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Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_5968_Библиотеки_им_академика_М_И_Перельмана
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326 S. Pattnaik
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, invoke special interest (England et al. 2023). Novel
approaches are in progress to classify plant kingdom based upon phylogens. The
synthesis and biological role of these chemical principles are to be deciphered using
the contemporary techniques and tools. The plant being a solar power-induced
phytochemical factory (Padhan et al.
2017a) is to be deciphered with present-day
available tools and techniques. Contemporarily, the phytochemical profiling is
carried out primarily with metabolomics and further proceeding toward whole-
genome sequencing, using NGS approaches. The analytical tools, namely,
UV-visible spectrophotometry, GC/LC-MS, MALDI-TOF MS, FTIR, HPLC,
NMR, and X-ray crystallography, are conventionally used. The results are scripted
through the pertinent softwares.
18.1.2 Metabolomics Study of Phytoconstituents Synthesized Under
Stress Condition (POIUS)
The profiling of phytoconstituents of interest under stress (POIUS), synthesized
under stress condition, deserves advanced instrumentation (Fig. 18.2). Primarily
there is a need for a profile study, using UV-visible spectrophotometry scanning
mode, identifying the POIUS at its λ max, with reference to standard drugs. Based
upon the results, inferred from the UV visible data, a GC-MS/LC-MS (gas
Phytoconstuents of Interest
Under Stress
UV-Visible Scanning GC/LC-MS MALDI-TOF MS FTIR
HPLC
NMR
Xraycrystallography
Sequence simulaon
and PDB strauctural
file generaon
Fig. 18.2 The workflow of metabolomics (analysis of metabolites by analytical tools, viz.
UV-visible scanning, GC/LC-MS, MALDI-TOF, FTIR, HPLC, NMR, X-Ray crystallography,
sequence simulation, and PDB file generation
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chromatography-mass spectra/liquid chromatography-mass spectra) metabolite
profiling is needed, for the set of POIUS detection, with respective mass spectra.
In addition, the FTIR (Fourier transform infrared spectral analysis is also
recommended, to recognize the functional groups of POIUS. The UV-visible spec-
tral data, GC-MS/LC-MS data, and moreover FTIR data may be compiled and using
the omics softwares. An automated R-based software entitled “RMet” has be
en
developed to overcome the challenges in the large-scale metabolomic analysis
workflow of GC-MS and GC×GC-MS datasets (Moayedpour and Parastar
2019).
The metaMS software package is in pipeline for reading the files in open format
(as mzXML, mzML, mzData, and netCDF, which are independent of the
constructors’ formats and operated with self R functions, which can extract, filter,
align, and filling gaps. There is provision for annotation of isotopes, adducts, and
fragments. OpenMS (Padhan et al.
2017b) offers an open-source C++ library
(+ Python bindings) for LC/MS data management, analysis, and visualization,
www.OpenMS.de, while, uFTIR is an R package that implements an automatic
approach to analyze μFTIR hyperspectral images, performing “image classification”
using a spectral angle mapper algorithm, a library search approach. It interacts with
other R packages used for spectral analysis (Corradini et al.
2021). The
abovementioned metabolomics data may be scrutinized, and the HPLC (high-
performance liquid chromatography) aided fraction of respective peaks eluted in
GC/LC-MS spectrum may be collected and subjected to NMR (nuclear magne tic
resonance)/X-ray crystallography (Smyth and Mar
2000) for three-dimensional
structural elucidation. Inventors are always making continuous effort, to process
and quantify high-throughput data, like Happytools (Jansen et al.
2018), for the
samples of pharmaceutical importance. sSNAKE program runs both interactive and
script-based processing of NMR data of solids and liquids to fit multiple spectra
(or curves) simultaneously (van Meerten et al.
2019).
18 Next-Generation Sequencing (NGS) for Metabolomics Study in... 327
18.1.3 Generation of PDB Files of POIUS
Python scripting for biochemistry and molecular biology is considered as an essen-
tial tool in metabolomics approaches. A PDB (Protein Data Bank) file is typically
created from source files during compilation. It stores a list of all symb ols in a
module with their addresses and possibly the name of the file and the line on which
the symbol was declared. A typical PDB formatted file includes a large “header”
section of text which sums up the protein, citation information, and the details of the
structure solution, followed by the sequence and total list of atoms and their
respective coordinates. The file is called a “coordinate file” because it contains a
list of coordinates for all atoms of the protein structure in a conventional orthogonal
coordinate system, and the position o f each atom is defined by its x, y, and
z coordinates (Fig.
18.3). The PDB files of respective POIUS are visualized in
visualization programming softwares like Discovery Studio and Pymol, and the
biochemical characteristic features, bond angle, bond length, hydrophobicity, hydro-
gen bond donor and acceptor candidates, etc. are studied through computer-based
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softwares, a part of metabolomics. With compilation of metabolomics data, the
source plant of POIUS is subjected to whole-genome sequencing of either cytoplas-
mic DNA and/or plastid DNA, using NGS efforts.
328 S. Pattnaik
Model
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PROTEIN
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10.679
8.851
11.658
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9.256
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7.805
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–9.769
Fig. 18.3 The PDB structural file is constituted with header, enlisting the different atoms of the
molecule, the protein, metabolite, the chain IDs/number, residue numbers, and more so respective
atom coordinates at x, y, and z
18.1.4 Next-Gen Sequencing Using Whole-Genome Approach
Whole-genome sequencing is the subtle approach to have a comprehensive knowl-
edge on location and detection of both coding and noncoding gen es of interest. The
complete set of gene entities comprising adenine, guanine, cytosine, and thiamine of
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proportionate percentages can eluted at a time, focusing the structural as well as
functional genes. The set of eluted sequences are defined as sequence-gram
(Fig. 18.4) The NGS, next-generation sequencing technique refers appropriately to
robustness wi th dot point accuracy. WGS is the reflection of genotype of the plant
life.
18 Next-Generation Sequencing (NGS) for Metabolomics Study in... 329
18.1.4.1 Genome Sequencing Methods
There are two fundamental genome sequencing methods, which are used in sequenc-
ing labs driving automated tools, namely, (1) dideoxy (Sanger) sequencing (chain
termination method), pioneered by Sanger, which is primed with a DNA primer, a
denatured singl e-strand of DNA, mixture of the four deoxyribonucleotide precursors
(dNTPs), mixture of four deoxyribonucleotide precursors (ddNTPs) that are tagged
with different color fluorescent molecules, and a DNA polymerase. The N in NTPs
refers to all the nucleotide bases: adenine (dATP), thymine (dTTP), cytosine (dCTP),
and guanine (dGTP); together they are referred to as dNTPs. DNA polymerase
synthesizes the new DNA in the 5′ to 3′ direction, starting at the primer and stops
every time the DNA incorporates one of the ddNTPs instead of the normal dNTPs.
The ddNTPs have a single hydrogen, bound to the 3′ carbon, instead of the usual
OH, so when a ddNTP is added, another nucleotide cannot bind and continue the
chain and replication is stopped. Replication co ntinues and the participating DNA
strands are terminated randomly. This step produces a collection of DNA strands of
varying sizes that all end with a fluorophore-ddNTP. The other method is (2) the
chemical method, pioneered by Maxam-Gilbert, is carried out with working princi-
ple, of nucleobase-specific partial chemical modification of DNA and subsequent
cleavage of the DNA backbone at sites adjacent to the modified nucleotides. As a
result of which, the sequences are aligned, and the degree of intensity of respective
sequences is read, with depiction of representative peaks, namely, adenine, guano-
sine, cytosine, and more so thymine. This is important to mention that there is a great
importance of tagging of fluorophores with the sequences and measuring the degree
of intensity of fluorescence, using FRET (fluorescence resonance energy transfer
technology).
Fig. 18.4 The art work depicting sequence-gram of a stretch of chromosomal DNA of interest
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330 S. Pattnaik
18.1.4.2 Genome Sequencing Strategies Using NGS
The genome sequencing strategy is a plan of action designed with a goal of
sequencing of complete genome through certain crucial steps. After the selection
of genome of interest, there is a need for library creation (Fig.
18.5). Assembly of
contigs, ‘Prefinishing’ and ‘Finishing’ phase, after which the sequences are read by
pertinent softwares and is visualized in computer screen. The NGS can be defined as
the multi-taxing tool. The basic next-generation sequencing process involves
fragmenting DNA/RNA into multiple pieces, adding adapters, sequencing the
libraries, and reassembling them to form a genomic sequenc e.
The Illumina sequencing workflow is structured as (a) library preparation,
(b) cluster generation, (c) sequencing, and (d) data analysis.
The library is optimized with binding regio ns for clustering, b inding site for
sequencing, and also indexes for multiplexing. Libraries must have also binding
regions for specific adaptors. The clustering step is defined with positioning closely,
a group of DNA strands. Each cluster represents an array of copies of same DNA
strand in spots (diameter 1–2 μm), of a flow cell, constructed with microchannels
(Fig.
18.6). Each microchannel is coated with synthetic oligonucleotides, which
have complementarity with adapter sequences. The single DNA libraries are
hybridized to primer lawn; then the bound libraries are extended by polymerase
enzymes. For the purpose of sequencing, the total genetic entity, which is subjected
to shotgun fragmentation of genome, and the sequence of fragments called reads,
which are placed contiguously, called contigs. The contigs which are placed contin-
uously are called scaffolds, and gaps are filled with depiction of whole genome
(Fig. 18.7). Further, the WGS are subjected to BLASTn and or BLASTp analysis in
the NCBI portal (www.ncib.nim.nih). Further the sequences are screened for open
reading frames (ORFs) using online or offline (standalone) ORF finder softwares,
thus genes of interest.
18.1.5 Whole-Genome Sequencing Using NGS for POIUS
of Medicinal Plants
Plant chloroplasts genes matK and rbcL are conventionally used for the identifica-
tion of plants. The ITS, internal transcribed spacer 1 and spacer 2, genomic regions
Library
Creaon
Producon
of Congs
Assembly Prefinishing
Finishing
Fig. 18.5 The basic process of whole-genome sequencing comprising major steps: library crea-
tion, production of contigs, assembly of contings, and prefinishing and finishing
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are recommended as a core plant DNA barcode, which may be eluted in WGS, as the
chloroplast genes are maternally inherited, which may not be assured in all plants
(Upton et al. 2020). Basically, the hybrid plants will fall in this category. In wild
plants, stress-associated genes of chloroplast DNA are of utmost important as
the bifurcated secondary metabolite pathway is active in chloroplast (Fig. 18.8).
The metabolic gatekeeper enzymes, namely, “terpene synthases,” are synthesized by
the cytoplasmic as well as chloroplast DNA, thus catalyzing the sesquiterpenes and
triterpenes in cytoplasm and the diterpenes and monoterpenes in the chlor oplast
using respective pathways. The P450, (cytochrome P450 oxygenases), in endoplas-
mic reticulum (ER), mediates terpenoids synthesis in cytoplasm.
18 Next-Generation Sequencing (NGS) for Metabolomics Study in... 331
Fig. 18.6 The library
preparation of
DNA
sequences of interest. In the
flow cell a, spots; b, the
oligonucleotides are adsorbed;
the complementary sequence
with c, adapter is clutched
with spot adsorbed
oligonucleotide; e, extension
of oligonucleotide initiated
with the help of e, polymerase
Fig. 18.7 Showing the definitions used in whole-genome sequencing. The total genetic entity is
known as genome, which is subjected to shotgun fragmentation of genome, and the sequence of
fragments called reads, which are placed contiguously, called contigs, placed continuously, called
scaffolds and gaps are filled with depiction of whole genome
Genome skimming (Straub et
al.
2012) is a sequencing approach that uses
low-pass, shallow sequencing of a genome (up to 5%), to generate fragments of
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DNA, known as genome skims. Of note, the organellar DNA (OD), like plastid/
mitochondrion DNA, are in higher amount than the copies compared to the nuclear
DNA (ND). A shallow, low-pass sequencing attempt can yield many more reads for
OD than ND, making it easier assembly and thereby paving the way in a more
complete and contiguous genome assembly. Therefore, skimming of genome of OD,
emphasizing upon allocation of the genes of medicinal importance either in plastid/
mitoc
hon
drion genome, is highly recommended.
332 S. Pattnaik
Fig. 18.8 The art work depicts a typical plant cell can secrete the secondary metabolites
(phytoconstituents of interest under stress, POIUS) genes harbored in both cellular and chloroplast
DNA. The P450, (cytochrome P450 oxygenases) residing in endoplasmic reticulum (ER), mediates
terpenoids synthesis in cytoplasm; the key enzymes, “terpene synthases,” and the metabolic
gatekeepers keep on synthesizing sesquiterpenes and triterpenes in cytoplasm as well as diterpenes
and monoterpenes in chloroplast
The grand entry of whole-genome
sequencing using NGS robust tools had made
many successful stories in past, which may be defined as land marks in the scienti fic
endeavors. The major stepping stones for conferring (a) herbarium identification
supplementation, (b) genomics, (c) proteomics, (d) metabolomics,
(e) transcriptomics, (f) pathogenomics, (g) tracking of evolution, (h) DNA
barcoding, and moreover (i) SNP detection are highlighted in the following
paragraphs.
18.1.5.1 Authentication of Herbal Supplement
Herbarium is the critical resource of identification of plants, biodiversity, and
evolutionary linkages. However, the morphological characterization of plants may
have gaps in the knowledge. Therefore, due to advent of 18 s r RNA sequencing
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(Soltis et al. 1999; Komatsu et al. 2001; Wu et al. 2015; Li-Ping et al. 2021), the
taxonomy has much been in resolution. At least the genetic linkages could have
established. While WGS is the best approach to read all the sequences of interest,
more so the genes associated with synthesis of phytochemicals can be spotted from
the whole-genome unit. As WGS is a dynamic process, the medicinal plants,
specifically medicinal and aromatic plants, being enriched with bioactive molecules,
are stress or biocompetitive products, which can be recurrently
sequenced, and the
phytochemical expressing genes can be used as biomarkers. In this context, the
essential oil-producing grasses, belonging to family Poaceae L., namely,
Cymbopogon citratus, Cymbopogon martini, Cymbopogon flexuosus, Cymbopogon
nardus, Cymbopogon winterianus, Cymbopogon schoenanthus, and Cymbopogon
giganteus, are rich in limonene, geraniol, citral-α, citral-β, citronellol, citronellal,
geranyl acetate, neral, nerol, Myrcene, elemol, l
inalool, menthol, caryophyllene,
citronellyl acetate, α-terpineol, thymol, Germacrene-D, nerolidol, farnesol acetate,
and β-ocimene, as inferred from literature (Pattnaik et al.
1995a, b, 1996, 1997), and
so on. These phytoconstituents are of immense importance in pharmaceutical indus-
try, because of high therapeuti c index. The herbarium identification system (HIS)
only considers the Poaceae family characteristics, considering either natural system
of classification by Carolus Linnaeus, Bentham, and Hooker, phylogenetic classifi-
cation by Adolf Engler (1844–1930) and Karl A. Prantl (1849–1893), or Cronquist
classification (1999–1992) may not be able to ex
plain about chemotypic variation or
markers.
18 Next-Generation Sequencing (NGS) for Metabolomics Study in... 333
Hence, the h
erbarium identification procedure may be expedited with detecting
the genes engaged with expression of specific constituents, at a particular time
period/seasonally, and should be sequenced for whole-genome data, which may
pave a way for designated biomarkers. This is to mention that the system is not very
useful for identification and cannot be adopted in herbaria due to its high phyloge-
netic nature. Hence, the herbarium with well-preserved and well-protected DNA
sample is to be sequenced with NGS format, and the requisite documentation on the
genes of medicinal importance may be uncovered. Decades back, interested
investigators had generated sequence data from plant species, used as medicaments
against health-related issues for each genus in the three regions, namely, Nepal,
New Zealand, and the Cape of South Africa (Saslis-Lagoudakisa et al. 2012). The
authors had adapted phylogenetic methods from community ecology and
reconstructed a phylogeny for each of the three floras, as well as a combined
phylogeny to represent all three floras. It was reported that the investigators had
made a study on the distribution of medicinal plants that these hyper-diverse floras
encompass and identification nodes on the phylogeny medicinal plants of tradi tion-
ally used, which were defined as “hot nodes.” Acco
rdingly, the au
thors could infer
about identification of bioactive compounds used in medical purposes and could
cluster 1500 plants having history of therapeutic activity.
Efforts are in queue to bring renaissances in the process. There was introduction
(Folk et al.
2021) of an integrated Specimen-to-Laboratory Information Manage-
ment System (SLIMS), connecting sampling, and wet lab efforts stage wise. The
researchers use unique identifiers encoded in QR codes and a taxonomic database,
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and herbarium images may be uploaded to a citizen science platform for metadata
generation. The tissue samples can be subjected to high-throu ghput, plate-based
herbarium DNA extraction and sequencing and linking the herbarium image with
sequences using bioinformatics tools. This effort may be considered as a stepping
stone for herbarium identification using sequencing data. However, there is a lacuna
in the effort, not including the medicinal plants and its active c
onstituent biomarkers.
Successful efforts were made with short -read NGS sequencing in approximately
8000 specimens, linking with herbarium specimen characteristics (Kates et al.
2021).
It was inferred that there was elution of lower amount of DNA on timeworn,
degraded samples but had consistent sequencing success. Later, the captured
sequence libraries, along with paired-end reads comparisons, were evaluated by
bait set (Tohidia et al.
2020
), and SNPs were detected correctly from the captured
reads, from the DNA mat erial extracted from preserved specimens. For the creation
of a dataset production of complete cpDNA and rDNA sequences, isolated from
herbaria, in large scale, approaches were made and phylogenomics studies were
carried forward. Therefore, rDNA and plastid genome sequences from herbarium
specimens were sequenced from 25 herbarium specimens up to 80 years old from
16 different Angiosperm fa
milies (Zeng et al.
2018)
,
w
ith generation of paired-end
reads, yielding successful plastid genome assemblies for 23 species and nuclear
rDNAs for 24 species, using genome skimming approach.
334 S. Pattnaik
18.1.5.2 Genomics, Transcriptomics, and Metabolomics of POIUS
The genomes of medicinal plants are complex (Cheng et al. 2021), but due to advent
of next-gen WGS, with introduction of long read sequencings, several plant-derived
metabolites with medicinal importance and their genes could be traced out, because
of NGS. From the Medicinal Plant Genomics Resources (
http://mpgr.uga.edu), the
plants with medicinal active principles (Atropa belladonna (Solanaceae),
Camptotheca acuminata (Cornaceae), Cannabis sativa (Cannabaceae),
Catharanthus roseus (Apocynaceae), Digitalis purpurea (Plantaginaceae),
Dioscorea villosa (Dioscoreaceae), Echinacea purpurea (Asteraceae), Ginkgo
biloba (Ginkgoaceae), Hoodia gordonii (Apocynaceae), Hypericum perforatum
(Hypericaceae), Panax quinquefolius (Araliaceae), Rauvolfia serpentine
(Apocynaceae) Rosmarinus officinalis (Lamiaceae), and Valeriana officinalis
(Valerianaceae) are included in public database, integrated with respective medicinal
metabolites. The genes associated with expression of various phytoconstituents, of
medicinally important plants, under stress are reported by the interested researchers.
Gentiana crass icaulis and Gentiana straminea, the alpine medicinal plants, were
considered (Ala et al. 2023), and sequencings were made for the mitochondrial
genomes (mtDNAs), of 368,808 and 410,086 bp long using whole-genome sequenc-
ing approaches. The genome was harbored with of 52 and 49 unique genes, 18 core
genes.
In addition, the WGS sequencing of Digitalis purpurea (Plantaginaceae) (Amiri
et al.
2023) had been made from which there was detection of transcription factors,
transcriptional regulators, protein kinases, transporters, noncoding RNAs, and also
hub genes that are involved in the production of secondary metabolites. Besides,
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cardiac glycosides, the candidate genes for Scarecrow-Like Protein 14 (SCL14),
Delta24-sterol reductase (DWF1), HYDRA1 (HYD1), and Jasmonate-ZIM domain
(JAZ3) were amplified and validated with OMICs approaches. Moreover, the
upstream (HMGR), midstream (FPS), and downstream (DBR2) genes being respon-
sible for production of artemisinin (Artemisia annua L., Asteraceae) were also
deciphered by the said report ers.
18 Next-Generation Sequencing (NGS) for Metabolomics Study in... 335
In
a
review
r
eport
(Younessi-Hamzekhanlu et al.
2022), it was indicated that the
genes involved in secondary metabolite pathways are still incomplete. The de novo
assembly of chromosome-level genome of Gentiana macrophylla was finished,
using a combination of Nanopore, Illumina, and Hi-C scaffolding approaches
(Hu et al. 2022) of genome size, ~1.79 Gb (contig N50 = 720.804 kb).
In the past, attempts were made for the de novo transcriptome assembly and
analysis of Cymbopogon flexuosus by Illumina sequencing (Meena et al. 2016). The
key enzymes, namely, terpene synthases, pyrophosphatases, alcohol
dehydrogenases, aldo-keto reductases, carotenoid cleavage dioxygenases, alcohol
acetyltransferases, and aldehyde dehydrogenases were employed by candidate plants
in essential oil biosynthesis. Comparative essential oil profiling and mRNA expres-
sion analysis could categorize three Cymbopogon species (C. flexuosus, aldehyde
type; Cymbopogon martinii , alcohol type; and C. winterianus, intermediate type).
More so the proteomics approaches made by the authors led to a conclusive remark
about involvement of proteins for aromatic principle exerted by the said herbs.
Precisely, the stress-exposed factors and associated genes (Table 18.1) can be
detected, consi dering the stress-exposed plants, extracting the total RNA,
categorizing the 18s r RNA and mRNA for the authentication of identi fication of
plant variety, amplifying 18 s r RNA by PCR, sequencing using specific primers, and
more so separating mRNA for making cDNA (copy DNA). As per the strategy, the
DNA of interest may be subjected to shotgun sequencing of whole genome and
creating a library by inserting the sequences, using a compatible vector like
Ti-plasmid, and transforming to a host cell, making more reliable copies. The contig
sequence reads are kept aligned contiguously and joined following the “gap filling”
procedure, using cognate adapters. After joining and making a long stretch of
sequence line, which is the representative of codons, ascribed in mRNA, for
expression of metabolites of medicinal importance, under stress-associated gene
operon, the sequences are read, using bioinformatics softwares, both offline and
online. The key steps in sequencing approaches are drawn in Fig. 18.9, while a
typical transcriptomic checkerboard, generated by omics technology, is given in
Fig. 18.10, demonstrating the degree of expression level of genes associated with
POIUS.
Each of the genes, eluted in WGS, may be tagged with gene ontology (GO) terms
and linked with KEGG (Kyoto Encyclopaedia of Genes and Genomes), and the
whole dataset may be deposited in public domain for the purpose of open access. The
individual POIUS may be screened for druggability and lead likeness, following the
Lipinski’s rule of five (Das Mohapatra et al.
2020).
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