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17 Omics’ Approaches to Analysis of Stress Response Genes in Medicinal Plants 315
17.7 Data Integration and Mining
The requirement for strong and enlightening bioinformatics tools that can provide
quickly accessible and effective integrative views to the enriched information that
data can deliver is constantly increasing due to the production of enormous volumes
of data from various -omics techniques. From this perspective, it is impressive to list
the key databases or sources for examining processes and their constituent parts in
terms of the roles played by genes, proteins, and metabolites in particular functional
processes. The three commonly used databases, KEGG, Reactome, and MetaCyc,
are examples of reference sources that provide details on biological and metabolic
processes. Querying for “abiotic stress” in the main page of the KEGG database
resulted in only five Oryza sativa (rice) proteins involved in responses to abiotic
stress. However, querying for “abiotic stress” exclusively in the pathways section of
KEGG resulted in only one MAPK signaling pathway in plants which includes,
among others, responses to cold, salt, drought, and osmotic stress (Mousavi et al.
2016; Jassal et al. 2020).
AgriGO, a comprehensive web-based GO analysis toolkit for the agricultural
world, was created more recently. SEA (singular enrichment analysis), PAGE
(parametric analysis of gene set enrichment), BLAST4ID (transfer IDs using
BLAST), and SEACOMPARE (cross comparison of SEA) are additional bioinfor-
matics analyses that AgriGO can run on 45 species and 292 data types (Thimm et al.
2004). AgriGO2.0, an improved version of this technology, has since been made
accessible to the general public. AgriGO2 is distinguished by a number of
implementations, such as the supported species count (394) and data type count
(865). Additionally, a greater user-friendliness of the web pages and an increased
computational performance, including batch analysis and p-value distribution
(PVD), as wel l as tools like direct acyclic graph (DAG) and scatter plots, were
accomplished (Arita et al. 2021).
The control of the timing and magnitude of certain stress responses occurs in
plants under abiotic stress and is regulated by upstream biological molecules.
Posttranscriptional processes, as opposed to RNA processing, alternative splicing,
and RNA silencing, define the actual transcriptome that stimulates the stress
response. A quick stress response is maintained by a variety of posttranslational
modifications, including sumoylation and ubiquitinati on, which regulate the activa-
tion of previously existing molecules outside regulatory proteins. In addition, there
has been a link between these mechanisms that amply illustrates extra and layered
layers of complexity in response to the environmental conditions (Raza et al.
2019).
Downstream stress-related genes are expressed in a time- and space-appropriate
manner thanks to the system of posttranscriptional and posttranslational
modifications.
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316 D. Sharma
17.8 Conclusion and Future Perspective
In agricultural research, high-throughput approaches have been utilized to compre-
hend functional analysis, molecular mechanisms of genes, and gene networks. The
development of climate-smart cultivars of legumes is a result of the major influence
that climate change has had on agriculture. Planning molecular studies has been
completely rethought, thanks to bioinformatics, which has made important advances
in scientific knowledge. For const ructing useful data collections, information from
bioinformatics and -omics programs is still crucial. Numerous statistics acquired by
omics research at the transcript, protein, and metabolite levels have been used to
study the capacity of plants to endure abiotic stress. To develop superior agronomic
features for crop improvements under environmental stress circumstances, func-
tional genomics can be used with transcriptomics, proteomics, metabolomics, and
ionomics. In light of this, we propose combining the application of multi-omics with
systems biology utilizing a top-down (phenotype to genotype) and bottom-up
(genotype to phenotype) strategy that might be useful to produce high-quality
agronomic traits for agricultural advances under environmental stress scenarios.
The most efficient way to give high-throughput data and predict future understand-
ing is through computational biology technologies.
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323
Next-Generation Sequencing (NGS)
for Metabolomics Study in Medicinal Plants
Under Stress Condition
18
Smaranika Pattnaik
Abstract
Medicinal plants are the nature’s best gift to mankind, with adequate source of
medicaments, the phytoconstituents which have tremendous importance in phar-
maceutical industry. The phytoconstituents are synthesized in a plant purpose-
fully to defend against the adverse conditions, specifically stress. Hence, the
stress factors like elevation of temperature, pH, salinity, osmolarity, and more
so wounding triggers the cascade reactions logarithmically to synthesize the
secondary metabolites, opting the secondary metabolism pathways, with expres-
sion of genes associated with stress factors. The chromosomal genes and plastid-
ial genes both are engaged for the purpose. The whole-genome sequencing
(WGS) using NGS approaches felt to be most contemporary strategy to tress
the genes expressing the phytoconstituents of interest under stress (POIUS).
Many authors have taken interest and carried out the WGS of medicinal plant
genomes using next-generation sequencing (NGS). This communication has
emphasized upon the sequent ial metabolomics studies, starting from UV-visible
scanning mode spectrophotometric analysis with detection of lambda (λ) maxima
of POIUS, using Fourier transform infrared (FTIR), for functional group recog-
nition, and GC/LC-MS spectrum diagnosis and conferring putative POIUS struc-
ture, carry forwarding the eluted peak fraction, collected by high-performance
liquid chromatography (HPLC), followed by nuclear magnetic resonance
(NMR)/X-ray crystallography for structural elucidation. The sequence of gene
(s) associated with expression of POIUS is annotated with bioinformatics
approaches. The Protein Data Bank (PDB) file (structural file) generation, its
S. Pattnaik (✉)
Laboratory of Medical Microbiology, School of Life Sciences, Sambalpur University, India,
Sambalpur
e-mail: smaranika2010@suniv.ac.in
#
The Author(s), under exclusive license to Springer Nature Singapore Pte
Ltd. 2023
D. Singh et al. (eds.), Stress-responsive Factors and Molecular Farming
in Medicinal Plants,
https://doi.org/10.1007/978-981-99-4480-4_18
https://t.me/medicina_free
solvent-based simulation, ORF detection, conserved domain identification , gene
ontology term annotation, and moreover deposition in public domain are the
essentials of contemporary research. The WGS using NGS has also impact upon
authentication of herbarium supplements also.
324 S. Pattnaik
Keywords
Medicinal plants · NGS · Phytoconstituents of interest under stress (POIUS) ·
Metabolomics · Genomics · Herbarium authentication
18.1 Introduction
Medicinal plants can be conside red as treasure trove of nature, providing safe, cost-
effective, target-oriented phytoconstituents to combat dreaded diseases since the
time immemorial. The traditional and historical examples of the usage of bioactive
natural products all originated in the ancient cultures, without any knowledge about
the underlying chemistry. Accordingly, the pharmacological or clinical charact eri-
zation of several known plant-derived compounds like the taxanes, artemisinin
derivatives or boswellic acids, tacrolimus, ascomycin, betulinic acid, and shikonin
were significantly broadened. For several hundred medicinal plants, reported from
corners of world, monographs have been published, in which the therapeutic evi-
dence has been synchronized. The important monographs are the German Commis-
sion E the European Pharmacopeia (PhEur), proceedings from a symposium held at
the Norwegian Academy of Science and Letter (2008), the European Scientific
Cooperative on Phytotherapy (ESCOP), the World Health Organization (WHO
monographs), and the European Medicines Agency—Herbal Medicinal Products.
Phytochemical constituents of medicinal plants encompass a diverse space of chem-
ical scaffolds which can be used for rational design of novel drugs (Pattnaik and
Mohapatra 2019). A distinct phytochemical entity of a medicinal plant is the
phytochemical profile of natural products. It is worthwhile to study the variety of
coexisting phytochemical constituents in the plant, which may be responsible for its
unique pharmacological activity (Liu et al. 2013). Phytochemicals vary in their
chemistry but can be divided into hydrophilic and hydrophobic compounds, of
which a wide variety of polyphenolic and terpenoid compounds, as well as alkaloids,
carbohydrates, and non-protein amino acids invoke special interest (Acamovic and
Brooker 2005). Novel approaches are in progress to classify plant kingdom based
upon phylogens (it is mainly the secondary metabolites that are utilized). The
synthesis and biological role of these chemical principles, as related to the products
of the primary metabolism, are special (Pattnaik and Behera 2019). As a result of
increasing interest in ethnic and traditional phytotherapeutics, medicinal plants are
the most important source of life-saving drugs for the majority of the world’s
population.
The development of new techniques in the fields of multi-omics technology,
biochemistry, cell biology, and molecular biology, e.g., new assay techniques, which
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are also applicable in the field of natural products chemistry, allowed the finding of
several new insights into the molecular mode of action and the pharmacological
characterization of known plant secondary metabolites. Biotechnology is also
playing a major role in the production of natural products through biosynthesis
and bioengineering. But at the same time, recent developments in the fields of
combinatorial chemistry, high-throughput screening, computational
capabilities,
and large database management are obligatory tasks in the process of drug develop-
ment strategies. In addition to the products of photosynthesis, the chloroplast
provides the energy and carbon building blocks required for synthesis of a wealth
of bioactive natural products of which many have potential uses as pharmaceuticals.
Hence, plants can be defined as a solar-powered biochemical factory (Fig.
18.1),
synth
esizing a myriad of secondary metabolites (SMs) that are derived from central
or primary metabolism.
18 Next-Generation Sequencing (NGS) for Metabolomics Study in... 325
Fig. 18.1 The essentials
of
medicinal plant life.
Herbarium identification
supplementation, genomics,
metabolomics,
transcriptomics,
pathogenomics, tracking of
evolution, DNA barcoding,
and moreover SNP detection
Pathogenomics
Metabolomics
DNA
barcoding
Transcriptomics
Tracking of
Evolution
SNP
detection
Genomics
Proteomics
identification
supplementation
Hebarium
18.1.1 Phytochemical Profile of Medicinal Plants
Phytochemical constituents of medicinal plants encompass a diverse space of chem-
ical scaffolds which can be used for rational desig n of novel drugs (Das Mohapatra
and Pattnaik 2021). A distinct phytochemical entity of a medi cinal plant is the
phytochemical profile of natural products (Dhami and Mishra 2015).
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