In large research institutions and academic communities, documentation of resources and results in databases is state of the art. Database systems are used to manage genetic resources ([6–10]). Databases make scientific results available to the scientific community, especially in the areas of transcriptomics [11], proteomics [12] and metabolomics [13]. The general availability of these data in standardized formats enable derived knowledge and integrative approaches [14–17]. The big exception from standardized formats is the documentation of experimental methods that link the genetic resources with the result and the knowledge. Well established, reliably repeatable methods - so-called standard operation procedures (SOPs) - are a valuable part of the success of any research institution. SOPs are, however, mainly documented in text style as part of a publication or - in case of method evolution - several publications linked by references. Alternatively, methods are made available as text files on web sites [18, 19]. There are academic approaches to document SOPs in databases [20, 21]. In these databases, text files with the method description are stored and linked to the result. As pointed out in the introduction, text-based documents have their drawbacks. Some methods are better stored in a database, especially those that involve complicated media preparation or many steps performed over a long period of time. Most users are, however, more familiar with word processing programs than databases. The 'interface' problem can be solved by so-called laboratory information management systems (LIMS). A LIMS provides a user-friendly graphic user interface to a database. In these systems, methods can be modeled as workflows. However, commercial LIMS systems are unavailable for most academic institutions, because of the considerable investment to set up such a system and to keep it running. For transcript profiling, an excellent open-source database system allows to document parameters of transcript profiling experiments [22]. For plant transformation, we devised a simple system to store standard operation procedures. The system is based on the widespread database system MS-Access and thus can be adjusted to specific requirements with a minimum of programming knowledge.
One of important features of our system is the 'self-referencing' Media module that allows generating complex media stepwise from more simple stock solutions. Thus, the entire process of making media from - at the bottom - commercially available compounds is completely and easily documented. The second important feature of the Media module is the reporting tool that provides printouts. These are indispensable in daily work at the bench, as the computer screen is usually not close to the lab bench. The database-generated printouts also facilitate the identification of the right medium for a step of a method by the matching name and identifier number (id) in the method description and on the media container. The identifier does not only increase safety by double-coding but also makes multi-language versions of the method much easier. This is especially important in international labs, in which English speaking scientist cooperate with local staff less fluent in English. Media and method printouts are admittedly also risky, as it is tempting to document changes in the material or method on the printout. Thus, staff needs to be trained to use the database system as the primary data source and document any deviation from the standard in the database.
An important feature of the system is its ability to cope with media and method evolution. If the deviation from the standard becomes a new standard, the new medium or method can be easily documented by duplicating the old method. The administrator in charge of the database can then approve of the new method and prevent its further alteration. At the same time, old methods can be taken out of use, but remain available for cross referencing.
The Experiment module of our SOP system is the module, in which the user can document deviations from the standard. This module automatically produces the plan for the experiment from the standard method description and generates an electronic lab book. In this lab book, any deviation from the plan concerning timing, media or method can be documented. For long-term experiments, the automatic generation of work schedules is another comfortable asset of the system. The work schedule allows early detection of work-peaks and facilitates hand-over of work between technical staff for times of absence.
In the beginning, the SOP system was run as a standalone solution at the MPI-MP and all data were entered directly. However, some of the information required in an experiment e.g. on plasmids and users were also present in the LIMS plant database system of the institute [10], which resulted in double entries. To save time, we devised a read access for expert users. The read function imports the information needed in the transformation process from the LIMS into the SOP database.
Finally, the system documents the result (number of lines) of the experiment. Failures are documented in a standardized way, thus problems are detected in an early state. Thus, data are rapidly available for decision making, e.g. about the stop of a method because of low efficiency.
