Recombinant Listeria monocytogenes serotype 4b UPF0291 protein LMOf2365_0526 (LMOf2365_0526)

What is Listeria monocytogenes serotype 4b UPF0291 protein LMOf2365_0526?

Listeria monocytogenes serotype 4b UPF0291 protein LMOf2365_0526 is a protein expressed by Listeria monocytogenes, a Gram-positive, facultative anaerobic, non-spore-forming, rod-shaped bacterium. The protein belongs to the UPF0291 family, which consists of proteins with currently unknown functions. Listeria monocytogenes is notable for its ability to survive and replicate within host cells, making it an important pathogen and potential vaccine vector. The F2365 strain, from which this protein is derived, is a serotype 4b strain that has been extensively studied for its virulence properties and potential applications in vaccine development .

Structurally, the full amino acid sequence of the protein includes specific regions that allow it to integrate into expression systems, though the exact three-dimensional structure has not been fully characterized in the research literature. The protein's role in Listeria pathogenicity remains under investigation, with ongoing research examining its potential involvement in bacterial cellular processes.

How does the serotype 4b classification affect the protein's characteristics and research applications?

The serotype 4b classification of Listeria monocytogenes refers to specific antigenic determinants on the bacterial surface and has significant implications for research applications. Serotype 4b strains are particularly associated with listeriosis outbreaks and have enhanced virulence compared to other serotypes. This classification affects the protein in several important ways:

• Immunogenicity profile: Serotype 4b-specific proteins often elicit distinct immune responses compared to proteins from other serotypes.

• Host-pathogen interactions: The protein may participate in serotype-specific interactions with host cells, potentially contributing to the enhanced virulence of serotype 4b strains.

• Vaccine development considerations: When using this protein in vaccine research, the serotype-specific immunity must be considered, as protection may not extend to other serotypes .

• Experimental design: Researchers must account for serotype-specific behaviors when designing experiments, particularly when comparing results across different Listeria strains.

The serotype 4b classification thus provides important context for understanding the protein's biological relevance and potential applications in vaccine development and immunological studies.

What expression systems are most effective for producing recombinant LMOf2365_0526 protein?

The expression of recombinant LMOf2365_0526 requires careful selection of an appropriate system based on research objectives. Based on established protocols for similar Listeria proteins, the following expression systems have proven effective, each with distinct advantages:

For optimal expression, the protein coding sequence should be codon-optimized for the selected expression system. When using E. coli, inclusion of a 6xHis-tag facilitates purification while maintaining protein functionality. Expression in E. coli typically employs IPTG induction (0.1-1.0 mM) at reduced temperatures (16-25°C) to enhance soluble protein production .

For functional studies requiring proper protein folding, yeast or baculovirus systems are recommended despite their lower yields, as they provide post-translational modifications that may be essential for the protein's native conformation and activity.

What purification challenges are specific to LMOf2365_0526, and how can they be addressed methodologically?

Purifying recombinant LMOf2365_0526 presents several protein-specific challenges that require methodological solutions:

• Membrane association: Though not classified as a true membrane protein, LMOf2365_0526 may associate with membranes during expression, reducing solubility. This can be addressed by:

  • Incorporating detergents (0.5-1% Triton X-100 or 0.1-0.5% DDM) during lysis

  • Using sonication protocols specifically optimized for membrane-associated proteins (6-10 cycles of 10-second pulses with 30-second cooling intervals)

  • Employing denaturing conditions followed by refolding if necessary

• Protein aggregation: The protein may form aggregates during concentration steps. This can be mitigated by:

  • Adding 5-10% glycerol to all buffers

  • Maintaining protein solutions below 2 mg/mL during processing

  • Using step-wise dialysis when changing buffer conditions

• Protease sensitivity: LMOf2365_0526 may be susceptible to proteolytic degradation. Recommended countermeasures include:

  • Adding protease inhibitor cocktails during initial extraction

  • Maintaining samples at 4°C throughout purification

  • Minimizing purification duration with optimized protocols

• Tag interference: Purification tags may affect protein structure or function. Researchers should:

  • Evaluate both N- and C-terminal tag placements

  • Consider tag removal using specific proteases (e.g., TEV, thrombin) followed by secondary purification

  • Validate protein activity both with and without tags

A successful purification workflow typically combines immobilized metal affinity chromatography (IMAC) for initial capture, followed by size exclusion chromatography to remove aggregates and ion exchange chromatography for final polishing. This multi-step approach typically yields >90% pure protein suitable for downstream applications .

How does LMOf2365_0526 protein contribute to recombinant Listeria monocytogenes vaccine vector systems?

LMOf2365_0526 protein can be strategically utilized within recombinant Listeria monocytogenes vaccine vector systems in several ways that leverage the unique properties of both the protein and the bacterial vector:

The fundamental advantage of using L. monocytogenes as a vaccine vector stems from its ability to enter the cytosol of host cells, allowing expressed proteins to efficiently access the endogenous antigen-processing pathway. This leads to presentation by MHC class I molecules and robust activation of CD8+ T cells . The LMOf2365_0526 protein can be incorporated into this system through genetic engineering approaches:

• As a carrier protein: LMOf2365_0526 can be used as a fusion partner for heterologous antigens, potentially enhancing their immunogenicity through associated molecular patterns.

• As part of expression cassettes: The protein's coding sequence can be modified and incorporated into site-specific integration systems for the Listeria genome, creating stable expression platforms.

• For secretion enhancement: When engineered with appropriate secretion signals, LMOf2365_0526-based constructs can improve the delivery of vaccine antigens to the host cytosol.

The effectiveness of this approach has been demonstrated in multiple disease models. For example, vaccination of mice with recombinant Listeria strains expressing LCMV antigens induced LCMV-specific CD8+ T cells that protected mice against subsequent LCMV challenge. Similarly, in a cottontail rabbit papillomavirus model, recombinant Listeria strains stimulated protective antitumor immunity .

To optimize LMOf2365_0526 function within vaccine vectors, researchers should consider:

• Codon optimization for expression within Listeria

• Strategic placement of heterologous antigens (N-terminal vs. C-terminal)

• Selection of appropriate promoters for controlled expression timing

• Inclusion of secretion signals to enhance cytosolic delivery

How can site-specific integration of LMOf2365_0526 expression cassettes be optimized in the Listeria genome?

Optimizing site-specific integration of LMOf2365_0526 expression cassettes into the Listeria genome requires sophisticated genetic engineering approaches that balance stable expression with minimal disruption of bacterial fitness:

Integration Site Selection:

The choice of genomic integration site is critical for optimal expression and minimal physiological impact. Recommended sites include:

• Intergenic regions: Particularly those between convergently transcribed genes to minimize polar effects on neighboring genes.

• Pseudogenes or non-essential genes: Such as comK or inlB for serotype 4b strains, which can be disrupted without significantly affecting bacterial fitness.

• tRNA loci: These regions often contain integrase recognition sites that facilitate site-specific recombination while maintaining chromosomal stability.

Integration Methodologies:

For homologous recombination approaches, flanking the expression cassette with 500-1000 bp homology arms matching the target integration site significantly improves efficiency. The integration vector should contain a temperature-sensitive origin of replication (e.g., pKSV7 derivatives) and appropriate selection markers (typically chloramphenicol resistance) .

Expression Control Elements:

To achieve regulated expression and secretion of LMOf2365_0526:

• Promoter selection: The prfA-dependent promoter (PprfA) offers environment-responsive expression, while the constitutive promoter (Phly) provides consistent high-level expression.

• Secretion signals: The listeriolysin O (LLO) signal sequence (MSKKFKLFLVILAVSIVSALSAEKKK) has proven particularly effective for secretion of heterologous proteins.

• Codon optimization: Adjusting the codon usage to match the preference of L. monocytogenes improves translation efficiency.

Successful integration should be verified through multiple methods including PCR amplification across integration junctions, whole-genome sequencing to confirm single integration, and expression analysis using quantitative RT-PCR and Western blotting to assess protein production levels.

What are the critical parameters for evaluating long-term immunological memory induced by LMOf2365_0526-containing vaccine constructs?

Evaluating long-term immunological memory induced by LMOf2365_0526-containing vaccine constructs requires comprehensive assessment of multiple immune parameters over extended timeframes. The following critical evaluation framework addresses both quantitative and qualitative aspects of memory responses:

Temporal Assessment Points:

• Short-term: Peak response (7-14 days post-immunization)

• Medium-term: Early memory phase (30-60 days)

• Long-term: Established memory (6 months to >1 year)

Critical Immunological Parameters:

• Memory T-cell Phenotyping:

  • Quantification of antigen-specific CD8+ T cells using MHC tetramers/multimers

  • Differentiation of memory subsets (TCM, TEM, TSCM) by flow cytometry markers:

    • TCM: CD62L+, CCR7+, CD127+

    • TEM: CD62L-, CCR7-, CD127+

    • TSCM: CD62L+, CCR7+, CD127+, CD95+

• Functional Memory Assessment:

  • Proliferative capacity upon antigen re-encounter (CFSE dilution assays)

  • Cytokine polyfunctionality (simultaneous production of IFN-γ, TNF-α, IL-2)

  • Cytotoxic potential (Granzyme B, Perforin expression, in vitro killing assays)

• In Vivo Protection Metrics:

  • Challenge studies at multiple time points post-vaccination

  • Pathogen burden quantification (CFU counts, viral titers)

  • Survival rates and disease severity scoring

• Memory Persistence and Quality:

  • T-cell receptor (TCR) repertoire analysis (diversity and avidity)

  • Metabolic profiling of memory cells (oxygen consumption rate, mitochondrial mass)

  • Epigenetic analysis of memory-associated gene loci (ATAC-seq, ChIP-seq)

Comparison Matrix for LMOf2365_0526 Construct Evaluation:

When evaluating LMOf2365_0526-containing constructs, researchers should implement longitudinal experimental designs with sufficient statistical power to detect differences in memory qualities between vaccine formulations. Blood and tissue sampling (spleen, lymph nodes, bone marrow) should be performed at predetermined intervals to track the anatomical distribution and migration patterns of memory cells .

The ultimate validation of effective memory induction comes from challenge studies performed at distant time points (>6 months post-vaccination), demonstrating rapid recall responses and protection against pathogen challenge.

How can researchers address instability issues with LMOf2365_0526 expression constructs in Listeria vectors?

Researchers frequently encounter instability issues when working with LMOf2365_0526 expression constructs in Listeria vectors. These problems manifest as loss of expression over time, genetic alterations, or reduced viability of the recombinant bacteria. The following methodological approaches address these challenges:

Root Causes and Solutions for Expression Construct Instability:

• Metabolic Burden

  • Diagnostic signs: Slow growth rate, small colony size, rapid loss of expression during subculture

  • Solutions:

    • Implement inducible rather than constitutive promoters (e.g., PactA, PprfA)

    • Reduce protein expression levels by modifying ribosome binding sites

    • Consider using lower-copy integration methods

    • Optimize media composition to alleviate metabolic pressure

• Genetic Instability

  • Diagnostic signs: Deletions or rearrangements in the expression cassette, PCR products of unexpected sizes

  • Solutions:

    • Avoid repetitive sequences in construct design

    • Select optimal integration sites away from recombination hotspots

    • Screen multiple clones and select for stable variants

    • Sequence verify constructs after each major experiment

• Protein Toxicity

  • Diagnostic signs: Extremely slow growth, growth only in certain media, compensatory mutations

  • Solutions:

    • Use tight transcriptional control with minimal leaky expression

    • Express as fusion protein with solubility/stability enhancers

    • Design expression strategy to sequester protein in specific cellular compartments

    • Create truncated versions lacking toxic domains

Experimental Validation Protocol for Construct Stability:

For particularly problematic constructs, implementing a selective pressure system that links LMOf2365_0526 expression to bacterial survival can enforce construct maintenance. This might involve co-expression with essential genes or incorporating auxotrophic complementation systems.

When instability persists despite these measures, researchers should consider alternative expression strategies, such as using different Listeria strains (e.g., attenuated strains with improved tolerance for foreign protein expression) or episomal expression systems with enhanced stability features .

What approaches can resolve data inconsistencies in immunological studies using LMOf2365_0526-based vaccine constructs?

Immunological studies using LMOf2365_0526-based vaccine constructs sometimes yield inconsistent results due to complex interactions between the vaccine vector, the host immune system, and experimental variables. Resolving these data inconsistencies requires systematic troubleshooting and methodological refinements:

Common Sources of Data Inconsistency and Remediation Strategies:

• Pre-existing Immunity to Listeria Vector

  • Problem: Background immunity to L. monocytogenes can significantly alter responses to recombinant vaccines

  • Detection: Screen for Listeria-specific antibodies and T cells in experimental animals

  • Resolution:

    • Use Listeria strains with altered serotypes or attenuated variants

    • Implement prime-boost strategies using heterologous vectors

    • Statistically account for pre-existing immunity in data analysis

    • Select animals from Listeria-free colonies

• Variability in Vaccine Preparation

  • Problem: Batch-to-batch variations in bacterial viability, protein expression, or attenuation

  • Detection: Comprehensive quality control of each vaccine preparation

  • Resolution:

    • Standardize growth conditions (temperature, media, harvest time)

    • Quantify viable bacteria and protein expression for each preparation

    • Prepare large single batches for entire studies when possible

    • Implement reference standards for inter-experiment normalization

• Heterogeneous Immune Responses

  • Problem: Individual variation in immune response magnitudes and kinetics

  • Detection: High individual variability in immune parameters within groups

  • Resolution:

    • Increase sample sizes based on power calculations

    • Use paired analysis methods when appropriate

    • Consider genetic background effects in animal models

    • Implement longitudinal sampling from the same individuals

Decision Framework for Resolving Contradictory Data:

When confronted with persistently inconsistent data, a systematic approach involves:

• Implementing factorial experimental designs to identify interacting variables

• Developing robust internal controls and normalization methods

• Establishing clear criteria for data inclusion/exclusion before experiments begin

• Considering environmental factors (microbiome, housing conditions) that may influence immune responses

Finally, researchers should differentiate between biological variation (which may represent important immunological phenomena) and technical variation (which should be minimized through standardization). This distinction is particularly important when translating findings from animal models toward clinical applications .

What emerging technologies can enhance the study and application of LMOf2365_0526 in vaccine development?

The field of vaccine development using recombinant Listeria monocytogenes proteins like LMOf2365_0526 is rapidly evolving with several emerging technologies poised to transform research approaches and applications:

CRISPR-Based Genome Engineering:
Advanced CRISPR-Cas systems now enable precise modifications to both the Listeria vector and the LMOf2365_0526 gene sequence with unprecedented accuracy. This allows:

• Multiplex editing of several genomic locations simultaneously

• Creation of protein variants with modified immunogenicity profiles

• Fine-tuning of expression levels through promoter engineering

• Development of conditional expression systems responsive to specific stimuli

Single-Cell Technologies:
Single-cell RNA sequencing and CyTOF (mass cytometry) are revolutionizing our understanding of immune responses to vaccination:

• Identification of rare responding cell populations that may be missed in bulk analyses

• Characterization of full response trajectories from naive to memory T cells

• Mapping of clonal expansion patterns following vaccination

• Correlation of TCR repertoires with functional outcomes

Structural Vaccinology:
Advanced structural biology techniques are enabling rational design approaches:

• Cryo-EM and X-ray crystallography to determine LMOf2365_0526 structure

• Computational epitope prediction to identify immunodominant regions

• Structure-guided design of fusion constructs with enhanced stability

• Development of self-assembling nanoparticles incorporating LMOf2365_0526 epitopes

Synthetic Biology Platforms:
New synthetic biology approaches offer expanded capabilities:

• Cell-free protein synthesis systems for rapid prototyping

• Codon-optimization algorithms that balance expression with immunostimulation

• Genetic circuits for programmed antigen expression and release

• Biosensors for real-time monitoring of in vivo vaccine function

Comparative Effectiveness Matrix for Emerging Technologies:

The integration of these technologies creates new research possibilities, such as combining structural insights with CRISPR engineering to create optimized LMOf2365_0526 variants with enhanced immunogenicity profiles while maintaining the beneficial properties of the Listeria delivery platform. Additionally, systems vaccinology approaches that integrate multi-omics data can identify molecular signatures of successful vaccination, potentially accelerating vaccine development timelines .

How might combining LMOf2365_0526 with other immunomodulatory molecules enhance vaccine efficacy?

Combining LMOf2365_0526 with carefully selected immunomodulatory molecules represents a promising strategy to enhance vaccine efficacy through synergistic effects on immune activation. This approach can address multiple aspects of the immune response simultaneously, potentially overcoming limitations of single-antigen formulations:

Adjuvant Combinations and Their Mechanistic Benefits:

• TLR Ligands

  • Mechanism: TLR ligands activate pattern recognition receptors on antigen-presenting cells

  • Examples:

    • TLR9 agonists (CpG oligonucleotides): Enhanced Th1 polarization

    • TLR3 agonists (Poly I:C): Improved cross-presentation

  • Expected outcome: 5-10 fold increase in CD8+ T cell responses compared to LMOf2365_0526 alone

  • Implementation approach: Co-expression within Listeria vector or co-administration

• Cytokine Adjuvants

  • Mechanism: Direct modulation of immune cell function and trafficking

  • Examples:

    • IL-12: Promotes Th1 differentiation and CD8+ T cell expansion

    • GM-CSF: Enhances dendritic cell recruitment and function

  • Expected outcome: Extended persistence of antigen-specific T cells

  • Implementation approach: Genetic fusion to LMOf2365_0526 or co-expression

• Checkpoint Inhibitors

  • Mechanism: Prevent T cell exhaustion and maintain functional responses

  • Examples:

    • Anti-PD-1 antibodies or engineered PD-1 ligand traps

    • CTLA-4 blocking strategies

  • Expected outcome: Sustained T cell function during repeated antigen exposure

  • Implementation approach: Sequential administration following LMOf2365_0526 vaccination

• Co-stimulatory Molecule Enhancers

  • Mechanism: Amplify T cell activation signals

  • Examples:

    • CD40L expression constructs

    • 4-1BBL fusion proteins

  • Expected outcome: Lower activation threshold for antigen-specific T cells

  • Implementation approach: Co-expression within the same vector

Combination Efficacy Comparison Data:

Optimization Considerations:

The timing and dosing of combination components significantly impact efficacy and require careful optimization:

• Sequential vs. simultaneous administration:

  • Checkpoint inhibitors often show enhanced effects when administered after initial T cell priming

  • TLR ligands generally work best when co-administered with antigen

• Spatial co-localization:

  • Physical linkage of immunomodulators to LMOf2365_0526 can enhance local effects

  • Targeted delivery to lymphoid tissues may improve efficacy while reducing systemic effects

• Dosing ratios:

  • Optimal ratios between LMOf2365_0526 and immunomodulators must be empirically determined

  • Potential for non-linear dose-response relationships requires systematic testing

Mathematical modeling of these combination approaches can help predict optimal formulations, potentially accelerating the optimization process. These models can incorporate parameters such as receptor occupancy, signaling pathway activation thresholds, and cellular trafficking dynamics to guide experimental design .