ami project_ biofuel group

7/29/2019 AMI Project_ Biofuel Group

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ANR-GUI-AAP-5 Doc Scientifique 2012 1/6

ImportantThis document, appendices excluded, must not exceed 30 pages, body of text in font size 11. This

constitutes an acceptability criterion for the project proposal. Project proposals that do not satisfy

the acceptability criteria will not be evaluated. For transnational projects this document shall be

written in English

Project Acronym AMI (Artificial Microalgae Intelligence)

Project title (in

French)

Production en masse de biodiesel: ingnierie mtabolique applique

loptimisation de la voie de biosynthse des TryAcylGlycerols chez lesmicro-algues.

Project title (in

English)

Biodiesel mass production: metabolic engineering applied to

TriAcylGlycerols biosynthesis pathway optimization in microalgae.

Multidisciplinary

project

YES

NO

Type of research Basic Research

Industrial Research

Total funding

requested500000

Project duration 36 months


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1. CONTEXT, POSITION AND OBJECTIVES OF THE PROPOSAL1.1. CONTEXT, SCIENTIFIC, SOCIAL AND ECONOMIC ISSUESClimate changes due to GreenHouse Gases (GHG) are an important contemporary issue. Different

large-scale initiatives try to address this global problem, such as the Kyoto Protocol which was

ratified by 191 countries (1). The main reason for GHG emissions is the consumption of fossil fuels;

indeed 23% of the carbon dioxide generation on earth is due to traffic emissions and 41% is due to

electricity and heating systems (2). Moreover, a recent study estimated that fossil fuels reserves,

excepting coal, will be fully depleted by 2043 (3). All those facts highlight the importance of

developing alternative sources of energy. Biofuels, especially the latest generations, address thisenergy problem since they are a renewable and much less polluting source of energy. Over the past

five years biofuel production has been in constant progress; the production increase per year was

17% for bioethanol and 27% for biodiesel (4). Additionally, it has been estimated that biofuels will

represent 38% of the worlds direct fuel use by 2050 (5). In the coming years biofuels will benefit to

society in an economically and environmentally sustainable way: avoiding long oil piping

transportation and oil crisis that depend on several geopolitical conditions, generating zero CO2

cycles and also creating millions of new jobs all over the world (4,5,6,7). One can note that, among

the renewable energies, it is already the sector with the highest number of employees (4).

Biofuel promotion programs were first launched about 30 years ago by Brazil and USA in responseto the 1970s oil crises and commercial biofuels have been produced for the last 15 years (7). The first

generation consisted on using different food stocks to produce mainly bioethanol, which has been

having a negative impact on food prices (8). The second generation of biofuels is intended to

consume lignocellulosic biomass to produce biofuels. The main drawback of this technology is the

actual poor yield (8). The third generation of biofuels appeared during the second part of the 2000

decade with new researches on photosynthetic organisms, mainly cyanobacteria and microalgae, to

produce biodiesel. Microalgae present many advantages: they are solar energy driven, have high

lipid content (they can reach up to 70% of dry weight against 5% for classical crop), a high growth

rate, limited nutrient requirements, and abilities to survive in some types of waste water and to fix

carbon dioxide (6, 9, 8). Furthermore, they do not need fertilizers and can be cultured in open pondsin very different climate conditions, so the biodiesel production could be distributed all over the

world. Moreover biodiesel is a very promising biofuel. It has the advantage to produce much more

energy than ethanol (90% of gasoline calorific capacity versus 70% for ethanol) and to have similar

properties with comparable fossil diesels with an even higher cetane value and a better lubricity (7).

Indeed it is the second most produced biofuel after ethanol but the demand is rising for biodiesel

and going down for ethanol (10). The fourth generation biofuels offer even better perspectives as

metabolic engineering is going to boost micro-organisms capabilities by optimizing their metabolic

pathways towards metabolites synthesis among others (8).

Triacylglycerols (TAGs) produce biodiesel by a transesterification reaction. The most importantroute to triacylglycerol biosynthesis is the Kennedy pathway by means of which more than 70% of


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triacylglycerols (TAG) are produced. Fatty acids (FA) are directly linked to TAG synthesis becausethey are used to produce Acetyl-CoA (A-CoA), which is then in a few steps converted into TAG. On

one hand decreasing FA degradation will increase their accumulation. On the other hand, we want

to optimize the anabolism of TAG. It is possible to overexpress factors involved in the

biotransformations happening during the A-CoA to TAG conversion. Adopting such an

experimental approach would in the same time avoid degradation of FA and optimize their

conversion into TAG by increasing the enzyme level. This procedure is explained by the following

figure where we can observe the complete metabolic pathway and its simplified version:

1.2. OBJECTIVES, ORIGINALITY AND INNOVATIVE NATURE OF THE PROJECTThis research follows two main goals; the first one is to implement recent approaches that have been

successfully carried out in terrestrial plants for optimized lipids production to algae cells

metabolism. In this sense, future research will profit from the knowledge gained in this project for

further biofuel generation optimization. The second aim is to achieve an improved production of

lipid in microalgae. That is to make a strain more productive than the strain with the highest yield,

which is 140KLiter of oil/ha year (11). The biodiesel yield increase will occur thanks to genetic

modifications coupled to optimum growth conditions for the created mutants cultivated in novelphotobioreactors (12). So far no relevant work has been published in lipid biosynthesis metabolism

in genetically modified microalgae due to the reduced number of genetic tools that are available to

these organisms (8, 14, 13). Nevertheless, recent improvements in Molecular Biology techniques for

photosynthetic model make it now possible to transform it with different novel experimental

approaches. For this project, we choose to use Chlamydomonas Reinhardtii because it is the most

well-known microalgae organism, one of the few to have its nuclear genome sequenced, and it has

been the subject of some metabolic modelling effort by the scientific community (14, 2, 15).

The strategies that are going to be followed in this research will mainly focus on the optimization of

the expression and the efficiency of one enzyme of the Kennedy pathway that has been reported as

the bottleneck for the final lipids biosynthesis: the diacylglycerol O-acyltransferase (DGAT) (14, 16).


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There are two isozymes and both will be studied; DGAT1 that transforms diglycerol lipids intotriacylglycerides (TAG), the pathways final product, and DGAT2 that directly converts

monoglycerides into TAG at a lower rate but in just one step, therefore avoiding other intermediate

steps from the Kennedy pathway (14, 16). Additionally further research will be done on beta-

oxidase inhibition. Finally, cells are going to be cultured under strict growth conditions in second

generation microscale photobioreactors to study optimal nutrient intake, CO2 fluxes and light

regimen for maximal biomass growth of the created mutant strains (12, 6). The combination of the

bioprocess and the genetic approaches will together contribute to the optimal production of lipids.

These will finally be transformed to biodiesel through the classical transesterification step (7, 8).

In summary, this research is intended to transform C. Reinhardtii into a real cell factory on which

further R&D steps can be articulated, either by public or private institutions, to achieve a higherbiodiesel production. All these efforts could lead to completely profitable biodiesel generations in

the course of this decade if the oil prices continue to increase as expected. Such a green technology

would gradually reduce the dependency towards fossil origin energy sources therefore contributing

to a more sustainable world.

2. SCIENTIFIC AND TECHNICAL PROGRAMME,PROJECT ORGANISATION2.1. SCIENTIFIC PROGRAMME, PROJECT STRUCTUREThe idea that genes involved in TAG assembly are of importance for total seed oil production is

further supported by several other studies in which overexpression of TAG assembly genes resultedin increase in seed oil content. For example, overexpression of glycerol-3-phosphate acyltransferase,

lysophosphatidic acid acyltransferase, or diacylglycerol acyltransferase all result in significant

increases in plant lipid production.

Among all of these enzymes, the one that catalyzes the transformation of diglycerides into the final

TGA (DAGAT) is considered to have the slowest kinetics mechanism [ref and one expression more]

and so most of the latest efforts have been directed towards different solutions for this enzymatic

reaction. There are two types of proteins in DGAT: DGAT-1 and DGAT-2. In order to improve the

enzyme efficiency in DAG to TAG catalysis, we may consider a couple of approaches. On one hand

DGAT-1 could be optimized for catalysis if some mutagenesis pipeline were set up. For example theenzyme could be submitted to directed evolution or even insertion mutations. We also may

consider codon optimization such as a clue for our aim. On the other hand DGAT-2 is promiscuous

to catalyze the complete biotransformation from mono-acylglycerides to tri-acylglycerides in a

single step.

Additionally, a complementary strategy to increase lipid accumulation is to decrease lipid

catabolism. Genes involved in oxidation of fatty acids (-oxidases), have been partially inactivated

resulting in increased cellular lipid content either through random mutagenesis or through the use

of RNA silencing. One challenge is that there are different enzymes with overlapping functions for

many of the steps of oxidation, making it difficult to completely abolish these functions and sostrategies proposed for yeast have to be adapted. The catabolism of fatty acids through beta-


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oxidation occurs exclusively in peroxisomes and here fatty acyl-CoA oxidase is the rate-limiting

enzyme in this system. Thus, dysfunction of this enzyme leads to the inactivation of the beta-

oxidation process will result in the accumulation of cellular fatty acids. To elucidate the molecular

mechanism governing the action of the oxidases, we have to isolate a yeastmutant, B-l that exhibitsa reduced acyl-CoA oxidase activity. Following mutagenesis of B-l by UV irradiation, a mutant,

YTSSl, which secretes free fatty acids, should be isolated. Then, we have to screen the genes that

complement mutation. We can search for similar genes in algae by using homology modeling since

extensive studies of fatty acid catabolism were not done in algae.

One might consider the computational research as a starting point for experimental studies.

Computational biology would be applied here such as a modelling approach in order to reconstruct

the lipids metabolic pathway, so integrating different omics levels after raw data analysis. Theobtained model should be adjusted by simulations and concordance between reality and

computations, using well studied bioinformatic tools such as flux balance or MOMA. Besides, the

computer scientist will have to build a mutagenesis pipeline involving structural studies, similarity

approaches and directed evolution. Steps of docking may also help for justifying the theoretical

approach. Finally this pipeline should generate mutant libraries submitted to a scoring algorithm

that would specify what the best candidates for experimental tests of DGAT are.

The main aim of putting the computational

studies in the beginning of the project is that it

will provide a reliable model in order to orient

and adjust further experimental studies. It willalso provide a mutagenesis pipeline necessary for

advanced experiments to the anabolism of TAGs.

Having recreated the metabolic pathways, the

mathematical model should be adjusted by the

experiments that would be run in parallel.

Experiments will begin during the first 6 months

to build the constructs that the experimental

researchers need in order to decrease the

catabolism of FAs and increase the anabolism of TAGs. This coupled approach will allow to get

initial data that would be used to improve the model itself. After, transcriptomic and proteomicstudies should be led for up to 18 months in order to experimentally justify the estimated

production outputs. Once the proteomics and transcriptomics results converge with the

experimental ones, some fluxomic studies should be carried out using the provided computational

tool to evaluate and improve the model. Hence, fluxomics should be tightly related to the

metabolomic studies necessary to evaluate the full engineering system.


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3. SCIENTIFIC JUSTIFICATION OF REQUESTED RESOURCES EquipmentFor the microalgae growth, we need to buy 2 photobioreactors of 400 mL, at the price of 20 K each.

Around 15 K per year should be budgeted for the everyday-use lab equipment. Overhead fees are

up to 10 % of the overall amount of money granted.

Staff- 1 Post-Doc in computational biology specialized in modelling and FBA with strong skills in

mutagenesis. If we consider 45 K/year, the 2 years contract would lead up to 90 K.

- 2 PhD for 3 years: the first one specialized in molecular biology experiments; the second onewith a biotechnological background for efficient usage of photobioreactors. The cost of 1 PhD is

around 35 K/year. 2 PhD for 3 years would therefore each cost 105 K.

TravelWe will assume that the Post-Doc scientist and the PhD will have to attend to respectively 3 and 2

conferences or symposium. The overall budget for travelling will be 7 K, assuming 1K per trip.

Other operating expensesThree publications should be done by PhD students and two by the Post-Doc. If we assume that one

article costs 1 K, this budget should be fixed to 5 K. Of course if the research shows good results,

some supplementary publications will be considered. Finally at the end of the project, if it is

successful, we would like to patent the research protoco l, which will cost up to 10 K. Additionally

40 K should be reserved for future works such as development and industrial applications.

Expenses summaryEquipment Staff Travel Other expenses Total

Final budget 130 K 300 K 7 K 55 K 492 K

4. REFERENCES1) Mario Molinaa et al. (2009, PNAS); Reducing abrupt climate change risk using the

2) Merchant et al. (2007, Science); "The Chlamydomonas Genome Reveals the Evolution of

3) Shafiee et al. (2008, Energy Policy); When will fossil fuel reserves be diminished?

4) Ghasemi et al. (2012, Applied Biochemistry and Microbiology); Microalgae biofuel potentials 5) le

B. Williams et al. (2010, Energy & Environmental Science); Microalgae as biodiesel &6) Ratha et al. (2012, Applied Biochemistry and Microbiology); Bioprospecting microalgae as

7) Govinda et al. (2011, Energy); how much hope should we have in biofuel

8) L et al. (2011, Energy Environ. Sci.); Metabolic engineering of algae for 4th generation...

9) Suali et al. (2012, Renewable and sustainable Energy Reviews); Conversion of microalgae

10) REN21 (2012, Renewable Energy Policy Network for the 21st century); Renewable 2012

11) Aguirre et al. (2012, Critical Reviews In Biotechnology); Engineering challenges in biodiesel

12) Fu et al. (2012, Journal of Biotechnology); Maximizing biomass productivity and cell

13) Larkum et al. (2012, Trends in Biotechnology); Selection, Breeding and engineering

14) Radakovits et al. (2012, Eukaryotic cell); Genetic Engineering of algae for enhanced

15) L. Beer et al. (2009, Current Opinion in Biotechnology); Engineering algae for16) Ern Chen et al. (2012, Journal of Biotechnology); A look at DGATs in algae

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