Suspect, Nontarget Screening, and Toxicity Prediction of Per- and Polyfluoroalkyl Substances in the Landfill Leachate.

Landfills are the final stage of urban wastes containing perfluoroalkyl and polyfluoroalkyl substances (PFASs). PFASs in the landfill leachate may contaminate the surrounding groundwater. As major environmental pollutants, emerging PFASs have raised global concern. Besides the widely reported legacy PFASs, the distribution and potential toxic effects of numerous emerging PFASs remain unclear, and unknown PFASs still need discovery and characterization. This study proposed a comprehensive method for PFAS screening in leachate samples using suspect and nontarget analysis. A total of 48 PFASs from 10 classes were identified; nine novel PFASs including eight chloroperfluoropolyether carboxylates (Cl-PFPECAs) and bistriflimide (HNTf2) were reported for the first time in the leachate, where Cl-PFPECA-3,1 and Cl-PFPECA-2,2 were first reported in environmental media. Optimized molecular docking models were established for prioritizing the PFASs with potential activity against peroxisome proliferator-activated receptor α and estrogen receptor α. Our results indicated that several emerging PFASs of N-methyl perfluoroalkyl sulfonamido acetic acids (N-MeFASAAs), n:3 fluorotelomer carboxylic acid (n:3 FTCA), and n:2 fluorotelomer sulfonate (n:2 FTSA) have potential health risks that cannot be ignored.

Tissue culture and Agrobacterium-mediated genetic transformation of the oil crop sunflower.

Sunflower is one of the four major oil crops in the world. 'Zaoaidatou' (ZADT), the main variety of oil sunflower in the northwest of China, has a short growth cycle, high yield, and high resistance to abiotic stress. However, the ability to tolerate adervesity is limited. Therefore, in this study, we used the retention line of backbone parent ZADT as material to establish its tissue culture and genetic transformation system for new variety cultivating to enhance resistance and yields by molecular breeding. The combination of 0.05 mg/L IAA and 2 mg/L KT in MS was more suitable for direct induction of adventitious buds with cotyledon nodes and the addition of 0.9 mg/L IBA to MS was for adventitious rooting. On this basis, an efficient Agrobacterium tumefaciens-mediated genetic transformation system for ZADT was developed by the screening of kanamycin and optimization of transformation conditions. The rate of positive seedlings reached 8.0%, as determined by polymerase chain reaction (PCR), under the condition of 45 mg/L kanamycin, bacterial density of OD600 0.8, infection time of 30 min, and co-cultivation of three days. These efficient regeneration and genetic transformation platforms are very useful for accelerating the molecular breeding process on sunflower.

The miR169b/NFYA1 module from the halophyte Halostachys caspica endows salt and drought tolerance in Arabidopsis through multi-pathways.

Salt and drought are the major abiotic stress factors plaguing plant growth, development and crop yields. Certain abiotic-stress tolerant plants have developed special mechanisms for adapting to adverse environments in the long process of evolution. Elucidating the molecular mechanisms by which they can exert resistance to abiotic stresses is beneficial for breeding new cultivars to guide agricultural production. Halostachys caspica, a perennial halophyte belonging to Halostachys in Amaranthaceae, is extremely tolerant to harsh environments, which is commonly grown in the saline-alkali arid desert area of Northwest, China. However, the molecular mechanism of stress tolerance is unclear. Nuclear Factor Y-A (NFYA) is a transcription factor that regulates the expression of downstream genes in plant response to adverse environments. It has also been reported that some members of the NFYA family are the main targets of miR169 in plants. In this study, we mainly focused on exploring the functions and preliminary mechanism of the miR169b/NFYA1 module from H. caspica to abiotic stress. The main results showed that RLM-RACE technology validated that HcNFYA1 was targeted by HcmiR169b, qRT-PCR revealed that HcmiR169b was repressed and HcNFYA1 was induced in the H. caspica branches under various abiotic stress as well ABA treatment and Arabidopsis stable transformation platform with molecular methods was applied to elucidate that the HcmiR169b/HcNFYA1 module conferred the salt and drought tolerance to plants by enhancing ABA synthesis and ABA signal transduction pathways, maintaining ROS homeostasis and the stability of cell membrane. HcNFYA1 is expected to be a candidate gene to improve plant resistance to salt and drought stresses.

Profiling of pesticides and pesticide transformation products in Chinese herbal teas.

Herbal teas have potential health benefits, but they also contain a variety of pesticides and pesticide transformation products (PTPs) that might brings health risks. Our study maps the pesticides and PTPs in two herbal teas (chrysanthemum and Lusterleaf Holly) from two main producing areas in China. Almost all 122 samples contain pesticides, with concentration ranging from 0.0005 to 10.305 mg/kg. Nearly 40% carbendazim and imidacloprid in chrysanthemum teas and λ-cyhalothrin in Lusterleaf Holly have higher concentration levels than the values permitted in EC Regulation No. 396/2005. Distinct distributions of pesticides were found in different teas and production areas. Eight PTPs were identified along with their parents, and were confirmed using a biosynthetic strategy. Acute, chronic and cumulative health risk assessments of pesticides revealed acceptable results. Our study uncovers the profile of pesticides in herbal teas, and provides new insight into discovering the potential environmental pollution and food contaminants.

The Halophyte Halostachys caspica AP2/ERF Transcription Factor HcTOE3 Positively Regulates Freezing Tolerance in Arabidopsis.

The APETALA2 (AP2) and ethylene-responsive element-binding factor (ERF) gene family is one of the largest plant-specific transcription factor gene families, which plays a critical role in plant development and evolution, as well as response to various stresses. The TARGET OF EAT3 (TOE3) gene is derived from Halostachys caspica and belongs to the AP2 subfamily with two AP2 DNA-binding domains. Currently, AP2 family mainly plays crucial roles in plant growth and evolution, yet there are few reports about the role of AP2 in abiotic stress tolerance. Here, we report HcTOE3, a new cold-regulated transcription factor gene, which has an important contribution to freezing tolerance. The main results showed that the expression of HcTOE3 in the H. caspica assimilating branches was strongly induced by different abiotic stresses, including high salinity, drought, and extreme temperature (heat, chilling, and freezing), as well as abscisic acid and methyl viologen treatments. Overexpressing HcTOE3 gene (OE) induced transgenic Arabidopsis plant tolerance to freezing stress. Under freezing treatment, the OE lines showed lower content of malondialdehyde and electrolyte leakage and less accumulation of reactive oxygen species compared with the wild type. However, the survival rates, antioxidant enzyme activities, and contents of osmotic adjustment substance proline were enhanced in transgenic plants. Additionally, the OE lines increased freezing tolerance by up-regulating the transcription level of cold responsive genes (CBF1, CBF2, COR15, COR47, KIN1, and RD29A) and abscisic acid signal transduction pathway genes (ABI1, ABI2, ABI5, and RAB18). Our results suggested that HcTOE3 positively regulated freezing stress and has a great potential as a candidate gene to improve plant freezing tolerance.

Evaluation and application of machine learning-based retention time prediction for suspect screening of pesticides and pesticide transformation products in LC-HRMS.

Computational QSAR models have gradually been preferred for retention time prediction in data mining of emerging environmental contaminants using liquid chromatography coupled with mass spectrometry. Generally, the model performance relies on the components such as machine learning algorithms, chemical features, and example data. In this study, we evaluated the performances of four algorithms on three feature sets, using 321 and 77 pesticides as the training and validation sets, respectively. The results were varied with different combinations of algorithms on distinct feature sets. Two strategies including enhancing the complexity of chemical features and enlarging the size of the training set were proved to improve the results. XGBoost, Random Forest, and lightGBM algorithms exhibited the best results when built on a large-scale chemical descriptors, while the Keras algorithm preferred fingerprints. These four models have comparable prediction accuracies that at least 90% of pesticides in validation set can be successfully predicted with ΔRT <1.0 min. Meanwhile, a blended prediction strategy using average results from four models presented a better result than any single model. This strategy was used for assisting identification of pesticides and pesticide transformation products in 120 strawberry samples from a national survey of food contamination. Twenty pesticides and twelve pesticide transformation products were tentatively identified, where all pesticides and two pesticide transformation products (bifenazate diazene and spirotetramat-enol) were confirmed by standard materials. The outcome of this study suggested that retention time prediction is a valuable approach in compound identification when integrated with in silico MS2 spectra and other MS identification strategies.

Comprehensive strategy for analysis of pesticide multi-residues in food by GC-MS/MS and UPLC-Q-Orbitrap.

A rapid and high-throughput method using both GC-MS/MS and UPLC-Q-Orbitrap systems was applied for pesticide multi-residues analysis in food samples. Strategies based on QuEChERs extraction, intelligent data mining tools with in-house/online database, and in-silico fragment prediction system were introduced to screen and identify target/untargeted features. Full-scan combined with data-independent-acquisition modes was evaluated in real sample in an attempt to improve and facilitate the pesticide screening process, of which the results showed that FS-vDIA provided equal detection rate (100%) and far less false positive results than FS-AIF did. The proposed methodology was evaluated in analysis of pesticide multi-residues in several proficiency test samples provided by EURL, and exhibited a high detection rate (>90%) of various pesticide residues with satisfactory recoveries (70-130%) without reporting false positive results. The method was also applied in China's national surveys from 2016 to 2019, and results showed its high performance in pesticide analysis in different food matrices.

Distribution of the parent compound and its metabolites in serum, urine, and feces of mice administered 2,2',4,4'-tetrabromodiphenyl ether.

2,2',4,4'-Tetrabromodiphenyl ether (BDE-47) is a predominant polybromodiphenyl ether congener in the environment. Its absorption, excretion, and metabolism in animals have been investigated; however, the distribution of BDE-47 and its metabolites in excreta and blood at steady-state conditions has been unclear. In the present study, we addressed the issue by determining the amounts of BDE-47, eight monohydroxylated metabolites (OH-BDEs), and 2,4-dibromophenol (2,4-DBP) in serum, urine, and feces of gpt delta transgenic mice orally administered BDE-47 at 1.5, 10, and 30 mg/kg/d for 6 weeks during the 24 h period (for urine and feces) or at 24 h (for blood) post-last dosing. The distribution profiles in the three matrices showed that BDE-47, OH-BDEs, and 2,4-DBP were mostly distributed in urine (59-70%), feces (95-96%), and urine (51-80%), respectively. In each matrix, BDE-47 was the predominant compound under all doses, which accounted for 84-96% in serum, 68-98% in urine, and 37-92% in feces. However, exclusive of BDE-47, OH-BDEs were the predominant class of metabolites in serum (72-86%) and feces (67-87%), whereas 2,4-DBP was the major metabolite in urine (98-99%). Among monohydroxylated metabolites, the dominant compounds were 4-hydroxy-2,2',3,4'-tetrabromodiphenyl ether (4-OH-BDE-42) and 4'-hydroxy-2,2',4,5'-tetrabromodiphenyl ether (4'-OH-BDE-49) in feces (27-33% and 25-43%, respectively), and 3-hydroxy-2,2',4,4'-tetrabromodiphenyl ether (3-OH-BDE-47) in serum (26-43%). Thus, BDE-47 and 2,4-DBP were mostly present in urine, and OH-BDEs were primarily found in feces. Blood was not an important carrier for either BDE-47 or its metabolites. The data provide information for distribution and elimination of BDE-47 and its metabolites in mice at steady-state conditions.