87
navigation figures in the “Acyl lipid: pathways” homepage (http://aralip.plantbiology.
msu.edu/pathways/pathways); ARALIP is also very helpful for annotation of plant
lipids and their pathways representation.
However, only a few studies have been reported in seaweeds correlating genemetabolite (including lipid molecules) co-expression deciphering their adaptive/
acclimation responses to external cues (Dittami et al. 2011, 2012; Gravot et al.
2010; Groisillier et al. 2014; Rousvoal et al. 2011) recently reviewed by Kumar
et al. (2016). Tonon et al. (2011) proposed a protocol focusing on integrating heterogeneous knowledge gained on brown algal metabolism in Ectocarpus. The
resulting abstraction of the system will help in understanding how brown algae
cope with changes in abiotic parameters within their unique habitat and in deciphering the mechanisms underlying their acclimation and adaptation, respectively,
consequences of the behavior, or the topology of the system resulting from the
integrative approach. The transcriptomic and metabolomic analysis of copper stress
acclimation in E. siliculosus provided insight into the role of lipid and oxylipin
metabolic pathways in seaweeds (Ritter et al. 2014). The gene-metabolite coexpression data highlighted the activation of oxylipins and repression of inositol
(myoinositol) signaling pathways, together with the regulation of genes encoding
for several transcription associated proteins. A significant accumulation of
12-OPDA, PPA1, and PPA2, C20:4 cyclic prostaglandins such as PGA 2 and PGJ 2
with no change in MeJA was observed along with the upregulation of genes belonging to the CYP74 family (an interesting candidate for AOS activity involved in the
synthesis of oxylipins). Apart from this, there is hardly any information on correlation network analysis specifically focusing on integration of lipidomic data with
either gene or proteome data.
With recent development of lipidomic strategies in seaweeds (da Costa et al.
2015; Kumari et al. 2015; Melo et al. 2015), the futuristic development of lipidomegene as well as lipidome-proteome co-expression studies to decipher the novel lipid
pathways and their regulation under different perturbations can be foreseen.
Lipidomics in conjunction with other omic studies could also decipher the seaweed
lipid metabolic pathways, which is believed to be identical to higher plants and
microalgae, but not studied much. Recently only, it has been found that KAS II, one
of the key enzymes involved in FA biosynthesis in higher plants and microalgae, is
not found in Pyropia sp., and its role is played by its another isoform, KAS I (Chan
et al. 2012), as discussed above in Sect. 4.3. Moreover, there are many dissimilarities in the lipid metabolic pathways (specifically in oxylipin biosynthetic and metabolic pathways) in the elucidated genomes of different seaweeds; which may be due
to phyla- and/or species-specific variations due to conserved phyla-specific FA
compositions in seaweeds (Kumari et al. 2013b). For example, genes for both plastidial and microsomal desaturases are present in the genome of E. siliculosus, while
C. crispus genome does not have any gene for plastidial ACP desaturases. Instead it
contains stearoyl desaturase, which produces 18:1 from 18:0 in the endoplasmic
reticulum (Cock et al. 2010; Collén et al. 2013). The evolution of conserved lipid
biosynthetic pathway and the huge diversity and variability present among different
4 Seaweed Lipidomics in the Era of ‘Omics’ Biology: A Contemporary Perspective
navigation figures in the “Acyl lipid: pathways” homepage (http://aralip.plantbiology.
msu.edu/pathways/pathways); ARALIP is also very helpful for annotation of plant
lipids and their pathways representation.
However, only a few studies have been reported in seaweeds correlating genemetabolite (including lipid molecules) co-expression deciphering their adaptive/
acclimation responses to external cues (Dittami et al. 2011, 2012; Gravot et al.
2010; Groisillier et al. 2014; Rousvoal et al. 2011) recently reviewed by Kumar
et al. (2016). Tonon et al. (2011) proposed a protocol focusing on integrating heterogeneous knowledge gained on brown algal metabolism in Ectocarpus. The
resulting abstraction of the system will help in understanding how brown algae
cope with changes in abiotic parameters within their unique habitat and in deciphering the mechanisms underlying their acclimation and adaptation, respectively,
consequences of the behavior, or the topology of the system resulting from the
integrative approach. The transcriptomic and metabolomic analysis of copper stress
acclimation in E. siliculosus provided insight into the role of lipid and oxylipin
metabolic pathways in seaweeds (Ritter et al. 2014). The gene-metabolite coexpression data highlighted the activation of oxylipins and repression of inositol
(myoinositol) signaling pathways, together with the regulation of genes encoding
for several transcription associated proteins. A significant accumulation of
12-OPDA, PPA1, and PPA2, C20:4 cyclic prostaglandins such as PGA 2 and PGJ 2
with no change in MeJA was observed along with the upregulation of genes belonging to the CYP74 family (an interesting candidate for AOS activity involved in the
synthesis of oxylipins). Apart from this, there is hardly any information on correlation network analysis specifically focusing on integration of lipidomic data with
either gene or proteome data.
With recent development of lipidomic strategies in seaweeds (da Costa et al.
2015; Kumari et al. 2015; Melo et al. 2015), the futuristic development of lipidomegene as well as lipidome-proteome co-expression studies to decipher the novel lipid
pathways and their regulation under different perturbations can be foreseen.
Lipidomics in conjunction with other omic studies could also decipher the seaweed
lipid metabolic pathways, which is believed to be identical to higher plants and
microalgae, but not studied much. Recently only, it has been found that KAS II, one
of the key enzymes involved in FA biosynthesis in higher plants and microalgae, is
not found in Pyropia sp., and its role is played by its another isoform, KAS I (Chan
et al. 2012), as discussed above in Sect. 4.3. Moreover, there are many dissimilarities in the lipid metabolic pathways (specifically in oxylipin biosynthetic and metabolic pathways) in the elucidated genomes of different seaweeds; which may be due
to phyla- and/or species-specific variations due to conserved phyla-specific FA
compositions in seaweeds (Kumari et al. 2013b). For example, genes for both plastidial and microsomal desaturases are present in the genome of E. siliculosus, while
C. crispus genome does not have any gene for plastidial ACP desaturases. Instead it
contains stearoyl desaturase, which produces 18:1 from 18:0 in the endoplasmic
reticulum (Cock et al. 2010; Collén et al. 2013). The evolution of conserved lipid
biosynthetic pathway and the huge diversity and variability present among different
4 Seaweed Lipidomics in the Era of ‘Omics’ Biology: A Contemporary Perspective