**Decarboxylation of Pyruvate to Acetaldehyde for Ethanol Production by Hyperthermophiles**

#### **Mohammad S. Eram and Kesen Ma**

**Abstract:** Pyruvate decarboxylase (PDC encoded by *pdc*) is a thiamine pyrophosphate (TPP)-containing enzyme responsible for the conversion of pyruvate to acetaldehyde in many mesophilic organisms. However, no *pdc*/PDC homolog has yet been found in fully sequenced genomes and proteomes of hyper/thermophiles. The only PDC activity reported in hyperthermophiles was a bifunctional, TPP- and CoA-dependent pyruvate ferredoxin oxidoreductase (POR)/PDC enzyme from the hyperthermophilic archaeon *Pyrococcus furiosus*. Another enzyme known to be involved in catalysis of acetaldehyde production from pyruvate is CoA-acetylating acetaldehyde dehydrogenase (AcDH encoded by *mhpF* and *adhE*). Pyruvate is oxidized into acetyl-CoA by either POR or pyruvate formate lyase (PFL), and AcDH catalyzes the reduction of acetyl-CoA to acetaldehyde in mesophilic organisms. AcDH is present in some mesophilic (such as clostridia) and thermophilic bacteria (e.g., *Geobacillus* and *Thermoanaerobacter*). However, no AcDH gene or protein homologs could be found in the released genomes and proteomes of hyperthermophiles. Moreover, no such activity was detectable from the cell-free extracts of different hyperthermophiles under different assay conditions. In conclusion, no commonly-known PDCs was found in hyperthermophiles. Instead of the commonly-known PDC, it appears that at least one multifunctional enzyme is responsible for catalyzing the non-oxidative decarboxylation of pyruvate to acetaldehyde in hyperthermophiles.

Reprinted from *Biomolecules*. Cite as: Eram, M.S.; Ma, K. Decarboxylation of Pyruvate to Acetaldehyde for Ethanol Production by Hyperthermophiles. *Biomolecules* **2013**, *3*, 578-596.

#### **1. Introduction**

Thermophilic microorganisms can be categorized into several groups: moderate thermophiles, or simply thermophiles, are those that grow optimally between 50–64 °C, extreme thermophiles are those with optimal growth temperatures between 65–79 °C. Finally, the organisms that can grow optimally above 80 °C are called hyperthermophiles. Hyperthermophiles can survive at room temperature for long periods of time, but cannot propagate at temperatures lower than 50 °C [1–5].

Hyperthermophilic microorganisms are widely studied for their remarkable scientific values and industrial potential. It is generally accepted that hyperthermophilic enzymes have very similar functions and catalytic mechanisms to their mesophilic ones. However, most of the hyperthermophilic enzymes characterized so far have optimum temperatures close to the host organism's growth requirements; thus, due to their intrinsic properties, the enzymes are stable and active under conditions that are detrimental to their mesophilic counterparts. Interestingly, enzymes from such extremophiles usually show increased stability not to one, but to several environmental factors. There are a number of advantages for using the hyper/thermophilic enzymes (especially for industrial applications) over their mesophilic partners, including the reduced risk of contamination during industrial processes, the possibility of self-distillation of the products at high temperatures, decreased viscosity and increased solubility/bioavailability of both the enzyme and the substrate(s) leading to minimization of the diffusion limitations, and elimination of the costly transportation under cold temperature-controlled environment [6–10].

The aforementioned properties along with high demand from the biotech industries for the development of "tailor-made" bio-catalysts have created significant attention on the biochemistry and physiology of these organisms. Enzymes such as proteases, polymerases, hydrolases, isomerases, lipases, and oxidases are studied for their potential biotechnological exploitation, with the ultimate goal of using them or their products (mainly enzymatic) for biotechnological applications.

It is also appealing to determine the molecular, biochemical, physiological, and evolutionary mechanisms that enable these organisms to adapt to such hostile environments. Furthermore, hyperthermophilic proteins serve as models to study enzyme evolution, structure-function relationships and catalytic mechanisms. The findings of these studies can benefit the design of highly stable and active enzymes to be used for many applications [6,11,12].

#### **2. Microbial Production of Ethanol**

Demand for biofuel as substitutes for oil-based fuels is increasing due to concerns related to national security, economic stability, environmental impacts, and global warming. The national research council of the United States has predicted that, by 2020, half of all organic chemicals and materials will be produced by bioconversion. Bio-ethanol can also be used as a precursor for many other commodity chemicals, such as acetaldehyde, acetic acid and their derivatives [13–15].

The most commonly used ethanologenic organisms being intensively studied or already in use for industrial-scale production are *Zymomonas mobilis*, *Saccharomyces cervisiae*, *Escherichia coli*, and *Klebsiella oxytoca*. Substantial attention and effort have been dedicated to redirecting the metabolic pathways of these and others towards higher yield of ethanol production, by means of metabolic engineering [16–18].

However, lack of suitable microorganisms that can efficiently convert the raw biomaterials to bio-ethanol has been one of the main obstacles to widespread use of bio-fuels. In addition to the ability to ferment a wide variety of sugars, some other features must be considered when choosing organisms for industrial-scale bio-ethanol production. These important features include but are not limited to the ability to have high ethanol yield, tolerance to fermentation products/by-products, simple growth requirements, and the ability to grow under conditions that prevent contaminating organisms from growing [14,16].

Production of bio-ethanol using thermophilic and hyperthermophilic organisms is the focus of many research groups. Extremophiles in general and hyperthermophiles in particular are outstanding organisms that produce highly stable enzymes due to their natural habitats, and many of them are able to tolerate changes in environment; making them good candidates for bio-ethanol production [19].

Several distinct advantages are associated with using thermophiles over mesophiles, including high temperatures and the mostly anaerobic nature of thermophilic organisms, which result in elimination of oxygenation and cooling of the fermenter. Another aspect is improved solubility of many reaction components at elevated temperatures [20]. In addition, the high temperature of the process leads to lowering the viscosity of reaction mixtures, causing improved production yields. Various thermophiles can ferment hexose and/or pentose sugars, as well as more complex substrates such as cellulose and xylan in some cases. Many of these organisms and their enzymes are relatively resistant to sudden pH or temperature changes and high concentrations of solvents [21–23]. High temperatures can result in lower gas solubility and significantly decrease the risk of process failure and product loss due to contamination that is the common problem in the yeast-based fermentation system. At the same time, high temperatures lower the cost of ethanol recovery due to the high volatility of ethanol at high fermentation temperatures [14,19,24,25]. However, there are some disadvantages associated with using hyperthermophiles, the most important one being their intrinsic low substrate tolerance and product/by-product inhibition [26,27]. Moreover, some of these organisms are mixed-fermenters that result in production of sometimes too many types of products during growth [14,16].

Application of metabolic engineering approaches has had a great impact on elimination of the problems associated with using thermophiles, and led to development of strains with bio-ethanol yields that are almost equal to those of the yeast-based systems. Members of the genus C*lostridium*, especially thermophilic members such as *Clostridium thermocellum*, have been studied intensively due to their competence in production substantial amounts of ethanol, butanol and hydrogen [24,28,29]. Members of the genus *Thermoanaerobacter*, including *T. ethanolicus*, *T. tengcongensis*, and *T. pentosaceus* are extremely thermophilic bacteria that are well studied for their high ethanol production potential especially from pentoses [30–34]. The genus *Geobacillus* has been studied widely for bio-ethanol production potential [19,29,35,36]. Production of ethanol, although at lower concentrations, has also been reported for the extremely thermophilic *Caldicellulosiruptor* species that includes *C. owensensis* [37], *C. kristjanssonii* [38], and *C. saccharolyticus* [39]*.*

Compared to the thermophilic ethanol producers, very little is known about the ethanol production levels and pathways in the extremely thermophilic and hyperthermophilic microorganisms. It was shown that the peptide- and carbohydrate-fermenting hyperthermophilic archaeon *Pyrococcus furiosus* can produce H2, CO2, acetate, alanine, and small amounts of ethanol [40]. The strictly anaerobic archaeon *Thermococcus* sp. strain ES1 produced some ethanol and butanol when cultures were grown at low concentrations of elemental sulfur [41]. The production of ethanol as an end product of fermentation was also shown in the hyperthermophilic anaerobic archaeon *Thermococcus guaymasensis* [42] and more recently in the autotrophic hyperthermophile, *Thermococcus onnurineus* [43]. Within the bacterial hyperthermophiles, traces of ethanol have been reported in cultures of different Thermotogales including *T. hypogea* [44], *T. lettingae* [45], *T. neapolitana* [46], *Kosmotoga olearia* [47], and *Thermosipho affectus* [48].

#### **3. Key Enzymes Involved in Ethanol Production**

One of the key enzymes in both ethanol production pathways is alcohol dehydrogenase. Alcohol dehydrogenases are members of the oxidoreductase family and are present in all three domains of life [49,50]. They belong to the dehydrogenase/reductase superfamily of enzymes and catalyze the reversible inter-conversion of alcohols to corresponding aldehydes or ketons. ADHs can be classified based on their cofactor requirements: (I) the flavin adenine di-nucleotide (FAD)-dependent ADHs; (II) the pyrollo-quinoline quinone (PQQ), heme or cofactor F420 dependent ADHs; (III) NAD(P)-dependent ADHs [49,51]. Alternatively, they can be divided into three major groups based on their molecular size and metal contents: the first group is known as zinc-dependent long chain alcohol dehydrogenase; which have sizes of 300–900 amino acids, the second group is the short chain alcohol dehydrogenase: which contain no metal ions and have approximate lengths of 250 amino acids; and the third group is the long-chain iron dependent ADHs; with a length of 385– 900 residues [49–52].

Many different ADHs have been characterized from various thermophilic and hyperthermophilic bacteria and archaea, with a majority of them being NAD(P)-dependent. Some of the more recently characterized hyper/thermophilic ADHs are those from *P. furiosus* [53,54], *Thermococcus hydrothermalis* [55], *Thermococcus kodakarensis* [56–58], *Thermococcus sibiricus* [59,60], *Thermococcus guaymasensis* [42], *Sulfolobus acidocaldarius* [61], *Thermococcus* strain ES1 [62], *Aeropyrum pernix* [63], *Thermotoga hypogea* [64], and *Pyrobaculum aerophilum* [65].

Although there is a relatively long list of ADHs isolated and characterized from thermophilic and hyperthermophilic archaea and bacteria, with the physiological roles of several proposed to be in the reduction of aldehydes to alcohols, other enzymes involved in the ethanol production pathways are not well characterized, especially the enzyme(s) that catalyze the production of acetaldehyde from pyruvate.

#### **4. Pathways for the Production of Acetaldehyde from Pyruvate**

Pyruvate is an intermediate in the central metabolism of carbohydrates [66,67], and it can be converted to acetaldehyde that will eventually be reduced to ethanol using one of the following two pathways:

(1) A two-step pathway that is used by yeast and a few bacteria like *Zymomonas mobilis* [68] and *Sarcina ventriculi* [69]. In this pathway pyruvate is non-oxidatively decarboxylated to acetaldehyde and carbon dioxide, which is catalyzed by pyruvate decarboxylase (PDC). Acetaldehyde is then converted to ethanol that is catalyzed by ADH (Figure 1);

(2) A three-step pathway that is more widespread in bacteria. Pyruvate is oxidatively decarboxylated to acetyl-coenzyme A (acetyl-CoA) by the metalloenzyme pyruvate ferredoxin oxidoreductase (POR) and/or pyruvate formate lyase (PFL). Acetyl-CoA is then converted to acetaldehyde by a CoA-dependent-acetylating acetaldehyde dehydrogenase (AcDH). Finally, acetaldehyde is reduced to ethanol by ADH.

The key metabolite for the two known pathways is acetaldehyde. The thiamine pyrophosphate (TPP)-dependent enzyme pyruvate decarboxylase is the only enzyme proficient at direct conversion of pyruvate to acetaldehyde. Interestingly, a majority (but not all) of the enzymes which are involved in the acetaldehyde production pathways are members of the superfamily of TPP-dependent enzymes, which includes PDC, POR, and PFL [70,71].

**Figure 1.** Two pathways of ethanol production from pyruvate. POR; Pyruvate ferredoxin oxidoreductase; PFL; Pyruvate formate lyase, AcDH; Acetaldehyde dehydrogenase, ADH; Alcohol dehydrogenase, PDC; pyruvate decarboxylase; CoASH; coenzyme A, Fdox; oxidized ferredoxin, Fdred; reduced ferredoxin.

TPP, also known as thiamine diphosphate (ThDP), is composed of an aromatic methylaminopyrimidine ring, linked to a methyl thiazolium ring via. a methylene group with a pyrophosphate group attached to a hydroxylethyl side chain. TPP is derived from the water-soluble vitamin B1 and is the most common cofactor for enzymes that catalyze the cleavage and formation of carbon-carbon bonds next to a carbonyl group; hence TPP-dependent enzymes are involved in a wide range of metabolic pathways. Unlike many other cofactors (e.g., nicotinamide adenine dinucleotide, NADH) which are basically co-reactants, TPP remains at the enzymes' catalytic center and is directly involved in the catalysis of the reaction [72]. The reactions catalyzed by TPP-dependent enzymes can be divided into at least three groups: the oxidative reactions, non-oxidative reactions, and carboligation reactions [73].

#### **5. Pyruvate Decarboxylase (PDC)**

In 1911, Neuberg and Karczag for the first time described the decarboxylation of pyruvate to acetaldehyde in *S. cerevisiae*. In 1922, the same research group detected the potential of yeast in the formation of C-C bonds. Neuberg named the new enzyme "carboligase", and assumed it to exist apart from "Į-carboxylase" (PDC) in yeast [74]. However, the preliminary characterization of the enzymes' cofactor was delayed until 1937, when Lohmann and Schuster analyzed structure of the enzymes' cofactor to be "cocarboxylase" or "aneurinpyrophosphate" or thiamin diphosphate [73].

The enzyme catalyzes non-oxidative decarboxylation of Į-keto acids to produce a corresponding aldehyde and carbon dioxide. The most extensively examined enzymes of this group are the ones from *Saccharomyces cerevisiae* and its bacterial counterpart *Z. mobilis*. In addition to decarboxylation of pyruvate, PDC also catalyzes the enantio-selective formation of 2-hydroxy ketons via. carboligase side reactions.

PDC, or its gene (*pdc*), is found to be widely distributed in fungi and higher plants but it is relatively rare in prokaryotes and unknown in animals. In fungi, PDC is found in *Saccharomyces cerevisiae*, *Saccharomyces carlsbergensis* (also known as *S. pastorianus*) and *Saccharomyces uvarum*, *Neurospora crassa*, members of the *Kluyveromyces* species, members of the *Aspergillus* species, *Hanseniaspora uvarum*, *Schizosaccharomyces pombe*, and in *Candida* (*Torulopsis*) *glabrata*. PDC is present in a variety of plants, including maize (*Zea maize*), parsnip, orange, pea (*Pisum sativum*), jack bean, sweet potato, wheat, cotton wood, soybean and rice (*Oryza sativa*). In prokaryotes, PDC is found and studied in *Z. mobilis*, *Sarcina ventriculi*, *Clostridium botulinum*, *Acetobacter* species, *Zymobacter palmae*, and in *Erwinia amylovora* [75–79]. So far there has been no report on finding PDC/*pdc* homolog in thermophilic or hyperthermophilic bacteria or in any of the members of the third major evolutionary lineage of life, archaea as a whole [76–78,80].

PDCs from different organisms show at least a 30% identity at the amino acid level and most of them are composed of subunits of 562–610 amino acid residues. The holoenzyme is usually composed of four identical or non-identical subunits of approximately 60 kDa (ensuing in a total mass of about 240 kDa) in which every two subunits binds tightly (but not covalently) to a set of cofactors including TPP and Mg2+ ion. PDCs with four subunits are often arranged as a dimer of dimers, with multiple close contacts within the dimers and several contacts between the dimers. The contact area between two related dimers forms the "V" conformation that is a common property of all TPP-dependent enzymes studied so far, and it also has an essential role in cofactor binding for this group of enzymes [81,82].

The catalytic mechanism of PDC for the most part follows the principles of catalytic mechanisms of other TPP-dependent enzymes: in brief, carbonyl addition of pyruvate to the reactive C2 atom of the cofactor thiazolium ring [73] yields the intermediate 2-(2-lactyl)-TDP (LTDP). The subsequent release of carbon dioxide produces resonating carbanion/enamine forms of 2-(1-hydroxyethyl)-TDP (HETDP, also known as hydroxyethylidene-TPP). The resonating form is considered to be a central and highly reactive intermediate state in TPP-dependent enzymes acting on pyruvate. However, unlike most other TPP-dependent enzymes in which the intermediate is oxidized, the carbanion/enamine in PDC is protonated at the C2Į position, yielding C2Į-hydroxylethylthiamine diphosphate (HETDP) before the final release of acetaldehyde completes the reaction [72,83,84].

Crystal structures of several pyruvate decarboxylases are solved particularly from yeasts and *Z. mobilis* [81,85–87]. The active sites of these enzymes are also studied comprehensively using site-directed mutagenesis [88–90].

#### **6. Pyruvate Ferredoxin Oxidoreductase (POR)**

The enzyme pyruvate ferredoxin oxidoreductase (also known as pyruvate synthase as the reaction is reversible) is one of the best studied members of the 2-oxoacid oxidoreductase family [91–93]. The enzyme catalyzes coenzyme A and TPP-dependent oxidative decarboxylation of pyruvate to acetyl-CoA, releasing a molecule of CO2 and transferring the reducing equivalents to the electron acceptor ferredoxin or flavodoxin. Alternatively, in other pyruvate oxidizing enzymes, the reducing equivalents are transferred to NAD+ (in the case of pyruvate dehydrogenase using lipoate as oxidizing agent for the production of acetyl-CoA), to molecular-oxygen-producing hydrogen peroxide (in the case of pyruvate oxidase), or to the carbonyl groups producing formate (in case of pyruvate formate lyase) [94–96]. In acetaldehyde- and ethanol-producing organisms, acetyl-CoA is usually converted to acetaldehyde via. the CoA-dependent (acetylating) acetaldehyde dehydrogenase.

POR uses iron-sulfur cluster chemistry to catalyze the pyruvate decarboxylation and release of acetyl-CoA. POR is an ancient molecule, and it seems to have existed even before the divergence of the domains of the bacteria and archaea [97]. The enzyme is present in all three domains of life. All archaea catalyze the conversion of pyruvate to acetyl-CoA using POR, and all of the archaeal genomes sequenced so far contain hetero-tetrameric PORs, which have been proposed to be the closest to the POR common ancestor [97,98].

POR is prevalent mainly in anaerobic bacteria and infrequently found in anaerobic protozoa, for example, in *Giardia duodenalis* [99] and *Enthamoeba histolytica* [100,101]. The enzyme has been isolated and studied from many different anaerobic or microaerophilic microorganisms including anaerobic bacteria like the genera *Clostridium* [102], *Moorella thermoacetica* [103] and anaerobic sulphate-reducing bacteria *Desulfovibrio africanus* [104–107]. In hyperthermophiles, PORs are characterized from the hyperthermophilic bacterium *Thermotoga maritima* [108] and hyperthermophilic archaea *Pyrococcus furiosus* [109] and *Archaeoglobus fulgidus* [110], as well as the methanogenic archaea *Methanosarcina barkeri* [111,112] and *Methanobacterium thermoautotrophicum* [113].

The quaternary oligomeric structure of the POR is variable depending on the source microorganism and can be homo-dimeric (e.g., most bacterial PORs), hetero-dimeric (e.g., POR of *Halobacterium salinarium*), hetero-tetrameric (archaeal PORs), and heteropentameric (anabolic PORs), although all of the PORs studied so far, regardless of their source and structure, seem to be phylogenetically related and derived from a common archaeal-type heterotetrameric ancestor [97,98].

The crystal structures of several POR have been determined. PORs from *Desulfovibrio africanus*  (with and without bound substrate) and *Desulfovibrio vulgaris* [114–116] are among the most extensively studied PORs. POR is a metalloenzyme and all PORs studied so far contained between one and three [4Fe-4S] clusters arranged in a spatial order from the TPP located at the active center of the enzyme toward its surface, suggesting that they are part of an electron transfer pathway [117,118].

POR can also catalyze the reaction to form pyruvate from acetyl-CoA and carbon dioxide, which is the basis of the carbon dioxide fixation in many autotrophic microorganisms [119]. This type represents the so-called "anabolic" PORs that are studied from the thermophilic facultative aerobic bacterium *Hydrogenobacterthermophilus* [120–122], as well as the hydrogenotrophic methanoarchaeon *Methanococcus maripaludis* [123,124]. Interestingly, in the case of the heteropentameric POR of *M. maripaludis*, four subunits are very closely related to the archaeal heterotetrameric (ancestral) PORs, the fifth subunit has no known homologue within PORs.

The general steps of the POR catalytic reactions follow the same principles as those of other TPP-dependent enzymes. However, the enzyme is unique in one aspect: unlike most other TPP-dependent enzymes, POR takes advantage of free radical chemistry to catalyze the decarboxylation reaction [94,125].

Pyruvate dehydrogenase complexes (PDH), which also catalyze the oxidative decarboxylation of pyruvate to acetyl-CoA using NAD<sup>+</sup> as an electron acceptor, are normally present in aerobic organisms [126,127], which have been found in some thermopiles [128–130]. But no PDH has been identified in hyperthermophiles [131]. Since PDH does not play any significant role in the production of acetaldehyde and ethanol, no further description of this enzyme complex will be given in this review.

#### **7. POR/PDC Bi-Functional Enzyme**

In 1997, it was reported that the POR was also capable of converting pyruvate to acetaldehyde in the hyperthermophilic anaerobic archaeon *Pyrococcus furiosus* [80]. Unlike the commonly-known PDCs, which employ chemical rather than radical intermediates and therefore are oxygen insensitive, the reported PDC activity was highly oxygen sensitive. Both the POR and PDC activities of the hyperthermophilic enzyme were TPP- and coenzyme A-dependent. By using the coenzyme A analogue (desulfocoenzyme A), it was shown that coenzyme A has only a structural, and not a catalytic role in the catalyzed PDC reaction. Consequently, a "switch" mechanism was proposed for the enzyme's bi-functionality, suggesting the conversion of active aldehyde to either acetyl-CoA or acetaldehyde, depending on the binding of CoA. According to the proposed model, binding of coenzyme A causes conformational changes in the intermediate structure, causing its protonation and generation of hydroxyethyl-TPP (HETDP). This reaction leads to release of acetaldehyde, allowing for the regeneration of TPP and possible release of CoA [80]. Ferredoxin is not required for its full PDC activity nor has any inhibitory effect when tested under *in vitro* conditions. However, it is likely that the *in vivo* PDC activity might be dependent on the availability of oxidized ferredoxin, which means that a lower ratio of oxidized to reduced ferredoxin may favor the PDC activity and *vice versa*. Therefore, it can be predicted that more acetaldehyde would be produced for being reduced to ethanol if the ratio of the oxidized to reduced ferredoxin would be kept very low under the anaerobic growth condition. Such a low ratio may also require a relatively low activity of the ferredoxin-oxidizing hydrogenases present in *P. furiosus* [132,133].

To date there has been no further study on the bi-functionality of the POR enzyme or the physiological relevance of such bifunctionality in any other organisms. It is not clear whether this bi-functionality is only a trait of *Pyrococcales*' POR or a common property of all hyper/thermophilic PORs.

#### **8. Acetaldehyde Dehydrogenase (CoA-Acetylating)**

Acetaldehyde dehydrogenase (CoA-acetylating, EC <IP_ADDRESS>) is a member of a very divergent superfamily of enzymes known as the "aldehyde dehydrogenases". The prototype enzyme (*adhE*) was first discovered in *Escherichia coli* and is required for its anaerobic growth [134]. It was then discovered in the strictly anaerobic bacterium *Clostridium kluyveri* [135]. The enzyme is responsible for the conversion of acetyl-coenzyme A (acetyl-CoA) to acetaldehyde that is eventually converted to ethanol. Two forms of the enzyme are available: one is the monofunctional enzyme with only AcDH activity (*mhpF*) and the other is the bifunctional enzyme with both AcDH and ADH activities (*adhE*). The latter group is composed of an ADH active *C*-terminal and an AcDH active *N*-terminal, a structure believed to be the result of gene fusion between the genes encoding for each single enzyme [136,137].

Reports are available on isolation and characterization of the bifunctional NADP-dependent alcohol/acetaldehyde dehydrogenase (CoA-acetylating) from mesophilic microorganisms including *Giardia lamblia* [138] and *Enthamoeba histolytica* [101,139]. They are also present in some thermophiles, including *T. ethanolicus* [140,141], *T. mathranii* [32] and members of the genus *Geobacillus* [19]. However, no mono- or bi-functional AcDH activity was characterized from hyperthermophiles. Survey of the fully sequenced genomes of hyperthermophilic archaea and bacteria has shown no *adhE* or *mhpF* homologue either (Eram and Ma, unpublished data).

#### **9. Conclusions**

Many hyperthermophilic microorganisms produce ethanol as an end metabolic product. Although alcohol dehydrogenase and pyruvate ferredoxin oxidoreductase are found to be present, enzymes catalyzing the production of acetaldehyde from pyruvate are not well characterized. The commonly-known pyruvate decarboxylase and coenzyme A-dependent aldehyde dehydrogenase have not been identified. The only report of a bi-functional pyruvate decarboxylase is the POR/PDC from *P. furiosus*, which is thermostable but oxygen-sensitive. Therefore, it is likely that they use a two-step pathway to convert pyruvate to ethanol. The regulation of each of the POR/PDC activities is not clear but it may be related to the redox states inside the cells. To date, it appears that at least one multifunctional enzyme is responsible for catalyzing the non-oxidative decarboxylation of pyruvate to acetaldehyde in hyperthermophiles, and further study is needed to understand the catalysis of acetaldehyde production from pyruvate at high temperatures.

#### **Acknowledgments**

This work was supported by research grants from the Natural Sciences and Engineering Research Council (Canada), Genome Canada/Genome Prairie and Canada Foundation for Innovation to KM.

#### **Conflicts of Interest**

The authors declare no conflict of interest.

#### **References**


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**The Impact of Retrospective Childhood Maltreatment on Eating Disorders as Mediated by Food Addiction: A Cross-Sectional Study**

**Rami Bou Khalil 1,2,\*, Ghassan Sleilaty 3, Sami Richa 1, Maude Seneque 2,4, Sylvain Iceta 5,6,7, Rachel Rodgers 4,8, Adrian Alacreu-Crespo 2, Laurent Maimoun 9,10, Patrick Lefebvre 11, Eric Renard 11,12, Philippe Courtet 2,4 and Sebastien Guillaume 2,4**

Received: 3 August 2020; Accepted: 25 September 2020; Published: 28 September 2020

**Abstract:** Background: The current study aimed to test whether food addiction (FA) might mediate the relationship between the presence of a history of childhood maltreatment and eating disorder (ED) symptom severity. Methods: Participants were 231 patients with ED presenting between May 2017 and January 2020 to a daycare treatment facility for assessment and management with mainly the Eating Disorder Inventory-2 (EDI-2), the Child Trauma Questionnaire (CTQ), and the Yale Food Addiction Scale (YFAS 2.0). Results: Participants had a median age of 24 (interquartile range (IQR) 20–33) years and manifested anorexia nervosa (61.47%), bulimia nervosa (16.88%), binge-eating disorders (9.09%), and other types of ED (12.55%). They were grouped into those likely presenting FA (*N* = 154) and those without FA (*N* = 77). The group with FA reported higher scores on all five CTQ subscales, as well as the total score of the EDI-2 (*p* < 0.001). Using mediation analysis; significant indirect pathways between all CTQ subscales and the EDI-2 total score emerged via FA, with the largest indirect effect emerging for physical neglect (standardized effect = 0.208; 95% confidence interval (CI) 0.127–0.29) followed by emotional abuse (standardized effect = 0.183; 95% CI 0.109–0.262). Conclusion: These results are compatible with a model in which certain types of childhood maltreatment, especially physical neglect, may induce, maintain, and/or exacerbate ED symptoms via FA which may guide future treatments.

**Keywords:** eating disorders; food addiction; childhood trauma; maltreatment; physical neglect

#### **1. Introduction**

According to the World Health Organization, "childhood maltreatment is the abuse and neglect that occurs to children under 18 years of age. It includes all types of physical and/or emotional ill-treatment, sexual abuse, neglect, negligence, and commercial or other exploitation, which results in actual or potential harm to the child's health, survival, development, or dignity in the context of a relationship of responsibility, trust, or power" [1]. On the other hand, eating disorders (EDs) are multifactorial mental disorders affecting young individuals and are associated with a mortality rate higher than that of the general population of the same age [2]. The relationship between a history of childhood maltreatment and the later development of an ED is well established, as supported by two major meta-analyses [3,4]. Abused and/or neglected children who have experienced any type of maltreatment (i.e., emotional, sexual, and physical) are at least threefold more likely to develop a future ED [3,4]. Furthermore, a dose–effect relationship between the number of subtypes of childhood trauma experienced and the severity of ED clinical features has been evidenced, suggesting a consistent and partly independent association between these traumatic events and more severe clinical and functional characteristics of ED [5]. While childhood maltreatment may be reported by a high proportion of patients with ED, only a minority of those previously exposed to one or more traumatic events (9–24%) may subsequently present a comorbid post-traumatic stress disorder (PTSD) [6]. Accordingly, beyond the simple comorbidity with PTSD, it is not yet understood how different types of childhood maltreatment impact the clinical presentation of ED, with emotion dysregulation being consistently considered as an important factor mediating this effect [6,7].

In addition to emotion dysregulation, PTSD, and depression as known mediators of ED development in patients who have been exposed to childhood maltreatment, food addiction (FA) may constitute a yet unexplored contributing mediator [6–9]. FA is characterized by poorly controlled intake of preferred foods, which are postulated to act via similar mechanisms as both illicit and licit drugs of abuse in the brain [10]. An increasing amount of evidence of biological and behavioral changes in response to preferred foods (such as brain reward changes, impaired control, genetic susceptibility, substance sensitization and cross-sensitization, and impulsivity) has been sufficiently convincing to conceptualize FA as an addiction disorder [11]. FA has been increasingly considered as an important psychological dimension that leads, in patients with a history of complex trauma, to ED and more specifically binge-eating disorders (BED) and bulimia nervosa (BN) [10]. Despite being a clinical manifestation of addiction to food, as much as 61.5% of patients with anorexia nervosa (AN) of the restrictive type were found to suffer from FA, which translates how much the addictive behavior related to food can be a common pathological dimension to all EDs, as well as a possible accompanying manifestation of other forms of behavioral addiction to fasting, physical exercising, etc. [12].

Although data on the relationships between childhood maltreatment and FA are lacking to date, evidence from clinical studies examining closely related dimensions suggests that such an association might exist. Although not measuring childhood maltreatment per se, in a cohort study of 49,408 female nurse participants, the prevalence of FA increased with the number of lifetime PTSD symptoms, and women with the greatest number of PTSD symptoms reported more than twice the prevalence of FA compared to women with neither PTSD symptoms nor trauma histories. Interestingly, however, in this study, the relationship between FA and PTSD did not differ by trauma type [13]. Furthermore, the co-occurrence of FA symptoms with emotional dysregulation symptoms has led to the suggestion that these might share common characteristics and, potentially, risk factors [14]. In further support of this, when compared to individuals without addictive behaviors, both women with FA and women with substance use presented higher levels of depressive and PTSD symptoms, as well as greater emotion dysregulation [15]. It has been proposed that childhood maltreatment might also be associated with decreased emotional regulation, as well as a greater propensity to and severity of addictive-like behaviors due to structural brain changes (mainly diminished hippocampus volume) [16,17]. Taken together, converging evidence, therefore, seems to exist for an indirect

relationship such that FA might constitute an intervening factor in the cross-link between childhood maltreatment and ED symptom severity.

To our knowledge, no study has yet assessed this proposed indirect pathway in patients with ED. We, therefore, hypothesized that retrospective childhood maltreatment would be indirectly related to ED symptom severity via FA among a transdiagnostic sample of ED patients. In this cross-sectional study design, we aim to establish a conceptual model to further the understanding of how different types of childhood maltreatment might impact ED in order to guide future assessment strategies and treatment development models.


**5. Using ILF neurofeedback to train the conductor of the brainwave symphony**

Despite an attempt to present this information fairly and objectively, my personal bias for ILF neurofeedback is likely obvious.  Each brainwave is like the music playing from each section of the orchestra, such as the winds, brass, strings, or percussion sections. You can train each section separately, but, due to the nature of systems, by training - and possibly changing - one section, the other sections will also likely be perturbed in some way that may not be readily discernable or beneficial. Alternatively, you can train the conductor, which, in this analogy, is the ISO or ILF. Thus, when you train the ILF, you train the entire symphony of brainwaves, which continue to play together, but with greater harmony after neurofeedback training.


**2. Results**

#### *2.1. Selection of Human Anti-SARS-2 RBD Fabs*

To isolate a specific SARS-CoV-2 antibody, the KFab-I library [42,43] was panned against a recombinant SARS-2 RBD immobilized on magnetic beads (Figure 1a). After five rounds of panning, the phage ELISA was performed on immobilized SARS-2 RBD surfaces, using each panning library to monitor the enrichment (Figure 1b). Ninety-five monoclonal phages were randomly picked from the third and fourth rounds, and the binding on the SARS-2 RBD was evaluated by ELISA (Figure S1). Of the 190 individual clones from the third and fourth rounds, 70 clones showed higher absorbances at 450 nm (A450 nm) than those of the negative control (no immobilized SARS-2 RBD control) in the ELISA read-out. The 70 clones were sequenced: 55 were confirmed to be complete and the remaining clones had mutations, such as frame-shifts and stop codons. By analyzing the CDR sequences of the 55 clones, ten unique Fab clones were identified in total and, of these, D12 (Fab) was dominantly selected (60% of sequenced clones (33 out of the 55)), while the other clones showed selection frequencies of about 11% (G3 (Fab)), 9% (E10 (Fab)), 7% (E4 (Fab)), 4% (F7 (Fab)), and 2% (C2 (Fab), C12 (Fab), G9 (Fab), H1 (Fab), and H3 (Fab)) (Figure 1c). In addition, it was observed that nine out of the ten Fabs had CDR3 lengths greater than 12 amino acid residues (70% and 20% for 12 and 14 amino acid residues, respectively), while 10% of the Fabs had shorter CDR3 lengths, such as eight amino acid residues (Figure 1c). In order to confirm that the ten selected clones bound to the SARS-2 RBD and SARS-2 S1 proteins as well, a binding assay was performed, revealing that all of the antibody clones bound to the RBD and the S1 proteins (Figure 1d). In parallel, a binding analysis for RBD variants was also performed using the ten selected clones (Figure S2). This showed that all the phage clones bound to each RBD variant. Two of them (G9 and E4) bound weakly to one RBD variant (N354D; D364Y).

**Figure 1.** Panning of the phage-displayed synthetic Fab library on an immobilized SARS-2 receptor-binding domain (RBD). (**a**) Monitoring of the phage titers over four rounds (R2–R5) of panning. Black and gray bars indicate the ratio of the phage output to the input titers, presented as a percentage (%), from panning on immobilized SARS-2 RBD (black, SARS-2 RBD (+)) and non-immobilized SARS-2 RBD (gray, SARS-2 RBD (−)) surfaces. The ratio of the output to the input (%) = (phage output titer ÷ phage input titer) × 100. (**b**) Phage ELISA performed on the immobilized SARS-2 RBD surfaces using each panning library phage. (**c**) Frequency of ten Fab phage clones selected in the third and fourth rounds (left) and the distribution of HCDR3 lengths (right). The selection frequency of a unique clone (%) = (number of unique clones ÷ total number of phage ELISA positives) × 100. (**d**) Monoclonal ELISA of ten Fab phage clones against the SARS-2 RBD (red) and SARS-2 S1 protein (green). AA: amino acid residue; NC: negative control.

### *2.2. Production and Characterization of Human Anti-SARS-2 RBD Fabs*

To order to produce and characterize the selected clones as Fab proteins, clones were cloned into an in-house *E. coli* expression vector (pKFAB). The Fab proteins were expressed and purified as described in the Section 4. The protein yields of these Fab clones were 11 mg/L, 6.5 mg/L, 106 mg/L, 15.5 mg/L, 12.5 mg/L, 125.5 mg/L, 8.5 mg/L, 17.5 mg/L, 9.5 mg/L, and 40 mg/L for C2 (Fab), C12 (Fab), D12 (Fab), F7 (Fab), H1 (Fab), E4 (Fab), E10 (Fab), G3 (Fab), G9 (Fab), and H3 (Fab), respectively (Figure S3 and Table 1).

**Table 1.** Physicochemical properties of human anti-SARS-2 RBD antibodies.

Fab: antigen-binding fragment; IgG: immunoglobulin G; n.d.: not determined; *T*m: melting temperature. *T*m1 and *T*m2 are the first and second apparent melting temperatures determined by differential scanning fluorimetry (DSF), respectively; *EC*50: half maximal effective concentration; *K*D: equilibrium dissociation constant; *IC50*: half maximal inhibitory concentration; Mon.: monomer; Agg.: aggregate; *IC*50P and *IC*50A: *IC*50 determined by a pseudo-typed virus (D614 spike) and authentic SARS-CoV-2 virus, respectively.

> The apparent affinities of the ten Fabs for the SARS-2 RBD were assessed using an ELISA (*EC*50, nM) (Figure 2a and Table 1). While six Fabs (G9 (Fab), C2 (Fab), F7 (Fab), H1 (Fab), H3 (Fab), and E4 (Fab)) had low to intermediate apparent affinities for the SARS-2 RBD (*EC*50 = 112–663 nM), the remaining four Fabs—D12 (Fab), E10 (Fab), G3 (Fab), and C12 (Fab)—showed relatively higher apparent affinities (19 nM, 62 nM, 67 nM, and 83 nM, respectively) (Figure 2a).

> To examine the potential neutralizing ability of the selected Fabs, we conducted a competitive binding assay between the SARS-2 RBD and ACE2 protein or ACE2-overexpressed cells (Figure 2b). It was found that five Fabs (C2 (Fab), C12 (Fab), D12 (Fab), F7 (Fab), and H1 (Fab)) significantly antagonized the interaction between the SARS-2 RBD and biotinylated ACE2 protein (Figure 2c). The same five Fabs seemed to block the interaction between SARS-2 RBD-mFc protein and ACE2-overexpressed cells in a flow cytometry analysis as well (Figure 2d and Figure S4).

> Next, in order to determine whether the ten Fabs could cross-react with the S1 proteins from other coronaviruses, such as SARS-CoV and MERS-CoV, an ELISA was conducted. This showed that three of the Fabs (E4 (Fab), E10 (Fab), and G3 (Fab)) indeed cross-reacted with the SARS-CoV S1, whereas no Fabs bound with the MERS-CoV S1 (Figure S5).

**Figure 2.**  Arrows indicate potentially neutralizing clones. mFc-PE: anti-mouse PE (phycoerythrin) conjugate; MFI: mean fluorescence intensity; n.s: not significant (*p* > 0.05); NC: negative control. \* and \*\*: *p* < 0.05 and *p* < 0.01, respectively.

### *2.3. Production and Characterization of Human Anti-SARS-2 RBD IgGs*

To produce and characterize the five anti-SARS-2 RBD antibodies that seemed to have neutralizing activities in IgG forms, the five Fabs were individually reformatted to IgG forms. That is, the individual VH and VL sequences from each of the Fabs were cloned into heavy- (IgG1 Fc) and light-chain (Ck1) expression vectors, respectively. The five IgGs were transiently expressed in HEK293 cells and subsequently purified as described in the Section 4. The resulting IgGs were highly pure and their protein yields were 9.6 mg/L, 12.9 mg/L, 13.5 mg/L, 13.2 mg/L, and 12.5 mg/L for C2 (IgG), C12 (IgG), D12 (IgG), F7 (IgG), and H1 (IgG), respectively (Figure S6 and Table 1).

In order to confirm whether the purified IgGs could bind to the SARS-2 RBD and its variants—and also whether they could cross-react with other coronavirus S1 proteins, as observed with the Fabs—an ELISA binding assay was conducted, revealing that all the IgGs bound to the SARS-2 RBD and SARS-2 S1, as well as the RBD variants, whereas all of them did not bind to the MERS-CoV S1 (Figure 3a). In particular, one clone, H1 (IgG), was found to cross-react with the SARS-CoV S1 and three IgGs (C2 (IgG), D12 (IgG), and F7 (IgG)) seemed to bind with the SARS-CoV S1 but the binding was too weak to confirm their cross-reactivity.

**Figure 3.** Characterization of anti-SARS-2 RBD immunoglobulin Gs (IgGs). (**a**) Binding analysis of five human anti-SARS-2 RBD IgGs—C12 (IgG), H1 (IgG), C2 (IgG), D12 (IgG), and F7 (IgG)—to the SARS-2 RBD and its variants (top) and the SARS-CoV-2 S1 (D614G) and other coronavirus S1 proteins (bottom), respectively. (**b**) Soluble ELISA of five serially diluted human anti-SARS-2 RBD IgGs on immobilized SARS-2 RBD surfaces to measure their apparent affinities (*EC*50, nM). (**c**) ELISA detection for five human anti-SARS-2 RBD IgGs blocking the binding of the ACE2 protein with the SARS-CoV-2 RBD (top) and analysis of the flow cytometry for the blocking effect between the SARS-CoV-2 RBD and an ACE2-overexpressed cell (bottom). (**d**) Size-exclusion chromatography analysis of five human anti-SARS-2 RBD IgGs. The positions of the molecular mass markers, shown as kDa, on the retention time *x*-axis are indicated above the peaks. The data are presented as the mean ± standard error (SEM). MFI: mean fluorescence intensity; NC: negative control; \*, \*\*, and \*\*\*: *p* < 0.05, *p* < 0.01, and *p* < 0.001, respectively.

To determine whether the apparent affinities of the anti-SARS-2 RBD IgGs were altered by reformatting the Fabs into the IgGs, the apparent affinities of the IgGs were examined using ELISA (*EC*50, nM). As shown in Figure 3b, the five clones (C2 (IgG), C12 (IgG), D12 (IgG), F7 (IgG), and H1 (IgG)) increased their apparent affinities approximately 100- to 1800-fold compared to their Fab formats (Figure 3b and Table 1), which might have been due to an avidity effect [42,43]. Next, a size-exclusion chromatography analysis was performed to assess their non-aggregation properties, revealing that the IgGs were monomeric without forming high molecular weight (HMW) aggregates (Figure 3d and Table 1). The five IgGs were further analyzed using a protein thermal shift (PTS) assay to determine their thermal stabilities; the assay showed that all the IgGs had *T*m over 70.0 ◦C, confirming that they were thermally stable (Figure S7 and Table 1). To determine whether the thermal stability of the IgGs was due to the intrinsically high stability of the Fabs, the five Fabs were analyzed with the same PTS assay and the results showed that all of the Fabs had *T*m values over

76.0 ◦C, indicating that the high thermal stability of the IgGs was derived from the intrinsic properties of the Fabs (Figure S8).

Next, to determine whether the neutralizing activities of the SARS-2 RBD IgGs remained after reformatting the Fabs into IgGs, we performed a competitive binding assay demonstrating the IgGs' antagonizing activities in the interaction between the SARS-2 RBD and ACE2 protein or ACE2-expressed cells (Figure 3c). All the IgGs significantly antagonized the interaction between the RBD and biotinylated ACE2 protein (Figure 3c top) and also inhibited the interaction between the SARS-2 RBD-mFc protein and ACE2 overexpressed cells in a flow cytometry analysis, although C12 (IgG) showed a slightly reduced inhibition compared to the other IgGs (Figure 3c bottom and Figure S9).

#### *2.4. Neutralization Assay against SARS-CoV-2 Pseudovirus and Authentic SARS-CoV-2*

To evaluate the neutralization potency of the five human SARS-CoV-2 RBD IgGs, we carried out a pseudo-typed virus neutralization assay using a lentiviral HIV-1 pseudotyping system [44]. The five IgGs were found to display strong neutralizing activity against the SARS-CoV-2 pseudo-typed virus, among which C2 (IgG) and D12 (IgG) showed the most potent activity. The *IC*50 values of C2 (IgG) and D12 (IgG) in the pseudo-typed virus neutralization were 0.015 and 0.035 μg/mL, respectively (Figure 4a and Table 1).

**Figure 4.** In vitro neutralization assay of human anti-SARS-2 RBD IgGs. Pseudo-typed virus-based neutralization (**a**) and a neutralization assay using authentic SARS-CoV-2 (**b**). (**c**) Correlation in neutralization potencies between pseudo-typed virus- and authentic virus-based assays. (**d**) Correlation between affinities of anti-SARS-2 RBD IgGs and their neutralization potencies for the authentic virus. The data are showed as the mean ± standard error (SEM).

Based on our previous competitive binding assays, we examined the five IgGs in order to evaluate their neutralizing effects on authentic SARS-CoV-2. The observations of luminescent signals showed that two of the IgGs, C2 (IgG) and D12 (IgG), exhibited high protection upon SARS-CoV-2 exposure for three days. The *IC50* values of C2 (IgG) and D12 (IgG) in the authentic SARS-CoV-2 neutralization were 0.018 and 0.036 mg/mL, respectively (Figure 4b, Figure S10, and Table 1). The rest of the IgGs showed less neutralization compared to the two IgGs: 0.102 mg/mL, 0.151 mg/mL, and 0.232 mg/mL for H1 (IgG), F7 (IgG), and C12 (IgG), respectively (Table 1). In order to know whether there was any correlation present between the neutralization potencies from the pseudo-typed virus and the authentic virus, we compared and plotted the values from the assays and found that a strong correlation was indeed present between the neutralization potencies from the two different neutralization assays (Figure 4c). In addition, we also found that there was a strong correlation between the affinity and the neutralization potency of the anti-SARS-2 RBD IgGs as well (Figure 4d).

The two human anti-SARS-2 RBD IgGs, C2 and D12, were further characterized by BLI (Octet) in order to determine their affinities with the SARS-2 RBD, and it was found that C2 (IgG) and D12 (IgG) had binding affinities of 0.13 nM and 0.57 nM, respectively (Figure S11). This confirmed that some avidity effects were reflected in the apparent affinities from the previous ELISA (Figure 3b and Table 1), which was performed with an immobilized SARS-2 RBD, unlike the BLI (Octet), which was undertaken with the human IgGs immobilized on the sensor.