Enrichment of electrogenic consortiums for the degradation of vinasses and molasses in MFC

doi:10.21203/rs.3.rs-4986770/v1

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Enrichment of electrogenic consortiums for the degradation of vinasses and molasses in MFC

https://doi.org/10.21203/rs.3.rs-4986770/v1

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Energy production in bioelectrochemical systems is affected by microorganisms developed during the degradation processes of organic matter from wastewater from the sugar industry and alcoholic beverages such as tequila and mezcal. However, the efficiencies of chemical to electrical energy conversion remain insufficient for large scale implementation of this technology. Microorganisms used for bioelectricity generation; model organisms such as Geobacter sulfurreduscens and Shewanella oneidensis have been studied exhaustively. However, there are few reports about the capabilities of mixed consortiums for the degradation of organic matter and bioelectricity production. In the present study, the performance of MFC was evaluated with equivalent circuit modeling. Results suggest that internal resistances affect performance. In addition, capacitive and ion transport elements are also influenced by the consortiums that have been developed. Scanning electronic microscopy analysis showed differences in anodic biofilm density and, together with an analysis of amplicon sequences of the 16S rRNA gene, it was found that the substrate has a direct effect on the development of Electrogenic Microbial Consortiums (EMC) an their organic matter degradation and bioelectricity production capacities.

Electrogenic microbial consortium

Microbial fuel cell

Molasse

Vinasse

Bioelectricity production

Vinasses and molasse contains compounds can be used for bioelectricity production.

The substrate directly affected the microbial populations developed in the biofilm.

Associations of electrogenic microorganisms were identified in consortia in MFC.

Electrical energy consumption has doubled in the last 20 years, and their production depends on fossil fuels such as coal, natural gas, and oil, which increase pollution. Furthermore, we have reached a point of no return in terms of the consumption of fossil fuels, where we will witness their imminent depletion (Martins et al., 2019). In contrast, electricity generation through renewable resources, such as hydroelectric, nuclear, and wind, represents 30% of total production. However, electricity production from waste barely reaches 0.4% (IEA, 2023). In Mexico, industries such as tequila and sugar (sugar cane) represent a significant activity within the country's agriculture and economy. However, their production processes generate a large amount of liquid organic waste that contaminates nearby bodies of water. These wastes contain a high content of organic matter, such as vinasses (waste from the tequila industry), and a high concentration of sugars, organic acids, esters, and alcohol (Moran-Salazar et al., 2016). For its part, molasses (waste from the sugar industry) is rich in sugars, mainly sucrose, glucose, and fructose. High organic load makes them excellent substrates for fermentation processes and energy production. Devices capable of generating clean electricity are rapidly gaining ground; for example, electricity production with photovoltaic systems increased 60 times from 2005 to 2015 (IEA, 2023). Therefore, we predict a high growth for this technology. Another device that is gradually gaining more ground at the research level is microbial fuel cells (MFC). Compared to photovoltaic systems, MFCs are interesting because they can produce electricity simultaneously and eliminate organic matter. Moreover, these devices can produce compounds of interest, such as some organic acids, alcohols, methane, and hydrogen, and they can function as biosensors or traps for recalcitrant compounds or heavy metals (Li et al., 2017). MFCs are electrochemical devices that degrade organic matter from liquid waste through bacterial metabolism, microorganisms use the waste liquid as a substrate to grow in the form of a biofilm on the surface of an electrode called the anode, and then the electroactive bacteria (EAB) are capable of transferring electrons to the anode by different mechanisms. Subsequently, the electrons are conducted through an external circuit to another electrode called the cathode. Due to an electrical potential differential between the anode and the cathode, an electrical voltage is generated. Finally, electrons together with the protons generated in the anode, and used to reduce oxygen (or another compound) using a catalyst in the cathode, usually platinum. In other cases, a biocathode makeup of a biofilm works as a biocatalyst instead of platinum, generating water as a final product. Based on the above, the consortia that grow in MFC play a role in the degradation of organic matter and bioelectricity production. Therefore, we have sought to describe microbial diversity to understand how EMC works (Yang and Cheng, 2021; Negassa et al., 2021; Choudhury et al., 2021).

The phylum Proteobacteria, Firmicutes, and Bacteriodetes have been found in high abundance within the consortia characterized in MFC using sequencing of the 16S ribosomal gene (16S rRNA) of the small subunit of the prokaryotic ribosome (Liu et al., 2018; Zhao et al., 2017). However, it is difficult to identify at the species level due to limitations in sequencing technologies and variable region analysis of the 16S rRNA gene since this gene presents high similarity between species (Kozich et al., 2013). The low cost of sequencing has allowed more complex studies to be carried out, such as those based on metagenomics (total DNA sequencing obtained from an environmental sample), and allowed a more robust analysis of microbial diversity (Segata et al., 2012). The best-described extracellular electron transfer mechanisms (EETM) were based on the study of Geobacter sulfurreducens and Shewanella oneidensis MR1. Both microorganisms present direct or indirect mechanisms that involve cytochromes C located on the surface of the plasma membrane or in the so-called pili, which are cable-shaped extensions of the membrane and reach up to 20 µm in length (Saratale et al., 2017; Ren et al., 2021). These mechanisms work synergistically within EMCs for electricity generation. However, other electron exchange mechanisms of other species can be involved, as well as syntrophic relationships for the use of the compounds generated between different species of microorganisms to improve the efficiency of MFC (Pirbadian et al., 2014; Wang et al., 2013; Wang et al., 2022). The goal of the present work is to determine the electrogenic microbial consortium developed using tequila vinasse, mezcal vinasse, and molasse, used as substrates for a DC-MFC.

2.1. Architecture of MFC and data acquisition system

Three MFC of modular design were built with acrylic sheets (PLEXIGLAS®) of 5 mm and 12 mm thickness for the covers and the body, respectively. This design allows the use configuration of two cameras separated by MIP. The plates that make up the body of the chamber measure 10 cm on the outside and 8 cm on the inside. Therefore, the volume of one module is equivalent to 75 ml. The volume of the DC-MFC is 150 ml, with a distance between electrodes of 1.2 cm. For the double chamber configuration separated by Proton exchange membrane (MEP) Nafion TM117 (DuPont Co), the MFC of 4 plates and the volume was 150 ml for each chamber. The cathode was immersed in a potassium ferrocyanide (100 mM) catholyte, and the distance between electrodes was 1.2 cm. Anode and cathode of graphite felt with a thermally conditioned (0.0025 m²). External resistance was 1000 Ohms. The data acquisition system was built with an Arduino Mega 2560 (ADC22, Pico Technology, Ltd.) connected to the three MFC through a breadboard with Dupont-type jumper cables and configured with the appropriate resistors (after characterizing the internal resistance of the system). The electronic system with the Simulink tool of the Matlab software (Mathworks®) was programmed. The Arduino is connected to a computer for closed-circuit voltage data recording. A period of fifteen days in an open circuit was necessary to allow the development of biofilms, the voltage production in a closed circuit for 650 h was monitored. The energy efficiency variables were obtained based on the previously reported methodology (Guadarrama-Pérez et al., 2024).

2.2. Electrochemical impedance spectroscopy

To determine the internal resistances of the electrolyte and the interface, electrochemical impedance spectroscopy (EIS) studies were carried out with a Potentiostat/galvanostat/ZRA 09097 (Gamry instrument Interface 1000TM). The frequency range used was 0.1 Hz-100 KHz with an alternating current signal to an amplitude of 5 mV to analyze the response without disturbing the operation of the reactors. The conditions of the test were manipulated with Gamry Framework software. The anodic potentials with the same equipment and a reference electrode (Ag/AgCl) (3 M KCl, + 207 mV, pH 7 to 25°C, Metrohm) were determined. The internal resistances (ohmic and anode-anolyte interface resistance), constant phase elements, and Warburg elements were analyzed using an equivalent circuit model for characterization of the MFC with the Zsim Demo (v3.20) software and the R model (Q(RW)).

2.3. Scanning electron microscopy

The scanning electron microscopy analysis was mounted on a Hitachi SU5000 model, using a 1cm² surface sample of the anode where the biofilm was fixed with a gold cover. The equipment was operated with a voltage acceleration of 5kV, and the micrographs were obtained to magnifications between 0.1 and 10kX.

2.4. Determination of microbial composition

A mixed inoculum was obtained from anaerobic granular sludge from a paper industry; anodic biofilm samples were collected from the MFC to determine the relative abundance. The biofilm and inoculum samples at -70°C were frozen. The DNA was extracted with a DNeasy PowerSoil kit (MOBIO) according to the manufacturer's instructions. The V3-V4 regions of the 16S rRNA were amplified in the Institute of Biotechnology (UNAM). Metagenomic libraries of 16S rRNA were constructed according to the protocol of the University Mass Sequencing and Bioinformatics Unit (UUSMB). The 16S rRNA amplicons were obtained from the V3-V4 variable regions by the Illumina MiSeq platform in a paired read configuration (2X250 bp) in 600 cycles. Quality control of the reads was performed with a minimum Phred index value of Q > 20 using FastQC software. Determination of microbial taxonomy was done by QIIME2 software (Hall and Beiko, 2018), and chimeras and sequencing errors were eliminated. With DADA2 software, the ASV (amplicon sequence variant) was generated (Callahan et al., 2016), and the taxonomic classification was assigned using SILVA (v138) database. Finally, with QIIME2, microbial diversity was determined using richness, Faith index for alpha diversity, and Shannon index for beta diversity.

Initially, the three MFC produced a maximum voltage of between 100 and 150 mV, and then gradually reduced during the subsequent 192 h. The voltage of the MFC fed with mezcal vinasse (mv-MFC) showed a minor effect compared to the MFC fed with tequila vinasse (tv-MFC) and molasses (ms-MFC). During cycle 1 (C1), mv-MFC produced a maximum voltage of 110 mV and the rest of the MFC produced between 50 and 80 mV. In cycle 2 (C2), tv-MFC produced a maximum voltage of 120 mV, and the rest of the MFC produced 100 mV. The maximum voltage for the three MFC occurred in cycle 3 (C3) with values between 140 and 160 mV, in which the tv-MFC presented the highest value. During the remainder, the maximum voltage decreased to levels similar to the first two cycles, and the MFC that produced the highest voltage were tv-MFC in cycle 4 (C4), mv-MFC in cycle 5 (C5), and tv-MFC in cycle 6 (C6) (Fig. 1a).

The power density generated by MFC was differential throughout the entire run; tv-MFC and mv-MFC presented the highest power density in C4/C5 and C1/C6, respectively. Furthermore, ms-MFC generated a lower power density. In C2/C3, not show significant difference. A gradual increase in the power density in MFC during the first three cycles, subsequently a reduction was generated, but mv-MFC recovered during C5 and C6. The tv-MFC showed less variation during the first five cycles, but in C6 was reduced (Fig. 1b). The COD was calculated in the raw substrates and thus adjusted to use a COD value between 3000 and 4200 mg/L as an influent (IN). The COD of the effluents was similar for all cycles, with values between 1500 and 2000 mg/L. The ms-MFC presented the lowest COD in the influent, while mv-MFC presented the highest COD (Fig. 1c). The degradation of organic matter was between 30 and 60%. However, the highest COD removal (%) is observed in the mv-MFC in C3 and C6 (Fig. 1d).

The EIS analysis showed the changes in internal resistances in each MFC during the operation. We observe a minimal difference in solution resistances (R_s) during C1-C3. In subsequent cycles, this difference will increase considerably; in mv-MFC, R_s increase 400%, while in the other MFCs increase less than 100%. It was not possible to determine graphically the charge transfer resistance (R_ct) values due to the limitations that present the Nyquist curves (Fig. 2). However, an analysis of modeling by equivalent circuits allowed us to determine the values of the Ohmic resistance (R₁), the charge transfer resistance (R₂), the constant phase elements (Q₂), and the Warburg elements (W₂). Table 1 shows the values obtained by modeling equivalent circuits with the R (Q (RW)) model. In general terms, an increase of R1 in C1, C2, and C6 was observed. Together, the R₂ values decrease, while the elements associated with the Q₂ capacitances decreased. Finally, W₂ decreased for tv-MFC and mv-MFC but increased for ms-MFC. Therefore, the smallest R1 value in ms-MFC, mv-MFC, and tv-MFC presented a high R1 value compared to ms-MFC. The R₂ value decreased by 50% for ms-MFC and tv-MFC, while i mv-MFC decrease was greater than 50%. Finally, lower values of Q₂ and W₂ occur in tv-MFC and mv-MFC compared to ms-MFC.

Table 1

Equivalent circuit modeling values in EIS testing.
	ms-MFC			mv-MFC			tv-MFC
Parameter	C 0	C 3	C 6	C 0	C 3	C 6	C 0	C 3	C 6
R₁ (Ω)	13.3	18.5	19.9	36.7	37.5	38.3	15.8	20.9	27.3
R₂ (Ω)x10⁸	2.8	1.8	1.4	4.9	3.4	1.9	4.4	3.5	2.2
Q₂ (CPE) x10^− 3	10.37	9.34	10.1	7.25	6.98	7.91	6.89	6.5	7.23
W₂ (Ω S^− 1/2)x10^− 4	2.4	13	13.4	8.5	6.6	5.4	5.4	2	3.1
R₁, Ohmic resistance; R₂, Load transfer resistance; Q₂, Capacitances of the electrical double layer corresponding to the interfaces between the anode/anolyte and cathode/catholyte; W₂, Warburg Elements. C0, initial phase; C3, middle phase; C6, final phase.

Scanning electron microscopy analysis allowed us to determine the state of the biofilms attached to the anode towards the end of the run; fibers that make up the carbon felt have cylindrical geometry and have organization in the form of a web. Images do not allow us to distinguish between the lengths of each strand, so we assume that the extension can be variable. Furthermore, the density and dimensions of the structures are similar. Accordingly, we assume that the surface area is not significantly different in the anode of each MFC. We observed a significant difference in the attached cell density; tv-MFC showed a higher density in the biofilm (Fig. 3a) that was slightly higher than mv-MFC (Fig. 3b), while ms-MFC the biofilm was scarce (Fig. 3c).

Amplicon sequencing of the 16S rRNA gene allowed us to determine the richness, alpha, and beta diversity index; tv-MFC presented the highest number of identified species, while inoculum and the mv-MFC film presented a similar richness, and mv-MFC presented the lowest richness of all and even lower inoculum (Fig. 4a). Faith's diversity index (alpha diversity) suggests that the inoculum is the most diverse and that the biofilms obtained in MFC decrease their diversity depending on the formation of new EMC. The consortium with the highest alpha diversity was found in tv-MFC, while mv-MFC showed the lowest alpha diversity (Fig. 4b). Furthermore, the Shannon index indicates that inoculum presents the highest beta diversity, EMCs found in tv-MFC and ms-MFC present similar values, and mv-MFC presents the lowest value. Our results suggest that microbial diversity decreases as an effect of selective pressure during the production of bioelectricity and the degradation of matter, forming specialized consortia (Fig. 4c).

Taxonomic assignment with QIIME2 with the SILVA (v138) database allowed resolution down to the genus level. Figure 5a shows the most abundant genera in tv-MFC identified were Bacteroides (38.1%), Pseudomonas (13.9%), Sphingobium (10.6%), and Taibaiella (8.9%), Oscillibacter (7.6%), Pullidibacter (7.5%), Parabacteroides (3.6%), Mecellibacteroides (3.5%). In mv-MFC, the genera with the highest abundance were Gluconobacter (57.5%), Lactobacillus (16.2%), Arconobacter (10.92%), Clostridium (10%), and Brevundimonas (4.6%). In ms-MFC, the genera Pseudomonas (19.2%), Brevundimonas (11.3%), Stenotrophomonas (31.4%), Clostridium (19.2%), Sphingobacterium (5.4%), Alcaligenaceae (5.2%), and Bifidobacterium (3.5%). Finally, the most abundant microorganisms in the inoculum were Rikenellaceae unculture (31.6%), Methanosaeta (14.9%), Anaerolinea (14.4%), Petrimonas (8.6%), Izemoplasmatales (5.5%) and Bacteroidales (4%). Interestingly, the EMC developed in each MFC are unique and have slight similarities; between ms-MFC and tv-MFC, the genera Sphingobacterium, Stentrophomonas, and Pseudomonas are repeated, while between ms-MFC and mv-MFC the genera Lactobacillus, Brevundimonas and Clostridium are repeated. However, there is no similarity between vinasses. Our results suggest a selective enrichment of bacteria is found in a small proportion of the inoculum and develops slowly in the MFC. Figure 5b shows a phylogenetic tree in which microorganisms are grouped based on their 16S rRNA sequence similarity. In some clades, genera are present in more than one MFC, while others are present in a single MFC. On top of the tree, Clostridia UCG-014 and Oscillibacter are present in tv-MFC. As well as the genera Eubacterium, Clostridium, Lactobacillus, and Bifidobacterium are present in mv-MFC, ms-MFC, and inoculum. In the third clade, microorganisms are present only in the inoculum, while in the fourth clade, Pseudomonas and Stenotrophomonas are present in ms-MFC and tv-MFC. Finally, several organisms that lose similarities are present in the inoculum or tv-MFC.

The voltages generated depended on each substrate feed and significant differences concerning the power density, with mv-MFC presenting the highest power density at the beginning and the end of the run. Furthermore, the COD removal (%) presented in mv-MFC was the lowest of all MFCs. Indeed, in terms of energy efficiency, mv-MFC was the best compared with other MFCs. Interestingly, mv-MFC presented the lowest alpha and beta diversity (Faith and Shannon indices). These results suggest that an efficient consortium for bioelectricity production does not necessarily have to be diverse and depends on the substrate fed into the MFC. In the density of the biofilm observed with an SEM analysis, ms-MFC had limitations in developing a robust and thick film, which may explain why this MFC presented a low performance in the production of bioelectricity but a high percentage of COD removal due to bacteria that could be in growth planktonic form. The mv-MFC and tv-MFC biofilms presented similar characteristics in biofilm density. In addition, they presented the highest power densities at some point in the run.

Some studies show the evaluation of biofilm thickness and power density generation. Ye et al. (2021) visualized the biofilm formation in real-time in a microfluidic MFC, supported with phase contrast microscopy techniques, and the authors evaluated the flow rate of the anolyte on the growth of the biofilm. The results showed a slow growth with slow flow, which means, in batch-fed MFC, this growth may be even lower. Furthermore, the authors observed that a thicker biofilm increases the R_ct. However, this contrasts with the data obtained in the present study (Table 1). In another study, Mahmoud et al. (2021) characterized the biofilm in DC-MFC with SEM using different materials in the anodes graphite, Multi-Walled Carbon Nanotubes (MWCNTs), and MWCNTs/MnO₂. The authors conclude that it is necessary to evaluate the cost-benefit of the electrode material based on its biocompatibility, stability, and conductivity characteristics. Recently, Hemdan et al. (2023) determined the structure of biofilms grown on graphite rod electrodes modified with soybean meal and a) graphene oxide, b) polyaniline, or c) CNTs. A Field Emission Scanning Electron Microscopy (FESEM) analysis showed that the biofilms presented different cellular morphologies and had a cover with different textures; the densest biofilm developed on the anode covered with polyaniline. The cell density on the electrode could be correlated with the power density since the anode covered with polyaniline had the highest power density. Consequently, microscopy tools allow us to observe the state of the biofilm and relate it to the development of EMC in bioelectrochemical systems to determine cell density, morphology, and biocompatibility with the electrode.

In this study, the modeling of equivalent circuits showed that the MFC fed with vinasse presented a better performance compared with the MFC fed with molasse (Table 1), and variations in resistance of the solution, charge transfer, capacitive elements, and Warburg elements were measured. The value of R₁ represents the Ohmic resistance and indicates the resistance produced by the solutions and transport of protons through the membrane; when the membrane fouling, R₁ is affected. R₂ represents the anodic and cathodic charge transfer resistances. Furthermore, this value is inversely proportional to the reaction rates produced in their respective chambers, which means a small value produces a higher redox potential and a higher voltage. Q₂ represents the capacitances of the electrical double layer corresponding to the interfaces between the cathode and the catholyte or between the anode and the anolyte, as well as high values of Q₂ mean energy wasted. W₂ is associated with diffusion processes through the surface of the electrodes, and high values could be due to the accumulation of electrons on the surface of the electrodes (Sindhuja et al., 2016).

In this study, a substantial increase in R₁ was observed for ms-MFC and tv-MFC, suggesting an increase in the resistance of the anolyte or the transport of protons through the MIP. Furthermore, mv-MFC showed the most drastic decrease in R₂ associated with the high power density performance towards the final phase of the run. In the case of the Q₂ and W₂ values, they explain why ms-MFC showed lower performance associated with the capacitive and ion diffusion elements (Warburg). Logan et al. (2018) investigate the role of internal resistances in an H-type bioelectrochemical system to evaluate the effect of electrode size. The authors determined that the electrode size does not significantly affect the internal resistance. However, the authors only determine the resistance in the R_s solution with the graphical method based on the Nyquist curves. This type of analysis is common in bioelectrochemical systems, but modeling by equivalent circuits could provide valuable information on the capacitive mechanisms and diffusion. In a previous study, equivalent circuit modeling analysis in a single chamber microbial fuel cell allowed us to determine the effect of inoculum on performance, with granular sludge being a better source of microorganisms versus stream sediments. Sediments showed higher solution and transfer resistances and decreased power density (Guadarrama-Pérez et al., 2024). Other studies also demonstrate the utility of EIS in the characterization of bioelectrochemical systems not only in determining internal resistances but also in the energy stored and the diffusion levels of ions or electrons three from the anode (Kandpal et al., 2021; Bian et al., 2018).

Beta diversity analysis determines differences in each of the microbial community structures. Principal Coordinate Analysis (PCoA) indicates that the Bray-Curtis and Jaccard indices obtained similar distances. Both Unifrac indices (Weighted and unweighted) show a different distance for each sample, suggesting that each consortium developed in the MFCs and the inoculum are unique communities (Supplementary Material S1). Since some genera were present in more than one MFC, beta diversity analysis showed differences between samples, indicating that the substrate fed in the MFC is a factor to consider in the development of EMC. The weighted Unifrac index (account abundance and richness) demonstrates that ms-MFC EMCs show a short distance from the inoculum. Results suggest a moderate similarity between the EMC of ms-MFC and the inoculum and correlated with the low power density produced but present a high percentage of COD removal. Thus, the change in microbial composition may be associated with the formation of EMC since tv-MFC and mv-MFC obtained a higher performance in power density concerning ms-MFC. Using the Unifrac indices, the structure of the tv-MFC microbial community was the one with the high distance from the inoculum. The EMC developed in tv-MFC was the least similar to the inoculum. Finally, ms-MFC showed a longer similarity distance with the rest of the MFC and suggested EMC development occurs slowly compared to tv-MFC. Indeed, the beta diversity indices show that the consortia formed in the biofilms obtained in MFC are different from each other and the inoculum. Accordingly, each consortium is unique, which showed the capacity to produce bioelectricity (tv-MFC and mv-MFC) or for the degradation of organic matter (ms-MFC).

Authors have reported that Pseudomonas is capable of generating bioelectricity under specific conditions. Wang et al. (2013) report that the Pseudomonas aeruginosa strain produces phenazines that function as mediators in various EETM. Furthermore, in this species, some genes responsible for the formation of quorum sensing have been identified and that, through the regulation of several genes, promote the production of phenazines (Yong et al., 2011). Pseudomonas aeruginosa can increase the extracellular electron exchange capacity by regulating gene IrrE (ionizing radiation resistance linking group E) (Luo et al., 2020). The Gluconobacter genus is capable of generating bioelectricity in some particular cases. Krishnaraj et al. (2015) found that Gluconobacter suboxydans have good electrogenic characteristics because they produce several dehydrogenase enzymes with high electrocatalytic activity. Plekhanova et al. (2019) found that Gluconobacter suboxydans can act as a biosensor growing on MWCNTs since a change in the enzymatic activity of the respiratory chain is not observed (carbon nanotubes can sometimes be toxic for some bacteria). This biosensor allowed the identification of some substrates, such as glucose and ethanol, generating electrical signals ranging from 65–869 nA and 181–1048 nA, respectively. In a previous study, Adachi et al. (2021) found that the Gluconobacter oxydans species has direct extracellular electron exchange mechanisms because the aldehyde dehydrogenase enzyme is located in the membrane and presents electrocatalytic activity. Other recent reports focus on studying its extensive enzymatic machinery for the degradation of different substrates (Habe et al., 2021; Kataoka et al., 2021), suggesting that it can occur in MFC. Besides, a recent report describes the effect on population dynamics of some electroactive genera in MFC. Rivalland et al. (2022) investigated the role of Clostridium in an interspecies cooperative system. The results showed that the genus Desulfuromonas dominated the biofilm. However, when the yield decreased, Clostridium was able to increase it, promoting the subsequent growth of Geobacter. Therefore, Clostridium can be associated with other electrogenic microorganisms. In another recent report, Huo et al. (2022) demonstrated that Clostridium kluyveri can grow in presence of short-chain fatty acids that include acetate, propionate, and butyrate. Results agree with the use of similar substrates as tequila vinasse or mezcal vinasse (Moran-Salazar et al., 2016). Finally, Clostridium grows in bioelectrochemical systems, and their role in particular has not been concretely described yet (Yang et al., 2021; Bhatti et al., 2022; Guan and Yu, 2021). Another predominant genus in mv-MFC was Bacteroides, a metal-reducing bacteria described as a fermentative bacteria capable of degrading complex substrates (Wang et al., 2010). Li et al. (2013) investigated the degradation of substrates from leachate of food waste in MFC; the enrichment of Bacteroides was modified with the degradation of organic matter, while bioelectricity production attributed to Geobacter. Furthermore, Bacteroides was reported as a good xylose degrader, producing intermediate metabolites for electricity generation in MFC with Geobacter (Mäkinen et al., 2013). The data suggest that Bacteroides can be associated with electrogenic microorganisms due to their ability to degrade complex substrates, thus generating syntrophism with Geobacter and others. In the present study, a similar phenomenon in mv-MFC was determined. The maximum power density produced in the final phase suggests that Bacteroides possibly favored the development of Pseudomonas. Another possible association identified in ms-MFC was Pseudomonas with Stenotrophomonas, where previous report shows that Pseudomonas is capable of producing bioelectricity by at least two different mechanisms (Chen et al., 2021) and has recently been identified in MFC as one of the microorganisms with high relative abundances (Rojas-Flores et al., 2021; Li et al., 2019).

In the present study, possible associations that could function as EMC in MFC have been identified. However, the information is still limited, so more studies are required to delve into these phenomena. Table 2 shows the communities described in the present study at the genus level, compared with those reported by other authors in similar studies. The genera Clostridium and Lactobacillus found in tv-MFC and processes fed with the same substrate for the production of hydrogen and methane, which suggests that they could be organic matter degraders (Arellano-García et al., 2021; García-Depraect et al., 2021). Regarding mv-MFC, information is limited, and this study is one of the few to date to characterize the microbial communities developed in MFC with this substrate, while reports of MFC fed with molasses are a little cruder. However, the description of the microbial communities for this substrate is rarely described, and reports presented here have no present coincidence with the microorganisms identified. This study means that the source of the inoculum is a factor to consider when describing communities (Yang et al., 2022; Tripathi et al., 2022). The importance of the inoculum and the substrate in the development of EMC are a couple of variables to consider in the performance of bioelectrochemical systems. On the other hand, operational parameters such as hydraulic residence time, MFC configuration, and substrate concentration are aspects linked to population dynamics that must be studied further using advanced techniques such as EIS, SEM, and genomic analyses to describe the development of EMC into MFC.

Table 2

Microbial Consortiums developed in bioprocesses with vinasses and molasses.
MFC type	Substrate	Microorganisms	Power density (mW/m²)	Reference
Dual Chamber	Mezcal vinasse	Bacteroides, Pseudomonas, Sphingobium and Taibaiella	25	Present study
Dual Chamber	Tequila vinasse	Gluconobacter, Pseudomonas, Clostridium, Lactobacillus, Arconobacter and Brevundimonas	18	Present study
Dual Chamber	Molasse	Pseudomonas, Brevundimonas Stenotrophomonas, Lactobaillus and Sphingobacterium	14	Present study
Sludge from molasse destilery	Molasse	Clostridium, Bacteroides, Tisierella and Firmicutes	Not apply	Tripathi et al. 2022
Dual Chamber	Molasse	Azospirillum, Sulfuricurvum, Syntrophomonas and Curvibacter	3 W/m³	Yang et al. 2022
Methane production	Tequila vinasse	Clostridium, Lactobacillus, Acetobacter, Sporolactobacillus and Caproiciproducens	Not apply	Arellano-García et al. 2021
Hydrogen production by dark fermentation	Tequila vinasse	Clostridium, Lactobacillus, Acetobacter, Klebsiella and Enterobacter	Not apply	García-Depraect et al. 2021
Not all systems involve vinasses or molasses for the production of bioelectricity as well as for the production of biogas.

MFC fed with vinasse showed higher power density in comparison with MFC fed with molasses. Differences in the internal resistances of the MFC were determined. The substrate type used in MFC directly affected the microbial composition developed in biofilms compared with the source, identifying some consortiums for bioelectricity production and organic matter degradation. The present research suggests that the selection of substrates can favor the formation of electrogenic microbial consortia in bioelectrochemical systems to obtain better performances to bioelectricity production in bioelectrochemical systems.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Author Contribution

Mijaylova-Nacheva Petia: Conceptualization, Supervision. Godoy-Lozano Elizabeth Ernestina: Methodology. Guadarrama-Pérez Oscar: Methodology. Alegría-Herrera Elian Yuritzi: Formal analysis. Estrada-Arriaga Edson Baltazar: Methodology. Hernández-Romano Jesús: Methodology. Guadarrama-Pérez Victor Hugo: Supervision, Conceptualization, Visualization, Investigation, Methodology, Formal analysis, Writing – review & editing.

Acknowledgement

This work was supported by Instituto Mexicano de Tecnología del Agua, Universidad Politécnica del Estado de Morelos and Consejo Nacional de Humanidades, Ciencias y Tecnologías.

Data availability

Data will be made available on request.

CRediT authorship contribution statement

Mijaylova-Nacheva Petia: Conceptualization, Supervision. Godoy-Lozano Elizabeth Ernestina: Methodology. Guadarrama-Pérez Oscar: Methodology. Alegría-Herrera Elian Yuritzi: Formal analysis. Estrada-Arriaga Edson Baltazar: Methodology. Hernández-Romano Jesús: Methodology. Guadarrama-Pérez Victor Hugo: Supervision, Conceptualization, Visualization, Investigation, Methodology, Formal analysis, Writing – review & editing.

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No competing interests reported.

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Enrichment of electrogenic consortiums for the degradation of vinasses and molasses in MFC

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Abstract

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Highlights

1. Introduction

2. Materials and methods

2.1. Architecture of MFC and data acquisition system

2.2. Electrochemical impedance spectroscopy

2.3. Scanning electron microscopy

2.4. Determination of microbial composition

3. Results

4. Discussion

5. Conclusions

Declarations

Declaration of Competing Interest

Author Contribution

Acknowledgement

Data availability

References

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Supplementary Files

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Version 1