Recombinant Listeria welshimeri serovar 6b Protein psiE homolog (psiE)

What is the Recombinant Listeria welshimeri serovar 6b Protein psiE homolog and how is it characterized?

Recombinant Listeria welshimeri serovar 6b Protein psiE homolog (psiE) is a protein derived from L. welshimeri serovar 6b (strain ATCC 35897 / DSM 20650 / SLCC5334). The protein has a UniProt identification number of A0AGW6 and is encoded by the gene psiE (ordered locus name: lwe0830). The full-length protein consists of 137 amino acids with the sequence: MKRLEKISSIVPILLRITLNLALIMVGFTLVAFLIREAFTIFNNIFFLDTDVSYYYMTQDILTFFLYFEFIALIVKYFESHFHFPLRYFIYIGITAIIRFIIVDHSSATSTLILSGAILLVAALFLANTKMLKREG . The protein appears to be membrane-associated based on its amino acid sequence, which contains several hydrophobic regions consistent with transmembrane domains.

How does Listeria welshimeri serovar 6b differ from pathogenic Listeria species?

Listeria welshimeri serovar 6b differs from pathogenic Listeria species in several key ways. L. welshimeri was originally isolated from decaying plants rather than clinical specimens. Unlike pathogenic species like L. monocytogenes, L. welshimeri produces negative results in the CAMP test with both Staphylococcus aureus and Rhodococcus equi, indicating the absence of key virulence factors. While it shares general Listeria characteristics (gram-positive rods, motile below 30°C via peritrichous flagella, growth at 4°C within 5 days), L. welshimeri's biochemical profile includes acid production from d-xylose and α-methyl-d-mannoside fermentation but not from l-rhamnose and d-mannitol . Genomic studies have revealed that L. welshimeri lacks the pathogenicity islands present in virulent Listeria species and has a chromosome devoid of mobile genetic elements and plasmids, suggesting evolutionary reduction from pathogenic ancestors .

What is the genomic context of the psiE gene in Listeria welshimeri?

The psiE gene in L. welshimeri is identified by the ordered locus name lwe0830 within the bacterial genome. Genomic analysis of L. welshimeri has revealed several significant features of the chromosomal organization. The psiE gene exists in a genomic landscape characterized by high synteny with other Listeria species, though with specific differences. L. welshimeri's genome shows evidence of gene loss compared to pathogenic Listeria species, with stable deletions that appear to be consistent across different strains of the species . The genomic neighborhood of psiE may be significant for understanding its function, particularly as certain regions in the L. welshimeri genome represent evolutionary "hot spots" that demonstrate species-specific adaptations. PCR analysis of different L. welshimeri serovar strains has shown that these genomic arrangements are stable within the species, suggesting that the development of L. welshimeri was likely a clonal evolutionary event .

How can homology modeling be applied to predict the structure and function of psiE protein?

Homology modeling of the psiE protein can be approached using advanced computational methods that leverage structural similarities with known protein domains. Recent advances in protein structure prediction have significantly improved our ability to model proteins with low sequence identity to known structures. When applying homology modeling to psiE:

• Begin with sensitive homology detection methods such as DHR (dense homolog retriever), which has demonstrated >10% increased sensitivity compared to traditional methods like PSI-BLAST and MMseqs2 . DHR utilizes protein language models to generate embeddings that capture evolutionary and structural information.

• For structural comparisons, consider implementing techniques similar to those used for PsaE protein analysis, where NMR-derived restraints helped determine a well-defined five-stranded beta-sheet structure . Although PsaE and psiE are different proteins, the methodology is transferable.

• Use multiple sequence alignments (MSAs) constructed from retrieved homologs to enhance the accuracy of structural predictions, as protein language models can effectively capture relationships between remote homologs even with low sequence identity .

• Validate structural predictions using established metrics such as template modeling score (TM-score), paying particular attention to transmembrane regions suggested by the hydrophobic segments in psiE's sequence .

This multi-layered approach can provide insights into psiE's potential functional domains and interaction surfaces that would not be apparent from sequence analysis alone.

What experimental approaches are most effective for studying protein-protein interactions involving psiE homolog?

For studying protein-protein interactions involving the psiE homolog, researchers should consider a strategic combination of complementary techniques:

The most effective strategy involves initial identification of potential interaction partners through pull-down assays with the recombinant psiE protein, followed by validation using complementary methods. When working with membrane-associated proteins like psiE, special consideration should be given to membrane solubilization conditions to maintain native conformations. Detergent screening is essential, as improper detergent selection can disrupt physiologically relevant interactions .

For more challenging interactions, consider advanced proximity-based labeling methods such as BioID or APEX2, which can identify proximal proteins in the native cellular environment. These approaches are particularly valuable for membrane proteins where traditional co-immunoprecipitation methods may fail to preserve weak or transient interactions.

How might the evolutionary relationship between psiE homologs across Listeria species inform functional predictions?

Evolutionary analysis of psiE homologs across Listeria species provides critical insights into functional conservation and divergence. By examining selection pressures and sequence conservation patterns:

• Comparative genomic analysis reveals that while L. welshimeri lacks many virulence factors present in pathogenic Listeria species, certain protein families and structural motifs are conserved across the genus . This conservation pattern can help identify functionally critical regions within the psiE protein.

• Analysis of genomic islands, such as LGI2-like islands which have been identified in non-pathogenic Listeria species, may reveal horizontal gene transfer events that have shaped psiE evolution . These islands can harbor genes that confer specific ecological adaptations.

• Systematic analysis of deletion patterns across L. welshimeri strains has shown remarkable stability in genomic architecture, suggesting that gene loss events were early and defining in the species' evolution . This stability allows researchers to reliably predict which protein interaction networks have been preserved or lost.

• Construction of phylogenetic trees specifically focused on psiE and its homologs can identify branches of functional diversification. Proteins that cluster with psiE in these analyses may share functional characteristics even if they have diverged significantly in sequence.

By mapping sequence conservation onto predicted structural models, researchers can identify surface patches that are likely involved in conserved protein-protein interactions or enzymatic functions. Regions showing accelerated evolution may indicate adaptation to species-specific environmental niches or escape from selective pressures present in pathogenic species.

What are the optimal conditions for expressing and purifying recombinant Listeria welshimeri psiE protein?

The optimal conditions for expressing and purifying recombinant L. welshimeri psiE protein involve careful consideration of expression systems, buffer conditions, and purification strategies:

Expression System Selection:

• Consider using E. coli BL21(DE3) for initial expression trials, as this strain is deficient in key proteases and suitable for membrane-associated proteins.

• For membrane proteins like psiE, expression using a fusion tag such as MBP (maltose-binding protein) can improve solubility and folding.

• Regulate expression using a tunable promoter system (e.g., T7lac) with reduced IPTG concentrations (0.1-0.5 mM) and lower incubation temperatures (16-25°C) to prevent inclusion body formation.

Purification Protocol:

• Extract the protein using a gentle lysis method combining lysozyme treatment (1 mg/ml) with mild detergents such as n-dodecyl-β-D-maltoside (DDM) at 1% concentration.

• Perform initial purification using affinity chromatography targeting the fusion tag (e.g., His-tag affinity with imidazole gradients).

• For membrane proteins like psiE, maintain critical micellar concentration (CMC) of appropriate detergents throughout all purification steps to prevent protein aggregation.

• Consider size exclusion chromatography as a final polishing step to ensure monodispersity.

Storage Conditions:
Based on available information, the optimal storage buffer should contain Tris-based buffer with 50% glycerol, and the protein should be stored at -20°C for short-term use or -80°C for extended storage . Repeated freeze-thaw cycles should be avoided, with working aliquots maintained at 4°C for up to one week.

The presence of transmembrane domains in psiE necessitates careful optimization of detergent conditions during all purification steps to maintain native conformation while preventing aggregation.

What are the most effective methods for generating recombinant constructs with the psiE gene for expression studies?

For generating effective recombinant constructs with the psiE gene, researchers should consider these methodological approaches:

• Homologous recombination strategy: Homologous recombination has proven highly efficient for generating recombinant constructs. For optimal results, maintain high genomic integrity during DNA isolation and carefully select linearization sites. Research on recombinant virus generation has demonstrated that specific restriction enzyme sites (analogous to XbaI and AvrII in PRV recombination) can significantly increase recombination efficiency .

• Vector selection and design: For membrane proteins like psiE, vectors containing fusion partners that aid solubility (such as MBP, SUMO, or TrxA) are recommended. Include TEV protease cleavage sites for tag removal and design constructs with both N- and C-terminal tag options to determine which maintains functionality.

• PCR-based cloning optimization: Design primers with 15-25 bp overlap with the vector and 20-25 bp complementarity to the psiE gene. For difficult templates with high GC content or secondary structures, consider using specialized polymerases like Q5 High-Fidelity DNA Polymerase with GC enhancer buffers.

• Site-directed mutagenesis approach: For structure-function studies, implement a systematic alanine scanning mutagenesis protocol targeting predicted functional domains and transmembrane regions. Use overlap extension PCR methods that allow precise nucleotide changes without introducing unwanted mutations elsewhere.

• Recombinant verification: Verify all recombinant constructs using a combination of restriction digestion patterns, PCR with locus-specific primers positioned 200 nt or more from the homologous extension regions , and DNA sequencing of the entire insert and junctions.

For optimal expression of membrane proteins like psiE, consider synthetic gene approaches with codon optimization for the expression host and the inclusion of regulatory elements that modulate expression levels to prevent toxicity or inclusion body formation.

How can researchers effectively analyze the subcellular localization and membrane topology of psiE protein?

Analyzing the subcellular localization and membrane topology of psiE protein requires a multi-technique approach that addresses both localization and orientation:

Experimental Approaches for Subcellular Localization:

• Fluorescent fusion proteins: Generate C- and N-terminal GFP or mCherry fusions of psiE and observe localization patterns in both homologous (Listeria) and heterologous (E. coli) expression systems using high-resolution confocal microscopy.

• Subcellular fractionation: Separate bacterial cells into cytoplasmic, membrane, and periplasmic fractions using differential centrifugation and osmotic shock techniques. Quantify psiE distribution using western blotting with specific antibodies.

• Immunogold electron microscopy: For nanometer-scale resolution, use immunogold labeling with anti-psiE antibodies and transmission electron microscopy to visualize precise membrane localization.

Membrane Topology Determination Methods:

• Cysteine accessibility method: Introduce cysteine residues at various positions in a cysteine-less psiE variant, then test accessibility to membrane-impermeable sulfhydryl reagents like MTSET to determine which regions face the cytoplasm versus periplasm.

• Protease protection assays: Expose membrane vesicles or spheroplasts containing psiE to proteases like proteinase K, then analyze protected fragments by mass spectrometry to identify membrane-embedded regions.

• Fluorescence quenching: Utilize pH-sensitive GFP variants (pHluorin) fused to different termini or loops of psiE to determine orientation relative to the membrane.

The amino acid sequence of psiE (MKRLEKISSIVPILLRITLNLALIMVGFTLVAFLIREAFTIFNNIFFLDTDVSYYYMTQDILTFFLYFEFIALIVKYFESHFHFPLRYFIYIGITAIIRFIIVDHSSATSTLILSGAILLVAALFLANTKMLKREG) suggests multiple potential transmembrane domains. Computational prediction using tools like TMHMM, TOPCONS, or DeepTMHMM should be used to guide experimental design, but experimental verification remains essential for accurate topology mapping.

What are the key considerations for designing structure-function studies of psiE protein?

When designing structure-function studies for the psiE protein, researchers should implement a comprehensive strategy that connects structural features with functional outcomes:

• Domain identification and targeted mutagenesis:

  • Begin with bioinformatic analysis to identify conserved domains and sequence motifs

  • Design a systematic mutagenesis strategy targeting:
    a) Predicted transmembrane regions
    b) Highly conserved residues across homologs
    c) Charged residues in predicted loops

  • Create both alanine substitutions and more conservative changes (e.g., Lys→Arg, Asp→Glu)

• Functional assay development:

  • Establish assays measuring membrane integrity in expressing cells

  • Develop protein-protein interaction assays using split-reporter systems

  • Consider phenotypic microarray analysis similar to methods used for E. coli mutants to identify conditions where psiE function becomes critical

• Structural analysis integration:

  • Correlate mutagenesis results with predicted structural models

  • Consider NMR studies of purified domains, similar to the approach used for PsaE protein analysis

  • Use crosslinking and mass spectrometry to identify interaction interfaces

• Evolutionary context integration:

  • Compare functional effects of mutations with conservation patterns across Listeria species

  • Investigate parallel mutations in homologs from both pathogenic and non-pathogenic Listeria

The hydrophobic nature of psiE (containing multiple potential transmembrane segments) presents specific challenges for structural studies. Consider lipid nanodiscs or amphipols to maintain native-like membrane environments during biochemical and structural analyses. For detailed interaction studies, proximity-dependent labeling methods may overcome limitations of traditional co-immunoprecipitation approaches with membrane proteins.

How can researchers troubleshoot common issues in psiE protein expression and purification?

Troubleshooting psiE protein expression and purification requires a systematic approach to address common challenges encountered with membrane proteins:

For membrane proteins like psiE with hydrophobic transmembrane domains, special attention must be paid to maintaining the critical micellar concentration (CMC) of detergents throughout all purification steps. Consider fluorescence-based thermal stability assays (Thermofluor) to rapidly screen buffer conditions that maximize protein stability.

When expression in E. coli proves challenging, alternative expression systems such as Listeria-specific vectors or cell-free expression systems supplemented with lipid nanodiscs may provide better results for maintaining native folding and functionality.

What strategies can be employed to investigate potential interaction partners of psiE protein in its native environment?

Investigating psiE protein interactions in its native environment requires specialized approaches that preserve physiologically relevant interactions:

• In vivo crosslinking approaches:

  • Implement formaldehyde crosslinking followed by immunoprecipitation (ChIP-like approach)

  • Use photoactivatable crosslinkers incorporated as unnatural amino acids at specific positions

  • Apply membrane-permeable, cleavable crosslinkers with different spacer arm lengths to capture interactions at various distances

• Proximity-based labeling techniques:

  • Develop psiE fusions with proximity labeling enzymes (BioID, TurboID, or APEX2)

  • Express these constructs in Listeria under native promoter control

  • Identify proximal proteins through streptavidin pulldown and mass spectrometry

• Membrane-specific interaction methods:

  • Implement split-ubiquitin membrane yeast two-hybrid system for membrane protein interactions

  • Use FRET-based approaches with fluorescent protein fusions expressed in Listeria

  • Consider bacterial two-hybrid systems optimized for membrane protein interactions

• Co-purification strategies:

  • Develop gentle solubilization protocols using digitonin or styrene maleic acid lipid particles (SMALPs)

  • Implement tandem affinity purification (TAP) methods adapted for membrane proteins

  • Use stable isotope labeling with amino acids in cell culture (SILAC) to differentiate specific from non-specific interactions

When working with Listeria, genetic manipulation techniques must be optimized. Consider the homologous recombination approaches shown effective for Pseudorabies virus , adapting the method to Listeria by identifying optimal linearization sites. For validation, compare interaction partners identified in L. welshimeri with those in other Listeria species to distinguish species-specific from conserved interactions.

How should researchers interpret structural homology between psiE and other bacterial proteins?

Interpreting structural homology between psiE and other bacterial proteins requires careful consideration of several analytical dimensions:

• Distinguishing functional from structural homology:

  • Structural similarity without sequence conservation may indicate convergent evolution rather than shared ancestry

  • Apply sensitive homology detection methods like DHR, which has demonstrated >10% increased sensitivity compared to traditional methods

  • Consider that structural homologs with <20% sequence identity may still share mechanistic features

• Functional inference from structural homologs:

  • When structural similarity is detected, perform detailed comparison of active site residues and binding pockets

  • Analyze electrostatic surface properties, as functionally related proteins often maintain similar surface charge distributions despite sequence divergence

  • Consider that membrane proteins like psiE may have structural constraints imposed by the lipid bilayer environment

• Evaluating evolutionary relationships:

  • Generate structure-guided sequence alignments rather than relying solely on primary sequence

  • Construct phylogenetic trees based on structure-informed alignments

  • Compare with genome-based phylogenies to identify potential horizontal gene transfer events

What statistical approaches are most appropriate for analyzing protein-protein interaction data involving psiE?

When analyzing protein-protein interaction data for psiE, researchers should implement statistical approaches tailored to the specific experimental techniques:

• For mass spectrometry-based interaction studies:

  • Implement SAINT (Significance Analysis of INTeractome) algorithm to distinguish true interactors from background

  • Use semi-quantitative approaches like normalized spectral abundance factors (NSAF) to compare relative abundance of interacting proteins

  • Apply multiple testing corrections (Benjamini-Hochberg procedure) to control false discovery rate

  • Compare against appropriate controls including:
    a) Unrelated membrane proteins expressed at similar levels
    b) Cells expressing tag-only controls
    c) Wild-type cells without tagged proteins

• For proximity labeling experiments:

  • Implement robust statistical frameworks that account for labeling efficiency biases

  • Use QSPEC or DESeq2-based approaches for quantitative comparison across conditions

  • Consider Bayesian approaches that integrate prior knowledge of membrane protein interactions

• Network analysis approaches:

  • Apply Markov clustering to identify functional modules within the interaction network

  • Calculate betweenness centrality and other network metrics to identify key nodes

  • Implement permutation-based approaches to assess the significance of network features

• Integrative statistical approaches:

  • Combine data from multiple interaction detection methods using heterogeneous data integration

  • Implement Bayesian integration frameworks that account for varying false positive and negative rates

  • Weight interaction confidence based on reproducibility across technical and biological replicates

How can researchers reconcile contradictory experimental results in psiE functional studies?

• Methodological evaluation:

  • Catalog all experimental approaches used across contradictory studies

  • Assess the strengths and limitations of each method specifically for membrane proteins

  • Evaluate whether differences in expression systems, tags, or purification methods could explain contradictions

  • Consider whether the protein's membrane topology was consistent across studies

• Conditional functionality assessment:

  • Determine whether contradictory results occurred under different experimental conditions

  • Investigate if psiE function is condition-dependent (pH, temperature, ionic strength)

  • Consider that membrane composition differences between expression systems may alter function

  • Evaluate whether observed differences represent true biological variability

• Integrated data analysis approaches:

  • Implement meta-analysis techniques appropriate for small sample sizes

  • Use Bayesian hierarchical models to integrate data across studies while accounting for study-specific effects

  • Apply random effects models to estimate true effect sizes while accounting for between-study variability

  • Consider whether apparently contradictory results may represent different aspects of a complex function

• Validation through orthogonal approaches:

  • Design experiments specifically targeting contradictory findings

  • Use complementary techniques that address limitations of previous methods

  • Perform genetic interaction studies to place contradictory functions in biological context

  • Consider synthetic biology approaches to reconstitute minimal systems for functional testing

When reconciling contradictions specifically for psiE, researchers should consider the protein's evolutionary context. The genomic reduction observed in L. welshimeri compared to pathogenic Listeria species suggests that psiE may have evolved altered functionality in this non-pathogenic context. This evolutionary perspective may help explain apparently contradictory findings between homologs in different Listeria species.

What emerging technologies hold promise for advancing psiE protein research?

Several cutting-edge technologies show significant potential for advancing psiE protein research:

• Cryo-electron microscopy advances:

  • Single-particle analysis optimized for membrane proteins in nanodiscs

  • Focused ion beam milling combined with tomography to visualize psiE in its native membrane context

  • Time-resolved cryo-EM to capture conformational changes during function

• Advanced protein structure prediction:

  • AlphaFold2 and RoseTTAFold can now predict membrane protein structures with increasing accuracy

  • Multi-state modeling approaches to capture conformational dynamics

  • Hybrid methods combining sparse experimental data with computational predictions

• Integrative structural biology approaches:

  • Combining hydrogen-deuterium exchange mass spectrometry (HDX-MS) with computational modeling

  • Integrating solid-state NMR constraints with molecular dynamics simulations

  • Advanced cross-linking mass spectrometry with photo-activatable unnatural amino acids

• High-throughput functional characterization:

  • Deep mutational scanning to comprehensively assess the impact of mutations on function

  • Microfluidic approaches for single-cell phenotyping of psiE variants

  • Multiplexed CRISPR interference screens to identify genetic interactions

• Single-molecule techniques:

  • Single-molecule FRET to monitor conformational changes in membrane proteins

  • Advanced fluorescence correlation spectroscopy to characterize protein diffusion and interactions in membranes

  • Nanopore-based electrical recordings for membrane protein activity

These emerging technologies are particularly relevant for membrane proteins like psiE where traditional structural biology approaches have been challenging. The combination of advanced computational methods with targeted experimental approaches holds particular promise for elucidating both structure and function of this protein class.

How might comparative genomics approaches enhance our understanding of psiE protein evolution and function?

Comparative genomics approaches offer powerful insights into psiE protein evolution and function through several strategic analyses:

• Pan-genome analysis across Listeria species:

  • Construct a comprehensive Listeria pan-genome focusing on psiE homologs

  • Identify core (conserved), accessory, and unique genomic elements associated with psiE

  • Map genomic context conservation to infer functional relationships

  • Compare synteny patterns around psiE loci to identify evolutionary events

• Selection pressure analysis:

  • Calculate dN/dS ratios across different Listeria lineages to identify regions under positive or purifying selection

  • Apply site-specific models to identify individual amino acids under selection

  • Compare selection patterns between pathogenic and non-pathogenic Listeria species

• Ancestral sequence reconstruction:

  • Infer ancestral psiE sequences at key evolutionary nodes

  • Experimentally test reconstructed proteins to understand functional evolution

  • Identify critical mutations that may have altered function during Listeria evolution

• Horizontal gene transfer analysis:

  • Investigate genomic islands and potential horizontal gene transfer events

  • Examine LGI2-like islands which have been identified in non-pathogenic Listeria species

  • Assess whether psiE shows evidence of acquisition from non-Listeria sources

• Co-evolution network analysis:

  • Identify proteins that show correlated evolutionary patterns with psiE

  • Construct co-evolution networks to predict functional relationships

  • Use these networks to guide experimental investigation of protein complexes

The whole-genome sequence analysis of L. welshimeri has already revealed common steps in genomic evolution with pathogenic Listeria species . Building on this foundation, researchers can now focus specifically on psiE to understand its role in the evolutionary divergence of pathogenic and non-pathogenic Listeria. This comparative approach is particularly valuable given the genomic reduction observed in L. welshimeri, which suggests that retained genes like psiE likely serve important functions.

What are the potential applications of psiE research in biotechnology and synthetic biology?

Research on psiE protein from L. welshimeri offers several promising applications in biotechnology and synthetic biology:

• Development of non-pathogenic Listeria as biosensors:

  • Engineer L. welshimeri strains expressing modified psiE fusion proteins

  • Develop environmental biosensors leveraging the robustness of Listeria in diverse conditions

  • Create detection systems for food safety applications based on psiE-reporter constructs

• Membrane protein engineering platforms:

  • Use psiE as a scaffold for developing novel membrane protein functions

  • Engineer chimeric proteins combining psiE transmembrane domains with functional domains

  • Develop synthetic signaling pathways utilizing psiE membrane insertion properties

• Biotechnological applications of L. welshimeri:

  • Exploit the non-pathogenic nature of L. welshimeri for biotechnological processes

  • Develop genetically modified L. welshimeri strains optimized for specific industrial applications

  • Engineer production strains leveraging the cold-tolerance of Listeria for low-temperature bioprocessing

• Synthetic biology applications:

  • Design minimal membrane protein systems based on psiE's structure

  • Create orthogonal membrane signaling systems for synthetic biology applications

  • Develop controllable membrane permeability systems for advanced cell engineering

• Advanced homologous recombination tools:

  • Adapt efficient homologous recombination methods optimized for Listeria

  • Develop tools similar to those used for recombinant virus production

  • Create streamlined systems for membrane protein expression and engineering

The development of these applications would benefit from the simplified genetic background of L. welshimeri, which lacks the pathogenicity islands and mobile genetic elements found in virulent Listeria species . This genomic simplicity makes L. welshimeri an attractive platform for synthetic biology applications, with psiE serving as a potential component in engineered membrane systems.