Название | Phytomicrobiome Interactions and Sustainable Agriculture |
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Автор произведения | Группа авторов |
Жанр | Биология |
Серия | |
Издательство | Биология |
Год выпуска | 0 |
isbn | 9781119644828 |
2.3 Phytomicrobiome: The Communication via Signaling
The phytomicrobial associations are very comfortably established between the plant and the microbes through the exchange of signals as a form of communication. The orchestration of signals occurs not only between the host plant and microbial species but also among the microbial species present in a consortium. Appropriate signaling may prevent an unfavorable association by eliciting the defenses against the pathogenic invasions. Signaling governs each other's activity in the consortium as well as the community (Engelmoer et al. 2014). In the event of chemical signals within the community aids positive association for the benefit by enabling the residence of endophytes (Hartmann et al. 2014) and prevents futile or harmful associations.
The microbes in the association of the host have a signature sequence at the molecular level which is highly conserved for that species. The term associated with this phenomenon is known as microbe‐associated molecular patterns (MAMP). These molecular receptors present on the microbial species are recognized by pattern recognition receptors (PRR) which are also the ligand‐binding ectodomains in plants. The best‐known example of this MAMP is where the bacterial species have flagellin and chitin is specific to fungi (Newman et al. 2013). MAMP has one of the highlighting features in establishing plant immunity as well as eliciting antibiotic secretion in microbes. Bacterial species have also been known to interfere with signaling between plants and other strains of microbes. In order to enable pathogenic association, Bacillus strains have been shown to minimize the favorable MAMP‐regulated immune response which may also hinder the secretion of antibiotic substances to enable and establish an infection successfully.
These chemical signals may also be termed as the stress signals, which, as the name suggests, are generated in the course of a stressed situation for the growth of the plant. These signals shall in turn elicit the microbial signal which prepares the microbe to provide aid to the stressed plant by its metabolic activity. Signaling compounds produced are either primary metabolic compounds such as carbohydrates, organic acids, and proteins; as well as secondary metabolites such as phenols, phytohormones, and flavonoids, etc. Microbes to host plant signaling compounds include compounds such as phenols, peptides, plant hormones, acyl homoserine lactones, etc., which can also act as microbe to microbe signal. The major contribution in the selection of microbial consortia around the roots happens by the secretions of compounds by the root exudates. Arabidopsis thaliana releases malic acid in defense of the attack by the foliage pathogen which stimulates the production of beneficial biofilms in the rhizosphere (Rudrappa et al. 2008).
2.4 Proteomics
Proteins are ubiquitous biomolecules, known to be present fundamentally in some form or another across all living beings. These are the manifestation of all the structural and functional information embedded within the genetic code of the organism. It forms the inevitable component of every bioprocess thus acting as a basic ingredient of a biological pathway. The transformation from one functional form to another to carry out a function is executed by a protein designed for that particular function. Since proteins assemble into functional complexes, every functional complex begs for a varied condition. This makes the protein structure, function, and architecture almost varying at every stage of the process.
The proteome of an organism epitomizes the entire comprehensive range of proteins expressed within an organism. The term also incorporates the analysis of an assortment of proteins expressed within a specified tissue under exceptional conditions. The proteome is derived from the genome of an organism, yet the study of genome contrasts from that of the proteome due to the characteristic stability of the genome under all conditions as a contrast to the dynamism of the proteome expression based on organism's stage of development and time of observation.
Proteomics is the in‐depth study of the proteome which implicates the perception of how the proteins fold, interact, and function within a biological system. For instance, several proteins fold to form intricate three‐dimensional structures, and several complexes of subunits come together to form a functional complex. Proteins also undergo post‐translational modification which decides the fate of their function. This forms an imperative part of the proteomic study as well. The proteins are very sensitive even within the most tightly regulated environment, thus making them vulnerable to distortion once removed from their natural environment. Hence, a proteomic study desires highly sensitive technique.
The major domains in a proteomic study are the in‐depth aspects dealing with protein expression levels, effects of post‐translational modifications and the behavior of the proteins thereafter; the dynamics of protein interaction with effector molecules and their subsequent effects upon the cellular system on the whole; proteome mining, structural and functional proteomics. Moreover, the proteomic study has been broadly categorized based upon the expression mapping and the interaction mapping pattern. The mapping of protein expression is a global assessment of the changes taking place in a targeted tissue or cell of the amount and type of proteins being expressed. This is done using two‐dimensional gel electrophoresis followed by mass spectrometry. For further assessment, in‐gel proteolysis is done to form protein spots followed by peptide mass fingerprinting and then mass spectroscopy (Bantscheff et al. 2007). Spots produced on the 2D gel can be used to analyze partial peptide sequences by using the nano‐spray method. This flow of technique is utilized to identify and characterize the proteins for further study. Once preliminary data is obtained, then this data is subjected to various bioinformatics assessment using various tools. Such technologies contribute to collating a database consisting of protein expression profiles of specific tissue and cell (Rasmussen et al. 1996).
The proteins within a tissue decide the functional phenotype of the cell. Hence an actual estimate of the progression of the disease and the pathway relevant for the disease manifestation owing to a particular condition and time is determined by proteome analysis. Even though several techniques are available, it is imperative to make a decision as to which technique shall be relevant at what stage of the study. Therefore, it becomes mandatory to take a characteristic overview of every technique and their relevance in brief.
Traditionally, the detection of any plant microbial association like a symbiotic assessment or phytopathogenesis needs a traditional culturing and cultivation method of the plant on the specific media in the laboratory with subsequent biochemical and morphological analysis. This makes the whole process tedious, expensive, and time‐consuming (Kav et al. 2007). Until recently, phytomicrobial assessments required distinguishing techniques for the plant as well as microbial characterization. Techniques such as gel electrophoresis, traditional electron microscopy, and serological techniques were needed to ascertain the features of plants under observation while pathogenic microbe detection shall be ascertained using isolation and microscopic analysis, biochemical assays for characterizations, various serological techniques, etc. (Kav et al. 2007).
The next revolution was brought on by the development techniques like enzyme‐linked immunosorbent assays (ELISA) and polymerase chain reaction (PCR). With these techniques, the detection and characterizations of phytomicrobial interactions became more reliable and faster. Techniques such as flow cytometry, DNA microarrays, and in situ hybridizations became the standard methods for detection and confirmation of the associations (Kav et al. 2007). Still, these techniques are laden with their own set of disadvantages.
In addition to ELISAs and PCR, currently utilized phytopathogen detection techniques include flow cytometry, fluorescence in situ hybridization and DNA microarrays. While many of the traditional