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1.
Environ Res ; 249: 118346, 2024 May 15.
Artigo em Inglês | MEDLINE | ID: mdl-38311204

RESUMO

Quantitative next-generation sequencing techniques have been critical in gaining a better understanding of microbial ecosystems. In soils, denitrifying microorganisms are responsible for dinitrogen (N2) production. The nosZ gene codes for nitrous oxide reductase, the enzyme facilitating the reduction of nitrous oxide (N2O) to N2. The objectives of this research were to: 1) understand how soil depth influences RNA concentration and nosZ gene abundance; 2) assess the spatial dependence of nosZ gene abundance in two claypan soil fields; and 3) compare and evaluate multiple RNA-based sequencing methods for quantifying nosZ gene abundance in soils in relation to dinitrogen (N2) production. Research sites consisted of two intensively studied claypan soil fields in Central Missouri, USA. Soil cores were collected from two landscape transects across both fields and analyzed for extractable soil RNA at two depths (0-15 cm and 15-30 cm). Measurements of nosZ gene abundance were obtained using real-time quantitative polymerase chain reaction (RT-qPCR), droplet digital polymerase chain reaction (ddPCR), and nanostring sequencing (NS). In both fields, soil RNA concentrations were significantly greater at 0-15 cm depth compared to 15-30 cm. These data indicated low overall soil microbial activity below 15 cm. Due to low quantities of extractable soil RNA in the subsoil, nosZ gene abundance was only determined in the 0-15 cm depth. Sequencing method comparisons of average nosZ gene abundance showed that NS results were constrained to a narrow range and were 10-20-fold lower than ddPCR and RT-qPCR at each landscape position within each field. Droplet digital PCR appears to be the most promising method, as it reflected changes in N2 production across landscape position.


Assuntos
Sequenciamento de Nucleotídeos em Larga Escala , Microbiologia do Solo , Solo , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Missouri , Oxirredutases/genética , Solo/química
2.
Sensors (Basel) ; 19(5)2019 Feb 27.
Artigo em Inglês | MEDLINE | ID: mdl-30818828

RESUMO

Optical diffuse reflectance spectroscopy (DRS) has been used for estimating soil physical and chemical properties in the laboratory. In-situ DRS measurements offer the potential for rapid, reliable, non-destructive, and low cost measurement of soil properties in the field. In this study, conducted on two central Missouri fields in 2016, a commercial soil profile instrument, the Veris P4000, acquired visible and near-infrared (VNIR) spectra (343⁻2222 nm), apparent electrical conductivity (ECa), cone index (CI) penetrometer readings, and depth data, simultaneously to a 1 m depth using a vertical probe. Simultaneously, soil core samples were obtained and soil properties were measured in the laboratory. Soil properties were estimated using VNIR spectra alone and in combination with depth, ECa, and CI (DECS). Estimated soil properties included soil organic carbon (SOC), total nitrogen (TN), moisture, soil texture (clay, silt, and sand), cation exchange capacity (CEC), calcium (Ca), magnesium (Mg), potassium (K), and pH. Multiple preprocessing techniques and calibration methods were applied to the spectral data and evaluated. Calibration methods included partial least squares regression (PLSR), neural networks, regression trees, and random forests. For most soil properties, the best model performance was obtained with the combination of preprocessing with a Gaussian smoothing filter and analysis by PLSR. In addition, DECS improved estimation of silt, sand, CEC, Ca, and Mg over VNIR spectra alone; however, the improvement was more than 5% only for Ca. Finally, differences in estimation accuracy were observed between the two fields despite them having similar soils, with one field demonstrating better results for all soil properties except silt. Overall, this study demonstrates the potential for in-situ estimation of profile soil properties using a multi-sensor approach, and provides suggestions regarding the best combination of sensors, preprocessing, and modeling techniques for in-situ estimation of profile soil properties.

3.
J Environ Qual ; 45(2): 565-75, 2016 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-27065404

RESUMO

Veterinary antibiotics (VAs) in manure applied to agricultural lands may change agrichemical degradation by altering soil microbial community structure or function. The objectives of this study were to investigate the influence of two VAs, sulfamethazine (SMZ) and oxytetracycline (OTC), on atrazine (ATZ) degradation, soil microbial enzymatic activity, and phospholipid fatty acid (PLFA) markers. Sandy loam soil with and without 5% swine manure (w/w) was amended with 0 or 500 µg kgC radiolabeled ATZ and with 0, 100, or 1000 µg kg SMZ or OTC and incubated at 25°C in the dark for 96 d. The half-life of ATZ was not significantly affected by VA treatment in the presence or absence of manure; however, the VAs significantly ( < 0.05) inhibited ATZ mineralization in soil without manure (25-50% reduction). Manure amendment decreased ATZ degradation by 22%, reduced ATZ mineralization by 50%, and increased the half-life of ATZ by >10 d. The VAs had limited adverse effects on the microbial enzymes ß-glucosidase and dehydrogenase in soils with and without manure. In contrast, manure application stimulated dehydrogenase activity and altered chlorinated ATZ metabolite profiles. Concentrations of PLFA markers were reduced by additions of ATZ, manure, OTC, and SMZ; adverse additive effects of combined treatments were noted for arbuscular mycorrhizal fungi and actinobacteria. In this work, the VAs did not influence persistence of the ATZ parent compound or chlorinated ATZ metabolite formation and degradation. However, reduced CO evolved from VA-treated soil suggests an inhibition to the degradation of other ATZ metabolites due to an altered soil microbial community structure.


Assuntos
Atrazina/metabolismo , Esterco , Microbiologia do Solo , Poluentes do Solo/metabolismo , Animais , Antibacterianos , Solo
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