\r\n\tto cover major health conditions that may benefit from Tai Chi, including neurodegenerative diseases, cardiopulmonary rehabilitation, psychosocial benefits, chronic fatigue and fibromyalgias, osteoporosis ad bone metabolism, and other chronic degenerative conditions that plague modern health. We seek to include reviews of underlying basic science as well as clinical trial data that demonstrate that multiplicity of benefits of this ancient exercise form to advance evidence-based understanding of Tai Chi exercise as an adjunct treatment.
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1. Introduction
Plants are attached immobile organisms and thus have to adapt to their environment in order to survive and reproduce successfully. Usually, plants experience multiple simultaneous impacts from different sources, so they developed complex signaling pathways to effectively detect these impacts and adequately respond to them [1]. Various microorganisms, which are constantly present in the environment, form one of the major factors affecting the life cycle of plants [2, 3]. Although many plant-associated microbes are pathogens that impair plant growth and reproduction, there are also a lot of beneficial (mutualistic) microorganisms able to provide plants with nutrition and additional defense mechanisms. Cooperation with such microorganisms constitutes the universal and highly effective strategy of plants’ ecological adaptation, so they tend to form long-lasting associations, which sometimes grow into highly integrated symbioses where one or both partners can develop novel features useful for their survival. Establishing of such symbiotic relationships involves the complicated developmental programs implemented under the joint control by plant and microbial partners and based on the cross-regulation of their genes.
Leguminous plants (or Legumes, family Fabaceae) are known to form symbioses with extremely broad range of beneficial soil microorganisms (BSM), representing examples of almost all plant-microbe mutualistic systems. One of the most ecologically important and well-studied legume-beneficial symbioses is root nodule (RN) symbiosis (symbiotic association with nitrogen-fixing bacteria). Compared with other interactions of legumes with BSM, RN symbioses demonstrate high level of genetic and metabolic integrity, which implies, inter alia, highly specific mutual recognition of partners. As legume plant plays a central role in establishing of RN symbiosis, performing functions of initiation, coordination, and regulation of all developmental processes, it possesses complex receptor system capable of accurate identification of microsymbiotic partner. In this chapter, we describe the mechanisms of plant-microbe recognition during initial steps of RN symbiosis using the interaction of model legumes – pea (Pisum sativum L.), barrel medic (Medicago truncatula Gaertn.), and Lotus japonicus (Regel.) K. Larsen – with rhizobia as an example. We pay particular attention to symbiotic system of P. sativum since pea, besides its importance as a model object of genetics, is also a valuable crop plant. Hence, in conclusion, we discuss the potential to use obtained knowledge for optimizing the broad spectrum of plant adaptive functions and to improve the sustainability of legume crop production.
2. Legume-rhizobial symbiosis: An example of highly integrated plant-microbe system
Nitrogen is an essential component of all living systems, since it is part of the most important biological molecules – DNA and proteins. Molecular nitrogen (N2) in the atmosphere, despite being abundant, is extremely chemically inert and thus cannot be used by the majority of organisms, causing them to compete for more accessible nitrogen sources. Leguminous plants are able to grow in the soil/substrate without any combined nitrogen due to the fixation of atmospheric nitrogen by their symbiotic nodule bacteria (collectively called rhizobia) [4]. Nitrogen fixation occurs within special plant organs – root nodules (or, in some associations, also stem nodules). Development of these organs represents a well-organized process based on the tightly coordinated expression of specialized symbiotic plant and bacterial genes. The legume nodules provide an ecological niche for bacteria, as well as structure for metabolic/signal exchange between the partners and for the control of symbionts by the hosts [5].
Family Fabaceae contains about 19,000 species divided between three subfamilies (Caesalpinioideae, Mimosoideae, and Papilionoideae), with more than 700 genera of worldwide distribution [6]. With a single exception (Parasponia, family Ulmaceae), the ability for symbioses with rhizobia is restricted to Fabaceae, although in eight related dicotyledonous families (Rosid I clade) an ability to form nodules with the nitrogen-fixing actinomycete Frankia is known [7].
By contrast to legumes, their nitrogen-fixing microsymbionts do not constitute a taxonomically coherent group of organisms. The majority of rhizobia belong to the α-proteobacteria previously assigned to the Rhizobiaceae family solely on the basis of their ability to nodulate the legumes (e.g., Azorhizobium, Bradyrhizobium, Mesorhizobium, Rhizobium, Sinorhizobium). In the last years, several non-rhizobial symbionts capable of forming nodules and fixing nitrogen in legume roots have been documented. According to modern conception, bacteria that can form RN symbiotic associations (about 44 species of 12 genera) are not clustered in any common lineage, instead being distributed in the classes α-proteobacteria and β-proteobacteria (close to Burkholderia, Cupriavidus and Ralstonia) and dispersed over nine monophyletic groups along with taxa that do not contain legume symbionts [8]. Recently, some γ-proteobacteria (belonging to Escherichia, Enterobacter, and Pseudomonas genera) have been discovered that can also form nitrogen-fixing nodules with the legumes [9]. All these bacteria (collectively still referred to as rhizobia) vary significantly in their overall genome structure, location of “symbiotic” (sym) genes, their molecular organization and regulation [10, 11]. However, a particular legume plant can find the appropriate rhizobial partner (species, or even strain) due to the fine-tuned mechanism of molecular interaction.
The development of nitrogen-fixing nodule is complex process that is traditionally divided into three major stages: preinfection, root colonization/nodule morphogenesis, and nitrogen fixation. On the first stage, the mutual recognition of partners occurs. The interaction between micro- and macrosymbiont begins with the activation of bacterial nod-genes under the influence of flavonoid molecules secreted by the plant root [12, 13]. nod-genes provide the synthesis of the main bacterial signaling molecule called Nod-factor (NF), which is crucial for identification of microsymbiont [14-16]. After the proper reception of Nod-factor, plant activates two parallel processes: bacterial penetration into root hair cells via so-called infection thread (IT), and differentiation of nodule from the root cortex. IT is a special structure generated by invagination of plant cell membrane, covered with plant-derived cell wall and filled with matrix produced by both plant and bacteria. It grows into root hair cell and then to the cortex where nodule tissues are formed (Figure 1) [17].
Figure 1.
General scheme of RN symbiosis formation and functioning in pea. From left to right: three major stages of symbiosis, namely preinfection, root colonization/nodule morphogenesis, and nitrogen fixation. F – flavonoids excreted by the plant, NF – Nod-factors excreted by nodule bacteria, IT – infection thread, B – bacteroids. Sym10 and Sym2, Sym37 – stages on which symbiosis is blocked in case of corresponding pea mutants/genotypes.
The key stage of nodule development is conversion of bacteria into the form of intracellular symbionts through endocytosis-like process. Herein, the distal area of IT transforms into structure called infection droplet (ID), which releases membrane vesicles containing bacteria into plant cytoplasm. After leaving IT, rhizobia for some time retain their size and shape, subsequently differentiating into a specific form called bacteroids [18]. Compared to free-living bacteria, bacteroids have significantly (about 3-7 times) increased size and more complex shape, which can be round, pear-shaped, Y- or X-like, depending on specific symbiotic system. After the aforesaid differentiation, the synthesis of nitrogenase (the enzyme catalyzing reduction of N2 into NH4+) and other proteins involved in nitrogen fixation is activated in bacterial cells [19].
Bacteroids are embedded into a membrane structure named symbiosome, which are derived from membrane vesicle originating from ID. They are organelle-like units of plant cell responsible for nitrogen fixation. Symbiosome formation as well as bacteroid differentiation is induced by plant. Peri-bacteroid membrane (PBM) that surrounds bacteroids is an active interface of RN symbiosis where exchange of metabolites between symbionts occurs [19, 20]. Plant cells containing symbiosomes also undergo the deep differentiation, increasing the amount of their membrane structures (endoplasmic reticulum and the Golgi complex), which participate in the development of PBM and biosynthetic processes. Many proteins associated with nitrogen fixation appear in these cells de novo.
The developmental program described above is typical only for evolutionary advanced legumes belonging to the inverted repeat–lacking clade (IRLC) of Papilionoideae, such as Medicago, Pisum, or Trifolium (clover). They form so-called “indeterminate” nodules which are characterized by stable apical meristem and division into histological zones with constantly renewed N2-fixing zone. Rhizobia in these nodules undergo terminal bacteroid differentiation and cannot revert to free-living form [21, 22]. Other legumes such as Lotus or Phaseolus (bean), however, form morphologically more simple “determinate” nodules, where apical meristem exists only for several days, nitrogen-fixing zone is not strongly expressed, and infected (N2-fixing) cells intermingle with noninfected ones [21]. Bacteroids in determinate nodules show no sign of terminal differentiation as they usually maintain their normal bacterial size, genome content, and reproductive capacity lacking from those in indeterminate nodules [22].
Several Papilionoideae members, such as Arachis and Stylosanthes, demonstrate the reductive scheme of nodule development: rhizobia invade roots through the cracks of epidermis, and instead of IT they are brought into cytoplasm by the direct endocytosis from intercellular space [6, 23]. Even more primitive morphology of symbiosis is typical for members of Caesalpinioideae subfamily, as they lack endocytosis step, and nitrogen fixation occurs within modified persistent ITs called “fixation threads” [24]. This is also relevant for evolutionary primitive woody plants from Papilionoideae: Andira and Hymenolobium, and for Parasponia.
Such a complicated system of biological nitrogen fixation will work properly only when suitable partners meet each other in soil. This rendezvous becomes possible owing to reciprocal molecular signal exchange, which is not exhaustively studied to date.
2.1. Specificity of legume-rhizobial symbiosis
Root-nodule symbiosis is well known as highly specific plant-microbe interaction. According to the early surveys of symbiotic specificity [25], legumes were suggested to comprise a range of taxonomically restricted cross-inoculation groups (CIG) within which the free cross-inoculation occurs, while the species from different groups do not cross-inoculate.
The best studied examples of this classification are represented by four CIG: “Trifolium – Rhizobium\n\t\t\t\t\tleguminosarum bv. trifolii,” “Pisum, Vicia, Lathyrus, Lens – R.\n\t\t\t\t\tleguminosarum bv. viciae,” “Galega – R.\n\t\t\t\t\tgalegae,” “Medicago, Melilotus, Trigonella – Sinorhizobium meliloti, S.\n\t\t\t\t\tmedicae.” However, it was demonstrated later that such strictly defined specificity is limited to the herbage papilionoid legumes growing in temperate zones and representing the so-called Galegoid complex [26, 27]. Other legumes, including the majority of tropical species, tend to broad their symbiotic specificity, where cross-inoculation is possible between tribes, subfamilies, and even with non-legume plant Parasponia [28].
The analysis of CIG structure for both strictly and broadly specific legumes has shown that plant specificity towards rhizobia has good correlation with plant taxonomy on the genus or tribe level. It was also revealed that specificity of nodule formation does not correlate with symbiotic efficiency, i.e., efficiency of nitrogen fixation: several bacterial strains form normal nodules with one plant species, and are inactive (not able to fix nitrogen, Fix-) with another [26]. This could be due to the fact that nodulation is an early stage of symbiosis similar (and supposedly related) to pathogenic interaction, and is based on strict cross-activation of plant and bacterial genes (“gene-for-gene” interaction), while nitrogen fixation occurs on the later stages for which “gene-for-gene” interaction is not typical.
Moreover, it is specificity that makes possible the natural selection of effective symbiotic pairs, but not the single “symbiotically effective” plant or single “symbiotically effective” microorganism. On the other side, specificity of legume-rhizobial symbiosis should be somewhat associated with nitrogen-fixing intensity, upon which is based the ecological efficiency of cooperation; otherwise it would not be an evolutionary advantage. The majority of “Galegoid complex” members have both narrow specificity and effective nitrogen fixation, suggesting that these two features are connected, though specificity of recognition is obviously not the only condition required for effective symbiosis.
It is also important to note that the range of potential symbiotic partners can vary for both bacteria and plants. Symbiotic pair Trifolium–Rhizobium leguminosarum bv. trifolii represents one side of this continuum, as they are the only possible partners for each other. On the opposite side are Phaseolus vulgaris and Vigna unguiculata, which are able to exchange their symbionts with many unrelated legume species [25]. In bacteria, the Sinorhizobium fredii strain NGR234 was shown to interact with more than 120 plant species from all three Fabaceae subfamilies, as well as with Parasponia, thus being the most “unscrupulous” strain known so far [29]. The most striking feature of this strain is that its genome, although not particularly large (6.9 Mbp), encodes more different secretion systems than any other known rhizobia and probably most known bacteria [30]. These, among others, include type III and type IV secretion systems which allow bacteria to direct effector proteins or DNA into the cytoplasm of their eukaryotic hosts. There seems to be a correlation between the host range of rhizobia and the number of specialized protein secretion systems they have, as “classic” narrow-host-range rhizobia such as S. meliloti and R. leguminosarum carry neither type III nor type IV secretion systems. Furthermore, NGR234 is shown to secrete a large family of NFs that are variously 3-O, 4-O, or 6-O carbamoylated, which are N-methylated, and which carry a 2-O-methyl-fucose residue that may be either 3-O sulfated or 4-O acetylated (see below) [29]. Since no other rhizobia synthesize such a large family of NFs, it should be proposed as one of the main aspects contributing to the broad host range of NGR234 [17, 31]. Another possible aspect is that NGR234 not only treats the legume root to a large palette of NFs, but that their concentration is much higher than in even very closely related rhizobia [32].
2.2. Initial steps of rhizobium-legume symbiosis
The specificity of legume-rhizobia interactions is expressed mostly during the preinfection stage when rhizobia recognize the roots of appropriate host plants and colonize their surfaces. When the root-excreted signals (in particular, flavonoids) are perceived by bacteria, they activate the bacterial nodulation genes (nod/nol/noe) [13]. These genes control the synthesis of lipo-chito-oligosaccharidic (LCO) nodulation factors (Nod-factors) which induce the early stages of RN symbiosis development. NFs represent the unique group of bacterial signal molecules not known outside legume-rhizobia symbiosis. They are among the most potent developmental regulators: their effect is expressed at concentrations merely of 10–8 – 10–12 M. The core structure of these molecules, common for all rhizobia species, consists of 3-6 residues of N-acetylglucosamine and of a fatty acid (acyl) chain (Figure 2). The type of symbiotic specificity is dependent mainly on the chemical modifications in NF structures [14-16]. However, a sufficient impact to the host specificity of RN symbiosis can also be made by the interactions between bacterial surface molecules (some polysaccharides and proteins) [33, 34] and the lectins located on the root hair surfaces, as well as by means of NFs secretion [35].
Figure 2.
Example of Nod-factor excreted by Rhizobium leguminosarum bv. viciae strain TOM nodulating Afghan peas.
Rhizobia possess a wide range of genes involved in the early stages of nodulation, i.e., the NFs production [36]. Genes which are common to all rhizobia – nodA, nodB, nodC, and their regulator nodD – are responsible for NF core structure synthesis [37]. The other genes specific for particular species or strains control various modifications of signaling molecule. The difference in the spectrum of hosts possible for microsymbiont to interact with is based on the variety of combinations of different nod-genes. For example, presence of gene nodE, which encodes protein similar to fatty acid synthase in several genera of rhizobia, provides modification of fatty acid moiety on the nonreducing end of NF molecule, thereby affecting the ability of bacteria to nodulate certain plant species [38, 39]. Genes nodH, nodP, and nodQ found in Sinorhizobium meliloti control the specific NF modification – the O-sulfation of reducing end – which makes it recognizable for Medicago receptors [40]. Overall, each strain of rhizobia is characterized by specific set of nod-genes, which together form the “molecular key” suitable for plant receptor. It is significant to note that most rhizobia secrete an assortment of NFs varying in their structure instead of just one particular kind [41, 42]. Thereby, the symbiotic success of bacteria could be directly connected with diversity of NFs they are able to produce, and “molecular key” rather becomes the “set of lock picks,” with secretion systems and surface molecules being additional tools in it (see above).
By perceiving the NF, plant starts various processes in root tissues. In particular, signaling molecule is required for the activation of plant genes in the epidermis cells and pericycle, as well as for mitotic reactivation of cortical cells and the formation of IT. Genes responsible for proper NF reception were first discovered in mutants of Lotus japonicus lacking any response to NFs [43, 44]. These genes were named NFR1 and NFR5, for Nod-Factor Receptor. Cloning of these genes revealed that they encode receptor-like kinases comprising LysM domains (LysM-RLK). LysM domains occur in a variety of proteins in bacteria and eukaryotes and have been shown to bind glycan-containing ligands (such as chitin) [45]. They consist of a repetition of a small motif typically containing from 44 to 65 amino acid residues – the LysM sequence, or LysM module [46, 47]. One LysM sequence has a βααβ secondary structure with the two helices packing onto the same side of an antiparallel β sheet. Multiple LysM modules in a protein are often separated by small Ser-, Thr-, and Asn-rich intervening sequences [48].
Only in plants are LysM domains associated with a kinase-like domain [49] forming two main LysM-RLK gene families: the LYK family and the LYR family. All the LysM-RLKs are predicted to contain three LysM modules, although these modules exhibit a high degree of divergence, both within a protein and between proteins. It is considered that the initial function of LysM-RLKs has been recognition of chitin-based signal molecules produced by hostile microbes (termed as MAMPs (“microbe-associated molecular patterns”) or PAMPs (“pathogen-associated molecular patterns”)), similar to the function of CERK1 receptor-like kinase from Arabidopsis thaliana [2]. Based on microsyntenies between genomic regions around LysM-RLK genes in legumes and non-legumes (A.thaliana, rice) plants, it has been speculated that these genes are the descendants of a common ancestor [50]. Zhang et al. (2007) [51] proposed that in Leguminosae LysM-RLKs have undergone further duplication and diversification, with some LysM-RLKs acquiring the ability to perceive bacterial NFs, leading to mutually beneficial endosymbiosis with rhizobia. One aspect of this diversification is the adaptation of extracellular LysM domains to recognize specific structures of NFs, while another being evolution of the intracellular kinase domains to switch the signals from cascades inducing defense responses to symbiotic gene cascades. Recently, the function of NFRs as NF receptors was confirmed by demonstration of their ability to directly bind NF molecule in vitro [52].
In Medicago and pea, which belong to IRLC (see above), NF perception seems to be more complicated than in Lotus. Genes orthologous to NFR1 and NFR5 were identified in Medicago truncatula (LYK3 and NFP) and in Pisum sativum (Sym37 and Sym10), with careful description of corresponding mutant phenotypes [44, 53-55]. While phenotype of nfp and sym10 mutants (in Medicago and pea, respectively) coincided with that of nfr5 mutants in Lotus, mutations in genes lyk3 and sym37 (orthologs of NFR1) led to significantly different phenotype – successful penetration of bacteria into root hair with subsequent block of IT progress, instead of complete absence of responses to rhizobia [55, 56]. These data support the “two-receptor” model of Nod-factor perception proposed more than 20 years ago [40]. According to this model, which was developed on the base of the infection phenotype of several S. meliloti nod mutants, there are two different types of NF receptors – the “recognition” (or “signaling”) receptor inducing early responses with high affinity for Nod-factor and low requirements toward its structure, and the “entry” receptor that controls penetration of bacteria into plant cell and has more stringent demands [40].
It is significant to note that NFR5 (and its homologs, NFP in Medicago and Sym10 in Pisum) lacks the independent kinase activity and thus can function properly only in complex with active kinase (which is suggested to be NFR1) [52]. It can be assumed, based on the above, that in general the “recognition” receptor (NFR5, NFP or Sym10) perceives NF and afterwards forms complex with another receptor possessing kinase activity (NFR1, LYK3 or Sym37, respectively), thus constituting the “entry” receptor. Still, results of genome and transcriptome sequencing in Lotus, Medicago and pea show that legumes possess more than 10 genes of receptor kinases similar by structure to the aforementioned ones. So, the system of NF receptors could be actually much more complicated, suggesting that the overall mechanism of NF perception is probably even more intricate than was thought before.
3. Molecular genetics of Nod-factor signaling in legumes
As reviewed in our recent publication [57], plant genes involved in development of RN symbiosis may be divided into two groups, according to approach which was used for the gene identification. The first group, Sym-genes, had been identified with the use of formal genetic analysis (started from selection of plant mutants defective in nodule development). The other group of genes called nodulins was identified by molecular genetic methods, through identification of proteins and/or RNAs synthesized de novo in root nodules.
The large sizes of genomes of crop legumes (e.g., soybean or pea) in which the formal genetics of symbioses was initially developed, as well as low capability for genetic transformation, complicate greatly the cloning of symbiotic genes, analysis of their primary structures, and gene manipulations. Therefore, in the early 1990s, Lotus japonicus [58] and Medicago truncatula [59, 60] have been introduced in symbiogenetic studies as model plants. These species are characterized by relatively small genomes (470-500 Mb; [61]) and can be easily genetically transformed [60, 62-64]. In addition, the short life cycle and high seed productivity made them attractive and convenient model objects for studying molecular bases of RN symbioses, as well as other types of plant-microbial symbioses.
The analysis of signaling pathway in RN symbiosis was started with experimental mutagenesis. Large-scale programs of insertion, chemical and X-rays mutagenesis, performed by different research groups, resulted in generation of numerous symbiotic mutants in L. japonicus and M. truncatula [65, 66] which allowed researchers to identify and characterize a series of Sym-genes. The genes involved at the initial stages of nitrogen-fixing symbiosis (named “early Sym-genes”) were of primary interest, allowing dissection of the mechanisms by which the NF signal is perceived and transduced by host plants.
3.1. Nod-factor signaling in model legumes
After the first step of NF reception implemented by LysM-receptor kinases (described above), the symbiotic signal is transmitted to the pathway named Common Symbiosis Pathway (CSP), for it shares components with another interaction – arbuscular mycorrhiza (AM) symbiosis, the association with obligate biotrophic fungi of phylum Glomeromycota. Arbuscular mycorrhiza is formed by at least 80% of contemporary land plants and is believed to be the most ancient plant-microbe symbiosis which has played a decisive role in plants adaptation for terrestrial life [67-69]. AM is the main source of plants’ phosphoric nutrition, although in many temperate and boreal species it is supplemented or even completely replaced by other forms of mycorrhiza (ectotrophic, ericoid) with various representatives of the Ascomycota and Basidiomycota, and for some plants (orchids) fungi supply not only mineral nutrition, but also organic carbon compounds [69, 70]. Being the first beneficial association with microorganisms known for plants (occurred approximately 400 million years ago), AM is considered as an ancestor for other mutualistic plant-microbe interactions, such as RN symbiosis. Therefore, it is supposed that NF signaling evolved on the base of previously existing AM signaling. Intriguingly, arbuscular mycorrhizal fungi excrete a set of chitin-derived Myc-factors structurally similar to Nod-factors [71], which also serve as the signaling molecules. It still remains unknown, however, how exactly the Myc-factors are percepted by plants.
The first player in the CSP was identified more than 10 years ago. It is LRR-receptor kinase, or SymRK (symbiotic receptor kinase) described for Lotus as SymRK (Symbiotic Receptor Kinase) and for Medicago as NORK (Nodulation Receptor Kinase) [72, 73]. In pea, the gene Sym19 is orthologous to SymRK in Lotus and NORK (also known as DMI2, for Doesn’t Make Infections) in Medicago [72]. Ligand of this receptor kinase is not known as yet (Figure 3). Interestingly, the activity of SymRK is also required for proper progression of late symbiotic stages, at least for rhizobial infection [74]. SymRK kinase domain has been shown to interact with 3-hydroxy-3-methylglutaryl CoA reductase 1 (HMGR1) from M.\n\t\t\t\t\ttruncatula [75], and an ARID-type DNA-binding protein [76]. These results suggest that SymRK may form complex with key regulatory proteins of downstream cellular responses. Symbiotic Remorin 1 (SYMREM1) from M. truncatula and SymRK-interacting E3 ligase (SIE3) from L. japonicus have also been shown to interact with SymRK [77, 78].
Figure 3.
Receptor kinases of pea participating in nodulation signaling.
The symbiosis receptor kinase SymRK acts upstream of the NF-induced Ca2+ spiking in the perinuclear region of root hairs within a few minutes after NF application [79]. Perinuclear calcium spiking involves the release of calcium from a storage compartment (probably the nuclear envelope) through as-yet-unidentified calcium channels. To date, it is known that the potassium-permeable channels might compensate for the resulting charge imbalance and could regulate the calcium channels in plants [80-84]. Also, nucleoporins NUP85 and NUP133 (described only in Lotus so far) are required for calcium spiking, although their mode of involvement is currently unknown. Probably, they might be a part of specific nuclear pore subcomplex that plays a crucial role in the signal process requiring interaction at the cell plasma membrane and at nuclear and plastid organelle membranes to induce a Ca2+ spiking [85-86]. Recently, the third constituent of a conserved subcomplex of the nuclear pore scaffold, NENA, was identified as indispensable component of RN endosymbiotic development [87].
Ca2+ spikes are supposed to activate a calcium- and calmodulin-dependent protein kinase (CCaMK). This kinase contains an autoinhibition domain which, when removed, leads to a spontaneous activation of downstream transcription events and induction of nodule formation even in the absence of rhizobia [88]. Thus, CCaMK appears to be a general “manager” for both RN and AM symbioses and the last member of Common Symbiosis Pathway, because the next steps of nodulation signaling are independent from those of AM: the mutations in downstream Sym-genes do not affect the AM symbiotic properties of legume. Interestingly, mutations in any Sym-genes do not influence the defense reactions, suggesting that signaling pathways of mutualistic symbioses and pathogenesis are sufficiently different.
The CCaMK is known to form a complex with CYCLOPS, a phosphorylation substrate, within the nucleus [89]. cyclops mutants of Lotus severely impair the infection process induced by the bacterial or fungal symbionts. During RN symbiosis, cyclops mutants exhibit the specific defects in IT initiation, but not in the nodule organogenesis [90], indicating that CYCLOPS acts in an infection-specific branch of the symbiotic signaling network [35]. Cyclops encodes a protein with no overall sequence similarity to proteins with known function, but containing a functional nuclear localization signal and a carboxy-terminal coiled-coil domain.
It is supposed that CCaMK with help of CYCLOPS probably phosphorylates the specific transcription factors already present in cell, NSP1 and NSP2, which influence the changes of expression in several genes related to the symbiosis development [91, 92]. The activity of these proteins leads to the transcriptional changes in root tissues, for instance, increasing the level of early nodulins ENOD40, ENOD11, ENOD12, ENOD5, which are known to be the potential regulators of IT growth and nodule primordium formation [93-95]. Also, the changes in cytokinin status of plant are detected, followed by up-regulation of genes encoding for RN symbiosis-specific cytokinin receptors [96-98]. Moreover, transcription regulators NIN and ERN are to be induced specifically downstream of the early NF signaling pathway in order to coordinate and regulate the correct temporal and spatial formation of root nodules [99-102].
The presented genes are responsible for the signal cascade which is aimed to induce the nodulin genes involved in building the symbiotic structures and implementing their biochemical functions. It is supposed that this signaling pathway did not appear de novo in legumes when they become able to form nodules, but was developed from already existing system of AM formation into which the novel, nodule-specific genes were recruited. Still, new genes had been involved in RN symbiosis development, especially those encoding the receptors recognizing hormones (e.g., cytokinins) and hormone-like molecules (Nod-factors).
Another important signaling process in RN symbiosis is an autoregulation of nodule formation. It takes place after successful mutual partners’ recognition and signal exchange. It is considered that legume host controls the root nodule numbers by sensing the external and internal cues. A major external cue is the concentration of soil nitrate, whereas a feedback regulatory system where nodules formed earlier suppress further nodulation through shoot-root communication is an important internal cue. The latter is known as the autoregulation of nodulation (AON), and is believed to consist of two long-distance signals: a root-derived signal that is generated in infected roots and transmitted to the shoot; and a shoot-derived signal that inhibits nodulation systemically [103-104]. Therefore, AON represents a strategy through which the host plant can balance the symbiotrophic N nutrition with the energetically more “cheap” combined N nutrition.
Recent findings on autoregulation of nodulation suggest that the root-derived ascending signals to the shoot are short peptides belonging to the CLE peptide family [105] [106]. The leucine-rich repeat receptor-like kinase HAR1 of Lotus and its homologues in M. truncatula and P. sativum (SUNN and Sym29, respectively) mediate AON and also the nitrate inhibition of nodulation, presumably by recognizing the root-derived signal [107-110] (Figure 3).
It was suggested that NF signaling induces expression or posttranslation processing of CLE peptides, which likely function as ascending long-distance signals to the shoot [110]. Thus, NF signaling is related to autoregulation as well, but in some indirect way. It is also worth noting that NF signaling pathway appears to work in mature nodules, since aforementioned “early nodulation genes” belonging to CSP, as well as NF receptor kinase genes, are highly expressed in nodule tissues (76, 111). Perhaps the active NF signaling is needed to prevent the induction of defense-like responses and/or to restrict the release of rhizobia into precise cell layers, thus regulating the formation of symbiotic interface [112].
3.2. Pea (Pisum sativum L.) as a unique example of increased specificity in plant-microbe interaction
Being one of the most ancient crops known to humanity, nowadays garden pea (Pisum sativum L.) is widely distributed in the world. According to the recent data, pea is a third most important legume for food industry, following beans and soybeans [113]. It is also the popular model for various genetic and physiological researches, including the studying of symbiosis with nodule bacteria. Despite the fact that work with pea is complicated by the presence of some negative properties, such as relatively large (about 4000 Mb) genome, low seed productivity, and poor transformation capability, the use of this object in study of symbiotic relationships continues and brings significant results.
There are several pea genes known to participate in NFs’ reception, with the most interesting of them being Sym2. This gene was first described in the 1970s as determinant of “resistance” to nodulation in pea cultivars from Afghanistan and Iran [114, 115]. While being unable to form nodules with the majority of natural Rhizobium leguminosarum bv. viciae (Rlv) strains obtained from European soils, these cultivars have demonstrated the ability to interact normally with strains from the Middle East, such as strain Rlv TOM [115]. This feature is controlled by specific recessive allele of Sym2 named “Afghan allele” (Sym2A). Presence of Sym2A in homozygous state leads to block of infection thread progression in the root hair, similarly to phenotype of sym37 mutants [55]. Later it was shown that Rlv strains able to nodulate “Afghan” cultivars have special gene called nodX, which is involved in the modification of NF structure [116, 117]. NodX encodes the acetyltransferase providing O-acetylation on reducing end of NF sugar backbone. Thus, only nodX-modified NFs can be recognized by plants with Sym2A allele, although Ovtsyna et al. (2000) [118] show that fucosylation on the same position controlled by nodZ gene can also induce nodulation of “Afghan” peas.
More than 20 years ago, Sym2 was localized on the pea genetic map. Using RAPD (Random Amplification of Polymorphic DNA) markers, Kozik and colleagues [119] created the detailed map of pea I linkage group fragment including Sym2 and a few other symbiotic genes (such as Nod3 and PsENOD7). Based on the fact that plants with Sym2A allele show the “Afghan” phenotype then exposed to NF with specific structure, it was suggested that Sym2 protein could act as an “entry” receptor during preinfection stage (similar to NFR1 in Lotus or LYK3 in Medicago).
When Pisum gene Sym37 was shown to be orthologous for NFR1 [55], it was at first proposed as a candidate for Sym2. This was strongly supported by the fact that the missense mutation in Sym37 carried by Pisum mutant line RisNod4 led to Nod- phenotype (the absence of nodulation), which could be suppressed by Rlv strain A1 known to produce broad specter of NFs, including nodX-modified one [55]. However, the paralogue of Sym37, gene K1, was discovered shortly after, the similar structure of which indicated a possible involvement in the reception of NF, although the purpose of this additional NF receptor remained unclear.
The comparison of Sym37 and K1 nucleotide sequences obtained from “Afghan” (Sym2A) and “European” pea varieties, as well as amino acid sequences of their corresponding proteins, shows that neither of these genes possesses any features correlating with “Afghan” phenotype [55]. Thus, there must be another determinant corresponding to Sym2. Recently, the promising candidate was found – the gene named LykX by the authors, which is the second paralogue of Sym37 localized in the same region of the pea genome (Sulima et al., 2015, in preparation). Analysis of the LykX protein sequences revealed that there are amino acid substitutions within first LysM module of receptor domain typical for plants with “Afghan” phenotype [120]. Simultaneously, Li and colleagues [121] compared the sequence of Sym37 from series of pea genotypes that differ in interaction with rhizobia mutant on nodE gene determining the structure of fatty acid on nonreducing end of NF. It was shown that the efficiency of interaction with mutant strain strictly correlates with particular variation of Sym37. Similar situation was observed for interaction between nodX and Sym2 (LykX) genes: “Afghan” pea varieties requiring NF with additional acetyl group on reducing end of molecule also display characteristic features in structure of receptor protein LykX.
We proposed a model, based on the above, according to which the less specific “recognition” receptor (Sym10, perhaps in complex with other proteins) perceives the NF signal per se and “anchors” NF molecule on the membrane, subsequently “presenting” it to other components of reception complex, with reducing end being tested by Sym2 (LykX), and nonreducing by Sym37 [122]. Only if all participants in the process react positively will the signal be considered as adequate, and symbiogenesis will start properly (see Figure 4). So, in pea not only one ortholog of Lotus\n\t\t\t\t\tNFR1, but two closely related paralogs – Sym37 and Sym2 – are involved in genetic control of Nod-factor reception. This is not surprising, if we take into account the complexity of Nod-factor molecule and the importance of its proper recognition for successful development of symbiosis.
Figure 4.
Hypothetical model for precise recognition of Nod-factor structure by receptor kinases in pea. The model is proposed by Dr. V.A. Zhukov (ARRIAM, St. Petersburg, Russia). At first step, less specific receptor (probably, Sym10) anchors NF molecule onto the membrane; then it presents it to Sym37, which tests the structure of the nonreducing end, and to Sym2, which tests the structure of reducing end. When both Sym37 and Sym2 bind NF, they activate downstream components of signal transduction pathway.
4. Conclusion
Among all the multicellular eukaryotes, plants have the greatest need for the beneficial interaction with microorganisms, as they lack active movement and therefore cannot choose more advantageous habitat. That kind of restriction can be compensated by the ability of photosynthesis, as carbon compounds produced by plants are a significant stimulus for various microbes to cooperate with them. As a result of such cooperation, plant acquires an access to the adaptations of microsymbiont, and vice versa, according to a principle of genome complementarity that was recently formulated by Prof. I.A. Tikhonovich and Dr. N.A. Provorov (ARRIAM, Russia) [122]. It means that, in spite of lacking the nitrogenase genes in its own genome, plant “exploits” corresponding part of microorganism’s genome in order to implement biological nitrogen fixation, while rhizobia “exploit” plant genes controlling photosynthetic apparatus, and so forth. Thereby the plant-microbe system acquires an advantage over plants and microbes that compete for survival separately.
The role of symbioses in the evolution of life, and plants in particular, cannot be underestimated. One can state that the tendency to establish mutually beneficial associations with microorganisms is an essential feature of plants, which has a wide variety of manifestations through a long coevolution of symbiotic partners. Photosynthesis itself, the main distinctive feature of plants, is provided by chloroplasts – the descendants of ancient symbiotic cyanobacteria. According to modern conception, plant colonization of land was possible primarily due to the symbiotic association with arbuscular mycorrhiza fungi. AM, in turn, is considered as a basis for the development of highly specific root-nodule symbiosis characteristic for legume plants. The possible path of the AM origin and its connection with RN was largely understood by studying Geosiphon pyriformis – the only representative of the phylum Glomeromycota that does not form symbiotic association with higher plants.. Instead, it contains intracellular symbiotic nitrogen-fixing cyanobacteria of the Nostoc genus which are essential for its proper nutrition and development [123, 124]. The intensive exchange of products of nitrogen, carbon, and phosphorus metabolism between partners indicates that mechanisms of reciprocal nutrients’ transport probably emerged in symbiotic systems formed by Geosiphon and Nostoc ancestors and lately have been recruited in the evolution of AM [124, 125]. The transition from Geosiphon-Nostoc-type association to AM could occur through an intermediate “triple” symbiosis including plant, common ancestor of AM fungi, and Geosiphon, and ancestral forms of Nostoc, with subsequent loss of cyanobiont. It should be noted that ancient symbiotic fungi presumably carried additional bacterial symbionts both on the surface and in the cytoplasm. In the cells of modern Glomeromycota, including Geosiphon, various symbiotic bacteria are found, including those capable of nitrogen-fixation (close to β-proteobacteria of Burkholderia genus, some members of which were shown to form the RN symbiosis with legumes; see above) [126]. Thus, the AM symbiosis could be the direct “gateway” for introducing symbiotic bacteria, including the ascendants of modern rhizobia, into plant tissues. This suggestion is also supported by the existence of CSP and the similarity of rhizobial and fungal signal molecules.
Emergence of Nod-factor signaling was among the most important factors that determined the evolutionary success of legume-rhizobial symbiosis. The wide variety of Nod-factors as well as finely tuned receptor system in plants ensure that only specific partners will meet each other in the soil and consequently form a superorganism with high level of genetic and metabolic integration. This appears to be a basis for evolution of the efficiency of symbiotic pairs, instead of single organisms – the results we now observe.
Legumes provide both an important food source for humanity and a unique model for investigation of the evolution and the underlying genetic mechanisms of mutualistic plant-microbe symbioses. Further studies of the genetic bases of signal interactions between plants and microbes can provide more information about evolution of such a mutually beneficial association, as well as about spreading of the legumes across the world. Discovery of genes involved in recognition of partners, transduction of symbiotic signals and overall “management” of symbiosis will also provide a useful tool for agriculture, as the knowledge obtained from this studying will facilitate the creation of highly-effective specific symbiotic pairs between crop plants and nitrogen-fixing bacteria in field..
Acknowledgments
A.S. Sulima was financially supported by the grant of Russian Foundation for Basic Research (RFBR) # 14-04-32289_mol-a. V.A. Zhukov, O.Y. Shtark, A.Y. Borisov, and I.A. Tikhonovich were financially supported by the grant of Russian Science Foundation (RSF) # 14-24-00135. The authors thank Dr. M.N. Povydysh (Saint-Petersburg State Chemical Pharmaceutical Academy, St.Petersburg, Russia) for help in preparation of figures.
\n',keywords:"legume-rhizobial symbiosis, Nod factor, plant signaling, genetic control",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/49073.pdf",chapterXML:"https://mts.intechopen.com/source/xml/49073.xml",downloadPdfUrl:"/chapter/pdf-download/49073",previewPdfUrl:"/chapter/pdf-preview/49073",totalDownloads:1600,totalViews:773,totalCrossrefCites:1,totalDimensionsCites:2,hasAltmetrics:0,dateSubmitted:"October 9th 2014",dateReviewed:"July 3rd 2015",datePrePublished:null,datePublished:"October 21st 2015",dateFinished:null,readingETA:"0",abstract:"Leguminous plants (or Legumes, family Fabaceae) are known to form symbioses with extremely broad range of beneficial soil microorganisms (BSM), representing examples of almost all plant-microbe mutualistic systems. One of the most ecologically important and well-studied legume beneficial symbioses is root nodule (RN) symbiosis (symbiotic association with nitrogen-fixing bacteria). Compared with other interactions of legumes with BSM, RN symbioses demonstrate high level of genetic and metabolic integrity, which implies, inter alia, highly specific mutual recognition of partners. In this chapter, we describe the mechanisms of plant-microbe recognition during initial steps of RN symbiosis using the interaction of model legumes - pea (Pisum sativum L.), barrel medic (Medicago truncatula Gaertn.) and Lotus japonicus (Regel.) K. Larsen - with rhizobia as an example. We paid particular attention to symbiotic system of P. sativum since pea, besides its importance as a model object of genetics, is also a valuable crop plant. Hence, in conclusion, we discuss the potential to use obtained knowledge for optimizing the broad spectrum of plant adaptive functions and to improve the sustainability of legume crop production.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/49073",risUrl:"/chapter/ris/49073",book:{slug:"plants-for-the-future"},signatures:"Sulima Anton Sergeevich, Zhukov Vladimir Alexandrovich, Shtark\nOksana Yurievna, Borisov Alexey Yurievich and Tikhonovich Igor\nAnatolievich",authors:[{id:"73360",title:"Dr.",name:"Alexey",middleName:"Y.",surname:"Borisov",fullName:"Alexey Borisov",slug:"alexey-borisov",email:"ayborisov@yandex.ru",position:null,institution:null},{id:"81134",title:"Dr.",name:"Vladimir",middleName:null,surname:"Zhukov",fullName:"Vladimir Zhukov",slug:"vladimir-zhukov",email:"zhukoff01@yahoo.com",position:null,institution:null},{id:"81139",title:"Dr.",name:"Oksana",middleName:"Yurievna",surname:"Shtark",fullName:"Oksana Shtark",slug:"oksana-shtark",email:"oshtark@yandex.ru",position:null,institution:{name:"All-Russian Research Institute of Agricultural Microbiology",institutionURL:null,country:{name:"Russia"}}},{id:"81142",title:"Prof.",name:"Igor",middleName:null,surname:"Tikhonovich",fullName:"Igor Tikhonovich",slug:"igor-tikhonovich",email:"contact@arriam.spb.ru",position:null,institution:{name:"All-Russian Research Institute of Agricultural Microbiology",institutionURL:null,country:{name:"Russia"}}},{id:"173550",title:"MSc.",name:"Anton",middleName:null,surname:"Sulima",fullName:"Anton Sulima",slug:"anton-sulima",email:"sulan555@mail.ru",position:null,institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Legume-rhizobial symbiosis: An example of highly integrated plant-microbe system",level:"1"},{id:"sec_2_2",title:"2.1. Specificity of legume-rhizobial symbiosis",level:"2"},{id:"sec_3_2",title:"2.2. Initial steps of rhizobium-legume symbiosis",level:"2"},{id:"sec_5",title:"3. Molecular genetics of Nod-factor signaling in legumes",level:"1"},{id:"sec_5_2",title:"3.1. Nod-factor signaling in model legumes",level:"2"},{id:"sec_6_2",title:"3.2. Pea (Pisum sativum L.) as a unique example of increased specificity in plant-microbe interaction",level:"2"},{id:"sec_8",title:"4. Conclusion",level:"1"},{id:"sec_9",title:"Acknowledgments",level:"1"}],chapterReferences:[{id:"B1",body:'Mulligan RM, Chory J, Ecker JR. Signaling in plants. Proc Natl Acad Sci USA. 1997;94: 2793-2795.'},{id:"B2",body:'Nakagawa T, Kaku H, Shimoda Y, Sugiyama A, Shimamura M, Takanashi K, Yazaki K, Aoki T, Shibuya N, Kouchi H. 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Mol Plant Microbe Interact. 1999;12(3): 252-258.'},{id:"B118",body:'Ovtsyna AO, Schultze M, Tikhonovich IA, Spaink HP, Kondorosi E, Kondorosi A, Staehelin C. Nod factors of Rhizobium leguminosarum bv. viciae and their fucosylated derivatives stimulate a nod factor cleaving activity in pea roots and are hydrolyzed in vitro by plant chitinases at different rates. Mol Plant Microbe Interact. 2000;13(8): 799-807.'},{id:"B119",body:'Kozik A, Matvienko M, Scheres B, Paruvangada VG, Bisseling T, van Kammen A, Ellis TH, LaRue T, Weeden N. The pea early gene PsENOD7 maps in the region of linkage group I containing sym2 and leghemoglobin. Plant Mol Biol. 1996;31(1): 149-156.'},{id:"B120",body:'Zhukov VA, Sulima AS, Porozov YB, Borisov AY, Tikhonovich IA. Polymorphism in gene sequence of LysM receptor kinase is associated with Sym2-controlled nodulation in pea (Pisum sativum L.). Proceedings of 18th International Conference on Nitrogen Fixation (14–18 October 2013, Myazaki, Japan): 76.'},{id:"B121",body:'Li R, Knox MR, Edwards A, Hogg B, Ellis TH, Wei G, Downie JA. Natural variation in host-specific nodulation of pea is associated with a haplotype of the SYM37 LysM-type receptor-like kinase. Mol Plant Microbe Interact. 2011;24(11): 1396-1403.'},{id:"B122",body:'Tikhonovich IA, Andronov EE, Borisov AY, Dolgikh EA, Zhernakov AI, Zhukov VA,Provorov NA, Roumiantseva ML, Simarov B.V. The Principle of Genome Complementarity in the Enhancement of Plant Adaptive Capacities. Russian J Genet. 2015;51(9): 831–846. '},{id:"B123",body:'Schüßler A. Molecular phylogeny, taxonomy and evolution of Geosiphon pyriformis and arbuscular mycorrhizal fungi. Plant Soil. 2002;244: 75-83.'},{id:"B124",body:'Schüßler A, Wolf E. Geosiphon pyriformis – a glomeromycotan soil fungus forming endosymbiosis with cyanobacteria. In: Declerck S, Strullu DG, Fortin JA. (eds.), In Vitro Culture of Mycorrhizas. Berlin–Heidelberg–New York: Springer; 2005. 271-290.'},{id:"B125",body:'Kluge M, Mollenhauer D, Wolf E, Schüßler A. The Nostoc-Geosiphon endocytobiosis. In: Rai AN, Bergman B, Rasmussen U. (eds.), Cyanobacteria in Symbiosis. Kluwer Academic Publishers; 2003. 19-30.'},{id:"B126",body:'Minerdi D, Bianciotto V, Bonfante P. Endosymbiotic bacteria in mycorrhizal fungi: from their morphology to genomic sequences. Plant Soil. 2002;244: 211-219.'}],footnotes:[],contributors:[{corresp:null,contributorFullName:"Sulima Anton Sergeevich",address:null,affiliation:'
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Farinazzi-Machado",authors:[{id:"32415",title:"Dr",name:"Sandra",middleName:"Maria",surname:"Barbalho",fullName:"Sandra Barbalho",slug:"sandra-barbalho"},{id:"33325",title:"MSc",name:"Flávia",middleName:"Maria Vasques",surname:"Farinazzi-Machado",fullName:"Flávia Farinazzi-Machado",slug:"flavia-farinazzi-machado"}]},{id:"19993",title:"Soybean the Main Nitrogen Source in Cultivation Substrates of Edible and Medicinal Mushrooms",slug:"soybean-the-main-nitrogen-source-in-cultivation-substrates-of-edible-and-medicinal-mushrooms",signatures:"Diego Cunha Zied, Jean-Michel Savoie and Arturo Pardo-Giménez",authors:[{id:"29145",title:"Dr.",name:"Diego",middleName:null,surname:"Zied",fullName:"Diego Zied",slug:"diego-zied"},{id:"45408",title:"Dr.",name:"Jean-Michel",middleName:null,surname:"Savoie",fullName:"Jean-Michel Savoie",slug:"jean-michel-savoie"},{id:"45409",title:"Dr.",name:"Arturo",middleName:null,surname:"Pardo-Giménez",fullName:"Arturo Pardo-Giménez",slug:"arturo-pardo-gimenez"}]},{id:"19994",title:"Assessing Compositional Differences in Soy Products and Impacts on Health Claims",slug:"assessing-compositional-differences-in-soy-products-and-impacts-on-health-claims",signatures:"Joyce Boye and Sabine Ribéreau",authors:[{id:"29137",title:"Dr.",name:"Joyce",middleName:null,surname:"Boye",fullName:"Joyce Boye",slug:"joyce-boye"},{id:"136334",title:"Dr.",name:"Sabine",middleName:null,surname:"Ribéreau",fullName:"Sabine Ribéreau",slug:"sabine-ribereau"}]}]}]},onlineFirst:{chapter:{type:"chapter",id:"68154",title:"A Comprehensive Overview of the Potential of Tequila Industry By-Products for Biohydrogen and Biomethane Production: Current Status and Future Perspectives",doi:"10.5772/intechopen.88104",slug:"a-comprehensive-overview-of-the-potential-of-tequila-industry-by-products-for-biohydrogen-and-biomet",body:'\n
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1. Tequila production process and its main by-products: agave bagasse and tequila vinasse
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Tequila is a Mexican alcoholic beverage obtained from the distillation of fermented juice of the mature stems of Agave tequilana Weber var. azul. It possesses appellation of origin since 1974 and has received international recognition in the market. As an example, tequila-processing plants produced around 309 million liters of tequila in 2018, of which ∼72% were exported, highlighting its international demand [1]. Thus, tequila production represents one of the most important activities for Mexico. In general, there are three major stages in the tequila production process, namely agave juice (must) extraction, fermentation, and distillation. In the first stage, the agave juice containing fermentable sugars is first obtained either through cooking or not-cooking processes. In the former, agave stems are cooked in ovens or autoclaves at high temperatures (95–120°C) for a long time (usually 8–12 h). Once cooked, the water-soluble carbohydrates are extracted by simultaneous shredding and pressure washing followed by pressing. In the latter, raw agave juice is obtained from previously shredded raw agave stems using hot water (80°C) through the use of equipment called diffuser. Afterward, the carbohydrates contained in the raw agave juice are hydrolyzed for 4–6 h under acidic conditions (pH 1.8–3) at high temperatures (80–85°C) [2, 3]. In the second stage, the agave juice is subjected to an alcoholic fermentation process, wherein agave sugars are transformed to ethanol, carbon dioxide, and other compounds (e.g. aldehydes, esters, furans, and ketones) by the action of different microorganisms, particularly yeasts [2, 3]. In the third stage, the fermented must is subjected to a two-step distillation process to obtain tequila [2, 4].
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At this point, it must be noted that enormous quantities of solid (Agave tequilana bagasse, hereinafter referred to as AB) and semi-liquid (tequila vinasse, hereinafter referred to as TV) by-products are generated each year during the process of tequila manufacturing, particularly after the stages of agave juice extraction and distillation, respectively (Figure 1). It has been estimated that 1.4 kg of AB and 10–12 L of TV are obtained by each liter of tequila produced [4, 5]. Considering the tequila production of 264.9 ± 31.2 million liters reported in the last lustrum (2014–2018) by the Tequila Regulatory Council [1], the generation of AB and TV is equivalent to 370,916 ± 43,701 tons and 2914.3 ± 343.3 million liters per year, respectively. The physicochemical composition of a given stream of AB and TV may change from batch to batch, depending mainly on the raw materials used (e.g. maturity of agave), juice extraction process (cooked and uncooked agave), and the prevailing conditions of fermentation and distillation in the case of TV [3, 6, 7, 8, 9]. Despite such influential factors, there are some general features that can be distinguished between AB and TV. Concerning AB, it is a lignocellulosic material with a composition of 11–57% hemicellulose, 31–53% cellulose, 7–15% lignin, and 19–57% extractives [4, 8, 9]. Extractives are the nonstructural components of lignocellulose, including fats, phenolics, resin acids, waxes, and inorganics [10]. Regarding TV, it is a brown and acidic wastewater (pH of 3.4–4.5, total acidity of 1500–6000 mg-CaCO3/L) containing high chemical oxygen demand (COD) concentration of 40–100 g/L, as well as high total solids (25–50 g/L), salts, metal ions, organic acids, phenolic compounds, and melanoidins [3, 5, 7, 11].
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Figure 1.
Tequila manufacturing process and generation of agave bagasse and tequila vinasse.
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Regarding the management and final disposition of AB and TV, it must be highlighted that only a small part of the whole AB generated is used in the manufacturing of different products such as animal feeds, fertilizers, bricks, mattresses, furniture, and packing materials [12, 13]. Therefore, most of AB is treated as waste and returned to the fields in the form of piles that are directly exposed to outdoor conditions, where they may cause leachates, odor generation, and atmospheric pollution [12, 14]. In the case of TV, it has been reported that approximately 80% of the total volume of TV generated is discharged without receiving adequate treatment into receiving water bodies (e.g. rivers, lakes, and sewer system) or directly onto soil, which in turn can result in adverse environmental and human health impacts [5]. To valorize AB and TV and to face such disposal problems, nowadays, engineers and scientists are focusing on using them as potential substrates for the production of biofuels and value-added products in a tequila biorefinery framework. However, there are still several challenges that must be overcome before full-scale facilities could be implemented. This chapter provides an extended insight on (i) the pretreatment or conditioning steps of tequila by-product streams; (ii) the use of AB and TV to produce biogenic hydrogen (bioH2) and methane (bioCH4) via anaerobic fermentation processes, with a special emphasis on reactor configuration and operation, producing/competing metabolic pathways and the characterization of microbial communities; (iii) the development of multi-stage anaerobic digestion (AD) processes; and (iv) limitations and avenues for future research toward improving bioH2 and bioCH4 production.
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2. Pretreatment/conditioning of agave bagasse and tequila vinasse
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AD is the core technology for the treatment of several biodegradable organic wastes with concomitant bioenergy recovery in the form of biogas that is rich in bioCH4, although bioH2 may also be recovered. Besides bioCH4 recovery, AD is advantageous due to low energy and nutrient requirements, low sludge production, and high organic loading capacity (20–35 g-COD/L-d) [15]. From a biochemical point of view, AD consists of four successive steps, namely hydrolysis, acidogenesis, acetogenesis and methanogenesis [15, 16].
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It is worth mentioning that in the case of AB, the low biodegradability due to its lignocellulosic structure constitutes one of the main barriers to accelerate hydrolysis and enhance the recovery of bioH2/bioCH4. In the case of TV, its complex composition such as high COD, high solids content, unbalanced nutrient, presence of putative toxicants (e.g. organic acids, phenols, melanoidins) and the negligible alkalinity along with the high concentration of components with a tendency to suffer very rapid acidification constitutes the major limitations for bioH2/bioCH4 production. Thus, in practice, before the feedstock (AB or TV) is sent to either the hydrogenogenic or the methanogenic stage, a pretreatment/conditioning step is commonly performed as a prerequisite to improve its biodegradability as well as to prevent DF/AD processes from potential toxicants, elevated solids, and organic overloading (Figure 2). Unlike AB, TV is only subjected to one or more conditioning steps. Commonly, they consist of lowering temperature, rising pH (adding alkalinity), diluting, adding complementary nutrients, and removing suspended solids (Figure 2).
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Figure 2.
Flow chart of biohydrogen and biomethane production process from agave bagasse and tequila vinasse.
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In contrast, AB is exposed to a drying step to prevent fungal and bacterial growth, mainly for long-time storage. Once AB is dried, it is subjected to a mechanical milling step devoted to reducing particle size, thereby increasing surface area, which makes carbohydrates more easily available for downstream processes. The mechanical fractionation also makes AB more homogeneous and easier to handle. After milling, the pretreatment applied to AB for either bioH2 or bioCH4 production may differ. For such purposes, dilute acid, alkaline hydrogen peroxide, detoxification and enzymatic hydrolysis have been evaluated in detail. Arreola-Vargas et al. [8] pretreated cooked and uncooked AB through a dilute acid hydrolysis at 5% (w/v), 56.4–123.6°C, 1.2–2.8% HCl, and 0.3–3.7 h reaction time, finding temperature as the principal factor which could increase the hydrolysis yield. Total sugars concentrations obtained were 27.9 and 18.7 g/L for cooked and uncooked AB hydrolysates, respectively. The higher yield of cooked AB was attributed to the fact that during the elaboration of tequila using cooking process, agave stems receives an in situ thermal treatment. Nevertheless, high concentrations (up to 1200 mg/L) of hydroxymethylfurfural (HMF) were detected in the cooked AB. In a further study, Arreola-Vargas et al. [17] pretreated AB through either acid or enzymatic hydrolysis for bioCH4 and bioH2 production. Acid hydrolysis was carried out for 1.3 h at 5% (w/v) of AB, 2.7% HCl and 124°C, while enzymatic hydrolysis was performed at 4% (w/v) of AB in 50 mM citrate buffer at pH 4.5 with Celluclast 1.5 L at 40 filter paper units (FPU) for 10 h at 45°C. As a result, 17.3 and 8.9 g-total sugars/L were obtained from acid and enzymatic hydrolysis, respectively. However, unlike enzymatic hydrolysates, acid hydrolysates promoted the generation of potential inhibitors such as formic acid (HFor), acetic acid (HAc), and phenolic and furanic compounds. In another study, Breton-Deval et al. [18] compared the type of acid catalyst (HCl vs. H2SO4) on the chemical composition of hydrolysates of AB. Overall, results showed that the use of HCl induced higher sugar recoveries than the use of H2SO4, 0.39 versus 0.26 g-total sugars/g of AB. Furthermore, the H2SO4 hydrolysate contained higher concentrations of HAc and furans. To remove undesirable compounds derived from acid hydrolysis of AB (30 g AB, HCl 1.9%, 130°C, 132 min reaction time), Valdez-Guzmán et al. [19] performed detoxification of acid AB hydrolysates using 1% (w/v) powdered coconut shell-activated carbon. Under batch conditions (pH 0.6, 20 min reaction time, 150 rpm, room temperature), the highest removal of HAc and phenols obtained were 89 and 21%, respectively, with minimal losses of fermentable sugars (3.6%). Besides, during acid hydrolysis, a hydrolysis yield of almost 40% of total sugars, a delignification of 44%, complete hydrolysis of hemicellulose, and no detection of furfural or HMF in the hydrolysate was obtained. In another study, Contreras-Dávila et al. [20] pretreated AB for bioH2 production using Celluclast 1.5 L during 10 h, obtaining sugar yields in the range of 0.19–0.38 g-total sugars/g of AB. Montiel and Razo-Flores [21] also pretreated AB by enzymatic hydrolysis to produce bioH2 and bioCH4. The conditions were 3.5% (w/v) of AB with Celluclast 1.5 L at 18 FPU/g of AB at 40°C during 12 h. The resulting hydrolysate had 27.2 g/L of total COD with 5.3 ± 0.8 g/L of total sugars (0.15 g-total sugars/g of AB) which contributed to 20% of the total COD, citrate buffer with 26%, enzyme with 38%, and other non-determined components with 16%. In the same year, Galindo-Hernández et al. [22] used alkaline hydrogen peroxide (AHP) as a pretreatment to remove lignin before enzymatic hydrolysis of AB. Under the experimental conditions tested (5% w/v of AB, 2% w/v of AHP, 50°C, pH 11.5 using NaOH, 120 rpm, 1.5 h reaction time), 97% of the lignin was removed and 88% of holocellulose (cellulose and hemicellulose) was recovered, promoting that the polysaccharide fractions are more available or exposed to a further enzymatic attack. The authors also demonstrated, in delignification terms, that it is better to use hydrogen peroxide and NaOH solution in a combined form than in a separate or sequential way and that using binary enzymatic hydrolysis (cellulases and hemicellulases) may improve the yield, percentage, and productivity of saccharification, which were 0.19 g-total sugars/g of AB, 26.7% and 17.1 g-total sugars/g of AB-h, respectively. The synergistic effect of using binary enzymatic hydrolysis was verified by Montoya-Rosales et al. [23], who compared the enzymatic hydrolysis of AB using a binary enzyme preparation that is composed of Celluclast 1.5 L and Viscozyme L with a single enzyme, that is, Stonezyme, which is a commercial cellulase preparation. The results showed that hydrolysis yields were higher with the binary enzymatic hydrolysis, 0.27 versus 0.22 g-carbohydrates/g of AB and 0.5 versus 0.28 g-COD/g of AB.
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3. Biohydrogen production from agave bagasse and tequila vinasse
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H2 is one of the most promising alternative energy carriers to partly fulfill the growing energy demands and overcome fossil fuel dependency and has attracted global attention for its highest energy content per unit weight (142 kJ/g) and carbon-free nature since it generates only water vapor during combustion. It can be used for a variety of purposes either alone to produce energy in fuel cells and combustion engines or blended with CH4 to produce a superior fuel known as hythane [24]. Comparing thermochemical, electrochemical, and biological ways of producing H2, the latter is considered the most sustainable because it is eco-friendlier and less energy intensive. Among biological processes, dark fermentation (DF) is thought to be practically applicable at large commercial scales in a near time horizon owing to its capability of producing bioH2 at higher rates and versatility of utilizing several different types of carbohydrate-rich wastes as substrate [25]. In this connection, since AB and TV are abundantly available, renewable, and have a high content of carbohydrates, they have been considered as suitable feedstocks for bioH2 production. In the following sections, the operational performance, metabolic pathways, and microbial communities of DF systems treating either AB or TV are extensively reviewed.
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3.1 Operational performance
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Regarding the use of AB for bioH2 production (Table 1), the first systematic study dealing with bioH2 production from AB was conducted by Arreola-Vargas et al. (2016) [17], who assessed the use of AB hydrolysates obtained either from acid or enzymatic pretreatment for bioH2 production. To the end, different proportions of hydrolysate (20, 40, 60, 80, and 100% v/v) were tested in an automatic methane potential test system (AMPTS II provided by Bioprocess control) at 37°C, 120 rpm, initial pH of 7, and using 10 g-volatile suspended solids (VSS)/L of heat-pretreated anaerobic granular sludge. Overall, the best bioH2 production performance was achieved in the assays with enzymatic hydrolysate, obtaining the maximal bioH2 yield (HY2) and volumetric bioH2 production rate (VHPR) of 3.4 mol-H2/mol-hexose and 2.4 NL-H2/L-d, respectively, both with the hydrolysate at 40% (v/v). The lower values observed with the acid hydrolysate were attributed to the feedstock composition in terms of sugar profile, weak acids, furans, and phenolics.
Comparison of the literature data on biohydrogen production efficiency using pretreated agave bagasse as feedstock.
Notes: All studies were conducted using thermally treated anaerobic granular sludge; aInitial pH value; bmol-H2/mol hexose; cmol-H2/mol of consumed sugar; dValue measured during the starting period; NR: not reported.
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In another work, Contreras-Dávila et al. [20] used an enzymatic AB hydrolysate for bioH2 production in a continuously stirred tank reactor (CSTR) and a trickling bed reactor (TBR), which were operated up to 87 days under different organic loading rates (OLR, 17–60 g-COD/L-d) obtained by varying hydrolysate concentration and/or hydraulic retention time (HRT). The reactor configurations showed different performances. In the CSTR, the VHPR and HY2 displayed an inverse correlation with maximum values of 2.53 L-H2/L-d and 1.35 mol-H2/mol-substrate, attained at OLR of 52.2 and 40.2 g-COD/L-d, respectively, both with 6 h HRT. The bioH2 concentrations of the produced gas were between 18 and 35% (v/v). In contrast, in the TBR, increasing OLR up to 52.9 g COD/L-d (4 h HRT) simultaneously enhanced VHPR and HY2, attaining values of 3.45 L-H2/L-d and 1.53 mol-H2/mol-substrate, respectively, with bioH2 concentrations of the produced gas between 26 and 52% (v/v). The observed bioH2 production performances were explained by differences in the liquid and gas flow rates, agitation speed, and liquid-gas interface between the CSTR and TBR configurations, which in turn may have caused distinct bioH2 concentrations in the liquid phase.
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In a further study which set up to assess the batch bioH2 production from pretreated AB with AHP followed by binary enzymatic saccharification (hemicellulases + cellulases), Galindo-Hernández et al. [22] performed a series of experiments in the AMPTS II system at 37°C, 150 rpm, initial pH of 7.5, and using an organic load of 5 g-COD/L and 13.5 g-volatile solid (VS)/L of thermally treated anaerobic sludge. The results suggested that delignification of AB and subsequent hydrolysis with a synergistic enzymatic mixture had a beneficial effect on bioH2 production, obtaining a YH2 of 3 mol-H2/mol-hexose and a VHPR of 0.93 NL-H2/L-d.
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In an investigation on the effect of OLR and agitation speed on the continuous bioH2 production from enzymatic hydrolysates of AB, Montiel and Razo-Flores [21] operated for 84 days a mesophilic (35°C) CSTR reactor (with a working volume of 1 L) inoculated with 4.5 g-VS/L of heat-treated anaerobic granular sludge and operated at different OLRs (40–52 g-COD/L-d), which were achieved by varying hydrolysate concentration. The evaluated stirring speeds were in the range of 150–300 rpm, while the HRT was maintained at 6 h during the whole operation. The authors observed that the strategy of increasing the agitation speed from 150 to 300 rpm favored both the VHPR and bioH2 content in the gas phase, obtaining 6 NL-H2/L-d and 55% (v/v), respectively, at an OLR of 44 g-COD/L-d. Such results indicated that the increase of the agitation speed in the CSTR improved the transfer of dissolved bioH2 from the liquid to the reactor gas phase, overcoming one of the limitations for bioH2 production previously observed by [21].
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In another study, Toledo-Cervantes et al. [26] addressed the bioH2 production from enzymatic hydrolysates of AB using an anaerobic sequencing batch reactor (AnSBR) with a working volume of 1.25 L. The reactor was inoculated with 10 g-VS/L of thermally treated anaerobic sludge and operated at 37°C, pH 4.8, and at four OLR (10.6–21.3 g-COD/L-d), which were modified by decreasing the cycle time (from 24 to 12 h) and increasing the COD concentration (from 8 to 12 and 16 g/L). Results showed that the highest OLR promoted the highest VHPR of 0.6 NL-H2/L-d. Conversely, the YH2 remained constant at 1.6 mol-H2/mol of consumed sugar.
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In a similar study, Valdez-Guzmán et al. [19] showed the importance not only of optimizing pretreatment but also of removing several compounds (e.g. furfural, HMF, phenolic compounds, and organic acids) that are generated during its application. They compared the bioH2 production potential of undetoxified and detoxified acid hydrolysates from AB. The authors reported ∼39 and ∼9% increases on YH2 and VHPR, respectively, comparing detoxified AB with activated carbon and undetoxified AB, 1.71 versus 1.23 mol-H2/mol of consumed sugar and 1.51 versus 1.38 NL-H2/L-d. Such increments were correlated to changes in the fermentation by-products suggesting the occurrence of different pathways or changes in the microbial community, since the detoxified hydrolysate produced HAc and butyric acid (HBu), while lactic acid (HLac) was found in the undetoxified hydrolysate.
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Most recently, Montoya-Rosales et al. [23] compared and evaluated the continuous bioH2 production from individual and binary enzymatic hydrolysates of AB in two different configurations, that is, CSTR and TBR. The experiments were carried out at 37°C and pH 5.5 and at various OLRs 36–100 g-COD/L-d, which were achieved by increasing the influent concentration, while keeping the HRT constant at 6 h. The results showed that the performance was highly dependent on the type of reactor and OLR. Regarding the CSTR configuration, in general, the higher OLR resulted in higher VHPR. Nonetheless, the bioH2 production efficiency using individual enzymatic hydrolysate (0.72–2.25 NL-H2/L-d and 11.8–20.4 NL-H2/kg of AB) was lower compared to that obtained with the binary enzymatic hydrolysate (3.9–13 NL-H2/L-d and 83.3–117.9 NL-H2/kg of AB), with the maximum VHPR and YH2 at 100 and 60 g-COD/L-d and 90 and 52 g-COD/L-d, respectively. Regarding the TBR configuration, the binary enzymatic hydrolysate also outperformed the individual one, obtaining the maximum VHPR of 5.76 NL-H2/L-d at an OLR of 81 g-COD/L-d and YH2 of 72.4 NL-H2/kg of AB at an OLR of 69 g-COD/L-d. The enhancement was attributed, on one hand, to the use of binary hydrolysis that could have contributed to produce a higher proportion of monomers of easy degradation by bioH2-producing bacteria (HPB) and to avoid the formation/release of potential inhibitors; on the other hand, to the differences of substrate availability given by the mode of growth in each reactor.
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Concerning the use of TV for bioH2 production (Table 2), there are a few studies in the literature, with a particular focus on (i) optimizing pretreatments to further enhance bioH2 production [27]; (ii) testing the effect of different operational conditions such as pH [28, 29], temperature [28, 30], substrate concentration [28, 30, 31], solid content [22, 31], nutrient formulation [22, 31], inoculum addition [22, 31], HRT [22, 30, 32], and OLR [22, 32]; (iii) producing bioH2 in different systems, such as serum bottle [33], fixed bed reactor (FBR) [34], and CSTR [35]; (iv) evaluating the feasibility of co-fermentation [11, 36]; and (v) exploring the microbial ecology of the process [32, 36, 37].
More particularly, Espinoza-Escalante et al. [27] evaluated the effect of three pretreatments, that is, alkalinization, cavitation, and thermal pretreatment, on the metabolic profile and the increments of COD and total reducing sugars (TRS) of TV, as well as on its bioH2 production potential. From that study, it can be concluded that the application of such pretreatments to raw TV resulted in different degrees of solubilization of COD and TRS, depending on the applied pretreatment and combinations thereof. However, there was no apparent relation in the consumption of TRS and COD with bioH2 production. Indeed, the optimal conditions that led to the highest solubilization of both COD and TRS did not result in a significant improvement in the YH2, which was about 2.8 NL-H2/L of reactor, indicating that compounds other than TRS could be involved in the mechanism of bioH2 production.
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In another report, Espinoza-Escalante et al. [28] studied the effect of pH (4.5, 5.5, and 6.5), HRT (1, 3, and 5 d), and temperature (35 and 55°C) on the semi-continuous production of bioH2 from TV. The experiments were performed in 1-L glass vessels inoculated with 10% (v/v) of mesophilic anaerobic digester sludge. The results showed that all factors studied had an important effect on bioH2 production. The highest efficiency in terms of bioH2 production was achieved at a pH of 5.5, an HRT of 5 d and a temperature of 55°C. Based on constructed mathematical models, pH was the most influential parameter.
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In a similar study, Buitrón and Carvajal [30] investigated the effect of temperature (25 and 35°C), HRT (12 and 24 h), and substrate concentration on bioH2 production from TV using a 7-L AnSBR, with a working volume of 6 L. The exchange volume was 50% with a reaction time of 11.3 or 5.3 h depending on the applied HRT, while pH and mixing were controlled at 5.5 and 153 rpm, respectively, in all cases. It was evidenced that all parameters studied affected the efficiency of bioH2 production. The HRT had a major influence on bioH2 production. It was found that the shorter the HRT, the higher the bioH2 production. Overall, the maximum VHPR of 2.2 NL-H2/L-d and an average bioH2 content in the biogas of 29.2 ± 8.8% (v/v) were obtained at 35°C, 12 h HRT, and 3 g-COD/L OLR.
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Later, Buitrón et al. [34] evaluated the performance of an FBR to produce bioH2 in a continuous mode from TV. The reactor had a working volume of 1.7 L and was packed with polyurethane rings for biomass immobilization. The temperature, pH, HRT, and OLR were kept constant at 35°C, 4.7, 4 h, and 2.15 g-COD/L-d (influent concentration of 8 g-COD/L), respectively. After an initial acclimatization period of HPB to TV, the FBR exhibited a VHPR of 1.7 NL-H2/L-d and a YH2 of 1.36 NL-H2/L of TV. In a follow-up study conducted by the same research group, by using a 0.6-L AnSBR operated under mesophilic and acidophilic conditions at an HRT of 6 h, it was observed that increasing substrate concentration from 2 to 16 g-COD/L increased the VHPR up to 1.4 NL-H2/L-d. Hence, the use of TV for bioH2 production did not result in inhibition [35].
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Another interesting advance was made by García-Depraect et al. [11], who studied the technical feasibility of using a co-fermentation approach to produce bioH2 from TV in a well-mixed reactor operated under batch mode. Nixtamalization wastewater (NW) was chosen as the complementary substrate based on its wide availability in Mexico and high alkalinity. The TV:NW ratio of 80:20 (w/w) resulted in the highest VHPR of 2.6 NL-H2/L-d with a bioH2 content in the gas phase of 71% (v/v). Interestingly, the co-fermentation study allowed the identification of iron and nitrogen as essential nutrients which may be limiting in TV-fed DF reactors. This identification becomes significant to avoid nutrient-limited conditions and to prevent excessive nutrient supplementation that has been occurring in several studies at bench scale, but its practice may be prohibited on larger scales.
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In this field of progressive research, the effect of pH on the bioH2 production efficiency was subsequently studied by García-Depraect et al. [29] through macro- and micro-scale behavior analysis approaches. It was found that fixed pH of 5.8 showed a longer lag phase compared with fixed pH of 6.5, but the latter promoted bioH2 sink through propionogenesis. Based on the above observations, a two-stage pH-shift control strategy was devised to further increase bioH2 production. The strategy entailed the control of pH at 6.5 for first ∼29 h of culture to decrease the lag time, and then the pH was maintained at 5.8 to increase the bioH2 conversion efficiency by inhibiting the formation of propionic acid (HPr). The pH-shift strategy reduced running time and enhanced bioH2 production by 17%, obtaining 2.5 NL-H2/L of reactor. In a further study, the use of TV as the sole carbon source in the batch bioH2-yielding process was evaluated through a comprehensive approach entailing the operational performance, kinetic analysis, and microbial ecology [37]. A YH2 of 4.3 NL-H2/L of reactor and a peak VHPR of 3.8 NL-H2/L-d were obtained.
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The effects of total solids content, substrate concentration, nutrient formulation, and inoculum addition on bioH2 production performance from TV have been also investigated in batch experiments [31]. It was observed a consistent bioH2 production which was primarily influenced by inoculum addition followed by substrate concentration, nutrient formulation, and solids content. Maximum VHPR (5.4 NL-H2/L-d) and YH2 (4.3 NL-H2/L of reactor) were achieved by removing suspended solids and enhancing nutrient content, respectively [31]. Finally, the highest VHPR (12.3 NL-H2/L-d, corresponding to ∼3.4 NL-H2/L of TV) up to date has been achieved via a novel multi-stage process operated under continuous mode for 6 h HRT, which also resulted in high stability (VHPR fluctuations <10%) and a high bioH2 content in the gas phase of ∼90% (v/v) [38].
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3.2 Metabolic pathways
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Following the by-products formed during fermentation is of utmost importance to understand, predict, control, and optimize the behavior of DF processes. It is well known that the distribution of the fermentation by-products may change depending on culture conditions. Low bioH2 productions matched with the presence of undesired electron sinks, such as HLac, HPr, iso-butyrate, valerate, iso-valerate, and solvents (e.g. ethanol, acetone, and butanol). For instance, the production of HPr reduces the amount of bioH2 that may be produced, as shown in reactions 1–3 (Table 3). Biomass growth also represents an electron sink. Commonly bioH2 production is growth-associated. However, higher biomass growth does not necessarily imply the achievement of the best bioH2 production [29]. Thus, a proper balance between biomass growth and bioH2 production is desirable. On the other hand, bioH2 sink through the formation of bioCH4 via the hydrogenotrophic pathway (reaction 4) seems to be less problematic in DF processes due to the application of inoculum pretreatments together with biokinetic control such as acidic pH and low HRT, even using attached-growth reactors [34]. The formation of HLac can also lead to stuck DF fermentations, as shown in reactions 5–7. Acetogenesis (reaction 8) and homoacetogenesis (reaction 9) may also occur during the process, decreasing the bioH2 production efficiency. It has been reported that the consumption of bioH2 and carbon dioxide due to homoacetogenesis depends on the type of reactor and OLR, being its occurrence accentuated in suspended growth systems and high OLR [20, 23].
Metabolic reactions occurring in dark fermentation systems treating tequila processing by-products.
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Contrarily, bioH2 production via DF is typically related to HBu and HAc production from carbohydrates degradation, as shown in reactions 10 and 11, respectively. Theoretically, 4 and 2 mol of H2 derive from 1 mol of glucose when HAc and HBu are the end-products, respectively. However, from published studies in the field of DF, it seems reasonable to conclude that, in mixed cultures, a high bioH2 production efficiency is rather related with the formation of HBu than HAc because the latter may come from acetogenesis/homoacetogenesis.
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At this point, it must be noted that bioH2 can also come from the degradation of HLac, as shown in reactions 12–14 [37]. The HLac-type fermentation could provide the basis for the design of stable bioH2-producing reactors whose feedstocks are rich in HLac and HAc such as distillery wastewater (including TV), food waste, dairy wastewater, ensiled crops, lignocellulosic residues, and their hydrolysates (including AB), among others [36]. The amount of bioH2 obtained from the HLac-type fermentation may vary significantly depending on several factors such as pH, temperature, HRT, OLR, operation mode, substrate type, mixing, and prevailing microorganisms [31]. Also, it has been observed that the HLac-type fermentation in vinasse-fed DF reactors could be induced by low carbohydrate-available conditions [31, 36, 37]. On the other hand, the formation of HFor also can yield bioH2 (reaction 15) via the action of HFor hydrogenase complexes [37]. In addition, ethanol-type fermentation (reaction 16) generates ethanol, HAc, bioH2, and carbon dioxide. According to Ren et al. [39], the ethanol-type fermentation is favored by a pH of 4.0–5.0 and oxidation-reduction potential (ORP) of < −200 mV. In comparison to the HAc-HBu-mixed type fermentation, which has been ascertained as the most common bioH2-producing pathway, the latter two reactions have been less frequently found in DF reactors fed with AB/TV.
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3.3 Microbial communities
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Another pertinent point is that the performance of bioH2-producing reactors strongly depends on the selection and maintenance of HPB. However, this is a difficult task because DF processes treating unsterilized feedstocks under continuous conditions are open systems, meaning that several microbial interactions may take place. In the literature, it has been used defined mixed cultures to inoculate DF reactors treating complex feedstocks such as AB and TV. In most cases, heat-shock pretreatment has been used as the selective method for the enrichment of HPB (based on their ability in forming spores), while killing bioH2 consumers. However, other aspects such as biological/physiological (e.g. growth rate, microbial interactions, auto/allochthonous bacteria, adaptation to environmental stress conditions, and nutrients requirements), the composition of broth culture (e.g. availability of substrate/nutrients, organic acids, and toxicants), process parameters (e.g. pH, temperature, HRT, OLR, and ORP) and reactor configurations (e.g. suspended and attached biomass, mixing, and liquid-gas interface mass transfer capacity) are also selective pressure factors to determine prevailing microbial community structure during operation. At this point, it must be noted that the application of the heat-shock pretreatment decreases the diversity eliminating not only microorganisms with a negative effect on the overall bioH2 production, but also with a potentially positive role. Besides having a high capacity to produce bioH2, the biocatalyst must be able to thrive on the presence of putative toxic by-products such as HFor, HAc, phenols, and furans which are commonly detected in pretreated AB and raw TV.
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Interestingly, molecular biology tools reveal that HPB (e.g. Clostridium, Klebsiella, and Enterobacter) are, in almost all DF systems, accompanied by lactic acid bacteria (LAB) (e.g. Lactobacillus and Sporolactobacillus) [40]. This co-occurrence could be attributed to the fact that LAB are ubiquitous in the environment, the physicochemical characteristics of feedstocks could sustain the proliferation of LAB, and LAB possess complex adaptation mechanisms that confer their ecological advantages over other bacteria [31]. Streptococcus and Lactobacillus have actually been detected in TV [31]. Bearing in mind such explanations, it is reasonable to assume that DF reactors fed with TV will naturally undergo the proliferation of LAB. Indeed, this assumption was verified by [11, 29, 31, 36, 37].
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Except for capnophilic HLac pathway, it is well known that HLac is produced through zero-bioH2-producing pathways. Moreover, the proliferation of LAB is commonly associated with the deterioration of bioH2 production, mainly due to substrate competition, acidification of cultivation broth, and excretion of antimicrobial peptides known as bacteriocins [41]. At this point, another important constraint to be mentioned is that methods devoted to preventing the growth of LAB such as pretreatment of inoculum and sterilization of feedstock may be expensive, thus imposing a high economic burden on the process. Besides, the application of pretreatments does not always hinder the proliferation of LAB [42]. Therefore, there is an urgent need for novel technical solutions to ensure a maximum VHPR and YH2.
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Fortunately, the activity of LAB may also have positive effects on the overall DF process, mainly through the aforementioned HLac-type fermentation (HLac-driven bioH2 production). Indeed, it is noteworthy mentioning that, under certain conditions, a DF process mediated by beneficial trophic links between HPB and LAB may be highly stable and consequently of high relevance for practical applications. In this case, LAB may help in the production of bioH2 by pH regulation, substrate hydrolysis, biomass retention, oxygen depletion, and substrate detoxification [36]. Nevertheless, to exploit these advantages, a thorough understanding of the mechanisms underlying the HLac-type fermentation is essential. In this context, molecular analyses have depicted a possible syntrophy between LAB, acetic acid bacteria (AAB) and HPB [11, 29, 31, 36, 37]. For instance, Illumina MiSeq sequencing has revealed that Clostridium beijerinckii, Streptococcus sp., and Acetobacter lovaniensis were the most abundant species at the highest bioH2 production activity [37]. The possible changes of metabolites and microbial communities through time have also been investigated to understand the potential mechanism of bioH2 production from HLac and HAc [36]. In this regard, the microbial structure showed coordinated dynamic behavior over time, identifying three stages throughout the process: (i) a first stage (corresponding to the lag phase in relation to bioH2 production) in which the major part of TRS were consumed by dominant LAB and AAB, (ii) a second stage (corresponding to the exponential bioH2 production phase) during which the HLac-type fermentation was catalyzed by emerging HPB, and (iii) a third stage (corresponding to the stationary bioH2 production phase) in which non-HPB regrown while HPB became subdominant [36]. Interestingly, it has been also shown that an operating strategy based on pH-control may stimulate the syntrophy between Clostridium and Lactobacillus, and reduced the proliferation of Blautia and Propionibacterium (which are undesirable microorganisms due to their homoacetogenic and propionogenic activity, respectively), trending bioH2 production to enhanced efficiency [29].
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4. Biomethane production from agave bagasse and tequila vinasse
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The operational performance, metabolic pathways, and microbial communities of the AD of AB and TV are extensively reviewed in the following sections.
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4.1 Operational performance
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In recent years, there have been several efforts to improve the AD performance of AB and TV (Table 4). Regarding the use of AB, the first study reported in this field was conducted by Arreola-Vargas et al. [8], who evaluated the feasibility of producing bioCH4 from acid uncooked AB hydrolysates under two conditions, that is, with and without nutrient addition. The experiments were conducted in a mesophilic (32°C) AnSBR (with recirculation) at an OLR of 1.3 g-COD/L-d (influent concentration of 5 g-COD/L). The reactor had a working volume of 3.6 L and was inoculated with 5.8 g-VSS/L of anaerobic granular sludge collected from a full-scale UASB reactor treating brewery wastewater. The total cycle time was 72 h with a reaction time of 71 h and an exchange ratio of 80% (v/v). Unexpectedly, the best performance was obtained without additional supplementation of nutrients, achieving a volumetric bioCH4 production rate (VMPR) of 0.3 NL-CH4/L-d and a bioCH4 yield (YCH4) of 0.26 NL-CH4/g-CODremoved with a CH4 content in the biogas of 70–74% (v/v).
Comparison of the literature data on biomethane production efficiency using pretreated agave bagasse as feedstock.
Notes: All studies were conducted using anaerobic granular sludge; aInitial pH value; *Units: bNL-CH4/g-CODremoved, cNL-CH4/kg of AB; dCalculated from provided information; NR: not reported.
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In a later study, Arreola-Vargas et al. [17], assessed the use of AB hydrolysates (20, 40, 60, 80, and 100% v/v) obtained either from acid or enzymatic pretreatment for bioCH4 production in single- and two-stage AD processes. The experiments were conducted in the AMPTS II system at 37°C, 120 rpm, initial pH of 8, and using 10 g-VSS/L of anaerobic granular sludge collected from a full-scale UASB reactor treating TV as inoculum. The highest VMPR for single- (0.84 NL-CH4/L-d) and two-stage (0.96 NL-CH4/L-d) processes were achieved in the assays with enzymatic hydrolysates at 100% and 20%, respectively. Regarding YCH4 results, the highest value with the single-stage process of 0.16 NL-CH4/g-CODremoved was obtained in the assays with 20% hydrolysate from enzymatic pretreatment, while the two-stage process attained up to 0.24 NL-CH4/g-CODremoved, also at 20% hydrolysate regardless of the type of pretreatment used. Although both hydrolysates harbor potential fermentation inhibitors (i.e. organic acids, furan derivatives, and polyphenols) in different concentrations, results showed no negative effects in the AD performance. Toledo-Cervantes et al. [7] also evaluated the bioCH4 production from the spent medium of DF of enzymatic hydrolysate of AB. The authors found that bioCH4 production in an AnSBR was severely inhibited likely because the remaining catalytic activity of the enzyme used may have contributed to the degradation of CH4 biocatalyst. In the same year, Breton-Deval et al. [18] contrasted the bioCH4 production from acid AB hydrolysates previously obtained using two different acid catalysts, that is, HCl and H2SO4. The experiments were carried out in the AMPTS II at 35°C, 120 rpm, initial pH of 7.5, an organic load of 8 g-COD/L, and using 10 g-VSS/L of anaerobic granular sludge collected from a full-scale UASB reactor treating TV as inoculum. The results showed that HCl hydrolysate outperformed the H2SO4 one by obtaining a four-fold increase on YCH4, that is, 0.17 versus 0.04 NL-CH4/g-CODremoved, respectively. The impairment of the methanogenic activity was attributed to the fact that the addition of sulfate ions favored the activity of sulfate-reducing bacteria (SRB). However, when using optimized HCl hydrolysates based on bioCH4 production (1.8% HCl, 119°C, and 103 min) rather than sugar recovery (1.9% HCl, 130°C, and 133 min), the highest YCH4 of 0.19 NL-CH4/g-CODremoved (0.09 NL-CH4/g-VS of AB) was obtained indicating that other components of the hydrolysates besides sugars may influence bioCH4 production, for example, extractives, potential microbial inhibitors.
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In another study, Galindo-Hernández et al. [22] evaluated the bioCH4 production potential from AB previously pretreated with AHP followed by enzymatic saccharification with hemicellulases and cellulases. The experiments were performed in the AMPTS II system at 37°C, 150 rpm, initial pH of 7.0, and using an organic load of 5 g-COD/L, 10 g-VS/L of inoculum (anaerobic granular sludge from a mesophilic full-scale TV treatment plant) and a defined mineral solution. Under such conditions, the YCH4 and VMPR were found as 0.2 NL-CH4/g-CODremoved (0.39 NL-CH4/g of AB) and 0.67 NL-CH4/L-d, respectively, indicating the potential advantage of integrating a delignification pretreatment and the use of synergistic enzymatic mixtures before the AD process.
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Regarding continuous processes, Montiel and Razo-Flores [21] studied the effect of OLR on the VMPR using a mesophilic (23–25°C) 1.5-L UASB reactor (with a working volume of 1.25 L) feeding with diluted (and supplemented with nutrients) acidogenic effluent generated during the DF of enzymatic hydrolysates of AB. The reactor was inoculated with 20 g-VS/L of anaerobic granular sludge from a full-scale UASB reactor treating TV and operated for 80 d to achieve OLRs between 1.35 and 24 g-COD/L-d by increasing the COD concentration of the influent and then by decreasing the HRT from 21 to 10 h. The highest VMPR and YCH4 of 6.4 NL-CH4/L-d and 0.32 NL-CH4/g-CODfed (225 NL-CH4/kg of AB) were achieved at an OLR of 20 g-COD/L-d (14 h HRT). Under such conditions, the COD removal efficiency was above 90% and the CH4 content in the gas phase was of 73% (v/v).
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Regarding the use of TV for bioCH4 production (Table 5), Méndez-Acosta et al. [43] assessed the mesophilic AD of TV in a lab-scale CSTR reactor for 250 d at HRTs of 14–5 d corresponding to increments in the OLR from 0.7 to 6 g-COD/L-d (influent COD concentrations of 10–33 g/L). The highest YCH4 of 0.32 L-CH4/g-CODremoved and VMPR of 2.8 L-CH4/L-d with bioCH4 concentrations in the biogas greater than 65% (v/v) and COD removal efficiencies over 90% were obtained, even with an unbalanced COD/N/P ratio, at 6 g-COD/L-d OLR. However, a relatively long start-up of 50 d and continuous supplementation of external alkalinity were needed in order to provide stability to the process.
Comparison of the literature data on biomethane production efficiency using tequila vinasse as feedstock.
Notes: All studies were conducted using anaerobic granular sludge; aCalculated from provided information; NR: not reported;
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With the aim of enhancing the stability of the AD of TV, López-López et al. [44] investigated the influence of alkalinity and volatile fatty acids (VFAs) on the performance of a 2-L UASB reactor. The UASB reactor was inoculated with anaerobic granular sludge and operated under mesophilic conditions during 235 d at OLRs from 2.5 to 20 g-COD/L-d with recirculation of the treated effluent at recycling flow rate to influent flow rate ratios of 1:1 to 10:1 in one-unit increments. In that study, it was found that, by maintaining a VFAs to alkalinity ratio ≤ 0.5 with recirculation 1:10, the recirculation of the effluent could induce stable performances by reducing the impact of VFAs and organic matter concentration present in the effluent, attaining a COD removal efficiency higher than 75% with a YCH4 of 0.33 NL-CH4/g-CODremoved. However, even though the high recirculation ratio led to the recovery of alkalinity without any addition of external alkalinity, the granular sludge tended to become flocculent with a reduction in the average size from 2.5 to 1.5 mm.
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In another study conducted by Jáuregui-Jáuregui et al. [45], after a start-up period of 28 d, a mesophilic up-flow FBR inoculated with anaerobic granular sludge withdrawn from a full-scale UASB reactor treating brewery wastewater exhibited a YCH4 of 0.27 NL-CH4/g-CODremoved with a CH4 content of 75% (v/v) and COD removal efficiencies of up to 90% under an OLR of 8 g-COD/L-d and an HRT of 4 d. However, the authors also reported the inhibition of biogas production due to digester clogging, which led to an excessive VFAs accumulation. In the same year, Buitrón et al. [35] reported the performance of a UASB reactor treating the resulting effluent of a DF stage at three different COD concentrations, that is, 0.4, 1.08, and 1.6 g/L, and two HRTs, that is, 24 and 18 h. The maximal content of CH4 in the gas phase (68% v/v) and COD removal (67%) were achieved at the concentration of 1.6 g-COD/L with an HRT of 24 h. A further decrease in HRT resulted in lower efficiencies, that is, 40% CH4 content and 52% removal efficiency.
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In a further study, Arreola-Vargas et al. [46] achieved YCH4 ranging from 0.25 to 0.29 NL-CH4/g-CODremoved with 75–90% (v/v) CH4 content and 85% COD removal using a bench scale AnSBR inoculated with anaerobic granular sludge and fed with diluted TV (8 g-COD/L), the reaction time varied within 3–9 d. Interestingly, later, the same research group performed a pilot scale study for the mesophilic AD treatment of TV using a 445-L packed bed reactor (PBR) which was operated for 231 d under increasing OLRs, from 4 to 12.5 g-COD/L-d [47]. The PBR showed a stable performance exhibiting COD removals and YCH4 in the range of 86–89% and 0.24–0.28 NL-CH4/g-CODremoved, respectively. Meanwhile, the highest VMPR of 3.03 NL-CH4/L-d was reached at the highest OLR of 12.5 g- COD/L-d [47].
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More recently, in two-stage PBRs operated over 335 d, Toledo-Cervantes et al. [7] achieved the highest YCH4 of 0.29 NL-CH4/g-CODremoved at OLRs in the range of 2.7–6.8 g-COD/L-d (6–2.4 d HRT) with COD removal efficiencies between 81 and 95%, and with average CH4 contents around 80% (v/v). However, further increasing the OLR to 12 g-COD/L-d (2.2-d HRT) decreased the removal efficiency of COD (from 81 to 74%) accompanied with HAc and HPr accumulation.
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4.2 Metabolic pathways
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As shown in Table 6, the majority of bioCH4 produced in AD systems occurs from the use of HAc and bioH2 via acetoclastic (reaction 17) and hydrogenotrophic (reaction 4) pathways, respectively. However, bioCH4 can also be evolved from HFor (reaction 18), compounds with the methyl group like methanol (reaction 19), and from the syntrophic degradation of HBu (reaction 20) and HPr (reaction 21) [48]. Thus, an even production and consumption rate of organic acids is a sign of healthy single-stage AD processes. Contrarily, excessive accumulation of organic acids in the effluent has been related to reactor upset and failure, causing a drop in biogas production and COD removal efficiency. For instance, the presence of HPr in a HPr/HAc ratio ≥ 1 is usually matched with operational instability [43]. The alkalinity ratio, α = intermediate alkalinity (pH = 5.75)/partial alkalinity (pH = 4.3), roughly relates the amounts of VFAs and bicarbonate alkalinity in anaerobic reactors, measuring the buffer potential of the systems [49]. Values ≤0.3 are reported as adequate for achieving stable operation; however, in the case of TV-fed anaerobic reactors, stable processes have been achieved at slightly higher range of α between 0.2 and 0.5 [44, 47]. Moreover, bioCH4 production can be disrupted by the formation of certain by-products such as long chain fatty acids or solvents, which may jeopardize the suitable availability of bioCH4 precursors. In this regard, in the case of integrated DF-AD schemes, special attention must be also paid to the concentration and composition of organic acids coming from the DF stage. At this point, it should be mentioned that the redirection of carbon through HLac has been reported as a strategy to enhanced AD processes due to its thermodynamic advantages [50, 51, 52].
AD reactors contain mixed microbial populations [15]. BioCH4 formation from AB and TV has been related with the coexistence of syntrophic bacteria (Anaerolineaceae, Candidatus, Cloacamonas, Syntrophobacter, Syntrophomonas, and Syntrophus), hydrogenotrophic (Methanobacterium and Methanocorpusculum) and acetoclastic (Methanosaeta and Methanosarcina) methanogens [7, 18, 47]. It has been previously observed that the two-stage AD of TV at low concentrations of VFAs (low OLRs) favored the acetoclastic pathway, in contrast, hydrogenotrophic methanogens enriched at high concentrations (high OLRs) [7]. This change in diversity has been also observed in an AnSBR digester fed with acid AB hydrolysates [53]. However, the opposite trend was observed during the single stage AD of TV using a pilot-scale PBR [47]. Regardless of the tequila by-product used, loss of syntrophic relationships for interspecies H2/HFor transfer and interspecies HAc transfer has been associated with microbial imbalance, which subsequently affects negatively bioCH4 production [8, 53]. However, in the case of multi-stage AD processes, unsuitable concentrations of hydrolytic/acidogenic bacteria in DF effluent may be quite detrimental for the granular methanogenic sludge [15]. In addition, other bacteria which can compete with the methanogens for bioCH4 precursors may also be present in AD reactors, for example, SRB [15, 18].
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5. Multi-stage anaerobic digestion
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Since TV has negligible levels of alkalinity and high concentrations of components with a tendency to suffer very rapid acidification [43, 44], two-stage AD processes have emerged as important operational strategies to provide enhanced stability of the CH4-producing stage [7, 24]. However, the multi-stage AD approach seems to be also applicable for pretreated AB [17, 21]. In fact, a two-stage AD process fed with AB hydrolysates showed up to 3.3-fold higher energy recovery than a single-stage process [17]. Indeed, according to Lindner et al. [16], two-stage systems seem to be only recommendable for digesting sugar-rich feed stocks, which undergo a quick hydrolysis/acidogenesis. This approach allows to provide optimal environmental conditions for the different groups of microorganisms which have differences in terms of physiology, nutrient intake, nutritional requirements, growth rate, optimum growth conditions such as pH, and adaptation to environmental stress conditions [16]. The acidogenesis and methanogenesis separated in space may also produce bioH2 via DF process [17, 24, 35]. However, it is not necessarily desirable to produce bioH2 in all cases [7]. In the latter case, a stream rich in HLac can be obtained through the HLac-type fermentation which can be further fed to the methanogenic stage [36, 37], where hydrogenotrophic may be benefited for the conversion of HLac to HAc by consuming the intermediate bioH2 gas immediately [52]. The possibility of operating at higher organic loading capacity (in the methanogenic stage), reducing alkali addition, and increasing COD removal efficiency are additional advantages of the two-stage AD as compared to single-stage AD [7, 21, 24]. A small number of reactor configurations devoted to bioH2/bioCH4 production from AB/TV can be found in the literature (Figure 3). Among them, for both AB and TV, the CSTR and UASB configurations have shown the highest performance to date for producing bioH2 and bioCH4, respectively, that is, 13 NL-H2/L-d from AB [23] and 12.3 NL-H2/L-d from TV [38] and 6.4 NL-CH4/L-d from AB [21] and 3.5 NL-CH4/L-d from TV [54].
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Figure 3.
Types of reactor configurations used for biohydrogen and biomethane production from tequila processing by-products. (a) Batch reactor, (b) continuously stirred tank reactor (CSTR) with recirculation, (c) CSTR, (d) anaerobic sequencing batch reactor (AnSBR), (e) trickling bed reactor with recirculation, (f) packed bed reactor, (g) up-flow anaerobic sludge blanket (UASB) reactor. AnSBR can integrate mechanical or hydraulic mixing. UASB can operate with effluent recycle.
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6. Current limitations and potential improvements
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Notwithstanding the enormous efforts made to achieve a better understanding of the DF/AD process of AB/TV, it is still necessary to improve not only bioH2 or bioCH4 productivities and yields but also the (long-term) stability of processes for commercialization purposes. TV is a highly complex wastewater that besides high COD and negligible alkalinity, harbors recalcitrant compounds such as phenols, which may act as inhibitors in DF/AD. While the main limitation to use AB as the feedstock is its recalcitrant structure. As mentioned earlier, some of the pretreatment/conditioning steps used in AB have been optimized not only in terms of hydrolysis yield, reaction time, the generation/release and effect of putative fermentation inhibitory compounds, cost-effectiveness but also in terms of bioH2/bioCH4 production efficiency. However, there is still a need to explore other pretreatments that have not been yet embraced in the field of DF/AD of AB but they have been ascertained as potentially useful in releasing sugars for other applications like the production of bioethanol, such as ammonia fiber explosion (AFEX), autohydrolysis, organosolv, high-energy radiation, ozonolysis, alkaline, ionic liquids, or any combination of those pretreatments. It could be also interesting to explore consolidated processes (direct fermentation) which combine into a single operation the enzymatic hydrolysis of (pretreated) biomass and biological conversion to the desired by-product (in this case bioH2/bioCH4) by mixed consortia.
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Besides the features described before, from practical purposes, the highly variable composition of AB/TV constitutes another constraint to produce bioH2 since DF systems are commonly unable to overcome perturbations in feedstock composition. One of the most significant challenges is to assure consistency in the prevailing metabolic pathways during the DF process and favor bioH2-producing pathways over other unwanted routes, for example, homoacetogenesis and methanogenesis. Very little is known about the microbial community structure of DF/AD processes treating AB/TV. In this regard, it is not clear the role of microorganisms and their association with operational parameters (e.g. pH, HRT, and OLR) and process indicators (e.g. VHPR, VMPR, and metabolic composition). Also, much less is known about how microbial assemblage may change through time, and what factors (operating parameters) govern its dynamics. It is worth noticing that HLac monitoring has been disregarded limiting the understanding of integrated DF-AD processes since it, as an intermediate, has a vital role in the carbon flux.
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Another concern worth to mention is that most of the previous studies were carried out in batch or semi-continuous reactors. Thus, it is vital to transfer the kinetic knowledge gained from such studies to the expansion of continuous systems. In this context, the development of integrated DF-AD schemes for the continuous production of bioH2 and bioCH4 using AB/TV as feed stocks requires intensive research on interlinking side streams for producing high added-value bioproducts in a biorefinery framework (e.g. HLac-bioH2-bioCH4) for better sustainability of the existing tequila industries.
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7. Conclusions
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Tequila industry generates huge amounts of AB and TV, which could be subjected to integrated DF-AD processes to produce bioH2 and bioCH4 while reducing their pollution potential. This chapter focused on the state-of-the-art of configurations and process parameters, metabolic pathways, and microbial ecology of bioH2- and bioCH4-producing reactors. The pretreatment/conditioning steps applied to enhance the valorization of AB/TV were also reviewed. It has been suggested that the HLac-type fermentation coupled to DF and AD can boost the development of cascading design in multi-stage AD processes. This multiproduct approach using AB/TV as resources in the biorefinery scheme may facilitate sustainability to the tequila industry.
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Acknowledgments
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This work was financially supported by Consejo Nacional de Ciencia y Tecnología (CONACYT) through the Project-PN-2015-2101-1024. Osuna-Laveaga D.R. acknowledges CONACYT for the Ph.D. scholarship: 267499.
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Conflict of interest
The authors declare no conflict of interest.
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Acronyms and abbreviations
\n\n\nHAc\n\n
acetic acid
\n\n\n\nAAB\n\n
acetic acid bacteria
\n\n\n\nAB\n\n
agave bagasse
\n\n\n\nAHP\n\n
alkaline hydrogen peroxide
\n\n\n\nAD\n\n
anaerobic digestion
\n\n\n\nAnSBR\n\n
anaerobic sequencing batch reactor
\n\n\n\nAMPTS II\n\n
automatic methane potential test system
\n\n\n\nbioH2\n\n
biohydrogen
\n\n\n\nYH2\n\n
biohydrogen yield
\n\n\n\nHPB\n\n
biohydrogen-producing bacteria
\n\n\n\nbioCH4\n\n
biomethane
\n\n\n\nYCH4\n\n
biomethane yield
\n\n\n\nHBu\n\n
butyric acid
\n\n\n\nCOD\n\n
chemical oxygen demand
\n\n\n\nCSTR\n\n
continuously stirred tank reactor
\n\n\n\nDF\n\n
dark fermentation
\n\n\n\nFPU\n\n
filter paper units
\n\n\n\nFBR\n\n
fixed bed reactor
\n\n\n\nHFor\n\n
formic acid
\n\n\n\nHRT\n\n
hydraulic retention time
\n\n\n\nHPB\n\n
hydrogen-producing bacteria
\n\n\n\nHMF\n\n
hydroxymethylfurfural
\n\n\n\nHLac\n\n
lactic acid
\n\n\n\nLAB\n\n
lactic acid bacteria
\n\n\n\nNW\n\n
nixtamalization wastewater
\n\n\n\nORP\n\n
oxidation-reduction potential
\n\n\n\nOLR\n\n
organic loading rate
\n\n\n\nPBR\n\n
packed bed reactor
\n\n\n\nHPr\n\n
propionic acid
\n\n\n\nSRB\n\n
sulfate-reducing bacteria
\n\n\n\nVFAs\n\n
volatile fatty acids
\n\n\n\nVS\n\n
volatile solid
\n\n\n\nVSS\n\n
volatile suspended solids
\n\n\n\nVHPR\n\n
volumetric biohydrogen production rate
\n\n\n\nVMPR\n\n
volumetric biomethane production rate
\n\n\n\nTV\n\n
tequila vinasse
\n\n\n\nTRS\n\n
total-reducing solids
\n\n\n\nTBR\n\n
trickling bed reactor
\n\n\n\nUASB\n\n
up-flow anaerobic sludge blanket reactor
\n\n\n\n
\n',keywords:"agave bagasse, tequila vinasse, dark fermentation, anaerobic digestion, biofuels",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/68154.pdf",chapterXML:"https://mts.intechopen.com/source/xml/68154.xml",downloadPdfUrl:"/chapter/pdf-download/68154",previewPdfUrl:"/chapter/pdf-preview/68154",totalDownloads:336,totalViews:0,totalCrossrefCites:1,dateSubmitted:"March 13th 2019",dateReviewed:"June 17th 2019",datePrePublished:"July 17th 2019",datePublished:"February 5th 2020",dateFinished:null,readingETA:"0",abstract:"Nowadays, the use of agro-industrial by-products as alternative sustainable resources to generate bioenergy and high-value bioproducts is one of the most important research topics to tackle environmental concerns related to the excessive consumption of fossil-based fuels and rapid urbanization and industrialization. This chapter provides a broad overview of the potential of the main tequila industry by-products, agave bagasse and tequila vinasse, for biohydrogen (bioH2) and biomethane (bioCH4) production via dark fermentation and anaerobic digestion, respectively. First, pretreatment or conditioning steps commonly applied to tequila by-product streams before downstream biological processes are highlighted. The operational performance of bioH2- and bioCH4-producing reactors is subsequently reviewed, with a focus on reactor configuration and performance, microbial metabolic pathways, and the characterization of microbial communities. Additionally, the development of multi-stage anaerobic digestion processes is comprehensively discussed from a practical point of view. Finally, limitations and potential improvements in the field of bioH2 and bioCH4 production are presented.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/68154",risUrl:"/chapter/ris/68154",signatures:"Octavio García-Depraect, Daryl Rafael Osuna-Laveaga and Elizabeth León-Becerril",book:{id:"8244",title:"New Advances on Fermentation Processes",subtitle:null,fullTitle:"New Advances on Fermentation Processes",slug:"new-advances-on-fermentation-processes",publishedDate:"February 5th 2020",bookSignature:"Rosa María Martínez-Espinosa",coverURL:"https://cdn.intechopen.com/books/images_new/8244.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",editors:[{id:"165627",title:"Dr.",name:"Rosa María",middleName:null,surname:"Martínez-Espinosa",slug:"rosa-maria-martinez-espinosa",fullName:"Rosa María Martínez-Espinosa"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"273360",title:"Dr.",name:"Elizabeth",middleName:null,surname:"León-Becerril",fullName:"Elizabeth León-Becerril",slug:"elizabeth-leon-becerril",email:"eleon@ciatej.mx",position:null,institution:null},{id:"299053",title:"MSc.",name:"Octavio",middleName:null,surname:"García-Depraect",fullName:"Octavio García-Depraect",slug:"octavio-garcia-depraect",email:"ogarcia_es@ciatej.mx",position:null,institution:null},{id:"306990",title:"MSc.",name:"Daryl Rafael",middleName:null,surname:"Osuna-Laveaga",fullName:"Daryl Rafael Osuna-Laveaga",slug:"daryl-rafael-osuna-laveaga",email:"ibt.drol@gmail.com",position:null,institution:null}],sections:[{id:"sec_1",title:"1. Tequila production process and its main by-products: agave bagasse and tequila vinasse",level:"1"},{id:"sec_2",title:"2. Pretreatment/conditioning of agave bagasse and tequila vinasse",level:"1"},{id:"sec_3",title:"3. Biohydrogen production from agave bagasse and tequila vinasse",level:"1"},{id:"sec_3_2",title:"3.1 Operational performance",level:"2"},{id:"sec_4_2",title:"3.2 Metabolic pathways",level:"2"},{id:"sec_5_2",title:"3.3 Microbial communities",level:"2"},{id:"sec_7",title:"4. Biomethane production from agave bagasse and tequila vinasse",level:"1"},{id:"sec_7_2",title:"4.1 Operational performance",level:"2"},{id:"sec_8_2",title:"4.2 Metabolic pathways",level:"2"},{id:"sec_9_2",title:"4.3 Microbial communities",level:"2"},{id:"sec_11",title:"5. Multi-stage anaerobic digestion",level:"1"},{id:"sec_12",title:"6. Current limitations and potential improvements",level:"1"},{id:"sec_13",title:"7. Conclusions",level:"1"},{id:"sec_14",title:"Acknowledgments",level:"1"},{id:"sec_17",title:"Conflict of interest",level:"1"},{id:"sec_14",title:"Acronyms and abbreviations",level:"1"}],chapterReferences:[{id:"B1",body:'CRT. Producción total Tequila y Tequila 100% [Internet]. 2019. Available from: https://www.crt.org.mx/EstadisticasCRTweb [Accessed: 14-05-2019]\n'},{id:"B2",body:'Villanueva-Rodríguez SJ, Rodríguez-Garay B, Prado-Ramírez R, Gschaedler A. Tequila: Raw material, classification, process, and quality parameters. Encyclopedia of Food and Health. Academic Press; 2016:283-289. DOI: 10.1016/B978-0-12-384947-2.00688-7\n'},{id:"B3",body:'Rodríguez-Félix E, Contreras-Ramos SM, Davila-Vazquez G, Rodríguez-Campos J, Marino-Marmolejo EN. Identification and quantification of volatile compounds found in vinasses from two different processes of tequila production. Energies. 2018;11:1-18. DOI: 10.3390/en11030490\n'},{id:"B4",body:'Cedeño-Cruz M. Tequila production from agave: Historical influences and contemporary processes. In: Jacques KA, Lyons TP, Kelsall DR, editors. The Alcohol Textbook. 4th ed. Oxford UK: Nottingham University Press; 2003. pp. 223-245\n'},{id:"B5",body:'López-López A, Davila-Vazquez G, León-Becerril E, Villegas-García E, Gallardo-Valdez J. Tequila vinasses: Generation and full scale treatment processes. Reviews in Environmental Science and Biotechnology. 2010;9:109-116. DOI: 10.1007/s11157-010-9204-9\n'},{id:"B6",body:'del Real-Olvera J, López-López A. Biogas production from anaerobic treatment of agro-industrial wastewater. In: Kumar S, editor. Biogas. Rijeka: InTech; 2012. pp. 91-112\n'},{id:"B7",body:'Toledo-Cervantes A, Guevara-Santos N, Arreola-Vargas J, Snell-Castro R, Méndez-Acosta HO. Performance and microbial dynamics in packed-bed reactors during the long-term two-stage anaerobic treatment of tequila vinasses. Biochemical Engineering Journal. 2018;138:12-20. 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Single and two-stage anaerobic digestion for hydrogen and methane production from acid and enzymatic hydrolysates of Agave tequilana bagasse. International Journal of Hydrogen Energy. 2016;41:897-904. DOI: 10.1016/j.ijhydene.2015.11.016\n'},{id:"B18",body:'Breton-Deval L, Méndez-Acosta HO, González-Álvarez V, Snell-Castro R, Gutiérrez-Sánchez D, Arreola-Vargas J. Agave tequilana bagasse for methane production in batch and sequencing batch reactors: Acid catalyst effect, batch optimization and stability of the semi-continuous process. Journal of Environmental Management. 2018;224:156-163. DOI: 10.1016/j.jenvman.2018.07.053\n'},{id:"B19",body:'Valdez-Guzmán BE, Rios-Del Toro EE, Cardenas-López RL, Méndez-Acosta HO, González-Álvarez V, Arreola-Vargas J. Enhancing biohydrogen production from Agave tequilana bagasse: Detoxified vs. Undetoxified acid hydrolysates. Bioresource Technology. 2019;276:74-80. DOI: 10.1016/j.biortech.2018.12.101\n'},{id:"B20",body:'Contreras-Dávila CA, Méndez-Acosta HO, Arellano-García LA, Alatriste-Mondragón F, Razo-Flores E. Continuous hydrogen production from enzymatic hydrolysate of Agave tequilana bagasse: Effect of the organic loading rate and reactor configuration. Chemical Engineering Journal. 2017;313:671-679. DOI: 10.1016/j.cej.2016.12.084\n'},{id:"B21",body:'Montiel CV, Razo-Flores E. Continuous hydrogen and methane production from Agave tequilana bagasse hydrolysate by sequential process to maximize energy recovery efficiency. Bioresource Technology. 2018;249:334-341. DOI: 10.1016/j.biortech.2017.10.032\n'},{id:"B22",body:'Galindo-Hernández KL, Tapia-Rodríguez A, Alatriste-Mondragón F, Celis LB, Arreola-Vargas J, Razo-Flores E. Enhancing saccharification of Agave tequilana bagasse by oxidative delignification and enzymatic synergism for the production of hydrogen and methane. International Journal of Hydrogen Energy. 2018;43:22116-22125. DOI: 10.1016/j.ijhydene.2018.10.071\n'},{id:"B23",body:'Montoya-Rosales JJ, Olmos-Hernández DK, Palomo-Briones R, Montiel-Corona V, Mari AG, Razo-Flores E. Improvement of continuous hydrogen production using individual and binary enzymatic hydrolysates of agave bagasse in suspended-culture and biofilm reactors. Bioresource Technology. 2019;283:251-260. DOI: 10.1016/j.biortech.2019.03.072\n'},{id:"B24",body:'Ruggeri B, Tommasi T, Sanfilippo S. Two-step anaerobic digestion process. In: Ruggeri B, Tommasi T, Sanfilippo S, editors. BioH2 & BioCH4 through Anaerobic Digestion. From Research to Full-Scale Applications. Green Energy and Technology. Springer London Heidelberg New York Dordrecht; Springer-Verlag London: 2015. pp. 161-191. DOI: 10.1007/978-1-4471-6431-9\n'},{id:"B25",body:'Ghimire A, Frunzo L, Pirozzi F, Trably E, Escudie R, Lens PNL, et al. A review on dark fermentative biohydrogen production from organic biomass: Process parameters and use of by-products. Applied Energy. 2015;144:73-95. DOI: 10.1016/j.apenergy.2015.01.045\n'},{id:"B26",body:'Toledo-Cervantes A, Arreola-Vargas J, Elias-Palacios SE, Marino-Marmolejo EN, Davila-Vazquez G, González-Álvarez V, et al. Evaluation of semi-continuous hydrogen production from enzymatic hydrolysates of Agave tequilana bagasse: Insight into the enzymatic cocktail effect over the co-production of methane. International Journal of Hydrogen Energy. 2018;43:14193-14201. DOI: 10.1016/j.ijhydene.2018.05.134\n'},{id:"B27",body:'Espinoza-Escalante FM, Pelayo-Ortiz C, Gutiérrez-Pulido H, González-Álvarez V, Alcaraz-González V, Bories A. Multiple response optimization analysis for pretreatments of Tequila’s stillages for VFAs and hydrogen production. Bioresource Technology. 2008;99:5822-5829. DOI: 10.1016/j.biortech.2007.10.008\n'},{id:"B28",body:'Espinoza-Escalante FM, Pelayo-Ortíz C, Navarro-Corona J, González-García Y, Bories A, Gutiérrez-Pulido H. Anaerobic digestion of the vinasses from the fermentation of Agave tequilana weber to tequila: The effect of pH, temperature and hydraulic retention time on the production of hydrogen and methane. Biomass and Bioenergy. 2009;33:14-20. DOI: 10.1016/j.biombioe.2008.04.006\n'},{id:"B29",body:'García-Depraect O, Rene ER, Gómez-Romero J, López-López A, León-Becerril E. Enhanced biohydrogen production from the dark co-fermentation of tequila vinasse and nixtamalization wastewater: Novel insights into ecological regulation by pH. Fuel. 2019;253:159-166. DOI: 10.1016/j.fuel.2019.04.147\n'},{id:"B30",body:'Buitrón G, Carvajal C. Biohydrogen production from tequila vinasses in an anaerobic sequencing batch reactor: Effect of initial substrate concentration, temperature and hydraulic retention time. Bioresource Technology. 2010;101:9071-9077. DOI: 10.1016/j.biortech.2010.06.127\n'},{id:"B31",body:'García-Depraect O, Rene ER, Diaz-Cruces VF, León-Becerril E. Effect of process parameters on enhanced biohydrogen production from tequila vinasse via the lactate-acetate pathway. Bioresource Technology. 2019;273:618-626. DOI: 10.1016/j.biortech.2018.11.056\n'},{id:"B32",body:'Marino-Marmolejo EN, Corbalá-Robles L, Cortez-Aguilar RC, Contreras-Ramos SM, Bolaños-Rosales RE, Davila-Vazquez G. Tequila vinasses acidogenesis in a UASB reactor with Clostridium predominance. Springerplus. 2015;4:1-8. DOI: 10.1186/s40064-015-1193-2\n'},{id:"B33",body:'Moreno-Andrade I, Moreno G, Kumar G, Buitrón G. Biohydrogen production from industrial wastewaters. Water Science and Technology. 2014;71:105-110. DOI: 10.2166/wst.2014.471\n'},{id:"B34",body:'Buitrón G, Prato-Garcia D, Zhang A. Biohydrogen production from tequila vinasses using a fixed bed reactor. Water Science and Technology. 2014;70:1919-1925. DOI: 10.2166/wst.2014.433\n'},{id:"B35",body:'Buitrón G, Kumar G, Martinez-Arce A, Moreno G. Hydrogen and methane production via a two-stage processes (H2-SBR + CH4-UASB) using tequila vinasses. International Journal of Hydrogen Energy. 2014;39:19249-19255. DOI: 10.1016/j.ijhydene.2014.04.139\n'},{id:"B36",body:'García-Depraect O, Valdez-Vázquez I, Rene ER, Gómez-Romero J, López-López A, León-Becerril E. Lactate- and acetate-based biohydrogen production through dark co-fermentation of tequila vinasse and nixtamalization wastewater: Metabolic and microbial community dynamics. Bioresource Technology. 2019;282:236-244. DOI: 10.1016/j.biortech.2019.02.100\n'},{id:"B37",body:'García-Depraect O, León-Becerril E. Fermentative biohydrogen production from tequila vinasse via the lactate-acetate pathway: Operational performance, kinetic analysis and microbial ecology. Fuel. 2018;234:151-160. DOI: 10.1016/j.fuel.2018.06.126\n'},{id:"B38",body:'García-Depraect O, van Lier JB, Muñoz R, Rene ER, Diaz-Cruces VF, León-Becerril E. Interlinking lactate-type fermentation in a side stream anaerobic digestion process of tequila vinasse: An alternative for highly stable and efficient biohydrogen production. (Unpublished)\n'},{id:"B39",body:'Ren N, Zhao D, Chrn X, LI J. Mechanism and controlling strategy of the production and accumulation of propionic acid for anaerobic wastewater treatment. Science In China. 2002;45:319-327\n'},{id:"B40",body:'Sikora A, Błaszczyk M, Jurkowski M, Zielenkiewicz U. Lactic acid bacteria in hydrogen-producing consortia: On purpose or by coincidence? In: Kongo J, editor. Lactic Acid Bacteria. R & D for Food, Health and Livestock Purposes. Rijeka: InThech; 2013. pp. 487-514. DOI: 10.5772/50364\n'},{id:"B41",body:'Elbeshbishy E, Dhar BR, Nakhla G, Lee HS. A critical review on inhibition of dark biohydrogen fermentation. Renewable and Sustainable Energy Reviews. 2017;79:656-668. DOI: 10.1016/j.rser.2017.05.075\n'},{id:"B42",body:'Cabrol L, Marone A, Tapia-Venegas E, Steyer JP, Ruiz-Filippi G, Trably E. Microbial ecology of fermentative hydrogen producing bioprocesses: Useful insights for driving the ecosystem function. FEMS Microbiology Reviews. 2017;41:158-181. DOI: 10.1093/femsre/fuw043\n'},{id:"B43",body:'Méndez-Acosta HO, Snell-Castro R, Alcaraz-González V, González-Álvarez V, Pelayo-Ortiz C. Anaerobic treatment of tequila vinasses in a CSTR-type digester. Biodegradation. 2010;21:357-363. DOI: 10.1007/s10532-009-9306-7\n'},{id:"B44",body:'López-López A, León-Becerril E, Rosales-Contreras ME, Villegas-García E. Influence of alkalinity and VFAs on the performance of an UASB reactor with recirculation for the treatment of tequila vinasses. Environmental Technology. 2015;36:2468-2476. DOI: 10.1080/09593330.2015.1034790\n'},{id:"B45",body:'Jáuregui-Jáuregui JA, Méndez-Acosta HO, González-Álvarez V, Snell-Castro R, Alcaraz-González V, Godonc JJ. Anaerobic treatment of tequila vinasses under seasonal operating conditions: Start-up, normal operation and restart-up after a long stop and starvation period. Bioresource Technology. 2014;168:33-40. DOI: 10.1016/j.biortech.2014.04.006\n'},{id:"B46",body:'Arreola-Vargas J, Jaramillo-Gante NE, Celis LB, Corona-González RI, González-Álvarez V, Méndez-Acosta HO. Biogas production in an anaerobic sequencing batch reactor by using tequila vinasses: Effect of pH and temperature. Water Science and Technology. 2016;73:550-556. DOI: 10.2166/wst.2015.520\n'},{id:"B47",body:'Arreola-Vargas J, Snell-Castro R, Rojo-Liera NM, González-Álvarez V, Méndez-Acosta HO. Effect of the organic loading rate on the performance and microbial populations during the anaerobic treatment of tequila vinasses in a pilot-scale packed bed reactor. Journal of Chemical Technology & Biotechnology. 2018;93:591-599. DOI: 10.1002/jctb.5413\n'},{id:"B48",body:'Gerardi MH. Anaerobic food chain. In: Gerardi MH, editor. The Microbiology of Anaerobic Digesters. Canada: John Wiley & Sons; 2003. p. 39-41\n'},{id:"B49",body:'Vuitik GA, Fuess LT, Del Nery V, Bañares-Alcántara R, Pires EC. Effects of recirculation in anaerobic baffled reactors. Journal of Water Process Engineering. 2019;28:36-44. DOI: 10.1016/j.jwpe.2018.12.013\n'},{id:"B50",body:'Detman A, Mielecki D, Pleśniak Ł, Bucha M, Janiga M, Matyasik I, et al. Methane-yielding microbial communities processing lactate-rich substrates: A piece of the anaerobic digestion puzzle. Biotechnology for Biofuels. 2018;11:1-18. DOI: 10.1186/s13068-018-1106-z\n'},{id:"B51",body:'Wu Y, Wang C, Liu X, Ma H, Wu J, Zuo J, et al. A new method of two-phase anaerobic digestion for fruit and vegetable waste treatment. Bioresource Technology. 2016;211:16-23. DOI: 10.1016/j.biortech.2016.03.050\n'},{id:"B52",body:'Pipyn P, Verstraete W. Lactate and ethanol as intermediates in two-phase anaerobic digestion. Biotechnology and Bioengineering. 1981;23:1145-1154\n'},{id:"B53",body:'Snell-Castro R, Méndez-Acosta HO, Arreola-Vargas J, González-Álvarez V, Pintado-González M, González-Morales MT, et al. Active prokaryotic population dynamics exhibit high correlation to reactor performance during methane production from acid hydrolysates of Agave tequilana var. Azul bagasse. Journal of Applied Microbiology. 2019;126:1618-1630. DOI: 10.1111/jam.14234\n'},{id:"B54",body:'Diaz-Cruces VF, García-Depraect O, León-Becerril E. Performance of two-stage anaerobic digestion of tequila vinasse with acidogenic lactate-type fermentation. (Unpublished)\n'}],footnotes:[],contributors:[{corresp:null,contributorFullName:"Octavio García-Depraect",address:null,affiliation:'
Department of Environmental Technology, Centro de Investigación y Asistencia en Tecnología y Diseño del Estado de Jalisco, A.C., Guadalajara, Jalisco, México
'},{corresp:null,contributorFullName:"Daryl Rafael Osuna-Laveaga",address:null,affiliation:'
Department of Environmental Technology, Centro de Investigación y Asistencia en Tecnología y Diseño del Estado de Jalisco, A.C., Guadalajara, Jalisco, México
Department of Environmental Technology, Centro de Investigación y Asistencia en Tecnología y Diseño del Estado de Jalisco, A.C., Guadalajara, Jalisco, México
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UK Research and Innovation (former Research Councils UK (RCUK) - including AHRC, BBSRC, ESRC, EPSRC, MRC, NERC, STFC.) Processing charges for books/book chapters can be covered through RCUK block grants which are allocated to most universities in the UK, which then handle the OA publication funding requests. It is at the discretion of the university whether it will approve the request.)
Wellcome Trust (Funding available only to Wellcome-funded researchers/grantees)
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