INTRODUCTION
Methyl coenzyme M reductase (MCR) catalyzes the final step of methane production in methanogenic archaea (
1). The active enzyme consists of three subunits in an α
2β
2γ
2 stoichiometry that is present in very high abundance in the cytosol. The operon encoding MCR dominates methanogen transcriptomes, where it is invariably found to be one of the most abundant mRNAs (
2), and MCR accounts for roughly 10% of the cytoplasmic proteome (
1,
3). MCR is also the first step of anerobic methane oxidation in anerobic methanotrophic archaea, where it is found in similarly high levels in transcriptomes (
4,
5) and proteomes (
6,
7). Despite its abundance, the isolation and biochemical characterization of active MCR is challenging. The active site contains a nickel porphyrin cofactor (F430) that is significantly oxygen-sensitive, and even when the enzyme is purified in the absence of oxygen, it can enter inactive product-inhibited states. While a few protocols have been developed to purify the active enzyme, or re-activate inactive states, from
Methanothermobacter marburgensis, these are not broadly applicable to other methanogens, especially strains with sophisticated tools for genetic manipulation, such as
Methanococcus maripaludis or
Methanosarcina spp. (
1). Based on these challenges, even straightforward experiments to measure kinetic parameters such as substrate affinities (K
m) or turnover rate (k
cat) have taken decades of effort from multiple research groups and have not been expanded to cover any significant phylogenetic diversity.
In contrast to the advances made in understanding the biochemical properties of the
M. marburgensis MCR in isolation, holistic questions that address the biogenesis and function of MCR, likely mediated by an interaction with other proteins, as well as with methanogen physiology more broadly, have received significantly less attention. We know very little about the proteins involved in the assembly, activation, and degradation of MCR
in vivo. Similarly, regulatory processes that control the expression of MCR in response to environmental cues such as resource availability or stress response have barely been studied. The only system where regulation has been investigated is the differential expression of the two isoforms of MCR present in
Methanothermobacter spp
. (
8) ; however, most methanogens carry only a single copy of MCR (
1). How, and to what extent, methanogens control the amount of MCR and its activity when conditions are unfavorable is an understudied but important question due to the growing interest in inhibiting methanogenesis for reducing methane emissions, as well as using methanogens as a chassis for bioengineering, wherein major metabolic end-products in addition to methane are desired (
9).
Recent advances in genetic tools available for the study of methanogens have facilitated targeted mutagenesis of genes encoding hypothesized accessory proteins of MCR and provided an avenue to investigate their cellular functions. Using this approach, the identity and function of many MCR-associated proteins involved in the installation of post-translational modifications and insertion of F430 have been successfully studied (
10–12). One surprising outcome of these genetic studies is that the loss of highly conserved MCR-associated proteins often has minimal or no significant effects on cell growth, even though, to the best of our knowledge, MCR is essential in all methanogenic archaea (
10–12). A possible explanation for these results is that MCR is not rate-limiting for growth in substrate-replete batch cultures. Therefore, even mutations that result in a substantial detrimental impact to MCR function may be tolerated without a notable growth defect, as has been recently suggested in (
1).
No direct evidence linking MCR abundance to growth and methanogenesis is currently available, and there are differing views in literature. A recent study used a kinetic and stoichiometric hybrid approach to model the growth of
Methanosarcina barkeri on methanol (
13). They showed that MCR has a high control coefficient (of ~0.9) during growth on high methanol concentrations (> 15 mM), i.e., small changes in MCR levels will have a dramatic impact on growth rate under typical batch-culture conditions. This model as well an older kinetic model for
Methanosarcina acetivorans (
14) corroborate a long-standing hypothesis that MCR is a rate-limiting enzyme during methanogenic growth (
8,
15). Alternately, other studies have targeted F430 biosynthesis, either through the omission of nickel in the growth medium or through the addition of levulinic acid, which inhibits porphyrin biosynthesis (
3,
16,
17). These studies show that a modest decrease in F430 abundance has no effect on cell growth, and only a drastic reduction in F430 levels, by fivefold or more, leads to growth defects and can alter subcellular localization of MCR. Taken together, these studies are consistent with the notion that MCR is present in excess in nickel-replete medium typically used for laboratory cultivation of methanogens (
3). One caveat of these studies is that nickel and porphyrins are present in many other bioenergetic enzymes essential for methanogenesis; hence, it is difficult to attribute any observed growth phenotypes entirely to MCR. Additionally, carbon monoxide supplementation inhibits methanogenesis in
Methanosarcina acetivorans, and growth under these conditions produces large quantities of acetate, formate, and methylsulfides and only a small amount of methane (
18–20). Acetogenic growth of
M. acetivorans can be further amplified in mutants where methane production is nearly completely abolished (
21). While it has been suggested that carbon monoxide is partially inhibitory to MCR (
18), it is not clear that there is a biochemical basis for this notion. Notably, even under conditions where methane production is an insignificant portion of catabolism, MCR remains essential and cannot be deleted (
21).
Based on the current literature, it is unclear if MCR is present in excess during laboratory growth, and if so, why such a substantial portion of their proteome and transcriptome might be allocated to it, especially when there is a well-established precedent that methanogens have elaborate mechanisms for modifying the expression of other metabolic genes (
22). Hence, to better understand this interplay between MCR abundance and cell growth, we investigated the physiology of the genetically tractable strain
M. acetivorans carrying an inducible MCR operon. Our results clearly demonstrate that wild-type expression of MCR far exceeds the cellular demand and also that MCR-limited growth is indeed possible at significantly lower levels of expression. Under these MCR-limiting conditions, there is a global transcriptional shift that alters the expression of hundreds of genes involved in a variety of cellular processes beyond methanogenesis.
DISCUSSION
In this study, we have carried out a comprehensive investigation into the physiological and transcriptomic response of a methanogenic archaeon, specifically to MCR limitation. We find that MCR is not limiting
M. acetivorans growth in substrate-replete batch cultures, and this observation may explain why some universally conserved MCR-associated proteins can be deleted with little to no effect on growth in this system (
10–12). Decreasing MCR can lead to two forms of growth limitation, linear growth under extreme MCR limitation or slower, sustained exponential growth under less drastic limitations (
Fig. 2). While this growth-limiting state cannot be maintained indefinitely due to the accumulation of escape mutations, we anticipate that the threshold tetracycline concentration at which a growth defect occurs may be a useful diagnostic feature in assessing the relative fitness of MCR mutants or strains lacking certain conserved MCR-associated proteins. This approach, particularly if coupled with high-throughput growth assays, may enable the screening and initial characterization of many MCR variants, far more than is feasible through existing biochemical approaches.
The global transcriptional response to MCR limitation shared similarities with prior observations of
M. acetivorans made under various stressful conditions. In particular, the upregulation of the
mtpCAP operon and
mtsD is reminiscent of increased methylsulfide production during growth on carbon monoxide (
18,
19,
28) and in the absence of HdrABC (
29) or pyrrolysine (
30). In some of these cases, it has been hypothesized that limitation in MCR activity or change in electron flow results in a buildup of methyl-coenzyme M, which can then be relieved by an increase in the expression of methylsulfide methyltransferases, possibly to help maintain redox balance. While there is no evidence for how this alternate pathway might allow
M. acetivorans to conserve energy, the results presented here are consistent with the idea that methyl-coenzyme M buildup may induce these alternative methyltransferase systems. It is interesting to note in this context that the MTR complex is significantly downregulated, suggesting that if methyl-coenzyme M build-up is indeed occurring, then the oxidative branch of the methylotrophic pathway is not a viable outlet for these methyl groups, presumably due to a buildup of electron carriers. It is also interesting that while MCR itself may not be actively regulated, as evidenced by the lack of expression change of
tetR, MCR-associated proteins such as
mmp10 and
cfbE are downregulated, suggesting a feedback to the expression of MCR-associated proteins. While this trend is not universally true (e.g.,
ycaO, the McrA-glycine thioamidation protein is not significantly regulated), the list of differentially expressed genes presented here may lead to the discovery of additional MCR-related systems of unknown function.
Altogether, we have developed a genetic platform to conclusively demonstrate that MCR does not mediate the rate-limiting step in M. acetivorans during routine laboratory growth conditions. While these data are consistent with prior observations from studies with Methanothermobacter spp., they diverge from predictions made by metabolic models of Methanosarcina spp. Clearly, more physiological studies like ours are required to bridge the gap between research with enzymes in isolation and systems-level analyses of methanogens. While this tool in and of itself will prove to be especially useful to study the properties of MCR mutants and of mutations in MCR-associated proteins, this experimental framework can be expanded to other important enzymes like HdrDE, HdrABC, and MTR to ultimately obtain a robust and quantitative view of methanogenesis.
MATERIALS AND METHODS
CRISPR-editing plasmid construction and mutant generation
A target sequence (
GTGGACACTTAAAAACGACG) for the
mcrB promoter in
M. acetivorans was identified using the CRISPR site finder tool in Geneious Prime version 11.0 with the following parameters: a) an NGG protospacer adjacent motif (PAM) site at the 3’ end and b) no off-target matches allowed. A DNA fragment encoding the single guide RNA (sgRNA) was synthesized as a gblock gene fragment from Integrated DNA Technologies (Coralville, IA, USA) using the target sequence. The sgRNA and a homology repair template to insert the
tetO1 operator site in the promoter of the
mcrBDCGA operon were cloned into the Cas9 containing vector pDN201, as described previously (
31), to generate pGLC001. pGLC001 was digested with PmeI and a repair template introduced, which included the p
mcrB(
tetO1) promoter in place of the native
pMcrB sequence generating pGLC002. The sequences of pGLC001 and pGLC002 were verified by Sanger sequencing at the Barker sequencing facility at the University of California, Berkeley. A cointegrate of pGLC002 and pAMG40 was generated using the Gateway BP Clonase II Enzyme mix as per the manufacturer’s instructions (Thermo Fisher Scientific, Waltham, MA, USA) and named pGLC003. All
E. coli transformations were conducted with WM4489 (
32), as described previously.
A 10-mL culture of
M. acetivorans in high salt (HS) medium with 50 mM trimethylamine (TMA) in the late-exponential phase was used for liposome-mediated transformation with pGLC003, as described previously (
33). Transformants were plated in agar solidified HS medium with 50 mM TMA, 100 µg/mL tetracycline, and 2 µg/mL puromycin and incubated in an anerobic incubator located inside the anerobic chamber at 37 ˚C with H
2S/CO
2/N
2 (1,000 ppm/20%/balance) in the headspace. Colonies were screened for the mutation and sequence-verified by Sanger sequencing at the Barker sequencing facility at the University of California, Berkeley. Several colonies that tested positive for the desired mutation were streaked out on HS medium with 50 mM TMA, 100 µg/mL tetracycline, and 20 µg/mL 8ADP to cure the mutagenic plasmid. Plasmid-cured mutants were verified by screening for the absence of the
pac gene present on the plasmid with PCR. A single isolate of the plasmid-cured mutant was grown in liquid culture with 50 mM TMA and 100 µg/mL tetracycline and saved as DDN032. All primers, plasmids, and strains used in this study are listed in Tables S1 and S3, respectively.
Growth measurements
All growth experiments were conducted using either WWM60 (
M. acetivorans ∆
hpt:: P
mcrB-tetR) (
23) or DDN032 [WWM60-P
mcrB(
tetO1)-
mcrBDCGA], a strain with the chromosomal
mcr genes containing a
tetO1 operator site inserted in the promoter. All growth analyses were conducted in 10 mL of high salt (HS) media containing methanol (125 mM), TMA (50 mM), sodium acetate (20 mM) as a carbon source, and a pressurized CO
2/N
2 (20:80) headspace, as previously described (
34). Various concentrations of tetracycline were added to the media, as indicated, requiring the media to be protected from light to prevent degradation. Anerobic tetracycline stocks were prepared using tetracycline hydrochloride (Millipore Sigma, Bulington, MA, USA; Product number T7660) fresh in anerobic water on the day of the inoculation, as described previously (
23).
All M. acetivorans growth rates were determined by measuring the optical density (at 600 nm) of cultures grown in Balch tubes containing 10 mL HS media with media additions as indicated. All optical density measurements were made using a UV–Vis spectrophotometer (Genesys50, Thermo Fisher Scientific, Waltham, MA, USA). Growth rates were determined using the best fit line of the log2-transformed optical density data with maximal R2 values.
DNA extraction and sequencing
Genomic DNA was extracted from a 10-mL late-exponential phase culture of DDN032 in HS medium with 125 mM methanol and 100 µg/mL tetracycline as well as the escape mutant in HS medium with 125 mM methanol using a Qiagen Blood and Tissue Kit as per the manufacturer’s instructions (Qiagen, Hilden Germany). Library preparation and Illumina sequencing (150-bp paired-end reads) were conducted at Seqcenter (Pittsburgh, PA). The sequencing reads were mapped to the
M. acetivorans C2A reference genome using breseq version 0.38.1 with default parameters (
35).
RNA extraction, sequencing, and transcriptomic analysis
Quintuplicate cultures of DDN032 and WWM60 were grown in 10 mL HS medium with 125 mM methanol and different concentrations of tetracycline, as indicated in the text. A 3-mL culture was removed for RNA extraction at an optical density between 0.2 and 0.6. The culture was immediately mixed at a ratio of 1:1 with RNA
later, centrifuged at 10,000 x g for 10 minutes at 4°C, and the resulting pellet was applied to a Qiagen RNeasy Mini Kit (Qiagen, Hilden, Germany) and RNA extraction proceeded according to the manufacturer’s instructions. DNAse treatment, rRNA depletion, cDNA preparation, and Illumina library preparation and sequencing were performed at SeqCenter (Pittsburgh, PA). Analysis of transcriptome data was carried out on the Kbase bioinformatics platform using default parameters for Bowtie2, Cufflinks, and DESeq2 (
36). Briefly, raw reads were mapped to the
M. acetivorans WWM60 genome using Bowtie2 (
37), assembled using Cufflinks (
38), and fold changes and significances values were calculated with DESeq2 (
39).
Immunoblot analysis of McrA
Late exponential-phase cultures were harvested by centrifugation, resuspended in 1 mL of lysis buffer (50 mM NaH2PO4, 2 U/mL DNase I, 1 mM phenylmethylsulfonyl fluoride) and incubated at room temperature for 10 minutes. An appropriate volume of a 5 M NaCl stock solution was added to bring the lysate to a final concentration of 300 mM NaCl. The lysate was then cleared by centrifugation [>10,000 rcf, 4°C, 30 m, Sorvall Legend XTR (Thermofisher, Waltham, MA)], and the decanted supernatant was quantified with a microplate Bradford assay as per the manufacturer’s instructions (Sigma-Aldrich, Sant Louis, MO, USA).
Dilution series containing equal amounts of protein were prepared and separated on 12% Mini-PROTEAN TGX gels (BioRad, Hercules, CA, USA) by SDS-PAGE and then transferred onto 0.2-µM polyvinylidene difluoride (PVDF) membranes using the Trans-Blot Turbo system (BioRad) using Trans-Blot Turbo 0.2 PVDF transfer packs as per the manufacturer’s instructions. The membranes were then washed with phosphate-buffered saline containing 0.05% (v/v) Tween-20 (PBST) for 5 minutes at room temperature. Nonspecific binding was blocked by incubating in PBST containing 5% (w/w) nonfat milk powder for 1 hour at room temperature and washing four times lasting 5 minutes each in PBST. The membranes were then incubated overnight at 4°C in PBST with polyclonal rabbit antibodies raised against McrA (1:10000 dilution) (GenScript, Piscataway, NJ, USA), washed four times for 5 minutes in PBST, and then incubated with anti-rabbit horseradish peroxidase (HRP) conjugate antibodies (1:20000 dilution) (Promega, Madison, WI, USA) for 2 hours at room temperature. Following four additional 5-minute washes in PBST and three final washes in phosphate-buffered saline without Tween-20, the membranes were developed with a 5-minute incubation in Immobilon Western Chemiluminescent HRP substrate (EMD Millipore, Burlington, MA, USA) and imaged using a ChemiDoc XRS+ (BioRad). Sixty images were collected over 1 minute of imaging, and the final images, which lacked oversaturation on any target bands, were selected for analysis using Image Lab.
ACKNOWLEDGMENTS
We would like to thank members of the Nayak lab for their feedback and input on the manuscript.
D.D.N. would also like to acknowledge funding from the Searle Scholars Program sponsored by the Kinship Foundation, the Rose Hills Innovator Grant, the Beckman Young Investigator Award sponsored by the Arnold and Mabel Beckman Foundation, the Simons Early Career Investigator in Marine Microbial Ecology and Evolution Award sponsored by the Simons Foundation, and the Packard Fellowship in Science and Engineering sponsored by the David and Lucille Packard Foundation. D.D.N. is a Chan-Zuckerberg Biohub – San Francisco Investigator. G.A.D. would like to acknowledge the NIH "Chemistry-Biology Interface" training program (award #5T32GM06698-14). G.L.C. is supported by the Miller Institute for Basic Research in Science, University of California Berkeley. The funders had no role in the conceptualization and writing of this manuscript or the decision to submit the work for publication.
G.L.C. contributed to conceptualization, data curation, formal analysis, supervision, methodology, and writing. G.A.D. contributed to data curation, formal analysis, methodology, and writing. D.D.N. contributed to conceptualization, data curation, formal analysis, supervision, funding acquisition, project administration, methodology, and writing.