Regulation of replication enzymes by metabolic enzymes in B. subtilis
Lead Research Organisation:
University of Nottingham
Department Name: Sch of Chemistry
Abstract
All organisms extract energy and precursors from the environment to fuel biosynthesis and biomass production. Since the 60s, it is well documented that degradation and biosynthesis are tightly coordinated for optimizing cell fitness. Although of paramount importance for the fundamental, medical and biotechnology sciences, the mechanism of these ubiquitous, global regulatory systems remains a mystery. My collaborator in this research Laurent Janniere has carried out experiments which revealed for the first time links between reactions of the cellular system that breaks down nutrients, called the central carbon metabolism (CCM), its regulators and DNA replication. Although we all understand that somehow the energy extracted from nutrients by CCM fuels growth and that growth must be related to DNA replication and cell division to produce progeny cells, we are still not sure how this linear link between nutrients at one end and DNA replication at the other end is maintained. For example, what are the signals that tell cells that nutrients are abundant and conditions are favourable for DNA replication? The aim of this research is to understand what these signals are at the molecular level.
CCM involves about 30 key reactions grouped in pathways of which glycolysis, gluconeogenesis, the pentose phosphate pathway, the tricarboxylic acid (TCA) cycle and the overflow pathway form the main routes for metabolizing nutrients. These pathways are tightly regulated by transcription factors and cofactors that dynamically sense the metabolic status of the cell for optimizing energy recovery in a range of nutrients by regulating CCM activity. By directly sensing the supply and demand, CCM and its regulators are at a strategic position for producing signals for adapting main cellular activities to nutrient richness. As CCM determinants (proteins and metabolites) are highly conserved and as CCM activity is ubiquitously under the control of regulators, one can speculate that the metabolic control of replication observed in all living organisms may involve signaling systems related to that detected in B. subtilis.
Using different approaches, we found that terminal reactions of glycolysis and downstream reactions carried out by the pyruvate dehydrogenase and the overflow pathway on one hand, and regulators of CCM activity on the other hand, are of prime importance in rich media to maintain the communication lines between nutrients and replication. We also showed that these CCM determinants modulate the initiation and elongation phase of replication via multiple, and intertwined links and that the main replication targets of these links are the universal initiation protein DnaA and three replication enzymes: the polymerase DnaE that synthesizes new DNA, primase DnaG that forms the primers to initiate DNA synthesis and helicase DnaC that separates the parental DNA strands to reveal the sequences to be copied into new DNA. My lab discovered that DnaE, DnaG and DnaC physically interact and modulate each others' activities supporting the notion that they form a distinct subcomplex acting specifically on one of the replicating strands known as the lagging strand. We further showed that DnaE plays a major role in the lagging strand synthesis. These data have been published. As a result of our collective findings we hypothesize that the lower part of glycolysis and downstream reactions as well as CCM regulators form a metabolic hub that sense the cell's metabolic status and send signals to the initiation and elongation phase of DNA replication machineries for modulating the rate of replication with respect to the energy extracted form nutrients.
Although we have identified main protein players in this communication pathway, the actual mechanisms of how these proteins communicate with each other are still a mystery. We propose a series of experiments to understand these mechanisms at the molecular level in B. subtilis.
CCM involves about 30 key reactions grouped in pathways of which glycolysis, gluconeogenesis, the pentose phosphate pathway, the tricarboxylic acid (TCA) cycle and the overflow pathway form the main routes for metabolizing nutrients. These pathways are tightly regulated by transcription factors and cofactors that dynamically sense the metabolic status of the cell for optimizing energy recovery in a range of nutrients by regulating CCM activity. By directly sensing the supply and demand, CCM and its regulators are at a strategic position for producing signals for adapting main cellular activities to nutrient richness. As CCM determinants (proteins and metabolites) are highly conserved and as CCM activity is ubiquitously under the control of regulators, one can speculate that the metabolic control of replication observed in all living organisms may involve signaling systems related to that detected in B. subtilis.
Using different approaches, we found that terminal reactions of glycolysis and downstream reactions carried out by the pyruvate dehydrogenase and the overflow pathway on one hand, and regulators of CCM activity on the other hand, are of prime importance in rich media to maintain the communication lines between nutrients and replication. We also showed that these CCM determinants modulate the initiation and elongation phase of replication via multiple, and intertwined links and that the main replication targets of these links are the universal initiation protein DnaA and three replication enzymes: the polymerase DnaE that synthesizes new DNA, primase DnaG that forms the primers to initiate DNA synthesis and helicase DnaC that separates the parental DNA strands to reveal the sequences to be copied into new DNA. My lab discovered that DnaE, DnaG and DnaC physically interact and modulate each others' activities supporting the notion that they form a distinct subcomplex acting specifically on one of the replicating strands known as the lagging strand. We further showed that DnaE plays a major role in the lagging strand synthesis. These data have been published. As a result of our collective findings we hypothesize that the lower part of glycolysis and downstream reactions as well as CCM regulators form a metabolic hub that sense the cell's metabolic status and send signals to the initiation and elongation phase of DNA replication machineries for modulating the rate of replication with respect to the energy extracted form nutrients.
Although we have identified main protein players in this communication pathway, the actual mechanisms of how these proteins communicate with each other are still a mystery. We propose a series of experiments to understand these mechanisms at the molecular level in B. subtilis.
Technical Summary
It is well established that DNA replication and growth in uni- and multi-cellular organisms is responsive to nutrient availability. In most organisms, DNA replication occurs in a specific window of time during the cell cycle, and this temporal compartmentalization of replication is under the control of growth rate and linked to nutrient availability. The way DNA replication is linked to nutrient availability and the central carbon metabolism is of fundamental and medical importance, but the precise molecular mechanism(s) underpinning this link remains largely unknown.
Work in Laurent Janniere's lab (collaborator in this project) revealed a strong genetic link between glycolysis and DNA replication in the model gram positive bacterium Bacillus subtilis. The second part of glycolysis, known as the C-3 (carbon-3), converts D-glyceraldehyde-3-phospate to pyruvate through a 5-step series of metabolic reactions catalyzed sequentially by 5 enzymes GapA, Pgk, Pgm, Eno and PykA. During a genetic search for suppressors of thermosensitive DNA replication mutants spontaneous suppressive mutations were identified in genes coding for these 5 enzymes. Further detailed characterization of these mutants revealed that their suppressive effects were limited to three replication elongation factors (the DnaE polymerase, DnaG primase and DnaC helicase) specializing in lagging strand replication. These data provided the first evidence that links DNA chain elongation to glycolysis and may have revealed a universally conserved regulatory hub modulating DNA replication in response to energy provided by environmental nutrients. Based upon these results, our working hypothesis is that this regulatory hub generates signals, in response to nutrient availability, that drive key structural/functional changes in key replication enzymes, DnaE, DnaG and DnaC, as well as the replication initiator DnaA. We propose to elucidate the molecular and biochemical mechanisms that underpin this regulatory hub.
Work in Laurent Janniere's lab (collaborator in this project) revealed a strong genetic link between glycolysis and DNA replication in the model gram positive bacterium Bacillus subtilis. The second part of glycolysis, known as the C-3 (carbon-3), converts D-glyceraldehyde-3-phospate to pyruvate through a 5-step series of metabolic reactions catalyzed sequentially by 5 enzymes GapA, Pgk, Pgm, Eno and PykA. During a genetic search for suppressors of thermosensitive DNA replication mutants spontaneous suppressive mutations were identified in genes coding for these 5 enzymes. Further detailed characterization of these mutants revealed that their suppressive effects were limited to three replication elongation factors (the DnaE polymerase, DnaG primase and DnaC helicase) specializing in lagging strand replication. These data provided the first evidence that links DNA chain elongation to glycolysis and may have revealed a universally conserved regulatory hub modulating DNA replication in response to energy provided by environmental nutrients. Based upon these results, our working hypothesis is that this regulatory hub generates signals, in response to nutrient availability, that drive key structural/functional changes in key replication enzymes, DnaE, DnaG and DnaC, as well as the replication initiator DnaA. We propose to elucidate the molecular and biochemical mechanisms that underpin this regulatory hub.
Planned Impact
Understanding how bacteria respond to environmental stimuli and nutritional challenges is of paramount importance and with potential impact across a wide range of applied and theoretical scientific fields.
Health and Bioengineering
Theoreticians and modellers will be able to use our data in order to mathematically model a variety of different nutritional versus growth scenaria in system approaches to biosciences (through metabolomics) and synthetic biology, both of which are explicit strategic priorities in the BBSRC research agenda. Such approaches will have a direct beneficial impact in the Health and Biotechnology sectors. Bacilli are major producers for the detergent, vitamin and biocompatible insecticide industries. Information on how to affect growth through nutritional modulation would be particularly useful to bioprocessing in industrial biotechnology. Bioengineers will be able to modify growth media to maximize or control output. Insights into nutritional challenges and cell growth will help us design and implement new strategic approaches to a wide range of bacteria-driven bioprocesses.
In the health sector, new innovative approaches could be considered to manage and combat infections through nutritional control (high or low glucose diet) where appropriate.
Food
Our work will have direct impact in the food sector. Bacillus subtilis, the model organism that we will be working in this project, and its close relatives are the biggest food spoilers in the food industry. Data from our work will potentially help to design new innovative approaches to improve food safety which is another strategic priority of the BBSRC research agenda (Healthy and Safe Food).
Cancer
The Nobel laureate Otto Heinrich Warburg in 1924 suggested that rapidly growing cancer cells are metabolically different than normal cells. They generate their energy through the non-oxidative breakdown of glucose during glycolysis rather than through the ribosomally driven oxidative phosphorylation through the Kreb's cycle. This bears a striking resemblance to the genetic link between the lower C-3 part of glycolysis and cell growth that we propose to investigate here. Data from our studies on a simple model organism such as Bacillus subtilis will have a direct impact on understanding further the "Warburg Effect" at the molecular level through translational routes. Many aspects of DNA replication at the mechanistic and regulatory levels show a striking conservation between different species, and regulatory mechanisms that will potentially be elucidated here may be applicable to cancer cells. New lines of investigations into cancer metabolism and cell proliferation are likely to emerge, particularly as the Bacillus subtilis replisome is more similar to the eukaryotic replisome than the Escherichia coli replisome. For example, both the B. subtilis and the eukaryotic replisomes utilize lagging strand specific DNA polymerases, DnaE and pol alpha, respectively. DnaE is hypothesized to be a potential regulatory end point linking glycolysis and DNA replication and pol alpha could be under similar regulation in rapidly growing cancer cells.
International Collaboration
A strategic priority of BBSRC is to harness mutual benefit that derives from international collaboration. We will gain access to a wealth of resources in the form of plasmids and strains that have been developed by our project partner in France. He will be engaging in a parallel modelling systems approach to investigate the whole network including global supercoiling effects and not just the glycolysis/replication link. He is working with collaborating physicists and mathematicians to develop new tools in order to model regulatory loops individually and collectively. Iterative cycles of prediction and experimentation will be conducted to generate an integrated understanding of the system. We will maintain a two-way communication during the project for our mutual benefit.
Health and Bioengineering
Theoreticians and modellers will be able to use our data in order to mathematically model a variety of different nutritional versus growth scenaria in system approaches to biosciences (through metabolomics) and synthetic biology, both of which are explicit strategic priorities in the BBSRC research agenda. Such approaches will have a direct beneficial impact in the Health and Biotechnology sectors. Bacilli are major producers for the detergent, vitamin and biocompatible insecticide industries. Information on how to affect growth through nutritional modulation would be particularly useful to bioprocessing in industrial biotechnology. Bioengineers will be able to modify growth media to maximize or control output. Insights into nutritional challenges and cell growth will help us design and implement new strategic approaches to a wide range of bacteria-driven bioprocesses.
In the health sector, new innovative approaches could be considered to manage and combat infections through nutritional control (high or low glucose diet) where appropriate.
Food
Our work will have direct impact in the food sector. Bacillus subtilis, the model organism that we will be working in this project, and its close relatives are the biggest food spoilers in the food industry. Data from our work will potentially help to design new innovative approaches to improve food safety which is another strategic priority of the BBSRC research agenda (Healthy and Safe Food).
Cancer
The Nobel laureate Otto Heinrich Warburg in 1924 suggested that rapidly growing cancer cells are metabolically different than normal cells. They generate their energy through the non-oxidative breakdown of glucose during glycolysis rather than through the ribosomally driven oxidative phosphorylation through the Kreb's cycle. This bears a striking resemblance to the genetic link between the lower C-3 part of glycolysis and cell growth that we propose to investigate here. Data from our studies on a simple model organism such as Bacillus subtilis will have a direct impact on understanding further the "Warburg Effect" at the molecular level through translational routes. Many aspects of DNA replication at the mechanistic and regulatory levels show a striking conservation between different species, and regulatory mechanisms that will potentially be elucidated here may be applicable to cancer cells. New lines of investigations into cancer metabolism and cell proliferation are likely to emerge, particularly as the Bacillus subtilis replisome is more similar to the eukaryotic replisome than the Escherichia coli replisome. For example, both the B. subtilis and the eukaryotic replisomes utilize lagging strand specific DNA polymerases, DnaE and pol alpha, respectively. DnaE is hypothesized to be a potential regulatory end point linking glycolysis and DNA replication and pol alpha could be under similar regulation in rapidly growing cancer cells.
International Collaboration
A strategic priority of BBSRC is to harness mutual benefit that derives from international collaboration. We will gain access to a wealth of resources in the form of plasmids and strains that have been developed by our project partner in France. He will be engaging in a parallel modelling systems approach to investigate the whole network including global supercoiling effects and not just the glycolysis/replication link. He is working with collaborating physicists and mathematicians to develop new tools in order to model regulatory loops individually and collectively. Iterative cycles of prediction and experimentation will be conducted to generate an integrated understanding of the system. We will maintain a two-way communication during the project for our mutual benefit.
Publications

He L
(2023)
Interaction of human HelQ with DNA polymerase delta halts DNA synthesis and stimulates DNA single-strand annealing.
in Nucleic acids research

Holland A
(2023)
The Replicative DnaE Polymerase of Bacillus subtilis Recruits the Glycolytic Pyruvate Kinase (PykA) When Bound to Primed DNA Templates.
in Life (Basel, Switzerland)

Horemans S
(2022)
Pyruvate kinase, a metabolic sensor powering glycolysis, drives the metabolic control of DNA replication.
in BMC biology


Martin E
(2019)
DNA replication initiation in Bacillus subtilis: structural and functional characterization of the essential DnaA-DnaD interaction.
in Nucleic acids research


Okoye J
(2023)
Ferric quinate (QPLEX) inhibits the interaction of major outer membrane protein (MOMP) with the Lewis b (Leb) antigen and limits Campylobacter colonization in broilers
in Frontiers in Microbiology

Okoye JC
(2022)
Ferric quinate (QPLEX) interacts with the major outer membrane protein (MOMP) of Campylobacter jejuni and enters through the porin channel into the periplasmic space.
in Computational and structural biotechnology journal

Soultanas P
(2023)
The metabolic control of DNA replication: mechanism and function
in Open Biology
Description | The homotetrameric DnaD protein is essential in low G+C content gram positive bacteria and is involved in replication initiation at oriC and re-start of collapsed replication forks. It interacts with the ubiquitously conserved bacterial master replication initiation protein DnaA at the oriC but structural and functional details of this interaction are lacking, thus contributing to our incomplete understanding of the molecular details that underpin replication initiation in bacteria. DnaD comprises N-terminal (DDBH1) and C-terminal (DDBH2) domains, with contradicting bacterial two-hybrid and yeast two-hybrid studies suggesting that either the former or the latter interact with DnaA, respectively. Using Nuclear Magnetic Resonance (NMR) we showed that both DDBH1 and DDBH2 interact with the N-terminal domain I of DnaA and studied the DDBH2 interaction in structural detail. We revealed two families of conformations for the DDBH2-DnaA domain I complex and showed that the DnaA-interaction patch of DnaD is distinct from the DNA-interaction patch, suggesting that DnaD can bind simultaneously DNA and DnaA. Using sensitive single-molecule FRET techniques we revealed that DnaD remodels DnaA-DNA filaments consistent with stretching and/or untwisting. Furthermore, the DNA binding activity of DnaD is redundant for this filament remodelling. This in turn suggests that DnaA and DnaD are working collaboratively in the oriC to locally melt the DNA duplex during replication initiation. Cells have evolved a metabolic control of DNA replication to respond to a wide range of nutritional conditions. Accumulating data suggest that this poorly understood control depends, at least in part, on Central Carbon Metabolism (CCM). In Bacillus subtilis, the glycolytic pyruvate kinase (PykA) is intricately linked to replication. PykA comprises a catalytic (Cat) domain (residues 1-476) that binds to phosphoenolpyruvate (PEP) and ADP to produce pyruvate and ATP, and a C-terminal domain (residues 477-585) of unknown function, termed PEPut. Interestingly, PEPut interacts with Cat and is homologous to a domain that, in other metabolic enzymes, is phosphorylated at a conserved TSH motif at the expense of PEP and ATP to drive sugar import and catalytic or regulatory activities. To gain insights into the role of PykA in replication, DNA synthesis was analyzed in various Cat and PEPut mutants grown in a medium where the metabolic activity of PykA is dispensable for growth. Measurements of replication parameters (ori/ter ratio, C period and fork speed) and of the PykA activity showed that PykA mutants exhibit replication defects resulting from side chain modifications in the PykA protein rather than a reduction of its metabolic activity. Interestingly, Cat and PEPut have distinct commitments in replication: while Cat modulates positively and negatively replication fork speed, PEPut stimulates initiation through a process depending on Cat-PEPut interaction and growth conditions. Residues binding to PEP and ADP in Cat, stabilizing the Cat-PEPut interaction and belonging to the TSH motif of PEPut were discovered to be important for the commitment of PykA in replication. In vitro, PykA affects the activities of replication enzymes (the polymerase DnaE, helicase DnaC and primase DnaG) essential for initiation and elongation and genetically linked to pykA. Our results thus connect replication initiation and elongation to CCM metabolites (PEP, ATP and ADP), critical Cat and PEPut residues and to multiple links between PykA and the replication enzymes DnaE, DnaC and DnaG. We propose that PykA is endowed with a moonlighting activity that senses the concentration of signaling metabolites and interacts with replication enzymes to convey information on the cellular metabolic state to the replication machinery and adjust replication initiation and elongation to metabolism. This defines a new type of replication regulator proposed to be part of the metabolic control that gates replication in the cell cycle. In collaboration with Heath Murray (Newcastle) we identified a novel DnaD-Recognition Element (DRE) within the oriC of Bacillus subtilis. This DRE orchestrates strand-specific recruitment of helicase during DNA replication initiation. These findings significantly advance our mechanistic understanding of bidirectional replication from a bacterial chromosome origin. Furthermore, we report both positive and negative mechanisms for directing helicase recruitment in the model organism Bacillus subtilis. Systematic characterization of the essential initiation protein DnaD revealed distinct protein interfaces required for homo-oligomerization, interaction with the master initiator protein DnaA, and interaction with the helicase co-loader protein DnaB. Informed by these properties of DnaD, we went on to find that the developmentally expressed repressor of DNA replication initiation, SirA, blocks the interaction between DnaD and DnaA, thereby restricting helicase recruitment from the origin during sporulation to inhibit further initiation events. |
Exploitation Route | Useful to academic researchers in the field of bacterial DNA replication.This may be a new antibiotic target as it is an essential interaction. |
Sectors | Healthcare |
Title | Additional file 1 of Pyruvate kinase, a metabolic sensor powering glycolysis, drives the metabolic control of DNA replication |
Description | Additional file 1: Fig. S1. Key amino-acids of the Cat and PEPut domains of PykA. A. Cat domain analysis. Clustalw and Chimera analysis of the pyruvate kinase of B. subtilis (PykA), human cells (PKM2) and Mycobacterium tuberculosis (PYK) identified key amino acids of the catalytic site of the B. subtilis protein. B. PEPut domain analysis. Alignment of the PEPut domain of PykA to related domains of various metabolic enzymes. The red arrow highlights the conserved LTSH motif (coordinates 536-539). Fig. S2. Effect of Cat and PEPut mutations on growth in MC. Wild-type and pykA mutants were first grown over-night in MC supplemented with antibiotic when appropriate. Upon saturation, cultures were diluted 1000-fold in the same medium without antibiotic and growth was monitored spectrophometrically. Left panel: Analysis of catalytic mutants (pykA?cat, pykAR32A, pykAR73A, pykAK220A, pykAGD245/6AA, pykAT278A, pykAJP). Right panel: Analysis of PEPut and Cat-PEPut interaction mutants (pykA?PEP, pykAT>A, pykAS>A, pykAH>A, pykATSH>AAA, pykAT>D, pykAS>D, pykAH>D, pykATSH>DDD, pykAE209A, pykAL536A). Controls: TF8A (wild-type) and ?pykA. Fig. S3. Analysis of NTP in the metabolome of wild-type and pykAT>D cells. ATP, GTP and CTP were detected in the positive ionization mode. UTP was detected in the negative ionization mode. Note that TTP signals were too low for quantifications. Data correspond to 3 independent extractions (solid cultures).*, p > 0.05 ; **, p < 0.05 (Welch's T-test). Values in bold indicate the fold change for each metabolite (WT vs pykAT>D). Fig. S4. LC/MS analysis of legionaminic acid in the metabolome. A. Extracted ion chromatogram (EIC) corresponds to the deprotonated molecule [M-H]- at m/z 333.1303 (5 ppm accuracy). B. Zoom on the mass spectrum of legionaminic acid in the negative mode. C. Collision Induced dissociation (CID) spectrum of legionaminic acid in the negative mode at 22% Normalized Collision Energy (NCE). D. CID spectrum of legionaminic acid in the positive mode at 22% NCE. E and F. Zoom on the mass spectrum of the deuterated forms of legionaminic acid in the negative and positive ionization mode, respectively. G and H. Comparison of legionaminic acid (G) and CMP-legionaminic (H) acid contents in wild-type (WT), ?spsE and ?spsF cells, respectively. Data correspond to 3 independent extractions (liquid cultures). ***, p < 0.001; **, p < 0.01 (Welch's T-test). Fig. S5. Representative cell cycle results in Cat and PEPut mutants. Top raw: Microscopy of exponentially growing cells stained with FM4-64 (membrane staining, red) and DAPI (nucleoid staining, blue). Middle raw: Representative runout DNA histograms (experiments were reiterated 3-12 times). Bottom raw: Representative marker frequency analysis along the right arm of the chromosome (experiments were reiterated at least three times). Fig. S6. Cell cycle parameters of wild-type and pykAT>D cells grown in proline and malate, respectively. Left panel: Growth in malate of wild-type (WT), ?pykA (?), pykAT>D (T>D) and other pykA mutants (pykAT>A, pykAGD245/6AA and pykAK220A, blue lines). Right panel: Runout DNA histograms and cell cycle parameters. Fig. S7. PykA-mCherryBSU localization. Strains deleted for the natural pykA gene and encoding the PykA-mCherryBSU fusion from an inducible promoter (Physpank) were grown in MC and microscopy analysis was carried out at OD600nm = 0.1 to 0.2. Top raw: analysis of the mCherryBSU signal produced at different IPTG concentrations. Bottom raw: analysis of cells grown in the absence of IPTG, fixed in a 1x PBS solution supplemented with 1% paraformaldehyde and stained with DAPI. Scale bar: 4 µm. Similar results were obtained with fusions mutated in the Cat or PEPut domain of PykA. Fig. S8. PykA purification and characterization of its function and oligomeric state. A. SDS-PAGE (15% polyacrylamide gel) showing over-expression of the 6His-MBP-PykA in Rosetta (DE3) E. coli. The soluble expressed tagged PykA protein is shown in a red rectangular in lane 4, whereas lanes M, 1, 2 and 3 show molecular weight standards, the control uninduced insoluble fraction, the control uninduced soluble fraction and the IPTG-induced insoluble fraction, respectively. B.1. SDS-PAGE (15% polyacrylamide gel) showing fractions from the first IMAC purification step of PykA. From left to right, lanes represent molecular weight standards (M), the flow-through (1), the eluted tagged PykA (2), the overnight TEV treated tagged PykA (3), the flow-through fractions containing untagged PykA from the second IMAC step after TEV proteolysis (4-10). B.2. SDS-PAGE (15% polyacrylamide gel) showing the final gel filtration column (HiLoad 26/60 Superdex 200 Prep Grade Gel Filtration Column). From left to right, lanes represent molecular weight standards (M) and fractions of the size exclusion chromatography (1-9). C. The graph shows a Hill plot for the activity of PykA at 25°C. The Rate/(Vmax-Rate) (Y-axis) was plotted against the PEP substrate concentration (X-axis) using GraphPad Prism 4 software and the Vmax (19.3 µmol/min), Km (2.7 mM) and the Hill coefficient n (0.8111) values are shown below the graph. The n value is <1 indicating negative cooperative binding of PykA to its PEP substrate. D. The graph shows a Michaelis-Menten plot for the activity of PykA at 25°C. The initial rate of the reaction (Y-axis) was plotted against the PEP substrate concentration (X-axis) using GraphPad Prism 4 software and the Vmax (16.3 µmol/min) and Km (1.7 mM) values are shown below the graph. E. A native mass spectrum showing the PykA tetramer and miniscule amounts of the dimer and monomer. The theoretical mass of the PykA monomer (62,314.9 Da), dimer (124,629.8 Da) and tetramer (249,259.6 Da). Native mass spectrometry showed that PykA was found to be predominantly tetrameric (250,092 ± 72 Da), with very low abundance dimer (124,811 ± 38 Da) and monomer (62,437 ± 8 Da) peaks. F. Collision induced dissociation of the 33+ charge state of the tetramer shows it to be very stable in the gas-phase, with no apparent dissociation to lower-order oligomers. G. Comparative analytical gel filtration of the PykA tetramer against molecular weight standards (Thyroglobulin 670 kDa, g-globulin 158 kDa, ovalbumin 44 kDa, myoglobin 17 kDa and vitamin B12 1.3 kDa) through a Superdex 200 10/300 GL prepacked Tricorn gel filtration column (GE Healthcare). H. Selectivity trendline constructed from the molecular weight standards (shown in graph G) for the estimation of the PykA MW. The x axis is in logarithmic scale. Graphpad was used for plotting the data points. The theoretical value of our PykA (249,259.6 Da) is close to the estimated (285,000 Da) which along with the MS data verifies the tetramer in solution. Kd is the equilibrium distribution coefficient. The numbers (1-5) on the data points correspond to the proteins shown in graph G. Fig. S9. Stimulation of DnaE activity by PykA but not by BSA. A. Primer extension assays monitoring the extension of a 5'-32P-radioactively labelled 60mer DNA primer annealed onto M13 ssDNA over time by the B. subtilis DnaE. The activity of DnaE polymerase (10 nM) was monitored in the presence and absence of PykA (10 nM, tetramer) through a time course (30-150 sec). Lanes in the gels from left to right indicate: (M): DNA-ladder and then the time course (0, 30, 60, 90, 120 and 150 sec) depicted by the rectangular triangle. B. Primer extension assays as above with or without 10 nM (monomer) BSA instead of PykA. C. DnaE (1 nM) polymerase activity at increasing BSA concentrations (0, 5, 50, 500 nM), as indicated by the rectangular triangle, monitored by alkaline agarose electrophoresis. The DNA substrate is a labelled 20mer (5'-CAGTGCCAAGCTTGCATGCC-3') primer annealed onto ssM13 ssDNA (2nM). The primer extension reaction was carried out for a longer time than above (5 min instead of 30-150 sec) and the film was over-exposed to compensate for the lower DnaE concentration. The assay was carried out at 37 °C in 50 mM Tris-HCl 7.5, 50 mM NaCl, 10 mM MgCl2 mM DTT, 1 mM dNTPs. No stimulation of the DnaE polymerase activity was observed in the presence of 5 and 50 nM BSA. The marginal stimulation observed at 500 nM BSA excess is likely because at this high concentration, BSA acts as a blocking agent preventing adhesion of DnaE to the plastic reaction tubes. Fig. S10. Stimulation of DnaE activity by PykA does not result from stimulation of DnaE binding to primed templates. EMSA investigation of the effect of PykA on the DNA binding of DnaE polymerase. The DNA substrate was constructed by annealing a 5'-32P-radioactively labelled 15mer (5'-AAGGGGGTGTGTGTG-3') primer annealed onto a 30mer (5'-ACACACACACACACACACACACACCCCCTT-3') oligonucleotide. Binding reactions were carried out with 1 nM DNA substrate, DnaE (500nM) and increasing concentrations (0, 12.5, 125 and 1,250 nM tetramer) of PykA, as indicated by the rectangular triangle for 10 min at 37°C in 50 mM NaCl, 10 mM MgCl2, 50 mM Tris-HCl pH 7.5. Lanes C and PykA represent the radioactive substrate in the absence of any proteins and in the presence of PykA (1,250 nM tetramer), respectively, showing that PykA does not bind to the DNA substrate. No stimulation of DnaE binding to DNA was observed in the presence of increasing concentrations of PykA indicating that PykA does not enhance the DNA binding activity of DnaE. Fig. S11. PEPut purification. A. SDS-PAGE showing overexpression of the His-MBP tagged PEPut in Rosetta (DE3) E. coli. From left to right, lanes show protein MW markers (M), the insoluble uninduced (1), soluble uninduced (2), insoluble induced (3) and soluble induced (4) fractions. The expressed soluble His-MBP tagged PEPut is shown by a red rectangular. B. SDS-PAGE showing the final purified untagged PEPut after removal of the His-MBP tag with TEV proteolysis. Lanes from left to right show protein MW markers (M) and fractions from the flow through the HisTrap column containing the pure untagged PEPut (lanes 1,2 and 3). Fig. S12. PEPut does not stimulate DnaE activity. Primer extension time course (30, 60, 90, 120 and 150 sec) assays using a primed DNA substrate (133 pM) constructed by annealing a radioactively labelled 5'-32P 15mer primer (5'-AAGGGGGTGTGTGTG-3') onto a 110mer oligonucleotide (5'-CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACCCCTTTAAAAAAAAAAAAAAAAGCCAAAAGCAGTGCCAAGCTTGCATGCC-3'), at suboptimal 25 pM DnaE concentration (left), in the presence of 25 pM PykA tetramer (middle) and 25 pM PEPut domain monomer (right). At this suboptimal DnaE concentration, there is no detectable DnaE primer extension activity in the absence of PykA but clear activity is visible in the presence of PykA. By comparison, no DnaE activity is detectable in the presence of the purified PEPut domain. These data show that full length PykA stimulates the DnaE activity while the PEPut domain alone does not. |
Type Of Material | Database/Collection of data |
Year Produced | 2022 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_1_of_Pyruvate_kinase_a_metaboli... |
Title | Additional file 1 of Pyruvate kinase, a metabolic sensor powering glycolysis, drives the metabolic control of DNA replication |
Description | Additional file 1: Fig. S1. Key amino-acids of the Cat and PEPut domains of PykA. A. Cat domain analysis. Clustalw and Chimera analysis of the pyruvate kinase of B. subtilis (PykA), human cells (PKM2) and Mycobacterium tuberculosis (PYK) identified key amino acids of the catalytic site of the B. subtilis protein. B. PEPut domain analysis. Alignment of the PEPut domain of PykA to related domains of various metabolic enzymes. The red arrow highlights the conserved LTSH motif (coordinates 536-539). Fig. S2. Effect of Cat and PEPut mutations on growth in MC. Wild-type and pykA mutants were first grown over-night in MC supplemented with antibiotic when appropriate. Upon saturation, cultures were diluted 1000-fold in the same medium without antibiotic and growth was monitored spectrophometrically. Left panel: Analysis of catalytic mutants (pykA?cat, pykAR32A, pykAR73A, pykAK220A, pykAGD245/6AA, pykAT278A, pykAJP). Right panel: Analysis of PEPut and Cat-PEPut interaction mutants (pykA?PEP, pykAT>A, pykAS>A, pykAH>A, pykATSH>AAA, pykAT>D, pykAS>D, pykAH>D, pykATSH>DDD, pykAE209A, pykAL536A). Controls: TF8A (wild-type) and ?pykA. Fig. S3. Analysis of NTP in the metabolome of wild-type and pykAT>D cells. ATP, GTP and CTP were detected in the positive ionization mode. UTP was detected in the negative ionization mode. Note that TTP signals were too low for quantifications. Data correspond to 3 independent extractions (solid cultures).*, p > 0.05 ; **, p < 0.05 (Welch's T-test). Values in bold indicate the fold change for each metabolite (WT vs pykAT>D). Fig. S4. LC/MS analysis of legionaminic acid in the metabolome. A. Extracted ion chromatogram (EIC) corresponds to the deprotonated molecule [M-H]- at m/z 333.1303 (5 ppm accuracy). B. Zoom on the mass spectrum of legionaminic acid in the negative mode. C. Collision Induced dissociation (CID) spectrum of legionaminic acid in the negative mode at 22% Normalized Collision Energy (NCE). D. CID spectrum of legionaminic acid in the positive mode at 22% NCE. E and F. Zoom on the mass spectrum of the deuterated forms of legionaminic acid in the negative and positive ionization mode, respectively. G and H. Comparison of legionaminic acid (G) and CMP-legionaminic (H) acid contents in wild-type (WT), ?spsE and ?spsF cells, respectively. Data correspond to 3 independent extractions (liquid cultures). ***, p < 0.001; **, p < 0.01 (Welch's T-test). Fig. S5. Representative cell cycle results in Cat and PEPut mutants. Top raw: Microscopy of exponentially growing cells stained with FM4-64 (membrane staining, red) and DAPI (nucleoid staining, blue). Middle raw: Representative runout DNA histograms (experiments were reiterated 3-12 times). Bottom raw: Representative marker frequency analysis along the right arm of the chromosome (experiments were reiterated at least three times). Fig. S6. Cell cycle parameters of wild-type and pykAT>D cells grown in proline and malate, respectively. Left panel: Growth in malate of wild-type (WT), ?pykA (?), pykAT>D (T>D) and other pykA mutants (pykAT>A, pykAGD245/6AA and pykAK220A, blue lines). Right panel: Runout DNA histograms and cell cycle parameters. Fig. S7. PykA-mCherryBSU localization. Strains deleted for the natural pykA gene and encoding the PykA-mCherryBSU fusion from an inducible promoter (Physpank) were grown in MC and microscopy analysis was carried out at OD600nm = 0.1 to 0.2. Top raw: analysis of the mCherryBSU signal produced at different IPTG concentrations. Bottom raw: analysis of cells grown in the absence of IPTG, fixed in a 1x PBS solution supplemented with 1% paraformaldehyde and stained with DAPI. Scale bar: 4 µm. Similar results were obtained with fusions mutated in the Cat or PEPut domain of PykA. Fig. S8. PykA purification and characterization of its function and oligomeric state. A. SDS-PAGE (15% polyacrylamide gel) showing over-expression of the 6His-MBP-PykA in Rosetta (DE3) E. coli. The soluble expressed tagged PykA protein is shown in a red rectangular in lane 4, whereas lanes M, 1, 2 and 3 show molecular weight standards, the control uninduced insoluble fraction, the control uninduced soluble fraction and the IPTG-induced insoluble fraction, respectively. B.1. SDS-PAGE (15% polyacrylamide gel) showing fractions from the first IMAC purification step of PykA. From left to right, lanes represent molecular weight standards (M), the flow-through (1), the eluted tagged PykA (2), the overnight TEV treated tagged PykA (3), the flow-through fractions containing untagged PykA from the second IMAC step after TEV proteolysis (4-10). B.2. SDS-PAGE (15% polyacrylamide gel) showing the final gel filtration column (HiLoad 26/60 Superdex 200 Prep Grade Gel Filtration Column). From left to right, lanes represent molecular weight standards (M) and fractions of the size exclusion chromatography (1-9). C. The graph shows a Hill plot for the activity of PykA at 25°C. The Rate/(Vmax-Rate) (Y-axis) was plotted against the PEP substrate concentration (X-axis) using GraphPad Prism 4 software and the Vmax (19.3 µmol/min), Km (2.7 mM) and the Hill coefficient n (0.8111) values are shown below the graph. The n value is <1 indicating negative cooperative binding of PykA to its PEP substrate. D. The graph shows a Michaelis-Menten plot for the activity of PykA at 25°C. The initial rate of the reaction (Y-axis) was plotted against the PEP substrate concentration (X-axis) using GraphPad Prism 4 software and the Vmax (16.3 µmol/min) and Km (1.7 mM) values are shown below the graph. E. A native mass spectrum showing the PykA tetramer and miniscule amounts of the dimer and monomer. The theoretical mass of the PykA monomer (62,314.9 Da), dimer (124,629.8 Da) and tetramer (249,259.6 Da). Native mass spectrometry showed that PykA was found to be predominantly tetrameric (250,092 ± 72 Da), with very low abundance dimer (124,811 ± 38 Da) and monomer (62,437 ± 8 Da) peaks. F. Collision induced dissociation of the 33+ charge state of the tetramer shows it to be very stable in the gas-phase, with no apparent dissociation to lower-order oligomers. G. Comparative analytical gel filtration of the PykA tetramer against molecular weight standards (Thyroglobulin 670 kDa, g-globulin 158 kDa, ovalbumin 44 kDa, myoglobin 17 kDa and vitamin B12 1.3 kDa) through a Superdex 200 10/300 GL prepacked Tricorn gel filtration column (GE Healthcare). H. Selectivity trendline constructed from the molecular weight standards (shown in graph G) for the estimation of the PykA MW. The x axis is in logarithmic scale. Graphpad was used for plotting the data points. The theoretical value of our PykA (249,259.6 Da) is close to the estimated (285,000 Da) which along with the MS data verifies the tetramer in solution. Kd is the equilibrium distribution coefficient. The numbers (1-5) on the data points correspond to the proteins shown in graph G. Fig. S9. Stimulation of DnaE activity by PykA but not by BSA. A. Primer extension assays monitoring the extension of a 5'-32P-radioactively labelled 60mer DNA primer annealed onto M13 ssDNA over time by the B. subtilis DnaE. The activity of DnaE polymerase (10 nM) was monitored in the presence and absence of PykA (10 nM, tetramer) through a time course (30-150 sec). Lanes in the gels from left to right indicate: (M): DNA-ladder and then the time course (0, 30, 60, 90, 120 and 150 sec) depicted by the rectangular triangle. B. Primer extension assays as above with or without 10 nM (monomer) BSA instead of PykA. C. DnaE (1 nM) polymerase activity at increasing BSA concentrations (0, 5, 50, 500 nM), as indicated by the rectangular triangle, monitored by alkaline agarose electrophoresis. The DNA substrate is a labelled 20mer (5'-CAGTGCCAAGCTTGCATGCC-3') primer annealed onto ssM13 ssDNA (2nM). The primer extension reaction was carried out for a longer time than above (5 min instead of 30-150 sec) and the film was over-exposed to compensate for the lower DnaE concentration. The assay was carried out at 37 °C in 50 mM Tris-HCl 7.5, 50 mM NaCl, 10 mM MgCl2 mM DTT, 1 mM dNTPs. No stimulation of the DnaE polymerase activity was observed in the presence of 5 and 50 nM BSA. The marginal stimulation observed at 500 nM BSA excess is likely because at this high concentration, BSA acts as a blocking agent preventing adhesion of DnaE to the plastic reaction tubes. Fig. S10. Stimulation of DnaE activity by PykA does not result from stimulation of DnaE binding to primed templates. EMSA investigation of the effect of PykA on the DNA binding of DnaE polymerase. The DNA substrate was constructed by annealing a 5'-32P-radioactively labelled 15mer (5'-AAGGGGGTGTGTGTG-3') primer annealed onto a 30mer (5'-ACACACACACACACACACACACACCCCCTT-3') oligonucleotide. Binding reactions were carried out with 1 nM DNA substrate, DnaE (500nM) and increasing concentrations (0, 12.5, 125 and 1,250 nM tetramer) of PykA, as indicated by the rectangular triangle for 10 min at 37°C in 50 mM NaCl, 10 mM MgCl2, 50 mM Tris-HCl pH 7.5. Lanes C and PykA represent the radioactive substrate in the absence of any proteins and in the presence of PykA (1,250 nM tetramer), respectively, showing that PykA does not bind to the DNA substrate. No stimulation of DnaE binding to DNA was observed in the presence of increasing concentrations of PykA indicating that PykA does not enhance the DNA binding activity of DnaE. Fig. S11. PEPut purification. A. SDS-PAGE showing overexpression of the His-MBP tagged PEPut in Rosetta (DE3) E. coli. From left to right, lanes show protein MW markers (M), the insoluble uninduced (1), soluble uninduced (2), insoluble induced (3) and soluble induced (4) fractions. The expressed soluble His-MBP tagged PEPut is shown by a red rectangular. B. SDS-PAGE showing the final purified untagged PEPut after removal of the His-MBP tag with TEV proteolysis. Lanes from left to right show protein MW markers (M) and fractions from the flow through the HisTrap column containing the pure untagged PEPut (lanes 1,2 and 3). Fig. S12. PEPut does not stimulate DnaE activity. Primer extension time course (30, 60, 90, 120 and 150 sec) assays using a primed DNA substrate (133 pM) constructed by annealing a radioactively labelled 5'-32P 15mer primer (5'-AAGGGGGTGTGTGTG-3') onto a 110mer oligonucleotide (5'-CACACACACACACACACACACACACACACACACACACACACACACACACACACACACACCCCTTTAAAAAAAAAAAAAAAAGCCAAAAGCAGTGCCAAGCTTGCATGCC-3'), at suboptimal 25 pM DnaE concentration (left), in the presence of 25 pM PykA tetramer (middle) and 25 pM PEPut domain monomer (right). At this suboptimal DnaE concentration, there is no detectable DnaE primer extension activity in the absence of PykA but clear activity is visible in the presence of PykA. By comparison, no DnaE activity is detectable in the presence of the purified PEPut domain. These data show that full length PykA stimulates the DnaE activity while the PEPut domain alone does not. |
Type Of Material | Database/Collection of data |
Year Produced | 2022 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_1_of_Pyruvate_kinase_a_metaboli... |
Title | Additional file 2 of Pyruvate kinase, a metabolic sensor powering glycolysis, drives the metabolic control of DNA replication |
Description | Additional file 2: Tables S1-S4. |
Type Of Material | Database/Collection of data |
Year Produced | 2022 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_2_of_Pyruvate_kinase_a_metaboli... |
Title | Additional file 2 of Pyruvate kinase, a metabolic sensor powering glycolysis, drives the metabolic control of DNA replication |
Description | Additional file 2: Tables S1-S4. |
Type Of Material | Database/Collection of data |
Year Produced | 2022 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_2_of_Pyruvate_kinase_a_metaboli... |
Title | Automated Quickchange Program |
Description | Site-directed mutagenesis (or Quickchange) is a method that can be used to introduce single amino-acid substitutions in a protein of interest based on a template plasmid (Liu and Naismith, 2008). One pair of mutagenic oligonucleotides is required per mutation, and creating these must follow specific design guidelines. Therefore, generating mutant primers can be a tedious process, which becomes increasingly laborious as the number of substitutions to make rises. Here, we created a program for the automation of Quickchange primer design. The software takes a DNA sequence encoding a protein as an input and generates oligonucleotide pairs for the mutagenesis of every amino-acid in that protein within seconds. Design rules are optimised for successful PCR amplification via the Q5 DNA polymerase and based on: (i) the melting temperature (TM) of the oligonucleotide part that anneals to the template plasmid DNA, (ii) the TM corresponding to a primer pair overlapping section, (iii) the GC-content within different sections of individual primers, (iv) the presence of a GC-clamp at every oligonucleotide 3'-end, and (v) the TM difference between forward and reverse primer pairs. Settings allow to change the annealing temperature of recombinant primers according to the basic parameters of PCR reactions including final buffer salt and oligonucleotide concentrations. We applied this program to the alanine scan of the B. subtilis DnaD protein and it can be used for the systematic mutagenesis of any protein of interest. |
Type Of Technology | Software |
Year Produced | 2021 |
Open Source License? | Yes |
URL | https://zenodo.org/record/5541537 |
Title | Automated Quickchange Program |
Description | Site-directed mutagenesis (or Quickchange) is a method that can be used to introduce single amino-acid substitutions in a protein of interest based on a template plasmid (Liu and Naismith, 2008). One pair of mutagenic oligonucleotides is required per mutation, and creating these must follow specific design guidelines. Therefore, generating mutant primers can be a tedious process, which becomes increasingly laborious as the number of substitutions to make rises. Here, we created a program for the automation of Quickchange primer design. The software takes a DNA sequence encoding a protein as an input and generates oligonucleotide pairs for the mutagenesis of every amino-acid in that protein within seconds. Design rules are optimised for successful PCR amplification via the Q5 DNA polymerase and based on: (i) the melting temperature (TM) of the oligonucleotide part that anneals to the template plasmid DNA, (ii) the TM corresponding to a primer pair overlapping section, (iii) the GC-content within different sections of individual primers, (iv) the presence of a GC-clamp at every oligonucleotide 3'-end, and (v) the TM difference between forward and reverse primer pairs. Settings allow to change the annealing temperature of recombinant primers according to the basic parameters of PCR reactions including final buffer salt and oligonucleotide concentrations. We applied this program to the alanine scan of the B. subtilis DnaD protein and it can be used for the systematic mutagenesis of any protein of interest. |
Type Of Technology | Software |
Year Produced | 2021 |
Open Source License? | Yes |
URL | https://zenodo.org/record/5541536 |