Review presentation of biofuels based on microalgae with focus on Chlamydomonas reinhardtii. The presentation includes microalgal biomass production process and the latest research on C. reinhardtii organisms such as genome and genetic engineering. Might be interesting for students and others who are interested in microalgal biofuels.

1. MICROALGAL
BIOFUELS
FE580 - SPECIAL TOPICS IN FOOD ENGINEERING
PRESENTED BY: FARID MUSA
İzmir Institute of Technology, Bioengineering dep. – Urla/IZMIR

2. OUTLINES
• GLOBAL ENERGY ISSUES
• INTRODUCTION TO BIOFUELS
• ALGAL BIOFUELS
• MICROALGAL MODEL ORGANISM GENOME (C. Reinhardtii)
• GENOME-SCALE METABOLIC NETWORK MODEL (AlgaGEM)
• CONCLUSION
2

3. WORLD ENERGY PRODUCTION
3
World Total Primary Energy Supply (2016) by fuel, Million Tonnes of Oil Equivalent
1 Mtoe = 11630 GWh
Ref: IEA (https://www.iea.org/statistics/kwes/supply)

4. GLOBAL ENERGY OUTLOOK
According to IEA there are two scenarios for future energy
outlook
• New Policies Scenario (NPS)
• Sustainable Development Scenario (SDS)
Change in Global Total Energy Demand
• Increase by 29% based on NPS
• Increase by 0.7% based on SDS
Change in Total CO2 Emissions
• Increase by 10% based on NPS
• Decrease by 45% based on SDS
4
Ref: IEA (https://www.iea.org/weo/)

5. TOTAL ENERGY DEMAND
5
NPS
SDS
Ref: IEA (https://www.iea.org/weo/)

6. GLOBAL CO2 EMISSIONS
6
NPS
SDS
Ref: IEA (https://www.iea.org/weo/)

7. GLOBAL TEMPERATURE ANOMALY
7
Ref: https://ourworldindata.org/co2-and-other-greenhouse-gas-emissions

8. INTRODUCTION TO BIOFUELS
• According to World Energy Council: Bioenergy is energy
from organic matter (biomass), i.e. all materials of biological
origin that is not embedded in geological formations (fossilised)
• Bioenergy supplies 10% of global energy supply
• Bioenergy is derived from biofuels
• Compared to other renewable energy sources like solar or
wind energy, biofuels can be transported much easier
• Biofuels can be primary and secondary.
• Primary biofuels are derived from: firewood, wood chips,
pellets, animal waste, etc.
• Secondary Biofuels are divided into Three Generations
8
Refs: https://www.worldenergy.org/wp-content/uploads/2017/03/WEResources_Bioenergy_2016.pdf ;
https://www.greenfacts.org/en/biofuels/l-2/1-definition.htm;
https://www.renewableenergyworld.com/bioenergy/tech/biofuels.html

9. TYPE OF BIOFUELS
9
Ref: (Luque et al., 2008)

10. FIRST GENERATION
Biofuels Biomass Feedstock Methods
Appx.
Production
Cost
Disadvantages
• Bioethanol
• Butanol
• Starch (wheat, barley,
corn, potato)
• Sugars (sugarance and
sugar beet.)
Fermentation
0.45-0.55 $/L Food vs Fuel
• Biodiesel
• Oil crops (rapeseed,
soybeans, sunflower,
palm, coconut, used
cooking oil, and animal
fats)
Transesterification
10
Ref: (Lam & Lee et al. 2012); (Rastogi et al. 2017); (Rodionova et al. 2017)

11. SECOND GENERATION
Biofuels Biomass Feedstock Methods
Appx.
Production
Cost
Disadvantages
• Bioethanol
• Butanol
• Lignocellulosic biomass
(poplar, miscanthus,
switch grass; sugarcane,
etc.
Fermentation
0.80-1.20 $/L
• Pre-treatment is
required
• Heavy fertilization
• Etc.
• Biodiesel
• Non-edible vegetable oil(
jatropha, karanja,
mahua, linseed, etc.)
Transesterification
11
Ref: (Lam & Lee et al. 2012); (Rastogi et al. 2017); (Rodionova et al. 2017)

12. THIRD GENERATION
ALGAL BIOFUELS
12

13. THIRD GENERATION BIOFUELS
• Biofuels: Bioethanol, Biodiesel, Hydrogen, Bio-Oil, Bio-Char,
etc.
• Biomass Feedstock:
• Microalgae: Eukaryotic or Cyanobacteria
• Macroalge or Seaweed: Red, Green, Brown
• Approximate Production Cost: 1.50 – 2.50 $/L
• Disadvantage: High Production Cost
13
Ref: (Chen et al. 2015); (Suali et al. 2012); (Rastogi et al. 2017)

14. ALGAL BIOMASS CONVERSION
14
Ref: (Suganya et al. 2016)

15. WHAT IS ALGAE?
The term “algae” has no formal taxonomic standing
It is used to refer to a diverse group of polyphyletic simple oxygen
evolving photosynthetic organisms that are not plants
There are more 20,000 known algae species
Algae are responsible for 40-50% of global photosynthesis
The study of algae is called phycology.
Algae live and affect marine, freshwater, and some
terrestrial ecosystems
Algae can be unicellular, colonial, or multicellular
Most algae are eukaryotic and live in aquatic habitat
Blue-green algae (Cyanobacteria ) are prokaryotic algae
15
Ref: (Hallmann et al. 2015); http://www.biologyreference.com/A-Ar/Algae.html

16. TREE OF LIFE
16
Ref: (Hallmann et al. 2015);
(Leiteet al. 2011);

17. PHENOTYPES SPECTRUM
& RESPECTIVE SIZES
17
Ref: (Hallmann et al. 2015);

18. BIOFUEL PRODUCTION
1 Algae
Cultivation
2Harvesting
3 Biomass
Extraction
4Conversion
18

19. MICROALGAL TRANSFORMATION
19
Ref: (Suali et al. 2012);

20. ALGAE CULTIVATION
20
• Open-Culture
• Main advantage: Cheap
• Main disadvantage: CO2 loss
• Targets lower value products like biomass for biofuels.
• Closed-Culture
• Main advantage: High control
• Main disadvantage: Expensive
• Targets high value products like pigments, proteins, lipids,
carbohydrates, vitamins, etc.
• Integrated Systems
• Agro-Industrial wastewater integration
• Industrial flue gas CO2 sequestration
Ref: (Hallmann et al. 2015); (Rastogi et al. 2017)

21. OPEN-SYSTEM CULTIVATION
Paddle-wheel raceway pond and Circular stirred pond
• Pros: Low costs, Direct Sun, Easy Clean, etc.
• Cons: Large Areas, Poor mixing and light penetration, Weather dependent, etc.
Open-air thin-layer culture system
• Pros: Simple and cheap construction, Efficient sunlight usage, Low energy
demand, etc.
• Cons: Difficult cleaning, CO2 loss, Chance of contamination, etc.
Tubular photobioreactor
• Pros: High surface-to-volume ratio, High photosynthetic efficiency, High mixing
efficiency, etc.
• Cons: Cell damage due to shear forces, increased dissolved oxygen, fouling etc.
Tubular photobioreactor
• Pros :Low CO2 loss, Best mixing, High mass transfer and growth rate, etc.
• Cons: Sophisticated construction, Inefficient large-scale mixing, Reduced
illumination, etc.
21
Ref: (Hallmann et al. 2015); (Rastogi et al. 2017)

22. CLOSED-SYSTEM CULTIVATION
Vertical or horizontal Flat
panel/plate photobioreactor
• Pros: Suitable for outdoor cultures,
Best solar energy harvesting, Low
accumulation of dissolved oxygen,
etc.
• Cons: Low surface-to-volume ratio,
difficult scale-up, fouling, etc.
22
Ref: (Hallmann et al. 2015); (Rastogi et al. 2017)

23. INTEGRATED SYSTEMS
23
Ref: (Rastogi et al. 2017)

24. HARVESTING
• Algae Harvesting refers to concentration of diluted algae suspension
until a thick algae paste is obtained
• Account approximately up to 20–30% of the total biomass production
cost
• It is one of the most challenging stages of algal biofuel production
towards efficient and cost-effective industrial scale process
• Common harvesting methods
• Physical: Centrifugation, Filtration, Flotation, Sedimentation
• Chemical: Flocculation (Autoflocculation, Inorganic, Polymeric,
etc.)
• Biological: Bio-flocculation
24
Ref: (Hallmann et al. 2015); (Rastogi et al. 2017); http://www.oilgae.com/algae/har/mia/mia.html

25. HARVESTING PROCESS
25
Ref: (Suali et al. 2012);

26. METHOD COMPARISON
26
Ref: (Shen et al. 2013)

27. FINAL BIOMASS
PRODUCTION STEPS
27
Ref: (Shen et al. 2013)

28. LIPID EXTRACTION
• “Purpose of the extraction process is to obtain oil from the algal
cells to ease their conversion into biofuel or other agricultural
products through biochemical or thermochemical means”
(Suali et al. 2012)
• There are several lipid extraction methods such as
mechanical, physical, chemical or enzymatic
• Solvent extraction of lipid from dry biomass is common and
efficient method, but biomass drying is highly energy
requiring process
• Therefore, lipid extraction from web biomass is more
feasible for biofuel production
• N and P starvation leads to higher lipid production in some
microalgae
28
Ref: (Hallmann et al. 2015); (Rastogi et al. 2017); (Rodionova et al. 2017)

29. LIPID EXTRACTION
• Organic solvents such as hexane can be highly flammable and toxic,
and high energy demanding during solvent recovery
• Although with different limitations lipid extraction using supercritical
CO2 is most promising method due to its inert, non-flammable, non-
toxic characteristics
• ScCO2 produce solvent free lipids without thermal degradation
from both dry and wet biomass
• Triacylglycerols (or triglycerides, TG, TAG) are lipid produced by
microalgae and converted into biofuels like biodiesel via
transesterification process
• Microalgae can have high TAG content ranging from 20 – 80% of dry
microalgae weight
• The rest of the algae dry weight contain carbohydrates and
proteins which can used to produce bioethanol or biohydrogen via
fermentation
29
Ref: (Hallmann et al. 2015); (Rastogi et al. 2017); (Suali et al. 2012); (Rodionova et al. 2017)

30. LIPID (TAG) BIOSYNTHESIS IN MICROALGAE.
30
Ref: (Radakovits et al. 2010)

31. CONVERSION INTO BIODIESEL
31
Ref: (Rodionova et al. 2017)

32. TRANSESTERIFICATION
32
Ref: (Suali et al. 2012)

33. CONVERSION INTO BIOETHANOL
33
Ref: (Suali et al. 2012)

34. CONVERSION INTO BIOHYDROGEN
34
Ref: (Rodionova et al. 2017)

35. MICROALGAE FOR BIOFUEL
35
Ref: (Lam et al. 2012)
continues…

36. TARGET ORGANISM
36
Chlamydomonas
reinhardtii

37. WHY C. REINHARDTII?
• Green alga Chlamydomonas reinhardtii has been the focus of
most molecular and genetic phycological research.
• This microalgae is a popular unicellular organism extensively
studied and provides an excellent microbial platform for the
investigation of fundamental biological functions
• Biomass obtained from C. reinhardtii can be used to produce
various biofuels including biohydrogen via dark fermentation
• There is a genome-scale metabolic network model called
AlgaGEM for C. reinhardtii
• Most research of microalgae genetic engineering studies are
based on C. reinhardtii
37
Refs: (Blabyal et al. 2014); (de Oliveira Dal’Molin et al; 2011); (Lam et al. 2012); (Rodionova et al. 2017)

38. KEY EVENTS IN MICROALGAE SYNTHETIC BIOLOGY
38
Ref: (Jagadevanet et al. 2018)

39. 39
Ref: (Merchant et al. 2007)

40. C. REINHARDTII GENOME
40
Ref: (Blaby et al. 2014)

41. C. REINHARDTII GENOME
ASSEMBLY
• C. Reinhardtii genome assembly version v3.1 carried out by
Merchant al. 2007 by whole-genome shotgun end sequencing of
plasmid and fosmid libraries, followed by assembly into ~1500
scaffolds
• Based on alignments of expressed sequence tags (ESTs) to the
genome, draft assembly is 95% complete
• 6968 protein families of orthologs, co-orthologs and paralogs
were identified
• 2489 were homologous to proteins from both Arabidopsis and
humans
• 706 protein families were shared with humans but not with
Arabidopsis
• 1879 protein families were shared with Arabidopsis but not
with humans
41
Ref: (Merchant et al. 2007)

42. C. REINHARDTII GENOME
42
Ref: (Merchant et al. 2007)
marine green alga
unicellular red alga
small flowering plant

43. LINKAGE GROUPS AND
HOMOLOGS
43
Ref: (Merchant et al. 2007)

44. SUMMARY OF GENOMIC COMPARISONS
44
Ref: (Merchant et al. 2007)

45. NEXT-GENERATION
SEQUENCING
• Assembly v3.1 contained many gaps due to high G+C% of
genome content
• Assembly v4.0 completely reassembled genome and
improved genome assembly by leaving only 7.5% gaps
• Assembly v5.0 was released in 2012 and covered half of
the remaining gaps via usage of new Sanger and Roche
454 NGS technology
• V5.0 integrated new expression data with total of 1.03
billion ESTs
• New assembly have only 3.6% gaps and 37 unanchored
scaffolds.
45
Ref: (Blaby et al. 2014)

46. 46
Ref: (Blaby et al. 2014)
GENE MODELS

47. 47
Ref: (Blaby et al. 2014)

48. SYNTHETIC BIOLOGY
48
Ref: (Jagadevan et al. 2018)

49. GENETIC ENGINEERING
49
Ref: (Jagadevan et al. 2018)
• Overexpression of acetyl-
CoA carboxylase (ACC)
increase TAG content
• Inactivation of the
peroxisomal long-chain
acylCoA synthetase (LACS)
isozymes inhibits lipid
breakdown and increase oil
content in A. Thaliana
• Overexpression of glycerol-3-
phosphate acyltransferase
(GPAT), lysophosphatidic
acid acyltransferase (LPAT),
or diacylglycerol
acyltransferase (DAGAT)
increase lipid production

50. ACETYL-COA CARBOXYLASE
50
Ref: https://phytozome.jgi.doe.gov/pz/portal.html#!gene?search=1&detail=1&method=4614&searchText=transcriptid:30773743

51. ALGAGEM
• AlgaGEM - a genome-scale metabolic reconstruction(GEM) of
algae based on the Chlamydomonas reinhardtii genome
• It is in silico GEM model that can be used to simulate C. reinhardtii
metabolic pathways in order to predict lipid production
• Model simulations are carried out using MATLAB using COBRA
Toolbox
51
Ref (de Oliveira Dal’Molin et al. 2011)

52. 52
Ref (de Oliveira Dal’Molin et al. 2011)

53. 53
Ref (de Oliveira Dal’Molin et al. 2011)

54. 54
Ref (de Oliveira Dal’Molin et al. 2011)

55. 55
Ref (de Oliveira Dal’Molin et al. 2011)

56. CONCLUSION
• Algae based biofuels promise sustainable carbon neutral
green energy future
• Current large-scale production technology is not feasible
and require extensive research
• R&D of algal biofuels require multidisciplinary approach
that include but not limited to biotechnology,
bioengineering, genomics and other –omics based fields,
process engineering, etc.
• Frameworks such as AlgaGEM combined with metabolic
patway engineering can significantly promote algae based
biofuels
56

57. REFERENCES
Blaby, I. K., Blaby-Haas, C. E., Tourasse, N., Hom, E. F., Lopez, D., Aksoy, M., . . . Prochnik, S. (2014). The Chlamydomonas genome
project: a decade on. Trends Plant Sci, 19(10), 672-680. doi:10.1016/j.tplants.2014.05.008
De Bhowmick, G., Sarmah, A. K., & Sen, R. (2019). Zero-waste algal biorefinery for bioenergy and biochar: A green leap towards
achieving energy and environmental sustainability. Sci Total Environ, 650(Pt 2), 2467-2482. doi:10.1016/j.scitotenv.2018.10.002
de Oliveira Dal’Molin, C. G., Quek, L.-E., Palfreyman, R. W., & Nielsen, L. K. (2011). AlgaGEM–a genome-scale metabolic
reconstruction of algae based on the Chlamydomonas reinhardtii genome. Paper presented at the BMC genomics.
Iwai, M., Hori, K., Sasaki-Sekimoto, Y., Shimojima, M., & Ohta, H. (2015). Manipulation of oil synthesis in Nannochloropsis strain
NIES-2145 with a phosphorus starvation-inducible promoter from Chlamydomonas reinhardtii. Front Microbiol, 6, 912.
doi:10.3389/fmicb.2015.00912
Jagadevan, S., Banerjee, A., Banerjee, C., Guria, C., Tiwari, R., Baweja, M., & Shukla, P. (2018). Recent developments in synthetic
biology and metabolic engineering in microalgae towards biofuel production. Biotechnol Biofuels, 11, 185. doi:10.1186/s13068-018-
1181-1
Lam, M. K., & Lee, K. T. (2012). Microalgae biofuels: A critical review of issues, problems and the way forward. Biotechnol Adv, 30(3),
673-690. doi:10.1016/j.biotechadv.2011.11.008
Merchant, S. S., Prochnik, S. E., Vallon, O., Harris, E. H., Karpowicz, S. J., Witman, G. B., . . . Maréchal-Drouard, L. (2007). The
Chlamydomonas genome reveals the evolution of key animal and plant functions. Science, 318(5848), 245-250.
Radakovits, R., Jinkerson, R. E., Darzins, A., & Posewitz, M. C. (2010). Genetic engineering of algae for enhanced biofuel production.
Eukaryot Cell, 9(4), 486-501. doi:10.1128/EC.00364-09
Rastogi, R. P., Pandey, A., Larroche, C., & Madamwar, D. (2017). Algal Green Energy–R&D and technological perspectives for
biodiesel production. Renewable and Sustainable Energy Reviews.
Rodionova, M. V., Poudyal, R. S., Tiwari, I., Voloshin, R. A., Zharmukhamedov, S. K., Nam, H. G., . . . Allakhverdiev, S. I. (2017). Biofuel
production: challenges and opportunities. international journal of hydrogen energy, 42(12), 8450-8461.
Chen, H., Zhou, D., Luo, G., Zhang, S., & Chen, J. (2015). Macroalgae for biofuels production: progress and perspectives. Renewable
and Sustainable Energy Reviews, 47, 427-437.
Suali, E., & Sarbatly, R. (2012). Conversion of microalgae to biofuel. Renewable and Sustainable Energy Reviews, 16(6), 4316-4342.
Suganya, T., Varman, M., Masjuki, H., & Renganathan, S. (2016). Macroalgae and microalgae as a potential source for commercial
applications along with biofuels production: a biorefinery approach. Renewable and Sustainable Energy Reviews, 55, 909-941
Hallmann, A. (2015). Algae biotechnology–green cell-factories on the rise. Current Biotechnology, 4(4), 389-415.
Leite, G., & Hallenbeck, P. (2011). 13 - Algal Oil. In (pp. 231-239).
Luque, R., Herrero-Davila, L., Campelo, J. M., Clark, J. H., Hidalgo, J. M., Luna, D., . . . Romero, A. A. (2008). Biofuels: a technological
perspective. Energy & Environmental Science, 1(5), 542-564.
Shen, Y., Cui, Y., & Yuan, W. (2013). Flocculation optimization of microalga Nannochloropsis oculata. Applied biochemistry and
biotechnology, 169(7), 2049-2063.
57

58. THANKS FOR LISTENING
Q/A
58