RESUMO
Advances in spatial omics technologies now allow multiple types of data to be acquired from the same tissue slice. To realize the full potential of such data, we need spatially informed methods for data integration. Here, we introduce SpatialGlue, a graph neural network model with a dual-attention mechanism that deciphers spatial domains by intra-omics integration of spatial location and omics measurement followed by cross-omics integration. We demonstrated SpatialGlue on data acquired from different tissue types using different technologies, including spatial epigenome-transcriptome and transcriptome-proteome modalities. Compared to other methods, SpatialGlue captured more anatomical details and more accurately resolved spatial domains such as the cortex layers of the brain. Our method also identified cell types like spleen macrophage subsets located at three different zones that were not available in the original data annotations. SpatialGlue scales well with data size and can be used to integrate three modalities. Our spatial multi-omics analysis tool combines the information from complementary omics modalities to obtain a holistic view of cellular and tissue properties.
RESUMO
Spatial transcriptomics technologies generate gene expression profiles with spatial context, requiring spatially informed analysis tools for three key tasks, spatial clustering, multisample integration, and cell-type deconvolution. We present GraphST, a graph self-supervised contrastive learning method that fully exploits spatial transcriptomics data to outperform existing methods. It combines graph neural networks with self-supervised contrastive learning to learn informative and discriminative spot representations by minimizing the embedding distance between spatially adjacent spots and vice versa. We demonstrated GraphST on multiple tissue types and technology platforms. GraphST achieved 10% higher clustering accuracy and better delineated fine-grained tissue structures in brain and embryo tissues. GraphST is also the only method that can jointly analyze multiple tissue slices in vertical or horizontal integration while correcting batch effects. Lastly, GraphST demonstrated superior cell-type deconvolution to capture spatial niches like lymph node germinal centers and exhausted tumor infiltrating T cells in breast tumor tissue.
Assuntos
Perfilação da Expressão Gênica , Transcriptoma , Encéfalo , Análise por Conglomerados , Centro GerminativoRESUMO
Natural siderite (FeCO3), simulated synthetic siderite and nZVI/FeCO3 composite were used as green and easily available iron-based catalysts in peroxydisulfate activation for remediating 2-chlorophenol as the target contaminant and this technique can effectively degrade organic pollutants in the soil. The key reaction parameters such as catalysts dosage, oxidant concentration and pH, were investigated to evaluate the catalytic performance of different materials in catalytic systems. The buffering property of natural soil conduced satisfactory degradation performance in a wide pH range (3-10). Both the main non-radical of 1O2 and free radicals of SO4·- and OH· were evidenced by quenching experiment and electron paramagnetic resonance. The reduction of nZVI on FFC surface not only has the advantage for electronic transfer to promote the circulation of Fe(III) to Fe(II), but also can directly dechlorinate. Furthermore, the intermediates were comprehensively analyzed by GC-MS and a potential removal mechanism of three oxidant system for 2-CP soil degradation was obtained. Briefly, this research provides a new perspective for organic contaminate soil treatment using natural siderite or simulated synthetic siderite as efficient and environmental catalytic material.
Assuntos
Compostos Férricos , Poluentes Químicos da Água , Compostos Férricos/química , Solo , Carbonatos/química , Oxirredução , Oxidantes , Poluentes Químicos da Água/análiseRESUMO
A novel synergistic oxidation technology based on modified nanoscale zero-valent iron (nZVI) and potassium permanganate (KMnO4) was developed for polycyclic aromatic hydrocarbons (PAHs) remediation in actual contaminated soil. In this study, three surfactants were used as dispersants to modify nZVI, including poly acrylic (PAA), sorbitan monolaurate (SPAN-20) and sugar esters (SE). The following parameters were studied to optimize the coupling oxidation process: dispersants/nZVI ratio, dosage of oxidant based on soil oxidation demand (SOD), amount of modified nanomaterials added in the coupling system. By using zeta potential, XRD, SEM, BET characterization methods, the results show that nZVI successfully coated with 5% PAA, 20% SE and 10% SPAN-20 have the best stability and mobility to effectively reduce the agglomeration effect. The conditions for treating PAH contaminated soil with the three best modified nanocomposites combined with KMnO4 were studied. The optimal conditions were defined as [SE-nZVI] = 10% and [KMnO4] = 40% SODmax for 24 h at 25 °C. The synergistic oxidation process under these optimal conditions and the two unoptimized processes of KMnO4 and nZVI-KMnO4 degraded 85%, 58.9% and 62% of PAHs, respectively. This showed that the treatment effect of the optimized oxidation process was improved by 1.3-1.5 times. Further, by using gas chromatography-mass spectrometry (GC-MS), adsorption and electrophilic substitution reaction were speculated as the oxidation mechanism of PAHs treated by the coupling system of SE-nZVI-KMnO4. PAHs could finally be decomposed into 9-methylene-9H-fluorene, fluoranthene and 1,5-diphenyl-1,4-pentadiyn-3-one and reached a safer status in the soil.
RESUMO
Lead (Pb) pollution in soil has become one of the most serious environmental problems, and it is more urgent in areas where acid rain is prevalent. Curing agents to solidify heavy metals in soil are efficiently applied to remediate Pb-contaminated soil. In this study, we prepared biochar, biochar loaded with nano-zero-valent iron (BC-nZVI), and biochar loaded with nano-ferroferric oxide (BC-nFe3O4), and investigated the Pb-immobilizing efficiency in contaminated soil in the condition of acid rain by them. The results showed that 8 g/kg is the best added dosage of curing agents for immobilizing Pb, which of the immobilizing efficiency of Pb were 19% (biochar), 42% (BC-nZVI), and 23% (BC-nFe3O4), respectively. Besides, the curing agents had positive effects on immobilizing Pb under acid rain condition, which could significantly reduce the content of acid extractable Pb, especially BC-nZVI (1.5%). And the immobilization efficiency of modified biochar was better than biochar, especially BC-nZVI (66%). BC-nZVI showed a more ideal effect on decreasing the leaching amount of Pb in the condition of acid rain. The results highlighted that biochar-loaded nano-iron-based materials, especially BC-nZVI, was promising and environmentally friendly materials for remediating Pb-contaminated soils, which provided scientific reference and theoretical basis for the treatment of Pb-contaminated soils around industrial sites particularly in acid rain area.
Assuntos
Recuperação e Remediação Ambiental , Poluentes do Solo/análise , Carvão Vegetal , Chumbo , SoloRESUMO
Itaconic acid, one of the most promising and flexible bio-based chemicals, is mainly produced by Aspergillus terreus. Previous studies to improve itaconic acid production in A. terreus through metabolic engineering were mainly focused on its biosynthesis pathway, while the itaconic acid-degrading pathway has largely been ignored. In this study, we used transcriptomic, proteomic, bioinformatic, and in vitro enzymatic analyses to identify three key enzymes, itaconyl-CoA transferase (IctA), itaconyl-CoA hydratase (IchA), and citramalyl-CoA lyase (CclA), that are involved in the catabolic pathway of itaconic acid in A. terreus. In the itaconic acid catabolic pathway in A. terreus, itaconic acid is first converted by IctA into itaconyl-CoA with succinyl-CoA as the CoA donor, and then itaconyl-CoA is hydrated into citramalyl-CoA by IchA. Finally, citramalyl-CoA is cleaved into acetyl-CoA and pyruvate by CclA. Moreover, IctA can also catalyze the reaction between citramalyl-CoA and succinate to generate succinyl-CoA and citramalate. These results, for the first time, identify the three key enzymes, IctA, IchA, and CclA, involved in the itaconic acid degrading pathway in itaconic acid producing A. terreus. The results will facilitate the improvement of itaconic acid production by metabolically engineering the catabolic pathway of itaconic acid in A. terreus.