Quantifying Spatial AMR Patterns across Urban and Rural Landscapes

抗生素耐药性在本质上正在增加，并威胁到我们药物治疗和感染控制的有效性。然而，仍然很难区分什么是源于人类活动，什么是自然。因此，我们必须扩大监测工作的规模和深度，以更好地了解是什么推动了抗性性状的增加。该项目将使用两组先前表征的土壤来比较和对比不同条件下AR基因的分布，包括城市、农业、遗留采矿和原始农村环境。该项目将利用DNA提取和新的遗传技术来量化样本中超过230个AR基因。土壤目录为我们提供了具有良好特征的土壤和描述土壤及其对源位置影响的丰富信息。该项目将产生惊人的120，000个AR相关数据点（400个位置x300个基因），每个位置都具有关于环境条件的扩展背景信息-创建了有史以来创建的景观中AR基因分布的最大地理代表性;足够详细，使横向观察景观的影响后天与先天AR水平。通过先进的多参数统计，我们将把特定的环境条件和因素与土壤中观察到的AR基因水平联系起来，以确定与抗性发展相关的风险因素以及对人类和农业健康的影响。

Antimicrobial resistance is increasing in nature and threatens the effectiveness of our drug therapies and infection control. However, it remains difficult to distinguish what originates from human activities or what is natural. Therefore, we must extend the scale and depth monitoring efforts to better understand what is driving the increases in resistance traits. This project will use two collections of previously characterised soils to compare and contrast distributions of AR genes under widely varying conditions, ranging from urban, agriculture, legacy mining, and pristine rural environments. The project will utilise DNA extractions and new genetic technology to quantify over 230 AR genes in the samples. Soil inventories provide us well-characterised soils and the wealth of information that describes both the soils and the impacts at source locations.The project will generate an astonishing 120,000 AR-related data points (400 locations x 300 genes), each with extended background information on environmental conditions-creating among the largest geographic representation of AR gene distribution across landscapes ever created; sufficiently detailed to make cross-cutting observations of landscape effects on acquired vs innate AR levels. With advanced multi-parametric statistics, we will relate specific environmental conditions and factors with observed AR genes levels in soils to identify risk factors associated resistance development and impacts on human and agricultural health.