163
10.3.2 Linking BGCs to NPs
Identification of corresponding BGCs is also an important task to discover the
source of ‘orphan’ secondary metabolites. The availability of sequenced genomes
can be exploited by mining to connect BGCs to compounds. Comparative analysis
presents the easiest approach to tackle this. They could be used to identify similar
BGCs from two or more species that produce same or highly similar compounds
(Bok et al. 2015; Nielsen et al. 2013; Lambertz et al. 2014; Liu et al. 2015). Such
techniques are called targeted approaches. The whole biosynthetic potential in one
or more genomes could be assessed by an untargeted approach that analyses all
detected BGCs in the genome to databases such as clustermine360 (Conway and
Boddy 2012), IMG-ABC (Hadjithomas et al. 2015) and MIBiG (Medema et al.
2015) that contain information on fungal BGCs and their compounds. Nevertheless,
the task of comparing and evaluating the similarities among BGCs in fungi for the
purpose of clustering them is a not-so-straight-forward task due to obvious reasons.
Large size, inaccurately described boundaries, re-arrangements and possible presence of non-relevant genes are all probable factors. Investigations of the similarities
and uniqueness of BGCs among fungal species have been conducted minimally and
concerning only a few major species (Nielsen and Nielsen 2017). Thus, the scope of
using genomics to identify BGCs and corresponding NPs is by itself limited, particularly so in the case of siderophores. These limitations can be immensely overcome using integrated approaches merging computational genomics with the
potentials of transcriptomics, proteomics and metabolomics.
10.3.3 Utilizing Integrated Omics Approaches for Revealing
Natural Product Biosynthetic Pathways
With the revolution of high-throughput technologies in genome research, other
omics technologies such as proteomics and metabolomics are often incorporated in
genomic studies for the sake of better analysis. The identification of NRPS from
fungal genomes provides only limited scope due to the requirement of prior homology data. Such bottlenecks in bioinformatic studies to identify novel clusters or to
link known products to corresponding clusters are overcome by integrating information from proteomic, transcriptomic or metabolomic data. Consequent to the
post-genomic era, integrating the omics approaches is becoming increasingly
important in the discovery of NPs, making tremendous improvements in fungal
characterization. The requirement of a genome a priori can also be bypassed using
proteome-based approaches (Hillman et al. 2017). The discovery of siderophores in
a bacterial species without a sequenced genome was also reported with the aid of
proteomics (Chen et al. 2013).
One of the prime techniques in proteomics, mass spectrometry (MS) in compound detection has become highly sensitive with respect to NRP analysis and is
10 Bioinformatics Applications in Fungal Siderophores: Omics Implications
10.3.2 Linking BGCs to NPs
Identification of corresponding BGCs is also an important task to discover the
source of ‘orphan’ secondary metabolites. The availability of sequenced genomes
can be exploited by mining to connect BGCs to compounds. Comparative analysis
presents the easiest approach to tackle this. They could be used to identify similar
BGCs from two or more species that produce same or highly similar compounds
(Bok et al. 2015; Nielsen et al. 2013; Lambertz et al. 2014; Liu et al. 2015). Such
techniques are called targeted approaches. The whole biosynthetic potential in one
or more genomes could be assessed by an untargeted approach that analyses all
detected BGCs in the genome to databases such as clustermine360 (Conway and
Boddy 2012), IMG-ABC (Hadjithomas et al. 2015) and MIBiG (Medema et al.
2015) that contain information on fungal BGCs and their compounds. Nevertheless,
the task of comparing and evaluating the similarities among BGCs in fungi for the
purpose of clustering them is a not-so-straight-forward task due to obvious reasons.
Large size, inaccurately described boundaries, re-arrangements and possible presence of non-relevant genes are all probable factors. Investigations of the similarities
and uniqueness of BGCs among fungal species have been conducted minimally and
concerning only a few major species (Nielsen and Nielsen 2017). Thus, the scope of
using genomics to identify BGCs and corresponding NPs is by itself limited, particularly so in the case of siderophores. These limitations can be immensely overcome using integrated approaches merging computational genomics with the
potentials of transcriptomics, proteomics and metabolomics.
10.3.3 Utilizing Integrated Omics Approaches for Revealing
Natural Product Biosynthetic Pathways
With the revolution of high-throughput technologies in genome research, other
omics technologies such as proteomics and metabolomics are often incorporated in
genomic studies for the sake of better analysis. The identification of NRPS from
fungal genomes provides only limited scope due to the requirement of prior homology data. Such bottlenecks in bioinformatic studies to identify novel clusters or to
link known products to corresponding clusters are overcome by integrating information from proteomic, transcriptomic or metabolomic data. Consequent to the
post-genomic era, integrating the omics approaches is becoming increasingly
important in the discovery of NPs, making tremendous improvements in fungal
characterization. The requirement of a genome a priori can also be bypassed using
proteome-based approaches (Hillman et al. 2017). The discovery of siderophores in
a bacterial species without a sequenced genome was also reported with the aid of
proteomics (Chen et al. 2013).
One of the prime techniques in proteomics, mass spectrometry (MS) in compound detection has become highly sensitive with respect to NRP analysis and is
10 Bioinformatics Applications in Fungal Siderophores: Omics Implications