Since the beginning of in vitro culture in 1902 when the Austrian botanist Gottlieb Haberlandt attempted to grow isolated plant cells and tissues (leaf mesophyll and hair cells) in nutritive solutions, a large body of work has emerged describing the optimization of different culture conditions to supply explants with all the components required for successful in vitro plant tissue propagation. During the past 70–80 years, more than 3000 scientific articles have described the use of over 2000 different culture media in plant tissue culture [1]. In vitro tissue propagation, however, is still a stressful procedure for plants, which can limit the successful establishment of plants upon transfer to ex vitro conditions [2]–[5]. In many cases, the best in vitro conditions do not lead to optimal ex vitro results. Therefore, a better understanding of the complex effects of the variables involved during the in vitro plant tissue growth on the in vitro culture and the ex vitro acclimatization results should lead to an improvement of the process. The effect of carbon in the media, light conditions and their interaction appear to be particularly important [6]–[8].
Sucrose is the most common carbon source used in plant cell, tissue and organ culture. Media with 3% sucrose have been the staple since Murashige and Skoog [9] described their MS medium. Sucrose acts during plant tissue culture as a fuel source for sustaining photomixotrophic metabolism, ensuring optimal development, although other important roles such as
carbon precursor or signaling metabolite have more recently been highlighted [10]–[13]. Sucrose also supports the maintenance of osmotic potential and the conservation of water in cells. However, high sucrose concentration in the media restricts the photosynthetic efficiency of cultured plants by reducing the levels of chlorophyll, key enzymes for photosynthesis and epicuticular waxes promoting the formation of structurally and physiologically abnormal stomata [3]. On the other hand, earlier studies have shown that plantlets growing under tissue culture conditions do not fix enough CO2 to sustain growth in the absence of sucrose, which is mainly due to limited CO2 inside the vessel [14]–[18].
High irradiance and low air humidity, during the subsequent acclimation phase are also stressful to plantlets when they are just starting to become photoautotrophic [19]–[21]. These limitations of in vitro-developed plants, many of which are specifically related to a low photosynthetic efficiency and a low capacity of regulating water loss, prompted the design of a large number of micropropagation protocols trying to favor the development of high photosynthesis capacity and subsequent ex vitro acclimatization [2], [22]–[30]. Most of these studies focused on discovering and identifying the best parameter(s) for an easy and fast assessment of the quality of in vitro cultured plantlets with regards to acclimation. Physiological parameters at subcellular levels, such as chlorophyll fluorescence, were widely proposed as a useful indicator of plant quality of acclimated plants [11], [31]–[33]. However, the use of chlorophyll fluorescence to assess the photoinhibition caused by the transfer of in vitro plants to ex vitro conditions has produced controversial results: while some researchers [34]–[38] found the largest photoinhibition in the least photoautotrophic rose plantlets; others [29] described that gardenia plantlets cultured under conventional sucrose concentration and irradiance, indeed photomyxotrophic plantlets, were the least photoinhibited. It seems clear, that a single level of response (any from subcellular up to whole plant scale) does not determine the quality of the plant due to the complexity of the responses of plants to the factors and their interactions at different levels of biological organization [39]. For instance, in vivo chlorophyll fluorescence cannot correlate with plant photosynthesis rate due to stomatal limitations [40] or the leaf level photosynthesis may not necessarily correlate with plant growth [41]–[42]. Hence, for proper development of an in vitro culture protocol, consideration should be given to analyzing the effect of in vitro factors (as sucrose or light) on parameters at the different levels of organization in a holistic plant system-biology approach. A review of the literature indicates that the evaluation of in vitro factor effects on the quality parameters of plants are typically performed using conventional statistical analysis of variance together with multiple comparison tests [43].
The development of platforms to integrate multidimensional and multiscale data and to derive models for explaining the process as a whole remains one of the main goals for the plant scientific community [45]–[49]. Soft-computing techniques, such as Artificial Neural Networks (ANN), appear to be quite promising in addressing complex analyses in biological studies [50]. ANNs are mathematical tools useful for modeling non-linear relationships between variables. Compared to conventional statistics, ANN has shown higher accuracy in prediction as pointed out in several plant science papers [43]–[44], [51]–[53] as well as in other scientific areas such as pharmaceuticals [54]–[55]. Recently, we have used a combination of ANN and fuzzy logic technology (neurofuzzy logic) to model complex multivariate datasets in order to find the best combination of factors for in vitro culture of grapevine [56] or to extract knowledge on apricot in vitro culture conditions from an historical collection of data via data mining [57]. However, these previous analyses were carried out using data from a single level of biological organization (one scale model). To the best of our knowledge, the utility of artificial intelligence to perform an analysis of the effect of in vitro factors on several parameters at different levels of biological organization (a multiscale approach) has never been proposed.
The advantage of the neurofuzzy logic technology for this purpose lies in its ability to process and model information and to present results in the form of linguistic terms (IF-THEN rules) and membership degrees [50]. Linguistic terms are the human tools to solve problems, make decisions or draw conclusions [50 and references therein].
In the present study, we test the validity of neurofuzzy logic as an appropriate strategy for modeling multivariate data and its effects on multiscale parameters for a better understanding and an improvement in the plant acclimation process. Specifically, the objectives of this work were: to assess the effectiveness of neurofuzzy logic technology in modeling multiscale data sets; to discover hidden knowledge and retrieve new insights into the regulation of sucrose and light on in vitro kiwifruit plant acclimation and, finally, to infer the optimal combination of plant traits to achieve the best acclimation.
No comments:
Post a Comment