The DNA is a code made of thousands of genes and contains all the necessary information for a plant to develop and carry all its vital functions: feeding, growing, fighting against pathogen attacks, etc. Depending on different conditions, the cells that form a plant will activate one or the other genes. For example, under drought conditions, genes leading to increased root length will be activated (to search for water in the soil); or after the attack of a pathogen, there will be activation of plant defense genes.
As an example, let’s think about a big factory in which there is a huge toolbox with everything you need for different tasks. The workers in that factory will choose only those tools which are necessary for their job:
As you can see, there are common tools for all the different workers (such as the screwdriver), some tools which are common to different workers but not to all of them (such as the adhesive tape, which is used by electricians and painters but not by plumbers) and some tools which are specific for a certain group of workers (such as the hammer for plumbers, the voltmeter for electricians or the brushes for painters). But, the most remarkable fact is that, even when they share some tools, there is a specific tool-set for each of the workers.
In this example, the factory would be a plant. Within this factory there would be a common tool-box (the DNA) but, each worker (each cell), would choose a specific set of tools (genes) to carry out a specific task.
In order to study how plants respond to specific conditions, it is necessary to know which genes are active in the different cells of the plant under those situations. For example, it would be interesting to know the genes which are active in the different cells of the leaves upon a pathogen attack. This knowledge could be used by scientists to modify the DNA of the plants in order to improve their response under this kind of adverse situations, which are frequently causing important agronomic losses.
Following our previous example, let´s imagine that our factory suffers a sudden power outage that needs to be repaired as soon as possible. We would need all the electricians working very efficiently. They would be using so much wire from the toolbox that, eventually, they would run out of it, and this would be a big problem for the factory because they would need to buy more wire and the repair of the power outage would be delayed. But what if we could modify this toolbox so there would be much more wire in it? Or even better, what if we could introduce a much more resistant wire into the toolbox? This is what we can do for plants by using genetic engineering techniques: increase the number of genes related to a given function (e.g., plant defense) or even improve these genes or introduce new genes which makes the plant more resistant to different plant stresses.
So, to reach this point, first we need to get to know very well which those genes are and how they meet their function. To do so, we need to isolate each individual cell so we can sequence their active genes separately. This is a difficult task due to the tiny size of the cells and the complexity of the DNA, but nowadays it is possible thanks to a combination of molecular genetic techniques and machine learning algorithms, giving raise to what is known as single cell RNA sequencing (scRNAseq).
Once we get to know the genetic components determining the behavior of the different cell types (this is, the tools used by the different workers), we can get advantage of this and apply it for our own interest. Potentially we could modify any plant process, introduce novel functions derived from other organisms or even create new ones. Although this might remind us of science fiction, there are some realistic approaches such as improving crop yield, reducing crop-diseases impact or obtaining beneficial compounds from plants (medicines, biofuel, etc.).
A strategy that we follow to control plant functions is the utilization of photoreceptors (which are molecules capable of responding to light stimuli) to activate the expression of genes at our will by applying lights of different colors. Going back to our factory, it would be like using a lantern to show the workers which tools they need to use, so they can work more efficiently. In addition, we could use different colors for the different tools, so each worker would know exactly which set of tools to use. This technology serves us to spatially and temporally control plant processes and it is called optogenetics (a combination of optic and genetic tools).
In the Cluster of Excellence on Plant Sciences (CEPLAS), we make a collaborative effort between the Plant Biochemistry and Synthetic Biology institutes to reach a common goal: understand the plant genetic code and use this knowledge to improve our lives and make a more sustainable world.
Under the heading Planter’s Punch we present each month one special aspect of the CEPLAS research programme. All contributions are prepared by our young researchers.
Dr. Miguel Miñambres Martín is a Postdoctoral Researcher at the Plant Biochemistry and Synthetic Biology Institutes at the Heinrich Heine University of Düsseldorf. His research area involves comparative transcriptomics and synthetic biology approaches to understand and control plant processes in a quantitative and spatiotemporally resolved manner.
During his PhD, Dr. Miñambres studied the transcriptional changes in Arabidopsis thaliana under phosphate starvation conditions at the Spanish National Centre for Biotechnology in Madrid, Spain.
Illustrations: María Miñambres Martín is a viticulturist at Ribera del Duero (Spain). Because of her job, she is in contact with agricultural biotechnology and benefits from plant research outputs.