전체메뉴
검색
Article Search

JMB Journal of Microbiolog and Biotechnology

QR Code QR Code

Research article


References

  1. Brodowski F, Duber A, Zagrodnik R, Oleskowicz-Popiel P. 2020. Co-production of hydrogen and caproate for an effective bioprocessing of waste. Bioresour. Technol. 318: 123895.
    Pubmed CrossRef
  2. Roghair M, Liu Y, Adiatma JC, Weusthuis RA, Bruins ME, Buisman CJN, et al. 2018. Effect of n-Caproate concentration on chain elongation and competing processes. ACS Sustain Chem. Eng. 6: 7499-7506.
    Pubmed PMC CrossRef
  3. Nzeteu CO, Trego AC, Abram F, O'Flaherty V. 2018. Reproducible, high-yielding, biological caproate production from food waste using a single-phase anaerobic reactor system. Biotechnol. Biofuels 11: 108.
    Pubmed PMC CrossRef
  4. Roghair M, Liu Y, Strik D, Weusthuis RA, Bruins ME, Buisman CJN. 2018. Development of an effective chain elongation process from acidified food waste and ethanol into n-Caproate. Front. Bioeng. Biotechnol. 6: 50.
    Pubmed PMC CrossRef
  5. Yang PX, Leng L, Tan GYA, Dong CY, Leu SY, Chen WH, et al. 2018. Upgrading lignocellulosic ethanol for caproate production via chain elongation fermentation. Int. Biodeter. Biodegr. 135: 103-109.
    CrossRef
  6. Spirito CM, Richter H, Rabaey K, Stams AJ, Angenent LT. 2014. Chain elongation in anaerobic reactor microbiomes to recover resources from waste. Curr. Opin. Biotechnol. 27: 115-122.
    Pubmed CrossRef
  7. Seedorf H, Fricke WF, Veith B, Bruggemann H, Liesegang H, Strittimatter A, et al. 2008. The genome of Clostridium kluyveri, a strict anaerobe with unique metabolic features. Proc. Natl. Acad. Sci. USA 105: 2128-2133.
    Pubmed PMC CrossRef
  8. Steinbusch KJJ, Hamelers HVM, Plugge CM, Buisman CJN. 2011. Biological formation of caproate and caprylate from acetate: fuel and chemical production from low grade biomass. Energy Environ. Sci. 4: 216-224.
    CrossRef
  9. Chen WS, Ye Y, Steinbusch KJJ, Strik DPBTB, Buisman CJN. 2016. Methanol as an alternative electron donor in chain elongation for butyrate and caproate formation. Biomass Bioenerg. 93: 201-208.
    CrossRef
  10. Kenealy WR, Waselefsky DM. 1985. Studies on the substrate range of Clostridium-Kluyveri - the use of propanol and succinate. Arch. Microbiol. 141: 187-194.
    CrossRef
  11. Jeon BS, Kim BC, Um Y, Sang BI. 2010. Production of hexanoic acid from D-galactitol by a newly isolated Clostridium sp. BS-1. Appl. Microbiol. Biotechnol. 88: 1161-1167.
    Pubmed CrossRef
  12. Kucek LA, Nguyen M, Angenent LT. 2016. Conversion of l-lactate into n-caproate by a continuously fed reactor microbiome. Water Res. 93: 163-171.
    Pubmed CrossRef
  13. Zhu X, Tao Y, Liang C, Li X, Wei N, Zhang W, et al. 2015. The synthesis of n-caproate from lactate: a new efficient process for medium-chain carboxylates production. Sci. Rep. 5: 14360.
    Pubmed PMC CrossRef
  14. Zhu X, Zhou Y, Wang Y, Wu T, Li X, Li D, et al. 2017. Production of high-concentration n-caproic acid from lactate through fermentation using a newly isolated Ruminococcaceae bacterium CPB6. Biotechnol. Biofuels 10: 102.
    Pubmed PMC CrossRef
  15. Wang H, Li X, Wang Y, Tao Y, Lu S, Zhu X, et al. 2018. Improvement of n-caproic acid production with Ruminococcaceae bacterium CPB6: selection of electron acceptors and carbon sources and optimization of the culture medium. Microb. Cell Fact. 17: 99.
    Pubmed PMC CrossRef
  16. Tao Y, Zhu XY, Wang H, Wang Y, Li XZ, Jin H, et al. 2017. Complete genome sequence of Ruminococcaceae bacterium CPB6: A newly isolated culture for efficient n-caproic acid production from lactate. J. Biotechnol. 259: 91-94.
    Pubmed CrossRef
  17. Sedlar K, Koscova P, Vasylkivska M, Branska B, Kolek J, Kupkova K, et al. 2018. Transcription profiling of butanol producer Clostridium beijerinckii NRRL B-598 using RNA-Seq. BMC Genomics. 19: 415.
    Pubmed PMC CrossRef
  18. Zararsiz G, Goksuluk D, Korkmaz S, Eldem V, Zararsiz GE, Duru IP, et al. 2017. A comprehensive simulation study on classification of RNA-Seq data. PLoS One 12: e0182507.
    Pubmed PMC CrossRef
  19. Erlich Y, Mitra PP, delaBastide M, McCombie WR, Hannon GJ. 2008. Alta-Cyclic: a self-optimizing base caller for next-generation sequencing. Nat. Methods 5: 679-682.
    Pubmed PMC CrossRef
  20. Cock PJ, Fields CJ, Goto N, Heuer ML, Rice PM. 2010. The sanger FASTQ file format for sequences with quality scores, and the Solexa/Illumina FASTQ variants. Nucleic Acids Res. 38: 1767-1771.
    Pubmed PMC CrossRef
  21. Langmead B, Salzberg SL. 2012. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9: 357-359.
    Pubmed PMC CrossRef
  22. Patro R, Mount SM, Kingsford C. 2014. Sailfish enables alignment-free isoform quantification from RNA-seq reads using lightweight algorithms. Nat. Biotechnol. 32: 462-U174.
    Pubmed PMC CrossRef
  23. Kirk DG, Palonen E, Korkeala H, Lindstrom M. 2014. Evaluation of normalization reference genes for RT-qPCR analysis of spo0A and four sporulation sigma factor genes in Clostridium botulinum Group I strain ATCC 3502. Anaerobe 26: 14-19.
    Pubmed CrossRef
  24. Love MI, Huber W, Anders S. 2014. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15: 550.
    Pubmed PMC CrossRef
  25. Riederer A, Takasuka TE, Makino S, Stevenson DM, Bukhman YV, Elsen NL, et al. 2011. Global gene expression patterns in Clostridium thermocellum as determined by microarray analysis of chemostat cultures on cellulose or cellobiose. Appl. Environ. Microbiol. 77: 1243-1253.
    Pubmed PMC CrossRef
  26. Rogatzki MJ, Ferguson BS, Goodwin ML, Gladden LB. 2015. Lactate is always the end product of glycolysis. Front. Neurosci. 9: 22.
    Pubmed PMC CrossRef
  27. Weghoff MC, Bertsch J, Muller V. 2015. A novel mode of lactate metabolism in strictly anaerobic bacteria. Environ. Microbiol. 17: 670-677.
    Pubmed CrossRef
  28. Skory CD. 2000. Isolation and expression of lactate dehydrogenase genes from Rhizopus oryzae. Appl. Environ. Microbiol. 66: 2343-2348.
    Pubmed PMC CrossRef
  29. Schoelmerich MC, Katsyv A, Sung W, Mijic V, Wiechmann A, Kottenhahn P, et al. 2018. Regulation of lactate metabolism in the acetogenic bacterium Acetobacterium woodii. Environ. Microbiol. 20: 4587-4595.
    Pubmed CrossRef
  30. Yang Q, Wei C, Guo S, Liu J, Tao Y. 2020. Cloning and characterization of a L-lactate dehydrogenase gene from Ruminococcaceae bacterium CPB6. World J. Microbiol. Biotechnol. 36: 182.
    Pubmed CrossRef
  31. Lee J, Jang YS, Han MJ, Kim JY, Lee SY. 2016. Deciphering Clostridium tyrobutyricum Metabolism based on the whole-genome sequence and proteome analyses. mBio 7: e00743-16.
    CrossRef
  32. Yang Q, Guo S, Lu Q, Tao Y, Zheng D, Zhou Q, et al. 2021. Butyryl/Caproyl-CoA:Acetate CoA-transferase: cloning, expression and characterization of the key enzyme involved in medium-chain fatty acid biosynthesis. Biosci. Rep. 41: BSR20211135.
    Pubmed PMC CrossRef
  33. Sauer U, Santangelo JD, Treuner A, Buchholz M, Durre P. 1995. Sigma factor and sporulation genes in Clostridium. FEMS Microbiol. Rev. 17: 331-340.
    Pubmed CrossRef
  34. Woods DR, Jones DT. 1986. Physiological responses of Bacteroides and Clostridium strains to environmental stress factors. Adv. Microb. Physiol. 28: 1-64.
    CrossRef
  35. Wang Y, Li XZ, Blaschek HP. 2013. Effects of supplementary butyrate on butanol production and the metabolic switch in Clostridium beijerinckii NCIMB 8052: genome-wide transcriptional analysis with RNA-Seq. Biotechnol. Biofuels 6: 138.
    Pubmed PMC CrossRef
  36. Hollenstein K, Dawson RJ, Locher KP. 2007. Structure and mechanism of ABC transporter proteins. Curr. Opin. Struct. Biol. 17: 412-418.
    Pubmed CrossRef
  37. Cui J, Davidson AL. 2011. ABC solute importers in bacteria. Essays Biochem. 50: 85-99.
    Pubmed CrossRef
  38. Qin J, Wang X, Wang L, Zhu B, Zhang X, Yao Q, et al. 2015. Comparative transcriptome analysis reveals different molecular mechanisms of Bacillus coagulans 2-6 response to sodium lactate and calcium lactate during lactic acid production. PLoS One 10: e0124316.
    Pubmed PMC CrossRef
  39. Zhu Z, Yang J, Yang P, Wu Z, Zhang J, Du G. 2019. Enhanced acid-stress tolerance in Lactococcus lactis NZ9000 by overexpression of ABC transporters. Microb. Cell Fact. 18: 136.
    Pubmed PMC CrossRef
  40. Jones PM, George AM. 2004. The ABC transporter structure and mechanism: perspectives on recent research. Cell Mol. Life Sci. 61: 682-699.
    Pubmed CrossRef
  41. Jason G, McCoy, Elena J. Levin, Zhou M. 2015. Structural insight into the PTS sugar transporter EIIC. Biochim. Biophys. Acta 1850: 577-585.
    Pubmed PMC CrossRef
  42. Nguyen TX, Yen MR, Barabote RD, Saier MH Jr. 2006. Topological predictions for integral membrane permeases of the phosphoenolpyruvate:sugar phosphotransferase system. J. Mol. Microbiol. Biotechnol. 11: 345-360.
    Pubmed CrossRef
  43. Nikaido H, Hall JA. 1998. Overview of bacterial ABC transporters. Methods Enzymol. 292: 3-20.
    CrossRef

Related articles in JMB

More Related Articles

Article

Research article

J. Microbiol. Biotechnol. 2021; 31(11): 1533-1544

Published online November 28, 2021 https://doi.org/10.4014/jmb.2107.07009

Copyright © The Korean Society for Microbiology and Biotechnology.

Genome-Wide Transcriptomic Analysis of n-Caproic Acid Production in Ruminococcaceae Bacterium CPB6 with Lactate Supplementation

Shaowen Lu1, Hong Jin2, Yi Wang4, and Yong Tao1,3*

1CAS Key Laboratory of Environmental and Applied Microbiology and Environmental Microbiology Key Laboratory of Sichuan Province, Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu 610041, P.R. China 2School of Basic Medical Science, Chengdu Medical College, Chengdu 610083, P.R. China 3Faculty of Bioengineering, Sichuan University of Science and Engineering, Xueyuan Street 180#, Huixing Rd. Zigong 643000, P.R. China 4Department of Biosystems Engineering, Auburn University, Auburn, Alabama, Alabama 36849, USA

Correspondence to:Yong Tao,        taoyong@cib.ac.cn

Received: July 6, 2021; Revised: August 25, 2021; Accepted: August 25, 2021

Abstract

n-Caproic acid (CA) is gaining increased attention due to its high value as a chemical feedstock. Ruminococcaceae bacterium strain CPB6 is an anaerobic mesophilic bacterium that is highly prolific in its ability to perform chain elongation of lactate to CA. However, little is known about the genome-wide transcriptional analysis of strain CPB6 for CA production triggered by the supplementation of exogenous lactate. In this study, cultivation of strain CPB6 was carried out in the absence and presence of lactate. Transcriptional profiles were analyzed using RNA-seq, and differentially expressed genes (DEGs) between the lactate-supplemented cells and control cells without lactate were analyzed. The results showed that lactate supplementation led to earlier CA p,roduction, and higher final CA titer and productivity. 295 genes were substrate and/or growth dependent, and these genes cover crucial functional categories. Specifically, 5 genes responsible for the reverse β-oxidation pathway, 11 genes encoding ATP-binding cassette (ABC) transporters, 6 genes encoding substrate-binding protein (SBP), and 4 genes encoding phosphotransferase system (PTS) transporters were strikingly upregulated in response to the addition of lactate. These genes would be candidates for future studies aiming at understanding the regulatory mechanism of lactate conversion into CA, as well as for the improvement of CA production in strain CPB6. The findings presented herein reveal unique insights into the biomolecular effect of lactate on CA production at the transcriptional level.

Keywords: n-Caproic acid, lactate, chain elongation, transcriptome, RNA-Seq

Introduction

The increasing demand for fuels and chemicals, and the scarcity of fossil resources necessitate the development of sustainable and innovative strategies for the industrial production. n-Caproic acid (CA) has recently gained considerable attention due to its high value as a chemical feedstock [1]. Organic residual streams (e.g., food waste and brewery wastewater) have great potential to be employed as feedstock for CA production [2, 3]. Many studies show that the addition of ethanol during the acidification of wastes can promote chain elongation, and lead to higher volumetric production rate and a high CA selectivity [4, 5]. Generally, biosynthesis of CA is achieved by some anaerobic microbes via the reverse β-oxidation pathway with ethanol as electron donor (ED) [4, 6], in which the oxidation of ethanol provides energy and acetyl-CoA for the chain elongation [7]. In addition to ethanol, many chemicals are explored as EDs for CA production, including hydrogen [8], methanol [9], propanol [10], and D-galactitol [11].

Recently, lactate is becoming a potential alternative to ethanol for the production of CA [12, 13]. Lactate can be efficiently converted into CA by a Ruminococcaceae bacterium CPB6 [14]. The phylogenic analysis based on 16S rRNA sequences and the whole genome show that strain CPB6 might belong to a new clade (genus) of the family Ruminococcaceae, it is thus tentatively christened with the name Ruminococcaceae bacterium CPB6 [14]. Strain CPB6 can produce CA (C6) from lactate (as ED) with C2-C4 carboxylic acids as electron acceptors (EAs), or heptoic acid (C7) from lactate with C3-C5 carboxylic acids [15]. More recently, complete genomic sequencing and annotation show that strain CPB6 encodes most genes related to glycolysis and the reverse β-oxidation pathway [16]. However, to date, very little information is available on genome-wide transcriptomic analysis of strain CPB6 for CA production using lactate as ED, which is essential to understand the effect of lactate on the metabolic pathway shift for CA production at the molecular level, and thus elucidate proper strategies for further strain improvement.

RNA-sequencing (RNA-Seq) is a powerful technique to investigate entire transcriptomes, and identify specific genes for the particular interesting metabolic pathways [17, 18]. In this study, RNA-Seq of the transcriptome of strain CPB6 was carried out to investigate the effect of lactate supplementation on gene expression, as well as to identify key genes related to CA production. These candidate genes are likely to be valuable for the metabolic engineering in the future to further improve the ability of strain CPB6 to convert lactate into CA.

Materials and Methods

Microorganisms, Media and Fermentation Experiment

Ruminococcaceae bacterium CPB6 (GDMCC No.60133) is a spore-forming, obligate anaerobic bacterium that can produce CA from lactate [14]. Strain CPB6 was routinely cultured at 37°C anaerobically in a modified tryptone-glucose-yeast extract (mTGY) medium containing the following compounds (pH 6.0): 5.0 g/l tryptone, 2.0 g/l glucose, 3.5 g/l sodium acetate, 0.41 g/l K2HPO4·3H2O, 0.23 g/l KH2PO4, 0.25 g/l NH4Cl, 0.20 g/l MgSO4·7H2O, 2.5 g/l NaHCO3, 0.50 g/l L-cysteine, 0.25 g/l Na2S·9H2O, 0.0005 g/l resazurin, and 1 ml of trace element solution SL-10 and 1ml of vitamin solution [13]. The suspension of activated strain CPB6 was inoculated with a 5% ratio into the same medium as described above, and incubated for 12 h until the optical density at 600 nm (OD600) of the culture reached 0.8-1.0. Then the culture would be used as the seed inoculum (5% ratio, v/v) for batch experiments. To investigate the effect of lactate on cell growth and CA production, 5 g/l sodium lactate was supplemented into the mTGY liquid medium (i.e., mTGYL). Batch experiments were performed in 250 ml serum bottles containing 100 ml of mTGY or mTGYL media. The headspace of the bottle was filled with highly pure N2. Each fermentation was performed in triplicate. The fermentation was carried out at 37°C in an E500 anaerobic workstation (Gene Science, USA) under N2: CO2: H2 (volume ratio of 80:10:10) atmosphere.

Samples were taken at specific times and processed for cell concentration determination and high-performance liquid chromatography (HPLC) analysis. Samples for RNA isolation were taken at the cell growth and stationary phases.

Analytical Methods

Culture growth was monitored by measuring the OD600 using a TU-1810 UV/Vis Spectrophotometer (Puxi Instrument Co. Ltd., China). Lactic acid, acetic acid, butyric acid, and caproic acid were quantified using an HPLC system (Agilent 1260 Infinity, USA) equipped with a differential refraction detector (RID) and a Agilent Hi-Plex H column (300 × 6.5 mm) following the procedure as previously described [15].

RNA Isolation, Library Construction, and Sequencing

In preparation for RNA isolation, 10 ml cell culture was harvested at each time point, and centrifuged at 8,000 ×g for 10 min at 4°C. Cells were then frozen in liquid nitrogen prior to storage at -80°C. The RNA was extracted and purified using a RNA extraction kit (DP430, Tiangen Biotech, China) following the manufacturer's protocol. RNA quality and quantity were characterized using a NanoDrop2000 (NanoDrop Technologies, USA), agarose gel electrophoresis (RNA integrity detection) and Agilent 2100 (RIN value measurement). Only the RNA samples with high-quality (≥ 5 μg; ≥ 200 ng/μl; OD260/280=1.8~2.2; RIN > 6.0) were used for the cDNA library construction and sequencing. Before library construction, rRNAs were removed with the Ribo-Zero rRNA Removal Kit (Epicentre, USA) following the manufacturer’s protocol. The enriched mRNA was randomly fragmented into 200 bp fragments by fragmentation buffer. The mRNA was then the first strand cDNA was synthesized using the random hexamer-primer with the mRNA fragment as the template. After synthesizing the second strand cDNA using DNA polymerase I and RNase H, double-stranded cDNA was further end repaired, A-tailed, and indexed adapters ligated. The final cDNA library was constructed using TruSeq RNA sample preparation Kit (Illumina Inc., USA), and then sequenced by Illumin Hiseq 4000 (Illumina Inc.) with 2 × 150 bp.

Sequencing trimming and quality control methods are as follows: (1) Remove the Adapter sequence in reads;(2) The bases containing non-A, G, C and T at the 5 'end were removed by shear; (3) Trim the ends of reads with low sequencing quality (< Q20); (4) Reads containing 10 % N were removed; (5) Remove Adapter and small segments with length less than 25 bp after quality pruning.

RNA-Seq Data Analysis

Raw data were processed, and reads containing adapter and poly-N sequences and low-quality reads were removed using Sickle and SeqPrep to obtain clean data [19, 20]. The trimmed reads in each sample were aligned to strain CPB6 genome (CP020705.1) using Bowtie2, and those that did not align uniquely to the genome were discarded using the default quality parameters [21]. Each base was assigned a value based on the number of mapped sequence coverage. Gene expression levels were defined using the number of transcripts per million (TPM), which is proportional to the quantity of cDNA fragments derived from the gene transcripts. The quantitative gene expression values between samples were identified by calculating the number of unambiguous tags for each gene and then normalizing this to TPM, which was calculated following the method reported by Parto et al. [22]. The gene expression results were visualized as a heat-map plot using ggplot2 package. The general changes in gene expression among different treatments were evaluated by permutational multivariate analysis of variance using the function Adonis in the R vegan package. Gene annotation was performed based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (http://www.genome.jp/kegg/).

Reverse Transcription-Quantitative PCR (RT-qPCR)

In order to validate the results of the RNA-Seq analysis, 5 candidate reference genes were selected for RT-qPCR confirmation. Primers used are listed in Supporting Information Table S3. Total RNA was extracted from three sets of independent cultures grown on cultures with or without lactate supplementation, and then converted to cDNA by random priming, using the Maxima Reverse Transcriptase (Thermo Scientific). PCR reactions were run in triplicate using procedure as follows: initial denaturation (3 min at 95°C), followed by 45 cycles of denaturation (5 s at 95°C), annealing and elongation (30 s at 60°C). The transcription level of genes was determined according to the 2-(ΔΔCt) method, using 16S rRNA as a reference gene for the normalization of gene expression levels [23].

Statistical Analysis

Significant differences of the gene expression between the culture with lactate supplementation and the control were determined using ANOVA in R software (version 3.5.2). TPM values were first transformed to log10-scale. The log10-transformed TPM values were then properly centered for better representation of the data using the heatmap plots. Fold changes (FCs) as the ratio of the TPM values were calculated following the method reported by Love et al. [24], and were used to compare the differentially expressed genes (DEGs) between the culture from fermentation with lactate supplementation and the control.

RNA-Seq Data

The RNA-Seq sequencing data have been deposited in the NCBI Sequence Read Archive (SRA) under the accession number PRJNA564589

Results

Cell Growth and the Production of CA

As shown in Fig. 1A, cells took approximately 18 h to grow to the stationary phase. Although the maximum OD600 of the lactate-supplemented cultures was slightly higher than that of control cultures without lactate at the stationary phase (1.25 vs 1.16), both cultures showed similar growth kinetics. The lactate was completely consumed in the lactate supplemented culture after 21 h of cultivation. Moreover, no lactate was detected throughout the control group. CA production was started to be observed in the lactate-supplemented cultures after 6 h of cultivation, and the CA titer continued to increase and reached 1,717.2 mg/l at 21 h (Fig. 1B), while CA was not detected in control cells until 15 h of cultivation, and the CA titer of which only reached 618 mg/l at 21 h (Fig. 1C). These results suggest that lactate supplementation had little effect on the cell growth, but led to earlier initiation for CA production (6 vs 15 h), higher final CA titer (1,717 vs 618 mg/l), and higher CA productivity (81.8 vs 29.4 mg/l h).

Figure 1. Fermentation kinetics of Ruminococcaceae bacterium CPB6. (A) Cell growth profiles. Time points for taking samples subjected to RNA-Seq are indicated with red vertical arrows. L: fermentation with lactate supplementation; C: control fermentation without lactate supplementation; (B) Sugar consumption and metabolites production during the fermentation with the supplementation of lactate; (C) Sugar consumption and metabolites production during the control fermentation. Values represent the mean of the biological triplicates and error bars represent the standard deviations.

RNA-Seq Statistics

Samples were taken for RNA-Seq analysis from both growth (12 h) and stationary (18 h) phases for the lactate-supplemented cultures and control cultures. For each culture, independent biological triplicates (a, b, and c) were included (Table 1). Therefore, a total of twelve samples were taken for cDNA libraries construction and sequencing on the Illumina HiSeq 4000 (Illumina). The number of raw reads generated from the sequencing for each library was from 15.7 to 23.5 million (Table S1). A total of 224 Mb sequence reads from 12 cDNA libraries were mapped to strain CPB6 genome. Only those reads that mapped unambiguously to strain CPB6 genome were used for further analysis.

Table 1 . Summary of RNA-Seq sequencing and data analysis results..

Sample NameL1L2C1C2

abcabcabcabc
Total reads229827921861453618087962168816481684405815343814186841121910814819099082199092582303212018662552
No. of read mapped226848581839070917865180167133191660672615098988184372611889387318905208196316862257287318285805
Ratio of reads mapped (%)98.798.898.779998.5998.498.6898.8898.9898.6198.0197.98
No. of unique reads mapped223390681791595417559600165400601632476814862898180503161850569718508661192472562218727217856892
No. of genes with detectable expression196919681968196819691968196819681968196819691969
Range in expression levels (TPM)8.3 - 2.7×1048.0-1.7×10411.5-1.7×1043.2-5.3×10426.4 -3.7×1046.6 -7.3×1044.3-2.0×1043.8-1.8×1044.1-1.9×1045.2-2.4×10410.8-1.8×10424.5-1.9×104

L1: cell culture with lactate supplementation from the growth phase;.

L2: cell culture with lactate supplementation from the stationary phase;.

C1: Control culture without lactate supplementation from the growth phase;.

C2: Control culture without lactate supplementation from the stationary phase. a and c represented the biological triplicate samples..



Overall, out of the reads derived from all samples, 15.1 to 22.7 million reads were unambiguously mapped to strain CPB6 genome, and over 98% reads were mapped (Table 1). A total of 1968/1969 out of 2045 protein-coding genes had detectable expression in all cells, covering 96% of strain CPB6 genome. This result indicated that the RNA-Seq analysis achieved comprehensive coverage of strain CPB6 transcriptome. The transcription levels (the number of transcripts per million, TPM) of most active protein-coding genes were in the range of 3.2 × 104 –7.3×104.

As illustrated in Fig. 2, the gene expression could be classified into four levels: low (TPM < 30), moderate (TPM: 30-150), high (TPM: 150-1000), and very high (TPM > 1000). The number of genes at some specific expression levels was significantly different for the two cultures. For the growth phase, there were slightly more genes in the moderate, high and very high expression level in the lactate-treated cells than in control cells, but lowly expressed genes were significantly decreased. While for the stationary phase, the lactate-treated cells had more genes in the moderate expression level, but fewer genes in the high and very high expression level.

Figure 2. Frequency histogram of transcripts from the RNA-Seq results. L: the lactate supplemented cells; C: control cells without lactate supplementation; Number 1 and 2 represented the growth phase and stationary phase, respectively. The diagram shows the distribution of the number of genes expressed at different transcripts per million (TPM) levels. The percentage value above each bar indicates the genes at the specific expression level accounting for the proportion of the total number of genes. The ‘*’ mark indicates that significantly different frequencies (i.e., numbers of genes) were observed between the two RNA-Seq data sets from the lactate-supplemented fermentation (L) vs. the control (C), respectively.

Functional Annotation and Classification

In the transcriptome of strain CPB6, a total of 1122 expressed genes were allocated into three primary Gene Ontology (GO) categories (Fig. 3), including the category of biological process (601 genes), cellular component (524 genes), and molecular function (916 genes). In each category, the genes were further assigned into 28 functional groups, such as metabolic process (478 genes), cellular process (440 genes), cell part (307 genes), membrane part (297 genes), catalytic activity (654 genes), binding (561genes), and etc. The analysis of the genes based on the KEGG annotation identified a total of 1046 unigenes allocated into six primary KEGG categories including 35 subcategories (Fig. S1). The analysis based on the Clusters of Orthologous Groups (COGs) showed that 1785 unigenes were allocated to four primary COG categories containing 20 COG functional clusters (Fig. S2).

Figure 3. Annotation of genes using Gene Ontology (GO) in the transcriptome of strain CPB6. Left axis: the proportion of genes falling into each GO category; right axis: the number of genes falling into each GO category.

DEGs Affected by Lactate Supplementation

The correct identification of DEGs between specific conditions is a key in understanding phenotypic variation of organisms under environmental stress. As shown in Table 2, only 34 DEGs (FC ≥2 or ≤ 0.5 with p-value < 0.05) were found in the lactate-supplemented cells compared to control cells at the growth phase, of which 15 genes were upregulated, and 19 genes were downregulated. At the stationary phase, a total of 245 DEGs were identified in both cultures, of which 123 genes were significantly upregulated and 122 genes were downregulated (Table S2). These results demonstrated that the addition of lactate led to differences in gene expression during different growth phases.

Table 2 . The differentially expressed genes in culture with/without lactate supplementation during the growth phase..

No.Gene_IDGene nameGene descriptionTPMFC (L1/C1)P-value

C1L1
15 upregulated genes (FC ≥ 2.0); all statistically significant (P < 0.05)
1B6259_RS06365AtoBacetyl-CoA C-acetyltransferase122452043.457.9E-39
2B6259_RS06360Crtenoyl-CoA hydratase79534343.462.4E-33
3B6259_RS06355Hbd3-hydroxybutyryl-CoA dehydrogenase141863063.492.3E-27
4B6259_RS07830Ptaphosphate acetyltransferase2716662.094.3E-24
5B6259_RS00440-methionine ABC transporter ATP-binding protein515045.256.2E-18
6B6259_RS00450-metal ABC transporter substrate-binding protein306995.695.9E-15
7B6259_RS00445-ABC transporter permease274465.176.9E-14
8B6259_RS08190CysKcysteine synthase A39074264.076.4E-10
9B6259_RS08440-unknown function104835982.335.2E-06
10B6259_RS06010-hypothetical protein21892.528.1E-06
11B6259_RS07140-hypothetical protein1544702.173.0E-05
12B6259_RS01720CadAcadmium-translocating P-type ATPase22662.163.9E-05
13B6259_RS06870-Hsp20/alpha crystallin family protein31511022.211.6E-04
14B6259_RS00455PepTpeptidase T375762.262.0E-04
15B6259_RS02585Bdhbutanol dehydrogenase822422.043.1E-04
19 downregulated genes (FC ≤ 0.5); all statistically significant (P < 0.05)
1B6259_RS08515-peptide ABC transporter substrate-binding protein98530.481.7E-23
2B6259_RS09280-PTS glucose transporter subunit IIA12004840.375.5E-23
3B6259_RS09735IlvHacetolactate synthase small subunit5643020.489.4E-19
4B6259_RS06995-hypothetical protein276430.202.7E-18
5B6259_RS08565-hypothetical protein143790.502.3E-13
6B6259_RS07000-sugar ABC transporter permease113310.309.2E-13
7B6259_RS01525-unknown function268310100.378.4E-12
8B6259_RS03200-unknown function268310100.378.4E-12
9B6259_RS07010Tagglycosylase144460.349.9E-11
10B6259_RS07005-carbohydrate ABC transporter permease90330.371.1E-09
11B6259_RS01865-DUF2520 domain-containing protein260850.366.7E-09
12B6259_RS01880PanDaspartate 1-decarboxylase4441560.379.5E-09
13B6259_RS01870PanB3-methyl-2-oxobutanoate hydroxymethyltransferase3141050.371.1E-08
14B6259_RS01875Pancpantoate-beta-alanine ligase3501150.371.2E-08
15B6259_RS01760-hypothetical protein8203690.448.9E-08
16B6259_RS02315-basic amino acid ABC transporter substrate-binding protein147790.501.8E-07
17B6259_RS00100FruK1-phosphofructokinase12562760.351.7E-06
18B6259_RS00095-PTS fructose transporter subunit IIC12733720.371.8E-06
19B6259_RS00105-DeoR/GlpR transcriptional regulator13042780.363.6E-06

L1: lactate-supplemented cells at growth phase.

C1: no-lactate-supplemented cells (control) at growth phase.



The COG distribution of DEGs is illustrated in Fig. S3. It revealed potential genes, processes and pathways that may participate in the utilization of lactate and CA production. Cluster analysis of the DEGs between the lactate-supplemented cells and control cells is showed in Fig. S4. Obviously, more DEGs was observed in the stationary phase (L2 vs C2) than in the growth phase (L1 vs C1).

As shown in Fig. 4, a total of 295 DEGs in expression pattern were substrate and/or growth dependent, of which 31 genes were substrate (lactate) dependent, 228 genes were growth dependent, and 36 genes were substrate-growth dependent (Fig. 4A). Specifically, 11 and 20 lactate-dependent genes were significantly upregulated and downregulated, as well as 98 and 130 growth-dependent genes were significantly upregulated and downregulated, respectively (Fig. 4B). It was suggested that the differences in gene expression are stronger for stationary phase vs growth phase than for plus/minus lactate. Similar results was observed for C. thermocellum, in which growth rate had stronger effects on gene expression than substrate type [25].

Figure 4. Venn diagram of the numbers of differentially expressed genes (DEGs) trigger by substrate type (plus/ minus lactate) vs growth stage (stationary phase vs growth phase) (A), the numbers of DEGs trigger by substrate type vs growth stage (B). The overlap of circles was defined as genes affected by both substrate type and growth stage.

Expression of Glycolysis Genes

An overview of the metabolic pathway in strain CPB6, and the expression levels of genes involved in key metabolic processes with their fold change (FC) were shown in Fig. 5 and Table 3. Most glycolytic genes were expressed at a relatively high level (TPM>150) between the lactate-supplemented cells and control cells, but there was no significant difference (p > 0.05) between them at the growth phase. Three glycolytic genes exhibited different expression patterns at the stationary phase. Gene encoding phosphofructokinase (Pfk, B6259_RS06095) was significantly downregulated (p < 0.05), while genes encoding glucose-1-phosphate adenylyltransferase (GlgC, B6259_RS09035) and 1, 4-alpha-glucan branching enzyme (GlgB, B6259_RS09040) were upregulated by 4.58 and 3.42-fold (p < 0.05) in the lactate-supplemented cells compared with control cells, respectively. GlgB and GlgC are typically associated with glycogen synthesis, why expression of these genes be affected by lactate supplementation remains unclear. Overall, the addition of lactate has little impact on the expression of glycolytic genes.

Table 3 . The differentially expressed genes within the important metabolic pathways in culture with/without lactate supplementation..

Functional descriptionGene_IDTPM of genes from culture with lactate supplementationaTPM of genes from the ControlaRNA relative fold change (Treatment/Control)

12h18h12h18h12h18h
Glycolysis
PTS-Glc-EIIA, PTS glucose transporter subunit IIAB6259_RS0928048426012005170.37 c0.62
GlgC, glucose-1-phosphate adenylyltransferaseB6259_RS0903515313232362410.574.58 b
GlgB, 1,4-alpha-glucan branching enzymeB6259_RS090401947452362010.723.42 b
sugar phosphate isomerase/epimeraseB6259_RS065001811751502331.050.88
Pgm, phosphoglucomutaseB6259_RS09200951891271130.661.80
Gpi, glucose-6-phosphate isomeraseB6259_RS0482520151789183318180.961.12
Pfk, phosphofructokinaseB6259_RS06095426975805160.660.23 c
Aldo, fructose-bisphosphate aldolaseB6259_RS004157494028008910.830.57
Tpi, triose-phosphate isomeraseB6259_RS091052242293154930.650.58
GapA, glyceraldehyde phosphate dehydrogenaseB6259_RS0905053224284479077320.980.70
Pgk, phosphoglycerate kinaseB6259_RS0910052352470510290.670.65
GpmI, 2,3-bisphosphoglycerate-independent phosphoglycerate mutaseB6259_RS091102032002844690.660.55
Eno, phosphopyruvate hydrataseB6259_RS04810416530521.141.46
PK, pyruvate kinaseB6259_RS023352541022932280.771.46
Central pyruvate metabolism
PpdK, pyruvate phosphate dikinaseB6259_RS001201301823116315350.990.69
Pfor, pyruvate: ferredoxin (flavodoxin) oxidoreductaseB6259_RS0913543294382204412251.833.26 b
Pck, phosphoenolpyruvate carboxykinaseB6259_RS0925536815955410310.620.23 c
PflD, formate C-acetyltransferaseB6259_RS09900981881074710.830.54
Adh, alcohol dehydrogenaseB6259_RS031002001161631591.070.84
Incomplete TCA cycle
Cs, citrate synthase, citrate lyaseB6259_RS033609361875436421.420.39 c
Aco, aconitate hydrataseB6259_RS057952271621532011.270.94
Idh, isocitrate dehydrogenaseB6259_RS058052372321972911.040.93
Fum, fumarate hydrataseB6259_RS072703101862604371.040.49 c
Pck, phosphoenolpyruvate carboxykinaseB6259_RS0925536815955410310.620.23 c
Hydrogen production
HydE, [FeFe] hydrogenase H-clusterB6259_RS0255011373174441.442.24 b
HydF, [FeFe] hydrogenase H-clusterB6259_RS09690674050241.431.17
Lactate fermentation pathway
D-ldh, D-lactate dehydrogenaseB6259_RS067707688581081.140.95
L-ldh, L-lactate dehydrogenaseB6259_RS09845791111192950.590.44 c
Acetate fermentation pathway
Pta, phosphate acetyltransferaseB6259_RS078306666972713212.09 b2.23 b
Ack, acetate kinaseB6259_RS034302902972882330.881.41
The reverse β-oxidation pathway
AtoB, acetyl-CoA C-acetyltransferaseB6259_RS0636552049909122410773.45 b6.31 b
Hbd, 3-hydroxybutyryl-CoA dehydrogenaseB6259_RS06355630613975141810223.49 b8.59 b
Crt, enoyl-CoA hydrataseB6259_RS06360343473487956473.46 b7.34 b
Bcd1, butyryl-CoA dehydrogenaseB6259_RS0179032783104378730140.761.19
Bcd2, butyryl-CoA dehydrogenaseB6259_RS026004231341660.904.49 b
EtfA, electron transfer flavoprotein subunit alphaB6259_RS0178526572968317525720.731.31
EtfB, electron transfer flavoprotein subunit betaB6259_RS0178039964830435741690.711.31
CoAT, butyryl-CoA: acetate CoA-transferaseB6259_RS0634552114972833301.554.01 b
Fructose fermentation pathway
Ppf, 1-phosphofructokinaseB6259_RS00100276217412562390.35 c7.33 b
Starch and sucrose metabolism
Pyg, glycogen phosphorylaseB6259_RS00300901631211030.661.71
MalQ, 4-alpha-glucanotransferaseB6259_RS078055327055610.854.34 b
Pgm, PhosphoglucomutaseB6259_RS09200951891271130.661.80
Energy conservation
energy-coupling factor transporter ATPaseB6259_RS027901411041171591.040.76
electron transport complex protein RnfAB6259_RS062452301623573620.580.52
Sporulation
stage 0 sporulation proteinB6259_RS002053792792332520.970.82
stage II sporulation protein DB6259_RS09065985996530.971.29
stage III sporulation protein ADB6259_RS039101265487261.671.27
stage IV sporulation protein AB6259_RS04975653058161.421.58
stage V sporulation protein ACB6259_RS09190894677400.991.42
stage V sporulation protein ADB6259_RS09195694166341.051.57
stage V sporulation protein AEB6259_RS005002922262001671.151.02
sporulation transcription factor Spo0AB6259_RS05505127115831060.940.94
sporulation transcriptional regulator SpoIIIDB6259_RS015502131881402070.791.01
sporulation protein YtfJB6259_RS048852911831451591.000.65
Transporter genes
ABC transporter permeaseB6259_RS00445446274272355.17 b1.27
metal ABC transporterB6259_RS00450699628304575.69 b1.52
ABC transporter permeaseB6259_RS026702961304413870.600.40 c
ABC transporter permeaseB6259_RS02665180962582310.620.48 c
carbohydrate ABC transporter permeaseB6259_RS070053312490410.37 c3.51 b
carbohydrate ABC transporter permeaseB6259_RS079057174471400.9012.71 b
carbohydrate ABC transporter permeaseB6259_RS078103922940450.855.48 b
carbohydrate ABC transporter permeaseB6259_RS02030267116391.352.14 b
sugar ABC transporter permeaseB6259_RS0791082117588500.8614.74 b
sugar ABC transporter permeaseB6259_RS033353940126611.305.61 b
sugar ABC transporter permeaseB6259_RS078153619737490.854.34b
sugar ABC transporter permeaseB6259_RS0700031135113380.30 c3.48 b
iron ABC transporter permeaseB6259_RS0032053127877890.6210.05 b
ABC transporter ATP-binding proteinB6259_RS00440504277512395.25 b1.39
ABC transporter ATP-binding proteinB6259_RS00325602032941000.5811.14 b
ABC transporter ATP-binding proteinB6259_RS089001536822332140.583.13 b
ABC transporter ATP-binding proteinB6259_RS0794019040259940.660.42
carbohydrate ABC transporter substrate-binding proteinB6259_RS0791521634342031030.9314.51 b
maltose ABC transporter substrate-binding proteinB6259_RS033453050122371.157.65 b
ABC transporter substrate-binding proteinB6259_RS0782037219134513440.734.63 b
sugar ABC transporter substrate-binding proteinB6259_RS02005309329480.922.29 b
peptide ABC transporter substrate-binding proteinB6259_RS085155378983690.48 c0.28 c
peptide ABC transporter substrate-binding proteinB6259_RS026851385819144222220.850.50 c
ABC transporter ATP-binding proteinB6259_RS026602381193693200.580.45 c
ABC transporter ATP-binding proteinB6259_RS07940190582591660.660.42 c
PTS fructose transporter subunit IICB6259_RS00095372211712734850.37 c3.87 b
PTS glucose transporter subunit IIAB6259_RS0928048426012005170.37 c0.62
PTS β-glucoside transporter subunit IIABCB6259_RS01415817601341410.544.70 b
PTS mannitol transporter subunit IICBAB6259_RS00370298919441.262.34 b
ferrous iron transport protein BB6259_RS038804713895311500.812.72 b

aData presented as mean of independent triplicates.

bSignificantly upregulated (FC ≥ 2.0, p < 0.05).

cSignificantly downregulated (FC ≤ 0.5, p < 0.05).



Figure 5. The overview of the central metabolic pathway in strain CPB6 with fold changes (FCs) of the expression of genes. The number in parentheses represents the FC of TPM between the lactate supplemented cells vs. control cells; the first and the second numbers in the same parentheses represent the gene expression FC in the growth and stationary phases, respectively. Black solid lines symbolize enzymatic reactions. Red dashed lines mark enzymatic reactions for which corresponding enzymes are probably not encoded in strain CPB6.

Two ldh genes (B6259_RS09845 and RS06770), encoding L-lactate dehydrogenase and D-lactate dehydrogenase, were detected in strain CPB6 transcriptome, respectively. The two ldh genes were expressed at low levels in the lactate-supplemented cells and control cells (Table 3), and there was no significant difference in the expression level between the two groups. The gene encoding pyruvate: ferredoxin (flavodoxin) oxidoreductase (Pfor, B6259_RS09135) was upregulated by 1.83- and 3.26-fold (p < 0.05) in the lactate supplemented cells than in control cells during the growth and stationary phases, respectively.

Expression of Butyrate- and CA-Producing Genes

The enzymes involved in the butyrate formation include acetyl-CoA acetyltransferase (AtoB), 3-hydroxybutyryl-CoA dehydrogenase (Hbd), enoyl-CoA hydratase (Crt), NAD-dependent butyryl-CoA dehydrogenase/Electron transfer flavoprotein complex (Bcd/Etf complex) and butyryl-CoA: acetate CoA transferase (CoAT) [7, 16]. In the present study, genes encoding AtoB (B6259_RS06365), Crt (B6259_RS06360) and Hbd (B6259_RS06355) maintained at very high expression levels (TPM>3000) in the lactate-supplemented cells, and were upregulated by 3.5-8.6 folds (p < 0.05) compared with control cells without lactate. Bcd (B6259_RS01790) was expressed at a very high level in the lactate-supplemented cells and control cells throughout the growth and stationary phases, but there was no difference between two groups. EtfAB (alpha unit, B6259_RS01785 and beta unit, B6259_RS01780) showed the Bcd-like expression profile. Another Bcd (B6259_RS02600) was expressed at relatively low level at the growth phase, but its expression was upregulated 4.5-fold (p < 0.05) at the stationary phase. One CoAT gene (B6259_RS06345) showed high expression level in the two cultures (TPM>150), and it was markedly upregulated by 4-fold (p < 0.05) in the lactate-supplemented cells than in the control at the stationary phase.

Additionally, the gene encoding phosphate acetyltransferase (Pta, B6259_RS07830) was remarkably upregulated (p < 0.05) at the two phases with the addition of lactate (Table 3). The expression of acetate kinase (Ack, B6259_RS03430) showed no change (p < 0.05) in response to the addition of lactate. The two genes can produce acetate from acetyl-CoA (sourced from glycolysis or lactate oxidation), contributing to a dynamic equilibrium of acetate in cultures to some extent. By including the production of H2 and CO2 into the loop, it could provide a whole picture for carbon balance for the substrate utilization and cell biomass production. Unfortunately, the production of H2 and CO2 was not monitored in this study. In the future studies, this should be taken into consideration for improvement.

Expression of Putative ABC Transporter and Sporulation Genes

As shown in Table 3 and Fig. 5, sporulation genes showed similar expression patterns in the lactate-supplemented cells and control cells, e.g., spo0, spoIIID, spoVAE, and spoYtfJ, were induced to high expression at the growth and stationary phases, while spoIID, spoIIIAD, spoIVA, spoVAC, and spoVAD were expressed at low or moderate levels.

Notably, most genes for ABC transporter and substrate-binding protein (SBP) were no significant changes (p > 0.05) in the two groups at growth phase, except two ABC transporter genes (B6259_RS00445, B6259_RS00450), and one SBP gene (B6259_RS00440) which were upregulated by more than 2-fold (p < 0.05, Table 3) with the addition of lactate. However, many of these genes were markedly upregulated at the stationary phase (p <0.05). Specially, B6259_RS07905, _RS07910, _RS00320, _RS00325 and B6259_RS07915 were increased over 10-fold (p < 0.05) in the lactate-supplemented cells compared with control cells.

In addition, four phosphotransferase system (PTS) transporter genes, including PTS fructose transporter subunit IIC (B6259_RS00095), PTS glucose transporter subunit IIA (B6259_RS09280), PTS β-glucoside transporter subunit IIABC (B6259_RS01415), and PTS mannitol transporter subunit IICBA (B6259_RS00370), were detected in the transcriptome of strain CPB6. Genes encoding PTS fructose and glucose transporters were expressed at high levels under both groups, but the two genes were significantly downregulated (p < 0.05) in the lactate-supplemented cells than in control cells at the growth phase, indicating that the two PTS transporters are sensitive to lactate supplementation. Moreover, the three PTS transporter genes (B6259_RS0095, RS01415 and RS00370) and one ferrous iron transporter gene (B6259_RS03880) were upregulated by 2- to 4-fold at stationary phase (p <0.05, Table 3).

RT-qPCR Verification

The fold-changes in expression of 5 genes (Pfor, AtoB, Hbd, Crt, and CoAT) were measured by RT-qPCR with 16S rRNA as reference gene. The five genes were significantly upregulated in the lactate-supplemented cells compared with control cells (Fig. S5). The RT-qPCR data mainly matched the RNA-Seq of 5 selected genes based FC values, which indicated that our RNA-Seq result is accurate and the conclusion from RNA-Seq should be reliable.

Discussion

Lactate is a major end-product of glycolysis or energy substrate for many anaerobic bacteria such as Acetobacterium woodii, C. botulinum and Desulfotomaculum reducens [26, 27]. The recent studies show that lactate as electron donor can be transformed into CA in either mixed anaerobes [3, 12, 13], or in the pure anaerobic bacterium [14], but the biochemistry of lactate oxidation to CA and underlying regulatory mechanisms are still obscure. Lactate dehydrogenase (LDH) is the key enzyme in lactate production from pyruvate. LDH catalyzes the reaction converts pyruvate to lactate or the reverse reaction that converts lactate to pyruvate coupled to NADH/NAD+ redox [28]. Generally, bacteria that grow on lactate as sole energy and carbon source have a serious energetic problem because of the high redox potential of the pyruvate/lactate pair. Recently, a novel mode of lactate metabolism is proposed for strictly anaerobic bacteria [27], in which the LDH/ Etf complex uses flavin-based electron confurcation to drive endergonic lactate oxidation with NAD+ as oxidant at the expense of simultaneous exergonic electron flow from reduced ferredoxin. And that, the lactate metabolism in these strictly anaerobic bacteria is negatively regulated by the transcriptional regulator [29]. In this study, the upregulation of LDHs was not observed with the addition of lactate, indicating that lactate supplementation does not trigger increased expression of LDH. Moreover, the L-ldh (B6259_RS09845) heterologously expressed in Escherichia coli BL21 (DE3) exhibits high LDH activity of driving endergonic lactate oxidation in the absence of Fd2−, and LDH oxidative activity predominates over reductive activity [30]. These results indicate that the lactate metabolism in strain CPB6 is different from other strict anaerobes. It warrants further investigation concerning the detailed regulatory mechanism of lactate oxidation in strain CPB6.

The bioproduction of CA is a well-known chain elongation process from acetate (C2) to butyrate (C4), and then to caproate (C6) via the reverse β-oxidation pathway [6]. The conversion of C2 to C4 is well understood, but little is known about the key enzymes responsible for caproyl-CoA or CA synthesis. Enzymes (e.g., AtoB, Crt, Hbd, Bcd/EtfAB complex and CoAT) responsible for butyrate synthesis via the reverse β-oxidation are assumed to have the function in the formation of caproyl-CoA and CA [7]. However, C. tyrobutyricum, which contains these genes, only produce butyric acid instead of CA [31], while C. kluyveri and strain CPB6, which contain these genes, can further elongate C4 to C6 [7, 15]. It indicates that there are differences in structure and function between these genes from different organisms. In this study, the three genes (AtoB, Crt, Hbd) responsible for the conversion of acetyl-CoA to crotonyl-CoA were markedly upregulated (p < 0.05) throughout the exponential and stationary phases with the addition of lactate. However, the Bcd (B6259_RS02600) and CoAT (B6259_RS06345) genes were only significantly upregulated at the stationary phase. Provided that the rate of CA accumulation was significantly higher during the stationary phase than the growth phase, the two genes are likely involved in the formation of caproyl-CoA and CA, The CoAT is the key enzyme responsible for the last step of the butyrate formation [31]. Theoretically, high-level expression of the CoAT gene should result in the accumulation of butyric acid, but significant accumulation of CA instead of butyric acid was observed in the lactate-supplemented cultures, suggesting that the CoAT prefers to convert caproyl-CoA to caproate than butyryl-CoA to butyrate. This speculate was verified by expression of the CoAT (B6259_RS06345) in E. coli BL21 (DE3). This CoAT protein could catalyze the conversion of both butyryl-CoA to butyrate and caproyl-CoA to caproate, but its catalytic efficiency with caproyl-CoA as the substrate was 3.8 times higher than that with butyryl-CoA [32]. Thus, the CoAT is a key gene that determines whether the final product is butyric acid or caproic acid.

Some bacteria develop into highly resistant spores to protect their genome and cell from certain doom when living conditions become intolerable [33]. It ensures bacterial survival under adverse environmental conditions. Sporulation in Clostridium spp. is ordinarily not triggered by starvation but by cessation of growth in the presence of excess carbon source or exposure to oxygen [33]. The two most critical factors involved in the shift to solventogenesis, a decrease in external pH and accumulation of acidic fermentation products, are generally assumed to be associated with the initiation of sporulation in Clostridium spp., to some extent [34]. Recent studies show that the sporulation events are uncoupled from the induction of solventogenesis in C. beijerinckii [35]. In this study, the sporulation genes showed no significant difference between the lactate supplemented cells and control cells, indicating that the sporulation events are not associated with the production of CA in strain CPB6 until the stationary phase. This may be because low concentrations of CA (1,717 mg/l) are not sufficient to initiate sporulation for strain CPB6.

ABC transporters are ubiquitous membrane proteins that couple the transport of diverse substrates across cellular membranes to the hydrolysis of ATP [36]. ABC transporters are generally divided into importers and exporters on the basis of the polarity of solute movement. ABC importers are found mostly in bacteria and are crucial in mediating the uptake of solutes including sugar, metal ions, and vitamins [37]. ABC transporters play important roles in response to lactate stress. High expression of ABC transporter genes may be of benefit to organisms to maintain intercellular homeostasis under lactate stress [38] or increase intracellular ATP concentrations to protect cells against acidic damage in the initial stage of acid stress [39]. Here, nine ABC transporter genes and six SBP genes were markedly upregulated at the stationary phase. Specially, B6259_RS07905, _RS07910, _RS00320, _RS00325, and B6259_RS07915 were increased over 10-fold in the lactate supplemented cells compared to control cells, demonstrating that these genes are associated with the extrusion of CA from the cell, and the maintenance of osmotic homeostasis in cytoplasm [40].

PTS is a multiple-component carbohydrate uptake system that drives specific saccharides across the bacterial inner membrane while simultaneously catalyzing sugar phosphorylation [41]. Five distinct subfamilies of proteins related to PTS have been identified within the glucose superfamily: the lactose family, the glucose family, the β-glucoside family, the mannitol family, and the fructose family [42]. In this study, genes encoding PTS fructose, β-glucoside, and mannitol transporters were all strikingly upregulated in the lactate-supplemented cells than in control cells at the stationary phase, suggesting that these transporters may be involved in the extrusion of intracellular CA in strain CPB6, similar to the role of ABC transporters [43].

In sum, this study showed that lactate supplementation induced earlier CA production, higher CA titer, and productivity. The gene transcriptional profiles based on RNA-Seq demonstrated that supplemented lactate promoted CA production by altering the expression patterns of genes responsible for crucial metabolic pathways. Specifically, 5 genes (AtoB, Hbd, Crt, Bcd/EtfAB, and CoAT) involved in the reverse β-oxidation pathway, 11 genes encoding ABC transporter, 6 SBP genes, and 4 PTS transporter genes showed high correlation with utilization of lactate and CA production. The findings presented herein provide unique insights into the metabolic effects of lactate on CA production at the gene regulation level.

Supplemental Materials

Acknowledgments

This work was supported by the Natural Science Foundation of China (31770090), Sichuan Science and Technology Support Program (2021YJ0022), and the Open-foundation project of CAS Key Laboratory of Environmental and Applied Microbiology (KLCAS-2017-01).

Conflict of Interest


The authors have no financial conflicts of interest to declare.

Fig 1.

Figure 1.Fermentation kinetics of Ruminococcaceae bacterium CPB6. (A) Cell growth profiles. Time points for taking samples subjected to RNA-Seq are indicated with red vertical arrows. L: fermentation with lactate supplementation; C: control fermentation without lactate supplementation; (B) Sugar consumption and metabolites production during the fermentation with the supplementation of lactate; (C) Sugar consumption and metabolites production during the control fermentation. Values represent the mean of the biological triplicates and error bars represent the standard deviations.
Journal of Microbiology and Biotechnology 2021; 31: 1533-1544https://doi.org/10.4014/jmb.2107.07009

Fig 2.

Figure 2.Frequency histogram of transcripts from the RNA-Seq results. L: the lactate supplemented cells; C: control cells without lactate supplementation; Number 1 and 2 represented the growth phase and stationary phase, respectively. The diagram shows the distribution of the number of genes expressed at different transcripts per million (TPM) levels. The percentage value above each bar indicates the genes at the specific expression level accounting for the proportion of the total number of genes. The ‘*’ mark indicates that significantly different frequencies (i.e., numbers of genes) were observed between the two RNA-Seq data sets from the lactate-supplemented fermentation (L) vs. the control (C), respectively.
Journal of Microbiology and Biotechnology 2021; 31: 1533-1544https://doi.org/10.4014/jmb.2107.07009

Fig 3.

Figure 3.Annotation of genes using Gene Ontology (GO) in the transcriptome of strain CPB6. Left axis: the proportion of genes falling into each GO category; right axis: the number of genes falling into each GO category.
Journal of Microbiology and Biotechnology 2021; 31: 1533-1544https://doi.org/10.4014/jmb.2107.07009

Fig 4.

Figure 4.Venn diagram of the numbers of differentially expressed genes (DEGs) trigger by substrate type (plus/ minus lactate) vs growth stage (stationary phase vs growth phase) (A), the numbers of DEGs trigger by substrate type vs growth stage (B). The overlap of circles was defined as genes affected by both substrate type and growth stage.
Journal of Microbiology and Biotechnology 2021; 31: 1533-1544https://doi.org/10.4014/jmb.2107.07009

Fig 5.

Figure 5.The overview of the central metabolic pathway in strain CPB6 with fold changes (FCs) of the expression of genes. The number in parentheses represents the FC of TPM between the lactate supplemented cells vs. control cells; the first and the second numbers in the same parentheses represent the gene expression FC in the growth and stationary phases, respectively. Black solid lines symbolize enzymatic reactions. Red dashed lines mark enzymatic reactions for which corresponding enzymes are probably not encoded in strain CPB6.
Journal of Microbiology and Biotechnology 2021; 31: 1533-1544https://doi.org/10.4014/jmb.2107.07009

Table 1 . Summary of RNA-Seq sequencing and data analysis results..

Sample NameL1L2C1C2

abcabcabcabc
Total reads229827921861453618087962168816481684405815343814186841121910814819099082199092582303212018662552
No. of read mapped226848581839070917865180167133191660672615098988184372611889387318905208196316862257287318285805
Ratio of reads mapped (%)98.798.898.779998.5998.498.6898.8898.9898.6198.0197.98
No. of unique reads mapped223390681791595417559600165400601632476814862898180503161850569718508661192472562218727217856892
No. of genes with detectable expression196919681968196819691968196819681968196819691969
Range in expression levels (TPM)8.3 - 2.7×1048.0-1.7×10411.5-1.7×1043.2-5.3×10426.4 -3.7×1046.6 -7.3×1044.3-2.0×1043.8-1.8×1044.1-1.9×1045.2-2.4×10410.8-1.8×10424.5-1.9×104

L1: cell culture with lactate supplementation from the growth phase;.

L2: cell culture with lactate supplementation from the stationary phase;.

C1: Control culture without lactate supplementation from the growth phase;.

C2: Control culture without lactate supplementation from the stationary phase. a and c represented the biological triplicate samples..


Table 2 . The differentially expressed genes in culture with/without lactate supplementation during the growth phase..

No.Gene_IDGene nameGene descriptionTPMFC (L1/C1)P-value

C1L1
15 upregulated genes (FC ≥ 2.0); all statistically significant (P < 0.05)
1B6259_RS06365AtoBacetyl-CoA C-acetyltransferase122452043.457.9E-39
2B6259_RS06360Crtenoyl-CoA hydratase79534343.462.4E-33
3B6259_RS06355Hbd3-hydroxybutyryl-CoA dehydrogenase141863063.492.3E-27
4B6259_RS07830Ptaphosphate acetyltransferase2716662.094.3E-24
5B6259_RS00440-methionine ABC transporter ATP-binding protein515045.256.2E-18
6B6259_RS00450-metal ABC transporter substrate-binding protein306995.695.9E-15
7B6259_RS00445-ABC transporter permease274465.176.9E-14
8B6259_RS08190CysKcysteine synthase A39074264.076.4E-10
9B6259_RS08440-unknown function104835982.335.2E-06
10B6259_RS06010-hypothetical protein21892.528.1E-06
11B6259_RS07140-hypothetical protein1544702.173.0E-05
12B6259_RS01720CadAcadmium-translocating P-type ATPase22662.163.9E-05
13B6259_RS06870-Hsp20/alpha crystallin family protein31511022.211.6E-04
14B6259_RS00455PepTpeptidase T375762.262.0E-04
15B6259_RS02585Bdhbutanol dehydrogenase822422.043.1E-04
19 downregulated genes (FC ≤ 0.5); all statistically significant (P < 0.05)
1B6259_RS08515-peptide ABC transporter substrate-binding protein98530.481.7E-23
2B6259_RS09280-PTS glucose transporter subunit IIA12004840.375.5E-23
3B6259_RS09735IlvHacetolactate synthase small subunit5643020.489.4E-19
4B6259_RS06995-hypothetical protein276430.202.7E-18
5B6259_RS08565-hypothetical protein143790.502.3E-13
6B6259_RS07000-sugar ABC transporter permease113310.309.2E-13
7B6259_RS01525-unknown function268310100.378.4E-12
8B6259_RS03200-unknown function268310100.378.4E-12
9B6259_RS07010Tagglycosylase144460.349.9E-11
10B6259_RS07005-carbohydrate ABC transporter permease90330.371.1E-09
11B6259_RS01865-DUF2520 domain-containing protein260850.366.7E-09
12B6259_RS01880PanDaspartate 1-decarboxylase4441560.379.5E-09
13B6259_RS01870PanB3-methyl-2-oxobutanoate hydroxymethyltransferase3141050.371.1E-08
14B6259_RS01875Pancpantoate-beta-alanine ligase3501150.371.2E-08
15B6259_RS01760-hypothetical protein8203690.448.9E-08
16B6259_RS02315-basic amino acid ABC transporter substrate-binding protein147790.501.8E-07
17B6259_RS00100FruK1-phosphofructokinase12562760.351.7E-06
18B6259_RS00095-PTS fructose transporter subunit IIC12733720.371.8E-06
19B6259_RS00105-DeoR/GlpR transcriptional regulator13042780.363.6E-06

L1: lactate-supplemented cells at growth phase.

C1: no-lactate-supplemented cells (control) at growth phase.


Table 3 . The differentially expressed genes within the important metabolic pathways in culture with/without lactate supplementation..

Functional descriptionGene_IDTPM of genes from culture with lactate supplementationaTPM of genes from the ControlaRNA relative fold change (Treatment/Control)

12h18h12h18h12h18h
Glycolysis
PTS-Glc-EIIA, PTS glucose transporter subunit IIAB6259_RS0928048426012005170.37 c0.62
GlgC, glucose-1-phosphate adenylyltransferaseB6259_RS0903515313232362410.574.58 b
GlgB, 1,4-alpha-glucan branching enzymeB6259_RS090401947452362010.723.42 b
sugar phosphate isomerase/epimeraseB6259_RS065001811751502331.050.88
Pgm, phosphoglucomutaseB6259_RS09200951891271130.661.80
Gpi, glucose-6-phosphate isomeraseB6259_RS0482520151789183318180.961.12
Pfk, phosphofructokinaseB6259_RS06095426975805160.660.23 c
Aldo, fructose-bisphosphate aldolaseB6259_RS004157494028008910.830.57
Tpi, triose-phosphate isomeraseB6259_RS091052242293154930.650.58
GapA, glyceraldehyde phosphate dehydrogenaseB6259_RS0905053224284479077320.980.70
Pgk, phosphoglycerate kinaseB6259_RS0910052352470510290.670.65
GpmI, 2,3-bisphosphoglycerate-independent phosphoglycerate mutaseB6259_RS091102032002844690.660.55
Eno, phosphopyruvate hydrataseB6259_RS04810416530521.141.46
PK, pyruvate kinaseB6259_RS023352541022932280.771.46
Central pyruvate metabolism
PpdK, pyruvate phosphate dikinaseB6259_RS001201301823116315350.990.69
Pfor, pyruvate: ferredoxin (flavodoxin) oxidoreductaseB6259_RS0913543294382204412251.833.26 b
Pck, phosphoenolpyruvate carboxykinaseB6259_RS0925536815955410310.620.23 c
PflD, formate C-acetyltransferaseB6259_RS09900981881074710.830.54
Adh, alcohol dehydrogenaseB6259_RS031002001161631591.070.84
Incomplete TCA cycle
Cs, citrate synthase, citrate lyaseB6259_RS033609361875436421.420.39 c
Aco, aconitate hydrataseB6259_RS057952271621532011.270.94
Idh, isocitrate dehydrogenaseB6259_RS058052372321972911.040.93
Fum, fumarate hydrataseB6259_RS072703101862604371.040.49 c
Pck, phosphoenolpyruvate carboxykinaseB6259_RS0925536815955410310.620.23 c
Hydrogen production
HydE, [FeFe] hydrogenase H-clusterB6259_RS0255011373174441.442.24 b
HydF, [FeFe] hydrogenase H-clusterB6259_RS09690674050241.431.17
Lactate fermentation pathway
D-ldh, D-lactate dehydrogenaseB6259_RS067707688581081.140.95
L-ldh, L-lactate dehydrogenaseB6259_RS09845791111192950.590.44 c
Acetate fermentation pathway
Pta, phosphate acetyltransferaseB6259_RS078306666972713212.09 b2.23 b
Ack, acetate kinaseB6259_RS034302902972882330.881.41
The reverse β-oxidation pathway
AtoB, acetyl-CoA C-acetyltransferaseB6259_RS0636552049909122410773.45 b6.31 b
Hbd, 3-hydroxybutyryl-CoA dehydrogenaseB6259_RS06355630613975141810223.49 b8.59 b
Crt, enoyl-CoA hydrataseB6259_RS06360343473487956473.46 b7.34 b
Bcd1, butyryl-CoA dehydrogenaseB6259_RS0179032783104378730140.761.19
Bcd2, butyryl-CoA dehydrogenaseB6259_RS026004231341660.904.49 b
EtfA, electron transfer flavoprotein subunit alphaB6259_RS0178526572968317525720.731.31
EtfB, electron transfer flavoprotein subunit betaB6259_RS0178039964830435741690.711.31
CoAT, butyryl-CoA: acetate CoA-transferaseB6259_RS0634552114972833301.554.01 b
Fructose fermentation pathway
Ppf, 1-phosphofructokinaseB6259_RS00100276217412562390.35 c7.33 b
Starch and sucrose metabolism
Pyg, glycogen phosphorylaseB6259_RS00300901631211030.661.71
MalQ, 4-alpha-glucanotransferaseB6259_RS078055327055610.854.34 b
Pgm, PhosphoglucomutaseB6259_RS09200951891271130.661.80
Energy conservation
energy-coupling factor transporter ATPaseB6259_RS027901411041171591.040.76
electron transport complex protein RnfAB6259_RS062452301623573620.580.52
Sporulation
stage 0 sporulation proteinB6259_RS002053792792332520.970.82
stage II sporulation protein DB6259_RS09065985996530.971.29
stage III sporulation protein ADB6259_RS039101265487261.671.27
stage IV sporulation protein AB6259_RS04975653058161.421.58
stage V sporulation protein ACB6259_RS09190894677400.991.42
stage V sporulation protein ADB6259_RS09195694166341.051.57
stage V sporulation protein AEB6259_RS005002922262001671.151.02
sporulation transcription factor Spo0AB6259_RS05505127115831060.940.94
sporulation transcriptional regulator SpoIIIDB6259_RS015502131881402070.791.01
sporulation protein YtfJB6259_RS048852911831451591.000.65
Transporter genes
ABC transporter permeaseB6259_RS00445446274272355.17 b1.27
metal ABC transporterB6259_RS00450699628304575.69 b1.52
ABC transporter permeaseB6259_RS026702961304413870.600.40 c
ABC transporter permeaseB6259_RS02665180962582310.620.48 c
carbohydrate ABC transporter permeaseB6259_RS070053312490410.37 c3.51 b
carbohydrate ABC transporter permeaseB6259_RS079057174471400.9012.71 b
carbohydrate ABC transporter permeaseB6259_RS078103922940450.855.48 b
carbohydrate ABC transporter permeaseB6259_RS02030267116391.352.14 b
sugar ABC transporter permeaseB6259_RS0791082117588500.8614.74 b
sugar ABC transporter permeaseB6259_RS033353940126611.305.61 b
sugar ABC transporter permeaseB6259_RS078153619737490.854.34b
sugar ABC transporter permeaseB6259_RS0700031135113380.30 c3.48 b
iron ABC transporter permeaseB6259_RS0032053127877890.6210.05 b
ABC transporter ATP-binding proteinB6259_RS00440504277512395.25 b1.39
ABC transporter ATP-binding proteinB6259_RS00325602032941000.5811.14 b
ABC transporter ATP-binding proteinB6259_RS089001536822332140.583.13 b
ABC transporter ATP-binding proteinB6259_RS0794019040259940.660.42
carbohydrate ABC transporter substrate-binding proteinB6259_RS0791521634342031030.9314.51 b
maltose ABC transporter substrate-binding proteinB6259_RS033453050122371.157.65 b
ABC transporter substrate-binding proteinB6259_RS0782037219134513440.734.63 b
sugar ABC transporter substrate-binding proteinB6259_RS02005309329480.922.29 b
peptide ABC transporter substrate-binding proteinB6259_RS085155378983690.48 c0.28 c
peptide ABC transporter substrate-binding proteinB6259_RS026851385819144222220.850.50 c
ABC transporter ATP-binding proteinB6259_RS026602381193693200.580.45 c
ABC transporter ATP-binding proteinB6259_RS07940190582591660.660.42 c
PTS fructose transporter subunit IICB6259_RS00095372211712734850.37 c3.87 b
PTS glucose transporter subunit IIAB6259_RS0928048426012005170.37 c0.62
PTS β-glucoside transporter subunit IIABCB6259_RS01415817601341410.544.70 b
PTS mannitol transporter subunit IICBAB6259_RS00370298919441.262.34 b
ferrous iron transport protein BB6259_RS038804713895311500.812.72 b

aData presented as mean of independent triplicates.

bSignificantly upregulated (FC ≥ 2.0, p < 0.05).

cSignificantly downregulated (FC ≤ 0.5, p < 0.05).


References

  1. Brodowski F, Duber A, Zagrodnik R, Oleskowicz-Popiel P. 2020. Co-production of hydrogen and caproate for an effective bioprocessing of waste. Bioresour. Technol. 318: 123895.
    Pubmed CrossRef
  2. Roghair M, Liu Y, Adiatma JC, Weusthuis RA, Bruins ME, Buisman CJN, et al. 2018. Effect of n-Caproate concentration on chain elongation and competing processes. ACS Sustain Chem. Eng. 6: 7499-7506.
    Pubmed KoreaMed CrossRef
  3. Nzeteu CO, Trego AC, Abram F, O'Flaherty V. 2018. Reproducible, high-yielding, biological caproate production from food waste using a single-phase anaerobic reactor system. Biotechnol. Biofuels 11: 108.
    Pubmed KoreaMed CrossRef
  4. Roghair M, Liu Y, Strik D, Weusthuis RA, Bruins ME, Buisman CJN. 2018. Development of an effective chain elongation process from acidified food waste and ethanol into n-Caproate. Front. Bioeng. Biotechnol. 6: 50.
    Pubmed KoreaMed CrossRef
  5. Yang PX, Leng L, Tan GYA, Dong CY, Leu SY, Chen WH, et al. 2018. Upgrading lignocellulosic ethanol for caproate production via chain elongation fermentation. Int. Biodeter. Biodegr. 135: 103-109.
    CrossRef
  6. Spirito CM, Richter H, Rabaey K, Stams AJ, Angenent LT. 2014. Chain elongation in anaerobic reactor microbiomes to recover resources from waste. Curr. Opin. Biotechnol. 27: 115-122.
    Pubmed CrossRef
  7. Seedorf H, Fricke WF, Veith B, Bruggemann H, Liesegang H, Strittimatter A, et al. 2008. The genome of Clostridium kluyveri, a strict anaerobe with unique metabolic features. Proc. Natl. Acad. Sci. USA 105: 2128-2133.
    Pubmed KoreaMed CrossRef
  8. Steinbusch KJJ, Hamelers HVM, Plugge CM, Buisman CJN. 2011. Biological formation of caproate and caprylate from acetate: fuel and chemical production from low grade biomass. Energy Environ. Sci. 4: 216-224.
    CrossRef
  9. Chen WS, Ye Y, Steinbusch KJJ, Strik DPBTB, Buisman CJN. 2016. Methanol as an alternative electron donor in chain elongation for butyrate and caproate formation. Biomass Bioenerg. 93: 201-208.
    CrossRef
  10. Kenealy WR, Waselefsky DM. 1985. Studies on the substrate range of Clostridium-Kluyveri - the use of propanol and succinate. Arch. Microbiol. 141: 187-194.
    CrossRef
  11. Jeon BS, Kim BC, Um Y, Sang BI. 2010. Production of hexanoic acid from D-galactitol by a newly isolated Clostridium sp. BS-1. Appl. Microbiol. Biotechnol. 88: 1161-1167.
    Pubmed CrossRef
  12. Kucek LA, Nguyen M, Angenent LT. 2016. Conversion of l-lactate into n-caproate by a continuously fed reactor microbiome. Water Res. 93: 163-171.
    Pubmed CrossRef
  13. Zhu X, Tao Y, Liang C, Li X, Wei N, Zhang W, et al. 2015. The synthesis of n-caproate from lactate: a new efficient process for medium-chain carboxylates production. Sci. Rep. 5: 14360.
    Pubmed KoreaMed CrossRef
  14. Zhu X, Zhou Y, Wang Y, Wu T, Li X, Li D, et al. 2017. Production of high-concentration n-caproic acid from lactate through fermentation using a newly isolated Ruminococcaceae bacterium CPB6. Biotechnol. Biofuels 10: 102.
    Pubmed KoreaMed CrossRef
  15. Wang H, Li X, Wang Y, Tao Y, Lu S, Zhu X, et al. 2018. Improvement of n-caproic acid production with Ruminococcaceae bacterium CPB6: selection of electron acceptors and carbon sources and optimization of the culture medium. Microb. Cell Fact. 17: 99.
    Pubmed KoreaMed CrossRef
  16. Tao Y, Zhu XY, Wang H, Wang Y, Li XZ, Jin H, et al. 2017. Complete genome sequence of Ruminococcaceae bacterium CPB6: A newly isolated culture for efficient n-caproic acid production from lactate. J. Biotechnol. 259: 91-94.
    Pubmed CrossRef
  17. Sedlar K, Koscova P, Vasylkivska M, Branska B, Kolek J, Kupkova K, et al. 2018. Transcription profiling of butanol producer Clostridium beijerinckii NRRL B-598 using RNA-Seq. BMC Genomics. 19: 415.
    Pubmed KoreaMed CrossRef
  18. Zararsiz G, Goksuluk D, Korkmaz S, Eldem V, Zararsiz GE, Duru IP, et al. 2017. A comprehensive simulation study on classification of RNA-Seq data. PLoS One 12: e0182507.
    Pubmed KoreaMed CrossRef
  19. Erlich Y, Mitra PP, delaBastide M, McCombie WR, Hannon GJ. 2008. Alta-Cyclic: a self-optimizing base caller for next-generation sequencing. Nat. Methods 5: 679-682.
    Pubmed KoreaMed CrossRef
  20. Cock PJ, Fields CJ, Goto N, Heuer ML, Rice PM. 2010. The sanger FASTQ file format for sequences with quality scores, and the Solexa/Illumina FASTQ variants. Nucleic Acids Res. 38: 1767-1771.
    Pubmed KoreaMed CrossRef
  21. Langmead B, Salzberg SL. 2012. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9: 357-359.
    Pubmed KoreaMed CrossRef
  22. Patro R, Mount SM, Kingsford C. 2014. Sailfish enables alignment-free isoform quantification from RNA-seq reads using lightweight algorithms. Nat. Biotechnol. 32: 462-U174.
    Pubmed KoreaMed CrossRef
  23. Kirk DG, Palonen E, Korkeala H, Lindstrom M. 2014. Evaluation of normalization reference genes for RT-qPCR analysis of spo0A and four sporulation sigma factor genes in Clostridium botulinum Group I strain ATCC 3502. Anaerobe 26: 14-19.
    Pubmed CrossRef
  24. Love MI, Huber W, Anders S. 2014. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15: 550.
    Pubmed KoreaMed CrossRef
  25. Riederer A, Takasuka TE, Makino S, Stevenson DM, Bukhman YV, Elsen NL, et al. 2011. Global gene expression patterns in Clostridium thermocellum as determined by microarray analysis of chemostat cultures on cellulose or cellobiose. Appl. Environ. Microbiol. 77: 1243-1253.
    Pubmed KoreaMed CrossRef
  26. Rogatzki MJ, Ferguson BS, Goodwin ML, Gladden LB. 2015. Lactate is always the end product of glycolysis. Front. Neurosci. 9: 22.
    Pubmed KoreaMed CrossRef
  27. Weghoff MC, Bertsch J, Muller V. 2015. A novel mode of lactate metabolism in strictly anaerobic bacteria. Environ. Microbiol. 17: 670-677.
    Pubmed CrossRef
  28. Skory CD. 2000. Isolation and expression of lactate dehydrogenase genes from Rhizopus oryzae. Appl. Environ. Microbiol. 66: 2343-2348.
    Pubmed KoreaMed CrossRef
  29. Schoelmerich MC, Katsyv A, Sung W, Mijic V, Wiechmann A, Kottenhahn P, et al. 2018. Regulation of lactate metabolism in the acetogenic bacterium Acetobacterium woodii. Environ. Microbiol. 20: 4587-4595.
    Pubmed CrossRef
  30. Yang Q, Wei C, Guo S, Liu J, Tao Y. 2020. Cloning and characterization of a L-lactate dehydrogenase gene from Ruminococcaceae bacterium CPB6. World J. Microbiol. Biotechnol. 36: 182.
    Pubmed CrossRef
  31. Lee J, Jang YS, Han MJ, Kim JY, Lee SY. 2016. Deciphering Clostridium tyrobutyricum Metabolism based on the whole-genome sequence and proteome analyses. mBio 7: e00743-16.
    CrossRef
  32. Yang Q, Guo S, Lu Q, Tao Y, Zheng D, Zhou Q, et al. 2021. Butyryl/Caproyl-CoA:Acetate CoA-transferase: cloning, expression and characterization of the key enzyme involved in medium-chain fatty acid biosynthesis. Biosci. Rep. 41: BSR20211135.
    Pubmed KoreaMed CrossRef
  33. Sauer U, Santangelo JD, Treuner A, Buchholz M, Durre P. 1995. Sigma factor and sporulation genes in Clostridium. FEMS Microbiol. Rev. 17: 331-340.
    Pubmed CrossRef
  34. Woods DR, Jones DT. 1986. Physiological responses of Bacteroides and Clostridium strains to environmental stress factors. Adv. Microb. Physiol. 28: 1-64.
    CrossRef
  35. Wang Y, Li XZ, Blaschek HP. 2013. Effects of supplementary butyrate on butanol production and the metabolic switch in Clostridium beijerinckii NCIMB 8052: genome-wide transcriptional analysis with RNA-Seq. Biotechnol. Biofuels 6: 138.
    Pubmed KoreaMed CrossRef
  36. Hollenstein K, Dawson RJ, Locher KP. 2007. Structure and mechanism of ABC transporter proteins. Curr. Opin. Struct. Biol. 17: 412-418.
    Pubmed CrossRef
  37. Cui J, Davidson AL. 2011. ABC solute importers in bacteria. Essays Biochem. 50: 85-99.
    Pubmed CrossRef
  38. Qin J, Wang X, Wang L, Zhu B, Zhang X, Yao Q, et al. 2015. Comparative transcriptome analysis reveals different molecular mechanisms of Bacillus coagulans 2-6 response to sodium lactate and calcium lactate during lactic acid production. PLoS One 10: e0124316.
    Pubmed KoreaMed CrossRef
  39. Zhu Z, Yang J, Yang P, Wu Z, Zhang J, Du G. 2019. Enhanced acid-stress tolerance in Lactococcus lactis NZ9000 by overexpression of ABC transporters. Microb. Cell Fact. 18: 136.
    Pubmed KoreaMed CrossRef
  40. Jones PM, George AM. 2004. The ABC transporter structure and mechanism: perspectives on recent research. Cell Mol. Life Sci. 61: 682-699.
    Pubmed CrossRef
  41. Jason G, McCoy, Elena J. Levin, Zhou M. 2015. Structural insight into the PTS sugar transporter EIIC. Biochim. Biophys. Acta 1850: 577-585.
    Pubmed KoreaMed CrossRef
  42. Nguyen TX, Yen MR, Barabote RD, Saier MH Jr. 2006. Topological predictions for integral membrane permeases of the phosphoenolpyruvate:sugar phosphotransferase system. J. Mol. Microbiol. Biotechnol. 11: 345-360.
    Pubmed CrossRef
  43. Nikaido H, Hall JA. 1998. Overview of bacterial ABC transporters. Methods Enzymol. 292: 3-20.
    CrossRef