89
approaches are the only answer to get an insight into complex seaweed lipid biology and its interactions with other metabolic pathways. It is anticipated that several models of lipid metabolic and signaling networks will be developed for
seaweeds in the near future, and systems biology tools and approaches will shape
the seaweed research landscape.
4.7 Conclusion
Recent advancements in MS-based approaches particularly the development of
(ultra)high-resolution/mass accuracy measurement capabilities and refinement of
soft ionization technique have been the driving force behind the successful application and integration of lipidomics in seaweed studies. Seaweed lipidomics has
opened up an unprecedented opportunity to explore the lipid diversity, discover new
lipid biomarkers, and deepen our understanding of seaweed lipid biochemical pathways that are crucial for adaptation and acclimation of seaweeds in diverse environmental conditions of marine ecosystem. To fully understand these mechanisms,
elucidation of seaweed lipidome (by targeted/nontargeted approaches) must be
combined with fluxes associated with lipidomic changes. The fluxes may also reveal
hitherto uncharacterized lipid biochemical pathways and can be achieved with isotopomer experiments. Lipidomics along with other omics technologies is emerging
as an important tool to practice systems biology in seaweeds as well, as lipids comprise a very significant part of the metabolome and play pleiotropic roles in cellular
functions. With the increasing availability of genomic, transcriptomic, and proteomic data in seaweeds, context-specific association of lipid molecular species
with proteins involved in biosynthesis and metabolism, and the concomitant genes
encoding these proteins, several lipid-specific pathways will be deciphered/reconstructed for seaweeds in the future.
However, a future challenge is to develop an integrative workflow that combines
different extraction procedures and mass spectrometric approaches to comprehensively assess all the lipid species in a given sample, as it is evident that no single
platform is sufficient to fully characterize the lipidome completely. A plethora of
different techniques is available, each with their own strengths and weaknesses.
It is believed that combining different lipidomic techniques, such as shotgun/LC
lipidomics, global profiling using LC-high-resolution MS, and quantitative targeted
lipid analyses with LC-QqQ MS and GC-MS, has the potential to yield the most
complete lipidomic datasets (Brügger 2014). Also, there is a great need for standardization and consolidation in the field of lipidomics, in terms of sample preparation, data collection methodology, and data management and analysis. Preprocessing
is a complicated step in the analysis of lipidomic data, and choices of parameter
settings greatly influence the outcome and thus the biological interpretation. More
bioinformatic research is required to develop improved algorithms that eventually
allow to preprocess data with no or only minimal human intervention. The standard4 Seaweed Lipidomics in the Era of ‘Omics’ Biology: A Contemporary Perspective
approaches are the only answer to get an insight into complex seaweed lipid biology and its interactions with other metabolic pathways. It is anticipated that several models of lipid metabolic and signaling networks will be developed for
seaweeds in the near future, and systems biology tools and approaches will shape
the seaweed research landscape.
4.7 Conclusion
Recent advancements in MS-based approaches particularly the development of
(ultra)high-resolution/mass accuracy measurement capabilities and refinement of
soft ionization technique have been the driving force behind the successful application and integration of lipidomics in seaweed studies. Seaweed lipidomics has
opened up an unprecedented opportunity to explore the lipid diversity, discover new
lipid biomarkers, and deepen our understanding of seaweed lipid biochemical pathways that are crucial for adaptation and acclimation of seaweeds in diverse environmental conditions of marine ecosystem. To fully understand these mechanisms,
elucidation of seaweed lipidome (by targeted/nontargeted approaches) must be
combined with fluxes associated with lipidomic changes. The fluxes may also reveal
hitherto uncharacterized lipid biochemical pathways and can be achieved with isotopomer experiments. Lipidomics along with other omics technologies is emerging
as an important tool to practice systems biology in seaweeds as well, as lipids comprise a very significant part of the metabolome and play pleiotropic roles in cellular
functions. With the increasing availability of genomic, transcriptomic, and proteomic data in seaweeds, context-specific association of lipid molecular species
with proteins involved in biosynthesis and metabolism, and the concomitant genes
encoding these proteins, several lipid-specific pathways will be deciphered/reconstructed for seaweeds in the future.
However, a future challenge is to develop an integrative workflow that combines
different extraction procedures and mass spectrometric approaches to comprehensively assess all the lipid species in a given sample, as it is evident that no single
platform is sufficient to fully characterize the lipidome completely. A plethora of
different techniques is available, each with their own strengths and weaknesses.
It is believed that combining different lipidomic techniques, such as shotgun/LC
lipidomics, global profiling using LC-high-resolution MS, and quantitative targeted
lipid analyses with LC-QqQ MS and GC-MS, has the potential to yield the most
complete lipidomic datasets (Brügger 2014). Also, there is a great need for standardization and consolidation in the field of lipidomics, in terms of sample preparation, data collection methodology, and data management and analysis. Preprocessing
is a complicated step in the analysis of lipidomic data, and choices of parameter
settings greatly influence the outcome and thus the biological interpretation. More
bioinformatic research is required to develop improved algorithms that eventually
allow to preprocess data with no or only minimal human intervention. The standard4 Seaweed Lipidomics in the Era of ‘Omics’ Biology: A Contemporary Perspective