217
The use of whole-cell modeling is also an attractive answer to the challenge
microbial engineering that can probe the bounds and productive potential of microalgae. This may be crucial for pathways or cellular functions whose operation
involves multigenic tuning, signaling and regulatory logic, subcellular organization,
or large-scale bulk cell properties and phenotypes. Honest estimates of uncertainties, model assumptions, and validating tests are all critical to the scientific relevance
of integrative analyses—as well as efficient and parsimonious algorithms that can be
widely adopted and understood. True biotechnological gains from data-based modeling in microbial systems will require the contextualization and design of methods
specifically to be predictive, parsimonious and practical engineering within larger
real-world goals, constrains, and opportunities (Georgianna and Mayfield 2012).
Marine systems are vast, and they are ubiquitously populated, produced, and balanced by the contextual operation of diverse and complex microalgae. Understanding
the molecular and genetic dynamics of present and future marine biological systems
will be crucial to interpret large-scale observations and shifts in marine ecosystems.
As cellular and biological systems often vary astonishingly in their distinctly varying modes of genome organization, regulation, metabolism, interactions, and environments, it will be crucial to begin modeling efforts by designing data collection,
analyses, model, and algorithms to suit the essential biology at hand. Many systems
may not simply conform to pre-existing assumptions, tools, or frameworks. As the
depth and variety of available data and modeling approaches continue to increase,
continued critical, honest, practical, efficient, and rigorous adaption of scientifically
focused thinking, data collection, modeling, analysis, prediction, and validation
methods will yield the most fit and fruitful and translatable products of systemslevel scientific research.
References
Ajjawi I, Verruto J, Aqui M, Soriaga LB, Coppersmith J, Kwok K, Peach L, Orchard E, Kalb R, Xu
W, Carlson TJ, Francis K, Konigsfeld K, Bartalis J, Schultz A, Lambert W, Schwartz AS,
Brown R, Moellering ER (2017) Lipid production in Nannochloropsis gaditana is doubled by
decreasing expression of a single transcriptional regulator. Nat Biotechnol 35(7):647–652
Alexander H, Jenkins BD, Rynearson TA, Dyhrman ST (2015) Metatranscriptome analyses indicate resource partitioning between diatoms in the field. Proc Natl Acad Sci 112:E2182–E2190.
doi:10.1073/pnas.1421993112
Armbrust EV, Berges JA, Bowler C et al (2004) The genome of the diatom Thalassiosira pseudonana:
ecology, evolution, and metabolism. Science 306:79–86. doi:10.1126/science.1101156
Ashworth J, Coesel S, Lee A et al (2013) Genome-wide diel growth state transitions in the diatom Thalassiosira pseudonana. Proc Natl Acad Sci U S A 110:7518–7523. doi:10.1073/
pnas.1300962110
Ashworth J, Turkarslan S, Harris M et al (2016) Pan-transcriptomic analysis identifies coordinated and orthologous functional modules in the diatoms Thalassiosira pseudonana and
Phaeodactylum tricornutum. Mar Genomics 26:21–28. doi:10.1016/j.margen.2015.10.011
Aylward FO, Eppley JM, Smith JM et al (2015) Microbial community transcriptional networks are
conserved in three domains at ocean basin scales. Proc Natl Acad Sci U S A 112:5443–5448.
doi:10.1073/pnas.1502883112
10 Marine Microalgae: Systems Biology from ‘Omics’
The use of whole-cell modeling is also an attractive answer to the challenge
microbial engineering that can probe the bounds and productive potential of microalgae. This may be crucial for pathways or cellular functions whose operation
involves multigenic tuning, signaling and regulatory logic, subcellular organization,
or large-scale bulk cell properties and phenotypes. Honest estimates of uncertainties, model assumptions, and validating tests are all critical to the scientific relevance
of integrative analyses—as well as efficient and parsimonious algorithms that can be
widely adopted and understood. True biotechnological gains from data-based modeling in microbial systems will require the contextualization and design of methods
specifically to be predictive, parsimonious and practical engineering within larger
real-world goals, constrains, and opportunities (Georgianna and Mayfield 2012).
Marine systems are vast, and they are ubiquitously populated, produced, and balanced by the contextual operation of diverse and complex microalgae. Understanding
the molecular and genetic dynamics of present and future marine biological systems
will be crucial to interpret large-scale observations and shifts in marine ecosystems.
As cellular and biological systems often vary astonishingly in their distinctly varying modes of genome organization, regulation, metabolism, interactions, and environments, it will be crucial to begin modeling efforts by designing data collection,
analyses, model, and algorithms to suit the essential biology at hand. Many systems
may not simply conform to pre-existing assumptions, tools, or frameworks. As the
depth and variety of available data and modeling approaches continue to increase,
continued critical, honest, practical, efficient, and rigorous adaption of scientifically
focused thinking, data collection, modeling, analysis, prediction, and validation
methods will yield the most fit and fruitful and translatable products of systemslevel scientific research.
References
Ajjawi I, Verruto J, Aqui M, Soriaga LB, Coppersmith J, Kwok K, Peach L, Orchard E, Kalb R, Xu
W, Carlson TJ, Francis K, Konigsfeld K, Bartalis J, Schultz A, Lambert W, Schwartz AS,
Brown R, Moellering ER (2017) Lipid production in Nannochloropsis gaditana is doubled by
decreasing expression of a single transcriptional regulator. Nat Biotechnol 35(7):647–652
Alexander H, Jenkins BD, Rynearson TA, Dyhrman ST (2015) Metatranscriptome analyses indicate resource partitioning between diatoms in the field. Proc Natl Acad Sci 112:E2182–E2190.
doi:10.1073/pnas.1421993112
Armbrust EV, Berges JA, Bowler C et al (2004) The genome of the diatom Thalassiosira pseudonana:
ecology, evolution, and metabolism. Science 306:79–86. doi:10.1126/science.1101156
Ashworth J, Coesel S, Lee A et al (2013) Genome-wide diel growth state transitions in the diatom Thalassiosira pseudonana. Proc Natl Acad Sci U S A 110:7518–7523. doi:10.1073/
pnas.1300962110
Ashworth J, Turkarslan S, Harris M et al (2016) Pan-transcriptomic analysis identifies coordinated and orthologous functional modules in the diatoms Thalassiosira pseudonana and
Phaeodactylum tricornutum. Mar Genomics 26:21–28. doi:10.1016/j.margen.2015.10.011
Aylward FO, Eppley JM, Smith JM et al (2015) Microbial community transcriptional networks are
conserved in three domains at ocean basin scales. Proc Natl Acad Sci U S A 112:5443–5448.
doi:10.1073/pnas.1502883112
10 Marine Microalgae: Systems Biology from ‘Omics’