KEGG: msu:MS1633
STRING: 221988.MS1633
Mannheimia succiniciproducens MBEL55E is a facultative anaerobic, capnophilic (CO2-loving) Gram-negative bacterium isolated from bovine rumen. This organism has gained significant research attention due to its ability to produce large amounts of succinic acid under anaerobic conditions in the presence of CO2, making it valuable for industrial applications including biodegradable polymers, synthetic resins, chemical intermediates, and additives . The complete genome sequence of M. succiniciproducens has been determined, enabling advanced genomic and proteomic studies for metabolic engineering purposes . The bacterium's unique metabolic capabilities, particularly its efficient carbon dioxide fixation and succinic acid production pathways, make it an excellent model organism for studying anaerobic metabolism and developing biotechnological applications.
Based on studies in related organisms like Bacillus subtilis, YjeA is characterized as a secreted protein with endonuclease activity. In B. subtilis, the YjeA protein has been shown to hydrolyze both single-stranded and double-stranded DNA, but not RNA . The protein contains a putative signal peptide at its N-terminus, supporting its classification as a secretory protein . When studying circular DNA substrates, YjeA from B. subtilis progressively nicks both DNA strands in a random fashion, creating intermediates of various structures and ultimately degrading the DNA into smaller fragments . While specific characterization of M. succiniciproducens YjeA remains limited, comparative genomic analysis suggests potential functional similarities with homologous proteins in related bacterial species.
Comprehensive proteome analysis of M. succiniciproducens has identified more than 200 proteins using 2-DE (two-dimensional gel electrophoresis) and MS (mass spectrometry) techniques . This proteome reference map includes whole cellular proteins, membrane proteins, and secreted proteins . While specific information about YjeA in these studies is limited, the proteome analysis has confirmed the presence of many proteins previously annotated as hypothetical or with putative functions . Comparative proteome profiling across different growth phases has provided valuable information for understanding physiological changes during growth and has suggested target genes for strain improvement . This proteome framework provides contextual information for studying individual proteins like YjeA, particularly regarding their expression patterns and potential functional relationships within the cellular network.
For recombinant expression of M. succiniciproducens proteins, Escherichia coli expression systems have been successfully employed in related studies. Based on methodologies used for similar proteins, the recommended approach includes:
Cloning the yjeA gene into an expression vector such as pET28a+ that incorporates a His6-tag for purification purposes
Using E. coli BL21(DE3) or similar strains optimized for protein expression
Inducing expression with IPTG (isopropyl β-D-1-thiogalactopyranoside) at appropriate concentrations (typically 0.5-1.0 mM)
Optimizing growth temperature post-induction (typically 16-30°C) to enhance soluble protein yield
The inclusion of the native signal sequence should be carefully considered, as it may affect localization in the heterologous host. For functional studies, it may be beneficial to design constructs both with and without the native signal sequence to compare protein activity and solubility.
Based on protocols used for similar secreted proteins with enzymatic activity, a multi-step purification approach is recommended:
Initial capture using immobilized metal affinity chromatography (IMAC) with Ni-NTA resin for His-tagged constructs
Secondary purification via ion exchange chromatography (typically Q-Sepharose or SP-Sepharose depending on the protein's theoretical pI)
Final polishing step using size exclusion chromatography to remove any remaining contaminants or aggregates
Buffer optimization is crucial for maintaining enzyme activity. A typical buffer system might include:
| Purification Stage | Buffer Composition | pH | Notes |
|---|---|---|---|
| Cell Lysis | 50 mM Tris-HCl, 300 mM NaCl, 10 mM imidazole, 1 mM PMSF | 8.0 | Include protease inhibitors to prevent degradation |
| IMAC Binding | 50 mM Tris-HCl, 300 mM NaCl, 10 mM imidazole | 8.0 | Low imidazole reduces non-specific binding |
| IMAC Elution | 50 mM Tris-HCl, 300 mM NaCl, 250 mM imidazole | 8.0 | Gradient elution may improve separation |
| Ion Exchange | 20 mM Tris-HCl, 50-500 mM NaCl gradient | 7.5 | Adjust pH based on theoretical pI |
| Size Exclusion | 20 mM Tris-HCl, 150 mM NaCl | 7.5 | Buffer can be modified based on downstream applications |
Activity assays should be performed after each purification step to monitor retention of enzymatic function.
Based on methodologies used for similar proteins, the following experimental approach can be employed to assess endonuclease activity:
Gel-based DNA degradation assay: Incubate purified YjeA with covalently closed circular plasmid DNA (e.g., pBR322) and analyze the reaction products by agarose gel electrophoresis. Progression from supercoiled to nicked circular to linear forms can be visualized and quantified .
Radioactive substrate assay: Use 32P-labeled DNA substrates to track the progressive nicking of DNA strands, enabling more sensitive detection of intermediates and final degradation products .
Substrate specificity assessment: Test activity against different nucleic acid substrates including double-stranded DNA, single-stranded DNA, and RNA to determine substrate specificity .
Kinetic analysis: Measure initial reaction rates using varying substrate concentrations to determine kinetic parameters (Km, Vmax) under standardized conditions.
A typical reaction buffer would contain:
50 mM Tris-HCl (pH 7.5-8.0)
5-10 mM MgCl2 (as a cofactor)
1-5 mM DTT (as reducing agent)
50-100 mM NaCl
Activity can be assessed at different temperatures (25-40°C) and pH values (6.0-9.0) to determine optimal conditions.
To determine the cellular localization of YjeA in M. succiniciproducens, a multi-faceted approach is recommended:
Computational prediction: Analyze the protein sequence using algorithms such as SignalP, TMHMM, and PSORT to predict the presence of signal peptides or transmembrane domains.
Subcellular fractionation: Separate cellular compartments (cytoplasm, membrane, periplasm, extracellular medium) using differential centrifugation followed by Western blot analysis with specific anti-YjeA antibodies.
Reporter fusion constructs: Create fusion proteins with reporters such as GFP or mCherry to visualize localization in vivo using fluorescence microscopy.
Immunogold electron microscopy: Use specific antibodies conjugated to gold particles to visualize the precise subcellular localization at high resolution.
Proteomic analysis of secretome: Analyze the culture supernatant using mass spectrometry to identify secreted proteins, as has been done previously for M. succiniciproducens .
Based on studies of YjeA in B. subtilis, which identified it as a secreted protein with a putative signal peptide , particular attention should be paid to analyzing the extracellular fraction and comparing results with computational predictions of signal sequences.
For determining the three-dimensional structure of YjeA, several complementary approaches can be employed:
The choice of method depends on protein characteristics, available resources, and the specific structural questions being addressed.
To investigate potential protein-protein interactions of YjeA in M. succiniciproducens, several methodologies can be employed:
Affinity purification coupled with mass spectrometry (AP-MS):
Express tagged YjeA in M. succiniciproducens
Perform pull-down experiments under native conditions
Identify co-purifying proteins by mass spectrometry
Validate interactions with reciprocal pull-downs
Bacterial two-hybrid system:
Test specific binary interactions with candidate proteins
Particularly useful for confirming direct interactions
Can be used for screening against a genomic library
Cross-linking coupled with mass spectrometry (XL-MS):
Treat cells with chemical cross-linkers to stabilize transient interactions
Digest cross-linked complexes and analyze by mass spectrometry
Identify interaction interfaces at amino acid resolution
Co-immunoprecipitation with specific antibodies:
Generate antibodies against YjeA
Precipitate native protein complexes from cell lysates
Identify co-precipitating proteins by Western blot or mass spectrometry
Proximity labeling approaches (e.g., BioID or APEX):
Express YjeA fused to a proximity labeling enzyme
Identify proteins in close proximity in vivo
Particularly useful for identifying transient or weak interactions
When investigating YjeA interactions, particular attention should be paid to potential connections with the metabolic pathways involved in succinic acid production, as well as with components of secretion systems given the likely secreted nature of the protein.
The potential contribution of YjeA to M. succiniciproducens metabolism can be investigated from several angles:
Genomic context analysis: Examine the genes flanking yjeA for functional associations or co-regulation patterns. This may provide clues about metabolic pathways it could influence.
Comparative genomics: Analyze the presence and conservation of yjeA across related species with varying metabolic capabilities, particularly focusing on organisms with similar succinic acid production efficiency.
Gene knockout studies: Generate a yjeA deletion mutant and characterize its phenotype under various growth conditions, particularly focusing on:
Succinic acid production efficiency
Growth rates under aerobic vs. anaerobic conditions
CO2 requirement and utilization
Response to environmental stressors
Transcriptomic analysis: Compare gene expression profiles between wild-type and yjeA mutant strains to identify affected pathways.
Metabolomic analysis: Measure changes in metabolite profiles resulting from yjeA deletion or overexpression.
Given that M. succiniciproducens is known for its efficient succinic acid production via a branched tricarboxylic acid cycle and CO2 fixation by phosphoenolpyruvate carboxylation , particular attention should be paid to whether YjeA affects these pathways directly or indirectly.
Based on the endonuclease activity observed in YjeA homologs , several hypotheses regarding its potential role in stress response can be investigated:
DNA damage repair: YjeA may participate in degrading damaged DNA during stress conditions, similar to other secreted nucleases involved in biofilm regulation or horizontal gene transfer.
Nutritional adaptation: As a secreted endonuclease, YjeA might facilitate utilization of extracellular DNA as a phosphate and nitrogen source during nutrient limitation.
Biofilm regulation: Many bacteria employ extracellular nucleases to modulate biofilm formation and dispersal. YjeA could regulate biofilm dynamics in M. succiniciproducens environments.
Defense against foreign DNA: YjeA may act as part of a primitive immune system against invading genetic elements.
Stress-induced gene regulation: The nuclease activity could potentially regulate gene expression under specific stress conditions by targeted degradation of certain DNA structures.
To investigate these possibilities, experiments comparing wild-type and yjeA mutant strains under various stress conditions (oxidative stress, nutrient limitation, pH stress, etc.) could be performed, measuring survival rates, biofilm formation, and gene expression changes.
Incorporating YjeA function into genome-scale metabolic models of M. succiniciproducens requires a systematic approach:
Model refinement: Update existing genome-scale metabolic models of M. succiniciproducens to include YjeA-related reactions based on experimental evidence of its function.
Constraint-based modeling: Use flux balance analysis (FBA) to predict the effect of YjeA activity on metabolic flux distributions, particularly focusing on pathways leading to succinic acid production.
Regulatory network integration: Incorporate transcriptional regulatory constraints based on experimental data showing how YjeA affects gene expression.
Multi-omics data integration: Use transcriptomic, proteomic, and metabolomic data from wild-type and yjeA mutant strains to refine model predictions.
In silico gene deletion analysis: Predict the metabolic consequences of yjeA deletion or overexpression and validate with experimental data.
Optimization algorithms: Apply computational strategies like OptKnock or OptForce to identify additional genetic modifications that, in combination with YjeA manipulation, could further enhance succinic acid production.
The existing metabolic flux analysis of M. succiniciproducens has shown that phosphoenolpyruvate carboxylation is a major CO2-fixing step with direct relationship to succinic acid flux . The potential interaction between YjeA and this pathway should be a particular focus of modeling efforts.
When facing contradictory experimental data regarding YjeA function, several methodological approaches can help resolve discrepancies:
Standardization of experimental conditions: Ensure all comparative experiments use:
Identical protein preparation methods
Consistent buffer compositions and pH
The same substrate sources and concentrations
Controlled temperature and reaction times
Multiple analytical techniques: Apply orthogonal methods to verify observations:
Combine gel-based assays with solution-based kinetic measurements
Verify protein-protein interactions using both in vitro and in vivo techniques
Use both tagged and untagged protein versions to rule out tag interference
Strain background effects: Test YjeA function in:
The native M. succiniciproducens background
Clean deletion strains with complementation
Heterologous expression systems
Different growth phases and conditions
Post-translational modification analysis: Investigate whether contradictory results stem from:
Different phosphorylation states
Proteolytic processing
Other modifications affecting activity
Protein structural analysis: Determine whether conformational differences explain functional variability:
Compare crystal structures from different conditions
Use hydrogen-deuterium exchange mass spectrometry to detect conformational differences
Apply circular dichroism to assess secondary structure under different conditions
A systematic approach that carefully controls variables and applies multiple methodologies is key to resolving contradictory data and establishing a consensus on YjeA function.
The potential interaction between YjeA and the Arc two-component signal transduction system in M. succiniciproducens presents an intriguing area for investigation:
Co-expression analysis: Determine whether yjeA expression correlates with arcA/arcB expression under various growth conditions, particularly during transitions between aerobic and anaerobic metabolism.
Phosphorylation studies: Investigate whether ArcA, as a response regulator, can directly influence yjeA expression through binding to its promoter region:
Perform electrophoretic mobility shift assays (EMSA) with phosphorylated and non-phosphorylated ArcA
Conduct DNase I footprinting to precisely map binding sites
Use reporter gene assays to quantify promoter activity under ArcA regulation
Genetic interaction studies: Create single and double mutants (ΔyjeA, ΔarcA, ΔarcB, ΔyjeA/ΔarcA, ΔyjeA/ΔarcB) and characterize their phenotypes regarding:
Growth under aerobic vs. anaerobic conditions
Succinic acid production efficiency
Response to redox signals and environmental stressors
Proteomic profiling: Compare the proteome of wild-type and various mutant strains to identify proteins affected by both YjeA and the Arc system.
Metabolic flux analysis: Determine whether YjeA influences the metabolic reprogramming normally mediated by the Arc system during adaptation to different oxygen levels.
The Arc system in M. succiniciproducens, like its E. coli counterpart, likely plays a role in regulating gene expression in response to changing oxygen levels . Understanding how YjeA intersects with this regulatory system could provide insights into the bacterium's adaptation to its capnophilic lifestyle.
To comprehensively study how environmental conditions affect YjeA expression and function, several approaches can be employed:
Transcriptional analysis:
qRT-PCR to measure yjeA mRNA levels under different conditions
RNA-seq for genome-wide transcriptional changes
Promoter-reporter fusions (e.g., yjeA promoter-GFP) to visualize expression in real-time
5' RACE to identify transcription start sites and potential alternative promoters
Protein level analysis:
Western blotting with specific antibodies to quantify YjeA protein levels
Proteomics to measure changes in YjeA abundance relative to other proteins
Pulse-chase experiments to determine protein stability under different conditions
Functional assays under varying conditions:
Endonuclease activity measurements across a range of:
pH values (5.5-8.5)
Temperatures (25-42°C)
Oxygen concentrations (aerobic, microaerobic, anaerobic)
CO2 concentrations (0-20%)
Carbon sources (glucose, fructose, xylose, etc.)
Growth phases (exponential, stationary)
In vivo localization studies:
Fluorescent protein fusions to track YjeA localization under different conditions
Subcellular fractionation followed by activity assays or Western blotting
| Environmental Condition | Measurement Methods | Expected Parameters |
|---|---|---|
| Oxygen levels | Dissolved oxygen probes, anaerobic chambers | 0-21% O2 |
| Carbon dioxide concentration | CO2 controllers, bicarbonate buffers | 0-20% CO2 |
| pH | pH probes, buffered media | pH 5.5-8.5 |
| Temperature | Controlled incubators | 25-42°C |
| Carbon source | Defined media with different carbon sources | Various sugars, organic acids |
| Growth phase | OD600 measurements, cell counts | Lag, exponential, stationary phases |
| Stress conditions | Oxidative stress agents, nutrient limitation | H2O2 (0-5 mM), nutrient-limited media |
For M. succiniciproducens, particular attention should be paid to CO2 concentration effects, given its capnophilic nature and the importance of CO2 in its metabolism .