Stark Lucy, Giersch Tina, Wünschiers Röbbe
Faculty of Mathematics, Natural Sciences and Computer Sciences, University of Applied Sciences Mittweida, Technikumplatz 17, 09648 Mittweida, Germany.
Faculty of Mathematics, Natural Sciences and Computer Sciences, University of Applied Sciences Mittweida, Technikumplatz 17, 09648 Mittweida, Germany.
Anaerobe. 2014 Oct;29:85-90. doi: 10.1016/j.anaerobe.2013.09.007. Epub 2013 Oct 4.
Understanding the microbial population in anaerobic digestion is an essential task to increase efficient substrate use and process stability. The metabolic state, represented e.g. by the transcriptome, of a fermenting system can help to find markers for monitoring industrial biogas production to prevent failures or to model the whole process. Advances in next-generation sequencing make transcriptomes accessible for large-scale analyses. In order to analyze the metatranscriptome of a mixed-species sample, isolation of high-quality RNA is the first step. However, different extraction methods may yield different efficiencies in different species. Especially in mixed-species environmental samples, unbiased isolation of transcripts is important for meaningful conclusions. We applied five different RNA-extraction protocols to nine taxonomic diverse bacterial species. Chosen methods are based on various lysis and extraction principles. We found that the extraction efficiency of different methods depends strongly on the target organism. RNA isolation of gram-positive bacteria was characterized by low yield whilst from gram-negative species higher concentrations can be obtained. Transferring our results to mixed-species investigations, such as metatranscriptomics with biofilms or biogas plants, leads to the conclusion that particular microorganisms might be over- or underrepresented depending on the method applied. Special care must be taken when using such metatranscriptomics data for, e.g. process modeling.
了解厌氧消化中的微生物群落是提高底物利用效率和过程稳定性的一项重要任务。发酵系统的代谢状态(例如由转录组所代表)有助于找到监测工业沼气生产的标志物,以防止出现故障或对整个过程进行建模。新一代测序技术的进展使得转录组能够用于大规模分析。为了分析混合物种样本的宏转录组,高质量RNA的分离是第一步。然而,不同的提取方法在不同物种中可能产生不同的效率。特别是在混合物种的环境样本中,无偏差地分离转录本对于得出有意义的结论很重要。我们将五种不同的RNA提取方案应用于九种分类学上不同的细菌物种。所选方法基于各种裂解和提取原理。我们发现不同方法的提取效率很大程度上取决于目标生物体。革兰氏阳性菌的RNA分离产量较低,而革兰氏阴性菌则可获得更高浓度的RNA。将我们的结果应用于混合物种研究,如生物膜或沼气厂的宏转录组学研究,得出的结论是,根据所应用的方法,特定微生物可能会被过度或不足代表。在将此类宏转录组学数据用于例如过程建模时必须格外小心。