer Imaging Archive (TCIA) were retrieved and subjected to repeat least absolute shrinkage and selection operator for feature reduction. The radiomic scores (rad_score) for Treg infiltration estimation were calculated via support vector machine (SVM) and logistic regression (LR) algorithms, and validated on the remaining patients. RESULTS: Landmark analysis indicated Treg infiltration was a risk factor for BC patients in the first 5 years and after 10 years of diagnosis (p = 0.007 and 0.018, respectively). Altogether, 108 radiomic features were extracted from MRI images, 4 of which remained for model construction. Areas under curves (AUCs) of the SVM model were 0.744 (95% CI 0.622-0.867) and 0.733 (95% CI 0.535-0.931) for training and validation sets, respectively, while for the LR model, AUCs were 0.771 (95% CI 0.657-0.885) and 0.724 (95% CI 0.522-0.926). The calibration curves indicated good agreement between prediction and true value (p > 0.05), and DCA shows the high clinical utility of the radiomic model. Rad_score was significantly correlated with immune inhibitory genes like CTLA4 and PDCD1. CONCLUSIONS: High Treg infiltration is a risk factor for patients with BC. The Rad_score formulated on radiomic features is a novel tool to predict Treg abundance in the tumor microenvironment.

Pre-oxidation coupled with charged covalent organic framework membranes for highly efficient removal of organic chloramines precursors in algae-containing water treatment.

Organic chloramines in water would pose both chemical and microbiological risks. It is essential to remove the precursors of organic chloramine (amino acids and decomposed peptides/proteins) to limit its formation in disinfection. In our work, nanofiltration was chosen to remove organic chloramines precursors. To solve the "trade-off" effect and low rejection of small molecules in algae organic matter, we synthesized a thin film composite (TFC) nanofiltration (NF) membrane with a crumpled polyamide (PA) layer via interfacial polymerization on polyacrylonitrile (PAN) composite support loaded with covalent organic framework (COF) nanoparticles (TpPa-SO3H). The obtained NF membrane (PA-TpPa-SO3H/PAN) increased the permeance from 10.2 to 28.2 L m-2 h-1 bar-1 and the amino acid rejection from 24% to 69% compared to the control NF membrane. The addition of TpPa-SO3H nanoparticles decreased the thickness of PA layers, increased the hydrophilicity of the membrane, and increased the transition energy barrier for amino acids transferring through the membrane, which was identified by scanning electron microscope, contact angle test, and density functional theory computations, respectively. Finally, pre-oxidation coupled with PA-TpPa-SO3H/PAN membrane nanofiltration on the limitation of organic chloramines formation was evaluated. We found that the combined application of KMnO4 pre-oxidation and PA-TpPa-SO3H/PAN membranes nanofiltration in algae-containing water treatment could minimize the formation of organic chloramines in subsequent chlorination and maintain a high flux during filtration. Our work provides an effective way for algae-containing water treatment and organic chloramines control.

Identification of multi-component metal ion mixtures in complex systems using fluorescence sensor arrays.

The growing co-contamination of multiple metal ions seriously influences human health due to their synergistic and additive toxicological effects, whereas the rapid discrimination of multiple heavy metal ions in complex aquatic systems remains a major challenge. Herein, a high- throughput fluorescence sensor array was fabricated based on three gold nanoclusters (GSH-Au NCs, OVA-Au NCs, and BSA-Au NCs) for the direct identification and quantification of seven heavy metal ions (Pb2+, Fe3+, Cu2+, Co2+, Ag+, Hg2+ and As3+) from environmental waters without sample pretreatment other than filtration. At the detection system, three gold nanoclusters with various ligands possessed distinct binding capacities against metal ions and induced aggregation-induced fluorescence enhancement and quenching, resulting in a unique pattern of fluorescence variations. Meanwhile, integrated the collected fluorescence fingerprints with linear discriminant analysis (LDA) and hierarchical cluster analysis (HCA), a discrete database was obtained for the accurate recognition and sensitive detection of metal ions. Under the optimized conditions, the limit of detection (LOD) of the proposed fluorescence sensor array for metal ions detection at nM concentration level along with a satisfactory accuracy. Importantly, our study indicated that the fluorescence sensor array could be widely used as a general platform in environmental monitoring against multiple targets at low concentrations.