BioQuest | Vol. 1, No. 1 (July 2017)
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Introduction
Metagenomics is the study of the collective
genomes recovered from environmental samples
without prior cultivation. It enables the investigation of
genome information on organisms. It is widely accepted
that up to 99.8% of the microbes present in many
environments are not readily culturable. ‘Metagenome
technology’ tries to overcome this bottleneck by
developing and using culture-independent approaches.
From the outset, metagenome-based approaches have
led to the accumulation of an increasing number of
DNA sequences, but until this time the sequences
retrieved have been those of uncultured microbes.
These genomic sequences are currently exploited for
novel biotechnological and pharmaceutical applications
and to increase our knowledge on microbial ecology
and physiology of these microbes. Using the
metagenome sequences to fully understand how
complex microbial communities function and how
microbes interact within these niches represents a major
challenge for microbiologists today (1).
In plant pathology, the metagenome of disease-
suppressive soils is of particular interest given the
expected prevalence of antibiotic biosynthetic clusters.
However, owing to the complexity of soil microbial
communities, deciphering this key genetic information
is challenging (2). There is a clear potential for
metagenomics to contribute to the study of microbial
communities of the rhizosphere, in particular PGPR.
Possible contributions include the discovery of novel
plant growth promoting genes and gene products, and
the characterization of unculturable PGPRs (3).
Metagenomics provides a new rationale and effective
methodology for identification of potentially important
genes, enzymes and biomolecules present in microbial
community. It is based on studies of ecological
diversity of uncultured and cultural microorganisms
using molecular biology (4).
Sampling and processing
Sample processing is the first and most crucial
step in any metagenomics project. The DNA extracted
should be representative of all cells present in the
sample and sufficient amounts of high-quality nucleic
acids must be obtained for subsequent library
production and sequencing. Processing requires specific
protocols for each sample type, and various robust
methods for DNA extraction are available (5,6).
Initiatives are also under way to explore the microbial
biodiversity from tens of thousands of ecosystems using
a single DNA extraction technology to ensure
comparability.
Sequencing technology
The metagenomic shotgun sequencing has
gradually shifted from classical Sanger sequencing
technology to next-generation sequencing (NGS).
Sanger sequencing, however, is still considered the gold
standard for sequencing, because of its low error rate,
long read length (> 700 bp) and large insert sizes (e.g. >
30 Kb for fosmids or bacterial artificial chromosomes
(BACs). All of these aspects will improve assembly
outcomes for shotgun data, and hence Sanger
sequencing might still be applicable if generating close-
to-complete genomes in low-diversity environments is
the objective (7).
Genome assembly
Genome assembly is a process wherein a large
number of sequences are assembled together to generate
a representation of the original chromosomes from
which the DNA originated. If the research aims at
recovering the genome of uncultured organisms or
Metagenomics and its prospects in phytopathology
Jeevan B1*, Rajal D, Subrahmanyam G, Veeranna D, Vijay N, Chutia M
1Central Muga Eri Research and Training Institute, Central Silk Board, Jorhat, Assam (India)
* Corresponding author email: [email protected]
BioQuest | Vol. 1, No. 1 (July 2017)
37
obtain full-length CDS for subsequent characterization
rather than a functional description of the community,
then assembly of short read fragments will be
performed to obtain longer genomic contigs. The
majority of current assembly programs were designed
to assemble single, clonal genomes and their utility for
complex pan-genomic mixtures should be approached
with caution and critical evaluation.
Binning
Binning refers to the process of sorting DNA
sequences into groups that might represent an
individual genome or genomes from closely related
organisms. Several algorithms have been developed,
which employ two types of information contained
within a given DNA sequence. Firstly, compositional
binning makes use of the fact that genomes have
conserved nucleotide composition (e.g. a certain GC or
the particular abundance distribution of k-mers) and this
will be also reflected in sequence fragments of the
genomes. Secondly, the unknown DNA fragment might
encode for a gene and the similarity of this gene with
known genes in a reference database can be used to
classify and hence bin the sequence.
Genome annotation
It includes two sequential processes i.e.,
structural annotation and functional annotation.
Structural annotation refers to the identification of open
reading frames (ORFs) (or hypothetical genes) in a
DNA sequence by means of computational gene
discovery software tools. Functional annotation deals
with assigning function to the predicted genes by
similarity searches against genes of known functions in
the database. The entire process of sequencing,
assembly and annotations generates enormous data that
act as a storehouse of information which can be used
later for various studies and comparisons.
Applications of metagenomics in Phytopathology
• Optimization of natural plant fertilization, rapid
identification of plant pathogens responsible of
emerging diseases.
• The antibiotic activity towards plant pathogens can
be assessed by Metagenomics.
• To locate the source for Induced Systemic
resistance.
• The genes for nitrogen fixation are retrievable with
the use of Metagenomics.
• The efficacy of PGPR is unrivalled by the use of
Metagenomics. Ex - A mutant of Pseudomonas
putida WCS358 unable to produce the antibiotic
pseudobactin 358.
Challenges and Future Directions
• Low abundance species overlooked.
• Lack of reference genomes.
• Sequencing complex environments cost
prohibitive.
• Standardizing metadata.
• New enzymes, antibiotics, and other reagents can
be identified.
• More exotic habitats can be studied.
• Improved bioinformatics will quicken analysis for
library profiling.
• Identified novel gene can be used in crop
improvement.
• Discoveries such as phylogenic tags (rRNA genes,
etc) will give momentum to the growing field.
• Discovery of novel plant growth promoting gene
and gene product from the rhizosphere.
References
Wolfgang R, Ruth A (2004) Metagenomics – the key to
the uncultured microbes. Current Opinion in
Microbiology, 7: 492–498.
Mendes R, Kruijt M, Bruijn L, Dekkers L, Voort M,
Schneider J, Piceno Y et al. (2011) Deciphering
the rhizosphere microbiome for disease-
suppressive bacteria. Science, 332: 1097-1100.
Daniel R (2005) The metagenomics of soil. Nature
Reviews Microbiology, 3: 470–478.
Lara VF, Castillo RF, Flores G, Aguilar CN, Rodriguez
HR (2011) Metagenomics in plant pathology.
Phytopathology, 31(2): 978-981.
Delmont TO, Robe P, Clark I, Simonet P, Vogel TM
(2011) Metagenomic comparison of direct and
indirect soil DNA extraction approaches. Journal
of Microbiological Methods, 86(3): 397–400.
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