Recombinant Listeria monocytogenes serovar 1/2a UPF0316 protein lmo1776 (lmo1776)

What distinguishes Listeria monocytogenes serovar 1/2a from other serovars in research applications?

L. monocytogenes serovar 1/2a represents one of the most frequently isolated serovars in both clinical and food samples. Research indicates that serovar 1/2a strains can be divided into two distinct genetic groups based on molecular typing methods. When applying PCR-restriction enzyme analysis (PCR-REA) to regions containing virulence genes such as inlA and inlB, researchers found that out of 100 tested strains, 70 shared one restriction profile (1/2a:I) while 30 shared a second profile (1/2a:II) . This genetic heterogeneity has significant implications for experimental design, as it suggests potential functional differences between subgroups. When designing experiments involving serovar 1/2a strains, researchers should consider characterizing their specific strains to determine which genetic subgroup they belong to, as this may influence protein expression and virulence characteristics.

What is the typical genetic organization of virulence factor genes in L. monocytogenes serovar 1/2a?

The virulence genes in L. monocytogenes serovar 1/2a demonstrate a specific organization pattern that impacts recombinant protein expression strategies. Particularly well-studied are the inlA and inlB genes, which belong to the same gene family and are located adjacent to each other with only an 85 bp intergenic space . The inlA gene encodes internalin, which is essential for L. monocytogenes to invade epithelial cells, while inlB is necessary for hepatocyte invasion . These genes display a relatively low degree of polymorphism across strains, which makes them reliable targets for genetic manipulation and protein expression. Understanding this genetic architecture is critical when designing expression constructs for proteins like lmo1776, as neighboring sequences may impact transcriptional efficiency.

What are the optimal expression systems for recombinant L. monocytogenes proteins like lmo1776?

While there is no single optimal expression system for all L. monocytogenes proteins, Escherichia coli remains a common and effective heterologous expression host. For example, recombinant listeriolysin (LLO) protein has been successfully expressed in E. coli with >90% purity . For membrane or secreted proteins, expression can be particularly challenging. Recent statistical modeling approaches have shown that sequence-derived features can predict expression success in E. coli, with proper selection of construct design potentially more than doubling the number of successfully expressed targets .

When expressing L. monocytogenes proteins, researchers should consider:

• Codon optimization for the host organism

• Inclusion of appropriate secretion signals if the native protein is secreted

• Selection of fusion tags that enhance solubility without interfering with function

• Expression temperature optimization (often lower temperatures improve folding)

• Induction conditions that balance expression level with proper protein folding

How can researchers optimize purification protocols for recombinant L. monocytogenes proteins?

Purification of recombinant L. monocytogenes proteins requires a strategic approach based on the protein's biochemical properties. For listeriolysin O, purification to >90% purity has been achieved, making it suitable for applications including SDS-PAGE and functional studies . A systematic purification approach should include:

• Initial clarification of lysate by centrifugation (10,000-15,000 g for 30 minutes)

• Capture chromatography (typically affinity chromatography if using tagged constructs)

• Intermediate purification using ion exchange chromatography

• Polishing step using size exclusion chromatography

• Quality control by SDS-PAGE, Western blotting, and activity assays

For membrane-associated proteins, consider detergent screening to identify optimal solubilization conditions that maintain protein stability and function. The choice between harsh (e.g., SDS) and mild (e.g., digitonin, DDM) detergents should be guided by downstream applications.

What expression vector design considerations are critical for successful production of L. monocytogenes serovar 1/2a proteins?

When designing expression vectors for L. monocytogenes proteins, researchers should apply data-driven approaches similar to the IMProve statistical model described for membrane proteins . Critical considerations include:

• Promoter selection: Strong inducible promoters (T7, tac) for high expression or weaker promoters for potentially toxic proteins

• Signal sequence selection: Native or optimized sequences depending on cellular localization

• Fusion partner integration: Solubility-enhancing tags (MBP, SUMO, TrxA) for challenging proteins

• Inclusion of proteolytic cleavage sites: For tag removal without affecting protein structure

• Codon optimization: Particularly for rare codons in the expression host

For proteins like LLO, expressing fragments (such as aa 60-529) rather than full-length proteins can improve expression success while maintaining functionality . This approach may be applicable to lmo1776 if expression of the full protein proves challenging.

What assays are most appropriate for characterizing the biochemical activities of L. monocytogenes proteins?

The appropriate assays for functional characterization depend on the predicted functions of the protein of interest. For well-characterized virulence factors like LLO, researchers have established several functional assays:

• Pore formation assays using artificial membranes or erythrocyte lysis

• MAP kinase activation assays in host cells

• Proteasome-dependent and independent degradation assays

• Vacuolar escape assays

For proteins of unknown function like many UPF (uncharacterized protein family) members, a broader approach is needed:

• Protein-protein interaction studies (pull-downs, yeast two-hybrid, BioID)

• Cellular localization studies using fluorescent tags

• Phenotypic analysis of knockout/overexpression strains

• Structural characterization by X-ray crystallography or cryo-EM

• In silico prediction of function based on structural homology

How can researchers assess the impact of recombinant L. monocytogenes proteins on host cell signaling pathways?

Assessment of host cell signaling impacts requires both targeted and untargeted approaches. For LLO, it has been demonstrated that this protein activates mitogen-activated protein (MAP) kinase activity in host cells and induces both proteasome-independent degradation of UBE2I and proteasome-dependent degradation of sumoylated proteins . To assess similar effects for proteins like lmo1776, researchers could employ:

• Phosphorylation-specific antibody arrays to detect activation of kinase cascades

• Mass spectrometry-based proteomics to identify degraded or modified host proteins

• Transcriptome analysis (RNA-seq) to detect host cell transcriptional responses

• Cytokine profiling (ELISA, multiplex bead arrays) to assess inflammatory responses

• Live-cell imaging with fluorescent reporters for real-time signaling visualization

What are the challenges in differentiating the functions of recombinant proteins versus their native counterparts in L. monocytogenes?

Recombinant proteins may not fully recapitulate the functions of their native counterparts due to several factors:

• Post-translational modifications: L. monocytogenes may process proteins differently than heterologous expression systems

• Protein folding differences: Especially when expressing in E. coli versus gram-positive bacteria

• Lack of natural binding partners: Proteins often function in complexes that may be absent in vitro

• Concentration effects: Recombinant proteins may be tested at non-physiological concentrations

To address these challenges, researchers should:

• Compare the function of recombinant proteins with native proteins extracted from L. monocytogenes

• Conduct complementation studies in knockout strains to verify functional equivalence

• Perform structure-function analyses to identify critical regions and residues

• Use site-directed mutagenesis to verify active sites or functional domains

How can recombinant L. monocytogenes proteins be utilized in immunological research?

Recombinant L. monocytogenes proteins serve as valuable tools in immunological research. LLO, for example, is recognized by serum from both healthy humans exposed to L. monocytogenes and patients who have recovered from listeriosis . For research applications, recombinant proteins can be used for:

• Development of serological assays for exposure/infection detection

• Studying antigen presentation pathways and T-cell responses

• Examining innate immune recognition mechanisms

• Vaccine development using protein subunits or as carrier proteins

In studies with recombinant Listeria strains expressing heterologous antigens, researchers found that strains expressing LLO induced higher levels of cytokines (TNF-α, IL-6, and IFN-γ) compared to control strains . This suggests that incorporating virulence factors like LLO into experimental designs can enhance immunogenicity.

What animal models are most appropriate for studying recombinant L. monocytogenes proteins?

The mouse model dominates research involving L. monocytogenes proteins due to its well-characterized immune system and availability of genetic tools. When studying recombinant L. monocytogenes proteins, consider:

• Mouse strain selection: Different strains (BALB/c, C57BL/6) may show varied susceptibility

• Route of administration: Intravenous delivery typically shows most consistent results

• Infection dose: Titration is necessary to balance lethality with experimental duration

• Readout timepoints: Cytokine production peaks at different times (e.g., IL-6 and TNF-α early, IFN-γ later)

In challenge studies with recombinant Listeria strains expressing LLO, protection rates reached 40-60% compared to 0% in control groups . When designing similar studies with recombinant proteins, researchers should consider both survival endpoints and mechanistic measurements (cytokine levels, bacterial burden, cellular responses).

How do L. monocytogenes serovar 1/2a strain variations impact recombinant protein studies?

The genetic heterogeneity within L. monocytogenes serovar 1/2a (profiles 1/2a:I and 1/2a:II) has important implications for recombinant protein studies . To account for this variation:

• Specify the exact strain used as the source for recombinant protein sequences

• Consider testing proteins from multiple representative strains within each genetic subgroup

• Verify sequences against reference databases before expression construct design

• Acknowledge potential functional differences between proteins from different strain backgrounds

While no direct correlation was found between PCR-REA types and strain origins (human, animal, food, or environmental sources) , researchers should still report comprehensive strain information to enable cross-study comparisons.

How can researchers address structural characterization challenges for L. monocytogenes membrane proteins?

Membrane proteins present unique challenges for structural studies. The IMProve statistical model demonstrates that sequence-derived features can predict expression success, potentially doubling the number of successfully expressed membrane protein targets . When approaching structural studies of L. monocytogenes membrane proteins:

• Construct optimization: Express stable domains or fragments rather than full-length proteins

• Detergent screening: Test multiple detergents for extraction and purification efficiency

• Lipid nanodisc reconstitution: For maintaining native-like lipid environment

• Crystallization strategies: Use of antibody fragments or fusion partners to enhance crystallization

• Alternative structural approaches: Cryo-EM for larger complexes, NMR for smaller domains

What strategies can overcome the low immunogenicity challenges when working with certain L. monocytogenes proteins?

Some L. monocytogenes proteins exhibit lower immunogenicity, limiting their utility in vaccine development or diagnostic applications. Research with recombinant Listeria strains suggests potential strategies to enhance immunogenicity:

• Fusion to immunogenic carriers: Attaching proteins to known immunogenic proteins like LLO

• Adjuvant co-administration: Testing various adjuvant formulations

• Delivery system optimization: Using liposomes, nanoparticles, or virus-like particles

• Prime-boost strategies: Heterologous prime-boost approaches with DNA vaccines followed by protein

Research comparing Listeria ivanovii strains expressing native ivanolysin versus recombinant listeriolysin O demonstrated improved cytokine responses (TNF-α, IL-6, and IFN-γ) with the LLO-expressing strain . This suggests that strategic protein engineering can enhance immunological properties.

How should researchers interpret contradictory data between in vitro and in vivo studies of L. monocytogenes proteins?

Discrepancies between in vitro and in vivo studies of L. monocytogenes proteins require careful interpretation:

• Physiological context differences: In vitro systems lack the complex environment of living organisms

• Concentration considerations: Protein concentrations in vitro often exceed physiological levels

• Temporal dynamics: In vivo responses evolve over time with multiple regulatory mechanisms

• Cell type interactions: In vivo effects may depend on interactions between multiple cell types

A systematic approach to resolving contradictions includes:

• Refining in vitro models to better reflect in vivo conditions

• Conducting dose-response studies across a physiologically relevant range

• Employing ex vivo approaches as intermediate validation steps

• Using genetic approaches (knockouts, point mutations) to verify specific mechanisms

What are the most effective genetic modification approaches for studying L. monocytogenes proteins in their native context?

For studying proteins like lmo1776 in their native context, several genetic approaches have proven effective:

• Allelic exchange: Precise replacement of target genes with modified versions

• Homologous recombination: As demonstrated in the construction of LIΔilo:hly strains

• CRISPR-Cas9 systems: For precise genome editing without antibiotic resistance markers

• Integrative vectors: For stable expression of recombinant proteins

When constructing recombinant strains, verification through multiple methods is essential:

• PCR confirmation of genetic modifications

• Sequencing of modified regions

• Protein expression verification by Western blot

• Functional validation through appropriate assays

How can researchers distinguish between the effects of recombinant proteins versus confounding factors in experimental systems?

To distinguish specific protein effects from experimental artifacts:

• Include multiple controls:

  • Empty vector controls

  • Inactive mutant protein controls

  • Heterologous protein controls of similar size/structure

• Implement rescue experiments:

  • Complement knockout strains with wild-type and mutant versions

  • Use domain-specific mutations to identify critical functional regions

• Apply dose-dependent analyses:

  • Test across concentration ranges to establish response curves

  • Compare to physiologically relevant concentrations

• Conduct temporal studies:

  • Examine both immediate and delayed responses

  • Track the progression of effects over time

What bioinformatic approaches best predict the function of uncharacterized L. monocytogenes proteins like UPF0316 protein lmo1776?

For uncharacterized proteins like lmo1776, comprehensive bioinformatic analysis should include:

• Sequence homology searches:

  • BLASTp against diverse bacterial genomes

  • Position-Specific Iterated BLAST (PSI-BLAST) for distant homologs

  • Hidden Markov Model (HMM) searches of protein family databases

• Structural prediction and analysis:

  • AlphaFold2 or RoseTTAFold for 3D structure prediction

  • Structural alignment with characterized proteins

  • Active site prediction based on conserved residues

• Genomic context analysis:

  • Examination of neighboring genes for functional relationships

  • Operon prediction to identify co-regulated genes

  • Comparative genomics across Listeria species

• Integration with experimental data:

  • Transcriptomic data to identify co-expressed genes

  • Proteomic data to confirm expression and potential modifications

  • Phenotypic data from knockout libraries