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Development of a methodological approach for the characterization of bioaerosols in exhaust air from pig fattening farms with MALDI-TOF mass spectrometry

机译:MALDI-TOF质谱法表征猪育肥场废气中生物气溶胶的方法学方法的开发

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In this paper, we evaluated matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) as a cultivation-independent, routinely applicable approach to identify microbial fractions in bioaerosol emission samples. We developed a streamlined protocol in line with the German state-of-the-art impingement sampling guideline. Following isokinetic sampling, a fast and reliable pretreatment methodology involving a series of cascade filtration steps was implemented, which produced fractions for spectrometric measurement devoid of interfering substances. We sampled the exhaust air from eight pig fattening farms around western Germany, which yielded two sets of samples for both method development and validation. For method development, in total 65 bacterial isolates were produced directly from the exhaust air samples, taxonomically classified by 16S rRNA-Gene sequencing, and subjected to MALDI-TOF analysis. In this way, we could assign fingerprint biomarkers to classified bacterial genera or even species to build up a preliminary reference database. For verification of the novel methodology and application of the reference database, we subjected the second set of exhaust air samples to the developed protocol. Here, 18 out of 21 bacterial species deposited in the database were successfully retrieved, including organisms classified in risk group 2, which might be used to evaluate the pathogenic potential of sampled exhaust air. Overall, this study pursues an entirely new approach to rapidly analyze airborne microbial fractions. (C) 2017 The Authors. Published by Elsevier GmbH.
机译:在本文中,我们评估了基质辅助激光解吸/电离飞行时间质谱(MALDI-TOF MS),作为一种独立于培养的常规应用方法来鉴定生物气溶胶排放样品中的微生物组分。我们根据德国最新的撞击采样指南开发了简化的协议。等速运动采样之后,实施了快速可靠的预处理方法,涉及一系列的级联过滤步骤,该方法产生的馏分用于光谱测量,没有干扰物质。我们对德国西部八个养猪场的废气进行了采样,得出了两组用于方法开发和验证的样品。为了进行方法开发,总共直接从废气样品中分离出65种细菌,并通过16S rRNA-Gene测序对其进行分类,然后进行MALDI-TOF分析。通过这种方式,我们可以将指纹生物标记物分配给分类的细菌属甚至物种,以建立初步的参考数据库。为了验证新颖的方法和参考数据库的应用,我们对第二组排气样品进行了开发。在这里,已成功检索到数据库中存储的21种细菌中的18种,包括归类于风险类别2中的生物,这些生物可用于评估采样废气的致病性。总的来说,这项研究采用了一种全新的方法来快速分析空气传播的微生物成分。 (C)2017作者。由Elsevier GmbH发布。

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