Transcriptomic Responses of the Interactions between Clostridiumcellulovorans 743B and Rhodopseudomonas palustris CGA009 in aCellulose-Grown Coculture for Enhanced Hydrogen Production

Hongyuan Lu, Jiahua Chen, Yangyang Jia, Mingwei Cai, Patrick K. H. Lee

School of Energy and Environment, City University of Hong Kong, Hong Kong

ABSTRACT

Coculturing dark- and photofermentative bacteria is a promising strategy for enhanced hydrogen (H2) production. In this study,next-generation sequencing was used to query the global transcriptomic responses of an artificial coculture of Clostridium cellu-lovorans 743B and Rhodopseudomonas palustris CGA009. By analyzing differentially regulated gene expression, we showed that,consistent with the physiological observations of enhanced H2 production and cellulose degradation, the nitrogen fixation genesin R. palustris and the cellulosomal genes in C. cellulovorans were upregulated in cocultures. Unexpectedly, genes related to H2

production in C. cellulovorans were downregulated, suggesting that the enhanced H2 yield was contributed mainly by R. palus-tris. A number of genes related to biosynthesis of volatile fatty acids (VFAs) in C. cellulovorans were upregulated, and corre-spondingly, a gene that mediates organic compound catabolism in R. palustris was also upregulated. Interestingly, a number ofgenes responsible for chemotaxis in R. palustris were upregulated, which might be elicited by the VFA concentration gradientcreated by C. cellulovorans. In addition, genes responsible for sulfur and thiamine metabolism in C. cellulovorans were down-regulated in cocultures, and this could be due to a response to pH changes. A conceptual model illustrating the interactions be-tween the two organisms was constructed based on the transcriptomic results.

IMPORTANCE

The findings of this study have important biotechnology applications for biohydrogen production using renewable cellulose,which is an industrially and economically important bioenergy process. Since the molecular characteristics of the interactions ofa coculture when cellulose is the substrate are still unclear, this work will be of interest to microbiologists seeking to better un-derstand and optimize hydrogen-producing coculture systems.

Microorganisms do not live in isolation in nature; instead,they interact with each other in complex ecological net-

works within a microbial community in order to function andresist stresses in various environments (1). In general, interspeciesinteractions define the characteristics and robustness of microbialcommunities. The concept of microbe-microbe interactions hasbeen harnessed and applied in the bioremediation (2, 3), food andbeverage (4–7), and biofuel (8–12) industries. The application ofmultispecies systems could be a promising alternative bioprocessstrategy to the use of single species, which requires extensive ge-netic engineering before multiple desirable traits are incorpo-rated, whereas these functions are distributed among differentorganisms in a multispecies system (13). However, multispeciessystems can be challenging to control (14); therefore, a detailedunderstanding of the physiological and molecular mechanisms ofmicrobial interactions is important in engineering robust com-plex microbial communities.

Studying the interactions that occur in a complex microbialcommunity involving hundreds of species is inherently challeng-ing because of the metabolic complexity of individual species aswell as all the potential interactions between species. Hence, thereis growing interest in studying artificial coculture or triculturemodels, in which the interactions are simpler and can thereby bemore precisely analyzed and interpreted. For example, He et al.imitated the natural dechlorinating communities and establisheda coculture to investigate the positive impact of microbial interac-tions on the dechlorination activity and growth of dechlorinatingstrains (2). Xie et al. cultivated algae with cobalamin-producing

bacteria to study the algal-bacterial mutualistic interaction thatresulted in thermal tolerance enhancement in the algae (15).Cheirsilp et al. employed a coculture of a lactic acid bacterium anda lactic acid-assimilating yeast, which led to higher kefiran pro-ductivity (7). In the field of biofuels, such as biohydrogen, cocul-ture models have also been established. For example, studies havedemonstrated that cocultures containing dark-fermentative bac-teria such as Clostridium species and photosynthetic bacteria suchas Rhodopseudomonas species can enhance hydrogen (H2) pro-duction and substrate consumption (16–22).

The experimental characterizations of the physiology of cocul-ture models have provided some basic understanding of microbialinteractions. However, in order to obtain a system understandingof how species interact, it is also essential to probe the genome-

Received 10 March 2016 Accepted 11 May 2016

Accepted manuscript posted online 20 May 2016

Citation Lu H, Chen J, Jia Y, Cai M, Lee PKH. 2016. Transcriptomic responses of theinteractions between Clostridium cellulovorans 743B and Rhodopseudomonaspalustris CGA009 in a cellulose-grown coculture for enhanced hydrogenproduction. Appl Environ Microbiol 82:4546 – 4559. doi:10.1128/AEM.00789-16.

Editor: H. Nojiri, The University of Tokyo

Address correspondence to Patrick K. H. Lee, patrick.kh.lee@cityu.edu.hk.

Supplemental material for this article may be found at http://dx.doi.org/10.1128/AEM.00789-16.

Copyright © 2016, American Society for Microbiology. All Rights Reserved.

crossmark

4546 aem.asm.org August 2016 Volume 82 Number 15Applied and Environmental Microbiology

on August 11, 2019 by guest

http://aem.asm

.org/D

ownloaded from

wide molecular responses. Sieuwerts et al. have applied physiolog-ical and transcriptome profiling approaches to a yogurt fermen-tation process of a coculture containing two species of lactic acidbacteria. They have identified the molecular basis of the mutualbeneficial interactions between the bacteria that influenced theirgrowth and fermentation performance (23). Beliaev et al. haveanalyzed the photoautotroph-heterotroph interactions between acyanobacterium and a marine facultative aerobe with transcrip-tome sequencing. Their results have not only provided insightsinto the interactions between cyanobacteria and heterotrophs butalso allowed the formulation of new hypotheses on cyanobacte-rial-heterotrophic interactions (24). Furthermore, Men et al. havecharacterized the interactions of a dechlorinating coculture andtriculture by transcriptome and proteome analyses. The molecu-lar data have revealed the mechanisms of the enhanced dechlori-nation activity observed in the cocultures (3).

In view of the breadth of information that can be gained fromadvanced molecular tools, the combination of physiological char-acterization and gene expression profiling could provide novelinsights into microbial interactions involved in biofuel produc-tion, which could ultimately enhance the yield of biofuels. WhileH2 production from dark-fermentative and photosynthetic bac-teria in cocultures has been intensively investigated in small-scaleexperiments and large-scale reactors (8, 10, 19, 21, 25–27), themolecular mechanisms governing the bacterial dynamics and in-teractions remain unclear. In particular, to the best of our knowl-edge, the use of a high-throughput sequencing (RNA-seq) strategyto query the transcriptomic responses of H2-producing coculturesutilizing cellulose as the sole carbon source has not been previ-ously investigated.

We have previously established and investigated a coculturemodel containing a cellulose-degrading bacterium, Clostridiumcellulovorans 743B, and a photosynthetic bacterium, Rhodopseu-domonas palustris CGA009, for enhanced H2 production (26). Amutant strain of R. palustris with constitutively expressed nitro-genases in the presence of ammonium (NH4

�) (28) is not inves-tigated in the artificial coculture, as our study intends to mimic anatural microbial community. In the cocultures, the physiology(such as H2 yield, cell growth, and extent and rates of transforma-tion of cellulose degradation, production of volatile fatty acids[VFAs], and pH) and the impacts of different cellulose concentra-tions have been characterized to obtain a basic understanding ofthe interactions between the two strains. In the cocultures, signif-icantly higher H2 yield and more-complete cellulose degradationare achieved than in the monocultures. In addition, since the con-sumption of VFAs by R. palustris can help to control pH, lesschemical buffer is required; hence, this coculture strategy has eco-nomic advantages for future large-scale industrial applications.The objective of this study is to further investigate the interactionsbetween these two H2 fermenters at the transcription level. Geneexpression levels of the cocultures and the respective monocul-tures at the early, mid-, and late exponential growth phases wereanalyzed and compared via genome-wide transcriptome sequenc-ing. Furthermore, the transcriptome results were correlated withthe physiological characteristics of the cocultures to achieve amore comprehensive understanding of the microbial interactions.

MATERIALS AND METHODSCulture experimental conditions. Monocultures of C. cellulovorans andof R. palustris were grown with 3 g/liter of cellulose and 20 mM acetate,

respectively, and light in 100 ml of the same defined medium in 160-mlserum bottles as described previously (26). Sodium bicarbonate (30 mM)and N-[Tris(hydroxymethyl)methyl]-2-aminoethanesulfonic acid (10mM) were used as a buffer to maintain the medium pH (initially at pH7.2); however, C. cellulovorans inherently produces VFAs, leading to adrop in pH. Compared to C. cellulovorans monocultures, cocultures ex-hibited a strong buffering capacity due to the VFA consumption by R.palustris. In order to prevent repression of the nitrogenases of R. palustrisby NH4

�, the headspace of the bottles was filled with argon gas, andglutamate instead of NH4

� served as the nitrogen source for both C.cellulovorans and R. palustris (29–31). Cocultures of C. cellulovorans andR. palustris were inoculated at a cell ratio of 1:4 with 3 g/liter of cellulose.All monocultures and cocultures were incubated at 30°C and 100 rpm andunder 6,000 lx of illumination from six 15-W Grolux fluorescent tubes.For both monocultures and cocultures, cellulose was the sole carbon andenergy source for C. cellulovorans. On the other hand, while light was theenergy source for R. palustris in both monocultures and cocultures, vari-ous VFAs produced by C. cellulovorans were the carbon sources for R.palustris in cocultures, whereas acetate was the sole carbon source for R.palustris in monocultures. The design of the cultivation experiments wasto compare C. cellulovorans and R. palustris in cocultures grown with lightand cellulose as the only exogenous substrate with their respective mon-ocultures so that any changes in conditions because of coculturing wouldbe reflected in the transcriptome. Monocultures and cocultures were har-vested for transcriptomic sequencing when cells reached the early, mid-,and late exponential growth phases as determined by the amount of H2

produced via a gas chromatograph equipped with a thermal conductivitydetector as described previously (26). Two identical monocultures or co-cultures were prepared for duplicate transcriptomic analysis at each timepoint. The effect of NH4

� on repressing the nitrogenases of R. palustriswas tested using the culture conditions as described above, except that11.2 mM NH4

� was added to the growth medium of cocultures and mon-ocultures. Triplicate cultures were set up for the experiment. The obtainedphysiological results were compared with data derived from cultureswithout NH4

� (26).RNA extraction and sequencing. Cells were harvested from each du-

plicate culture by centrifugation at 21,100 � g for 3 min at 4°C. The cellpellets were immediately flash frozen in liquid nitrogen and stored at�80°C until further processing within 24 h. Total RNA was extractedusing the RNeasy minikit (Qiagen, California, USA) according to themanufacturer’s protocol with the addition of lysozyme (7.5 mg/ml finalconcentration) for cell lysis. Contaminating DNA was removed by on-column and in-solution DNase digestion with an RNase-free DNase set(Qiagen, California, USA) according to the manufacturer’s instructions.

In order to examine the completeness of DNA removal, total RNA wasfirst reverse transcribed into cDNA using the Superscript III (Invitrogen,California, USA) reverse transcriptase according to the manufacturer’sinstructions. For negative reverse transcriptase controls, diethylpyrocar-bonate (DEPC)-treated water replaced the SuperScript III reverse trans-criptase. The resulting cDNA and the negative controls were used in thesubsequent PCR step for amplifying the cellulase gene of C. cellulovorans(GeneID 9607758) and the 16S rRNA genes of R. palustris (GeneID2690886 and GeneID 2690040) with primers described previously (26).PCR products were visible in the samples with reverse transcriptase whilethe negative reverse transcriptase controls resulted in no band.

The purity and concentration of the total RNA were determined by aNano Drop 2000 spectrophotometer (Thermo Fisher Scientific, Massa-chusetts, USA). For all the samples, the A260/A280 ratios ranged from 2.0 to2.1 and the concentrations were �149 ng/�l. The integrity and quality ofthe total RNA were further assessed on a Bioanalyzer 2100 (Agilent, Cal-ifornia, USA) with the Agilent RNA 6000 Pico kit (Agilent, California,USA) according to the manufacturer’s instructions, and only sampleswith an RNA integrity number (RIN) of �7.8 were selected for sequenc-ing. The average RIN for all the samples was 9.0. Total RNA was depletedof rRNA using the Ribo-Zero rRNA removal Gram-negative bacteria kit

Transcriptome of Dark- and Photofermented H2 Cocultures

August 2016 Volume 82 Number 15 aem.asm.org 4547Applied and Environmental Microbiology

on August 11, 2019 by guest

http://aem.asm

.org/D

ownloaded from

(Epicentre, Wisconsin, USA). A total of 18 samples were submitted to thesequencing facility (BGI Tech Solutions, Hong Kong) for library con-struction and sequencing. Libraries were sequenced on a HiSeq 2000 plat-form (Illumina, California, USA) to yield 91 paired-end reads.

RNA-sequencing data analysis. In order to obtain high-quality readsfor downstream analyses, reads with adaptor sequence, reads with un-known bases representing greater than 10% of a read, and low-qualityreads (i.e., for which the percentage of low-quality bases was greater than50% of a read) were removed. The retained high-quality data for eachmonoculture and coculture sample were �0.55 Gb and �1.1 Gb, respec-tively. High-quality reads were mapped to the genomes of C. cellulovorans(GenBank accession no. NC_014393.1) and R. palustris (GenBank acces-sion no. NC_005296.1) using the SOAP aligner (32). By not allowingmore than two mismatches in the alignment, the average percentage oftotal reads mapped to the reference genomes for all the samples is 97.0%.

Normalization of the RNA-sequencing data was conducted using thereads per kilobase per million (RPKM) calculation (33). The transcriptiondata were analyzed using the nonparametric NOIseq method (34) to iden-tify differentially expressed genes (DEGs). Specifically, a q value (differ-ential expression probability) of �0.8 (34) and the absolute value of log2

(coculture/monoculture) of �1 were used as thresholds to identify genesthat exhibited significant differences in expression between coculturesand monocultures at each growth phase. Throughout this study, upregu-lation refers to a higher relative molar concentration of transcripts of aparticular gene of C. cellulovorans or R. palustris detected in coculturesrelative to the respective monocultures, and downregulation refers to alower relative molar concentration of transcripts detected in cocultures.In addition, a positive expression ratio represents upregulation, and anegative one represents downregulation. The genes of C. cellulovorans aredesignated “Clocel,” and those of R. palustris are “RPA.”

In order to determine the main biological functions that the DEGsrepresent, all DEGs were subjected to Gene Ontology (GO) (35) func-tional annotation by using Blast2GO (36) to determine GO terms. Inaddition, GO functional classification and plotting of DEGs were per-formed by using WEGO (37) to understand the distribution of gene func-tions from the macro level (see Fig. S1 and S2 in the supplemental mate-rial). DEGs were annotated across the GO subcategories and grouped bybiological process, cellular component, or molecular function. Further-more, in order to identify significantly enriched metabolic pathways andsignal transduction pathways related to the identified DEGs, Kyoto Ency-clopedia of Genes and Genomes (KEGG) (38) annotation was also per-formed using Blast2GO. In order to gain an overview of the completemetabolism in the interactions, KEGG-based maps were generated. Firstof all, the key pathways were identified based on the DEGs. Once the keypathways were identified, all of the DEGs in the same pathway were eval-uated to determine whether they were upregulated or downregulated rel-ative to the monocultures. If �50% of the DEGs in the pathway possessedthe same trend, then the pathway would be designated upregulated ordownregulated according to the majority. The cellular pathways are dis-played using the iPath 2.0 platform (39). Heat maps were generated usingthe “ggplot2” package in R for comparing the expression level of genesacross different growth phases (40).

RT-qPCR. In order to verify the RNA-sequencing results, 16 differen-tially expressed genes (Table 1) spanning a range of expression levels at themid-exponential growth phase were selected and analyzed by reversetranscription-quantitative PCR (RT-qPCR) using specific primers de-signed by using Primer Express 3.0 (Applied Biosystems, California,USA). Total RNA from two biological replicates of cocultures and mon-ocultures was reverse transcribed into cDNA using SuperScript III (Invit-rogen, California, USA) according to the manufacturer’s instructions.Amplification of the synthesized cDNA (two technical replicates per bio-logical replicate) was performed with a StepOne Plus real-time PCR sys-tem (Applied Biosystems, California, USA) using the PowerUp SYBRgreen master mix (Applied Biosystems, California, USA) according to themanufacturer’s instructions and the default thermal-cycling conditions.

Comparative threshold (CT) differences between cocultures and mon-ocultures were calculated from averages of quadruplicate samples. Thefold difference for each target gene was calculated using the 2���CT

method (41).Accession number(s). All RNA-sequencing data have been deposited

in the NCBI Sequence Read Archive (SRA) (BioProject accession numberPRJNA280696).

RESULTS AND DISCUSSIONValidation of transcriptome sequencing results. To validate thetranscriptome sequencing results, RT-qPCR was used to quantifychanges in the transcript levels of selected C. cellulovorans and R.palustris genes (Table 1) between the cocultures and monocultures.The transcriptome sequencing and RT-qPCR results for the 16 testedgenes (eight each for C. cellulovorans and R. palustris) were stronglycorrelated (R2 0.88; slope 0.93), and the expected trend in geneexpression was obtained (see Fig. S3 in the supplemental material).This indicates that the transcriptome sequencing results can be reli-ably used to infer the metabolism in the cocultures.

Overview of the transcriptome. In order to understand themolecular responses of C. cellulovorans and R. palustris in cocul-tures, the transcriptomes of cells at the early, mid-, and late expo-

TABLE 1 Primer sequences for RT-qPCR validation against RNA-seqresults

Gene category andprimer Sequence (5= to 3=)Upregulated

Clocel 1529-F AAAGGAGGAAGGAAAAAATGTGAAClocel 1529-R GAGAGCCAGAACCAGCAAAATTClocel 3111-F ATGCCAACTGACCCAGCAAClocel 3111-R TCTTCAGCTGTTCCCCAGGTAClocel 4138-F CTCCTGTAGACAAGATAGTGGAAGAAACClocel 4138-R GCCTCAGGACTTGGTGCATTClocel 2295-F AGAACTCGCGAACAGGTCCTTClocel 2295-R AAGCCTTAAAGTGGTCGCTAACARPA 4628-F GGGCGACTACAAGCTGTTTCTGRPA 4628-R TCGGATCGTGGAACATGAAGRPA 4209-F GCGGCAAGGAGTATTTCGAARPA 4209-R AGGACCATACACCGCGATGTRPA 4784-F TTACGTGTTCCGAGCCTACAAGRPA 4784-R ACGCTCGCTTTGAGGTTGTCRPA 4618-F CCGAACGAGTCGATCAACTTCRPA 4618-R GTGTAATCGACGCCCATCAGTRPA 1435-F GCGACTTCGTCAAGCATTTCTRPA 1435-R TCTCGATCTCGAACAACACGTTRPA 0275-F CCTGCATTATTTGGGCTCTGTACRPA 0275-R GCGCAGAAGGTCATCTGGAA

DownregulatedClocel 0527-F CACTGTCCATTCCCATTTATACATGClocel 0527-R CCCATTCCAGCTTCAATAGCTTClocel 3433-F ATTGCTGCAACTACCGTTGAAGClocel 3433-R AGTCGTGCTTTGGGCCTGTAClocel 3475-F GTGCCGGGTTTGTACCAGATClocel 3475-R CTCCTGATGAAATTCCGACCAAClocel 4097-F ATCGGCGGAAGTGAGTATAACGTClocel 4097-R AGGTTGACCTCCTCCGTTCARPA 0137-F AGCTGCGTCGTATTCGGTATGRPA 0137-R GGTTCAGCGACACAACCTTCTCRPA 1259-F TGCAGAGCTACGGACCCAATRPA 1259-R AGCAGGAAGTAGATCAGCGTGTT

Lu et al.

4548 aem.asm.org August 2016 Volume 82 Number 15Applied and Environmental Microbiology

on August 11, 2019 by guest

http://aem.asm

.org/D

ownloaded from

nential growth phases were examined and compared with those ofthe respective monocultures. For C. cellulovorans, a total of 73,134, and 146 genes (Fig. 1; see also Table S1 in the supplementalmaterial) were differentially expressed at the early, mid-, and lateexponential growth phases, respectively. Specifically, 33 and 40genes at the early exponential growth phase, 58 and 76 genes at themid-exponential growth phase, and 65 and 81 genes at the lateexponential growth phase were up- and downregulated, respec-tively, with �2-fold changes. On the other hand, for R. palustris, atotal of 155, 421, and 1,116 genes (Fig. 1; see also Table S2 in thesupplemental material) were differentially expressed at the early,mid-, and late exponential growth phases, respectively. Specifi-cally, 93 and 62 genes at the early exponential growth phase, 204and 217 genes at the mid-exponential growth phase, and 290 and826 genes at the late exponential growth phase were up- anddownregulated, respectively, with �2-fold changes. Notably, thenumber of downregulated R. palustris genes at the late exponentialgrowth phase was significantly greater than the number of up-regulated genes. This might be due to the fact that the pH ofcocultures at the late exponential growth phase (Fig. 2a) was sig-nificantly lower than the constant neutral pH in R. palustris mon-

FIG 1 Number of differentially expressed genes (DEGs) at the early, mid-, andlate exponential growth phases when comparing C. cellulovorans (CC) or R.palustris (RP) in cocultures (Co) with their respective monocultures.

FIG 2 Comparison of pH (a), H2 production (b), cellulose degradation (c), and VFA concentrations (d) for cocultures (Co) and monocultures of C. cellulovorans(CC) at a cellulose concentration of 3 g/liter. HAc, acetic acid; HBu, butyric acid; FA, formic acid; LA, lactic acid. Each data point is an average of biologicaltriplicate results, and error bars represent 1 standard deviation. (Modified from reference 26 with permission from Elsevier.)

Transcriptome of Dark- and Photofermented H2 Cocultures

August 2016 Volume 82 Number 15 aem.asm.org 4549Applied and Environmental Microbiology

on August 11, 2019 by guest

http://aem.asm

.org/D

ownloaded from

ocultures. The acidic pH likely inhibited cellular metabolism,which resulted in a cell-wide downregulation of transcription. TheDEGs of C. cellulovorans represent 1.7% to 3.5% of the 4,220 totalpredicted protein-encoding genes in its genome, while the DEGsof R. palustris represent 3.2% to 23% of the 4,836 predicted pro-tein-encoding genes in its genome.

In order to obtain an overview on how cells responded to coc-ultivation, the identified DEGs were classified according to GeneOntology (GO) terms (see Fig. S1 and S2 in the supplementalmaterial). For both C. cellulovorans and R. palustris, the categoryof “biological process” was the most enriched, containing bothup- and downregulated genes of the transcriptome from all threegrowth phases. Furthermore, the identified DEGs were mapped tothe corresponding metabolic pathways to highlight the key cellu-lar metabolism (see Fig. S4 and S5 in the supplemental material).In general, the DEGs were distributed in a number of differentpathways in C. cellulovorans and R. palustris.

According to our previous physiological study (26), the mid-exponential growth phase is most representative of the character-istics of the interactions between C. cellulovorans and R. palustris(Fig. 2). Hence, analysis of the interactions at the molecular levelhere focused mainly on the transcriptomic responses at the mid-exponential growth phase. Genes and pathways that are associatedwith important cellular metabolic processes and deemed statisti-cally significant are highlighted and discussed in the followingsections.

H2 production. From our previous study (26), cocultures of C.cellulovorans and R. palustris exhibited enhanced H2 productioncompared to the monocultures of C. cellulovorans (Fig. 2b). Pyru-vate:ferredoxin oxidoreductase and hydrogenase are known toplay critical roles in catalyzing H2 evolution during dark fermen-tation by C. cellulovorans. In the dark fermentation, pyruvate isoxidized to acetyl-coenzyme A (acetyl-CoA) by ferredoxin oxi-doreductase and simultaneously electrons are donated to convertthe oxidized ferredoxin to its reduced form. Subsequently, thereduced ferredoxin is oxidized by hydrogenase to generate H2 byusing protons as terminal electron acceptors (42). In this study,coculturing with R. palustris did not lead to an increase in tran-script abundance of genes related to H2 evolution in C. cellulo-vorans. Instead, the transcripts of a pyruvate:ferredoxin oxi-doreductase (Clocel 1684) and a hydrogenase (Clocel 4097) weredownregulated (Table 2).

On the other hand, during photofermentation by R. palustris,H2 evolution is mediated mainly by nitrogenases through nitro-gen fixation. In particular, when R. palustris is grown on poornitrogen sources or under NH4

� deprivation, the proton-reduc-ing activity of nitrogenases can be retained at a high level to ac-tively convert the proton to H2 if provided with sufficient ATP andreducing power (43). In addition to the molybdenum (Mo) cofac-tor nitrogenases (encoded by nif genes), R. palustris also encodestwo alternative functional nitrogenase isozymes: vanadium (V)cofactor (encoded by vnf genes) and iron (Fe) cofactor (encodedby anf genes) nitrogenases. However, reactions involving V and Fenitrogenases theoretically consume more reducing power thanMo nitrogenases, and they have been reported (44, 45) to serve asalternative routes for nitrogen fixation only when Mo is deficientin the environment. Conversely, the synthesis of alternative nitro-genases can be repressed by Mo (46). From the transcriptome, thenitrogenase genes of R. palustris were upregulated as much as 10-fold in cocultures compared to monocultures. Specifically, 26 of

32 genes in the nif cluster (RPA 4602 to 4633) and 3 of 5 genes inthe anf cluster (RPA 1435 to 1439) were upregulated more than2-fold (Table 3), while no genes in the vnf cluster (RPA 1370 to1380) were differentially expressed. These results are supported bya previous study aiming to understand the regulation of nitroge-nase expression and activity in monocultures of R. palustris. Theirresults demonstrated that R. palustris preferentially expressed Monitrogenase over V and Fe nitrogenases when Mo was present inthe growth medium (44).

Nitrogenase activity not only is an energy-demanding processbut also requires a large amount of reducing power. Accordingly,the ferredoxin (RPA 1927 to 1928) and flavodoxin (RPA 2116 to2117) genes were also upregulated along with the nitrogenasegenes (Table 3), likely to generate more electrons for the nitroge-nases. In addition, the gene encoding a NAD-dependent formatedehydrogenase gamma subunit (RPA 0732) was also upregulatedmore than 2-fold, suggesting that R. palustris is seeking more re-ducing power in cocultures with C. cellulovorans. Furthermore,several genes in the Ntr regulon of R. palustris, such as genes en-coding the glutamine synthetase, glnAII (RPA 4209), and the ni-trogen regulatory protein P-II, glnB (RPA 2966), the glnK2 gene(RPA 0274), and the gene encoding signal transduction histidinekinase, ntrB (RPA 2592), which controls nitrogenase activity (47,48), were all upregulated in the cocultures (Table 3).

Besides upregulation of the nif and anf operons, reductant-encoding genes, and the Ntr regulon, a number of genes that en-code transport systems for nitrogenous compounds were also up-regulated. Transcripts were upregulated for the amtB gene (RPA0275) encoding NH4

� transporters (Table 3). Meanwhile, a gene(RPA 4714) encoding a hypothetical protein for an ABC trans-porter for Mo was upregulated (Table 3), suggesting that Mo istransported to support the synthesis of Mo nitrogenases. Further-more, genes predicted to encode an ABC transporter for nitrate(RPA 2112 to 2114) were all upregulated (Table 3). In the pathwayof assimilatory nitrate reduction, nitrate can be reduced to ammo-nia, which is then incorporated into the amino acids glutamineand glutamate using the glutamine synthetase-glutamate synthase(GS/GOGAT) system. Glutamate and glutamine are the primarynitrogen suppliers for the other nitrogen-containing compoundsin cells, and they serve as the amino donors for nucleic acid andamino acid biosynthesis and other reactions (49). Hence, the in-flux of nitrate and the upregulation of the glutamine synthetase-encoding gene (RPA 4209) suggest that the demand for a nitrogensource is higher for R. palustris in the cocultures.

Overall, the higher transcript levels of the nif and anf operons,reductant-encoding genes, Ntr regulon, and transporter genes forNH4

�, Mo, and nitrate in R. palustris indicate that the presence ofC. cellulovorans had a stimulatory effect on the expression of ni-trogen fixation-related genes. These results, coupled with the ob-servation that the H2 evolution-related genes of C. cellulovoranswere downregulated, suggest that the measured enhanced H2 pro-duction in the cocultures is most likely from R. palustris aloneinstead of C. cellulovorans or both. To further examine whetherthe enhanced H2 production resulted from the activity of nitroge-nases, we tested the effect of adding NH4

� in the growth mediumfor cocultures and monocultures to repress the expression of ni-trogenases. While there was no H2 produced in R. palustris mon-ocultures with NH4

�, the cocultures with NH4� produced 46 ml

of H2, which was 20 ml less than the cocultures without NH4� and

6 ml more than C. cellulovorans monocultures with NH4� (see Fig.

Lu et al.

4550 aem.asm.org August 2016 Volume 82 Number 15Applied and Environmental Microbiology

on August 11, 2019 by guest

http://aem.asm

.org/D

ownloaded from

S6 in the supplemental material). These results further confirmedthat the enhanced H2 production was due mainly to the nitroge-nases activity of R. palustris. Although R. palustris cannot produceH2 in the cocultures with NH4

�, it enhanced the buffering capac-ity by consuming some of the VFAs, which stabilized the pH andin turn allowed C. cellulovorans to consume extra cellulose foradditional H2 production (see Fig. S7 in the supplemental mate-rial).

Cellulose degradation. Aside from enhanced H2 production,cocultures were also associated with more-complete cellulose deg-radation (Fig. 2c). Clostridium species are capable of producingcellulosomes, which are multienzyme complexes for efficient deg-radation of polysaccharides (e.g., cellulose and xylan). In the ge-

nome of C. cellulovorans, a total of 57 cellulosomal genes are pres-ent (50), including 53 dockerin-containing proteins and fourcohesin-containing scaffolding proteins. Of all the cellulosomalgenes, 29 are predicted to encode enzymes with cellulolytic, hemi-cellulolytic, and pectin-degrading functions. In this study, two C.cellulovorans cellulase genes (Clocel 3111 and Clocel 3359) encod-ing family 5 glycosyl hydrolases (GHs) were upregulated in thecocultures (Table 2), suggesting that cellulolytic activity was en-hanced in the presence of R. palustris. Furthermore, one C. cellu-lovorans xylanase gene (Clocel 2295) encoding family 11 GH wasalso upregulated in response to cocultivation with R. palustris (Ta-ble 2), suggesting that cellulase and hemicellulase might share aregulatory mechanism that can be induced by the presence of

TABLE 2 Selected differentially expressed genes of C. cellulovorans grouped into functional categories in response to cocultivation with R. palustrisat mid-exponential growth phase

Functional category and gene ID Description log2 (Coa/C. cellulovorans)

H2 production (2 genes)Clocel 1684 Pyruvate ferredoxin/flavodoxin oxidoreductase �1.3Clocel 4097 Hydrogenase, Fe only �2.3

Cellulose degradation (3 genes)Clocel 3359 Cellulase, glycosyl hydrolase family 5 protein 1.7Clocel 3111 Cellulase, glycosyl hydrolase family 5 protein 2.1Clocel 2295 Xylanase, glycosyl hydrolase family 11 protein 2.5

Fatty acid biosynthesis (3 genes)Clocel 4138 Acetyl-CoA carboxylase, biotin carboxyl carrier protein 2.7Clocel 4144 3-Oxoacyl-(acyl-carrier-protein) synthase III 2.6Clocel 4162 Beta-ketoacyl-ACP synthase 1.4

Sulfur metabolism (10 genes)Clocel 0525 Fumarate reductase/succinate dehydrogenase flavoprotein domain-containing protein �5.2Clocel 0526 4Fe-4S ferredoxin �13.6Clocel 2532 O-acetylhomoserine/O-acetylserine sulfhydrylase �4.8Clocel 0527 Phosphoadenosine phosphosulfate reductase (thioredoxin) �7.3Clocel 0528 Sulfate adenylyltransferase, large subunit �6.0Clocel 3475 Cysteine synthase �5.4Clocel 0521 Sulfate ABC transporter, periplasmic sulfate-binding protein �3.9Clocel 0524 Sulfate ABC transporter ATPase �4.5Clocel 0523 Sulfate ABC transporter, inner membrane subunit CysW �5.5Clocel 0522 Sulfate ABC transporter, inner membrane subunit CysT �5.9

Thiamine metabolism (6 genes)Clocel 2812 Thiamine biosynthesis protein ThiC �1.9Clocel 0684 Thiazole biosynthesis protein ThiH �2.0Clocel 0685 Thiazole biosynthesis family protein �2.2Clocel 0683 Thiamine biosynthesis protein ThiF �2.6Clocel 0682 Thiamine-phosphate pyrophosphorylase �2.9Clocel 3433 Biotin and thiamine synthesis-associated protein �3.1

Nitrogen metabolism (5 genes)Clocel 1684 Pyruvate ferredoxin/flavodoxin oxidoreductase �1.3Clocel 1284 Glu/Leu/Phe/Val dehydrogenase �1.9Clocel 2836 Nitrogenase iron protein 2.0Clocel 2838 NADH dehydrogenase ubiquinone 24-kDa subunit 2.0Clocel 4147 2-Nitropropane dioxygenase 2.1

Molybdate transport (3 genes)Clocel 1529 Molybdenum ABC transporter periplasmic molybdate-binding protein 2.5Clocel 1530 Molybdate ABC transporter inner membrane subunit 2.0Clocel 1531 ABC transporter 2.1

a Co, cocultures of C. cellulovorans and R. palustris.

Transcriptome of Dark- and Photofermented H2 Cocultures

August 2016 Volume 82 Number 15 aem.asm.org 4551Applied and Environmental Microbiology

on August 11, 2019 by guest

http://aem.asm

.org/D

ownloaded from

TABLE 3 Selected differentially expressed genes of R. palustris grouped into functional categories in response to cocultivation with C. cellulovoransat mid-exponential growth phase

Functional category and gene ID Description log2 (Coa/R. palustris)

Nitrogen metabolismnif cluster (26 genes)

RPA 4602 Ferredoxin-like protein FixX 2.5RPA 4603 Electron-transferring-flavoprotein dehydrogenase 1.4RPA 4604 Electron transfer flavoprotein subunit beta 1.2RPA 4606 Nitrogenase-stabilizing/protective protein 1.9RPA 4607 Homocitrate synthase 1.6RPA 4608 Class V aminotransferase 1.3RPA 4611 Nitrogen fixation protein NifQ 2.7RPA 4612 4Fe-4S ferredoxin 3.2RPA 4613 Hypothetical protein 2.0RPA 4614 Hypothetical protein 1.8RPA 4615 Dinitrogenase iron-molybdenum cofactor biosynthesis 2.2RPA 4616 Nitrogenase molybdenum-cofactor biosynthesis protein NifN 1.8RPA 4617 Nitrogenase molybdenum-cofactor biosynthesis protein NifE 1.8RPA 4618 Nitrogenase molybdenum-iron protein subunit beta 1.8RPA 4619 Nitrogenase molybdenum-iron protein subunit alpha 1.6RPA 4620 Nitrogenase reductase 1.3RPA 4621 Hypothetical protein 1.8RPA 4622 Hypothetical protein 2.1RPA 4623 Hypothetical protein 1.7RPA 4624 Hypothetical protein 2.6RPA 4625 Nitrogen fixation protein NifZ 2.2RPA 4626 Hypothetical protein 2.1RPA 4627 Hypothetical protein 1.7RPA 4628 HesB/YadR/YfhF 1.5RPA 4629 4Fe-4S ferredoxin 2.0RPA 4631 4Fe-4S ferredoxin 1.1

anf cluster (3 genes)RPA 1435 Alternative nitrogenase 3 subunit beta 2.8RPA 1437 Nitrogenase molybdenum-iron protein subunit alpha 2.1RPA 1438 Nitrogenase reductase 3.3

Reductant-encoding genes (5 genes)RPA 1927 Hypothetical protein 1.4RPA 1928 Ferredoxin 1.3RPA 2116 Hypothetical protein 1.6RPA 2117 Flavodoxin FldA 1.4RPA 0732 Formate dehydrogenase subunit gamma 1.3

Ntr regulon (4 genes)RPA 4209 Glutamine synthetase 1.4RPA 2966 Nitrogen regulatory protein P-II 1.4RPA 0274 GlnK nitrogen regulatory protein P-II 1.7RPA 2592 Signal transduction histidine kinase, nitrogen specific, NtrB 1.1

Transporters (5 genes)RPA 0275 Ammonium transporter 1.5RPA 4714 Hypothetical protein 1.6RPA 2112 Nitrate transporter component NrtA 2.7RPA 2113 Nitrate transport system permease 2.6RPA 2114 Nitrate transport system ATP-binding protein 3.0

Organic compound catabolismRPA 2940 NADH dehydrogenase subunit K 1.3

Bacterial chemotaxis (18 genes)RPA 0137 Chemotaxis methylesterase CheB1 1.2RPA 4784 OmpA/MotB domain-containing protein �1.3RPA 1884 Methyl-accepting chemotaxis receptor/sensory transducer 1.2

(Continued on following page)

Lu et al.

4552 aem.asm.org August 2016 Volume 82 Number 15Applied and Environmental Microbiology

on August 11, 2019 by guest

http://aem.asm

.org/D

ownloaded from

cellulose. The coordinated expression of both cellulase and hemi-cellulase genes has previously been reported when C. cellulovoranswas cultivated with cellulose as the carbon source in monoculture(51). The upregulation of a number of cellulosomal genes is con-sistent with the physiological characterization whereby enhancedcellulolytic activity was observed in cocultures (Fig. 2c). The en-hanced cellulose degradation is attributed to the consumption ofVFAs by R. palustris, which in turn stabilizes the pH of cocultures,in contrast to the more-acidic pH in the monocultures (Fig. 2a).Acidic pH likely negatively influences the expression of cellulo-somal genes in monocultures of C. cellulovorans, as it has previ-ously been shown that cellobiose and cellulose degradation wasinhibited in the cellulolytic ruminal bacterium Bacteroides succi-nogenes under low pH (52).

Fatty acid metabolism. The fermentative metabolites of C. cel-lulovorans are H2, carbon dioxide, ethanol, and VFAs, includingformate, acetate, butyrate, and lactate (50). In the cocultures, fattyacid biosynthesis of C. cellulovorans is critical to R. palustris since itis obligately dependent on the VFAs from C. cellulovorans as elec-tron donors and carbon sources for growth. During dark fermen-tation by C. cellulovorans, acetyl-CoA carboxylase is the essentialenzyme that functions in the first committed step of fatty acidbiosynthesis (53). Acetyl-CoA carboxylase comprises two car-boxyl transferase subunits, as well as biotin carboxylase and biotincarboxyl carrier protein (BCCP). Together, these four compo-nents of acetyl-CoA carboxylase are encoded by Clocel 4134 to4136 and Clocel 4138, respectively. In the acetyl-CoA carboxylase

reaction, biotin is first coupled to BCCP. Following that, the biotincarboxylase catalyzes the Mn-ATP-dependent carboxylation ofbiotin to generate CO2

�-BCCP. Subsequently, the transcarboxy-lase transfers the carboxyl group from the biotin moiety of BCCPto acetyl-CoA to form malonyl-CoA, the precursor to all the elon-gation steps of fatty acid biosynthesis (53). In the cocultures, thegene (Clocel 4138) encoding BCCP in C. cellulovorans was up-regulated (Table 2). Although the other three acetyl-CoA carbox-ylase-encoding genes were not statistically classified as differen-tially expressed, they were all consistently upregulated.

Moreover, the beta-ketoacyl-acyl-carrier-protein (ACP) syn-thase and the 3-oxoacyl-ACP synthase III are the key enzymesinvolved in the initiation of fatty acid biosynthesis. They conductthe condensation of acetyl-CoA with malonyl-ACP to supply theintermediates of short-chain fatty acids (54, 55). In the cocultures,the beta-ketoacyl-ACP synthase gene (Clocel 4162) and 3-oxoacyl-ACP synthase III gene (Clocel 4144) of C. cellulovoranswere both upregulated (Table 2). The upregulation of the fattyacid biosynthesis-related genes suggests that C. cellulovorans wasattempting to synthesize more VFAs when R. palustris was present(Fig. 2d). This could be due to the consumption of VFAs by R.palustris, which prompted further VFA production. The genomeof R. palustris encodes two homologues of NADH dehydrogenasecomplexes (RPA 2937 to 2952 and RPA 4252 to 4264), whichmediate the catabolism of organic compounds (e.g., fatty acids,dicarboxylic acid, and lignin monomers) (56). In R. palustris, thegene nuoK1 (RPA 2940) encoding NADH dehydrogenase subunit

TABLE 3 (Continued)

Functional category and gene ID Description log2 (Coa/R. palustris)

RPA 0999 Hypothetical protein �2.1RPA 4639 Methyl-accepting chemotaxis receptor/sensory transducer 1.1RPA 1678 Chemotaxis methyltransferase CheR3 1.2RPA 3709 Hemoprotein 2.2RPA 1267 Flagellar motor switch protein 1.1RPA 4481 Methyl-accepting chemotaxis sensory transducer 1.1RPA 0139 Methyl-accepting chemotaxis receptor/sensory transducer 1.4RPA 3751 Hypothetical protein 1.1RPA 3185 Methyl-accepting chemotaxis receptor/sensory transducer 1.4RPA 3750 Methyl-accepting chemotaxis sensory transducer 1.4RPA 0138 Chemotaxis methyltransferase CheR1 1.3RPA 4531 Histidinol dehydrogenase �1.1RPA 0140 Chemotaxis signal transduction/oligomerization protein CheW1-2 1.1RPA 1774 Porin 1.7RPA 0141 Chemotaxis signal transduction/oligomerization protein CheW1-1 1.4

Photosynthesispuc operon (8 genes)

RPA 2653 Light harvesting protein b-800-850 alpha subunit A 3.0RPA 2654 Light harvesting protein b-800-850 beta subunit A 2.5RPA 3009 Light harvesting protein b-800-850 beta subunit C 1.8RPA 3010 Pseudo 2.0RPA 1491 Light harvesting protein b-800-850 beta subunit E 2.1RPA 1492 Light harvesting protein b-800-850 alpha subunit E 1.9RPA 4291 Light harvesting protein b-800-850 beta subunit B 2.3RPA 4292 Light harvesting protein b-800-850 alpha subunit B 1.9

puf operon (3 genes)RPA 1525 Antenna complex alpha/beta subunit 2.2RPA 1526 Light-harvesting complex 1 subunit alpha 1.5RPA 1527 Photosynthetic reaction center subunit l 1.2

a Co, cocultures of C. cellulovorans and R. palustris.

Transcriptome of Dark- and Photofermented H2 Cocultures

August 2016 Volume 82 Number 15 aem.asm.org 4553Applied and Environmental Microbiology

on August 11, 2019 by guest

http://aem.asm

.org/D

ownloaded from

K was upregulated (Table 3), suggesting that the VFA catabolismof R. palustris in the cocultures was more active than in the mon-ocultures. This is probably due to the fact that multiple VFAsproduced by C. cellulovorans were utilized as the carbon substratesand electron donors for R. palustris, while there was only acetate inthe monocultures of R. palustris.

Bacterial chemotaxis. As a motile bacterium with flagella, R.palustris is able to perform chemotaxis. In general, most bacteriaare too small to accurately measure the chemoeffector gradientbetween the ends of the cell. Therefore, bacteria measure changesin chemoeffector concentrations over time rather than detectingthe spatial gradient within the bacterium itself (57). On the otherhand, although C. cellulovorans also has peritrichous flagella (58),they are nonmotile. In contrast to R. palustris monocultures,where acetate was initially amended at a relatively high concentra-tion (20 mM), the VFA concentrations in the cocultures began atzero and increased over time as a result of the continuous VFAsynthesis by C. cellulovorans during dark fermentation (Fig. 2d).Although it was previously reported that permeant acids such asacetate and benzoate act as repellents and elicit negative che-motaxis (59) in Escherichia coli K-12, another study has demon-strated that Rhodobacter sphaeroides, a nonenteric bacterial modelfor the chemotaxis pathways, is chemotactic to organic acids suchas succinate, pyruvate, propionate, and acetate (60). Since VFAsare the carbon sources for R. palustris, a logical assumption is thatR. palustris might move toward VFAs, which is favorable for thegrowth of R. palustris. Interestingly, this assumption seems to besupported by the transcriptome results of R. palustris in the cocul-tures.

The genome of R. palustris contains the essential proteins re-quired for chemotaxis. In the chemotaxis process, the periplasmicconcentrations of chemoeffectors are first sensed by the trans-membrane sensor proteins, which are usually referred to as themethyl-accepting chemotaxis proteins (MCPs). The MCPs theninteract with the cytoplasmic signaling proteins (CheW andCheA), resulting in a change in the rate of autophosphorylation ofCheA. Subsequently, the phosphoryl group from the phosphory-lated CheA is transferred to the response regulator proteins (CheYand CheB). At the end, the phosphorylated CheY in turn interactswith the flagellar motor switch protein (FliM, FliN, FliG) to in-duce cell movement. Furthermore, CheR is a methyltransferaseresponsible for the methylation of MCPs, which plays a crucialrole in modulating the adaptation to chemoeffectors. In the co-cultures, genes predicted to encode MCPs CheW, CheB, CheR,CheY, and FliN were all upregulated at least 2-fold (Table 3),suggesting that the chemotaxis response of R. palustris is elicitedduring cocultivation with C. cellulovorans, or more likely, movingtoward the VFAs produced by C. cellulovorans.

Sulfur metabolism. In response to cocultivation with R. palus-tris, a number of C. cellulovorans genes responsible for assimilativesulfur metabolism were downregulated (Table 2). In particular,several genes related to sulfate reduction and conversion of intra-cellular sulfate to cysteine were expressed at a significantly lowerlevel. For example, the gene for sulfate adenylyltransferase (Clocel0528), which converts sulfate to adenosine-5=-phosphosulfate(APS) in the first step of assimilatory sulfate reduction, was down-regulated nearly 60-fold. Also, the gene for thioredoxin (Clocel0527), which reduces the phosphoadenosine phosphosulfate(PAPS) to sulfite, was significantly downregulated more than 162-fold. In addition, the gene for cysteine synthase (Clocel 3475),

which synthesizes cysteine from O-acetylserine and sulfide, wasdownregulated more than 41-fold. Previous studies have shownthat the gene expression of cysteine synthase is a general stressresponse to tellurite, hydrogen peroxide, acid, and diamide (61,62). Corresponding with the downregulation of sulfate reductiongenes, genes predicted to encode an ABC transporter for sulfate(Clocel 0521 to 0524) were also downregulated (Table 2).

The downregulation of the genes related to sulfate transportand reduction in the cocultures is physiologically interesting, asthe final product of the sulfate reduction pathway is cysteine, anessential amino acid that plays a vital role in the catalytic activityand stress responses. In particular, cysteine is known as a source ofsulfur required to repair oxidatively damaged iron-sulfur clusterproteins with essential roles in metabolism (63). Specifically, thecysteine-containing molecules glutathione and thioredoxin areknown to play a protective role in maintaining an intracellularreducing environment in response to oxidative stress (64). Thehigher expression level of sulfate reduction in the C. cellulovoransmonocultures (i.e., downregulation in cocultures) seems to sug-gest an enhanced cellular demand for cysteine, which might be adirect response to oxidative stress. However, here both the cocul-ture and monoculture experiments were conducted under anaer-obic conditions. It is unlikely that the assumed oxidative stress wascaused by oxygen. Previous studies have reported that acid cancause an imbalance in the thiol redox status of the cytoplasm, andresponses to stresses such as oxidative stress, heat shock, and en-velope stress have been shown to be strongly connected with pHstress and pH resistance in some bacteria (62, 65). Therefore, thegene expression of sulfate transport and reduction could be linkedto pH changes.

As opposed to a more stabilized pH as the VFAs were con-sumed by R. palustris in the cocultures, the pH of C. cellulovoransmonocultures was increasingly becoming more acidic as VFAsaccumulated during dark fermentation (Fig. 2a). Our data showthat most of the sulfate transport and reduction genes of C. cellu-lovorans in the cocultures were becoming more downregulatedover time from the early to late exponential phases (Fig. 3), whenthe pH of C. cellulovorans monocultures was becoming moreacidic, while the pH of cocultures changed more slowly. Coinci-dentally, acetate stress has previously been shown to result in up-regulation of genes related to the uptake and conversion of sulfateto cysteine in Clostridium acetobutylicum, although the oppositedownregulation was observed upon butyrate stress (66). Further-more, a previous study carried out with Shewanella oneidensis hasalso shown that genes involved with sulfate transport and assimi-lative sulfur metabolism were induced upon pH stress (alkaline)(67). Although further investigations are required to fully appre-ciate the exact physiological role of cysteine under conditions ofpH stress, our results suggest that the synthesis of cysteine mightbe physiologically important for C. cellulovorans to protect againstacid stress and the expression of related genes might be a stressresponse to maintain cellular metabolism.

Thiamine metabolism. The downregulation of C. cellulo-vorans genes related to the thiamine metabolism pathway was alsoobserved in response to cocultivation with R. palustris (Table 2).These genes include those encoding thiamine-phosphate pyro-phosphorylase (Clocel 0682), biotin and thiamine synthesis-asso-ciated protein (Clocel 3433), thiamine biosynthesis proteins ThiCand ThiF (Clocel 2812 and Clocel 0683), and thiazole synthaseThiH and ThiG (Clocel 0684 and Clocel 0685), which catalyze the

Lu et al.

4554 aem.asm.org August 2016 Volume 82 Number 15Applied and Environmental Microbiology

on August 11, 2019 by guest

http://aem.asm

.org/D

ownloaded from

formation of 5-(2-hydroxyethyl)-4-methylthiazole, the precursorto the condensation of thiamine monophosphate. The down-regulation of these genes likely influences the biosynthesis ofthe final products of thiamine metabolism, namely, thiamineand its active form, thiamine pyrophosphate (TPP). The phys-iological role of TPP has been well characterized as the univer-sal cofactor for enzymes engaged in crucial metabolic path-ways, such as transketolase, involved in the pentose phosphatepathway, and pyruvate:ferredoxin oxidoreductase, requiredfor the interconversion of pyruvate and acetyl-CoA in the py-ruvate metabolism pathway. Notably, the C. cellulovorans genes(Clocel 1257 and Clocel 1684) annotated to encode these twoTPP-dependent enzymes were both downregulated in response tococultivation with R. palustris.

In addition, studies have shown that thiamine metabolismmight play a protective role in defending the cell against ad-verse conditions. It has been reported that thiamine com-pounds accumulated in response to amino acid starvation andenergy stress conditions in E. coli (68). Also, a recent study (69)carried out with Saccharomyces cerevisiae showed that genes re-lated to TPP biosynthesis were significantly upregulated andthe corresponding enzymatic activity levels increased in re-sponse to oxidative and osmotic stresses, indicating that thia-mine metabolism can partly compensate for damages of theyeast general defense systems. Surprisingly, similar to what isobserved with the sulfate transport and reduction genes, astrong correlation of thiamine metabolism gene expressionwith pH was also observed for C. cellulovorans (Fig. 4). From theearly to late exponential phases, the expression level of a numberof the thiamine metabolism genes of C. cellulovorans (10 of 22)decreased over time in cocultures (Fig. 4). The downregulation ofthiamine metabolism genes in the cocultures reflects the increasedtranscriptional level of thiamine metabolism genes in C. cellulo-vorans monocultures, indicating that an enhanced thiamineand TPP biosynthesis was elicited in response to acidic pH.

Although the gene expression of thiamine metabolism seems tobe an oxidative stress response, it might be induced by acidicpH as well. These results again suggest that R. palustris in thecocultures can play an important role in mitigating the pH-in-duced oxidative stress response.

Photosynthesis. Under anaerobic conditions, R. palustris iscapable of conserving energy from light via photosynthesis usingits photosystem. From an energetic point of view, the photosystemis extremely important because it carries out the main photo-chemical reactions within a cell, including light absorption andenergy and electron transfer. The structure of a photosystem iscomprised of two light-harvesting complexes, I and II (encoded bythe puc and puf operons, respectively), and the reaction center(encoded by the puh operon) (70). In response to cocultivationwith C. cellulovorans, 11 of 14 genes in the puc, puf, and puh oper-ons in R. palustris were upregulated more than 2-fold (Table 3).Although the upregulations of two puc operon genes (RPA 3012 to3013) and a puh operon gene (RPA 1548) were below 2-fold, thesethree genes were still upregulated more than 1.7-fold. The over-expression of these photosystem-encoding genes strongly indi-cates that the photosynthesis of R. palustris was more active in thecocultures than in the monocultures. This most likely reflects theincreased metabolic activity and cellular energy demand of R.palustris in the cocultures. For example, the above-mentioned ni-trogen fixation, carbon assimilation, and chemotaxis are all ener-gy-demanding processes.

Other genes and pathways of significance. In response to coc-ultivation with R. palustris, a number of C. cellulovorans genesresponsible for nitrogen metabolism were upregulated (Table 2).For example, the ABC transporters genes for Mo (Clocel 1529 to1531) were upregulated (Table 2). The upregulation of a few ni-trogen metabolism and related genes (Clocel 2836, Clocel 2838,and Clocel 4147) suggests that nitrogen demand was enhanced forC. cellulovorans in cocultures, possibly due to the increased overallmetabolic level of C. cellulovorans triggered by the presence of R.

FIG 3 (a) Upregulated (red) and downregulated (blue) expression profiles of C. cellulovorans genes related to sulfate transport and reduction at the early, mid-,and late exponential growth phases in response to cocultivation with R. palustris. DEGs (genes differentially expressed at any time point) are marked with anasterisk (*). (b) The genes indicated in panel a are shown in the corresponding metabolic pathways. APS, adenosine-5=-phosphosulfate; PAPS, phosphoadenosinephosphosulfate. A question mark (?) indicates that the gene has not been annotated in the C. cellulovorans genome.

Transcriptome of Dark- and Photofermented H2 Cocultures

August 2016 Volume 82 Number 15 aem.asm.org 4555Applied and Environmental Microbiology

on August 11, 2019 by guest

http://aem.asm

.org/D

ownloaded from

palustris. In our previous physiological study (26), cocultivationwith R. palustris did not result in significant differences in celldensity for C. cellulovorans relative to the monocultures. Consis-tent with this observation, none of the C. cellulovorans genes re-lated to cell division were differentially expressed in the cocul-tures. Similarly, the R. palustris genes responsible for cell divisionwere also not differentially expressed. In addition, a number of R.palustris genes exhibited downregulation in response to cocultiva-tion with C. cellulovorans. For example, genes related to nicotinateand nicotinamide metabolism, alanine, aspartate, and glutamatemetabolism, and RNA degradation were downregulated.

In summary, a number of physiological studies of H2-produc-ing cocultures (18–21, 26) incorporating dark-fermentative andphotosynthetic bacteria have shown that H2 yield and substrateutilization are enhanced during coculturing. However, the de-tailed molecular mechanisms of how each organism in the cocul-ture responds to the presence of the culturing partner and thechanging culturing conditions (e.g., pH) remain unclear. In orderto further understand the interactions in an H2-producing cocul-ture, we report a transcriptomic analysis of the H2-producing co-culture of C. cellulovorans and R. palustris utilizing cellulose as thesole carbon substrate in this study. By correlating the transcrip-tomic data to the physiological characteristics of the cocultures, aconceptual model that summarizes the key differentially regulatedresponses in both strains was developed and is illustrated in Fig. 5.In this coculture model, three cellulosomal genes of C. cellulo-vorans were upregulated, indicating enhanced cellulolytic activityin response to cocultivation with R. palustris. Meanwhile, genesinvolved in nitrogen metabolism and fatty acid biosynthesis in C.cellulovorans were also upregulated in the cocultures. The upregu-lation of fatty acid biosynthesis in C. cellulovorans is likely to in-crease VFA production, which could be further utilized by R.

palustris as the carbon source for growth. Accordingly, a geneinvolved in VFA consumption in R. palustris was also upregulated.As the VFAs were consumed by R. palustris, the pH in cocultureswas stabilized in comparison to the acidic pH in C. cellulovoransmonocultures. Surprisingly, a strong correlation of sulfur and thi-amine metabolism gene expression with pH was observed for C.cellulovorans, in which these genes were downregulated in the co-cultures, which suggests that they function as a stress responseagainst acidic pH in the monocultures.

In addition, as a motile bacterium, a number of chemotaxisgenes in R. palustris were upregulated, most likely moving to-ward the VFAs produced by C. cellulovorans. Consistent withthe physiological observations of enhanced H2 production,genes related to nitrogen fixation in R. palustris were upregu-lated. These genes include the nif and anf operons, reductant-encoding genes, Ntr regulon, and transporter genes for NH4

�,Mo, and nitrate. However, unexpectedly, genes related to H2

production in C. cellulovorans were downregulated; hence, theenhanced H2 yield most likely was from R. palustris alone insteadof C. cellulovorans or both. Moreover, genes involved in photosyn-thesis in R. palustris were upregulated, reflecting an increased met-abolic activity of R. palustris in the cocultures. The derived con-ceptual model is inferred from results at the transcription levelonly; hence, future studies should also apply high-throughputshotgun proteomics to examine the expressed proteins so thatour understanding of the coculture interactions can be furtherenhanced. Nevertheless, the global transcriptomic analysis inthis study enables a molecular view of the interactions of anH2-producing coculture and provides insights into the ob-served physiological characteristics, which would benefit theengineering of more-effective consortia for H2 production inindustrial processes.

FIG 4 (a) Upregulated (red) and downregulated (blue) expression profiles of C. cellulovorans genes related to thiamine metabolism at the early, mid-, and lateexponential growth phases in response to cocultivation with R. palustris. DEGs (genes differentially expressed at any time point) are marked with an asterisk (*).(b) The genes indicated in panel a are shown in the corresponding metabolic pathways. HET, 5-(2-hydroxyethyl)-4-methylthiazole; HET-P, HET phosphate;HMP, 4-amino-5-hydroxymethyl-2-methylpyrimidine; HMP-P, HMP phosphate; HMP-PP, HMP diphosphate; TMP, thiamine monophosphate; TDP, thia-mine diphosphate; AIR, 1-(5=-phospho-ribosyl)-5-amino-imidazole; COSH, thiocarboxylate. A question mark (?) indicates that the gene has not been annotatedin the R. palustris genome.

Lu et al.

4556 aem.asm.org August 2016 Volume 82 Number 15Applied and Environmental Microbiology

on August 11, 2019 by guest

http://aem.asm

.org/D

ownloaded from

ACKNOWLEDGMENTS

This research was supported by the Research Grants Council of HongKong through projects 116111 and 11206514 and a grant from the AbilityR&D Energy Research Centre.

FUNDING INFORMATIONThis work, including the efforts of Patrick Lee, was funded by Ability R&DEnergy Research Centre (AERC). This work, including the efforts of Pat-rick Lee, was funded by Research Grants Council, University Grants Com-mittee (RGC, UGC) (116111 and 11206514).

REFERENCES1. Faust K, Raes J. 2012. Microbial interactions: from networks to models.

Nat Rev Microbiol 10:538 –550. http://dx.doi.org/10.1038/nrmicro2832.2. He J, Holmes VF, Lee PKH, Alvarez-Cohen L. 2007. Influence of vitamin

B12 and cocultures on the growth of Dehalococcoides isolates in definedmedium. Appl Environ Microbiol 73:2847–2853. http://dx.doi.org/10.1128/AEM.02574-06.

3. Men Y, Feil H, Verberkmoes NC, Shah MB, Johnson DR, Lee PKH,West KA, Zinder SH, Andersen GL, Alvarez-Cohen L. 2012. Sustainablesyntrophic growth of Dehalococcoides ethenogenes strain 195 with Desulfo-vibrio vulgaris Hildenborough and Methanobacterium congolense: globaltranscriptomic and proteomic analyses. ISME J 6:410 – 421. http://dx.doi.org/10.1038/ismej.2011.111.

4. Rossouw D, Du Toit M, Bauer FF. 2012. The impact of co-inoculationwith Oenococcus oeni on the transcriptome of Saccharomyces cerevisiae andon the flavour-active metabolite profiles during fermentation in syntheticmust. Food Microbiol 29:121–131. http://dx.doi.org/10.1016/j.fm.2011.09.006.

5. Maligoy M, Mercade M, Cocaign-Bousquet M, Loubiere P. 2008. Tran-scriptome analysis of Lactococcus lactis in coculture with Saccharomycescerevisiae. Appl Environ Microbiol 74:485– 494. http://dx.doi.org/10.1128/AEM.01531-07.

6. Mendes F, Sieuwerts S, de Hulster E, Almering MJH, Luttik MAH,Pronk JT, Smid EJ, Bron PA, Daran-Lapujade P. 2013. Transcriptome-based characterization of interactions between Saccharomyces cerevisiaeand Lactobacillus delbrueckii subsp. bulgaricus in lactose-grown chemostatcocultures. Appl Environ Microbiol 79:5949 –5961. http://dx.doi.org/10.1128/AEM.01115-13.

7. Cheirsilp B, Shoji H, Shimizu H, Shioya S. 2003. Interactions betweenLactobacillus kefiranofaciens and Saccharomyces cerevisiae in mixed culturefor kefiran production. J Biosci Bioeng 96:279 –284. http://dx.doi.org/10.1016/S1389-1723(03)80194-9.

8. Zhang X, Ye X, Finneran KT, Zilles JL, Morgenroth E. 2013. Interac-tions between Clostridium beijerinckii and Geobacter metallireducens inco-culture fermentation with anthrahydroquinone-2,6-disulfonate(AH2QDS) for enhanced biohydrogen production from xylose. Biotech-nol Bioeng 110:164 –172. http://dx.doi.org/10.1002/bit.24627.

9. Chen Y. 2011. Development and application of co-culture for ethanolproduction by co-fermentation of glucose and xylose: a systematic review.J Ind Microbiol Biotechnol 38:581–597. http://dx.doi.org/10.1007/s10295-010-0894-3.

10. Fang HHP, Zhu H, Zhang T. 2006. Phototrophic hydrogen productionfrom glucose by pure and co-cultures of Clostridium butyricum and Rho-dobacter sphaeroides. Int J Hydrogen Energy 31:2223–2230. http://dx.doi.org/10.1016/j.ijhydene.2006.03.005.

11. Chang JJ, Chou CH, Ho CY, Chen WE, Lay JJ, Huang CC. 2008.Syntrophic co-culture of aerobic Bacillus and anaerobic Clostridium forbio-fuels and bio-hydrogen production. Int J Hydrogen Energy 33:5137–5146. http://dx.doi.org/10.1016/j.ijhydene.2008.05.021.

12. He Q, Hemme CL, Jiang H, He Z, Zhou J. 2011. Mechanisms ofenhanced cellulosic bioethanol fermentation by co-cultivation of Clostrid-ium and Thermoanaerobacter spp. Bioresour Technol 102:9586 –9592.http://dx.doi.org/10.1016/j.biortech.2011.07.098.

13. Alper H, Stephanopoulos G. 2009. Engineering for biofuels: exploitinginnate microbial capacity or importing biosynthetic potential? Nat RevMicrobiol 7:715–723. http://dx.doi.org/10.1038/nrmicro2186.

14. Brenner K, You L, Arnold FH. 2008. Engineering microbial consortia: a

FIG 5 The physiological and transcriptome conceptual model of C. cellulovorans and R. palustris in cocultures. The key differentially regulated genes and theirpathways of interaction are highlighted. The final products of the metabolic pathways are also shown in order to describe the carbon and cellular metabolism inthe coculture model. Red and blue, upregulated and downregulated genes and pathways, respectively. Green, correlations between VFAs, pH, and pathways.

Transcriptome of Dark- and Photofermented H2 Cocultures

August 2016 Volume 82 Number 15 aem.asm.org 4557Applied and Environmental Microbiology

on August 11, 2019 by guest

http://aem.asm

.org/D

ownloaded from

new frontier in synthetic biology. Trends Biotechnol 26:483– 489. http://dx.doi.org/10.1016/j.tibtech.2008.05.004.

15. Xie B, Bishop S, Stessman D, Wright D, Spalding MH, Halverson LJ.2013. Chlamydomonas reinhardtii thermal tolerance enhancement medi-ated by a mutualistic interaction with vitamin B12-producing bacteria.ISME J 7:1544 –1555. http://dx.doi.org/10.1038/ismej.2013.43.

16. Chen CY, Yang MH, Yeh KL, Liu CH, Chang JS. 2008. Biohydrogenproduction using sequential two-stage dark and photo fermentation pro-cesses. Int J Hydrogen Energy 33:4755– 4762. http://dx.doi.org/10.1016/j.ijhydene.2008.06.055.

17. Su H, Cheng J, Zhou J, Song W, Cen K. 2009. Combination of dark- andphoto-fermentation to enhance hydrogen production and energy conver-sion efficiency. Int J Hydrogen Energy 34:8846 – 8853. http://dx.doi.org/10.1016/j.ijhydene.2009.09.001.

18. Liu BF, Ren NQ, Xie GJ, Ding J, Guo WQ, Xing DF. 2010. Enhancedbio-hydrogen production by the combination of dark- and photo-fermentation in batch culture. Bioresour Technol 101:5325–5329. http://dx.doi.org/10.1016/j.biortech.2010.02.024.

19. Ding J, Liu BF, Ren NQ, Xing DF, Guo WQ, Xu JF, Xie GJ. 2009.Hydrogen production from glucose by co-culture of Clostridium butyri-cum and immobilized Rhodopseudomonas faecalis RLD-53. Int J HydrogenEnergy 34:3647–3652. http://dx.doi.org/10.1016/j.ijhydene.2009.02.078.

20. Liu BF, Ren NQ, Tang J, Ding J, Liu WZ, Xu JF, Cao GL, Guo WQ, XieGJ. 2010. Bio-hydrogen production by mixed culture of photo- and dark-fermentation bacteria. Int J Hydrogen Energy 35:2858 –2862. http://dx.doi.org/10.1016/j.ijhydene.2009.05.005.

21. Jiao Y, Navid A, Stewart BJ, McKinlay JB, Thelen MP, Pett-Ridge J.2012. Syntrophic metabolism of a co-culture containing Clostridium cel-lulolyticum and Rhodopseudomonas palustris for hydrogen production. IntJ Hydrogen Energy 37:11719 –11726. http://dx.doi.org/10.1016/j.ijhydene.2012.05.100.

22. Cheng J, Su H, Zhou J, Song W, Cen K. 2011. Hydrogen production bymixed bacteria through dark and photo fermentation. Int J HydrogenEnergy 36:450 – 457. http://dx.doi.org/10.1016/j.ijhydene.2010.10.007.

23. Sieuwerts S, Molenaar D, van Hijum SAFT, Beerthuyzen M, StevensMJA, Janssen PWM, Ingham CJ, de Bok FAM, de Vos WM, vanHylckama Vlieg JET. 2010. Mixed-culture transcriptome analysis revealsthe molecular basis of mixed-culture growth in Streptococcus thermophilusand Lactobacillus bulgaricus. Appl Environ Microbiol 76:7775–7784. http://dx.doi.org/10.1128/AEM.01122-10.

24. Beliaev AS, Romine MF, Serres M, Bernstein HC, Linggi BE, MarkillieLM, Isern NG, Chrisler WB, Kucek LA, Hill EA, Pinchuk GE, BryantDA, Steven Wiley H, Fredrickson JK, Konopka A. 2014. Inference ofinteractions in cyanobacterial-heterotrophic co-cultures via transcrip-tome sequencing. ISME J 8:2243–2255. http://dx.doi.org/10.1038/ismej.2014.69.

25. Liu BF, Xie GJ, Wang RQ, Xing DF, Ding J, Zhou X, Ren HY, Ma C,Ren NQ. 2015. Simultaneous hydrogen and ethanol production fromcascade utilization of mono-substrate in integrated dark and photo-fermentative reactor. Biotechnol Biofuels 8:8. http://dx.doi.org/10.1186/s13068-014-0191-x.

26. Lu H, Lee PKH. 2015. Effects of cellulose concentrations on the syn-trophic interactions between Clostridium cellulovorans 743B and Rhodo-pseudomonas palustris CGA009 in coculture fermentation for biohydro-gen production. Int J Hydrogen Energy 40:11800 –11808. http://dx.doi.org/10.1016/j.ijhydene.2015.05.135.

27. Pawar S, Vongkumpeang T, Grey C, van Niel E. 2015. Biofilm formationby designed co-cultures of Caldicellulosiruptor species as a means to im-prove hydrogen productivity. Biotechnol Biofuels 8:19. http://dx.doi.org/10.1186/s13068-015-0201-7.

28. Adessi A, McKinlay JB, Harwood CS, De Philippis R. 2012. A Rhodo-pseudomonas palustris nifA* mutant produces H2 from NH4

�-containingvegetable wastes. Int J Hydrogen Energy 37:15893–15900. http://dx.doi.org/10.1016/j.ijhydene.2012.08.009.

29. Sun Q, Xiao W, Xi D, Shi J, Yan X, Zhou Z. 2010. Statistical optimiza-tion of biohydrogen production from sucrose by a co-culture of Clostrid-ium acidisoli and Rhodobacter sphaeroides. Int J Hydrogen Energy 35:4076 – 4084. http://dx.doi.org/10.1016/j.ijhydene.2010.01.145.

30. Hillmer P, Gest H. 1977. H2 metabolism in the photosynthetic bacteriumRhodopseudomonas capsulata: H2 production by growing cultures. J Bac-teriol 129:724 –731.

31. Hillmer P, Gest H. 1977. H2 metabolism in the photosynthetic bacterium

Rhodopseudomonas capsulata: production and utilization of H2 by restingcells. J Bacteriol 129:732–739.

32. Li R, Yu C, Li Y, Lam TW, Yiu SM, Kristiansen K, Wang J. 2009.SOAP2: an improved ultrafast tool for short read alignment. Bioinformat-ics 25:1966 –1967. http://dx.doi.org/10.1093/bioinformatics/btp336.

33. Mortazavi A, Williams BA, McCue K, Schaeffer L, Wold B. 2008.Mapping and quantifying mammalian transcriptomes by RNA-Seq. NatMethods 5:621– 628. http://dx.doi.org/10.1038/nmeth.1226.

34. Tarazona S, Garcia-Alcalde F, Dopazo J, Ferrer A, Conesa A. 2011.Differential expression in RNA-seq: a matter of depth. Genome Res 21:2213–2223. http://dx.doi.org/10.1101/gr.124321.111.

35. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, DavisAP, Dolinski K, Dwight SS, Eppig JT, Harris MA, Hill DP, Issel-Tarver L,Kasarskis A, Lewis S, Matese JC, Richardson JE, Ringwald M, Rubin GM,Sherlock G. 2000. Gene Ontology: tool for the unification of biology. NatGenet 25:25–29. http://dx.doi.org/10.1038/75556.

36. Conesa A, Götz S, García-Gómez JM, Terol J, Talón M, Robles M. 2005.Blast2GO: a universal tool for annotation, visualization and analysis infunctional genomics research. Bioinformatics 21:3674 –3676. http://dx.doi.org/10.1093/bioinformatics/bti610.

37. Ye J, Fang L, Zheng H, Zhang Y, Chen J, Zhang Z, Wang J, Li S, Li R,Bolund L, Wang J. 2006. WEGO: a web tool for plotting GO annotations.Nucleic Acids Res 34:W293–W297. http://dx.doi.org/10.1093/nar/gkl031.

38. Kanehisa M, Araki M, Goto S, Hattori M, Hirakawa M, Itoh M,Katayama T, Kawashima S, Okuda S, Tokimatsu T, Yamanishi Y. 2008.KEGG for linking genomes to life and the environment. Nucleic Acids Res36:D480 –D484. http://dx.doi.org/10.1093/nar/gkm882.

39. Yamada T, Letunic I, Okuda S, Kanehisa M, Bork P. 2011. iPath2.0:interactive pathway explorer. Nucleic Acids Res 39:W412–W415. http://dx.doi.org/10.1093/nar/gkr313.

40. Wickham H (ed). 2009. ggplot2: elegant graphics for data analysis.Springer, New York, NY.

41. Livak KJ, Schmittgen TD. 2001. Analysis of relative gene expression datausing real-time quantitative PCR and the 2���CT method. Methods 25:402– 408. http://dx.doi.org/10.1006/meth.2001.1262.

42. Mathews J, Wang G. 2009. Metabolic pathway engineering for enhancedbiohydrogen production. Int J Hydrogen Energy 34:7404 –7416. http://dx.doi.org/10.1016/j.ijhydene.2009.05.078.

43. Harwood CS. 2008. Nitrogenase-catalyzed hydrogen production by pur-ple non-sulfur photosynthetic bacteria, p 259 –272. In Wall JD, HarwoodCS, Demain A (ed), Bioenergy. ASM Press, Washington, DC.

44. Oda Y, Samanta SK, Rey FE, Wu L, Liu X, Yan T, Zhou J, Harwood CS.2005. Functional genomic analysis of three nitrogenase isozymes in thephotosynthetic bacterium Rhodopseudomonas palustris. J Bacteriol 187:7784 –7794. http://dx.doi.org/10.1128/JB.187.22.7784-7794.2005.

45. Kutsche M, Leimkuehler S, Angermueller S, Klipp W. 1996. Promoterscontrolling expression of the alternative nitrogenase and the molybdenumuptake system in Rhodobacter capsulatus are activated by NtrC, indepen-dent of 54, and repressed by molybdenum. J Bacteriol 178:2010 –2017.

46. Lehman LJ, Roberts GP. 1991. Identification of an alternative nitrogenasesystem in Rhodospirillum rubrum. J Bacteriol 173:5705–5711.

47. Drepper T, Groß S, Yakunin AF, Hallenbeck PC, Masepohl B, Klipp W.2003. Role of GlnB and GlnK in ammonium control of both nitrogenasesystems in the phototrophic bacterium Rhodobacter capsulatus. Microbi-ology 149:2203–2212. http://dx.doi.org/10.1099/mic.0.26235-0.

48. Leigh JA, Dodsworth JA. 2007. Nitrogen regulation in bacteria andarchaea. Annu Rev Microbiol 61:349 –377. http://dx.doi.org/10.1146/annurev.micro.61.080706.093409.

49. Reitzer L. 2003. Nitrogen assimilation and global regulation in Escherichiacoli. Annu Rev Microbiol 57:155–176. http://dx.doi.org/10.1146/annurev.micro.57.030502.090820.

50. Tamaru Y, Miyake H, Kuroda K, Nakanishi A, Matsushima C, Doi RH,Ueda M. 2011. Comparison of the mesophilic cellulosome-producingClostridium cellulovorans genome with other cellulosome-related clostrid-ial genomes. Microb Biotechnol 4:64-73. http://dx.doi.org/10.1111/j.1751-7915.2010.00210.x.

51. Han SO, Cho HY, Yukawa H, Inui M, Doi RH. 2004. Regulation ofexpression of cellulosomes and noncellulosomal (hemi)cellulolytic en-zymes in Clostridium cellulovorans during growth on different carbonsources. J Bacteriol 186:4218-4227. http://dx.doi.org/10.1128/JB.186.13.4218-4227.2004.

52. Russell JB. 1987. Effect of extracellular pH on growth and proton motive

Lu et al.

4558 aem.asm.org August 2016 Volume 82 Number 15Applied and Environmental Microbiology

on August 11, 2019 by guest

http://aem.asm

.org/D

ownloaded from

force of Bacteroides succinogenes, a cellulolytic ruminal bacterium. ApplEnviron Microbiol 53:2379 –2383.

53. Magnuson K, Jackowski S, Rock CO, Cronan JE, Jr. 1993. Regulation offatty acid biosynthesis in Escherichia coli. Microbiol Rev 57:522–542.

54. Taguchi F, Ogawa Y, Takeuchi K, Suzuki T, Toyoda K, Shiraishi T,Ichinose Y. 2006. A homologue of the 3-oxoacyl-(acyl carrier protein)synthase III gene located in the glycosylation island of Pseudomonas syrin-gae pv. tabaci regulates virulence factors via N-acyl homoserine lactoneand fatty acid synthesis. J Bacteriol 188:8376 – 8384. http://dx.doi.org/10.1128/JB.00763-06.

55. Lai C-Y, Cronan JE. 2003. �-Ketoacyl-acyl carrier protein synthase III(FabH) is essential for bacterial fatty acid synthesis. J Biol Chem 278:51494 –51503. http://dx.doi.org/10.1074/jbc.M308638200.

56. Larimer FW, Chain P, Hauser L, Lamerdin J, Malfatti S, Do L, LandML, Pelletier DA, Beatty JT, Lang AS, Tabita FR, Gibson JL, HansonTE, Bobst C, Torres JL, Peres C, Harrison FH, Gibson J, Harwood CS.2004. Complete genome sequence of the metabolically versatile photosyn-thetic bacterium Rhodopseudomonas palustris. Nat Biotechnol 22:55– 61.http://dx.doi.org/10.1038/nbt923.

57. Macnab RM, Koshland DE, Jr. 1972. Gradient-sensing mechanism inbacterial chemotaxis. Proc Natl Acad Sci U S A 69:2509 –2512. http://dx.doi.org/10.1073/pnas.69.9.2509.

58. Sleat R, Mah RA, Robinson R. 1984. Isolation and characterization of ananaerobic, cellulolytic bacterium, Clostridium cellulovorans sp. nov. ApplEnviron Microbiol 48:88 –93.

59. Maurer LM, Yohannes E, Bondurant SS, Radmacher M, Slonczewski JL.2005. pH regulates genes for flagellar motility, catabolism, and oxidativestress in Escherichia coli K-12. J Bacteriol 187:304 –319. http://dx.doi.org/10.1128/JB.187.1.304-319.2005.

60. Jeziore-Sassoon Y, Hamblin PA, Bootle-Wilbraham CA, Poole PS,Armitage JP. 1998. Metabolism is required for chemotaxis to sugars inRhodobacter spheroides. Microbiology 144:229 –239. http://dx.doi.org/10.1099/00221287-144-1-229.

61. Vorobjeva L, Leverrier P, Zinchenko A, Boyaval P, Khodjaev E, Vari-oukhina S, Ponomareva G, Gordeeva E, Jan G. 2004. Anti-stress activityof Propionibacterium freudenreichii: identification of a reactivative pro-

tein. Antonie Van Leeuwenhoek 85:53– 62. http://dx.doi.org/10.1023/B:ANTO.0000020276.18127.99.

62. Lithgow JK, Hayhurst EJ, Cohen G, Aharonowitz Y, Foster SJ. 2004.Role of a cysteine synthase in Staphylococcus aureus. J Bacteriol 186:1579 –1590. http://dx.doi.org/10.1128/JB.186.6.1579-1590.2004.

63. Frazzon J, Fick JR, Dean DR. 2002. Biosynthesis of iron-sulphur clustersis a complex and highly conserved process. Biochem Soc Trans 30:680 –685. http://dx.doi.org/10.1042/bst0300680.

64. Carmel-Harel O, Storz G. 2000. Roles of the glutathione- and thiore-doxin-dependent reduction systems in the Escherichia coli and Saccharo-myces cerevisiae responses to oxidative stress. Annu Rev Microbiol 54:439 – 461. http://dx.doi.org/10.1146/annurev.micro.54.1.439.

65. Storz G, Hengge-Aronis R. 2000. Microbial responses to acid stress. ASMPress, Washington, DC.

66. Alsaker KV, Paredes C, Papoutsakis ET. 2010. Metabolite stress andtolerance in the production of biofuels and chemicals: gene-expression-based systems analysis of butanol, butyrate, and acetate stresses in theanaerobe Clostridium acetobutylicum. Biotechnol Bioeng 105:1131–1147.http://dx.doi.org/10.1002/bit.22628.

67. Leaphart AB, Thompson DK, Huang K, Alm E, Wan XF, Arkin A,Brown SD, Wu L, Yan T, Liu X, Wickham GS, Zhou J. 2006. Tran-scriptome profiling of Shewanella oneidensis gene expression followingexposure to acidic and alkaline pH. J Bacteriol 188:1633–1642. http://dx.doi.org/10.1128/JB.188.4.1633-1642.2006.

68. Gigliobianco T, Lakaye B, Wins P, El Moualij B, Zorzi W, BettendorffL. 2010. Adenosine thiamine triphosphate accumulates in Escherichia colicells in response to specific conditions of metabolic stress. BMC Microbiol10:148. http://dx.doi.org/10.1186/1471-2180-10-148.

69. Kowalska E, Kujda M, Wolak N, Kozik A. 2012. Altered expression andactivities of enzymes involved in thiamine diphosphate biosynthesis inSaccharomyces cerevisiae under oxidative and osmotic stress. FEMS YeastRes 12:534 –546. http://dx.doi.org/10.1111/j.1567-1364.2012.00804.x.

70. Jagannathan B, Golbeck JH. 2009. Photosynthesis: microbial, p 325–341.In Schaechter M (ed), Encyclopedia of microbiology, 3rd ed. AcademicPress, Oxford, England. http://dx.doi.org/10.1016/B978-012373944-5.00352-7.

Transcriptome of Dark- and Photofermented H2 Cocultures

August 2016 Volume 82 Number 15 aem.asm.org 4559Applied and Environmental Microbiology

on August 11, 2019 by guest

http://aem.asm

.org/D

ownloaded from