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Risk assessment on the use of Genetically Modified Organisms (GMOs) for
biofuel production
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Agriculture, Food and Analytical Bacteriology
Risk assessment on the use of Genetically Modified Organisms (GMOs)
for biofuel production
A. Limayem1
1
Department of Cell Biology, Microbiology and Molecular Biology, University of South Florida,
4202 East Fowler Avenue, Tampa, FL 33620, USA
ABSTRACT
In recent years concerns about energy security and climate change have sparked government interest in
biofuels from crops. However, water and land availability for biofuel production could become major obstacles, if effective conservation practices are not implemented. In an effort to increase crop productivity with
minimal use of natural resources, genetic manipulations of corn plants are conducted in the U.S. and worldwide to convey pest and herb resistance. Moreover, genetically engineered microorganisms have been
developed to render biomass conversion to fuels cost competitive. This review summarizes the evolution
of biotechnology in agricultural systems and its most current use in biofuel production. This includes the
review of the recent genetically engineered microorganisms (GMOs) as well as the nanotechnology used
to biofuel yield optimization. Potential bottlenecks pertaining to GMOs dispersal from biofuel production
are thoroughly addressed. Novel point-of-care approaches exclusively adopted by the federal agencies
and arising from systemic core modeling such as biotechnology risk assessment are discussed. Optimizing
these tools by revealing a proficient model engineering practices toward achieving greater GMO traceability, biosafety and operational performance remains the option of choice to intervention.
Keywords: Biotechnology, Biofuel, Biomass, Genetically modified organisms (GMOs), Risk assessment modeling
Agric. Food Anal. Bacteriol. 5: xx-xx, 2015
INTRODUCTION
With rising concerns about energy security, climate change, and sustainable development, agriculture-based biofuels have gained considerable atCorrespondence: Alya Limayem, alimayem@usf.edu
Tel: +1 -813-974-7404
tention from governments, investors, and scientists
in the U.S. and worldwide (Youngquist, 1999). The
passage in the U.S. of the Energy Policy Act of 2005
and the Energy Independence and Security Act of
2007 (Bothast and Schlicher, 2005; Brookes 2009) has
spurred growth in biofuel production from 1.6 billion
gallons per year (6 billion liters) in 2000 to 13.3 billion
gallons (50 billion liters) in 2014 (RFA, 2014).
Agric. Food Anal. Bacteriol. • AFABjournal.com • Vol. 5, Issue 3 - 2015
XX
The continuous expansion of the biofuels industry
at such a fast pace has prompted substantial growth
in modern biotechnology (James, 2011; Sanchez
and Cardona, 2008). To date, agro-biotechnology involves mainly the use of genetically modified organisms (GMOs), including both transgenic crops and
genetically transformed microorganisms (Holmes,
2010). GMO manipulations offer economic advantages to investors by maximizing product yield from
limited land and water use (Ramasamy et al., 2007).
In the last decade, the U.S. has become the world
leader in the cultivation of genetically modified (Ladisch et al., 2010) crops, involving primarily corn and
soybeans. In 2010, Brazil achieved the world’s sec-
provide a qualitative and quantitative risk estimate
to biotechnology investors and policy makers. These
approaches assess the probability of occurrence and
the severity of effects from exposure to GM living
organisms. While a temperature of 500°F would be
sufficient to inactivate the DNA from biofuel downstream operations (Gryson, 2010; Krohn et al., 2011),
there is an imperative need to generate a comprehensive insight of all the operation steps that determine the risk. The biotechnology risk assessment is a
comprehensive approach that should emerge as the
method of choice to provide greater predictability
of GMO dispersal during bioprocessing operations
(Flory et al., 2012).
ond largest increase in soybean cultivation, reaching a total area of approximately 23 million hectares
(Cerdeira et al., 2010). In contrast, in Europe mandatory labeling and public concerns have so far
substantially limited GM investments (Carter and
Gruère, 2003). Currently, China is emerging in biotechnology, particularly in the cultivation of GM rice
and cotton, followed by India in development of GM
fiber, primarily cotton (Huang et al. 2002).
Aside from transgenic plants, biofuel production
from corn and lignocellulosic feedstocks also involves the use of GM fermentative microorganisms
in various parts of the technologies (Phillips, 2008).
However, as investment in agricultural biotechnology and in the biofuels industry expands, concerns
about the risks of adverse health effects from GMOs
have also increased. Within the last decade there
have been a number of different groups calling for
protection of the ecosystem and of biodiversity from
GMO effects. Researchers indicate that adverse outcomes of GMOs could present a real risk to the environment from irreversible and unforeseen dissemination (Ho et al., 1999). Although clear evidence of
adverse effects from GMO applications is currently
lacking, the adoption of a scientifically sound method, such as risk assessment, would help develop
This review encompasses the advancement of
agricultural biotechnology in the U.S. and worldwide.
It provides a summary on the most current GMOs
used in biofuel production in the U.S. This review
also examines potential obstacles related to GMOs
dissemination. Future directions describing systemic
core modeling such as Biotechnology Risk Assessment approach are suggested to maintain biosafety
and bioprocessing operational performance.
biosafety measures through a comprehensive model
that could subside public concern and ensure environmental safety (Brookes, 2009). Systemic methods,
including Biotechnology Risk Assessment, are gaining attention as potential statistical approaches that
isms. From this perspective, the molecular explanation of life arose at the Rockefeller Institute of New
York in the late 1930s as a novel discipline named
“molecular biology” by Warren Weaver (Sarkar,
1991). Between 1926 and 1960 there were consid-
XX
HISTORICAL AND EMERGING TRENDS
Background
Although the public has become aware of genetic alterations rather recently, modifying genomes of
plants via breeding methods has been carried out
over a long period of time (Phillips, 2008). At the end
of the nineteenth century physiological genetics
started to emerge over the classical theory of chromosome heredity, along with the segregation and
inheritance law of Mendel (Burian and Gayon, 1999).
At that time, several disciplines, such as physics, biology and virology, started to interact in an effort to
achieve a scientific understanding of living organ-
Agric. Food Anal. Bacteriol. • AFABjournal.com • Vol. 5, Issue 3 - 2015
erable advances in physiological genetics that were
devoted to explaining the gene and protein relationship from the Drosophila fly and Neurospora fungus
(Beadle and Tatum, 1941) up to the new model organism, a bacteriophage (T1 through T7), described
by Delbrück and his group at the beginning of
1940 (Delbrück, 1949; Machine, 1984). More modern genetic engineering approaches that involve
precise manipulation of genomic vectors (plasmid
constructs and recombinant DNA) in bacteria and
mice began in 1972 and 1974, respectively ( Arnold,
2009; Cohen et al., 1972; Jaenisch and Mintz, 1974).
In the early 1980s the development of insulin-producing microorganisms (Crea et al., 1978; Whitman
along with the employed major GMO techniques
and gene sources used, are summarized in Table 1.
Currently, both herbicide tolerance and insect resistance are among the most prevalent GMO traits that
are used in agronomical biotechnology (Cerdeira et
al. 2010; Edmeades, 2013; James, 2011). In 2006 insect- and herbicide-resistant GM plant cultivations,
mainly soybean and corn, reached 101 million hectares across 22 countries (James, 2011). The most
common herbicide tolerance is achieved by the
insertion of glyphosate and glufosinate resistance
genes, such as the 5-enolpyruvylshikimate-3-phosphate synthetase (EPSPS) gene, into the target plant
(Powles and Yu, 2010). On the other hand, insect re-
et al., 1996) was commercialized in the medical field.
Then, the rapid evolution of agricultural biotechnology by the end of the twentieth century gave rise to
genetically modified crops first for food and later for
biofuel production (James, 2011).
Agricultural biotechnology approaches have
been widely used to ensure biological and economic
benefits from the extensive cultivation of GM crops
(Brookes, 2007). Increasing yields associated with
less land erosion and water use are among the most
desirable benefits of transgenic plants (Dunn et al.,
2013; Mumm et al., 2014; Ramasamy et al., 2007).
Genetically engineered corn has been grown in the
U.S. since 1997 (James, 2011). It has been reported
that 36% of corn planted around the world is genetically modified with 86% of it been planted in the U.S.
(Boryan et al., 2011; Edmeades, 2013).
sistance is conferred by genes that originate from
the well-known Bacillus thuringiensis strain, whose
toxic crystal protein causes host cell death (Shen
et al., 2013). As a result, plants transformed by B.
thuringiensis genes for insect resistance are called
Bt crops (Entwistle et al., 1993). The Bt gene can be
incorporated into the plant cell via various transformation techniques.
ADVANCEMENTS IN AGRO-BIOTECHNOLOGY
Currently, there are almost 150 million hectares of
GM crops planted in 25 countries around the world.
The U.S. alone grows almost 50% of the world’s
transgenic plants (soybean and corn) with approximately 67 million hectares, followed by Brazil and Argentina that account for approximately 25.5 and 23
Although research and development in gene
transfer technology has led to enhancements in cell
transformation, genetic trait isolation (Feltus and
Vandenbrink, 2012) has also achieved considerable
progress, leading to greater insect resistance and
herbicide-tolerance in biofuel and food crop. The Bt
protein is variably pathogenic, meaning that it impacts specific species via a specific toxin receptor interaction, but not others lacking the receptor (Shen
et al., 2013). During the last decade, B. thuringiensis strains including the Cry1A and Cry1B delta
toxins were known for their effects on specific type
of strains such as, Lepidoptera and Diptera insects
million hectares, respectively (Cerdeira et al., 2010).
Transgenic crops have reportedly helped U.S. farmers increase their product yield by 30% over the last
decade (Erickson and Winters, 2012).
The most prevalent transgenic plants in the world,
(Carpenter et al., 2002). Currently, the pilot studies
have demonstrated that genetically modified E. coli
vectors are engineered so as to contain a wide range
of Bt toxins in the same strain, thus optimizing Bt
utility to convey greater stability, delivery, and ver-
Current trends
Agric. Food Anal. Bacteriol. • AFABjournal.com • Vol. 5, Issue 3 - 2015
XX
Table 1. Most prevalent transgenic plants and GMO techniques used for biofuel production.
(Brookes, 2007; Phillips 2008; Piekarowicz, 1978; Schell et al., 2007; Uchtmann and Nelson, 2000)
Plants
Corn
Major components of the delivery system
Desired traits and sources
Transciption/translation genes and
sources
• Pest resistance: Cry genes
• Promoter from rice
from Bacillus thuringiensis (i.e.,
Cry 1A.105, Cry 2Ab2, Cry 1F
for aerial pests and Cry 3Bb1,
Cry 34Ab1 and Cry 35 Ab1 for
subsoil pest resistance)
• Terminator from Agrobacterium tumefaciens
• CTP peptide (EPSPS transporter) from
Selective
markers
• Antibiotic
resistance
marker (ARM),
beta-lactamase (bla)
corn itself and sunflower
• Resistance to herbicides:
EPSPS genes isolated from A.
tumefaciens CP4 (resistance to
glyphosate)
• Promoter from cauliflower mosaic virus,
Soy
CamV 35S
beans
• Terminator from Arabidopsis plant
ARM, neomycin
phosphotranspherase II
• CTP peptide (EPSPS transporter) from
• Resistance to herbicides:
Sugar
beet
EPSPS genes isolated from A.
tumefaciens CP4 for herbicide
resistance
Canola • Herbicide resistance: EPSPS
from A. tumefaciens CP4
• Increased content of laurate:
petunia plant
• Promoter from cauliflower mosaic virus,
Marker genes
NPTII (neomycin/kanamycin
• 3’nos terminator from A. tumefaciens
phosphotrans• Tn 5 terminator from bar from Streptomy- ferase) from
ces hygroscopicus along with 3’ocs and
microbial trans3’g7 controlled by bidirectional TR1/2
poson
promoter from A. tumefaciens
CamV 35S
• Promoter from figwort mosaic virus
• Terminator from pea
ARM, streptomyin
GOX from Ochrobactrum
anthorpi strain LBAA; ACP
thiosterase genes from California tree
Sugar
cane
• Resistance to some insecticides: Cry genes from B.
thuringiensis
• Increased sugar content in the
• Promoter from cauliflower mosaic virus,
CamV 35S
• Terminator, nopaline synthase (nos) from
A. tumafaciens
Selective markers, kanamycin
(Kan) or hygromycin (Hyg)
plant: Gene BetA from Escherichia coli (EcBetA) or Rhizobium meliloti (RmBetaA)
Rice
• Drought tolerant
• Resistance to insects: CryIA (b)
and CryIA (c) from B. thuringiens
• Promoter from cauliflower mosaic virus,
CamV 35S
• Nopaline synthase promoter (Pnos)
• NT, 3’ terminator
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Agric. Food Anal. Bacteriol. • AFABjournal.com • Vol. 5, Issue 3 - 2015
ARM, neomycin
phosphotranspherase II (NPTII,
hygromycin
(Hyg)
Figure 1. Generalized method for creating transgenic plants using the A. tumefaciens delivery
system: (1) Sources of genes; (2) Delivery system (e.g. E. coli plasmid); (3) Mediated transformation of plant with A. tumefaciens.
(1)
Trait, promoter, and terminator
genes from soil or other
microorganisms and plants
(2)
Desired traits 1
Promoter 5
Sel. Marker 6
TT 7
(3)
Agrobacterium
tumefaciens
plasmid
OriT 3
Oriv 4
Transgenic plants
Amp 2
1
Desired “traits”: (e.g. EPSPS gene isolated from A. tumefaciens; Cry1Ab gene from Bacillus thuringiensis)
2
Amp: Ampicillin marker gene for selecting transformation in A. tumefaciens
3
OriT: Transfer origin for conjugal transfer of the plasmid to recipient cell
4
OriV: Origin of replication
5
Promoter: Promoter gene (e.g. gene from cauliflower mosaic virus, such as CamV 35S, used for soybean
vectors)
6
Sel. Marker: Selection marker (e.g kanamycin resistance or bla for beta lactamase or NPTII for neomycin/
kanamycin phosphotransferase) for selecting transformation in plants
7
TT: Termination of transcription (e.g. nopaline synthase, nos, from Arabidopsis plant)
Agric. Food Anal. Bacteriol. • AFABjournal.com • Vol. 5, Issue 3 - 2015
XX
satility to cope with different hosts and to control a
wide range of insects (Feltus and Vandenbrink, 2012;
Shen et al., 2013). Biolistic injection of constructs
containing Bt, as well as the EPSPS gene, is now the
most common technique to protect plants from insects and herbicides (FAO, 2009). In addition to its
herbicide tolerance ability, the EPSPS gene is also
used as a selection marker in the plant, thus conferring both resistance and selection to the target
plant. It should be noted that along with insect- and
herbicide-resistance traits that are used to increase
plant yield performance, there is an increasing interest in enhancing the nutritional value of GM plants,
as well as in developing cold- and drought-tolerance
sect resistance Bt genes (e.g. Cry1A), are most commonly isolated from soil microorganisms (Agrobacterium tumefaciens and B. thuringiensis) or plants.
E. coli plasmids constitute an ideal platform and
cloning vector for gene transcription and translation
to proteins, with most such genes originating from
plants and microorganisms (Abbott, et al., 1998).
They include promoters that enable target gene
transcription (e.g. cauliflower mosaic virus (CamV
35S) and nopaline synthase (nos) from Arabidopsis plant) and provide termination signals (James,
2011; Nida et al., 1996). In addition, a selective gene
marker is often incorporated to aid in the detection
or tracking of the DNA delivery package within the
crop variants via genetic modification. Perhaps the
best-known example thus far is the drought-resistant
gene BetA from E. coli (EcBetA) and Rhizobium meliloti (RmBetA), which have been demonstrated to be
beneficial to plants without adverse effects (Kempken and Jung, 2009).
There are a substantial number of transformation
techniques that have been used till date, ranging
from the indirect delivery-system-based Agrobacterium method to the direct transfer Agrobacterium
microprojectile bombardment (biolistic) method
( FAO, 2009; Klein et al., 1987; Koziel et al., 1993).
Typically, the delivery-system-based Agrobacterium
method has been widely used to form a transgenic plant. This technique, also called binary-vector
Agrobacterium, is summarized in Figure 1. It requires
first the isolation of the gene of interest for its “desired traits” before its insertion into a delivery vector
(plasmid) to form recombinant DNA (rDNA) (Berg
and Mertz, 2010; Kiermer, 2007). The most common
transfer and cloning vectors used in medical and
agricultural biotechnology are bacterial plasmids
transformed cells. This way only the transformed
cells carrying the selective marker will be regenerated and transferred to the mediated transformation
strain.
The causative agent of crown gall disease A. tumefaciens has been used for its ability to infect plants and
transfer genes into a callus (embryonic plant tissue)
via insertion of its tumor-inducing Ti plasmid (Gelvin,
2003; Nester, 2014). Initially, the desired gene is transferred into the Ti plasmid through DNA recombination. This mechanism is enabled by the cleavage of
the plasmid at specific sites for gene insertion, which
is carried out with the use of endonuclease restriction
enzymes (Piekarowicz et al., 1978). The same enzymes
are also used to cleave the host cell DNA before ligation via a DNA-joining enzyme, ligase (Zimmerman
et al., 1967). Finally, the transformed Ti plasmid (with
its tumor-inducing mechanism deactivated) is injected into plant embryos (callus). Successful transfer of
the desired trait gene to the plant chromosome is
detected via the selective marker that was originally
incorporated in the plasmid vector. Thus, transgenic
plant regeneration is ensured by successfully injecting trait genes into the plant chromosome, which
subsequently propagates as the plant grows. Molecular techniques including Polymerase Chain Reaction
from Escherichia coli, selected primarily for their
ability to generate numerous copies of the desired
gene (James, 2011). The desired trait genes, such as
the herbicide tolerance gene EPSPS (Marketed as
Roundup Ready®) (Powles and Yu, 2010) or the in-
(PCR), Southern hybridization, and DNA sequencing
confirm gene transfer and its inheritance by the target plant (Lupien, 2000). The PCR technique traces
the inserted gene in the plant through DNA amplification, confirming gene inheritance by the plant.
Gene transfer methods and mechanisms in crops
XX
Agric. Food Anal. Bacteriol. • AFABjournal.com • Vol. 5, Issue 3 - 2015
Figure 2. Ethanol and major co-product manufacturing from GM corn using the wet-milling and
dry-milling processes. Existing and potential GMO flows are depicted with black arrows. Potential gene dissemination through co-products is marked with an asterisk (*).
Desired trait genes
E. coli plasmids
Agrobacterium
GM corn
Wet-milling Process
Dry-milling Process
Cleaning
Steeping (Degermination)
*
*
*
Enzymes
Milling
Cyclone Separation
Corn
Oil
*
Cleaning
Grinding
Cooking
Liquefaction/Saccharification
Yeast
Corn Gluten
Feed
Grinding
Starch/Gluten Separation
Corn Gluten
Meal
Centrifugation
Dextrin
Washing/Filtering
Acid/Cooking of Starch
Fermentation
CO2
Distillation/Dehydration
Ethanol
Enzymes
Centrifugation
Liquefaction/Saccharification
Yeast
Fermentation
CO2
Distillation/Dehydration
Ethanol
Residue
*
Drying
Evaporation
Distillers Dry
Grains
Distillers
Solubles
Distillers Dry Grains
with Solubles (DDGS)
(animal feed)
*
Agric. Food Anal. Bacteriol. • AFABjournal.com • Vol. 5, Issue 3 - 2015
XX
While the binary-vector Agrobacterium technique
requires a vector (plasmid) to transfer the desired
trait, direct gene transfer methods do not require
a delivery system to enable gene transfer to the recipient organism. Currently, there are several direct
gene transfer methods that include primarily Agrobacterium microprojectile bombardment in addition
to chemical mediation and electroporation, as well
as microinjection (Kempken and Jung, 2009; Klein
et al., 1987). However, Agrobacterium-mediated recombination is often preferred over direct methods
because it causes less damage to the plant tissue
(Koziel et al., 1993). Direct techniques have been
extensively described by the Food and Agriculture
cesses and the generated co-products are illustrated
in Figure 2. Wet milling separates corn into several
components, such as oil, gluten meal, starch, and fiber, producing livestock co-products and corn oil in
addition to ethanol from starch, but also increasing
the chances of GMO release into the environment.
The more popular dry milling process requires less
capital per gallon of ethanol produced and involves
fewer steps (Bothast and Schlicher, 2005). The solid
residue from the ethanol distillation column is centrifuged and dried to form distiller’s dry grain with
solubles (DDGS), a major source of animal feed that
is vulnerable to GMO concerns.
Although the corn ethanol industry has expe-
Organization (FAO, 2009).
Aside from modification of crops for higher plant
productivity and resilience, considerable research
has also been directed towards engineering enzymeproducing and fermentative microorganisms for wider sugar utilization and increased biofuel yield.
rienced significant growth in the last 15 years, increasing societal and economic concerns regarding
food-based biofuels have shifted researchers’ focus
towards non-food biomass sources, such as cellulosic materials. Such biofuels, termed advanced or
second-generation, could help significantly the U.S.
reach its Renewable Fuel Standard (RFS) annual target of 36 billion gallons of biofuels by 2022 (Corredor et al., 2007).
CROP-BASED BIOFUEL PRODUCTION IN
THE U.S.
Biomass-derived biofuels
Corn-based biofuels
Biofuels have gained significant attention in the
last decade thanks to benefits they bring to energy security, lower carbon emissions, and cleaner air
(Sticklen, 2008). Among several countries around the
world that have invested in the biofuel sector, the
U.S. is the leader in ethanol production with approximately 70% of the total world production, followed
by Brazil (RFA, 2015). In the U.S. corn is the primary
feedstock for ethanol production, which reached
13.3 billion gallons (50 billion liters) in 2014 (RFA,
2015). Among the 29 ethanol-producing States, the
top ones are located in the U.S. Midwest “corn belt”
(James, 2011).
Lignocellulosic feedstocks are the most prevalent
biofuel resources worldwide in the form of agricultural residues, forestry residues, energy crops (e.g.
Miscanthus and switchgrass), and municipal solid
waste (MSW) (Pettersen, 1984). The U.S. is believed
to generate over one billion tons of cellulosic biomass annually that, if converted to ethanol, could
replace 30% of petroleum-derived gasoline by 2030
(Perlack et al., 2005). Another study estimated that
the same ethanol target could be reached if energy crops were cultivated on available federal land,
in addition to agricultural and forestry residues, to
reduce feedstock cost and make ethanol cost competitive (Khanna et al., 2011). Feedstocks for biofuel
According to the Renewable Fuels Association
(RFA) there are 204 operational corn-ethanol plants
in the U.S. using the wet milling (33%) or the dry milling (67%) technology (RFA, 2014). The major steps involved in these two corn ethanol manufacturing pro-
production have already been extensively reviewed
(Sticklen, 2008).
The major steps involved in cellulosic ethanol
production are illustrated in Figure 3. Pretreatment,
which intended to render recalcitrant biomass more
XX
Agric. Food Anal. Bacteriol. • AFABjournal.com • Vol. 5, Issue 3 - 2015
Figure 3. Ethanol and major co-product manufacturing from lignocellulosic biomass. Potential
GMO inputs and outputs are depicted with black arrows, whereas potential gene dissemination
through co-products is marked with an asterisk (*).
Lignocellulosic
biomass
Pretreatment
- Mechanical and/or
- Thermo-chemical and/or
- Biological
Potential GMO inputs
Cellulolytic enzymes
Liquefaction/Saccharification
CBP microorganisms
CO2
Fermentation
SSCF microorganisms
Ethanol
Lignin combustion
Distillation/Dehydration
Residue
*
White-rot fungi
(lignin degradation)
Power
Generation
Biological Decomposition
Fungal proteins
(animal feed)
*
Agric. Food Anal. Bacteriol. • AFABjournal.com • Vol. 5, Issue 3 - 2015
XX
Figure 4. Hypothetical modeling of GMOs risk exposure in lignocellulosic-based biofuel (CBP:
Consolidated Bioprocessing, SSCombF: Simultaneous Enzymatic Saccharification and Combined
Fermentation).
GMOs use
for CBP or
SSCombF
Cellulosic feedstocks
Bioprocessing:
Distillation/
Dehydration (500°F)
GMOs
Concentrations
GMOs
Prevalence
-Pretreatment
-Hydrolysis
-Fermentation
Potential
GMOs
spread
Biofuel and Co-products
Risk Characterization
amenable to further processing, accounts for almost
one third of the total operating cost (Mosier et al.,
2005). The high level of non-conventional pentose
sugars in cellulosic materials constitutes another
challenge for ethanol productivity (Wyman et al.,
2005). Furthermore, the use of high-cost enzymes in
the hydrolysis step is of particular financial concern
(Wyman et al., 2005; 2009). Residual lignin can serve
would be potential sources of GMOs that could affect the environment.
as a fuel for power generation (Ladisch et al., 2010)
or can be converted by fungal microorganisms, such
as the white rot fungus Basidiomycete, to fungal proteins for animal consumption (Zadrazel, 1976). The
distillation residue and any animal feed byproducts
Fermentative microorganisms can be engineered
with several important characteristics: wider sugar
substrate range, elimination of toxicity by cellulose
hydrolysates and fermentation products, and improvement of regulatory functions (Lee et al., 2008).
XX
CURRENT GENETICALLY ENGINEERED
MICROORGANISMS AND NANOTECHNOLOGY FOR BIOFUEL
Agric. Food Anal. Bacteriol. • AFABjournal.com • Vol. 5, Issue 3 - 2015
Overexpression of Inulinase Gene (INU)
Insertion of pdc and adhB genes from Z.
mobilis
Deletion of lactate dehydrogenase gene
(ldh)
Functional heterologous expression of an
engineered full length CipA from Clostridium thermocellum
Isolation of endogenous GAP promoter
and GAP terminator
•
•
•
•
•
Kluyveromyces marxianus
Escherichia coli
Clostridium thermocellum
Thermoanaerobacterium
saccharolyticum
Candida lignohabitans
•
•
•
•
•
(Yuan et al.,
2013)
(Currie et al.,
2013)
(Biswas et al.,
2014)
Expression of lactate dehydrogenase and cis(Bellasio et
aconitate decarboxylase resulted in stable and re- al., 2015)
producible production of lactic acid and itaconic
acid, respectively
The expression of a critical C. thermocellum cellulosomal component in T. saccharolyticum as a
step toward creating a thermophilic bacterium
capable of consolidated bioprocessing
-ncreasing in ethanol yield
The enzymes pyruvate decarboxylase and alcohol (Yang et al.,
dehydrogenase are overexpressed, resulting in
2014)
high ethanol production
Increasing ethanol production from Jerusalem
artichoke tubers by CBP
Reduction of cell growth and ethanol production
under osmotic, heat and ethanol stresses
•
Inactivation of gfo (ZMO0689) gene by
homologous recombination (fusion-PCRbased construction technique)
•
(Sootsuwan
et al., 2013,
Wang et al.,
2013)
Inactivation of gfo (ZMO0689) gene by
site-specific FLP recombinase
•
Zymomonas mobilis
Improves growth and ethanol production without
formation of sorbitol as a by-product in sucrose
medium
Increasing tolerance to inhibitors such as ethanol
•
•
Use glucose and D-xylose with high consumption Demeke et
rates and partial cofermentation in various ligno- al., 2013
cellulose hydrolysates with very high ethanol yield
•
The gene Clostridium phytofermentans
XylA, encoding D-xylose isomerase (XI),
and enzymes of the pentose phosphate
pathway was inserted
•
Saccharomyces cerevisiae
References
Expected Outcomes
Genetic Modification
Species
Table 2. The most promising GMOs for biofuel production in the U.S
Agric. Food Anal. Bacteriol. • AFABjournal.com • Vol. 5, Issue 3 - 2015
XX
Genetically engineered fermentative microorganisms, such as Saccharomyces cerevisiae (Almaida et
al., 2008; Toon et al., 1997) and Zymomonas mobilis
(He et al., 2014), along with Phanerochaete chrysosporium, Kluyveromyces marxianus and Clostridium
cellulolyticum, have been developed over the last 20
years with a potential to advance the commercialization of advanced biofuels. The promising microorganisms for genetic manipulation in lignocellulosebased biofuel systems are extensively reviewed by
Limayem and Ricke (Limayem and Ricke, 2012) and
the expected outcomes are summarized in Table 2.
Recent development in nanotechnology has been
also made to advance the biofuel system productivity through gene transformation (Tzfira and Citovsky,
2006; Ziemienowicz, 2001; Ziemienowicz et al. 2012).
A novel nano-complex method derived from Agrobacterium T-DNA has been developed by Pitzschke
and Hirt (Pitzschke and Hirt, 2010) and optimized by
Gelvin ( 2012) to add substantial value to agricultural
biotechnology (Tzfira and Citovsky, 2006). The nanocomplex is composed of Agrobacterium T-DNA,
single stranded DNA binding protein RecA and virulence protein VirD2. It is delivered to triticale microspores by the assistance of a Tat2 cell- penetrating
peptide (CPP) (Chugh et al., 2009). This evidence will
protect the integration of single transgene copy and
inhibit the degradation of the target DNA (Ziemienowicz et al., 2012).
tions have been associated with new allergens, toxins, and antibiotic resistance. Transgenic crops could
develop tolerance to abiotic hurdles and conditions
(Mei et al., 2005). The case of the Bt Cry9C protein
used in corn that was alleged to have caused allergic
reactions has raised concerns among epidemiologists and regulators (EPA, 2003). However, the Centers for Diseases Control (CDC) suggest otherwise
by concluding that the risk of allergic reactions to
Cry9C is very low (EPA, 2003). Concerns also exist
about altered genes resisting abiotic stressors that
could be transferred to microorganisms via animal
digestion and hence could transform bacteria into
altered-gene vectors. In a biofuels system altered
genes could be transmitted to organisms like Lactobacillus strains, which are common contaminants in
ethanol fermentations. The main issue would be the
dispersal of these strains in the surrounding environment (Curragh and Collins, 1992).
BIOTECHNOLOGY RISK ASSESSMENT
MODELING
According to an extensive study conducted by the
Council for Agricultural Science and Energy (Carpenter et al., 2002), GMOs could impact considerably
the environment by reducing biodiversity via cross-
The Biotechnology Risk Assessment models have
emerged as potential means for enhancing biosafety in agricultural systems (Wolt, 2009). This statistical approach is a leading scientific method that
estimates the biological and physical risks of release
to the environment of genetically engineered microorganisms, plants, and animals. It integrates the
distribution of exposure to GMOs with data on probability of occurrence and the severity of the effect
(dose response). Currently, the systemic approach is
emerging as the most effective point-of-care method
adopted by federal regulatory agencies attempting
to create a set of practical management tools pertaining to GMO dispersal in the environment (Flory
et al., 2012). It provides proper accounting of inputs
and outputs and hence helps elucidate all potential
pollination or by destroying beneficial organisms, in
addition to other unforeseen outcomes. The study
placed emphasis on the potential adverse effects of
GMOs on human health through the risk assessment
approach. Potential hazards from GMO manipula-
process steps that carry the risk of exposure to irreversible potentially harmful gene mutations (Krimsky and Golding, 1992). It also provides a qualitative
and quantitative risk estimation that can assist users
in setting up preventive action to ensure ecosystem
POTENTIAL BOTTLENECKS
GMOs dispersal
XX
Agric. Food Anal. Bacteriol. • AFABjournal.com • Vol. 5, Issue 3 - 2015
biosafety. The risk analysis relies primarily on hazard
identification, collection of data, and subsequent estimation of the likelihood of occurrence and severity of effects in all steps of the production process.
This includes the exposure assessment modeling
through the GMO dynamic flow (Flory et al. 2012;
Krimsky and Golding, 1992; Schierow, 2008).
GMO dynamic flows in biofuel system
Unlike biomass-derived ethanol that usually requires genetic modifications to enable microorganisms to efficiently co-ferment pentose sugars,
corn-based biofuel production includes transgenic
(Ribeiro, 2004)
Where the horizontal axe shows the interdependent variables and vertical axe conveys the probability of uncertain numbers.
Thus, the algorithm analyzes uncertainty variables, such as size of GMO-containing stream (solid,
liquid or gaseous) released to the environment and
GMO concentration in the released stream. This holistic integration estimates the overall risk posed by
feedstocks but not necessarily GM microorganisms
(Tomás-Pejó et al., 2009; Yanase et al., 2010). From
this perspective, aside from GM corn by-products,
it is quite possible that inadvertent GMO dissemination could also occur during various processing
steps, such as starch hydrolysis and sugar fermentation (Kádár et al., 2004). Moreover, a number of modified microorganisms in lignocellulosic biofuels have
been identified to render the promising CBP and
SSCF processes cost-effective (Limayem and Ricke,
2012; Yamada et al., 2010,). Although a high temperature of 500°F in downstream operations would suppress GMOs residues, such GMO applications need
to be traced from the source to the final product. A
hypothetical modeling to GMOs risk exposure from
feedstocks to biofuel production and end-products
is depicted in Figure 4.
Computationally, the assessment uses a probability density function in conjunction with Monte Carlo
simulations that select randomly a set of data from
numerous probability distributions.
The certified software (i.e., @ Risk tool) enables
the random inputs selection from extensive number of probability distributions (Haas et al., 1999).
As such, it determines the interdependent variables
through a high selected number of repetitions (i.e.,
GMOs. Hence, a holistic view of the GMO dynamic
flow constitutes a comprehensive first step for GMO
users in the biofuel industry through Biotechnology
Risk Assessment analysis and development of proper management practices (Haas et al., 1999).
104 trials). The Gaussian probability density function
p(x) equation is described as follows:
can serve as a decision-making tool to help institute
comprehensive protective standards as the sector
grows. The same risk assessment approach could
also serve the industry well when GMOs are introduced on a large scale biofuel production annually
CONCLUSIONS
The development of agricultural biotechnology in
the 1980s has given rise to a genetic revolution in
crops. More recently, the biofuel industry has opted
for GMO practices to increase product yields and
minimize land and water use via transgenic plants
and engineered microorganisms. Corn-derived
biofuels have benefitted from government incentives and extensive cultivation of transgenic plants.
Biomass-derived ethanol and other biofuels hold
great promise for energy security owing to the development of novel GM microorganisms that allow
process-step integration and higher efficiencies with
minimal capital cost. Although to date there is no
clear evidence or direct proof of GMO side effects
on the environment, preventive measures should be
undertaken by the industry to drastically ensure the
environmental safety. The risk assessment approach
Agric. Food Anal. Bacteriol. • AFABjournal.com • Vol. 5, Issue 3 - 2015
XX
as dictated by the federal government’s renewable
fuel standard. Elucidating a practical engineered
core modeling to optimization of GMOs traceability
and biosafety in biofuel production holds promises
as the future method of interest to sustain biotechnology advancement.
ABBREVIATIONS
GMOs: Genetically Modified Organisms
GM: genetically modified
RA: Biotechnology Risk Assessment
RFA: Renewable Fuels Association
DDGS: distiller’s dry grain with solubles
RFS: Renewable Fuel Standard
MSW: municipal solid waste
EPSPS: 5-enolpyruvylshikimate-3-phosphate synthetase
Bt: Bacillus thuringiensis
DNA: recombinant DNA
CR: Polymerase Chain Reaction
CBP: consolidated bioprocessing
SSCF: simultaneous saccharification and
co fermentation
CDC: Centers for Disease Control and Prevention
FIB: fecal indicator bacteria
HGT: Horizontal Gene Transfer
CTP: Cytoplasmic Transduction Peptide
GOX: Glyphosate Oxidase
ACP: Palmitoyl-Acyl Carrier Protein
ACKNOWLEDGEMENTS
This research was partially supported by grants
from the South Central Sun Grant Program (U.S. Department of Transportation) and Novozyme North
America, Inc. (Franklinton, NC).
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