Recombinant Desulfovibrio vulgaris UPF0059 membrane protein DVU_2910 (DVU_2910)

What is currently known about the function of DVU_2910 in Desulfovibrio vulgaris?

DVU_2910 is classified as a hypothetical protein belonging to the UPF0059 family of membrane proteins in Desulfovibrio vulgaris Hildenborough. According to functional annotation data, it is predicted to be a membrane protein based on computational analysis . While the specific biological function remains uncharacterized, network analysis indicates DVU_2910 is regulated by 20 different influences and participates in modules 69 and 113, suggesting potential involvement in complex cellular processes . The protein has been successfully expressed recombinantly with an N-terminal His-tag in E. coli expression systems, facilitating further biochemical studies .

How is DVU_2910 positioned within the genomic organization of Desulfovibrio vulgaris?

DVU_2910 exists within a genomic neighborhood containing several other genes, including DVU2908 (hypothetical protein), DVU2916 (hemK protein), and DVU2917 (lpxC) . This genomic organization may provide contextual clues about its functional associations. Notably, DVU_2910 shares module membership (modules 69 and 113) with 59 gene neighbors that participate in various cellular functions, suggesting potential functional relationships or co-regulation . The gene appears to be part of a more extensive regulatory network involving transcription factors and combinatorial regulators, as evidenced by the multiple regulatory influences documented in the Network Portal database .

What expression systems are recommended for producing recombinant DVU_2910?

For recombinant expression of DVU_2910, E. coli has been successfully employed as demonstrated by commercially available preparations . When expressing this protein, consider the following methodology:

• Vector Selection: Use vectors containing an N-terminal His-tag to facilitate purification.

• Expression Conditions:

  • Induce at lower temperatures (16-20°C) to promote proper folding of membrane proteins

  • Consider specialized E. coli strains optimized for membrane protein expression (e.g., C41(DE3), C43(DE3))

  • Test varying IPTG concentrations (0.1-1.0 mM) to optimize expression levels

• Protein Extraction: Use gentle detergents appropriate for membrane proteins (e.g., DDM, LDAO, or Triton X-100) during cell lysis and purification steps.

The full-length protein (amino acids 1-201) has been successfully expressed with an N-terminal His-tag, suggesting this approach is viable for research applications .

What approaches are recommended for functional characterization of DVU_2910?

Given the hypothetical nature of DVU_2910, a multi-faceted approach to functional characterization is recommended:

• Genetic Manipulation Strategies:

  • Generation of deletion mutants using transposon mutagenesis approaches similar to those employed in the genome-wide DvH study

  • Complementation studies to confirm phenotypes

  • Construction of conditional expression systems to study essentiality

• Phenotypic Analysis:

  • Growth assays under various metabolic and stress conditions to identify conditional phenotypes

  • Comparative analysis with wild-type strains under sulfate-reducing conditions

  • Fitness profiling across diverse environmental conditions

• Protein-Protein Interaction Studies:

  • Bacterial two-hybrid assays

  • Co-immunoprecipitation with predicted interacting partners

  • Crosslinking studies followed by mass spectrometry

This methodological framework mirrors successful approaches used to characterize other hypothetical proteins in DvH, such as the comprehensive transposon mutant library that defined conditional phenotypes for 1,137 non-essential genes .

How can researchers investigate the membrane topology and structural features of DVU_2910?

Investigating the membrane topology and structural features of DVU_2910 requires specialized approaches for membrane proteins:

• Computational Prediction Methods:

  • Use membrane protein topology prediction tools (TMHMM, Phobius)

  • Apply hydropathy analysis to identify transmembrane regions

  • Employ homology modeling if structural homologs exist

• Experimental Validation Approaches:

  • Cysteine scanning mutagenesis coupled with accessibility assays

  • PhoA/LacZ fusion analysis to determine orientation within the membrane

  • Limited proteolysis followed by mass spectrometry to identify exposed domains

• Advanced Structural Analysis:

  • Cryo-electron microscopy of purified protein

  • X-ray crystallography (challenging for membrane proteins but possible with appropriate detergents)

  • Solid-state NMR for specific structural elements

These methodological approaches provide complementary data that can build a comprehensive structural model of this predicted membrane protein.

What purification strategies are most effective for obtaining high-quality DVU_2910 protein samples?

Purification of DVU_2910 requires specialized approaches for membrane proteins:

• Solubilization Optimization:

  • Screen multiple detergents (DDM, LDAO, Triton X-100, CHAPS) at various concentrations

  • Test solubilization efficiency at different temperatures (4°C, room temperature)

  • Evaluate addition of stabilizing agents (glycerol, specific lipids)

• Chromatography Sequence:

  • Initial capture: Nickel affinity chromatography utilizing the N-terminal His-tag

  • Intermediate purification: Ion exchange chromatography

  • Polishing: Size exclusion chromatography to remove aggregates

• Quality Assessment:

  • SDS-PAGE analysis for purity

  • Western blotting with anti-His antibodies

  • Mass spectrometry to confirm protein identity

  • Dynamic light scattering to assess monodispersity

Commercially available preparations utilize His-tag affinity purification following expression in E. coli, demonstrating the viability of this approach .

How is DVU_2910 regulated within the Desulfovibrio vulgaris genome?

DVU_2910 exhibits a complex regulatory profile as evidenced by network analysis data:

• Transcriptional Regulation:
  DVU_2910 is regulated by 20 distinct influences, including direct transcription factors and combinatorial regulators . Key regulators include:

  Regulator Type	Regulator ID	Module	Regulatory Mechanism
  Transcription Factor	DVU3167	113	Direct regulation
  Transcription Factor	DVU3220	113	Direct regulation
  Transcription Factor	DVU1063	69	Direct regulation
  Transcription Factor	DVU1744	69	Direct regulation
  Combinatorial Regulator	DVU2547 DVU1419	113	Combinatorial regulation
  Combinatorial Regulator	DVU2557 DVU2547	113	Combinatorial regulation

• Motif-Based Regulation:
  Four distinct motifs have been identified in the upstream region of DVU_2910:

  • Motif ID 135: Consensus sequence ttCattcTcttttccgGtcgCgca

  • Motif ID 136: Consensus sequence ATGACa

  • Motif ID 217: Consensus sequence TTTGcCataT

  • Motif ID 218: Consensus sequence atAtCgtagccGcgcgCCTTGC

These regulatory elements suggest DVU_2910 is under sophisticated transcriptional control, potentially responding to various environmental and cellular signals.

What methodologies can researchers employ to investigate protein-protein interactions involving DVU_2910?

To investigate protein-protein interactions of DVU_2910, consider these methodological approaches:

• In Vivo Approaches:

  • Bacterial two-hybrid system optimized for membrane proteins

  • Protein-fragment complementation assays

  • FRET-based interaction studies using fluorescently tagged proteins

• In Vitro Methods:

  • Pull-down assays using the His-tagged recombinant protein

  • Surface plasmon resonance with immobilized DVU_2910

  • Crosslinking followed by mass spectrometry identification

• Network-Based Prediction and Validation:

  • Analysis of module neighborhood data to identify potential interacting partners

  • Prioritize testing interactions with the 59 gene neighbors that share modules 69 and 113

  • Focus on functional neighbor genes involved in related processes

Given the module neighborhood information available, priority candidates for interaction studies would include DVU2908, DVU2916, and DVU2917, which are genomically proximal to DVU_2910 .

How can researchers determine if DVU_2910 is essential for Desulfovibrio vulgaris survival?

Determining the essentiality of DVU_2910 requires systematic experimental approaches:

• Transposon Mutagenesis Analysis:

  • Analyze transposon insertion patterns in DVU_2910 from existing libraries, such as the one described for DvH

  • Compare insertion frequencies with known essential and non-essential genes

  • Look for significant gaps in transposon insertion sites across the gene

• Conditional Expression Systems:

  • Develop inducible/repressible promoter systems to control DVU_2910 expression

  • Monitor growth under depletion conditions

  • Quantify expression levels correlated with growth rates

• Complementation Studies:

  • Attempt gene deletion in the presence of a complementing copy

  • Test complementation under various growth conditions

  • Employ plasmid loss systems to confirm essentiality

The comprehensive transposon mutagenesis approach used in DvH identified 380 essential genes shared between wild-type and JW710 strain backgrounds . This methodology could be specifically applied to determine if DVU_2910 falls within this essential gene set.

What is the potential role of DVU_2910 in sulfate reduction pathways?

While direct evidence for DVU_2910's role in sulfate reduction is not provided in the search results, its potential involvement can be methodologically investigated:

• Comparative Expression Analysis:

  • Perform RT-qPCR under various sulfate availability conditions

  • Compare expression profiles with known sulfate reduction genes (e.g., dsrAB, sat)

  • Conduct RNA-seq to position DVU_2910 within global expression networks during sulfate reduction

• Protein Localization Studies:

  • Fluorescent protein fusions to determine subcellular localization

  • Immunogold electron microscopy to verify membrane association

  • Co-localization with known components of the sulfate reduction machinery

• Metabolic Impact Assessment:

  • Measure sulfate reduction rates in DVU_2910 mutants (if non-essential)

  • Analyze metabolite profiles using targeted and untargeted metabolomics

  • Examine electron transfer capabilities through electrochemical techniques

Given that essential genes directly involved in sulfate reduction include dsrAB (dissimilatory sulfite reductase) and sat (sulfate adenylyltransferase) , examining functional relationships between DVU_2910 and these pathways would be valuable.

How can DVU_2910 be studied in the context of biofilm formation and stress response?

Investigating DVU_2910 in biofilm formation and stress response contexts requires:

• Biofilm Analysis Methods:

  • Quantitative biofilm assays comparing wild-type and DVU_2910 mutants

  • Confocal microscopy with fluorescent stains to examine biofilm architecture

  • Gene expression analysis within biofilm versus planktonic states

• Stress Response Experiments:

  • Expose cultures to various stressors (oxidative, nitrosative, osmotic, pH)

  • Compare survival rates between wild-type and mutant strains

  • Conduct fitness profiling under stress conditions as performed in the RB-TnSeq analysis for DvH

• Multi-Omics Integration:

  • Combine transcriptomics, proteomics, and metabolomics data

  • Map DVU_2910 function onto stress response networks

  • Use systems biology approaches to identify emergent properties

This multi-faceted approach mirrors the conditional phenotype analysis conducted for 1,137 non-essential genes in DvH under various metabolic and stress conditions .

What biotechnological applications might exploit DVU_2910 function in environmental or industrial contexts?

Potential biotechnological applications involving DVU_2910 could include:

• Bioremediation Engineering:

  • Develop engineered strains with modified DVU_2910 expression for enhanced metal reduction

  • Design biosensors based on DVU_2910 regulation for detecting environmental contaminants

  • Create immobilized cell systems optimized for specific remediation tasks

• Biofilm Control Strategies:

  • Target DVU_2910 to modify biofilm formation in industrial settings

  • Develop anti-fouling approaches based on regulatory mechanisms

  • Engineer surfaces that modulate DVU_2910 function to control adhesion

• Metabolic Engineering Applications:

  • Incorporate DVU_2910 into synthetic pathways for sulfur metabolism

  • Optimize electron transfer processes for biotechnological applications

  • Develop biological catalysts for specific chemical transformations

These applications would build upon understanding gained from fundamental research into DVU_2910's function and regulation within the Desulfovibrio vulgaris system.

How can CRISPR-Cas9 genome editing be optimized for studying DVU_2910 in Desulfovibrio vulgaris?

Optimizing CRISPR-Cas9 for studying DVU_2910 in Desulfovibrio vulgaris involves:

• Vector and Delivery System Development:

  • Design plasmids containing Cas9 optimized for expression in DvH

  • Develop efficient transformation protocols (electroporation parameters optimized for DvH)

  • Consider inducible Cas9 expression systems to minimize toxicity

• Guide RNA Design and Validation:

  • Analyze the DVU_2910 sequence for optimal gRNA target sites

  • Avoid targets with potential off-target effects in the DvH genome

  • Test gRNA efficiency using in vitro cleavage assays before in vivo implementation

• Homology-Directed Repair Templates:

  • Design templates with sufficient homology arms (800-1000 bp)

  • Include selection markers compatible with DvH genetics

  • Consider counter-selection strategies for marker removal

• Verification Methods:

  • PCR screening of transformants

  • Sequencing verification of edited regions

  • Functional assays to confirm phenotypic changes

This methodological approach would expand upon genetic manipulation strategies previously employed in DvH, such as the counter-selection system based on resistance to 5-fluorouracil in the JW710 strain background .

What approaches can be used to investigate the role of DVU_2910 in multi-species biofilm communities?

Investigating DVU_2910 in multi-species biofilms requires specialized methodologies:

• Co-Culture System Development:

  • Establish reproducible co-culture models with relevant partner species

  • Optimize growth media supporting all community members

  • Develop quantification methods for each species within the biofilm

• Spatial Organization Analysis:

  • Apply fluorescence in situ hybridization (FISH) with species-specific probes

  • Use confocal microscopy with 3D reconstruction of biofilm architecture

  • Employ nanoscale secondary ion mass spectrometry (nanoSIMS) for metabolic interactions

• Community Interaction Measurements:

  • Analyze gene expression changes in DVU_2910 during inter-species interactions

  • Compare wild-type and DVU_2910 mutant effects on community structure

  • Examine metabolite exchanges using stable isotope probing

• Multi-Omics Integration:

  • Combine metatranscriptomics, metaproteomics, and metabolomics

  • Develop computational models of community interaction networks

  • Identify emergent properties dependent on DVU_2910 function

This comprehensive approach would provide insights into how DVU_2910 influences not only DvH physiology but also inter-species interactions within complex biofilm communities.

How can high-throughput screening approaches be developed to identify compounds that modulate DVU_2910 function?

Developing high-throughput screening for DVU_2910 modulators requires:

• Assay Development and Validation:

  • Design reporter systems linked to DVU_2910 function or expression

  • Develop cell-based assays with quantifiable outputs (fluorescence, luminescence)

  • Establish robust positive and negative controls

• Compound Library Selection:

  • Curate libraries targeting membrane proteins

  • Include known modulators of related bacterial systems

  • Consider natural product collections with activity against sulfate-reducing bacteria

• Screening Methodology:

  • Optimize assay conditions for 384 or 1536-well formats

  • Implement automated liquid handling and detection systems

  • Develop data analysis pipelines for hit identification

• Hit Validation and Characterization:

  • Confirm activity in secondary assays

  • Determine structure-activity relationships

  • Assess specificity using related protein targets

This methodological approach could leverage the regulatory information about DVU_2910, particularly its association with 20 regulatory influences and participation in modules 69 and 113 , to design specific functional assays.