Scholarly article on topic 'Amino acid catabolism-directed biofuel production in  Clostridium sticklandii:  An insight into model-driven systems engineering'

Amino acid catabolism-directed biofuel production in Clostridium sticklandii: An insight into model-driven systems engineering Academic research paper on "Industrial Biotechnology"

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Abstract of research paper on Industrial Biotechnology, author of scientific article — C Sangavai, P Chellapandi

Abstract Model-driven systems engineering has been more fascinating process for the microbial production of biofuel and bio-refineries in chemical and pharmaceutical industries. Genome-scale modeling and simulations have been guided for metabolic engineering of Clostridium species for the production of organic solvents and organic acids. Among them, Clostridium sticklandii is one of the potential organisms to be exploited as a microbial cell factory for biofuel production. It is a hyper-ammonia producing bacterium and is able to catabolize amino acids as important carbon and energy sources via Stickland reactions and the development of the specific pathways. Current genomic and metabolic aspects of this bacterium are comprehensively reviewed herein, which provided information for learning about protein catabolism-directed biofuel production. It has a metabolic potential to drive energy and direct solventogenesis as well as acidogenesis from protein catabolism. It produces by-products such as ethanol, acetate, n-butanol, n-butyrate and hydrogen from amino acid catabolism. Model-driven systems engineering of this organism would improve the performance of the industrial sectors and enhance the industrial economy by using protein-based waste in environment-friendly ways.

Academic research paper on topic "Amino acid catabolism-directed biofuel production in Clostridium sticklandii: An insight into model-driven systems engineering"

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Title: Amino acid catabolism-directed biofuel production in Clostridium sticklandii: An insight into model-driven systems engineering

Authors: Sangavai C, Chellapandi P



S2215-017X(17)30185-6 BTRE 222

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Please cite this article as: C Sangavai, P Chellapandi, Amino acid catabolism-directed biofuel production in Clostridium sticklandii: An insight into model-driven systems engineering, Biotechnology Reports

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Amino acid catabolism-directed biofuel production in Clostridium sticklandii: An insight into model-driven systems engineering

Sangavai C and Chellapandi P*

Molecular Systems Engineering Lab, Department of Bioinformatics, School of Life Sciences,

Bharathidasan University, Tiruchirappalli-620 024, Tamil Nadu, India

Tel: +91-431-2407071 Fax: +91-431-2407045 Email:

*Corresponding author

Graphical Abstract

L-Citrulline ^ K

Caibomyl-P04 ,

'L-Ghitamate y-semi aldeh

1 Pynoline-5 carboxylate L-Proline D-Proline



5 Aminopentanoate xaloacetate

-Hydro xyglutarate


8.3.12 "


H i.12 [

BUjV Urocaiioate Imidazolone-5 pronale

j nninin o-L- glmamate \L-Glutamate y

2-1 [ydroxygli

1.2.1.- | L-Isoleucine


Glutacon^-cjjA L-Glutamate

3-Methyl 2-axopentanoate

1 1.70

Butanoyl-CoA Acetate.




n-Bntanoate Acetoacetyl-Q

Acetyl^CoA 6.2.1 13

C02+y 1.2.1

2 -Methylbutanoyl-CQA

3 -Hyroxybutanjjyl-CoA 2-Methylciotcmoyi-CoA

Amino acetones-


_ 2-Amino-30xobutanoate


Acetyl Co A ^J Glyt

+7,8 -D ihydr obi opterin 1.5.1 -

H20 Tetrahydrobiopterin L J 1 1

• L-Phenylalanine+ L-Tyrosin ■ 4 Hydroxyl-t etrahydrobi opterin

. N-Lipoyl- L-Lysine


Acetyl CoA ^^ ,

N-D iam in omethyi dihydrohpoyi L-Lysine

N-Dihydrdipoyl -L-Lysine

2-Methyl-3 hydroxybutyiyl CoA

L-Methionine » 2-Ammo prop-2-enoate -



2-Immunobiitaiioaie Methanethiol +NH3


Proponyl phosphate -► Prop a no a U-


■ Model-driven systems engineering has been more fascinating process for the microbial production of biofuel and bio-refineries.

■ Clostridium sticklandii is one of the potential interests to be exploited as an industrial strain for the solventogenesis and acidogenesis.

■ The present review provides information for learning about protein catabolism-directed biofuel production.


Model-driven systems engineering has been more fascinating process for the microbial production of biofuel and bio-refineries in chemical and pharmaceutical industries. Genome-scale modeling and simulations have been guided for metabolic engineering of Clostridium species for the production of organic solvents and organic acids. Among them, Clostridium sticklandii is one of the potential organisms to be exploited as a microbial cell factory for biofuel production. It is a hyper-ammonia producing bacterium and is able to catabolize amino acids as important carbon and energy sources via Stickland reactions and the development of the specific pathways. Current genomic and metabolic aspects of this bacterium are comprehensively reviewed herein, which provided information for learning about protein catabolism-directed biofuel production. It has a metabolic potential to drive energy and direct solventogenesis as well as acidogenesis from protein catabolism. It produces by-products such as ethanol, acetate, n-butanol, n-butyrate and hydrogen from amino acid catabolism. Model-driven systems engineering of this organism would improve the performance of the industrial sectors and enhance the industrial economy by using protein-based waste in environment-friendly ways.

Key words: Biofuel, Amino acid catabolism, Genome-scale model, Metabolic engineering,

Systems biology, ABE fermentation, Clostridium sticklandii


Chemical and pharmaceutical industries are manufacturing fine chemicals in use of organic solvents and acids. Acetone is a solvent in the production of cordite, a smokeless ammunition propellant. Ethanol is a gasoline additive to increase octane and improve vehicle emissions. Butanol is used as an alternative liquid transportation fuel and can be catalytically converted into jet fuels. Moreover, butanol has proved to be a better biofuel than acclaimed ethanol owing to it is less corrosive and easily blend with gasoline (Tracy et al. 2012). Isobutyric acid and n-butyric acid are commercially used in the production of artificial fibers, plastics and herbicides. Isovaleric acid is mainly used for perfumery production and intensive care medicine (Schonicke et al. 2015). The worldwide biofuel production reached 105 billion liters in 2010 and a contribution largely made up of ethanol and biodiesel (Koltuniewicz 2014) (Fig. 1). Using biotechnological processes and renewable resources, the worldwide production of acetic acid exceeds 2 million metric tons per year. The worldwide annual production quantity of propionic acid was estimated to 377,000 metric tons in 2006 (Schonicke et al. 2015). Economic development of renewable chemicals and biofuel technologies rests on several important parameters. The social, environmental and technical

crises and substrate availability are being the most important factors in determining bioprocess viability and economical feasibility (Tracy et al. 2012).

Microorganisms are rich sources for natural products, some of which are used as fuels, commodity chemicals, fine chemicals, and polymers (Chubukov et al. 2016). Genetically engineered microbial strains should have a metabolic capability of utilizing multiple substrates with variable composition and without catabolite repression, which are crucial for the development of economic processes (Demain 2010). A microbial strain that has diverse substrate utilization potential would offer a major competitive advantage to the biofuel production from various feedstock such as carbohydrates, lipids and proteins. Carbohydrate-based substrates

Acetone-butanol-ethanol (ABE) fermentation is a known metabolic process of Clostridium sp. for the production of acetone, n-butanol, and ethanol from lignocellulosic biomass degradation (Formanek et al. 1997; Ezeji et al. 2004; Tracy et al. 2012). Starches and simple sugars derived from sugar cane and corn are the most commonly used feedstock for the industrial production of biofuels. Microbial fermentation converts sugars produced from lignocellulosic biomass into biofuels or biorefineries using Clostridium sp. The theoretical maximum calculated to be 0.939 mol butanol/1 mol glucose by ABE fermentation (Papoutsakis 1984) and ~1.33 mol butanol/1 mol glucose by mixotrophic fermentation (Fast and Papoutsakis 2012). Clostridium acetobutylicum has been studied as a model organism of biofuel production for several decades (Lee et al. 2008). C. acetobutylicum ATCC 824 and C. beijerinckii BA101 were proved to increase n-butanol tolerance and for n-butanol production from carbohydrates (Formanek et al. 1997; Ezeji et al. 2004). Butanol production was previously commercialized from molasses produced from sugar cane industry using C. acetobutylicum (Ennis et al. 1986). C. beijerinckii BA101 mutant produced the highest concentration of n-butanol (17-21 g/L) from glucose across all microorganisms (Annous and Blaschek 1991). However, lignocellulosic biomass has to be pretreated for biofuel production under harsh conditions that requires a large amount of energy consumption (Humbird et al. 2011; Balan 2014). Lipid-based substrates

Compared to cellulosic biomass, food waste holds several significant advantages to produce butanol, since it comprises with significant quantities of sugar, starch, fatty acids, proteins and minerals. The considerable amounts of these functionalized substrates can act as nutrients to proliferate the culture growth during ABE fermentation (Lin et al. 2013; Huang et al. 2015). Even if lipids used for biodiesel generation using transesterification process, current production technology is not being economical to make biofuels through lipid fermentation (Vlysidis et al. 2011). However, a coproduct derived from high-value fatty acids could potentially make the biorefinery process economical (Ratledge and Wynn 2002). The maximum theoretical yield of ethanol obtained from palmitic acid (1.38g ethanol/g palmitic acid) is significantly higher than that obtained from glucose (0.51g ethanol/g glucose) (Clomburg and Gonzalez, 2010; Dellomonaco et al. 2011). Clomburg and Gonzalez (2010) calculated the maximum theoretical yield of 1 mol each of ethanol and hydrogen per mole of glycerol fermented with an ethanol production of 4.6 mmol/L/h. Protein-based substrates

Bioconversion process for releasing protein/amino acids from algal biomass or protein-rich waste may be easier than breaking down lignocellulosic to fermentable sugars (Mielenz 2011). The conversion efficiency of total sugar in food waste was up to 88%, but of protein was 40-70% (Yin et al. 2016). Therefore, the conversion of proteins into biofuel is usually the rate limiting step during acidogenesis and solventogenesis phases (Shen et al. 2017). Amino acids released by proteolysis of a protein-based substrate are catabolized to produce keto acids, which are synthesized into biofuels (ethanol, isobutanol, 2-methyl-1-butanol, and 3-methyl-1-butanol) (Choi et al. 2014). Valine, leucine, threonine and isoleucine biosynthetic pathways have been overexpresed in Escherichia coli host for the production of isobutanol (Atsumi et al. 2008), 2-methyl-1-butanol (Cann and Liao, 2008), and 3-methyl-1-butanol (Connor and Liao 2008). Engineered E. coli achieved a yield of ~4 g/l of alcohols from a yeast extract containing 21.6 g/l of amino acids at 56% of the theoretical yield (Huo et al. 2011). Rerouting nitrogen flux in E. coli was allowed to producing up to 4,035 mg/l of alcohols from Saccharomyces cerevisiae, E. coli, Bacillus subtilis and microalgae that can be used as protein sources containing ~22 g/l of amino acids (Mielenz 2011). E. coli carrying Clostridial butanol dehydrogenase (bdh) gene metabolically engineered for the conversion of protein hydrolysate to n-butanol and n-pentanol (Huo et al. 2011). Molecular and biochemical characteristics of many Clostridium species have been extensively studied for biofuel production. However, industrial and economic importance of them on the protein-based waste are hindered due to a lack of knowledge of their complex nature of metabolic and regulatory networks at a genome-scale. Hence, systems-metabolic engineering of industrially important Clostridium would advance in the development of economically viable processes. Clostridium sticklandii genome

C. sticklandii is a Gram-positive, anaerobic, motile and non-pathogenic bacterium isolated from mud of the San Francisco Bay Area (Stadtman and McClung 1957). It utilizes amino acids as an important carbon and energy sources. It also catabolizes purines, glucose, maltose and galactose through a fermentation process, but these compounds are only minor substrates for its energy and growth (Schwartz and Schäfer 1973; Schäfer and Schwartz 1976). It contains a single circular chromosome of 2,715,461 bp. It encompasses 2573 coding sequences, 77 RNA genes and 38 pseudogenes. Its coding sequences contain high protein coding density of 89.2% and 2.1% repeated regions (Fonknechten et al. 2010). C. sticklandii genome consists of 199 pathways, 1103 metabolic reactions, 829 metabolites and 739 enzymes. It shares the highest number of genes that are homologous to the pathogenic C. difficile and hype-ammonia producing Clostridium species. In this genome, 33% coding sequences are annotated as conserved hypothetical proteins. Comparative genomic analysis

The genomes of Clostridium genus are highly diverse in morphology, the G+C content of the DNA (24-55 mol%), and metabolic activity (Cato and Stackebrandt 1989). C. acetobutylicum, C. beijerinckii and C. ljungdahlii have 250 pathways, 1300 metabolic reactions and 1000 metabolites, which exhibited their complex nature of metabolic and regulatory networks (Fig. 2). C. sticklandii, C. bifermentans and C. aminophilum consist of a typical transporter system that is able to transport most of the amino acids and amine-derived compounds across membranes. C. beijerinckii has a well-established transcriptome structure, but its transcript boundaries are not well understood. It is still not clear in other Clostridial

genomes (Wang et al. 2011). Genes involved in carbohydrate, lipid and nucleotide metabolism and their annotated features are extensively available for C. acetobutylicum, C. beijerinckii, C. cellulolyticum and C. ljungdahlii to date (Fig. 3). Energetic metabolism is vastly studied to know ion-gradient driven chemiosmotic ATP generation in all Clostridial genomes excluding C. bifermentans and C. aminophilum. Genes involved in amino acid metabolism of many Clostridial genomes including C. sticklandii are greatly annotated with detailed functional information, suggesting their physiological importance in the growth and catabolism in different environmental niche. General metabolism

The simultaneous presence of genes encoding for the complete Wood-Ljungdahl pathway and the glycine synthase is a particular metabolic feature of C. sticklandii (Fonknechten et al. 2010). Genes coding for sulfate assimilate pathway are absent in this genome. Biotin and pantothenate are the absolute requirement for its growth, as those vitamins biosynthesis pathways absent in this genome (Golovchenko et al. 1985). The genes of the non-oxidative pentose phosphate pathway are present. The Rnf complex, Na+-dependent F0F1-ATPase and an additional V-ATPase perform ion-gradient driven chemiosmotic ATP generation via electron-transport phosphorylation (Müller and Grüber 2003; Fonknechten et al. 2010). Superoxide reductase, Mn-superoxide dismutase, PerR homolog, glutathione peroxidases, seleno-peroxiredoxin and thioredoxin-dependent peroxidase are defense systems that enhance its survival under microaerophilic conditions (Hillmann et al. 2008). Amino acid catabolism Protein degradation and transport

Proteins are initially hydrolyzed by exogenous proteases to small peptides and amino acids. C. sticklandii can be able to ferment amino acids to ammonia, CO2, hydrogen, acetate and short chain fatty acids by the catalytic action of different metabolic enzymes as presented in Table 1. It has ABC transporters for oligopeptides, methionine, and branched-chain amino acids, serine/threonine symporter and also arginine/ornithine antiporter, which can mediate amino acid transport across the membrane (Fonknechten et al. 2010). It has a typical system for amino acid catabolism (Fig. 4). Stickland reactions

Stickland reaction is a particular kind of fermentation of amino acids in the hype-ammonia producing Clostridium species. It is characterized by simultaneous oxidation of one amino acid and reduction of another amino acid (Stickland 1934; Nisman 1954). Approximately 0.5 mole ATP is generated per mole amino acid transformed in Stickland reaction (Andreesen et al. 1989). The S-aminovalerate is an intermediate of arginine and proline degradation, which makes up approximately 70 percent of the theoretical propionic acid production. The theoretical stoichiometric coefficient for H2 is 0.134, which produces about 20% H2 from amino acid fermentation consumed by amino acids reduction (Ramsay and Pullammanappallil 2001). C. bifermentans, C. sordellii and C. sticklandii are belonged to Group IA strains. All strains utilize serine and threonine. The most strains produce a-amino butyrate and y-amino butyrate (Mead 1971). Amino acid fermentation pattern is remarkably similar in C. sticklandii, C. aminophilum, C. aminovalericum, C. acidiurici and C. barkeri, but their growth patterns are varied in some extent (Paster et al. 1993). These bacteria were produced up to 20-fold more ammonia than other ammonia-producing bacteria and therefore,

these are considered to be ecologically important. C. sticklandii oxidizes ornithine, arginine, threonine, serine, and reduces proline and glycine (Stadtman and WhiteJr 1954; Mead 1971; Barker 1981). It utilizes glycine and ornithine pair in the Stickland reaction by 2,4-diaminopentanoate dehydrogenase (EC Aliphatic amino acids

Glycine reductase, glycine acetyltransferase, phosphotransacetylase and acetate kinase are key enzymes involved in the L-glycine catabolism in C. sticklandii (Golovchenko et al. 1982; Graentzdoerffer et al. 2001). Methylene-tetrahydrofolate, CO2 and ammonia are produced from glycine by direct oxidation of NAD+ via either glycine cleavage system or reduced to the acetyl phosphate by glycine reductase (Andreesen 1994). L-Alanine is deaminated to acetate and ammonia with reduction of NADH as NAD+ by L-alanine dehydrogenase (CLOST_0512|CLOST_0519). Glycine reductase (EC reduces L-glycine alone to acetate with the release of ammonia via intermediate acetyl phosphate. Reduced thioredoxin and ATP molecules are produced as end products by glycine reductase and acetate kinase, respectively. Acetate is formed from pyruvate via acetyl-coA and acetyl phosphate by a combined action of phosphate acetyltransferase and acetate kinase. Pyruvate-formate lyase converts pyruvate into acetyl-coA. Pyruvate dehydrogenase transfers an acetyl group with the use of electron donor NAD+, which reduced to NADH2 in the conversion of pyruvate into acetyl-CoA.

C. sticklandii has two adaptable catabolic systems such as ornithine degradation I (proline biosynthesis) and ornithine degradation II (Stickland reaction) for the degradation of L-ornithine. It contains all important genes coding for ornithine carbamoyltransferase, carbamate kinase, ornithine cyclodeaminase, ornithine aminotransferase, 2,4-diaminopentanoate dehydrogenase, and pyrroline-5-carboxylate reductase for ornithine catabolism. Ornithine racemase, adenosylcobalamin-dependent D-ornithine aminomutase and D-ornithine 4,5-aminomutase are identified and characterized for their enzymatic functions (Chen et al. 2000, 2001, 2004; Tang et al. 2002; Tseng et al. 2007). L-Proline is directly produced in the exponential phase from the breakdown of L-ornithine by a catalytic action of ornithine cyclodeaminase. Ornithine can be reduced to 5-aminovalerate through the formation of D-proline as an intermediate (Baker 1981; Kenklies et al. 1999; Fonknechten et al. 2009). This organism has a typical operon that performs the reductive ring cleavage of D-proline into 5-aminovalerate, which is subsequently excreted (Madigan et al. 1997; Kenklies et al. 1999). Proline reductase, proline racemase and proline racemase are key enzymes involved in proline catabolism (Stadtman and Elliott 1957; Kabisch et al. 1999; Bednarski et al. 2001; Harty et al. 2014).

L-Alanine-L-glycine pair could not be catabolized in the Stickland reaction as it does not have alanine dehydrogenase (Stadtman 1954). L-Valine, L-leucine, and L-isoleucine are probably transaminated to 2-ketoacids. These amino acids are subsequently assimilated in the primary metabolism by branched-chain-amino-acid transaminase, 2-methyl-branched-chain-enoyl-CoA reductase, enoyl-CoA hydratase, and 3-hydroxy-2-methylbutyryl-CoA dehydrogenase (Elsden and Hilton 1978). Aromatic amino acids

Aromatic amino acids are catabolized by oxidative system of C. sticklandii, but its catabolic pathways is still unknown (Elsden et al. 1976). However, genes coding for phenylalanine 46

monooxygenase and 4a-hydroxytetrahydrobiopterin dehydratase were recently identified from this genome, which could possibly metabolize L-phenylalanine. This genome contains all the genes (hutH, hutU, hutI and hutG) involved in the L-histidine metabolism. Acidic amino acids

L-Histidine is assimilated into glutamate that is not exogenously used by C. sticklandii (Mead 1971; Elsden and Hilton 1979). Glutamate is metabolized to acetyl-coA with consecutive catalytic action of glutaminase, glutamate dehydrogenase, glutaconate CoA-transferase and glutaconyl-CoA decarboxylase via glutamate degradation V (via hydroxyglutarate) or glutamine degradation I (Fonknechten et al. 2010). Neutral amino acids

Branched chain amino acids are catabolized by the oxidative system of this organism (Elsden and Hilton 1978). The NAD-dependent L-threonine-3-dehydrogenase and L-threonine dehydrogenase are identified and characterized from this organism. It indicates the potential of using L-threonine as carbon and nitrogen sources for its growth (Wagner and Andreesen 1995; Edgar 2002). These enzymes oxidize threonine to 2-amino-3-ketobutyrate that is split into glycine and acetyl-CoA (Wagner and Andreesen 1995). Threonine aldolase transforms threonine to glycine and acetaldehyde. Threonine dehydratase catalyzes threonine to ammonia and 2-ketobutyrate, which are oxidized to propionate and CO2 or reductively aminated to 2-aminobutyrate (Elsden and Hilton 1979). L-Serine catabolism is rapidly mediated in the exponential growth phase by the presence of iron-dependent serine dehydratase and serine racemase (Zinecker et al. 1998; Harty et al. 2014). This organism is able to catabolize both D-serine and L-serine due to its genome contains D-serine ammonia-lyase and D-serine ammonia-lyase. Pyruvate is an intermediate product resulted from dehydration of serine. Asparaginase is a key enzyme involved in the degradation of L-asparagine to ammonia and CO2 via asparagine degradation I pathway. Basic amino acids

L-Arginine is quickly metabolized into ornithine via citrulline and conserves energy without any redox reaction. This organism contains all the genes (speA and speB) involved in the arginine deiminase pathway as well as the ornithine oxidative-reductive pathway (Kenklies et al. 1999; Fonknechten et al. 2009). Cobamide coenzyme-dependent beta-lysine mutase, lysine-5,6-aminomutase and lysine decarboxylase are isolated and studied for understanding its L-lysine catabolism (Stadtman and Renz 1968; Berkovitch et al. 2004). Lysine is catabolized into acetate, butyrate, and ammonia by exergonic reduction of crotonyl-CoA to butyryl-CoA (Stadtman 1973; Chang and Frey 2000; Kreimeyer et al. 2007; Seedorf et al. 2008). After depletion of serine, arginine and cysteine, crotonyl-CoA is formed from the condensation of two acetyl-CoAs via butyrate fermentation during its exponential growth phase (Fonknechten et al. 2010). Sulfur-containing amino acids

A putative L-cysteine sulfide lyase found to degrade L-cysteine into pyruvate, ammonia and hydrogen sulfide. Methionine sulfoxide reductase is involved in the repair of oxidative damaged methionine, which may enhance its growth under microaerophilic condition. Gene (megL) coding for methionine y-lyase possibly degrades L-methionine through the methionine degradation II pathway. A selenium-containing tRNAGIU was isolated and characterized from this organism for a better understanding of the functional role of selenium

in specific tRNA species that modulate the protein synthesis efficiency of certain mRNAs (Ching et al. 1985; Ching 1986). The presence of D-selenocystine alpha, beta-lyase supports selenocysteine metabolism (Esaki et al. 1988). Biofuels from amino acid catabolism

In the C. sticklandii, pyruvate is a major metabolic intermediate produced from amino acid catabolism, which further ferments into organic solvents (ethanol and n-butanol) and organic acids (acetate and n-butyrate). The proposed pathway for the solventogenesis and acidogenesis from amino acid catabolism is represented in Fig. 5. 2-Ketobutyrate formate-lyase converts pyruvate to acetyl-CoA that can be fermented in several routes. Aldehyde-alcohol dehydrogenase converts acetyl-coA to acetaldehyde, leading to produce ethanol by an alcohol dehydrogenase reaction (Eram and Ma 2013). Butanol biosynthesis

C. sticklandii has many branch points to execute solventogenesis and acidogenesis. Acetyl-CoA, acetoacetyl-CoA, and butanoyl-CoA are key intermediates produced during biofuel synthesis (Herrmann et al. 2008; Li et al. 2008). Acetyl-CoA is converted to acetate in a single step, catalyzed by the enzyme acetate-CoA ligase. Acetyl-coA acetyltransferase converts acetyl-coA to acetoacetyl-coA that forms acetoacetate. Acetone is produced from decarboxylation acetoacetate by acetoacetate decarboxylase. Acetone is reduced to 2-proponal by a reaction catalyzed by NADP+-dependent oxidoreductase. Butanoyl- CoA is formed from acetoacetyl-coA via intermediates 3-hydroxybutonyl-coA and crotonyl- CoA by the consecutive action of 3-hydroxybutyryl-coA dehydrogenase, (S)-3-hydroxybutanoyl-CoA hydro-lyase and butyryl-coA dehydrogenase. Finally, n-butanote is produced from butanoyl-coA through butanoyl-coA and butanoyl phosphate by two modifying enzymes, phosphate butyryltransferase and butyrate kinase. Butanoyl-coA is repeatedly transformed to n-butanol in two step mechanisms by butanal: NAD+ oxidoreductase or butanal dehydrogenase with NAD+ as an acceptor and oxidoreductase with the reduction of NADH. C. sticklandii uses lysine as a sole source of carbon and nitrogen, leading to produce n-butanoate and acetate via 3-keto-5-aminohexanoate pathway (Barker 1981). The (3S, 5S)-3, 5-diaminohexanoate is resulted L-P-lysine, an isomerised form of L-Lysine. Crotonyl-CoA is consecutively produced from (S)-3-aminobutanoyl-CoA and then is reduced to butanoyl-CoA.

Hydrogen production

C. sticklandii genome composes genes coding for periplasmic [Fe-Fe] hydrogenase (hymC), two cytoplasmic iron-only hydrogenases (hydA and hymABC) and [Fe-Fe]-hydrogenase maturation proteins, hydF, hydG and hydE. HydA is clustered together with genes coding for a formate dehydrogenase (fdhAB). The presence of periplasmic [Fe-Fe] hydrogenase catalyzes the reduction of protons to the hydrogen along with translocates protons. The proton concentration is also lowered by the oxidation of formate to CO2 from which released electrons are transferred directly to the hydrogenase via ferredoxin to reduce H+ ions. Hydrogen is generated from reducing equivalents during amino acid catabolism with the proton transport and energy conservation ferredoxin oxidoreductase. It is an alternative energy-conserving system to increase its growth efficiency on formate (Stadtman and WhiteJr 1954).

Molecular hydrogen is produced by the reduction of protons resulted from the reversible interconversion of protons, electrons and H2 through the action of hydrogenase.

Endogenously produced formate is oxidized into CO2 and H+ to evolve hydrogen by formate hydrogenlyase complex formed from NAD-dependent formate dehydrogenase H (fdhH) and hydrogenase 3 (Bohm et al. 1990; Sauter et al. 1992). FdhH catalyzes the oxidation of formate generating CO2 and transferring the electrons to hydrogenase 3. It tranfers electrons to the catalytic subunit hydE of hydrogenase 3 via hydF and hydG subunits [Maeda et al. 2008). HydH is required for the conversion of a precursor form of hydE into the mature form. HydA is a repressor protein that represses the hyd operon (Leonhartsberger et al. 2002) and increases fdhH and hydrogenase activity (Sauter et al. 1992). It is likely to control formate oxidation and the hydrogen production rate by manipulating fdhH and hydA (Yoshida et al. 2005). Gene expression analysis suggested that the concentration of formate in the cell determines the biosynthesis of formate hydrogenlyase complex (Rossmann et al. 1991). Endogenous selenium and molybdenum are required for the catalytic activity of formate dehydrogenase while nickel is necessary at the active site of hydrogenase 3 (Boyington et al. 1997).

End-product feedback inhibition

Feedback repression is effected by amino acid end-products acting as co-repressors interfering with transcription initiation in C. sticklandii (Sanchez and Demain 2008). Nitrogen metabolite repression, nitrogen catabolite repression and ammonia repression are known nitrogen source regulation in proteolytic Clostrdium sp., which typically control proteases, amidases, ureases, nitogenase, hydrogenase and those that degrade amino acids (ter Schure et al. 2000). It also controls the key ammonium assimilation such as NADP-glutamate dehydrogenase, glutamine synthetase, glutamate synthase and alanine dehydrogenase. The pool sizes of one or more substrates and/or products of these enzymes may suppress the enzymatic activities (Sanchez et al. 2008; Harper et al. 2010). TnrA becomes bound to the feedback inhibited form of glutamine synthetase, when nitrogen is excessed in the culture medium (Fedorova et al. 2013). Biosynthetic intermediates of aspartate kinase can be feedback inhibited by its end product either by lysine or threonine and activated by metabolite from a competing branch as similar to C. acetobutylicum (Manjasetty et al. 2014). Engineering nitrogen flux favors the breakdown of amino acids rather than their synthesis, resulting in 2-keto-methylvalerate, 2-keto-isocaproate and 2-keto-isovalerate (Huo et al. 2011). This approach is a great concern to overcome their feedback repression and to improve the biofuel production efficiency in E. coli (Mielenz 2011). Metabolic simulation for biofuel production

Mathematical models describing the overall physiology of the process, design features, mode of operation along with comparison and validation with experimental results of ABE fermentation were reviewed by Mayank et al (2013). Ethanol production is optimized in Synechocystis mutant by using the flux balance analysis, method of minimization of metabolic adjustment and regulatory on/off minimization (Sengupta et al. 2013). It is also improved in C. thermocellum by making more electrons available for acetyl coenzyme A reduction. In this approach, hydrogenase active site assembly is eliminated for hydrogen production that redirected carbon flux towards ethanol production (Biswas et al. 2015). A genetic change in C. phytofermentans demonstrated to improve its ethanol tolerance (Tolonen et al. 2015). E. coli harboring engineered C. acetobutylicum butanol biosynthetic pathway efficiently converted n-butyric acid to n-butanol (Mattam and Yazdani 2013). Therefore,

mathematical models and metabolic simulation tools are under intense development to metabolically engineer Clostridial strains for the biofuel production (Desai et al. 1999a, 1999b; Shinto et al. 2007; Amador-Nogue et al. 2010; Tracy et al. 2012). Genome-scale models for biofuel production

Systems biology is the quantitative analysis of biological systems using predictive mathematical models. It is focused on interpreting biological function and behavior at a cellular level by using very large-scale datasets (Mast et al. 2014). The in silico metabolic reconstruction is a common approach permitting simulations of engineered genotypes to elicit desired phenotypes, as outlined in Fig. 6. Constraint-based metabolic simulation in rational metabolic engineering requires a metabolic network reconstruction and a corresponding in silico metabolic model for the microorganism of interest (Simeonidis and Price 2015). A genome-scale metabolic model is fundamentally defined by a list of mass-balanced and charge-balanced reactions, which can simulate regulatory changes, genetic engineering effects, and dynamic cell behavior. Genome-scale metabolic networks have become more refined and complex, allowing for the expanded scopes in systematic metabolic engineering for microbial biofuel production (Davidson 2008; Senger 2010; Milne et al. 2011). However, integrated models of metabolism will become particularly important for understanding and manipulating biological behavior on a genome scale in the future. To meet industrial biotechnology process development needs, microbial cell factories are now being constructed faster and more efficiently through the use of systems biology resources (Otero and Nielsen 2010; Simeonidis and Price 2015).

Genome-scale models have been developed as a computational initiative for unraveling the systems-level metabolic competence of an organism and guiding metabolic engineering strategies for strain development (Chellapandi et al. 2010). Using these models, cofactors and energetic requirements can be metabolically balanced for the microbial growth. These models are used to predict the availability of biosynthetic precursors in response to environmental and genetic perturbations (Davidson 2008; Senger 2010). Genome-scale models for a range of different Clostridium sp. with varying metabolic capabilities have been published over the last ten years (Table 2). Several successes have been demonstrated for model-driven systems engineering of C. acetobutylicum (Lee et al. 2008, 2009; 2012; Senger et al. 2008a, 2008b), C. thermocellum (Roberts et al. 2010), C. cellulolyticum (Salimi et al. 2010), C. beijerinckii (Milne et al. 2011) and C. ljungdahlii (Nagarajan et al. 2013) for solventogenesis and acidogenesis. Constraint-based genome-scale metabolic model has been developed in a step-wise optimization procedure by which the solvent production was predicted in the continuous culture of immobilized C. acetobutylicum cells (Wallenius et al.

2013). A genome-scale metabolic model integrated with stress-related specific transcriptomics is used for the prediction of its focal points of gene regulation (Dash et al.

2014). The interdependence of gene regulation, metabolism, and environmental cues can be elucidated for ABE fermentation on the basis of its systems metabolic picture (Liao et al.

2015). Using its quantitative system-scale model, the biofuel producing steady-state can be determined for a better understanding of the functional regulation of primary metabolism (Yoo et al. 2015).

Model-driven systems metabolic engineering

In this approach, genome-scale metabolic modeling and x-ome technologies are deployed an increasing extent looking into the metabolic landscape to be engineered in order to establish an economically viable process it is necessary to improve the performance of the microorganism (Otero and Nielsen 2010; Simeonidis and Price 2015). Metabolic engineering of C. sticklandii is challenging due to the lack of an efficient gene inactivation system and the existence of complex metabolic networks. Extensive studies on protein catabolism-directed solventogenesis and acidogenesis are needed for guiding metabolic engineering of C. sticklandii to improve the yield of biofuel. Metabolic engineering targets for biofuel production have been evaluated from several Clostridial strains using conventional molecular approaches (Amador-Nogue et al. 2010; Tracy et al. 2012; Dusseaux et al. 2013; Tolonen et al. 2015). Systems-level characterization of C. sticklandii comprehensively examines metabolic networks to be engineered and provides a scaffold for more effective bioprocess development. Molecular complexity and the functional behavior of engineered C. sticklandii that plays a role in the response to alternative substrates have been efficiently explored with advances in an integrated knowledge base of its metabolic interaction networks. Current systems biological understanding of C. sticklandii would make it possible to expansively guide model-driven systems metabolic engineering within context of entire host metabolism, to diagnose stresses due to product synthesis, and provides the rationale to cost-effectively engineering strategies. Even if chemical processing systems are more convenient to produce fuel and refineries, these processes are very toxic to the environment and human health (Lin et al. 2013). Concerning the green biotechnology, its systems-level modeling framework would explore the metabolic capabilities to decipher a complex genotype-phenotype relationship governing its biofuel synthesis from protein-based waste.


C. sticklandii has a great concern of utilizing proteins for producing renewable alternatives to the petroleum-based chemicals and fuels using a metabolic model at the genome-scale. Target genes for guiding metabolic engineering and novel pathways to be engineered have to be elucidated to the scientific community for competent biofuel production at industrial scale. Genome-scale model of C. sticklandii would provide a skeleton for predicting its metabolic behavior and emphasizing metabolic connections to biofuel synthesis. It will afford a guide for parallel reconstruction of genome-scale metabolic networks of related species. Of particular importance is the development of a regulatory circuit that allows a recombinant pathway to become part of a heterologous metabolic network for biofuel production (Colin et al. 2011) and tolerance (Dunlop et al. 2011). Evolving genetic regulatory circuits would perform a self-regulating gene expression and enzyme activity in response to the precursor and or substrate supply in the host cell (Chatterjeee and Yuan 2005; Brophy and Voigt 2014). Genome-scale model of C. sticklandii will also provide a clue to design a synthetic pathway that needs to be integrated into the metabolic network of heterologous host in order to achieve optimal production levels. Optimized bioprocess parameters would be implemented for biofuel production from waste recycling of protein industry-based biomass in the biotechnology industry with eco-friendly manner. The present review concluded that model-driven systems metabolic engineering approach would advance the broaden applicability of using C. sticklandii for biofuel production in the industrial sector.

Compliance with ethical standards

The article does not contain any studies with human participants or animals performed by any of the authors. Conflict of interest

The author declares that this article's content has no conflicts of interest.


Empowerment and Equity Opportunities for Excellence in Science, Science and Engineering Research Board, Department of Science and Technology (Sanction No. SERB/F/8173/2015-16), New Delhi, India, is duly acknowledged for financial support.


Amador-Noguez D, Feng X-J, Fan J, Roquet N, Rabitz H, Rabinowitz JD (2010) Systemslevel metabolic flux profiling elucidates a complete, bifurcated tricarboxylic acid cycle in Clostridium acetobutylicum. J Bacteriol 192:4452-4461.

Andreesen JR (1994) Glycine metabolism in anaerobes. Antonie Van Leeuwenhoek 66:223237.

Andreesen JR, Bahl H, Gottschalk G (1989) Introduction to the physiology and biochemistry of the genus Clostridium. In: Minton NP & Clarke DC (eds.) Clostridia, Vol. 3 (pp 27-62). Plenum Press, New York

Annous BA, Blaschek HP (1991) Isolation and characterization of Clostridium acetobutylicum mutants with enhanced amylolytic activity. Appl Environ Microbiol 57:25442548.

Atsumi S, Hanai T, Liao JC (2008) Non-fermentative pathways for synthesis of branched-chain higher alcohols as biofuels. Nature 451:86-89.

Balan V (2014) Current callenges in commercially producing biofuels from lignocellulosic biomass. ISRN Biotechnol 2014: Article ID 463074

Barker HA (1981) Amino acid degradation by anaerobic bacteria. Annu Rev Biochem 50: 2340.

Bednarski B, Andreesen JR, Pich A (2001) In vitro processing of the proproteins GrdE of protein B of glycine reductase and PrdA of D-proline reductase from Clostridium sticklandii: formation of a pyruvoyl group from a cysteine residue. Eur J Biochem 268:3538-44. Berkovitch F, Behshad E, Tang KH, Enns EA, Frey PA, Drennan CL (2004) A locking mechanism preventing radical damage in the absence of substrate, as revealed by the x-ray structure of lysine 5,6-aminomutase. Proc Natl Acad Sci U S A 101:15870-15875. Biswas R, Zheng T, Olson DG, Lynd LR, Guss AM (2015) Elimination of hydrogenase active site assembly blocks H2 production and increases ethanol yield in Clostridium thermocellum. Biotechnol Biofuels 12:8-20.

Bohm R, Sauter M, Bock A (1990) Nucleotide sequence and expression of an operon in Escherichia coli coding for formate hydrogenlyase components. Mol Microbiol 4:231-243. Boyington JC, Gladyshev VN, Khangulov SV, Stadtman TC, Sun PD (1997) Crystal structure of formate dehydrogenase H: catalysis involving Mo, molybdopterin, selenocysteine, and an Fe4S4 cluster. Science 275:1305-1308.

Brophy JA, Voigt CA (2014) Principles of genetic circuit design. Nat Methods 11:508-520. Cann AF, Liao JC (2008) Production of 2-methyl-1-butanol in engineered Escherichia coli. Appl Microbiol Biotechnol 81:89-98.

Cato EP, Stackebrandt E (1989) Taxonomy and phylogeny. In N. P. Minton and D. J. Clarke (ed.), Clostridia. Plenum Press, New York., pp. 1-26

Chang CH, Frey PA (2000) Cloning, sequencing, heterologous expression, purification, and characterization of adenosylcobalamin-dependent D-lysine 5, 6-aminomutase from Clostridium sticklandii. J Biol Chem 275:106-14.

Chatterjee and Yuan (2005) Directed evolution of metabolic pathways. Trends Biotechnol 24:28-38.

Chellapandi P, Sivaramakrishnan S, Viswanathan MB (2010) Systems biotechnology: An emerging trend in metabolic engineering of industrial microorganisms. J Comput Sci Syst Biol 3: 43-49.

Chen HP, Hsui FC, Lin LY, Ren CT, Wu SH (2004) Coexpression, purification and characterization of the E and S subunits of coenzyme B(12) and B(6) dependent Clostridium sticklandii D-ornithine aminomutase in Escherichia coli. Eur J Biochem 271:4293-4297. Chen HP, Lin CF, Lee YJ, Tsay SS, Wu SH (2000) Purification and properties of ornithine racemase from Clostridium sticklandii. J Bacteriol 182:2052-2054.

Chen HP, Wu SH, Lin YL, Chen CM, Tsay SS (2001) Cloning, sequencing, heterologous expression, purification, and characterization of adenosylcobalamin-dependent D-ornithine aminomutase from Clostridium sticklandii. J Biol Chem 276:44744-44750. Ching WM (1986) Characterization of selenium-containing tRNAGlu from Clostridium sticklandii. Arch Biochem Biophys 244:137-146.

Ching WM, Alzner-DeWeerd B, Stadtman TC (1985) A selenium-containing nucleoside at the first position of the anticodon in seleno-tRNAGlu from Clostridium sticklandii. Proc Natl Acad Sci USA 82:347-350.

Choi KY, Wernick DG, Tat CA, Liao JC (2014) Consolidated conversion of protein waste into biofuels and ammonia using Bacillus subtilis. Metab Eng 23:53-61. Chubukov V, Mukhopadhyay A, Petzold CJ, Keasling JD, Martín HG. (2016) Synthetic and systems biology for microbial production of commodity chemicals. Syst Biol Appl 2:16009. Clomburg JM, Gonzalez R (2010) Biofuel production in Escherichia coli: the role of metabolic engineering and synthetic biology. Appl Microbiol Biotechnol 86:419-434. Colin VL, Rodríguez A, Cristóbal HA (2011) The role of synthetic biology in the design of microbial cell factories for biofuel production. J Biomed Biotechnol 2011:601834. Connor MR, Liao JC (2008) Engineering of an Escherichia coli strain for the production of 3-methyl-1-butanol. Appl Environ Microbiol 74:5769-5775.

Dash S, Mueller TJ, Venkataramanan KP, Papoutsakis ET, Maranas CD (2014) Capturing the response of Clostridium acetobutylicum to chemical stressors using a regulated genome-scale metabolic model. Biotechnol Biofuels 7:144.

Davidson S (2008) Sustainable bioenergy: Genomics and biofuels development. Nature Education 1:175.

Dellomonaco C, Clomburg JM, Miller EN, Gonzalez R (2011) Engineered reversal of the ß-

oxidation cycle for the synthesis of fuels and chemicals. Nature 476:355-359.

Demain A (2010) Recombinant organisms for production of industrial products. Bioeng Bugs


Desai RP, Harris LM, Welker NE, Papoutsakis ET (1999a) Metabolic flux analysis elucidates the importance of the acid-formation pathways in regulating solvent production by Clostridium acetobutylicum. Met Eng 1: 206-213.

Desai RP, Nielsen LK, Papoutsakis ET (1999b) Stoichiometric modeling of Clostridium acetobutylicum fermentations with non-linear constraints. J Biotechnol 71: 191-205. Dunlop MJ, Dossani ZY, Szmidt HL, Chu HC, Lee TS, Keasling JD, Hadi MZ, Mukhopadhyay A (2011) Engineering microbial biofuel tolerance and export using efflux pumps. Mol Syst Biol 7:487.

Dusseaux S, Croux C, Soucaille P, Meynial-Salles I (2013) Metabolic engineering of Clostridium acetobutylicum ATCC 824 for the high-yield production of a biofuel composed of an isopropanol/butanol/ethanol mixture. Metab Eng 18:1-8.

Edgar AJ (2002) Molecular cloning and tissue distribution of mammalian L-threonine 3-dehydrogenases. BMC Biochem 3:19.

Elsden SR, Hilton MG (1978) Volatile acid production from threonine, valine, leucine and isoleucine by clostridia. Arch Microbiol 117:165-72.

Elsden SR, Hilton MG (1979) Amino acid utilization patterns in clostridial taxonomy. Arch Microbiol 123:137-41.

Elsden SR, Hilton MG, Waller JM (1976) The end products of the metabolism of aromatic amino acids by Clostridia. Arch Microbiol 107:283-288.

Ennis BM, Marshall CT, Maddox IS, Paterson AHJ (1986) Continuous product recovery by in-situ gas stripping/condensation during solvent production from whey permeate using Clostridium acetobutylicum. Biotechnol Lett 8:725-730.

Eram and Ma (2013) Decarboxylation of pyruvate to acetaldehyde for ethanol production by hyperthermophiles. Biomolecules 3: 578-596

Esaki N, Seraneeprakarn V, Tanaka H, Soda K (1988) Purification and characterization of Clostridium sticklandii D-selenocystine alpha, beta-lyase. J Bacteriol 170:751-756 Ezeji TC, Qureshi N, Blaschek HP (2004) Butanol fermentation research: upstream and downstream manipulations. Chem Rec 4:305-314.

Fast AG, Papoutsakis ET (2012) Stoichiometric and energetic analyses ofn non-photosynthetic CO2 fixation pathways to support synthetic biologynstrategies for production of fuels and chemicals. Curr Opin Chem Eng1:380-395.

Fedorova K, Kayumov A, Woyda K, Ilinskaja O, Forchhammer K (2013) Transcription factor TnrA inhibits the biosynthetic activity of glutamine synthetase in Bacillus subtilis. FEBS Lett 587:1293-1298.

Feinberg L, Foden J, Barrett T, Davenport KW, Bruce D, Detter C, Tapia R, Han C, Lapidus A, Lucas S, Cheng JF, Pitluck S, Woyke T, Ivanova N, Mikhailova N, Land M, Hauser L, Argyros DA, Goodwin L, Hogsett D, Caiazza N (2011) Complete genome sequence of the cellulolytic thermophile Clostridium thermocellum DSM1313. J Bacteriol 193:2906-2907. Fonknechten N, Chaussonnerie S, Tricot S, Lajus A, Andreesen JR, Perchat N, Pelletier E, Gouyvenoux M, Barbe V, Salanoubat M, Le Paslier D, Weissenbach J, Cohen GN, Kreimeyer A (2010) Clostridium sticklandii, a specialist in amino acid degradation: revisiting its metabolism through its genome sequence. BMC Genomics 11:555. Fonknechten N, Perret A, Perchat N, Tricot S, Lechaplais C, Vallenet D, Vergne C, Zaparucha A, Le Paslier D, Weissenbach J (2009) A conserved gene cluster rules anaerobic oxidative degradation of L-ornithine. J Bacteriol 191:3162-3167.

Formanek J, Mackie R, Blaschek HP (1997) Enhanced butanol production by Clostridium beijerinckii BA101 grown in semi-defined P2 medium containing 6 percent maltodextrin or gucose. Appl Environ Microbiol 63:2306-2310.

Golovchenko N, Belokopytov B, Chuvil'skaya N, Akimenko V (1985) Minimal synthetic culture medium for the bacterium Clostridium sticklandii. Appl Biochem Microbiol 20:430434.

Golovchenko NP, Belokopytov BF, Akimenko VK (1982) Catabolism of threonine in the bacterium Clostridium sticklandii. Biokhimiia 47:1159-1164.

Graentzdoerffer A, Pich A, Andreesen JR (2001) Molecular analysis of the grd operon coding for genes of the glycine reductase and of the thioredoxin system from Clostridium sticklandii. Arch Microbiol 175:8-18.

Harper CJ, Hayward D, Kidd M, Wiid I, van Helden P (2010) Glutamate dehydrogenase and glutamine synthetase are regulated in response to nitrogen availability in Myocbacterium smegmatis. BMC Microbiol 10:138.

Harty M, Nagar M, Atkinson L, Legay CM, Derksen DJ, Bearne SL (2014) Inhibition of serine and proline racemases by substrate-product analogues. Bioorg Med Chem Lett 24:390-

Herrmann G, Jayamani E, Mai G, Buckel W (2008) Energy conservation via electron-transferring flavoprotein in anaerobic bacteria. J Bacteriol 190:784-791. Hillmann F, Fischer RJ, Saint-Prix F, Girbal L, Bahl H (2008) PerR acts as a switch for oxygen tolerance in the strict anaerobe Clostridium acetobutylicum. Mol Microbiol 68:848-

Huang H, Singh V, Qureshi N (2015) Butanol production from food waste: a novel process for producing sustainable energy and reducing environmental pollution. Biotechnol Biofuels

Humbird D, Davis R, Tao L, Kinchin C, Hsu D, Aden A, Schoen P, Lukas J, Olthof B, Worley M, Sexton D, Dudgeon D (2011) Process design and economics for biochemical conversion of lignocellulosic biomass to ethanol. Dilute acid pretreatment and enzymatic hydrolysis of corn stover. National Renewable Energy Laboratory, Technical Report NREL/TP-5100-47764.

Huo YX, Cho KM, Rivera JG, Monte E, Shen CR, Yan Y, Liao JC (2011) Conversion of proteins into biofuels by engineering nitrogen flux. Nat Biotechnol 29: 346-351. Kabisch U, Gräntzdörffer A, Schierhorn A, Rücknagel KP, Andreesen JR, Pich A (1999) Identification of D-proline reductase from Clostridium sticklandii as a selenoenzyme and indications for a catalytically active pyruvoyl group derived from a cysteine residue by cleavage of a proprotein. J Biol Chem 274:8445-8454.

Kenklies J, Ziehn R, Fritsche K, Pich A, Andreesen JR (1999) Proline biosynthesis from L-ornithine in Clostridium sticklandii: purification of delta1-pyrroline-5-carboxylate reductase, and sequence and expression of the encoding gene, proC. Microbiology 145:819-826. Koltuniewicz AB (2014) Sustainable Process Engineering: Prospects and Opportunities. De Gruyter.

Köpke M, Held C, Hujer S, Liesegang H, Wiezer A, Wollherr A, Ehrenreich A, Liebl W, Gottschalk G, Dürre P (2010) Clostridium ljungdahlii represents a microbial production platform based on syngas. Proc Natl Acad Sci U S A 107:13087-13092. Kreimeyer A, Perret A, Lechaplais C, Vallenet D, Medigue C, Salanoubat M, Weissenbach J (2007) Identification of the last unknown genes in the fermentation pathway of lysine. J Biol Chem 282:7191-7197.

Lee J, Jang YS, Choi SJ, Im JA, Song H, Cho JH, Seung do Y, Papoutsakis ET, Bennett GN, Lee SY (2012) Metabolic engineering of Clostridium acetobutylicum ATCC 824 for isopropanol-butanol-ethanol fermentation. Appl Environ Microbiol 78:1416-1423.


Lee J, Yun H, Feist AM, Palsson BO, Lee SY (2008) Genome-scale reconstruction and in silico analysis of the Clostridium acetobutylicum ATCC 824 metabolic network. Appl Microbiol Biotechnol 80:849-862.

Lee JY, Jang YS, Lee J, Papoutsakis ET, Lee SY (2009) Metabolic engineering of Clostridium acetobutylicum M5 for highly selective butanol production. Biotechnol J. 4:1432-1440.

Leonhartsberger S, Korsa I, Bock A (2002) The molecular biology of formate metabolism in enterobacteria. J Mol Microbiol Biotechnol 4:269-276.

Li F, Hinderberger J, Seedorf H, Zhang J, Buckel W, Thauer RK (2008) Coupled ferredoxin and crotonyl coenzyme A (CoA) reduction with NADH catalyzed by the butyryl-CoA dehydrogenase/Etf complex from Clostridium kluyveri. J Bacteriol, 190:843-850. Liao C, Seo SO, Celik V, Liu H, Kong W, Wang Y, Blaschek H, Jin YS, Lu T (2015) Integrated, systems metabolic picture of acetone-butanol-ethanol fermentation by Clostridium acetobutylicum. Proc Natl Acad Sci USA 112:8505-8510.

Lin SK, Pfaltzgraff LA, Davila LH, Mubofu EB, Abderrahim S, Clark JH, Koutinas AA, Kopsahelis N, Stamatelatou K, Dickson F, Thankappan S, Mohamed Z, Brocklesby R, Luque R (2013) Food waste as a valuable resource for the production of chemicals, materials and fuels. Current situation and global perspective. Energy Environ Sci 6:426-464. Madigan MT, Martinko JM, Parker J (1997) Brock Biology of Microorganisms. Eighth Edition, Prentice Hall.

Maeda T, Sanchez-Torres V, Wood TK (2008) Metabolic engineering to enhance bacterial hydrogen production. Microb Biotechnol 1:30-39.

Manjasetty BA, Chance MR, Burley SK, Panjikar S, Almo SC (2014) Crystal structure of Clostridium acetobutylicum Aspartate kinase (CaAK): An important allosteric enzyme for amino acids production. Biotechnol Rep 3:73-85.

Mast FD, Ratushny AV, Aitchison JD (2014) Systems cell biology. J Cell Biol206 :695-706. Mattam AJ and Yazdani SS (2013) Engineering E. coli strain for conversion of short chain fatty acids to bioalcohols. Biotechnol Biofuels 6: 128.

Mayank R, Ranjan A, Moholkar VS (2013) Mathematical models of ABE fermentation: review and analysis. Crit Rev Biotechnol 33:419-447.

Mead GC (1971) The Amino Acid-fermenting Clostridia. J Gen Microbiol 67:47-56. Mielenz JR (2011) Biofuels from protein. Nat Biotechnol 29:327-328. Milne CB, Eddy JA, Raju R, Ardekani S, Kim PJ, Senger RS, Jin YS, Blaschek HP, Price ND (2011). Metabolic network reconstruction and genome-scale model of butanol-producing strain Clostridium beijerinckii NCIMB 8052. BMC Syst Biol 5:130.

Müller V, Grüber G (2003) ATP synthases: structure, function and evolution of unique energy converters. Cell Mol Life Sci 60:474-494.

Nagarajan H, Sahin M, Nogales J, Latif H, Lovley DR, Ebrahim A, Zengler K (2013) Characterizing acetogenic metabolism using a genome-scale metabolic reconstruction of Clostridium ljungdahlii. Microb Cell Fact 12:118. Nisman B (1954) The Stickland reaction. Bacteriol Rev 18:16-42.

Nölling J, Breton G, Omelchenko MV, Makarova KS, Zeng Q, Gibson R, Lee HM, Dubois J, Qiu D, Hitti J, Wolf YI, Tatusov RL, Sabathe F, Doucette-Stamm L, Soucaille P, Daly MJ,

Bennett GN, Koonin EV, Smith DR (2001) Genome sequence and comparative analysis of the solvent-producing bacterium Clostridium acetobutylicum. J Bacteriol 183:4823-4838. Otero JM, Nielsen J (2010) Industrial systems biology. Biotechnol Bioeng 105:439-460. Papoutsakis ET (1984) Equations and calculations for fermentations of butyric-acid bacteria. Biotechnol Bioeng 26:174 -187.

Paster B, Russell JB, Yang CMJ, Chow JM, Woese CR, Tanner R (1993) Phylogeny of the Ammonia-Producing Ruminal Bacteria Peptostreptococcus anaerobius, Clostridium sticklandii, and Clostridium aminophilum sp. International J Syst Bacteriol 43:107-110. Ramsay IR, Pullammanappallil PC (2001) Protein degradation during anaerobic wastewater treatment: derivation of stoichiometry. Biodegradation 12: 247-257.

Ratledge C, Wynn JP (2014) The biochemistry and molecular biology of lipid accumulation in oleaginous microorganisms. Adv Appl Microbiol 51:1-51.

Roberts SB, Gowen CM, Brooks JP, Fong SS (2010) Genome-scale metabolic analysis of Clostridium thermocellum for bioethanol production. BMC Syst Biol 4:31. Rossmann R, Sawers G, Bock A (1991) Mechanism of regulation of the formate-hydrogenlyase pathway by oxygen, nitrate, and pH: definition of the formate regulon. Mol Microbiol 5:2807-2814.

Salimi F, Zhuang K, Mahadevan R (2010) Genome-scale metabolic modeling of a clostridial co-culture for consolidated bioprocessing. Biotechnol J 5:726-738.

Sanchez S, Demain AL (2008) Metabolic regulation and overproduction of primary metabolites. Microbial Biotechnol 1: 283-319.

Sauter M, Bohm R, Bock A (1992) Mutational analysis of the operon (hyc) determining hydrogenase 3 formation in Escherichia coli. Mol Microbiol 6:1523-1532 Schäfer R, Schwartz AC (1976) Catabolism of purines in Clostridium sticklandii. Zentralbl Bakteriol Orig A 235:165-172.

Schönicke P, Shahab R, Hamann R, Kamm B (2015) Microbial Life on Green Biomass and Their Use for Production of Platform Chemicals. B. Kamm (ed.), Microorganisms in Biorefineries, Microbiol Monographs 26:21-49.

Schwartz AC, Schäfer R (1973) New amino acids, and heterocyclic compounds participating

in the Stickland reaction of Clostridium sticklandii. Arch Microbiol. 93:267-276.

Seedorf H, Fricke WF, Veith B, Brüggemann H, Liesegang H, Strittmatter A, Miethke M,

Buckel W, Hinderberger J, Li F (2008) The genome of Clostridium kluyveri, a strict anaerobe

with unique metabolic features. Proc Natl Acad Sci USA 105;2128-2133.

Senger RS (2010) Biofuel production improvement with genome-scale models: The role of

cell composition. Biotechnol J 5:671-685.

Senger RS, Papoutsakis ET (2008a) Genome-scale model for Clostridium acetobutylicum: Part I. Metabolic network resolution and analysis. Biotechnol Bioeng 101: 1036-52. Senger RS, Papoutsakis ET (2008b) Genome-scale model for Clostridium acetobutylicum: Part II. Genome-scale model for Clostridium acetobutylicum: Part II. Development of specific proton flux states and numerically determined sub-systems. Biotechnol Bioeng 101:1053 -1071

Sengupta T, Bhushan M, Wangikar PP (2013) Metabolic modeling for multi-objective optimization of ethanol production in a Synechocystis mutant. Photosynth Res 118: 155-165.

Shen D, Yin J, Yu X, Wang M, Long Y, Shentu J, Chen T (2017) Acidogenic fermentation characteristics of different types of protein-rich substrates in food waste to produce volatile fatty acids. Bioresour Technol 227:125-132.

Shinto H, Tashiro Y, Yamashita M, Kobayashi G, Sekiguchi T, Hanai T, Kuriya Y, Okamoto M, Sonomoto K (2007) Kinetic modeling and sensitivity analysis of acetone-butanol-ethanol production. J Biotechnol 131: 45-56.

Simeonidis E, Price ND (2015) Genome-scale modeling for metabolic engineering. J Ind Microbiol Biotechnol 42:327-338.

Stadtman T (1973) Lysine metabolism by Clostridia. Adv Enzymol 38: 413-448.

Stadtman TC (1954) On the metabolism of an amino acid fermenting Clostridium. J Bacteriol


Stadtman TC and Elliott P (1957) Studies on the enzymic reduction of amino acids. II. Purification and properties of D-proline reductase and a proline racemase from Clostridium sticklandii. J Biol Chem 228:983-997.

Stadtman TC, McClung LS (1957) Clostridium sticklandii nov. spec. J Bacteriol 73: 218-219. Stadtman TC, Renz P (1968) Anaerobic degradation of lysine. V. Some properties of the cobamide coenzyme-dependent beta-lysine mutase of Clostridium sticklandii. Arch Biochem Biophys 125:226-39.

Stadtman TC, WhiteJr FH (1954) Tracer studies on ornithine, lysine, and formate metabolism in an amino acid fermenting Clostridium. J Bacteriol 67:651-657.

Stickland LH (1934) Studies in the metabolism of the strict anaerobes (genus Clostridium): The chemical reactions by which Clostridium sporogenes obtains its energy. Biochem J 28:1746-1759.

Tang KH, Harms A, Frey PA (2002) Identification of a novel pyridoxal 5'-phosphate binding site in adenosylcobalamin-dependent lysine 5,6-aminomutase from Porphyromonas gingivalis. Biochem 41:8767-8776

ter Schure EG, van Riel NA, Verrips CT (2000) The role of ammonia metabolism in nitrogen catabolite repression in Saccharomyces cerevisiae. FEMS Microbiol Rev 24:67-83. Tolonen AC, Zuroff TR, Ramya M, Boutard M, Cerisy T, Curtis WR (2015) Physiology, genomics, and pathway engineering of an ethanol-tolerant strain of Clostridium phytofermentans. Appl Environ Microbiol 81:5440-5448.

Tracy BP, Jones SW, Fast AG, Indurthi DC, Papoutsakis ET (2012) Clostridia: the importance of their exceptional substrate and metabolite diversity for biofuel and biorefinery applications. Curr Opin Biotechnol 23:364-381.

Tseng CH, Yang CH, Lin HJ, Wu C, Chen HP (2007) The S subunit of D-ornithine aminomutase from Clostridium sticklandii is responsible for the allosteric regulation in D-alpha-lysine aminomutase. FEMS Microbiol Lett 274:148-153

Vlysidis A, Binns M, Webb C, Theodoropoulos C (2011) A techno-economic analysis of biodiesel biorefineries: assessment of integrated designs for the co-production of fuels and chemicals. Energy 36:4671-4683.

Wagner M, Andreesen JR (1995) Purification and characterization of threonine dehydrogenase from Clostridium sticklandii. Arch Microbiol 163: 286-290.

Wallenius J, Viikilä M, Survase S, Ojamo H, Eerikäinen T (2013) Constraint-based genome-scale metabolic modeling of Clostridium acetobutylicum behavior in an immobilized column. Bioresour Technol 142: 603-610.

Wang Y, Li X, Mao Y, Blaschek HP (2011) Single-nucleotide resolution analysis of the transcriptome structure of Clostridium beijerinckii NCIMB 8052 using RNA-Seq.BMC Genomics 30:12-479.

Wong YM, Juan JC, Gan HM, Austin CM (2014) Draft Genome Sequence of Clostridium bifermentans Strain WYM, a Promising Biohydrogen Producer Isolated from Landfill Leachate Sludge. Genome Announc. doi: 10.1128/genomeA.00077-14. Yin B, Liu HB, Wang YY, Bai J, Liu H, Fu B (2016) Improving volatile fatty acids production by exploiting the residual substrates in post-fermented sludge: protease catalysis of refractory protein. Bioresour Technol 203:124-131.

Yoo M, Bestel-Corre G, Croux C, Riviere A, Meynial-Salles I, Soucaille P (2015) A Quantitative system-scale characterization of the metabolism of Clostridium acetobutylicum. MBio 6. pii: e01808-15.

Yoshida A, Nishimura T, Kawaguchi H, Inui M, Yukawa H (2005) Enhanced hydrogen production from formic acid by formate hydrogen lyase-overexpressing Escherichia coli strains. Appl Environ Microbiol 71:6762-6768.

Zinecker H, Andreesen JR, Pich A (1998) Partial purification of an iron-dependent L-serine dehydratase from Clostridium sticklandii. J Basic Microbiol 38:147-155.

Fig. 1 International Energy Statistics for global biofuel production and consumption

Fig. 2 Genome-scale metabolic information of Clostridium sticklandii DSM 519 and related Clostridium species, collected from the MetaCyc database. We compared metabolic pathways (a), metabolic properties (b), membrane transporter (c), and transcriptional units to infer genomic similarities and dissimilarities across the closely related Clostridial genomes. (CST: C. sticklandii; CBI: C. bifermentans; CAM: C. aminophilum; CAC: C. acetobutylicum; CBE: C. beijerinckii; CCE: C. cellulolyticum; CLJ: C. ljungdahlii; CTH: C. thermocellum)

Fig. 3 Central metabolic information of Clostridium sticklandii DSM 519 and related Clostridium species, collected from the MetaCyc database. In our study, various subsystems involved in the metabolism of carbohydrate (a), amino acid (b), lipid (c), nucleotide (d) and energetic process (e) were compared to capture the metabolic abundance in environmental niche across the closely related Clostridial genomes (CST: C. sticklandii; CBI: C. bifermentans; CAM: C. aminophilum; CAC: C. acetobutylicum; CBE: C. beijerinckii; CCE: C. celhdolyticam; CLJ: C. Ijimgdahlii; CTH: C. thermocellum)

(a) Carbohydrate metabolism

CST CBI CAM CAC CBE CCE CIJ CTH U Ail ab oil: m U Catabcliî.m


(с) Lipid metabolim

CST CBI CAM CAC CBE CCE CIJ CTH 'Anabolimi J Catabolimi


WAnaboliim Ü Catabolimi

(e) Energetic metabolism


Г ¿Та

Fig. 4 The proposed pathways for the catabolism of amino acids L-asparagine, L-histidine, L-threonine, L-proline, L-glutamate, L-isoleucine, and L-methionine in Clostridium sticklandii DSM 519. We proposed this pathway based on the metabolic reactions collected from the MetaCyc database.

1 I ItlTllllIi.

L-Omi thine


,_ 2-i

I Л sji.I?;s^mi



▼L-Glutamate y-semi aldeh CO,

^de 4.12

1 Pyrroline-5 carboxylate




2-Oxoglutaiate .1.1.-

5 Aminopentanoate



-Hydroxyglutarate Ace

2-1 [ydr о xyglutaryl -

tyl-CoA Acetate


Imidazolone-5 pronale

)miinino-L-glutamate V^L-GIutamate у

2-Amino-30xobutanoate L-Threonine ^ * »Acetaldehydi

Amino acetoneм


Glutaconyl-C 1.1.70

Butanoyl-CoA Acetate *




L-isoleucine 2-Oxogluturate

,д L-Glutamate

3-Methyl 2-oxopentanoate

— Crotonyl-CoA



NH^ 143 ' Metylglyoxal


>7,8-Dihydrobi opterin 1.5.1.-

H20 Tetrahydrobiopterin

Acetyl CoA ^J

Glycine ^ N-Iipoyl- L-Lysine

■— Glycine

^^ L-Phenylalanine+ L-Tyiosin 4<^Hydrox>d-tetrahydtobiopterin

N-Diaminomethyl dihydrolipoyl L-Lysine

N-Dihydr clip 03d — L-Lysine

Acetyl CoA



3-Hyroxybutan ^i-CoA 2 -Methyl er ot on ojl-CoA

2-Methyl-3 hydroxybutyiyl-CoA




► 2-Amino prop-2-enoate



2-Immunobutanoate Methanethiol +NH3 Л

2 Oxobutanoate

- 2 Methyl: .cetyl-CoA

Propanoyl-CoA .

Proponyl phosphate --¥ Propanoate

Fig. 5 The proposed pathway for protein catabolism-directed biofuel production in Clostridium sticklandii DSM 519. We proposed this pathway based on the metabolic reactions collected from the MetaCyc database for amino acid catabolism associated acetate, n-butanol, n-butyric acid, ethanol and hydrogen production. Enzyme commission was assigned according to the Kyoto Encyclopedia of Genes and Genomes database entries. Pyruvate was considered as a main metabolic precursor for the synthesis of organic solvents and organic acids in the proposed pathway. Ethanol is simply produced from acetaldehyde by alcohol dehydrogenase. Butanoyl-coA is a key metabolic switch to synthesis either n-butanol or n-butyric acid. Stickland reactions are a great concern of interest for amino acid catabolism by C. sticklandii. It has a separate pathway for lysine catabolism that directs n-butanol and n-butyric acid production. Hydrogen production is coupled with formate metabolism which may be directed by accumulation of pyruvate in the cytoplasm.

Stickland reactions


Formate metabolism

1 12.72 10-Foimyl-lelrahydrofolale




a[methyl-Co(m) coninoidFe-SProtein] .

—P04 + Thioredoxin , 1.21.42

Reduced ±ioredoxin

^■»CoA Acetoac dyl-CoA



^NAHT (S)-3-Hy diGsybutanoyl-C oA

Butanol biosynthesis

NAD"1 i

Butanal 4—


Crotonyl-CoA "

Reduced flavoprotein

Oxidized flavoprotein


»•ATP n-Butanoate

Butyric acid biosynthesis

L-3 -Aminoburyryl-CoA "

3 -Keto- 5 -aminphe cleavage ei

Lysine catabolism

L-Lysine X

3.6-Aiaminohexanoate 3.5 -Diaminohexanoaie


:nzyme (J

le (Kce)

Fig. 6 Metabolic map of Clostridium sticklandii DSM 519 genome for the production of biofuels from amino acid catabolism using model-driven systems metabolic engineereing. It was constructed from its complete genome by using Kyoto Encyclopedia of Genes and Genomes metabolic map generator. Amino acid catabolism-directed biofuel synthesis is outlined in this map.

Glycan biosynthesis Carbohydrate metabolism Amino acid metabolism Energy metabolism

Lipid metabolism Secondary metabolism Nucleotide metabolism

.Ammo acid catabolism-directed biofliel synthesis

Table 1 Genes involved in amino acids metabolism of Clostridium sticklandii DSM 519. Information of genes and enzymes listed in this table were collected for individual amino acid catabolism from the MetaCyc database.

Amino acids Gene EC Enzyme

Arginine speA Arginine decarboxylase

Arginine speB Agmatinase

Asparagine ansA Asparaginase

Aspartate yhdR Aspartate transaminase

D-Serine dsdA D-Serine ammonia-lyase

L-Serine sdaAA L-Serine ammonia-lyase

Glutamate gdhA Glutamate dehydrogenase

Glutamate gctA Glutaconate CoA-transferase

Glutamate gcdC Glutaconyl-CoA decarboxylase

Glutamate scad Short-chain acyl-CoA dehydrogenase

Glutamate atoA^toD Acetate CoA-transferase

Glutamine pdxS^snB Glutaminase

Glycine gcvPA^cvPB^ Glycine dehydrogenase (aminomethyl-

coL transferring)

Glycine gcv^acoL Aminomethyltransferase

Glycine acoL Dihydrolipoyl dehydrogenase

Histidine hutH Histidine ammonia-lyase

Histidine hutU Urocanate hydratase

Histidine hutI Imidazolonepropionase

Histidine hutG Formimidoylglutamase

Isoleucine ilvE Branched-chain-amino-acid transaminase

Isoleucine ecm 2-Methyl-branched-chain-enoyl-CoA reductase

Isoleucine paaF Enoyl-CoA hydratase

Isoleucine fabG 3-Hydroxy-2-methylbutyryl-CoA


Isoleucine atoB Acetyl-CoA C-acetyltransferase

Lysine speA Lysine decarboxylase

Methionine megL Methionine y-lyase

Phenylalani ti A pah Phenylalanine 4-monooxygenase

ne Phenylalani ti p pcbD1 4a-Hydroxytetrahydrobiopterin dehydratase

ne Threonine tdh L-Threonine 3-dehydrogenase

Threonine kbl Glycine C-acetyltransferase

Threonine tdh L-Threonine 3-dehydrogenase

Threonine aoc3 Primary-amine oxidase

Threonine ltaE|4.1.2. L-Threonine aldolase|low-specificity L-

48 threonine aldolase

Threonine eutE Acetaldehyde dehydrogenase (acetylating)

Citrulline arcB Ornithine carbamoyltransferase

Citrulline arcC Carbamate kinase

Ornithine arcB Ornithine cyclodeaminase

Ornithine orr Ornithine racemase

Ornithine oat Ornithine aminotransferase

Ornithine oraE^raS D-Ornithine 4,5-aminomutase

Ornithine ord 2,4-Diaminopentanoate dehydrogenase

Ornithine proC Pyrroline-5-carboxylate reductase

Ornithine prdF Proline racemase

Table 2 Genomic information of closely related Clostridium species to Clostridium sticklandii DSM 519, collected from respective literatures and MetaCyc database.

Code Genome Strain Size (Mbp) Coding genes RNA genes References

CST C. sticklandii DSM 519 2.7 2573 77 Fonknechten et al. 2010

CBI C. bifermentans ATCC 638 3.6 3176 125 Wong et al. 2014

CAM C. aminophilum DSM 10710 3.1 2240 67 -

CAC C. acetobutylicum ATCC 824 4.1 3778 107 Nolling et al. 2001

CBE C. beijerinckii NCIMB 8052 6.0 5020 140 Wang et al. 2011

CCE C. cellulolyticum H10 4.0 3391 88 -

CLJ C. ljungdahlii DSM 13528 4.6 4184 99 Köpke et al. 2010

CTH C. thermocellum DSM 1313 3.5 2911 71 Feinberg et al. 2011