Limits...
FluxTransgenics: a flexible LIMS-based tool for management of plant transformation experimental data

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ABSTRACT

Background: The production and commercial release of Genetically Modified Organisms (GMOs) are currently the focus of important discussions. In order to guarantee the quality and reliability of their trials, companies and institutions working on this subject must adopt new approaches on management, organization and recording of laboratory conditions where field studies are performed. Computational systems for management and storage of laboratory data known as Laboratory Information Management Systems (LIMS) are essential tools to achieve this.

Results: In this work, we have used the SIGLa system – a workflow based LIMS as a framework to develop the FluxTransgenics system for a GMOs laboratory of Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA) Maize and Sorghum (Sete Lagoas, MG - Brazil). A workflow representing all stages of the transgenic maize plants generation has been developed and uploaded in FluxTransgenics. This workflow models the activities involved in maize and sorghum transformation using the Agrobacterium tumefaciens method. By uploading this workflow in the SIGLa system we have created Fluxtransgenics, a complete LIMS for managing plant transformation data.

Conclusions: FluxTransgenics presents a solution for the management of the data produced by a laboratory of genetically modified plants that is efficient and supports different kinds of information. Its adoption will contribute to guarantee the quality of activities and products in the process of transgenic production and enforce the use of Good Laboratory Practices (GLP).

Conclusions: The adoption of the transformation protocol associated to the use of FluxTransgenics has made it possible to increase productivity by at least 300%, increasing the efficiency of the experiments from between 0.5 and 1 percent to about 3%. This has been achieved by an increase in the number of experiments performed and a more accurate choice of parameters, all of which have been made possible because it became easier to identify which were the most promising next steps of the experiments. The FluxTransgenics system is available for use by other laboratories, and the workflows that have been developed can be adapted to other contexts.

No MeSH data available.


Tasks’s Screen. Interface of the Tasks’ screen showing the executed activities.
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Figure 6: Tasks’s Screen. Interface of the Tasks’ screen showing the executed activities.

Mentions: In each transfer to a different medium, a control of the generated calluses is performed through the recording of inputs and outputs. This information contains the callus’ ID and the number of the copies of each callus (Figure 5). In the Transfer to A Medium activity, the stored calluses are identified and used (all or part of it) as input to the next activity. This behavior is repeated until the activity Transfer to Greenhouse. The following activity is the Pollination, where the pollination type used (self, cross or sibling) can be chosen from a drop-down menu. Pollination outputs are the id of the maize ear and the number of seeds. After the Pollination, the next activity is Harvesting. In this activity, the amount of picked seeds is stored as an output, including the date and the protocol used. The final activity is Destination, which stores the date and the protocol of the execution, allowing the user to record the destination of the seeds. This input/output feature is an important issue in FluxTransgenics. Through this procedure, the user can keep track of which calluses will generate the final genetically modified plants.During the laboratory routine, the user can access the system and verify, through the the tasks’ screen, which activities have been executed, which are available e which are scheduled to be executed (Figure 6).


FluxTransgenics: a flexible LIMS-based tool for management of plant transformation experimental data
Tasks’s Screen. Interface of the Tasks’ screen showing the executed activities.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4119470&req=5

Figure 6: Tasks’s Screen. Interface of the Tasks’ screen showing the executed activities.
Mentions: In each transfer to a different medium, a control of the generated calluses is performed through the recording of inputs and outputs. This information contains the callus’ ID and the number of the copies of each callus (Figure 5). In the Transfer to A Medium activity, the stored calluses are identified and used (all or part of it) as input to the next activity. This behavior is repeated until the activity Transfer to Greenhouse. The following activity is the Pollination, where the pollination type used (self, cross or sibling) can be chosen from a drop-down menu. Pollination outputs are the id of the maize ear and the number of seeds. After the Pollination, the next activity is Harvesting. In this activity, the amount of picked seeds is stored as an output, including the date and the protocol used. The final activity is Destination, which stores the date and the protocol of the execution, allowing the user to record the destination of the seeds. This input/output feature is an important issue in FluxTransgenics. Through this procedure, the user can keep track of which calluses will generate the final genetically modified plants.During the laboratory routine, the user can access the system and verify, through the the tasks’ screen, which activities have been executed, which are available e which are scheduled to be executed (Figure 6).

View Article: PubMed Central - HTML

ABSTRACT

Background: The production and commercial release of Genetically Modified Organisms (GMOs) are currently the focus of important discussions. In order to guarantee the quality and reliability of their trials, companies and institutions working on this subject must adopt new approaches on management, organization and recording of laboratory conditions where field studies are performed. Computational systems for management and storage of laboratory data known as Laboratory Information Management Systems (LIMS) are essential tools to achieve this.

Results: In this work, we have used the SIGLa system – a workflow based LIMS as a framework to develop the FluxTransgenics system for a GMOs laboratory of Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA) Maize and Sorghum (Sete Lagoas, MG - Brazil). A workflow representing all stages of the transgenic maize plants generation has been developed and uploaded in FluxTransgenics. This workflow models the activities involved in maize and sorghum transformation using the Agrobacterium tumefaciens method. By uploading this workflow in the SIGLa system we have created Fluxtransgenics, a complete LIMS for managing plant transformation data.

Conclusions: FluxTransgenics presents a solution for the management of the data produced by a laboratory of genetically modified plants that is efficient and supports different kinds of information. Its adoption will contribute to guarantee the quality of activities and products in the process of transgenic production and enforce the use of Good Laboratory Practices (GLP).

Conclusions: The adoption of the transformation protocol associated to the use of FluxTransgenics has made it possible to increase productivity by at least 300%, increasing the efficiency of the experiments from between 0.5 and 1 percent to about 3%. This has been achieved by an increase in the number of experiments performed and a more accurate choice of parameters, all of which have been made possible because it became easier to identify which were the most promising next steps of the experiments. The FluxTransgenics system is available for use by other laboratories, and the workflows that have been developed can be adapted to other contexts.

No MeSH data available.