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  • Research note
  • Open Access

The transcriptome response of the ruminal methanogen Methanobrevibacter ruminantium strain M1 to the inhibitor lauric acid

  • 1,
  • 2, 3,
  • 4,
  • 1,
  • 1,
  • 4, 5 and
  • 1, 6Email author
Contributed equally
BMC Research Notes201811:135

https://doi.org/10.1186/s13104-018-3242-8

Received: 30 December 2017

Accepted: 9 February 2018

Published: 17 February 2018

Abstract

Objective

Lauric acid (C12) is a medium-chain fatty acid that inhibits growth and production of the greenhouse gas methane by rumen methanogens such as Methanobrevibacter ruminantium. To understand the inhibitory mechanism of C12, a transcriptome analysis was performed in M. ruminantium strain M1 (DSM 1093) using RNA-Seq.

Results

Pure cell cultures in the exponential growth phase were treated with 0.4 mg/ml C12, dissolved in dimethyl sulfoxide (DMSO), for 1 h and transcriptomic changes were compared to DMSO-only treated cells (final DMSO concentration 0.2%). Exposure to C12 resulted in differential expression of 163 of the 2280 genes in the M1 genome (maximum log2-fold change 6.6). Remarkably, C12 hardly affected the expression of genes involved in methanogenesis. Instead, most affected genes encode cell-surface associated proteins (adhesion-like proteins, membrane-associated transporters and hydrogenases), and proteins involved in detoxification or DNA-repair processes. Enrichment analysis on the genes regulated in the C12-treated group showed a significant enrichment for categories ‘cell surface’ and ‘mobile elements’ (activated by C12), and for the categories ‘regulation’ and ‘protein fate’ (represssed). These results are useful to generate and test specific hypotheses on the mechanism how C12 affects rumen methanogens.

Keywords

  • Methanobrevibacter ruminantium
  • Methanogenesis
  • Fatty acid
  • Rumen
  • Gene expression
  • Lauric acid

Introduction

Ruminal methane-producing archaea acquire attention because ruminant livestock is estimated as the most important source of anthropogenic emission of the greenhouse gas methane [1]. Among the most-promising anti-methanogenic compounds are two medium chain fatty acids (MCFA), lauric acid (C12) and myristic acid (C14), which were shown to inhibit methanogenesis in vivo when supplemented to the diet of ruminants [24], in vitro in rumen fluid [5] and in methanogenic cultures [6]. MCFA cause leakage of K+ ions and decrease survival of Methanobrevibacter ruminantium, a dominant methanogen species in the rumen [6, 7]. Further, MCFA killed some, but not all methanogen cells, which implies that the cells may be capable to react to fatty acid-caused stress. In search of the mode of action, we investigated the transcriptional response of M. ruminantium to exposure of C12 in culture.

Main text

Methods

Experimental design

Methanobrevibacter ruminantium (strain M1, DSM 1093; ‘Deutsche Sammlung von Mikroorganismen und Zellkulturen’ (DSMZ), Braunschweig, Germany) was cultivated anaerobically in 50 ml of modified Methanobacterium medium (DSMZ No. 1523) in 116 ml bottles under a CO2/H2 (0.2:0.8) atmosphere at 150 kPa and at 39 °C in an incubation shaker as described previously [6]. Growth of the cultures was monitored by recording optical density at 600 nm and by methane (CH4) formation after 24, 48, 60 and 61 h. The culture was inoculated with 5 ml of an exponentially growing pre-culture (OD600 ~ 0.64) to 45 ml of medium. Cell survival was detected with the LIVE/DEAD BacLight Bacterial Viability Kit for microscopy and quantitative assays (Kit L7012; Invitrogen GmbH, Darmstadt, Germany) [6]. Lauric acid (≥ 97% purity) was obtained from Sigma-Aldrich (Buchs, Switzerland), and a stock solution with 200 mg/ml was prepared by dissolving the C12 in sterile dimethyl sulfoxide (DMSO) (Sigma-Aldrich), a commonly used solvent for water-insoluble substances [8]. After 60 h of incubation, when cells reached the exponential phase, three bottles were supplemented with 0.1 ml of the C12 stock solution to reach a final concentration of 0.4 mg C12/ml (treatment group), three bottles were supplemented with 0.1 ml of DMSO (final concentration: 0.2%) (control group), and three bottles received no supplement (blank group). The concentration of C12 and the exposure time of 1 h chosen were in a range where most cells remained alive and where CH4 formation was clearly but not completely inhibited. It was verified that, at 61 h of incubation, CH4 formation rates and proportion of living cells did not differ between DMSO-exposed control cultures (measured: 0.71 ± 0.03 µmol/ml × h and 97 ± 0.3%, respectively) and untreated blank cultures (0.74 ± 0.04 µmol/ml × h and 99 ± 1.2%). At 61 h, i.e. after 1 h of exposure to C12, CH4 formation rates in the hour after exposure were suppressed by 40 ± 6% compared to the control cultures (P < 0.05), and cell viability was reduced down to 71 ± 1.8% when compared to the control cultures (P < 0.05). At this time point, three samples per group (each 50 ml of culture) were anaerobically collected at 4 °C after centrifugation at 5000×g for 6 min. Cell pellets were immediately frozen in liquid nitrogen and stored at − 80 °C until RNA extraction.

RNA isolation

Total RNA was isolated from the frozen cell pellets by using TRIzol® Reagent (ThermoFisher, Waltham, MS, USA), according to the manufacturer’s protocol. In order to remove genomic DNA from total RNA samples, a DNA digestion was performed with the RNase-Free DNase Set (Qiagen, Hilden, Germany) following manufacturer’s instructions. Quantity and quality of extracted RNA were determined by a Qubit® 1.0 fluorometer with a Qubit RNA BR (Broad Range) assay kit (Invitrogen, Carlsbad, CA, USA) and by an Agilent 2200 TapeStation with the Agilent RNA ScreenTape assay (Agilent Technologies, Santa Clara, CA, USA), respectively. Nine purified total RNA samples with a yield of at least 5 µg and RNA integrity numbers (RIN) in a range of 5.6–7.6 were used for sequencing. These included three replicates per group: three DMSO-dissolved C12-treated samples (T1, T2 and T3), three samples with DMSO supplementation alone (control samples C1, C2, C3) and three samples without supplement (blank samples B1, B2, B3).

Ribosomal RNA depletion

The Ribo-Zero™ rRNA removal kit (Bacteria) (http://www.illumina.com/products/ribo-zero-rrna-removal-bacteria.html, Epicentre, San Diego, USA) was applied to deplete rRNA from the M. ruminantium total RNA samples (5 µg) by following the Illumina user guide for the Ribo-Zero Magnetic kits (Part#15065382 Rev. A, November 2014). The rRNA-depleted samples were purified with AMPure RNAClean XP Beads (Beckman-Coulter Genomics, Nyon, Switzerland) as recommended in the Illumina protocol mentioned above.

Next generation sequencing

Enriched RNA samples were used to produce library constructs by following the Illumina TruSeq® Stranded total RNA protocol (Part#15031048 Rev. C, September 2012) with the Illumina TruSeq Stranded total RNA Sample Preparation Kit. Libraries were quantified and quality checked using qPCR with Illumina adapter specific primers (Roche LightCycler® system, Roche Diagnostics, Basel, Switzerland) and by the Agilent Technologies 2100 Bioanalyzer with DNA-specific chips, respectively. Diluted indexed libraries (10 nM) were pooled, used for cluster generation (Illumina TruSeq SR Cluster Kit v4-cBot-HS reagents) and further sequenced (Illumina TruSeq SBS Kit v4-HS reagents) on the Illumina HiSeq 2500 instrument in the high output mode according to the manufacturer’s recommendations. Illumina single read approach (1 × 125 bp) was used to generate raw sequencing reads with a depth of approximately 20–30 million reads per sample.

RNA-sequencing data analysis

Data analyses were performed as described by Tanner et al. [9]. Shortly, reads (125 bp) were mapped against the genome of M. ruminantium M1 using the CLC Genomics Workbench 6.5.1 (CLC, Aarhus, Denmark). Statistical analysis was performed using Bioconductor EdgeR software package in R. A false discovery rate (FDR) value < 0.05 was used as cutoff for significance of differentially expressed genes and log2 fold change > 1 and < −1 was used as cutoff for differential transcription of genes higher (positive log2-fold change values) or lower (negative log2-fold change values) expressed in cultures [10]. To test for significant enrichment in each category listed in Table 1, a two-tailed Fisher test was performed at http://www.langsrud.com/fisher.htm.
Table 1

Number of genes significantly differential expressed within functional categories

Category

Gene count

Treatment vs. control

Control vs. blank

Treatment vs. blank

Up

Down

Up

Down

Up

Down

Amino acid metabolism

94

2b

3

0

4

1

2

Cell cycle

29

1

0

0

0

0

0

Cell envelope

189

28a

0b

2

4

2

3

Cellular processes

14

3

1

1

0

2a

0

Central carbon metabolism

61

2

1

0

1

2

0

Energy metabolism

141

9

9a

6

3

6

0

Lipid metabolism

21

0

0

1

0

0

3a

Mobile elements

87

37a

0

0

37a

0

0

Nitrogen metabolism

14

0

1

1

0

1

0

Nucleic acid metabolism

60

2

1

0

0

0

0

Protein fate

51

0b

2

1

0

1

0

Protein synthesis

169

7

1

0b

9

0b

0

Purines and pyrimidines

47

2

0

0

0

0

0

Regulation

68

0b

5a

5a

0

2

0

Secondary metabolites

12

4

0

0

0

0

0

Transcription

26

1

0

0

0

0

0

Transporters

97

11

1

7a

3

7a

1

Unknown function

183

10

8

4

2b

3

0

Vitamins and cofactors

142

8

3

2

4

5

1

Totalc

1505

127

36

30

67

32

10

aSignificant functional enrichment in a Fisher exact test (p < 0.05)

bSignificant functional underrepresentation in a Fisher exact test (p < 0.05)

cNon-conserved hypothetical genes and RNAs are omitted in the classification [11]. Treatment: with DMSO-dissolved C12, control: with DMSO alone, blank: without C12 and DMSO

Results and discussion

The Ribo-Zero™ rRNA Removal Kit can be used to efficiently remove the rRNA fraction from total RNA samples isolated from the archaeon M. ruminantium M1. The Epicentre probes (directed to bind rRNA from a broad spectrum of bacteria species) reduced the rRNAs in all samples tested, which resulted in 40–85% of non-rRNA sequencing reads in the samples (Fig. 1). More than 10 million mRNA sequencing reads per sample were mapped to the genome of M. ruminantium M1 (Fig. 1), which is a sufficient coverage for transcriptome analyses [11].
Figure 1
Fig. 1

Ribosomal RNA depletion and reads enrichment in RNA extracted from M. ruminantium M1. B: blank (without C12 and dimethyl sulfoxide, DMSO), C: control (with DMSO alone), T: treatment (with DMSO-dissolved C12). Note that the y-axis is non-linear

First, we compared the untreated cultures to the control cultures treated with DMSO. DMSO affected the expression of 97 out of 2280 genes in the M1 genome (Additional file 1). DMSO induced changes in gene expression of cell surface-related proteins, cell membrane-associated transporters and intracellular proteins; the latter maybe related to the observation that DMSO penetrates cell membranes [8]. DMSO-regulated genes included genes encoding proteins related to the cell envelope, mainly adhesion-like proteins (six genes; four down-regulated, two up-regulated). Others were classified as mobile genetic elements (38 genes including hypothetical genes; all down-regulated), and genes involved in energy metabolism, mainly hydrogen metabolism [nine genes, six up-regulated (frhA/B1/D/G, mtrA2, DsbD), three down-regulated (hypA/B, adh3)]. Genes involved in metabolism of vitamins and cofactors (six genes; four down-regulated, two up-regulated) as well as of amino acids (four genes, all down-regulated) were regulated. Moreover, cation transporters (five genes; four of five up-regulated), amino acid transporters (two genes; down-regulated), and other transporters (three genes, up-regulated) showed differential expression when untreated cultures were compared to DMSO-supplemented cultures. Overall, the set of genes regulated in the DMSO control group compared to the blank group was enriched for genes assigned to categories: ‘Mobile elements’, ‘Transporters’, and ‘Regulation’, whereas genes assigned to ‘protein synthesis’ and genes of unknown function were significantly underrepresented (Table 1).

The comparison between the C12 + DMSO-treated and the untreated cultures revealed 42 genes differentially regulated (Additional file 2), 26 of these also found in the DMSO-treated versus untreated comparison (Additional file 3).

Thereafter the transcriptome of the C12 + DMSO-treated and DMSO-treated cultures were compared to identify the mechanisms how MCFA affect methanogenesis. A total of 147 genes, 6.4% of all 2280 genes, were differentially regulated (Table 2).
Table 2

Significant changes of gene expression in M. ruminantium M1 cultures exposed to C12

Category and subcategory

ORF

Gene name

Annotated function

log2-fold change

log2 counts per 106 reads

Amino acid metabolism

 Lysine

mru_0152

lysA

Diaminopimelate decarboxylase LysA

− 1.02

7.66

 

mru_0153

dapF

Diaminopimelate epimerase DapF

− 1.00

7.01

 Histidine

mru_0182

hisH

Imidazole glycerol phosphate synthase glutamine amidotransferase subunit HisH

− 1.07

6.27

 Serine

mru_0678

serA

Phosphoglycerate dehydrogenase SerA

1.03

9.59

 Tryptophan

mru_2159

trpB2

Tryptophan synthase beta subunit TrpB2

1.00

11.31

Cell cycle

 Cell division

mru_2160

minD

Cell division ATPase MinD

1.08

5.46

Cell envelope

 Cell surface proteins

mru_1500

mru_1500

Adhesin-like protein

1.00

8.58

 

mru_0160

mru_0160

Adhesin-like protein

1.02

6.70

 

mru_0963

mru_0963

Adhesin-like protein

1.08

12.13

 

mru_1263

mru_1263

Adhesin-like protein

1.15

9.15

 

mru_0331

mru_0331

Adhesin-like protein

1.15

10.34

 

mru_0338

mru_0338

Adhesin-like protein

1.17

8.55

 

mru_1124

mru_1124

Adhesin-like protein

1.20

12.55

 

mru_0031

mru_0031

Adhesin-like protein

1.27

11.29

 

mru_0687

mru_0687

Adhesin-like protein

1.28

10.46

 

mru_0245

mru_0245

Adhesin-like protein

1.32

8.78

 

mru_1417

mru_1417

Adhesin-like protein

1.43

9.49

 

mru_1650

mru_1650

Adhesin-like protein

1.44

4.24

 

mru_1465

mru_1465

Adhesin-like protein

1.61

6.82

 

mru_1506

mru_1506

Adhesin-like protein

1.61

7.76

 

mru_0417

mru_0417

Adhesin-like protein

1.70

5.86

 

mru_0327

mru_0327

Adhesin-like protein

1.73

10.86

 

mru_0019

mru_0019

Adhesin-like protein

2.04

7.42

 

mru_0084

mru_0084

Adhesin-like protein

2.07

6.71

 

mru_2049

mru_2049

Adhesin-like protein

2.25

11.23

 

mru_2043

mru_2043

Adhesin-like protein

2.27

8.58

 

mru_1726

mru_1726

Adhesin-like protein

2.32

8.37

 

mru_2090

mru_2090

Adhesin-like protein

2.51

13.88

 

mru_2147

mru_2147

Adhesin-like protein

2.73

13.13

 

mru_0326

mru_0326

Adhesin-like protein

5.04

12.58

 

mru_0015

mru_0015

Adhesin-like protein with cysteine protease domain

1.49

9.07

 

mru_0020

mru_0020

Adhesin-like protein with cysteine protease domain

2.78

7.86

 Teichoic acid biosynthesis

mru_1079

mru_1079

CDP-glycerol:poly(glycerophosphate) glycerophosphotransferase

1.27

6.32

 Pseudomurein biosynthesis

mru_1118

mru_1118

Cell wall biosynthesis protein Mur ligase family

1.07

9.37

Cellular processes

 Oxidative stress response

mru_1507

fprA1

F420H2 oxidase FprA1

1.37

10.47

 

mru_0131

fprA2

F420H2 oxidase FprA2

3.58

12.42

 

mru_1367

rbr2

Rubrerythrin Rbr2

1.27

13.19

 Stress response

mru_0183

mru_0183

Protein disulfide-isomerase thioredoxin-related protein

− 1.19

7.79

Central carbon metabolism

 Gluconeogenesis

mru_0628

pgk2A

2-Phosphoglycerate kinase Pgk2A

1.85

7.69

 Other

mru_1685

deoC

Deoxyribose-phosphate aldolase DeoC

5.12

11.11

 Acetate

mru_1786

mru_1786

Transporter SSS family

− 1.18

8.66

Energy metabolism

 Electron transfer

mru_0915

mru_0915

4Fe–4S binding domain-containing protein

− 1.06

7.64

 

mru_2036

mru_2036

4Fe–4S binding domain-containing protein

1.25

5.60

 

mru_1345

mru_1345

4Fe–4S binding domain-containing protein

1.30

7.63

 Methanogenesis pathway

mru_0569

mer

5,10-methylenetetrahydro-methanopterin reductase Mer

− 1.36

12.71

 

mru_0526

hmd

Coenzyme F420-dependent N(5), N(10)-methenyltetrahydromethanopterin reductase Hmd

1.41

10.96

 

mru_1850

atwA2

Methyl-coenzyme M reductase component A2 AtwA2

1.05

10.86

 

mru_1927

mcrD

Methyl-coenzyme M reductase D subunit McrD

− 1.43

11.33

 

mru_0441

mtrA2

Tetrahydromethanopterin S-methyltransferase subunit A MtrA2

− 2.14

11.99

 

mru_1918

mtrF

Tetrahydromethanopterin S-methyltransferase subunit F MtrF

− 1.24

9.71

 Electron transfer

mru_0184

dsbD

Cytochrome C-type biogenesis protein DsbD

− 1.16

6.17

 

mru_0830

mru_0830

Ferredoxin

2.56

9.31

 H2 metabolism

mru_1410

ehaC

Energy-converting hydrogenase A subunit C EhaC

− 1.63

6.30

 

mru_1408

ehaE

Energy-converting hydrogenase A subunit E EhaE

− 1.74

7.34

 

mru_1632

hypB

Hydrogenase accessory protein HypB

2.25

7.90

 

mru_1633

hypA

Hydrogenase nickel insertion protein HypA

2.19

7.47

 Formate metabolism

mru_0332

fdhC

Formate/nitrite transporter FdhC

− 1.11

11.98

 Alcohol metabolism

mru_1445

adh3

NADP-dependent alcohol dehydrogenase Adh3

6.42

7.81

 

mru_1444

npdG2

NADPH-dependent F420 reductase NpdG2

3.84

5.32

Mobile elements

 Prophage

mru_0269

mru_0269

ATPase involved in DNA replication control MCM family

2.51

4.60

 

mru_0323

mru_0323

dnd system-associated protein 2

1.11

6.63

 

mru_0280

mru_0280

ParB-like nuclease domain-containing protein

2.52

1.87

 

mru_0256

mru_0256

Phage integrase

1.69

6.95

 

mru_0287

mru_0287

Phage portal protein

2.73

1.86

 

mru_0315

mru_0315

Phage tail tape measure protein

2.47

3.39

 

mru_0270

mru_0270

Phage-related protein

1.91

4.54

 

mru_0288

mru_0288

Phage-related protein

2.21

2.32

 

mru_0058

mru_0058

Phage-related protein

2.53

− 0.04

 

mru_0282

mru_0282

Phage-related protein

2.64

1.93

 

mru_0316

mru_0316

Phage-related protein

2.66

3.40

 

mru_0317

mru_0317

Phage-related protein

2.89

3.42

 

mru_0311

mru_0311

Phage-related protein

3.14

2.55

 

mru_0310

mru_0310

Phage-related protein

3.18

1.56

 

mru_0284

mru_0284

Phage-related protein

3.35

1.93

 

mru_0307

mru_0307

Phage-related protein

3.38

2.86

 

mru_0313

mru_0313

Phage-related protein

3.40

2.83

 

mru_0308

mru_0308

Phage-related protein

3.48

3.46

 

mru_0324

mru_0324

Type II restriction enzyme, methylase subunit

1.88

5.99

 CRISPR-associated genes

mru_0798

mru_0798

CRISPR-associated protein Cas1-1

1.93

4.09

 

mru_1181

mru_1181

CRISPR-associated RAMP protein Csm3 family

1.03

7.23

Nitrogen metabolism

 Other

mru_2121

hcp

Hydroxylamine reductase Hcp

− 1.46

12.26

Nucleic acid metabolism

 Helicase

mru_0981

mru_0981

Rad3-related DNA helicase

1.09

7.97

 Recombination and repair

mru_2097

recJ1

ssDNA exonuclease RecJ1

1.39

11.06

 

mru_1383

mru_1383

Staphylococcal nuclease domain-containing protein

− 1.30

7.06

Protein fate

 Protein folding

mru_1511

mru_1511

Nascent polypeptide-associated complex protein

− 1.00

6.61

 Protein secretion

mru_1581

mru_1581

Signal peptidase I

− 1.21

7.34

Protein synthesis

 RNA processing

mru_0589

mru_0589

NMD3 family protein

1.50

7.52

 Translation factors

mru_0728

mru_0728

Peptide chain release factor aRF1

1.46

7.74

 Ribosomal proteins

mru_0865

rpl5p

Ribosomal protein L5P Rpl5p

1.03

8.24

 

mru_0868

rpl6p

Ribosomal protein L6P Rpl6p

1.05

7.92

 

mru_2098

mru_2098

Ribosomal protein S15P Rps15p

1.19

9.21

 Other

mru_0519

mru_0519

RNA-binding protein

− 1.68

8.08

 

mru_1978

mru_1978

RNA-metabolising metallo-beta-lactamase

1.58

8.74

 RNA processing

mru_1846

dusA2

tRNA-dihydrouridine synthase DusA2

1.06

6.58

Purines and pyrimidines

 Interconversion

mru_2104

surE1

5′-Nucleotidase SurE1

1.02

7.02

 

mru_0241

nrdD

Anaerobic ribonucleoside-triphosphate reductase NrdD

1.47

11.08

Regulation

 Protein interaction

mru_1186

mru_1186

TPR repeat-containing protein

− 1.05

8.81

 Transcriptional regulator

mru_2122

mru_2122

Transcriptional regulator

− 1.62

8.68

 

mru_1447

mru_1447

Transcriptional regulator

− 1.55

8.56

 

mru_1446

mru_1446

Transcriptional regulator ArsR family

− 1.21

7.78

 

mru_0442

mru_0442

Transcriptional regulator MarR family

− 1.68

4.74

Secondary metabolites

 Other

mru_0514

mru_0514

4′-Phosphopantetheinyl transferase family protein

1.26

6.32

 

mru_0069

mru_0069

MatE efflux family protein

1.20

7.17

 

mru_0352

mru_0352

MatE efflux family protein

1.64

6.73

 NRPS

mru_0351

mru_0351

Non-ribosomal peptide synthetase

1.06

10.17

Transcription

 RNA polymerase

mru_0161

rpoF

DNA-directed RNA polymerase subunit F RpoF

1.05

9.66

Transporters

 Amino acids

mru_1775

mru_1775

Amino acid ABC transporter ATP-binding protein

1.03

5.46

 

mru_1776

mru_1776

Amino acid ABC transporter permease protein

1.25

4.94

 Cations

mru_1861

mru_1861

Heavy metal translocating P-type ATPase

− 6.61

10.24

 

mru_1706

nikD2

Nickel ABC transporter ATP-binding protein NikD2

1.15

6.54

 

mru_1617

nikB1

Nickel ABC transporter permease protein NikB1

1.10

7.35

 

mru_1709

nikB2

Nickel ABC transporter permease protein NikB2

1.43

7.34

 

mru_1708

nikC2

Nickel ABC transporter permease protein NikC2

1.31

7.03

 

mru_1710

nikA2

Nickel ABC transporter substrate-binding protein NikA2

1.14

11.86

 Other

mru_0253

mru_0253

ABC transporter ATP-binding protein

1.97

7.23

 

mru_0252

mru_0252

ABC transporter permease protein

1.71

7.40

 

mru_0251

mru_0251

ABC transporter substrate-binding protein

2.06

9.13

 

mru_0329

mru_0329

MotA/TolQ/ExbB proton channel family protein

1.56

6.00

Vitamins and cofactors

 Biotin

mru_0527

bioB2

Biotin synthase BioB2

1.24

7.09

 Cobalamin

mru_0539

cbiM1

Cobalamin biosynthesis protein CbiM1

1.21

9.82

 

mru_0540

cbiN1

Cobalt transport protein CbiN1

1.18

8.30

 

mru_0360

cbiA1

Cobyrinic acid a,c-diamide synthase CbiA1

− 1.60

8.09

 

mru_1852

cysG

Siroheme synthase CysG

1.20

7.47

 Coenzyme B

mru_0385

aksA

Homocitrate synthase AksA

− 1.15

10.22

 Metal-binding pterin

mru_0200

modB

Molybdate ABC transporter permease protein ModB

2.04

9.37

 

mru_0201

modA

Molybdate ABC transporter substrate-binding protein ModA

2.83

10.54

 Thiamine

mru_0247

thiC1

Thiamine biosynthesis protein ThiC1

− 1.18

9.24

 

mru_0532

mru_0532

ThiF family protein

1.38

4.67

 Others

mru_1769

nifB

Nitrogenase cofactor biosynthesis protein NifB

2.58

8.89

Unknown function

 Enzyme

mru_0455

mru_0455

Acetyltransferase

− 1.16

9.80

 

mru_1758

mru_1758

Acetyltransferase

− 1.10

6.05

 

mru_2170

mru_2170

Acetyltransferase

1.32

6.12

 

mru_0574

mru_0574

Acetyltransferase GNAT family

− 1.92

1.81

 

mru_1707

mru_1707

Acetyltransferase GNAT family

1.48

5.54

 

mru_0560

mru_0560

ATPase

1.11

8.14

 

mru_1613

mru_1613

SAM-dependent methyltransferase

1.58

4.18

 Other

mru_0231

mru_0231

CAAX amino terminal protease family protein

− 1.09

8.53

 

mru_1993

mru_1993

CBS domain-containing protein

− 1.65

10.72

 

mru_1994

mru_1994

CBS domain-containing protein

− 1.31

11.57

 

mru_0474

mru_0474

HD domain-containing protein

1.33

7.47

 

mru_1034

mru_1034

HEAT repeat-containing protein

2.35

8.75

 

mru_2109

mru_2109

Methanogenesis marker protein 12

− 1.01

7.90

 

mru_0562

mru_0562

PP-loop family protein

1.59

7.50

 

mru_1678

mru_1678

Redox-active disulfide protein

1.51

7.12

 

mru_0561

mru_0561

Von Willebrand factor type A domain-containing protein

1.33

8.52

 

mru_1510

mru_1510

YhgE/Pip-like protein

− 1.31

8.45

 

mru_0627

mru_0627

ZPR1 zinc-finger domain-containing protein

2.04

6.70

C12-treated cultures were compared to DSMO-exposed control cultures (significant change with log2fold changes < 1 and > 1 and a false discovery rate < 0.05). The list does not include the 71 regulated hypothetical proteins. The M. ruminantium (mru) open reading frame (ORF) codes are adopted from the Kyoto Encyclopedia of Genes and Genomes

The subcellular localization of the encoded protein could be identified for 75% of the regulated genes. Predominantly, genes associated with the cell envelope were affected, namely trans-membrane proteins or membrane-associated proteins. Enrichment analysis showed that, with C12 exposure, mainly adhesion-like proteins (category ‘cell surface’) and phage-related proteins (‘mobile elements’) were significantly enriched in the regulated genes data set (Table 1). This supports earlier suggestions that MCFA primarily target the cell envelope and processes that occur at the cell membrane [12]. For example, upon exposure to C12 in the present study, the mRNA abundance of 26 adhesion-like proteins (ALPs) (part of the cell envelope [13]), i.e. of 25% of all ALPs of M. ruminantium, and of two proteins involved in biosynthesis of teichoic acid and pseudomurein which are cell-wall related [14], were up-regulated compared to the DMSO control group (Table 2).

Two subunits of the membrane-bound energy-converting hydrogenase (Eha), which is involved in hydrogenotrophic methanogenesis [13, 15], were down-regulated by log21.6- and 1.7-fold in cultures exposed to C12, whereas two cytoplasmic hydrogenases (Frh, Mvh) were not. A gene encoding ferredoxin, a trans-membrane iron-sulfur protein involved in electron transfer from hydrogen, was up-regulated (log 2.6-fold upon C12 exposure). Expression of 3 genes encoding trans-membrane 4Fe-4S binding domain-containing proteins was affected by C12 exposure. Two subunits of the methyl-H4MPT:coenzyme M methyltransferase (Mtr), which is membrane-bound and plays a crucial role in the methanogenesis pathway [15, 16], were down-regulated by log2 2.1- and 1.2-fold upon C12 exposure. In total 13 genes encoding mainly transporters of amino acids and cations displayed differences in transcript abundance after C12 exposure (Table 2). For example, several genes encoding subunits of cations transporters, like the nickel ABC transporter permease proteins or nickel ABC transporter ATP-binding proteins, NikA2, NikB1, NikB2, NikC2 and NikD2, were differentially regulated. These cation transporters belong to a large family of ABC transporters (peptide/nickel transporter family) in ABC-type nickel transporter system, which is composed of a periplasmic binding protein (NikA), two integral membrane proteins (NikB and NikC) and two ABC proteins (NikD and NikE) [17]. One P-type ATPase, which are membrane-bound efflux pumps involved in metal homeostasis of microorganisms [18], was down-regulated. In prokaryotes, ABC transporters and P-type ATPases have important functions in maintaining appropriate concentrations of transition metals such as Ni, Co, Fe, Cu, and Zn, which are essential components of many prokaryotic enzymes [18]. Two transmembrane cobalt transport proteins (mru_0540; mru_0539), and two membrane-associated proteins involved in molybdate transport (mru_0200, mru_0201) [19], were up-regulated.

In addition, genes encoding intracellular proteins were affected by C12 exposure. These data support earlier observations that exposure to C12 causes leakage of intracellular K+ ions in M. ruminantium [6, 7], thus damages the cell envelope. Amongst the regulated genes, mostly genes encoding proteins involved in DNA repair, and genes controlling transcription/translation and redox homeostasis were affected. For example, thioredoxins and rubrerythrins showed an altered expression; they are considered to form a system protecting Archaea against oxidative stress [20, 21]. Thioredoxin-like proteins exhibit biochemical activities similar to thioredoxin and help methanogens maintain redox homeostasis [7]. Genes which were up-regulated by C12 included genes encoding proteins that are involved in nucleic acid metabolism and repair and in translation include a helicase (mru_0981), an exonuclease (mru_2097, recJ1), an anaerobic ribonucleosid-triphosphate reductase nrdD (mru_0241), a nucleotidase (mru_2104; SurE1), and a RNA-metabolizing metallo-beta-lactamase (mru_1978). Several genes involved in translation or post-translational modification were down-regulated, e.g. a staphylococcal nuclease domain-containing protein (mru_1383), a nascent polypeptide-associated complex protein (mru_1511), an RNA-binding protein (mru_0519) and a signal peptidase (mru_1581).

Conclusion

The transcriptional response of M. ruminantium to the fatty acid C12 does not involve repression of specific pathway such as the methanogenesis pathway. Instead, it implies that C12 provokes broad transcriptional changes, and targets primarily cell surface associated adhesion-like proteins, phage-related proteins, and transmembrane proteins. How this response affects methanogens remains unclear. Future studies may investigate how different dosages of and prolonged exposure to C12 affect gene and protein expression and survival of M. ruminantium.

Limitations

One limitation of our study is the low number of replicates per group. In addition, only one dosage of C12 was tested and samples for RNA sequencing were collected only at one time point; this precludes generalization to situations where C12 affects M. ruminantium stronger or weaker.

Notes

Abbreviations

MCFA: 

medium-chain fatty acids

C12

lauric acid

DMSO: 

dimethyl sulfoxide

CH4

methane

Declarations

Authors’ contributions

XZ participated in designing the study, performed the data collection, and drafted the manuscript. MJAS performed the data analysis and contributed to data interpretation. SN participated in designing the study, data collection and data interpretation and revised the manuscript. AS participated in data collection and critically revised the manuscript. MK participated in designing the study and critically revised the manuscript. AB participated in designing the study, performed the sequencing experiment, wrote the methods section of the manuscript, contributed to interpretation of the data and revised the manuscript. JOZ designed the study and wrote introduction, results and discussion of the manuscript. All authors read and approved the final manuscript.

Acknowledgements

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Availability of data and materials

The raw data can be accessed in the NCBI Sequence Read Archive (SRA) under the series record GSE81199 at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE81199.

Consent for publication

Not applicable.

Ethics approval and consent to participate

Not applicable.

Funding

This study was supported by the China Scholarship Council and the ETH Zurich Scholarship for Doctoral Students.

Publisher’s Note

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Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Institute of Agricultural Sciences, ETH Zurich, Zurich, Switzerland
(2)
Laboratory of Food Biotechnology, Institute of Food, Nutrition and Health, ETH Zurich, Zurich, Switzerland
(3)
Institute for Food Hygiene and Safety, University of Zurich, Zurich, Switzerland
(4)
Institute of Agricultural Sciences, ETH Zurich, Zurich, Switzerland
(5)
Functional Genomics Center Zurich, ETH Zurich and University of Zurich, Zurich, Switzerland
(6)
Institute of Animal Nutrition and Nutritional Physiology, Justus-Liebig University Giessen, Giessen, Germany

References

  1. UNFCC 2016 (United Nations Framework Convention on Climate Change). Greenhouse Gas Data, unfccc.int/ghg_data/ghg:data:unfccc/items/4146.php. Accessed 5 Sept 2016.
  2. Jordan E, Lovett DK, Hawkins M, Callan JJ, O’Mara FP. The effect of varying levels of coconut oil on intake, digestibility and methane output from continental cross beef heifers. Anim Sci. 2006;82:859–65.View ArticleGoogle Scholar
  3. Machmüller A, Kreuzer M. Methane suppression by coconut oil and associated effects on nutrient and energy balance in sheep. Can J Anim Sci. 1999;79:65–72.View ArticleGoogle Scholar
  4. Machmüller A, Soliva CR, Kreuzer M. Methane-suppressing effect of myristic acid in sheep as affected by dietary calcium and forage proportion. Br J Nutr. 2003;90:529–40.View ArticlePubMedGoogle Scholar
  5. Dohme F, Machmüller A, Wasserfallen A, Kreuzer M. Ruminal methanogenesis as influenced by individual fatty acids supplemented to complete ruminant diets. Lett Appl Microbiol. 2001;32:47–51.View ArticlePubMedGoogle Scholar
  6. Zhou X, Meile L, Kreuzer M, Zeitz JO. The effect of saturated fatty acids on methanogenesis and cell viability of Methanobrevibacter ruminantium. Archaea. 2013;2013:106916.View ArticlePubMedPubMed CentralGoogle Scholar
  7. Zhou X, Zeitz JO, Meile L, Kreuzer M, Schwarm A. Influence of pH and the degree of protonation on the inhibitory effect of fatty acids in the ruminal methanogen Methanobrevibacter ruminantium strain M1. J Appl Microbiol. 2015;119:1482–93.View ArticlePubMedGoogle Scholar
  8. Santos NC, Figueira-Coelho J, Martins-Silva J, Saldanha C. Multidisciplinary utilization of dimethyl sulfoxide: pharmacological, cellular, and molecular aspects. Biochem Pharmacol. 2003;65:1035–41.View ArticlePubMedGoogle Scholar
  9. Tanner SA, Chassard C, Rigozzi E, Lacroix C, Stevens MJA. Bifidobacterium thermophilum RBL67 impacts on growth and virulence gene expression of Salmonella enterica subsp. enterica serovar Typhimurium. BMC Microbiol. 2016;16:46–61.View ArticlePubMedPubMed CentralGoogle Scholar
  10. Rosenthal AZ, Matson EG, Eldar A, Leadbetter JR. RNA-seq reveals cooperative metabolic interactions between two termite-gut spirochete species in co-culture. ISME J. 2011;5:1133–42.View ArticlePubMedPubMed CentralGoogle Scholar
  11. Haas BJ, Chin M, Nusbaum C, Birren BW, Livny J. How deep is deep enough for RNA-Seq profiling of bacterial transcriptomes? BMC Genom. 2012;13:734–44.View ArticleGoogle Scholar
  12. Desbois AP, Smith VJ. Antibacterial free fatty acids: activities, mechanisms of action and biotechnological potential. Appl Microbiol Biotechnol. 2010;85:1629–42.View ArticlePubMedGoogle Scholar
  13. Leahy SC, Kelly WJ, Altermann E, Ronimus RS, Yeoman CJ, Pacheco DM, et al. The genome sequence of the ruminal methanogen Methanobrevibacter ruminantium reveals new possibilities for controlling ruminant methane emissions. PLoS ONE. 2010;5:e8926.View ArticlePubMedPubMed CentralGoogle Scholar
  14. Beld J, Sonnenschein EC, Vickery CR, Noelb JP, Burkart MD. The phosphopantetheinyl transferases: catalysis of a post-translational modification crucial for life. Nat Prod Rep. 2014;31:61–108.View ArticlePubMedPubMed CentralGoogle Scholar
  15. Thauer RK, Kaster AK, Seedorf H, Buckel W, Hedderich R. Methanogenic archaea: ecologically relevant differences in energy conservation, ‎Nature Rev. Microbiol. 2008;8:579–91.Google Scholar
  16. Kaster AK, Goenrich M, Seedorf H, Liesegang H, Wollherr A, Gottschalk G, Thauer RK. More than 200 genes required for methane formation from H2 and CO2 and energy conservation are present in Methanothermobacter marburgensis and Methanothermobacter thermautotrophicus. Archaea. 2011;2011:973848.View ArticlePubMedPubMed CentralGoogle Scholar
  17. Rodionov DA, Hebbeln P, Gelfand MS, Eitinger T. Comparative and functional genomic analysis of prokaryotic nickel and cobalt uptake transporters: evidence for a novel group of ATP-binding cassette transporters. J Bacteriol. 2006;188:317–27.View ArticlePubMedPubMed CentralGoogle Scholar
  18. Lewinson O, Lee AT, Rees DC. A P-type ATPase importer that discriminates between essential and toxic transition metals. Proc Natl Acad Sci. 2009;106:4677–82.View ArticlePubMedPubMed CentralGoogle Scholar
  19. Grunden AM, Shanmugam KT. Molybdate transport and regulation in bacteria. Arch Microbiol. 1997;168:345–54.View ArticlePubMedGoogle Scholar
  20. Pedone E, Bartolucci S, Fiorentino G. Sensing and adapting to environment stress: the archaeal tactic. Front Biosci. 2004;9:2909–26.View ArticlePubMedGoogle Scholar
  21. Kato S, Kosaka T, Watanabe K. Comparative transcriptome analysis of responses of Methanothermobacter thermautotrophicus to different environmental stimuli. Environ Microbiol. 2008;10:893–905.View ArticlePubMedGoogle Scholar

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