Fine-Tuned Protein Production in Methanosarcina acetivorans C2A

Subscriber access provided by EDINBURGH UNIVERSITY LIBRARY | @ http://www.lib.ed.ac.uk

Article

Fine-tuned Protein Production in Methanosarcina acetivorans C2A Ann A. Karim, Daniel R. Gestaut, Maeva Fincker, John C. Ruth, Eric C. Holmes, Wayne Sheu, and Alfred M. Spormann ACS Synth. Biol., Just Accepted Manuscript • DOI: 10.1021/acssynbio.8b00062 • Publication Date (Web): 19 Jun 2018 Downloaded from http://pubs.acs.org on June 20, 2018

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Synthetic Biology

Fine-tuned Protein Production in Methanosarcina acetivorans C2A Ann A. Karim,∗,† Daniel R. Gestaut,‡ Maeva Fincker,† John C. Ruth,¶ Eric C. Holmes,¶ Wayne Sheu,¶ and Alfred M. Spormann∗,†,¶ †Department of Civil and Environmental Engineering, Stanford University, Stanford, CA ‡Department of Biology, Stanford University, Stanford, CA ¶Department of Chemical Engineering, Stanford University, Stanford, CA E-mail: [email protected]; [email protected]

Abstract Methanogenic archaea can be integrated into a sustainable, carbon-neutral cycle for producing organic chemicals from C1 compounds if the rate, yield and titer of product synthesis can be improved using metabolic engineering. However, metabolic engineering techniques are limited in methanogens by insufficient methods for controlling cellular protein levels. We conducted a systematic approach to tune protein levels in Methanosarcina acetivorans C2A, a model methanogen, by regulating transcription and translation initiation. Rationally designed core promoter and ribosome binding site mutations in M. acetivorans C2A resulted in a predicable change in protein levels over a 60 fold range. The overall range of protein levels was increased an additional 3 fold by introducing the 5’ untranslated region of the mcrB transcript. This work demonstrates a wide range of precisely controlled protein levels in M. acetivorans C2A which will help facilitate systematic metabolic engineering efforts in methanogens.

1

ACS Paragon Plus Environment

ACS Synthetic Biology 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Keywords Methanosarcina acetivorans C2A, transcription, translation, promoter, ribosome binding site, 5’ untranslated region A carbon neutral cycle, where organic chemicals are produced directly from CO2 or from C1 compounds derived from CO2 , will be part of a solution to eliminate the use of fossil fuels. Methanogenic archaea have great potential to be used as a microbial platform to sustainably produce carbon-neutral organic chemicals because these microorganisms efficiently transform C1 compounds. These strictly anaerobic microorganims are specialized to metabolize C1 and C2 compounds and are capable of converting H2 /CO2 , formate, carbon monoxide, acetate, methanol, methylamines, methylsulfides, primary alcohols, secondary alcohols, and methoxylated compounds to methane as part of their energy metabolism. 1–5 Previous work has demonstrated that methanogens can be used to produce hydrogen and convert organic matter into biogas. 6 In addition, metabolic engineering can be used to modify energy metabolism in methanogens to optimize these pathways and produce products other than methane from C1 compounds. 3,7 There is now opportunity for metabolic engineering in methanogens because the energy conservation pathways have been characterized, 1 there is insight into anabolic pathways revealed by whole genome sequencing, 8 and genetics and molecular techniques are well established for some methanogens. 9 Previous metabolic engineering efforts in methanogens have centered around Methanosarcina acetivorans C2A and have increased the rate of methanogenesis, 10 expanded the range of methylated compounds used for methanogenesis to include methyl-esters, 11 and reversed the methanogenesis pathway to synthesize multi-carbon products from methane. 7,12,13 While those previous metabolic engineering efforts have demonstrated the ability to modify the methanogenesis pathway, few attempts have been reported to improve product formation rates, yields, or titers. Improving product formation by tuning pathway fluxes has been challenging because there are limited method for fine-tuned control of protein levels in M. acetivorans C2A using the tetracycline inducible gene expression systems. 14,15 The 2


Page 2 of 38

Page 3 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


tetracycline inducible gene expression systems are most useful when employed as a switch to tightly repress gene expression in the absence of tetracycline and fully induce gene expression in the presence of excess tetracycline. In addition, these systems can be used to tune protein levels at intermediate tetracycline concentrations. However, at intermediate tetracycline concentrations, small changes in tetracycline concentrations lead to large changes in gene expression levels. Therefore, a more reliable way of controlling protein levels that is independent of outside environmental factors is to modify the transcription and/or translation initiation rates by mutating promoter and ribosome binding site (RBS) sequences, respectively. In both Archaea and Eukaryotes, transcription initiation rate is controlled by the same three core promoter elements: the TATA box, the B recognition element (BRE), and the transcriptional start site (TSS) (Figure 1A). 16–18 Transcription is initiated when the TATA binding protein binds the 8 bp TATA box. This is followed by the binding of transcription factor B to the 5 bp BRE located 2 bp upstream of the TATA box. These two transcription factors are sufficient to recruit RNA polymerase and initiate transcription at the TSS typically located 23 bp downstream of the TATA box. The consensus promoter sequence has been determined for Methanosarcina mazei Gö1, a close relative of M. acetivorans C2A. 19 The consensus sequence is the predicted, ideal binding motif for the transcription factors and mutations introduced into this sequence are expected to decrease promoter activity. In addition, in vitro and in vivo promoter mutational studies in Sulfolobus sp. B12, Sulfolobus shibatae, Haloferax volcanii, and Methanococcus vannielii demonstrated that positions 2-5 of the TATA box, positions 4 and 5 of the BRE, and the TSS have a strong influence on transcription initiation rates. 20 Translation initiation in Archaea has been shown to proceed at both leaderless and leadered transcripts. In Sulfolobus solfataricus P2 and Haloferax volcanii DS2, 69 and 72% of the transcripts are leaderless, respectively. 21,22 In Methanosarcina mazei Gö1, Methanolobus psychrophilus, Pyrococcus abyssi GE5, and Thermococcus kodakarensis KOD1 over 85% of

3



the transcripts are leadered transcripts. 19,23–25 A ribosome binding site (RBS) analysis was performed for M. mazei Gö1 and T. kodkarensis KOD1 and 60% and 50% of the total transcripts had RBS that matched the consensus RBS sequence, respectively. 19,25 This suggests for archaeal species containing primarily leadered transcripts, translation initiation involving RBSs is an important form of translation initiation. Translation initiation from RBSs in Archaea is similar to Bacteria and is based on Shine-Dalgarno sequence recognition. 26 While the mechanism is similar to that of Bacteria, 27 the ribosome composition and initiation factors are similar to that of Eukaryotes, which have a different scanning mechanism for translation initiation. 28 It remains unclear how the Eukaryotic-like ribosome composition affects the Bacteria-like translation initiation mechanism in Archaea. 29 Some work has been done comparing leaderless translation initiation to RBS translation initiation in Halobacterium salinarum. More protein is produced from leaderless transcripts compared to leadered transcripts with RBSs suggesting RBSs moderate the rate of translation initiation. 26 These studies highlight different mechanisms of translation initiation are favored by different species of archaea and M. mazei Gö1, a close relative of M. acetivorans C2A, predominantly has leadered transcripts with RBSs. In addition to transcriptional and translational initiation regulation, factors that increase transcript stability or enhance RNA polymerase and ribosome binding have the potential to increase the range of protein levels. 30,31 In this work, rationally designed mutations were introduced into the core promoter and RBS of the methyl coenzyme M reductase β subunit (mcrB ) gene to establish fine-tuned control of protein levels for M. acetivorans C2A. In addition, we identified new enhancing regulatory sequences surrounding two highly conserved promoters Methanosarcina controlling expression of the mcrB and ATPase subunit H, atpH genes. This work for regulating protein levels can be used to modifying pathway flux for metabolic engineering in M. acetivorans C2A.

4


Page 4 of 38

Page 5 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Results and Discussion Design and Validation of Reporter Construct A β-galactosidase reporter system was used to assess protein levels from wild type and mutated methyl coenzyme M β subunit (mcrB, MA_4550) promoters and RBSs in M. acetivorans C2A. The parent reporter plasmid, pAL36, contains the minimal mcrB promoter, the native mcrB RBS, and the full length lacZ gene inserted into the Methanosarcina shuttle vector, pAL23 (Figure 1B, Supplemental Figure 1). The mcrB promoter chosen for this mutational study is a commonly used promoter in Methanosarcina. 14,32–34 A truncated version of the native mcrB promoter, the minimal mcrB promoter, 14 was used because it only contains the core promoter elements which eliminates effects from other potential regulatory sequences. The minimal mcrB promoter was created by deleting a 75 bp portion of the 5’ untranslated region (UTR) starting 18 bp downstream of the TSS. Also, the minimal mcrB promoter has a tetracycline operator directly downstream of the TATA box for inducible gene expression (Figure 1). Next, the mcrB RBS was selected for its predicted high translation rate due to its close match to the consensus Shine-Dalgarno sequence. In addition, lacZ was chosen as the reporter gene because this assay has been used previously for characterizing promoter activity in methanogens. 9 Finally, a single replicating vector has been characterized in Methanosarcina and was used for lacZ expression. 9,35 The copy number of this shuttle vector was determined to be 1-2 copies per chromosome (data not shown). Therefore, LacZ activity was not due to a high copy number of the lacZ gene. All reporter constructs were transformed into M. acetivorans WM60, a derivative of M. acetivorans C2A that has the tetracycline repressor gene integrated into the hpt locus (MA_0717) for tetracycline inducible gene expression. When necessary, all strains were fully induced with 35 µg/mL tetracycline 14 and it was confirmed the LacZ activity was stable over the OD600 sampling range (Supplemental Figure 2). All LacZ activities were assayed for methanol grown cells unless stated otherwise. LacZ activity associated with the minimal mcrB promoter

5



Page 6 of 38

(pAL36, AS1056) was measured for every experiment to normalize LacZ activities between experiments. Each LacZ activity is reported as the mean of three biological replicates and the error is reported as one standard deviation. The strains assayed for LacZ activity in this work are listed in Table 1.

A) Consenus Promoter and RBS CAAAA NN TTTATATA N21 YR Nx NNNNTTAGGAGGTNNNNN ATG

B) Minimal mcrB Promoter and mcrB RBS CAAAA GA TTTAAGTA CCCTATCAGTGATAGAGA TTT CA TTGGGAATAGTGGACACTCGA GAATTAAGGAGGAAATTAAA ATG -30

-20

-10

-1+1

+10

+20

+30

+40

C) Partial Deletion of the Minimal mcrB Promoter TATCGGAGAACA CAA CCCTATCAGTGATAGAGA TTT CA TTGGGAATAGTGGACACTCGA GAATTAAGGAGGAAATTAAA ATG -30

-20

-10

-1+1

+10

+20

+30

+40

Figure 1: A) Consensus Methanosarcina promoter and RBS sequence. The consensus BRE and TATA box from Methanosarcina mazei Gö1 are shown. 19 The consensus TSS based on 3 RNA-seq experiments in archaea is a pyrimidine/purine motif with transcription initiating at the purine. The consensus spacing between the end of the TATA box and the pyrimidine/purine motif of the TSS is 21 bp. 21–23 These RNA-seq experiments for the consensus TSS sequence and spacing are consistent with archaeal promoter mutational studies. 36 The perfect match for M. acetivorans C2A Shine-Dalgarno sequence is shown. The ideal spacing for bacterial Shine-Dalgarno sequence to the start codon is 5 bp, and a similar ideal spacing has been measured for one archaea, Halobacterium salinarum. 26 The standby site 4 bp directly upstream of the Shine-Dalgarno sequence contacts the ribosome in a sequence independent manner. 37 The ideal start codon is ATG, which is complimentary to the initiating tRNAM et . The 5’ untranslated region between the TSS and start codon can have variable length and over 50% of the transcripts sequenced for M. mazei Gö1 had 5’ UTR’s longer than 50 bp. 19 B) The minimal mcrB promoter region used as the template for core promoter and RBS mutations (pAL36, AS1056). C) The minimal mcrB promoter region with a deleted portion of the core promoter (pAL48, AS1057). pink: BRE, red: TATA box, blue: tetO, orange: TSS, green: RBS, yellow: start codon, overline: direct interaction of basal transcription factors with DNA bases, 38 underline: Shine-Dalgarno sequence, and bold: standby site. The numbering starts at the TSS indicated by the arrow.

To establish that LacZ activity was controlled by the minimal mcrB promoter, the core promoter was interrupted. A reporter construct with a deleted portion of the core promoter 6


Page 7 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Table 1: Strains and plasmids. The M. acetivorans WM60 strains assayed for LacZ activity. The Spormann lab strain designation and plasmid numbers are listed. Strain

Plasmid

Parent Plasmid

AS1058

pAL14

BRE 4th position A → G

AS1059

pAL15

TATA box 1st postion T → G

AS1060

pAL16

TATA box 2nd postion T → G

AS1061

pAL17

TATA box 3rd postion T → G

AS1062

pAL18

AS1063

pAL19

TATA box 5th postion A → G

AS1064

pAL20

TATA box 6th postion G → A

AS1065

pAL21

TATA box 7th postion T → G

AS1128

pAL22


AS1052

pAL23

pWM321

empty plasmid

background LacZ activity

AS1056

pAL36

pAL23

minimal mcrB promoter, mcrB RBS

reference LacZ activity

AS1129

pAL39

∆Gtot = -7.8 kcal/mol

AS1130

pAL40


AS1133

pAL41


AS1131

pAL42

AS1134

pAL43

∆Gtot = 0.8 kcal/mol

AS1135

pAL44


AS1136

pAL45


AS1132

pAL46

AS1057

pAL48

minimal mcrB promoter deletion

background promoter activity

AS1157

pAL54

full length mcrB 5’ UTR from M. barkeri Fusaro

enhancer sequence

AS1158

pAL55

M. mazei Gö1 consensus promoter

maximum core promoter activity

AS1160

pAL93

combined pAL15 and pAL39 mutations

AS1161

pAL94


AS1162

pAL95


pAL36

Relevant Genotype

Relevant Phenotype

weakened promoter


mcrB RBS mutation

strengthened promoter weakened promoter



pAL36

7


combined activities


Parent Plasmid

Relevant Genotype

Page 8 of 38

Strain

Plasmid

Relevant Phenotype

AS1165

pAL96

AS1166

pAL97

AS1163

pAL98


AS1170

pAL99

atpH promoter region with tetO1 replacing the minimal mcrB promoter

AS1204

pAL100

deleted upstream AT-rich region

repressor sequence

AS1205

pAL101

deleted downstream AT-rich region

enhancer sequence

AS1216

pAL102

deleted upstream and downstream AT-rich regions

AS1206

pAL112

variable hairpin deletion

AS1218

pAL113

inner backbone mutation

AS1203

pAL114

AS1209

pAL115

AS1233

pAL116

combined pAL17 and pAL39 mutations pAL36

pAL99

pAL54


combined activities

weakened predicted secondary structure

outer backbone mutation RBS hairpin mutation

strengthened predicted secondary structure weakened predicted secondary structure

(pAL48, AS1057) was created by removing the 4th position of the BRE to the 8th position of the TATA box in the minimal mcrB reporter construct (pAL36, AS1056, Figure 1). This deletion is expected to have very weak promoter activity due to the extensive deviation from the consensus promoter sequence. The non-induced and induced LacZ activity associated with the deleted promoter was compared to either the empty plasmid (pAL23, AS1054) with no promoter and no lacZ gene to determine the background LacZ activity in the cell extract or to the minimal mcrB promoter (pAL36, AS1056) to determine the level of inducible lacZ expression (Figure 2). LacZ activity associated with the empty plasmid (pAL23, AS1054) was less than 2.5 Miller Units (MU) demonstrating that there is low background LacZ activity in the cell extract. Next, induction of the deleted promoter (pAL48, AS1057) caused less than a 2 fold increase in LacZ activity from 14 ± 1 MU uninduced to 23 ± 1 MU induced. The slight increase in LacZ activity upon induction is likely caused by an alternative, weak promoter upstream of the minimal mcrB promoter, which was further investigated later in 8


Page 9 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


the paper. In addition, LacZ activity associated with the minimal mcrB promoter (pAL36, AS1056) had a 40 fold increase upon induction from 21 ± 1 MU uninduced to 859 ± 74 MU induced. Therefore, the minimal mcrB promoter reporter construct controls a majority of the tetracycline inducible lacZ expression. While there is some leaky promoter expression as demonstrated by the increase in non-induced LacZ activity associated with both reporter constructs relative to the empty plasmid, this leaky expression is small compared to the induced LacZ activity associated with the minimal mcrB promoter. Therefore, the low background LacZ activity and strong activation upon induction of LacZ activity by the minimal mcrB promoter makes this experimental platform useful to characterize promoter strength. It was investigated if LacZ activity changed when a strain was grown with different electron donors. The induced LacZ activity associated with the minimal mcrB reporter construct (pAL36, AS1056) was 2 fold higher in cells grown on methanol (1141 ± 82 MU) relative to acetate (575 ± 92 MU, Supplemental Figure 3, Supplemental Table 1). The LacZ activities are not consistent with M. acetivorans C2A proteomic data where there was close to a 3 fold decrease in McrB protein abundance during growth on methanol relative to acetate. 39 This difference in proteomic data is not unexpected because the promoter region in the minimal mcrB reporter construct was modified from the native promoter characterized in this study. It is unclear if the change in promoter sequence in the minimal mcrB reporter construct influenced targeted promoter regulation based on electron donor or influenced global regulation of transcription or translation, which could be affected by the slower growth rate on acetate. 40 These results demonstrate that the same LacZ activity cannot be expected from the minimal mcrB promoter for different growth substrates.

9



Non−induced

Induced

1000

LacZ Activity (Miller Units)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 10 of 38

100

Plasmid Empty Deleted Promoter

10

Minimal mcrB Promoter

1

Figure 2: Inducibility of the minimal mcrB promoter and deleted promoter. Non-induced and induced LacZ activity of the strains containing the empty plasmid with no promoter and no lacZ gene (pAL23, AS1054), the reporter constructs with the wild type minimal mcrB promoter (pAL36, AS1056) and with a portion of the core minimal mcrB promoter deleted (pAL48, AS1057). The small increase in LacZ activity of the empty plasmid upon induction is likely due to a small fraction of tetracycline becoming transformed into a yellow derivative 41 during incubation with tetracycline.

Effect of Core Promoter Mutations on Promoter Activity The dependence of transcription initiation on promoter nucleotide sequence was investigated by introducing specific base pair substitutions in the core promoter. First, the consensus promoter sequence was tested because it is expected to have one of the highest core promoter activities. Therefore, the LacZ activity from the consensus promoter places an upper limit on the expected LacZ activities from core promoter mutations. The consensus promoter was introduced into the minimal mcrB reporter construct from Methanosarcina mazei Gö1 (pAL55, AS1158), 19 which is expected to be similar to the consensus promoter for M. acetivorans C2A. The 5th and 6th position of the TATA box of the minimal mcrB promoter were substituted from AG to TA. The LacZ activity associated with the minimal mcrB promoter (741 ± 12 MU, pAL36, AS1056) was 79% of the LacZ activity associated with the consensus 10


Page 11 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


promoter (939 ± 82 MU), indicating the core mcrB promoter has relatively strong activity. To fine-tune transcription initiation, a rationally designed promoter library was generated by introducing single nucleotide substitutions into core promoter elements of the minimal mcrB promoter. The introduced mutations were selected based on previous promoter mutational studies performed in archaea outside of Methanosarcina. In those studies, introducing a C or a G into any position of the TATA box, or into the 4th or 5th position of the BRE decreased promoter activity. In addition, a strong reduction in promoter activity was observed when positions 2-5 of the TATA box were mutated to either a G or C. 36,42–45 Some of these previously tested mutations were introduced into the minimal mcrB promoter and tested in M. acetivorans C2A (Figure 3, Supplemental Table 3). All changes in LacZ activities due to the promoter mutations were compared to the LacZ activity associated with the minimal mcrB promoter (pAL36, AS1056). A or T → G mutations introduced into positions 2-5 of the TATA box reduced LacZ activity to 5-15% of the strain with the minimal mcrB reporter construct (pAL16-19, AS1060-AS1063). Introducing these substitutions into other positions of the TATA box reduced LacZ activity to 20-40% (pAL15, AS1059; pAL21, AS1065; pAL22, AS1128). An A → G mutation in the 4th position of the BRE reduced the LacZ activity to 15% (pAL14, AS1058) and a G → A mutation introduced into the TATA box at the 6th position enhanced LacZ activity by 23% (pAL20, AS1064). Overall, the obtained promoter sequences changed LacZ activity 24 fold between the promoter with the lowest and highest activity demonstrating a wide range of promoter activities based on single SNP’s. These trends are similar to the effects observed in previous promoter mutation studies in other archaea and support the concept of the conserved function of the basal transcription machinery in Archaea. 36,42–45 The promoter library developed in this work can be used directly to regulate gene expression, and the position specific trends will be useful when modifying expression of other promoters assuming these promoters are independent of other forms of regulation.

11



1000


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 12 of 38

750

SNP A

500

G

250

0 C A C A A A A G A T T T A A G T A C C

Figure 3: The induced LacZ activity associated with core promoter SNP’s introduced into the minimal mcrB reporter construct. The minimal mcrB promoter sequence is listed on the x axis. pink: BRE, red: TATA box, and blue: tetO. The gray horizontal line represents the LacZ activity associated with the minimal mcrB promoter. The SNP legend describes the mutation introduced into the minimal mcrB promoter sequence. Positions without bars were not tested. Plasmids, strains, promoter mutations, and LacZ activities from this experiment are listed in Supplemental Table 3.

Effect of Mutations in the RBS on Translation Initiation A previously developed translation initiation rate model was tested in M. acetivorans C2A to determine whether RBS mutations designed by the model could be used to control protein levels. This model 37,46 predicts translation initiation rates based on RNA interactions between the ribosome unbound and bound to the transcript at the RBS. The translation initiation rate (r) is predicted to be the pre-exponential factor (A) times the exponent of an apparent Boltzmann constant for the system (β) multiplied by the predicted ∆Gtot , r = Aexp(−β∆Gtot ). The pre-exponential factor, A, describes the number of translation initiation events which depends on factors such as the number of transcripts and ribosomes in the cell. The predicted ∆Gtot is the strength of the ribosome-transcript interaction and a more negative ∆Gtot correlates with faster translation initiation. The apparent Boltzmann 12


Page 13 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


constant describes how the translation initiation changes with ∆Gtot . A larger apparent Boltzmann constant leads to a larger change in the translation initiation with changing ∆Gtot . We tested the model in M. acetivorans C2A by mutating the native mcrB RBS in the minimal mcrB reporter construct (pAL36, AS1056) based on the degenerate sequence AANNNNNNAGGNAATTAAA to 8 RBS’s with a range of ∆Gtot between -7.8 and 6.9 kcal/mol (Supplemental Tables 4-6). The LacZ activities associated with the RBS mutations and the minimal mcrB promoter were measured (Figure 4; plasmids, strains, RBS sequences, and LacZ activities are listed in Supplemental Table 6). This work found the translation initiation rate model fit the data (R2 = 0.72, average ∆∆Gtot = 2.33 kcal/mol). There was a 15 fold change in LacZ activity between the weakest and strongest RBS. The translation initiation rate model was also tested for acetate grown cells. The relationship between LacZ activity and ∆G did not change by electron donor, demonstrating the same translation initiation rate model can apply to growth on different electron donors (Supplemental Figure 4; plasmids, strains, LacZ activities are listed in Supplemental Table 6). The effect of promoter activity on the fit of the translation initiation rate model was tested. Combinations of promoter and RBS mutations were tested in the same reporter construct (Figure 5; plasmids, strains, and LacZ activities are in Supplemental Table 7). There was no significant change in the apparent Boltzmann constant when promoters with different activities were tested. This demonstrates that the translation initiation rate model fit is unaffected by promoter activity. A 66 fold change in LacZ activity was observed from the promoter-RBS combination with the lowest and highest activity. This is a much larger range of LacZ activities than observed from promoter or RBS mutations alone.

13



y = 163.2 exp(− 0.17x)


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 14 of 38

R2 = 0.72

1000

RBS Native 100

Mutated

10 −8

−6

−4

−2

0

2

4

6

Predicted ∆Gtot (kcal/mol) Figure 4: Testing the translation initiation rate model in M. acetivorans C2A. A protein translation initiation rate model 37,46 was used to design 8 RBS with different translational efficiencies indicated by different predicted ∆ Gtot ’s and these mutations were introduced into the minimal mcrB reporter construct. The LacZ activity vs.∆ Gtot was reported for the strains harboring the native RBS and the mutant RBS reporter constructs. The plasmids, strains, and LacZ activities for this experiment are listed in Supplemental Table 6.

14


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60



Page 15 of 38

1000

Promoter/RBS Mutations Strong/Native Strong/Mutated 100

Medium/Mutated Weak/Mutated

10 −8 −6 −4 −2

0

2

4

6

Predicted ∆Gtot (kcal/mol) Figure 5: Translation initiation rate model tested with promoters of different strengths. All of the promoters tested were derivatives of the minimal mcrB promoter. The strong promoter was the wild type minimal mcrB promoter, the medium promoter had a G mutation in the first position of the TATA box, and the weak promoter had a G mutation in the 3rd position of the TATA box. The RBS’s tested were the native mcrB RBS or some of the mutated RBS designed by the protein translation initiation rate model (Supplemental Table 5). For the promoter and RBS mutant combinations, a linear regression with an interactive term was conducted in order to examine if the relationship between LacZ activity and ∆Gtot varied by promoter. The main effect of LacZ activity on ∆Gtot for the strong promoter was significant (F(5,21) = 238.8, p < 0.05, β = 0.17 mol/kcal). However, there is a non-significant change in this relationship for either the medium promoter (∆β = -0.01 mol/kcal, p > 0.1) or weak promoter (∆β = 0.01 mol/kcal, p > 0.1) compared to the strong promoter. The plasmids, strains, and LacZ activities for this experiment are listed in Supplemental Table 7.

Interestingly, the apparent Boltzmann constant for M. acetivorans C2A (0.17 mol/kcal) was smaller than reported for E. coli BL21, Pseudomonas fluorescens, Salmonella typhimurium LT2, and Corynebacterium glutamicum (average β of 0.42 mol/kcal). 47 The smaller apparent Boltzmann constant represents a slower change in translation initiation with changing ∆ Gtot leading to a smaller range in protein levels based on RBS regulation. This smaller range in protein level could be from differences in the ribosome composition due to evolutionary, 28 growth rate, 40 or specific M. acetivorans C2A differences. The model needs to be applied to more archaea and slower growing prokaryotes to determine what factors are responsible for 15



the smaller apparent Boltzmann constant in M. acetivorans C2A. The non-induced activity of promoter and RBS mutations were also tested to investigate the cause of the low background LacZ activity previously observed in the reporter construct (Figure 2). Core promoter mutations had a smaller effect on non-induced LacZ activity than RBS mutations (Figure 6; plasmids, strains and LacZ activities are in Supplemental Table 8). Therefore, the non-induced LacZ activity is likely the result of the presence of an alternative promoter with low activity, potentially in the AT-rich region upstream of the mcrB promoter in this construct.

Non−induced LacZ Activity (Miller Units)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 16 of 38

Induced

1000

Mutation 100

None: Minimal mcrB TATA Box: GTTAAGTA TATA Box: TTGAAGTA RBS: ∆Gtot = −1.8 kcal/mol

10

RBS: ∆Gtot = 6.9 kcal/mol

1

Figure 6: Inducible LacZ activity associated with mutated promoters and RBSs. Noninduced and induced LacZ activity comparing strains with the minimal mcrB reporter construct to strains with promoter and RBS mutations in the minimal mcrB reporter construct. The plasmids, strains, and LacZ activities for this experiment are in Supplemental Table 8.

The promoters and translation initiation rate model described in this work can be used to fine-tune protein levels in M. acetivorans C2A which will be a useful tool for controlling flux for metabolic engineering. In addition, a better understanding of regulation of transcription and translation initiation will help predict genes with other forms of regulation based on discrepancies between measured protein levels and predicted protein levels based on predicted 16


Page 17 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


initiation rates.

Regulatory Effect of Full Length mcrB 5’ UTR The nucleotide sequences surrounding core promoters and RBSs were investigated for potential regulatory sequences that could be used to expand the range of protein levels in the cell. The 5’ UTR was investigated for its ability to enhance transcript stability. Previous work has shown that more than half of the expressed transcripts in the M. mazei Gö1 have 5’ UTRs averaging 150-200 bp in length 19 and a similar trend is assumed for M. acetivorans C2A. The abundance of 5’ UTRs is likely an important form of regulation for controlling translation initiation and RNA half-lives. 48 This work focused on the mcrB 5’ UTR sequence because it is highly conserved across the 26 Methanosarcina complete genomes (85% of 5’ UTR positions had over 90% sequence similarity) which suggests a conserved function (Supplemental Figure 5 and Supplemental Table 9). In addition, predicted secondary structure was found for many of the mcrB 5’ UTR sequence variants (Supplemental Figure 6). In E. coli, secondary structure in the 5’ UTR has been associated with regulation that enhances transcript stability by preventing nucleases from degrading the mRNA, or with regulation that prevents translation initiation by shielding the RBS from the ribosome. 37,49 For the mcrB 5’ UTR (Figure 7A and B) there is an outer backbone structure that forms directly at the 5’ end and is conserved in all of the sequence variants except M. mazei TucO1 (Supplemental Figure 6). In addition, an inner backbone structure is conserved in 10 out of 14 variants. Finally, there is a variable hairpin region that can form a straight or branching hairpin in the variants with the conserved outer and inner backbone structure. Based on the predicted secondary structure in the native mcrB 5’ UTR, the secondary structure could contribute to transcript stability and in turn help increase overall protein levels. The effect of the 5’ UTR on protein levels was tested by inserting the 5’ UTR from Methanosarcina barkeri Fusaro into the minimal mcrB reporter construct. In addition, mutations were introduced into the reporter construct that either interrupted or stabilized the 17



predicted 5’ UTR secondary structure (the mutations are described in Figure 7B; plasmids, strains, and LacZ activities are listed in Supplemental Table 10; the 5’ UTR secondary structures are described in Supplemental Figure 7). The LacZ activity associated with native 5’ UTR (pAL54, AS1157) was enhanced 3 fold compared to the LacZ activity associated with minimal mcrB promoter (pAL36, AS1056, Figure 7C). For the single, destabilizing mutation introduced in the outer backbone (pAL114, AS1203), the LacZ activity was reduced 53% compared to the native 5’ UTR. The LacZ activity associated with 5’ UTR mutations other than the outer backbone mutation only changed by ±20% compared to the native 5’ UTR reporter construct. The larger reduction in LacZ activity associated with the outer backbone 5’ UTR mutation is consistent with higher rates of transcript degradation by 5’ to 3’ exonucleases such as RNAse J (MA0605: protein inferred from homology). In E. coli, RNAse J degrades single stranded RNA, and this degradation is accelerated due to the destabilized secondary structure from the outer backbone mutation at the 5’ end of the transcript. 49,50 While there is a clear phenotype associated with the outer backbone mutation in M. acetivorans C2A, future work needs to be performed to confirm that disruption of the 5’ UTR secondary structure is the mechanism through which the mutation is affecting protein production.

18


Page 18 of 38

Page 19 of 38

A) CAAAA GA TTTAAGTA CCCTATCAGTGATAGAGA TTT CA TTGGGA ATAG TGGACACTTA A AAACAAAGCGGTACTTGATTTATT -25

-1+1

+25

GAGTGCAAAGGCACTCGAG TAGGTGACCA G TCCCAA AA TGATTTT AAT AAATTAAGGAG GAAATTA AA ATG +50

+100

+75

B)

C) variable hairpin (deleted)


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


inner backbone

outer backbone

RBS hairpin

4000

5’ UTR Mutation 3000

Minimal mc rB Native Outer Backbone

2000

Inner Backbone Strengthened RBS Hairpin Weakened RBS Hairpin

1000

Deleted Variable Hairpins

0

Figure 7: Effect of including the full length mcrB 5’ UTR on LacZ activity A) The sequence of the minimal mcrB promoter modified with native full length 5’ UTR from M. barkeri Fusaro. pink: BRE, red: TATA box, blue: tetO, orange: TSS, solid green: native mcrB RBS, yellow: start codon, dashed green: RBS hairpin, solid black: outer backbone, dashed black: inner backbone, gray: variable hairpin region, underline: Shine-Dalgarno sequence, and bold: standby site. B) Predicted 5’ UTR RNA secondary structure. Mutations introduced into the 5’ UTR are labeled. Single SNP’s introduced into the 5’ UTR are noted by arrows and multiple base mutations in a single reporter construct are indicated by brackets. The overall free energy of secondary structure formation is noted in the bottom right corner. C) Induced LacZ activity comparing the strain with the minimal mcrB promoter construct to the strains with the full length 5’ UTR and mutated 5’ UTR reporter constructs. The plasmids, strains, and LacZ activities for this experiment are listed in Supplemental Table 10.

In order to study the overall enhancement of the mcrB 5’ UTR sequence compared to other forms of enhancing regulation, the transcript level of the native mcrB promoter was compared to other transcript levels. The mcrB transcript levels were measured in wild type M. acetivorans C2A (DSMZ 2834). Previous work set a reference for transcript levels in M. acetivorans C2A by characterizing 20 catabolic transcripts with RT-qPCR in reference

19



to the transcript level for a constitutively expressed transcript MA_3998, a predicted ABC transporter, ATP-binding protein. The MA_3998 transcript is present in low to medium amounts compared to the 20 other catabolic mRNA. 51 This work calculated the fold change of the mcrB transcript level relative to MA3998 as 1.5 ± 0.6 using RT-qPCR (Supplemental Figure 8). While this work demonstrates that the mcrB promoter is strong due to its high similarity to the core consensus promoter and has potential enhanced transcript stability due to the 5’ UTR secondary structure, it is not the transcript with the highest abundance compared to the other reference catabolic transcripts. This indicates that other forms of regulation can enhance transcript levels even further in these highly abundant catabolic transcripts.

Effects of Regulatory Sequences Surrounding the atpH Promoter The effect of other potential regulatory sequences surrounding core M. acetivorans C2A promoters were investigated through a general bioinformatic screen of highly conserved sequences. Out of 1590 homologous genes examined that were shared between the 26 complete Methanosarcina genomes, 331 homologous genes contained a TSS identified in M. mazei Gö1, 19 and 9 of these promoter regions were highly conserved (Supplemental Table 11). Due to the strict selection criteria, some highly conserved promoter regions were missed by this screen, including the mcrB promoter. The highly conserved atpH promoter (MA_4152, Supplemental Figure 9) was chosen for further investigation because the atpH transcript is one of the most abundant catabolic mRNA during growth on both methanol and acetate. 51 However, the atpH core promoter is not predicted to be strong due to a G in the 5th position of the BRE. This suggests another form of regulation besides basal regulation is causing the high transcript level. One potential regulatory region is an inverted repeat which overlaps the BRE (5’-CTTCG-7N-CGAAG). Inverted repeats that overlap promoter elements are associated with transcription factor binding sites in Archaea. 31 Another potential regulatory sequence, which is highly conserved 20


Page 20 of 38

Page 21 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


is a 32 bp 100% AT-rich sequence located in the 5’ UTR that overlaps the RBS. This sequence also has an inverted repeat (5’-AATTTA-5N-TAAATT) which could be a binding site for a regulatory protein. 31 Alternatively, AT-rich regions have been shown to help facilitate ribosome recruitment in bacteria independent of the Shine-Dalgarno sequence, and it is unclear whether a similar mechanism could operate in Archaea. 52 It is unlikely that secondary structure is involved in the regulation of this AT-rich region because the secondary structure from the three different 5’ UTR sequence variants across the 26 complete Methanosarcina genomes did not have highly conserved structures (Supplemental Figure 10). Finally, there is another 166 bp potential conserved AT-rich region (60% of the alignment had over 90% sequence similarity) located upstream of the core promoter. An interesting feature of this sequence is that it is comprised of 11 instances of three or more repeated T’s. Similar repeats have been observed surrounding other promoter regions and these regions have been compared to potential TATA boxes. 53 Having multiple TATA box binding sites surrounding a promoter region could help concentrate the TATA binding protein close to the promoter region for more frequent transcription initiation events. The LacZ activities associated with the atpH promoter was compared to the minimal mcrB promoter. A reporter construct was created using the atpH promoter region starting with the AT-rich region upstream of the promoter and continuing through the atpH RBS. A tetracycline operator for inducible expression was inserted 23 bp upstream of the TSS to not affect other regulation sites surrounding the core promoter (Supplemental Figure 11). However, the tetracycline operator could not act as a transcriptional block in this location and the expression of the reporter construct was not repressed (Supplemental Figure 12, Supplemental Table 14). The induced LacZ activity associated with the atpH promoter (pAL99, AS1170) was 75% of the minimal mcrB promoter (pAL36, AS1056) despite the high reported transcript levels from the native atpH transcripts 51 (Figure 8). The lower LacZ activity associated with atpH promoter can be partially attributed to the weak atpH RBS (Supplemental Table 12).

21



Next, the regulatory effect of the two conserved AT-rich regions in the atpH reporter construct was investigated by introducing single and double deletions of the conserved ATrich regions. To ensure the RBS was not affected, only a 28 bp AT-rich region downstream of the core promoter was deleted, leaving the four bp directly upstream of the RBS. The LacZ activity associated with the deletion of the AT-rich upstream region was increased by 138% (pAL100, AS1204) compared to the full length atpH reporter construct (pAL99, AS1170) and the LacZ activity associated with the deletion of the downstream region was decreased by 70% (pAL101, AS1205, Figure 8). Therefore, the upstream AT-rich region acts as a repressor and the downstream AT-rich region acts as an enhancer. Interestingly, the repression and enhancement for these regions appear to be independent because LacZ activity associated with the double deletion mutation (pAL102, AS1216) has the additive effects of each individual deletion. These AT-rich regions are involved in regulation and future work can investigate the mechanism of regulation.

22


Page 22 of 38

Page 23 of 38

A) TTTTTTATCAATTAATTATATTCAACTGTTTCTATTTAATTATTTTTTACTGTTCTATTTAATCTTTT -175

-200

GGATTTTAACCATATATTTTGATATTTATATTTTTAAAATTCTTAAAAATTTCCTGCACATTCAGT -125

-150

-100

ACATAATGATTGATCGTGATAATTATTAAT GTCCTCTTCGATAAAAC CGAAG CT GTTATATA G -75

-50

-25

TTCTTTCGCAAAGGATTTGT TA ACTAACCTCCATTGGAGTAGGG CCCTATCAGTGATAGAGA +25

-1+1

TTTTTAATTATTAATTTATATATTAAATTTT GAGAGACGGAGATTCAC ATG +50

+10

+20

+75

B) LacZ Activity (Miller Units)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


1000

Mutation Minimal mc rB promoter a tpH promoter

Upstream deletion Downstream deletion

500

Double deletion

0

Figure 8: A) atpH promoter region sequence modified with the tetracycline operator. pink: BRE, red: TATA box, blue: tetO, orange: TSS, green: native mcrB RBS, yellow: start codon, solid gray: upstream AT-rich sequence, dashed gray: downstream AT-rich sequence underline: Shine-Dalgarno sequence, and bold: standby site. B) Induced LacZ activity of the strains containing the minimal mcrB reporter construct compared to the strains with the atpH reporter constructs with the full length and AT-rich upstream, downstream, and double deletions. The plasmids, strains, and LacZ activities for this experiment are listed in Supplemental Table 14.

These results show that the mcrB promoter and atpH promoter display two types of regulation. The mcrB promoter has low transcript abundance due to the lack of enhancing regulatory sequences but has high protein abundance due to the strong RBS. This contrasts the regulation surrounding the atpH promoter which has high transcript abundance 51 but

23



low protein abundance. There is less variation in protein production associated with strong promoters and weak RBSs; therefore, the protein produced from the atpH reporter construct is expected to be more stable. 54 Future work needs to be performed to understand why these different forms of regulation evolved for these specific genes and how this affects cell physiology. Investigating conserved promoter regions across Methanosarcina identified new regulatory sequences surrounding the core promoter. The 5’ UTR from the mcrB promoter had a much larger effect on LacZ activity, enhancing LacZ activity 3 fold, compared to the AT-rich 5’ UTR region from the atpH promoter, which only enhanced LacZ activity by 30%. If the enhancement from the mcrB 5’ UTR is only dependent on RNA secondary structure, and is independent of any additional regulatory protein, then this form of regulation can be widely applied to expand range of protein production beyond what is possible with basal regulation. In summary, our work applied frameworks developed in other strains for regulating transcription and translation initiation in M. acetivorans C2A and tested these frameworks with a LacZ reporter system. The LacZ activity was precisely varied over a 60 fold range with different promoter and RBS combinations. This approach only required a small number of reporter constructs to be tested to demonstrate fine-tuned protein levels which is important for difficult to culture and transform strains such as M. acetivorans C2A. In addition, we investigated other native forms of regulation that had potential to expand protein production beyond what is possible by transcription and translation initiation regulation. The 5’ UTR of the mcrB promoter expanded the protein production range 3 fold. While this increase in protein production could be related to secondary structure at the 5’ UTR, the mechanism of this regulation needs to be confirmed. The tools developed in this work will facilitate precise engineering of complex metabolic fluxes in M. acetivorans C2A and other methanogens.

24


Page 24 of 38

Page 25 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Methods Strains and Cell Culture Escherichia coli DH5α λ pir 55 was used for plasmid construction. M. acetivorans C2A was purchased from DSMZ (Braunschweig, Germany). M. acetivorans WM60 14 was kindly provided by William Metcalf. M. acetivorans strains were cultured in modified high salt medium with 125 mM methanol unless stated that the cells were grown on 50 mM acetate. If necessary, 1 µg/mL puromycin was added (Supplemental Information Section 1). When strains were induced, 35 µg/mL tetracycline was added for full induction. Agarose shakes for selecting single colonies were performed in modified HS medium with 0.5% agarose based on the previously described top plate layer (Supplemental Information Section 2). 56 This shake method does not require H2 S addition. M. acetivorans strains were cultured without agitation at 37◦ C.

Plasmid Construction The plasmid maps for the new cloning vectors created in this work are shown in Supplemental Figure 1. The list of plasmids and strains used in this work are listed in Table 1 and Supplemental Table 15. Sequence diagrams were created with Snapgene (GSL Biotech LLC, Chicago, IL). A new Methanosarcina cloning vector, pAL23, was constructed using Gibson assembly following the manufacturer’s protocol (NEB, Ipswich, MA). pAL23 is comprised of the pWM321 vector backbone, 35 kindly provided by William Metcalf, with the original lacZα multiple cloning site (MCS) replaced by the multiple cloning site from pST39 (NCBI accession: MG595924). 57 The minimal mcrB reporter construct, pAL36, was constructed using overlap extension PCR and in gel ligation. The insert for the minimal mcrB reporter construct, pAL36, was constructed using overlap extension PCR 58 to add the full length lacZ gene from E. coli 25



Page 26 of 38

MG1655 behind the minimal mcrB promoter 14 and mcrB RBS (Figure 1). Construction of pAL36 was completed using in gel ligation 59 to place the pAL36 insert into the pAL23 vector between the BamHI and KpnI restriction sites (NCBI accession: MG595925). The atpH reporter construct, pAL99, was constructed using overlap extension PCR and in gel ligation. M. acetivorans C2A genomic DNA was extracted with the Qiagen blood and tissue kit following the gram negative protocol. The atpH promoter region was amplified from the M. acetivorans C2A genomic DNA extraction and PCR sewing was used to add the tetracycline operator and lacZ gene. In gel ligation was used to insert the atpH promoter region with lacZ gene between the BamHI and EcoRV restriction sites in pAL36. The exact sequence replacing the minimal mcrB promoter region in pAL36 including the BamHI restriction site and start codon is in Supplemental Figure 11. All mutations introduced into the promoter regions of pAL36 or pAL99 reporter constructs were produced using overlap extension PCR, or quick change in a subcloning vector pAL38. Quick change could not be performed directly in pAL36 because the Q5 polymerase could not amplify the entire plasmid (data not shown). Quick change was performed in pAL38, a plasmid with the promoter-lacZ portion between the BamHI and EcoRV restriction sites inserted into the pCDF-polycistronic vector, a small subcloning vector. pCDFpolycistronic was created by truncating the vector backbone from pCDFDuet (EMD Millipore, Billerica, MA) and replacing the native MCS with the MCS from pST39. 57 In gel ligation was used to insert the mutated sequences between the BamHI and EcoRV restriction sites in pAL36. The minimal mcrB promoter and RBS mutations are listed in Supplemental Tables 3 and 6, respectively. The full length mcrB 5’ UTR mutations are listed in Supplemental Table 10. Methanogen transformations with DOTAP Liposomal Transfection Reagent (Sigma-Aldrich Corp., St. Louis, MO) were performed as previously described. 35

26


Page 27 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


β-galactosidase Assay The β-galactosidase assay was modified based on previously described methods. 60 All samples were taken during mid exponential phase where the LacZ activity is stable (data not shown) and frozen in LacZ buffer modified with 2% glycerol to prevent activity loss upon freezing (data not shown, detailed protocol in Supplemental Information Section 3). All assays in the same graph were conducted on the same day with the same reagent preparations. Error bars represent one standard deviation of triplicate biological samples. The results were reported in Miller Units = 1000 x OD420 / (OD600 x time (min) x culture volume (mL))

RNA Extraction and Reverse Transcription RNA was extracted using the Ambion Bacterial RNApure Kit with DNAse I treatment according to the manufacturer protocol (Life Technologies, Carlsbad, CA) with 4.5 mL of culture grown to a OD600 between 0.5 and 0.6. The total RNA was quantified using the nanodrop (Thermo Scientific, Waltham, MA). Clear 16S and 23S rRNA peaks were observed on an agarose gel demonstrating no RNA degradation. Reverse transcription was performed with a dilution series of the RNA extraction using the iScript cDNA synthesis kit with random primers following manufacturer’s protocol (Biorad, Hercules, CA).

qPCR qPCR was performed with SsoAdvanced Universal SYBR Green Supermix on the CFX384 Real Time System thermocycler according to the manufacturer’s protocol. Data was analyzed with the Bio-rad CFX Manager 3.1 Software (Bio-rad, Hercules, CA). The primers were taken from previous work, 51 or were created with Primer3 61 with a melting temperature of 60◦ C, a primer length between 18-24 bp, a product length between 75-150 bp, and a primer GC content of 50-60% (Supplemental Table 13). Primers were selected that had at least 3 mismatches based on a short sequence BLASTn search (10 max E-value, 7 word size, no low

27



complexity filter, 5 open gap cost, 2 extend gap cost, 2 match, and -3 mismatch) 62 to other locations in the M. acetivorans C2A genome (RefSeq NC_003552). qPCR standard curves were created with a 10 fold serial dilution between 106 to 102 copies per reaction. qPCR DNA standards were from M. acetivorans WM60 genomic DNA extracted using the Blood and Tissue Kit (Qiagen, Germantown, MD) following the gram negative bacteria protocol with RNAse A treatment. The DNA concentration was quantified with the Qubit dsDNA BR kit (Life Technologies, Carlsbad, CA). The regression method was used to calculate Cq values. Triplicate qPCR reactions were performed for each standard and sample. All assays had efficiencies 90% or above and R2 values above 0.99. The RNA sample extracted from M. acetivorans C2A as described above was used to calculate the ratio of the mcr transcript to either MA3998 or rpoA1 transcripts. The ratios were calculated from the mean Cq values. The ratio error reported was one standard deviation from the propogated error assuming independent measurements from the mean Cq values. Melt curves were analyzed for all reactions with no unspecific products. No amplification was observed for all no template controls.

Promoter Alignments 26 Methanosarcina complete genomes were downloaded from NCBI (Supplemental Table 9). Groups of homologous genes across the different genomes were identified with PanOCT 63 using the default parameters. Focusing the analysis on only 12 reference strain genomes (Supplemental Table 9), 1590 groups of genes containing a homologue in at lest 10 of the 12 reference strains were identified. Groups that did not contain a gene whose TSS had been identified in M. mazei Gö1 by Jager et al. 19 were discarded. Assuming the TSS of each homologue could be estimated from the one identified in M. mazei Gö1, this analysis yielded 243 clusters of homologous genes with a predicted TSS. For each cluster, the predicted promoter and 5’-UTR regions (from 400bp upstream of the predicted TSS to 20 bp downstream of the start codon) were extracted and aligned with Muscle (v3.8.31, using the default pa28


Page 28 of 38

Page 29 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


rameters). 64 Manual inspection and curation of the alignments were used to determine highly conserved promoters. The alignment figures were generated using Jalview. 65

RNA Structures All structures were calculated and visualized using NuPack web interface (RNA nucleic acid type, 37◦ C, 1 strand species). 66 The predicted free energy of formation of the secondary structure is listed in the bottom right corner of the structure diagram.

Acknowledgement The author thanks William Metcalf for providing M. acetivorans strains and plasmids used in this work, Paula Welander for her advice on methanogen genetics, Jörg Deutzmann for his advice on anaerobic culture and feedback on the manuscript, and Robert Fisher for sharing his β-galactosidase methods. This research was supported by a grant from the Global Climate and Energy Project, Stanford University.

Author Contributions A.A.K., D.R.G., and A.M.S. contributed to experimental design. M.F. performed all bioinformatic design and analysis. A.A.K., J.C.R., E.C.H., and W.S. performed wetlab experiments. A.A.K., M.F., and A.M.S. wrote the manuscript and all authors revised the manuscript.

Supporting Information Available • Filename: Supplemental Information This material is available free of charge via the Internet at http://pubs.acs.org/.

29



References 1. Thauer, R. K., Kaster, A.-K., Seedorf, H., Buckel, W., and Hedderich, R. (2008) Methanogenic archaea: ecologically relevant differences in energy conservation. Nat. Rev. Microbiol. 6, 579–591. 2. Tallant, T. C., and Krzycki, J. A. (1997) Methylthiol: coenzyme M methyltransferase from Methanosarcina barkeri, an enzyme of methanogenesis from dimethylsulfide and methylmercaptopropionate. J. Bacteriol. 179, 6902–6911. 3. Rother, M., and Metcalf, W. W. (2004) Anaerobic growth of Methanosarcina acetivorans C2A on carbon monoxide: an unusual way of life for a methanogenic archaeon. Proc. Natl. Acad. Sci. U. S. A. 101, 16929–16934. 4. Imachi, H., Sakai, S., Nagai, H., Yamaguchi, T., and Takai, K. (2009) Methanofollis ethanolicus sp. nov., an ethanol-utilizing methanogen isolated from a lotus field. Int. J. Syst. Evol. Microbiol. 59, 800–805. 5. Mayumi, D., Mochimaru, H., Tamaki, H., Yamamoto, K., Yoshioka, H., Suzuki, Y., Kamagata, Y., and Sakata, S. (2016) Methane production from coal by a single methanogen. Science 354, 222–225. 6. Enzmann, F., Mayer, F., Rother, M., and Holtmann, D. (2018) Methanogens: biochemical background and biotechnological applications. AMB Express 8, 1. 7. Nazem-Bokaee, H., Gopalakrishnan, S., Ferry, J. G., Wood, T. K., and Maranas, C. D. (2016) Assessing methanotrophy and carbon fixation for biofuel production by Methanosarcina acetivorans. Microb. Cell Fact. 15, 10. 8. Thor, S., Peterson, J. R., and Luthey-Schulten, Z. (2017) Genome-Scale Metabolic Modeling of Archaea Lends Insight into Diversity of Metabolic Function. Archaea 2017 .

30


Page 30 of 38

Page 31 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


9. Leigh, J. A., Albers, S.-V., Atomi, H., and Allers, T. (2011) Model organisms for genetics in the domain Archaea: methanogens, halophiles, Thermococcales and Sulfolobales. FEMS Microbiol. Rev. 35, 577–608. 10. Catlett, J. L., Ortiz, A. M., and Buan, N. R. (2015) Rerouting cellular electron flux to increase the rate of biological methane production. Appl. Environ. Microbiol. 81, 6528– 6537. 11. Lessner, D. J., Lhu, L., Wahal, C. S., and Ferry, J. G. (2010) An engineered methanogenic pathway derived from the domains Bacteria and Archaea. mBio 1, e00243–10. 12. Soo, V. W., McAnulty, M. J., Tripathi, A., Zhu, F., Zhang, L., Hatzakis, E., Smith, P. B., Agrawal, S., Nazem-Bokaee, H., Gopalakrishnan, S., Salis, H. M., Ferry, J. G., Maranas, C. D., Patterson, A. D., and Wood, T. K. (2016) Reversing methanogenesis to capture methane for liquid biofuel precursors. Microb. Cell Fact. 15, 11. 13. McAnulty, M. J., Poosarla, V. G., Li, J., Soo, V. W., Zhu, F., and Wood, T. K. (2017) Metabolic engineering of Methanosarcina acetivorans for lactate production from methane. Biotechnol. Bioeng. 14. Guss, A. M., Rother, M., Zhang, J. K., Kulkkarni, G., and Metcalf, W. W. (2008) New methods for tightly regulated gene expression and highly efficient chromosomal integration of cloned genes for Methanosarcina species. Archaea 2, 193–203. 15. Demolli, S., Geist, M. M., Weigand, J. E., Matschiavelli, N., Suess, B., and Rother, M. (2014) Development of β-lactamase as a tool for monitoring conditional gene expression by a tetracycline-riboswitch in Methanosarcina acetivorans. Archaea 2014 . 16. Soppa, J. (1999) Normalized nucleotide frequencies allow the definition of archaeal promoter elements for different archaeal groups and reveal base-specific TFB contacts upstream of the TATA box. Mol. Microbiol. 31, 1589–1592.

31



17. Geiduschek, E. P., and Ouhammouch, M. (2005) Archaeal transcription and its regulators. Mol. Microbiol. 56, 1397–1407. 18. Nagy, J., Grohmann, D., Cheung, A. C., Schulz, S., Smollett, K., Werner, F., and Michaelis, J. (2015) Complete architecture of the archaeal RNA polymerase open complex from single-molecule FRET and NPS. Nat. Commun. 6 . 19. Jäger, D., Sharma, C. M., Thomsen, J., Ehlers, C., Vogel, J., and Schmitz, R. A. (2009) Deep sequencing analysis of the Methanosarcina mazei Gö1 transcriptome in response to nitrogen availability. Proc. Natl. Acad. Sci. U. S. A. 106, 21878–21882. 20. Bell, S., and Jackson, S. Transcription in archaea. Cold Spring Harbor symposia on quantitative biology. 1998; pp 41–52. 21. Wurtzel, O., Sapra, R., Chen, F., Zhu, Y., Simmons, B. A., and Sorek, R. (2010) A single-base resolution map of an archaeal transcriptome. Genome Res. 20, 133–141. 22. Babski, J., Haas, K. A., Näther-Schindler, D., Pfeiffer, F., Förstner, K. U., Hammelmann, M., Hilker, R., Becker, A., Sharma, C. M., Marchfelder, A., and Soppa, J. (2016) Genome-wide identification of transcriptional start sites in the haloarchaeon Haloferax volcanii based on differential RNA-Seq (dRNA-Seq). BMC genomics 17, 629. 23. Li, J., Qi, L., Guo, Y., Yue, L., Li, Y., Ge, W., Wu, J., Shi, W., and Dong, X. (2015) Global mapping transcriptional start sites revealed both transcriptional and post-transcriptional regulation of cold adaptation in the methanogenic archaeon Methanolobus psychrophilus. Sci. Rep. 5 . 24. Toffano-Nioche, C., Ott, A., Crozat, E., Nguyen, A. N., Zytnicki, M., Leclerc, F., Forterre, P., Bouloc, P., and Gautheret, D. (2013) RNA at 92 C: the non-coding transcriptome of the hyperthermophilic archaeon Pyrococcus abyssi. RNA Biol. 10, 1211– 1220.

32


Page 32 of 38

Page 33 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


25. Jäger, D., Förstner, K. U., Sharma, C. M., Santangelo, T. J., and Reeve, J. N. (2014) Primary transcriptome map of the hyperthermophilic archaeon Thermococcus kodakarensis. BMC genomics 15, 684. 26. Sartorius-Neef, S., and Pfeifer, F. (2004) In vivo studies on putative Shine–Dalgarno sequences of the halophilic archaeon Halobacterium salinarum. Mol. Microbiol. 51, 579– 588. 27. Coureux, P.-D., Lazennec-Schurdevin, C., Monestier, A., Larquet, E., Cladière, L., Klaholz, B. P., Schmitt, E., and Mechulam, Y. (2016) Cryo-EM study of start codon selection during archaeal translation initiation. Nat. Commun. 7 . 28. Lecompte, O., Ripp, R., Thierry, J.-C., Moras, D., and Poch, O. (2002) Comparative analysis of ribosomal proteins in complete genomes: an example of reductive evolution at the domain scale. Nucleic Acids Res. 30, 5382–5390. 29. Benelli, D., and Londei, P. Translation initiation in Archaea: conserved and domainspecific features. 2011. 30. Kozak, M. (2005) Regulation of translation via mRNA structure in prokaryotes and eukaryotes. Gene 361, 13–37. 31. Peeters, E., Peixeiro, N., and Sezonov, G. Cis-regulatory logic in archaeal transcription. 2013. 32. Zhang, J., Pritchett, M., Lampe, D., Robertson, H., and Metcalf, W. (2000) In vivo transposon mutagenesis of the methanogenic archaeon Methanosarcina acetivorans C2A using a modified version of the insect mariner-family transposable element Himar1. Proc. Natl. Acad. Sci. U. S. A. 97, 9665–9670. 33. Pritchett, M. A., Zhang, J. K., and Metcalf, W. W. (2004) Development of a markerless

33



genetic exchange method for Methanosarcina acetivorans C2A and its use in construction of new genetic tools for methanogenic archaea. Appl. Environ. Microbiol. 70, 1425–1433. 34. Nayak, D. D., and Metcalf, W. W. (2017) Cas9-mediated genome editing in the methanogenic archaeon Methanosarcina acetivorans. Proc. Natl. Acad. Sci. U. S. A. 114, 2976–2981. 35. Metcalf, W. W., Zhang, J. K., Apolinario, E., Sowers, K. R., and Wolfe, R. S. (1997) A genetic system for Archaea of the genus Methanosarcina: liposome-mediated transformation and construction of shuttle vectors. Proc. Natl. Acad. Sci. U. S. A. 94, 2626–2631. 36. Hausner, W., Frey, G., and Thomm, M. (1991) Control regions of an archaeal gene: a TATA box and an initiator element promote cell-free transcription of the tRNAval gene of Methanococcus vannielii. J. Mol. Biol. 222, 495–508. 37. Salis, H. M., Mirsky, E. A., and Voigt, C. A. (2009) Automated design of synthetic ribosome binding sites to control protein expression. Nat. Biotechnol. 27, 946–950. 38. Littlefield, O., Korkhin, Y., and Sigler, P. B. (1999) The structural basis for the oriented assembly of a TBP/TFB/promoter complex. Proc. Natl. Acad. Sci. U. S. A. 96, 13668– 13673. 39. Li, L., Li, Q., Rohlin, L., Kim, U., Salmon, K., Rejtar, T., Gunsalus, R. P., Karger, B. L., and Ferry, J. G. (2007) Quantitative Proteomic and Microarray Analysis of the Archaeon M ethanosarcina acetivorans Grown with Acetate versus Methanol. J. Proteome Res. 6, 759–771. 40. Sowers, K. R., Baron, S. F., and Ferry, J. G. (1984) Methanosarcina acetivorans sp. nov., an acetotrophic methane-producing bacterium isolated from marine sediments. Appl. Environ. Microbiol. 47, 971–978.

34


Page 34 of 38

Page 35 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


41. Mohammed-Ali, M. (2012) Stability study of tetracycline drug in acidic and alkaline solutions by colorimetric method. J. Biochem. Pharmacol. Res. 4, 1319–26. 42. Reiter, W.-D., Hüdepohl, U., and Zillig, W. (1990) Mutational analysis of an archaebacterial promoter: essential role of a TATA box for transcription efficiency and start-site selection in vitro. Proc. Natl. Acad. Sci. U. S. A. 87, 9509–9513. 43. Hain, J., Reiter, W.-D., Hüdepohl, U., and Zillig, W. (1992) Elements of an archaeal promoter defined by mutational analysis. Nucleic Acids Res. 20, 5423–5428. 44. Palmer, J. R., and Daniels, C. J. (1995) In vivo definition of an archaeal promoter. J. Bacteriol. 177, 1844–1849. 45. Qureshi, S. A., and Jackson, S. P. (1998) Sequence-specific DNA binding by the S. shibatae TFIIB homolog, TFB, and its effect on promoter strength. Mol. Cell 1, 389– 400. 46. Borujeni, A. E., Channarasappa, A. S., and Salis, H. M. (2013) Translation rate is controlled by coupled trade-offs between site accessibility, selective RNA unfolding and sliding at upstream standby sites. Nucleic Acids Res. gkt1139. 47. Farasat, I., Kushwaha, M., Collens, J., Easterbrook, M., Guido, M., and Salis, H. M. (2014) Efficient search, mapping, and optimization of multi-protein genetic systems in diverse bacteria. Mol. Syst. Biol. 10, 731. 48. Wan, Y., Kertesz, M., Spitale, R. C., Segal, E., and Chang, H. (2011) Understanding the transcriptome through RNA structure. Nat. Rev. Genet. 12 . 49. De La Sierra-Gallay, I. L., Zig, L., Jamalli, A., and Putzer, H. (2008) Structural insights into the dual activity of RNase J. Nat. Struct. Mol. Biol. 15, 206–212. 50. Zheng, X., Feng, N., Li, D., Dong, X., and Li, J. (2017) New molecular insights into

35



an archaeal RNase J reveal a conserved processive exoribonucleolysis mechanism of the RNase J family. Mol. Microbiol. 51. Rohlin, L., and Gunsalus, R. P. (2010) Carbon-dependent control of electron transfer and central carbon pathway genes for methane biosynthesis in the Archaean, Methanosarcina acetivorans strain C2A. BMC Microbiol. 10, 62. 52. Nakagawa, S., Niimura, Y., Miura, K.-i., and Gojobori, T. (2010) Dynamic evolution of translation initiation mechanisms in prokaryotes. Proc. Natl. Acad. Sci. U. S. A. 107, 6382–6387. 53. Harms, U., and Thauer, R. K. (1996) Methylcobalamin: coenzyme M methyltransferase isoenzymes MtaA and MtbA from Methanosarcina barkeri. FEBS J. 235, 653–659. 54. Vogel, C., and Marcotte, E. M. (2012) Insights into the regulation of protein abundance from proteomic and transcriptomic analyses. Nat. Rev. Genet. 13, 227. 55. Macinga, D. R., Parojcic, M. M., and Rather, P. N. (1995) Identification and analysis of aarP, a transcriptional activator of the 2’-N-acetyltransferase in Providencia stuartii. J. Bacteriol. 177, 3407–3413. 56. Sowers, K. R., Boone, J. E., and Gunsalus, R. P. (1993) Disaggregation of Methanosarcina spp. and growth as single cells at elevated osmolarity. Appl. Environ. Microbiol. 59, 3832–3839. 57. Tan, S. (2001) A modular polycistronic expression system for overexpressing protein complexes in Escherichia coli. Protein Expression Purif. 21, 224–234. 58. Ho, S. N., Hunt, H. D., Horton, R. M., Pullen, J. K., and Pease, L. R. (1989) Sitedirected mutagenesis by overlap extension using the polymerase chain reaction. Gene 77, 51–59.

36


Page 36 of 38

Page 37 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


59. Shattuck, R. L., and Register, S. P. (1995) Direct Electroporation of DNA from In-Gel Ligation Mixtures. Anal. Biochem. 230, 355–357. 60. Miller, J. (1972) Assay of β-galactosidase. Exp. Mol. Genet. 352–355. 61. Untergasser, A., Cutcutache, I., Koressaar, T., Ye, J., Faircloth, B. C., Remm, M., and Rozen, S. G. (2012) Primer3-new capabilities and interfaces. Nucleic Acids Res. 40, e115–e115. 62. Camacho, C., Coulouris, G., Avagyan, V., Ma, N., Papadopoulos, J., Bealer, K., and Madden, T. L. (2009) BLAST+: architecture and applications. BMC Bioinf. 10, 421. 63. Fouts, D. E., Brinkac, L., Beck, E., Inman, J., and Sutton, G. (2012) PanOCT: automated clustering of orthologs using conserved gene neighborhood for pan-genomic analysis of bacterial strains and closely related species. Nucleic Acids Res. 40, e172–e172. 64. Edgar, R. C. (2004) MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 32, 1792–1797. 65. Waterhouse, A. M., Procter, J. B., Martin, D. M., Clamp, M., and Barton, G. J. (2009) Jalview Version 2-a multiple sequence alignment editor and analysis workbench. Bioinformatics 25, 1189–1191. 66. Zadeh, J. N., Steenberg, C. D., Bois, J. S., Wolfe, B. R., Pierce, M. B., Khan, A. R., Dirks, R. M., and Pierce, N. A. (2011) NUPACK: analysis and design of nucleic acid systems. J. Comput. Chem. 32, 170–173.

37



Page 38 of 38

Graphical TOC Entry M. acetivorans C2A Fine-tuned Protein Production CAAAANNTTTATATA

AACTTAGGAGGTAATTAAA

CAAAANNTTTAAGTA

AACTTGGGAGGTAATTAAA

CAAAANNGTTAAGTA

AATTAAGGAGGAAATTAAA

CAAAANNTTTAAGTG

x

CAAGANNTTTAAGTA

x

AAATTGTTAGGAAATTAAA AAAGGAGTAGGAAATTAAA

CAAAANNTGTAAGTA

AAACCTTAAGGCAATTAAA

CAAAANNTTTGAGTA

5’ Untranslated Region

AAGAGAGGAGGAAATTAAA

CAAAANNTTTAGGTA

Promoter Activity

38

=

AATGTTCGAGGGAATTAAA

RBS Strength


Proteins/ Cell

Fine-Tuned Protein Production in Methanosarcina acetivorans C2A

Recommend Documents