Recombinant Escherichia coli O6:K15:H31 Uncharacterized protein yjiK (yjiK)

What is the Escherichia coli O6:K15:H31 Uncharacterized protein YjiK?

YjiK is a protein of 286 amino acids found in Escherichia coli that currently has no well-characterized function. It is classified as an uncharacterized protein in databases, with UniProt ID A1AJL2. The protein is encoded by the yjiK gene and also goes by synonyms including Ecok1_43580, APECO1_2085, and Uncharacterized protein YjiK . The term "uncharacterized" indicates that while the protein's sequence is known, its biological role, biochemical activities, and structural properties remain largely undefined through experimental validation.

Recent research approaches to uncharacterized proteins typically involve comparative sequence analysis, structural prediction, and functional genomics to generate hypotheses about potential roles. For researchers beginning work with YjiK, understanding that it represents one of many bacterial proteins whose functions remain to be elucidated is essential context for experimental design.

How is recombinant YjiK protein typically expressed and purified?

Recombinant YjiK protein is typically expressed in E. coli expression systems with an N-terminal histidine tag to facilitate purification. The expression construct generally includes the full-length protein (amino acids 1-286) fused to the His-tag . This approach leverages the well-established bacterial expression machinery while providing a convenient purification handle.

The expression and purification workflow typically involves:

• Cloning the yjiK gene into an appropriate expression vector with a His-tag

• Transformation into an E. coli expression strain

• Induction of protein expression (often using IPTG for T7-based systems)

• Cell lysis and clarification of lysate

• Affinity chromatography using nickel or cobalt resins to capture the His-tagged protein

• Optional tag removal using specific proteases (e.g., TEV protease)

• Further purification steps if necessary (ion exchange, size exclusion chromatography)

• Final concentration and buffer exchange

• Storage as aliquots in appropriate buffer conditions

The purified product is typically provided as a lyophilized powder to enhance stability during shipping and storage. Reconstitution in an appropriate buffer (typically Tris/PBS-based, pH 8.0) is recommended prior to use in experimental applications .

What are optimal conditions for expressing and purifying recombinant YjiK protein?

When designing experiments for optimal expression of recombinant YjiK protein, researchers should consider multiple parameters that can be systematically varied to maximize yield and quality. Based on established protocols for similar bacterial proteins, the following conditions should be tested:

Table 2: Experimental Parameters for Optimizing YjiK Expression

For purification, immobilized metal affinity chromatography (IMAC) using Ni-NTA or Co-NTA resins is the primary method, given the His-tag fusion. This should be followed by size exclusion chromatography to ensure homogeneity. The purification buffer should be optimized through a systematic approach testing different pH values (7.0-8.5), salt concentrations (100-500 mM NaCl), and stabilizing additives (glycerol 5-20%, reducing agents).

The experimental design should include randomization of samples and appropriate replication to ensure statistical validity, following basic experimental design principles as outlined in scientific literature4.

How should recombinant YjiK protein be stored and handled for maximum stability?

Proper storage and handling of YjiK protein is critical for maintaining its structural integrity and biological activity. Based on established protocols for similar recombinant proteins, the following recommendations apply:

Short-term storage (up to one week): Store at 4°C in appropriate buffer conditions. Avoid repeated freeze-thaw cycles as these can lead to protein denaturation and aggregation .

Long-term storage: Store at -20°C/-80°C in small aliquots to minimize freeze-thaw cycles. The addition of glycerol (final concentration 5-50%, with 50% being optimal for many applications) serves as a cryoprotectant .

Prior to use, vials should be briefly centrifuged to bring contents to the bottom. Reconstitution should be performed in deionized sterile water to a concentration of 0.1-1.0 mg/mL .

When designing experiments involving YjiK, researchers should include stability controls - samples stored under different conditions and tested at various time points to establish a stability profile. This systematic approach will help determine the optimal storage parameters for your specific experimental needs and provide confidence in the integrity of the protein throughout the experimental timeline.

What analytical methods are recommended for characterizing recombinant YjiK?

Comprehensive characterization of recombinant YjiK requires a multi-method approach addressing various protein properties. Researchers should implement the following analytical methods as part of their experimental design:

Table 3: Analytical Methods for YjiK Characterization

For experimental design, researchers should include appropriate controls for each method and perform sufficient technical replicates (minimum of three) to ensure statistical significance. When reporting results, detailed methodological information must be provided to enable reproducibility.

Given that YjiK is uncharacterized, these analytical methods should be considered baseline characterization. Additional functional assays should be designed based on bioinformatic predictions of potential activities or structural similarities to characterized proteins.

What approaches can researchers use to investigate potential functional roles of YjiK?

Investigating the function of an uncharacterized protein like YjiK requires a multi-pronged strategy combining computational prediction, genetic manipulation, and biochemical characterization. Researchers should consider implementing the following systematic approaches:

• Comparative Genomics Analysis:

  • Examine the genomic context of yjiK to identify neighboring genes that might suggest functional relationships

  • Analyze phylogenetic distribution across bacterial species to determine conservation patterns

  • Identify co-occurrence patterns with other genes across multiple genomes

• Structural Prediction and Analysis:

  • Employ homology modeling using templates from proteins with similar sequences

  • Conduct ab initio structure prediction using tools like AlphaFold

  • Identify potential binding pockets or active sites for functional hypothesis generation

• Gene Deletion and Complementation Studies:

  • Create a clean deletion of yjiK in E. coli

  • Characterize phenotypic changes under various growth conditions

  • Perform complementation with wild-type and mutant variants to verify specificity

• Protein-Protein Interaction Screening:

  • Conduct pull-down assays using tagged YjiK as bait

  • Perform bacterial two-hybrid screening

  • Use proximity labeling approaches like BioID to identify interacting partners in vivo

The experimental design should incorporate appropriate controls and replication. For instance, when examining phenotypic effects of gene deletion, isogenic strains differing only in the presence/absence of yjiK should be used, with multiple biological replicates (n≥3) and appropriate statistical analysis of results4.

How can researchers investigate potential interactions between YjiK and ribosomes?

While the search results primarily describe YjeQ interacting with ribosomes rather than YjiK, this provides a methodological framework that could be adapted to investigate potential YjiK-ribosome interactions. The systematic approach would include:

• Co-purification Analysis:

  • Isolate ribosomes from wild-type E. coli using established centrifugation protocols

  • Perform Western blotting with anti-YjiK antibodies to determine if YjiK co-purifies with ribosomes

  • Apply stringency washes (detergent and salt washes) to assess the stability of potential interactions

• Quantitative Co-localization:

  • Determine the cellular copy number of YjiK relative to ribosomes

  • Calculate the stoichiometric ratio of YjiK to ribosomes

  • Assess whether the association is sub-stoichiometric (as seen with YjeQ at a 1:200 ratio)

• In vitro Binding Assays:

  • Express and purify recombinant YjiK

  • Test binding to purified ribosomal subunits (30S, 50S) and complete 70S ribosomes

  • Examine the effects of nucleotides (GTP, GDP, GMP-PNP) on binding affinity

• Ribosomal Activity Influence:

  • Investigate whether YjiK affects ribosomal functions such as translation initiation or elongation

  • Determine if ribosome association stimulates any enzymatic activity of YjiK (if present)

For each experiment, researchers should include appropriate controls (such as testing known ribosome-binding proteins versus non-binding proteins) and perform sufficient biological and technical replicates to ensure statistical validity of results.

What bioinformatic approaches can predict potential functions of the uncharacterized YjiK protein?

Understanding the function of uncharacterized proteins like YjiK requires sophisticated bioinformatic analyses prior to experimental validation. Researchers should implement a comprehensive workflow:

• Sequence-Based Function Prediction:

  • Position-Specific Iterated BLAST (PSI-BLAST) to detect remote homologs

  • Multiple sequence alignment to identify conserved residues

  • Motif scanning using databases like PROSITE, PFAM, and InterPro

  • Transmembrane domain prediction using TMHMM or Phobius (relevant given the hydrophobic N-terminus of YjiK)

• Structural Prediction and Analysis:

  • Secondary structure prediction using methods like PSIPRED

  • Tertiary structure prediction using AlphaFold or RoseTTAFold

  • Structural comparison against known protein structures using DALI or TM-align

  • Active site prediction using tools like CASTp or POOL

• Network-Based Approaches:

  • Gene neighborhood analysis to identify functionally related genes

  • Co-expression network analysis using publicly available transcriptomic data

  • Protein-protein interaction prediction using tools like STRING

• Phylogenetic Profiling:

  • Analysis of the presence/absence pattern of YjiK across bacterial species

  • Correlation with specific metabolic capabilities or environmental adaptations

Table 4: Bioinformatic Tools for YjiK Function Prediction

The computational predictions generated through these approaches should be used to design targeted experimental validation studies, creating a feedback loop between bioinformatic analysis and wet-lab verification.

What controls should be included when designing experiments with recombinant YjiK?

Designing rigorous experiments with recombinant YjiK requires careful consideration of appropriate controls. Researchers should implement the following control framework:

• Expression and Purification Controls:

  • Empty vector control: Cells transformed with expression vector lacking the yjiK gene

  • Known expressible protein control: A well-characterized protein expressed under identical conditions

  • Tag-only control: Expression of the tag portion without the YjiK protein

• Protein Quality Controls:

  • Fresh versus aged protein samples to assess stability over time

  • Heat-denatured YjiK as a negative control for activity assays

  • Biological replicates from independent protein preparations

• Experimental Design Controls:

  • Randomization of samples to minimize systematic errors

  • Blinding of experimenters where applicable to reduce bias

  • Technical replicates (n≥3) for each experimental condition4

• Functional Assay Controls:

  • Positive control: Known protein with activity in the assay system

  • Negative control: Buffer-only or irrelevant protein control

  • Dose-response testing: Serial dilutions of YjiK to establish concentration dependence

When determining the number of replicates, researchers should consider statistical power requirements. While budget and time constraints often limit replication, obtaining as many replicates as practically possible within these constraints is recommended. For critical measurements, preliminary power analysis can determine the minimum number of replicates needed4.

All controls should be processed identically to experimental samples to ensure valid comparisons.

How can researchers troubleshoot issues with YjiK expression and purification?

Troubleshooting recombinant protein expression and purification requires systematic analysis of each step in the process. For YjiK protein, researchers should implement the following troubleshooting framework:

Table 5: Troubleshooting Guide for YjiK Expression and Purification

For each issue, researchers should implement changes systematically, modifying one variable at a time while keeping others constant to identify the specific factors affecting YjiK expression and purification. Documentation of all troubleshooting steps is essential for establishing reproducible protocols.

When encountering expression issues, examining the amino acid sequence for challenging features can be informative. For YjiK, the hydrophobic N-terminal region might suggest membrane association, potentially requiring specialized solubilization methods .

What methods can be used to validate functional predictions for YjiK?

Validating functional predictions for uncharacterized proteins like YjiK requires complementary approaches that provide converging evidence. Researchers should implement the following systematic validation framework:

• Site-Directed Mutagenesis:

  • Identify conserved residues from sequence analysis

  • Create point mutations of these residues

  • Test mutants for altered function in relevant assays

  • Establish structure-function relationships

• Domain Analysis:

  • Express isolated domains predicted by bioinformatics

  • Test each domain for specific activities

  • Create domain deletion constructs to assess functional contributions

• Heterologous Expression and Complementation:

  • Express YjiK in different bacterial species

  • Attempt to complement phenotypes of mutants in related genes

  • Test for restoration of wild-type phenotypes

• Interaction Verification:

  • Confirm predicted protein-protein interactions using multiple methods

  • Apply techniques such as pull-down assays, co-immunoprecipitation, and FRET

  • Determine specificity through competition assays

• Physiological Relevance Testing:

  • Create conditional expression systems

  • Examine phenotypes under various stress conditions

  • Correlate expression levels with physiological responses

The experimental design should follow the basic principles outlined in established methodological literature, including proper randomization, replication, and comparison between experimental and control groups4. For each validation experiment, appropriate positive and negative controls should be included, and multiple biological replicates (n≥3) should be performed to ensure statistical validity.

How should researchers analyze and interpret structural data for YjiK?

Analyzing structural data for an uncharacterized protein like YjiK requires a systematic approach that combines computational analysis with experimental validation. Researchers should implement the following analytical framework:

• Structural Model Quality Assessment:

  • Evaluate Ramachandran plots for backbone geometry

  • Calculate RMSD values for structural alignments

  • Assess model confidence scores (such as pLDDT in AlphaFold models)

  • Validate secondary structure predictions with experimental data (e.g., circular dichroism)

• Comparative Structural Analysis:

  • Perform structural alignment with proteins of known function

  • Identify conserved structural motifs and potential functional sites

  • Calculate structural similarity scores (TM-score, DALI Z-score)

  • Create structure-based phylogenetic trees

• Functional Site Prediction:

  • Identify cavities and pockets using computational tools

  • Map sequence conservation onto structural models

  • Analyze electrostatic surface potential

  • Predict ligand binding sites using tools like FTSite or CASTp

• Experimental Validation Design:

  • Select residues for mutagenesis based on structural analysis

  • Design truncation constructs to test domain functions

  • Plan crosslinking experiments to validate predicted interactions

When interpreting structural data, researchers should maintain awareness of model limitations, particularly for computationally predicted structures. Confidence metrics should be reported alongside structural interpretations, and multiple alternative models should be considered when making functional predictions.

The experimental design for structural validation should include circular dichroism to verify secondary structure content, limited proteolysis to identify domain boundaries, and thermal shift assays to assess stability of wild-type and mutant variants.

How can researchers reconcile conflicting experimental results about YjiK?

Addressing conflicting experimental results is a common challenge in the study of uncharacterized proteins like YjiK. Researchers should implement a systematic approach to reconcile discrepancies:

• Methodological Examination:

  • Compare experimental protocols in detail to identify potential sources of variation

  • Assess reagent quality, purity, and consistency across studies

  • Evaluate statistical approaches and sample sizes for adequate power

  • Consider the effects of different expression systems or tags

• Biological Variability Analysis:

  • Determine if different strains or genetic backgrounds were used

  • Assess growth conditions and their impact on protein function

  • Consider post-translational modifications or processing differences

  • Evaluate the role of potential binding partners present in some assays but not others

• Reconciliation Strategies:

  • Design experiments that directly address contradictions

  • Perform side-by-side comparisons using standardized protocols

  • Develop hypotheses that could explain apparent contradictions

  • Consider whether the protein may have multiple functions depending on context

• Meta-Analysis Approach:

  • Systematically review all available data

  • Weight evidence based on methodological rigor

  • Identify patterns across multiple studies

  • Develop integrated models that accommodate seemingly contradictory results

When designing experiments to resolve conflicts, researchers should apply the principles of randomization, replication, and comparison4. Special attention should be paid to blinding procedures to minimize bias, particularly when attempting to replicate contested findings.

The experimental design should include comprehensive controls and sufficient biological and technical replicates to ensure statistical validity. When reporting results, all methodological details should be explicitly stated to facilitate reproduction by other researchers.

What statistical approaches are appropriate for analyzing experimental data involving YjiK?

• Experimental Design Considerations:

  • Power analysis to determine appropriate sample sizes

  • Randomization of experimental units to minimize bias

  • Blocking designs to control for known sources of variation

  • Factorial designs to efficiently test multiple factors simultaneously

• Descriptive Statistics:

  • Central tendency measures (mean, median) with appropriate dispersion statistics (standard deviation, interquartile range)

  • Graphical representation of data distributions (box plots, violin plots)

  • Correlation analysis for related measurements

• Inferential Statistics:

  • Parametric tests (t-tests, ANOVA) when assumptions of normality and homoscedasticity are met

  • Non-parametric alternatives (Mann-Whitney U, Kruskal-Wallis) when parametric assumptions are violated

  • Multiple comparison corrections (Bonferroni, Benjamini-Hochberg) when performing numerous tests

• Advanced Analytical Approaches:

  • Regression models to identify relationships between variables

  • Principal component analysis for multivariate data reduction

  • Clustering methods to identify patterns in complex datasets

  • Bayesian approaches for incorporating prior knowledge

Table 6: Statistical Test Selection Guide for YjiK Research

When conducting statistical analyses, researchers should be transparent about all data transformations, exclusion criteria, and the specific tests applied. Pre-registration of statistical plans before data collection can help avoid p-hacking and increase the reliability of findings. All statistical analyses should be performed with appropriate software, and the specific packages and versions should be reported.