Recombinant Escherichia coli O45:K1 UPF0060 membrane protein ynfA (ynfA)

What is the UPF0060 membrane protein ynfA from E. coli O45:K1?

The UPF0060 membrane protein ynfA is a bacterial membrane protein expressed in Escherichia coli O45:K1 strain S88/ExPEC. It is classified as an uncharacterized protein family (UPF) member, specifically UPF0060, indicating that its precise biological function remains to be fully elucidated. The protein is encoded by the ynfA gene, with the ordered locus name ECS88_1627. The recombinant version of this protein is produced for research purposes to investigate its structure, function, and potential role in bacterial physiology and pathogenesis .

What are the recommended storage conditions for recombinant ynfA protein?

For optimal stability and activity of the recombinant E. coli O45:K1 UPF0060 membrane protein ynfA, specific storage conditions are recommended. The protein should be stored in a Tris-based buffer containing 50% glycerol, which has been optimized specifically for this protein. For short-term storage (up to one week), the protein can be kept at 4°C. For longer-term storage, it should be maintained at -20°C. For extended storage periods, conservation at either -20°C or -80°C is recommended. It is important to note that repeated freezing and thawing cycles should be avoided as they can lead to protein degradation and loss of activity. Therefore, it is advisable to prepare working aliquots to minimize freeze-thaw cycles .

How does recombinant E. coli O45:K1 relate to other E. coli strains used in research?

E. coli O45:K1 (strain S88/ExPEC) is an extraintestinal pathogenic E. coli strain that differs from commonly used laboratory strains like BL21 and its derivatives. While BL21 and related strains are primarily used for recombinant protein production due to their deficiency in proteases like Lon and OmpT, E. coli O45:K1 is of interest for its pathogenic properties. The O45 serogroup has been studied in the context of Shiga toxin-producing E. coli (STEC), although research specifically on O45:K1 is less abundant compared to other pathogenic strains. Phylogenetic analyses have shown that E. coli O45:H2 strains are evolutionarily close to E. coli O103:H2 strains, sharing homology in virulence factors, whereas they are distinct from E. coli O45:H16 strains .

What expression systems are most effective for producing recombinant membrane proteins like ynfA?

Expression of membrane proteins such as ynfA presents significant challenges due to potential toxicity and proper folding issues. Based on current research methodologies, the most effective expression systems for membrane proteins like ynfA involve specialized E. coli strains and optimized expression protocols:

For membrane proteins like ynfA, two strategies have proven particularly effective: (1) tuning transcription and translation rates to prevent saturation of the membrane insertion machinery, and (2) co-expression of biogenesis factors that assist in proper membrane protein folding and insertion. The SRP/Sec pathway is critical for membrane protein targeting and translocation, and overexpression can lead to saturation of this pathway, resulting in cytoplasmic aggregates. Adjusting expression parameters or co-expressing components of the secretory pathway can improve yields of properly folded membrane proteins .

What are the challenges in purifying recombinant membrane proteins like ynfA and how can they be addressed?

Purification of membrane proteins like ynfA presents multiple challenges due to their hydrophobic nature and requirement for membrane-mimetic environments. The following methodological approaches can address these challenges:

• Detergent selection: Screening multiple detergents is crucial for effective solubilization while maintaining protein structure and function. Mild non-ionic detergents like DDM (n-dodecyl-β-D-maltoside) often provide a good starting point.

• Fusion tags optimization: For membrane proteins like ynfA, the selection of appropriate fusion tags is critical:

  • N-terminal tags are generally preferred as they emerge first during translation and can improve folding

  • Maltose-binding protein (MBP) and glutathione S-transferase (GST) tags can enhance solubility

  • His-tags facilitate purification via immobilized metal affinity chromatography (IMAC)

  • The optimal position and linker composition between the tag and target protein require empirical determination

• Reconstitution strategies: Following purification, membrane proteins often require reconstitution into lipid bilayers or nanodiscs to maintain native structure and function. This process must be carefully optimized for each protein.

• Stability enhancement: Addition of specific lipids, cholesterol, or stabilizing agents during purification can enhance stability of membrane proteins like ynfA.

The purification protocol should be developed through systematic optimization of these parameters, with careful monitoring of protein quality at each step using techniques such as SDS-PAGE, Western blotting, and activity assays .

How can researchers effectively analyze the structural characteristics of recombinant ynfA?

Structural analysis of membrane proteins like ynfA requires specialized approaches that account for their hydrophobic nature and membrane environment. A comprehensive strategy includes:

• Computational prediction:

  • Transmembrane topology prediction using algorithms like TMHMM, HMMTOP, or Phobius

  • Secondary structure prediction using programs like PSIPRED

  • Homology modeling if structural homologs exist in the PDB

• Experimental methods:

  • Circular dichroism (CD) spectroscopy to determine secondary structure composition

  • Limited proteolysis combined with mass spectrometry to identify domain boundaries and accessible regions

  • Site-directed spin labeling electron paramagnetic resonance (SDSL-EPR) to analyze dynamic properties and distances between protein regions

  • Cryo-electron microscopy (cryo-EM) for higher-resolution structural determination without crystallization

• Advanced structural biology techniques:

  • X-ray crystallography using lipidic cubic phase (LCP) or bicelle crystallization methods

  • Solid-state NMR spectroscopy for membrane proteins reconstituted in lipid bilayers

  • Hydrogen-deuterium exchange mass spectrometry (HDX-MS) to probe protein dynamics and solvent accessibility

Each of these approaches provides complementary information about different aspects of ynfA structure, and integration of multiple methods yields the most comprehensive structural characterization .

What post-translational modifications might be relevant for ynfA function and how can they be studied?

While E. coli has traditionally been considered limited in its post-translational modification (PTM) capabilities, recent research has shown that several PTMs can occur in bacterial proteins and may be relevant for membrane proteins like ynfA. Key methodological approaches include:

For ynfA specifically, investigating these modifications requires:

• Mass spectrometry-based approaches to identify endogenous modifications

• Site-directed mutagenesis of potential modification sites to assess functional consequences

• Co-expression systems that incorporate the relevant modification enzymes

• Comparative analysis of modifications in different growth conditions to understand their regulatory significance

Recent advances have enabled production of post-translationally modified proteins in E. coli by co-expressing the target protein with the enzymes responsible for the modifications of interest. This approach can be valuable for studying how PTMs might influence ynfA function and interactions .

What are the optimal conditions for expressing recombinant ynfA in E. coli expression systems?

Optimization of expression conditions for membrane proteins like ynfA is critical for obtaining functional protein in sufficient yields. Based on established protocols for membrane protein expression, the following methodological approach is recommended:

• Strain selection:

  • Primary recommendation: C41(DE3) or C43(DE3) strains specifically developed for membrane protein expression

  • Alternative: Lemo21(DE3) for tunable expression through rhamnose-regulated T7 lysozyme levels

• Expression vector optimization:

  • Use vectors with tightly controlled promoters (T7lac or araBAD)

  • Include a fusion partner that enhances membrane integration (e.g., Mistic, YidC)

  • Incorporate a cleavable purification tag (His8 or twin-Strep)

• Culture conditions:

  • Growth temperature: 20-25°C after induction (lower than standard 37°C)

  • Media: Terrific Broth supplemented with glucose (0.2%) to reduce leaky expression

  • Induction: Low concentrations of inducer (0.1-0.4 mM IPTG or 0.002% arabinose)

  • Duration: Extended expression time (16-24 hours) at lower temperature

• Optimization strategy:

  • Perform small-scale expression tests varying temperature, inducer concentration, and duration

  • Analyze membrane fraction by Western blot to assess expression levels

  • Evaluate protein functionality through activity assays when possible

This systematic approach addresses the common challenges in membrane protein expression and provides a framework for optimizing conditions specifically for ynfA expression .

How can researchers assess the functional activity of recombinant ynfA?

Assessing the functional activity of uncharacterized membrane proteins like ynfA presents a significant challenge. In the absence of known biochemical activities, a combination of indirect approaches can be employed:

• Membrane localization analysis:

  • Subcellular fractionation followed by Western blotting

  • Fluorescence microscopy using GFP-tagged ynfA

  • Protease accessibility assays to determine topology

• Interaction partner identification:

  • Pull-down assays using tagged ynfA as bait

  • Bacterial two-hybrid screening

  • Chemical cross-linking followed by mass spectrometry

  • Proximity-dependent biotin labeling (BioID)

• Phenotypic analysis:

  • Construction of ynfA knockout strains and assessment of phenotypic changes

  • Complementation studies with wild-type and mutant ynfA variants

  • Stress response analysis (changes in sensitivity to antibiotics, pH, temperature)

• Structural integrity assessment:

  • Circular dichroism spectroscopy to confirm secondary structure

  • Thermal shift assays to evaluate protein stability

  • Limited proteolysis to assess proper folding

By combining these approaches, researchers can build evidence for the functional role of ynfA even without prior knowledge of its specific biochemical activity. The data generated can guide hypothesis formation for more targeted functional assays .

What are the considerations for designing experiments to study ynfA's role in bacterial membrane function?

Investigating the role of ynfA in bacterial membrane function requires a multifaceted experimental approach that considers both the protein's biochemical properties and its physiological context. Key experimental design considerations include:

• Genetic manipulation strategies:

  • Gene deletion: Construction of ynfA knockout strains using λ-Red recombination or CRISPR-Cas9

  • Controlled expression: Development of inducible expression systems for wild-type and mutant ynfA

  • Reporter fusions: Creation of transcriptional and translational fusions to monitor expression patterns

• Membrane physiology assays:

  • Membrane potential measurements using fluorescent dyes (DiSC3(5), JC-1)

  • Membrane permeability assays (SYTOX Green uptake, propidium iodide)

  • Lipid composition analysis by thin-layer chromatography or mass spectrometry

  • Atomic force microscopy to assess membrane mechanical properties

• Stress response analysis:

  • Growth curves under various stress conditions (pH, osmotic pressure, temperature)

  • Antibiotic susceptibility testing, particularly for compounds targeting membrane integrity

  • Transcriptomic analysis to identify co-regulated genes under stress conditions

• Protein-lipid interaction studies:

  • Liposome binding assays with purified ynfA

  • Lipid extraction and analysis from ynfA-containing membrane fractions

  • Differential scanning calorimetry to measure membrane thermodynamic properties

• Experimental controls:

  • Complementation with wild-type ynfA to confirm phenotype specificity

  • Use of related membrane proteins as comparison controls

  • Inclusion of established membrane function markers (positive controls)

These experimental approaches should be integrated into a coherent research program that progresses from phenotypic observations to mechanistic understanding of ynfA's role in membrane function .

How can researchers analyze sequence conservation of ynfA across different E. coli strains?

Sequence conservation analysis of ynfA across different E. coli strains provides valuable insights into functionally important regions and evolutionary relationships. A robust methodological approach includes:

• Database mining and sequence retrieval:

  • Extract ynfA homologues from genomic databases (NCBI, UniProt)

  • Include sequences from diverse E. coli pathotypes (STEC, UPEC, EPEC)

  • Incorporate ynfA sequences from related Enterobacteriaceae for broader evolutionary context

• Multiple sequence alignment:

  • Perform alignment using algorithms optimized for membrane proteins (e.g., MAFFT with E-INS-i strategy)

  • Refine alignments manually focusing on transmembrane regions

  • Generate consensus sequences for different E. coli pathotypes

• Conservation analysis:

  • Calculate position-specific conservation scores using tools like ConSurf

  • Identify highly conserved residues as candidates for functional importance

  • Map conservation patterns onto predicted structural models

• Evolutionary analysis:

  • Construct phylogenetic trees using maximum likelihood methods

  • Compare ynfA phylogeny with strain phylogeny to detect horizontal gene transfer events

  • Calculate selection pressure (dN/dS ratios) to identify positively selected residues

• Integration with structural predictions:

  • Correlate conservation patterns with predicted structural features

  • Identify conserved motifs potentially involved in protein function

  • Generate testable hypotheses about structure-function relationships

This analytical framework enables researchers to identify key residues for functional studies and understand how ynfA varies across different E. coli strains, including pathogenic variants like O45:K1 .

What statistical approaches are appropriate for analyzing ynfA expression data?

• Experimental design considerations:

  • Minimum of three biological replicates per condition

  • Inclusion of appropriate reference genes for normalization

  • Randomization of samples to minimize batch effects

• Data normalization strategies:

  • For qRT-PCR: ΔΔCt method with multiple reference genes

  • For RNA-seq: TPM/FPKM normalization with batch correction

  • For protein quantification: Total protein normalization or housekeeping protein references

• Statistical testing frameworks:

  • For two-group comparisons: Student's t-test or Mann-Whitney U test (non-parametric)

  • For multiple groups: ANOVA with appropriate post-hoc tests (Tukey's HSD, Dunnett's)

  • For complex designs: Linear mixed-effects models to account for nested variables

• Multiple testing correction:

  • Benjamini-Hochberg procedure for false discovery rate control

  • q-value calculation for genome-wide expression studies

  • Effect size calculation (Cohen's d) to assess biological significance

• Visualization approaches:

  • Box plots showing distribution of expression values

  • Volcano plots displaying statistical significance versus fold change

  • Heatmaps for clustering expression patterns across conditions

• Validation strategies:

  • Independent verification using alternative expression measurement techniques

  • Correlation analysis between transcript and protein levels

  • Functional validation of expression changes through phenotypic assays

These statistical approaches ensure robust analysis of ynfA expression data while minimizing false positives and accounting for biological variability .

How can researchers integrate structural and functional data to develop hypotheses about ynfA's role?

Developing comprehensive hypotheses about ynfA's role requires the integration of structural and functional data through a systematic analytical framework:

• Data integration methodology:

  • Create a centralized repository of all experimental data related to ynfA

  • Standardize data formats to enable cross-experimental comparisons

  • Develop visual representations that simultaneously display structural and functional information

• Structure-function correlation approaches:

  • Map functional data (e.g., mutational effects) onto structural models

  • Identify spatial clusters of residues with similar functional impacts

  • Correlate evolutionary conservation with functional importance

• Network analysis:

  • Construct interaction networks incorporating ynfA and its partners

  • Analyze co-expression networks to identify functionally related genes

  • Perform pathway enrichment analysis of interacting partners

• Computational modeling:

  • Molecular dynamics simulations to predict conformational changes

  • Ligand docking studies to identify potential binding partners

  • Electrostatic surface analysis to identify interaction interfaces

• Hypothesis development framework:

  • Formulate multiple competing hypotheses consistent with all available data

  • Design critical experiments that discriminate between competing hypotheses

  • Implement Bayesian approaches to update hypothesis probabilities as new data emerges

• Validation strategy:

  • Prioritize hypotheses for experimental testing based on their explanatory power

  • Design experiments with appropriate controls to test specific aspects of each hypothesis

  • Iterate between hypothesis refinement and experimental validation

This integrated approach transforms disparate experimental observations into coherent hypotheses about ynfA's biological role while providing a roadmap for further investigation .

How does ynfA from E. coli O45:K1 compare with membrane proteins from other pathogenic E. coli strains?

Comparative analysis of ynfA from E. coli O45:K1 with membrane proteins from other pathogenic E. coli strains reveals important evolutionary and functional relationships. Current research findings indicate:

• Serotype-specific variations:

  • E. coli O45:K1 ynfA shows distinctive sequence features compared to other serotypes

  • Phylogenetic analysis places O45:K1 strains in proximity to O103:H2 strains, suggesting evolutionary relatedness

  • Specific variations in transmembrane domains may reflect adaptation to different host environments

• Comparative genomic context:

  • The genomic neighborhood of ynfA varies between pathotypes, suggesting different regulatory contexts

  • E. coli O45:H2 strains share higher homology with O103:H2 strains in terms of virulence factors

  • Analysis of ynfA presence/absence across E. coli pathotypes indicates its conservation pattern

• Functional comparisons:

  • Membrane proteins from pathogenic strains often show adaptations related to host interaction

  • E. coli O45:K1 (strain S88/ExPEC) being an extraintestinal pathogenic strain may have membrane proteins adapted for survival outside the intestinal environment

  • Comparative analysis of protein-protein interaction networks across pathotypes can reveal strain-specific functional adaptations

• Virulence associations:

  • Analysis of co-occurrence patterns between ynfA variants and virulence factors across different strains

  • Correlation of ynfA sequence variations with pathogenicity island distribution

  • Potential role in serotype-specific virulence mechanisms based on comparative functional genomics

This comparative analysis framework provides insights into how ynfA may contribute to the specific pathogenic mechanisms of E. coli O45:K1 strains in contrast to other pathogenic E. coli lineages .

What are the implications of studying ynfA for understanding membrane protein biology in pathogenic bacteria?

Research on ynfA contributes significantly to the broader understanding of membrane protein biology in pathogenic bacteria, with several important implications:

• Model system for uncharacterized membrane proteins:

  • ynfA represents the UPF0060 family of uncharacterized proteins, making it a valuable model for studying proteins of unknown function

  • Methodologies developed for ynfA characterization can be applied to other uncharacterized membrane proteins

  • Results may inform annotation strategies for the significant proportion of bacterial genomes that encode proteins of unknown function

• Pathogenesis mechanisms:

  • Membrane proteins are critical interfaces between pathogens and their environment

  • Understanding ynfA may reveal novel mechanisms for bacterial adaptation to host environments

  • Potential identification of new virulence determinants in pathogenic E. coli strains

• Antimicrobial development:

  • Membrane proteins represent important targets for antimicrobial development

  • Detailed characterization of ynfA structure and function could reveal druggable sites

  • Comparative analysis across pathogenic strains may identify conserved targets for broad-spectrum interventions

• Technological advances:

  • Methods optimized for ynfA expression and characterization advance the technical toolkit for membrane protein research

  • Innovative approaches to structure determination of challenging membrane proteins

  • Development of new functional assays for proteins without known biochemical activities

• Evolutionary insights:

  • Understanding how membrane proteins like ynfA vary across pathogenic lineages provides insights into bacterial evolution

  • Identification of selection pressures acting on membrane proteins during host adaptation

  • Tracking horizontal gene transfer events involving membrane protein genes

These implications highlight the broader significance of ynfA research beyond its specific function, positioning it within the larger context of bacterial pathogenesis and membrane biology research .

What are the most promising future research directions for understanding ynfA function?

Based on current knowledge and technological capabilities, several promising research directions can advance understanding of ynfA function:

• Integrative structural biology:

  • Application of cryo-electron microscopy for high-resolution structure determination

  • Integration of complementary structural approaches (X-ray crystallography, NMR, molecular dynamics)

  • Structure-guided functional studies targeting specific domains or residues

• Systems biology approaches:

  • Global interactome mapping to identify ynfA protein partners

  • Multi-omics integration (transcriptomics, proteomics, metabolomics) under ynfA perturbation

  • Network analysis to position ynfA within cellular pathways

• In vivo relevance studies:

  • Animal infection models comparing wild-type and ynfA mutant strains

  • Tissue-specific expression analysis during infection

  • Competition assays to assess contribution to fitness in different environments

• Synthetic biology applications:

  • Engineering ynfA variants with enhanced expression or stability

  • Development of ynfA-based biosensors or reporting systems

  • Exploration of biotechnological applications based on ynfA properties

• Comparative genomics expansion:

  • Broader phylogenetic analysis across the Enterobacteriaceae family

  • Correlation of sequence variations with ecological niches

  • Ancient sequence reconstruction to track evolutionary trajectory

These research directions represent complementary approaches that together can elucidate the functional significance of ynfA in bacterial physiology and pathogenesis, while developing generalizable insights for membrane protein biology .

How can interdisciplinary approaches enhance our understanding of proteins like ynfA?

Interdisciplinary approaches offer powerful strategies to overcome the challenges in studying uncharacterized membrane proteins like ynfA:

• Computational biology and bioinformatics:

  • Advanced machine learning for predicting protein-protein interactions

  • Evolution-based covariance analysis to identify functionally linked residues

  • Network theory applications to position ynfA in global cellular networks

• Structural biology and biophysics:

  • Single-molecule techniques to study conformational dynamics

  • Advanced imaging approaches like super-resolution microscopy

  • Hydrogen-deuterium exchange mass spectrometry for dynamic structural information

• Synthetic biology and protein engineering:

  • Directed evolution to enhance expression and stability

  • Creation of chimeric proteins to map functional domains

  • Development of genetically encoded sensors based on ynfA

• Systems microbiology:

  • Host-pathogen interaction studies in complex model systems

  • Microbiome analyses to understand ecological context

  • Multi-species biofilm models to assess community roles

• Chemical biology:

  • Activity-based protein profiling to identify biochemical functions

  • Photo-crosslinking approaches to capture transient interactions

  • Small molecule screening to identify ligands or inhibitors

The integration of these diverse disciplines creates a comprehensive research framework that can reveal multiple facets of ynfA biology, from atomic-level structure to ecological significance. Such interdisciplinary approaches are particularly valuable for uncharacterized proteins where traditional single-discipline approaches may have limited success .