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一种基于KNIME的用于生物膜检测的半自动工作流程。

A semi-automated, KNIME-based workflow for biofilm assays.

作者信息

Leinweber Katrin, Müller Silke, G Kroth Peter

机构信息

Zukunftskolleg, Universitätsstraße 10, Postbox 216, Konstanz, 78457, Germany.

Konstanz Research School Chemical Biology (KoRS-CB), Universitätsstraße 10, Postbox 630, Konstanz, 78457, Germany.

出版信息

BMC Microbiol. 2016 Apr 6;16:61. doi: 10.1186/s12866-016-0676-9.

Abstract

BACKGROUND

A current focus of biofilm research is the chemical interaction between microorganisms within the biofilms. Prerequisites for this research are bioassay systems which integrate reliable tools for the planning of experiments with robot-assisted measurements and with rapid data processing. Here, data structures that are both human- and machine readable may be particularly useful.

RESULTS

In this report, we present several simplification and robotisation options for an assay of bacteria-induced biofilm formation by the freshwater diatom Achnanthidium minutissimum. We also tested several proof-of-concept robotisation methods for pipetting, as well as for measuring the biofilm absorbance directly in the multi-well plates. Furthermore, we exemplify the implementation of an improved data processing workflow for this assay using the Konstanz Information Miner (KNIME), a free and open source data analysis environment. The workflow integrates experiment planning files and absorbance read-out data, towards their automated processing for analysis.

CONCLUSIONS

Our workflow lead to a substantial reduction of the measurement and data processing workload, while still reproducing previously obtained results in the A. minutissimum biofilm assay. The methods, scripts and files we designed are described here, offering adaptable options for other medium-throughput biofilm screenings.

摘要

背景

生物膜研究当前的一个重点是生物膜内微生物之间的化学相互作用。该研究的前提是生物测定系统,其整合了用于实验规划的可靠工具,包括机器人辅助测量和快速数据处理。在此,兼具人类可读性和机器可读性的数据结构可能特别有用。

结果

在本报告中,我们展示了几种用于检测淡水硅藻极小曲壳藻(Achnanthidium minutissimum)细菌诱导生物膜形成的简化和自动化选项。我们还测试了几种用于移液以及直接在多孔板中测量生物膜吸光度的概念验证自动化方法。此外,我们举例说明了使用康斯坦茨信息挖掘器(KNIME,一个免费的开源数据分析环境)为该检测实施改进的数据处理工作流程。该工作流程整合了实验规划文件和吸光度读出数据,以便对其进行自动化处理以进行分析。

结论

我们的工作流程大幅减少了测量和数据处理工作量,同时仍能重现先前在极小曲壳藻生物膜检测中获得的结果。我们在此描述了所设计的方法、脚本和文件,为其他中等通量生物膜筛选提供了可适应的选项。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/870b/4823873/0a3c7863b8ac/12866_2016_676_Fig1_HTML.jpg

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