Recombinant Escherichia coli Uncharacterized protein yeiS (yeiS)

What is the predicted structure and function of E. coli YeiS protein?

YeiS is currently classified as an uncharacterized protein in Escherichia coli. Based on structural prediction models and comparative analysis with similar bacterial proteins, YeiS likely contains specific domain architectures that could indicate its functional role. Similar uncharacterized E. coli proteins, such as YjeQ, have been found to contain specific domain architectures including an N-terminal OB-fold RNA-binding domain, a central GTPase module, and a zinc knuckle-like C-terminal cysteine cluster . Structural analysis through methods like X-ray crystallography, NMR spectroscopy, or cryo-EM would be necessary to definitively determine YeiS structure. Functional prediction may involve analysis of conserved domains, motifs, and sequence homology with characterized proteins across bacterial species.

What expression systems are most efficient for producing recombinant YeiS protein?

For recombinant expression of E. coli proteins like YeiS, several expression systems can be employed with varying efficiency. The most common approach utilizes E. coli-based expression systems with vectors containing inducible promoters (T7, lac, or tac). For optimal expression, a screening of multiple vectors with different promoters, signal peptides, and fusion tags is recommended . Expression conditions including temperature (typically testing 16°C, 25°C, 30°C, and 37°C), induction timing, and inducer concentration should be systematically evaluated. For difficult-to-express proteins, specialized E. coli strains like BL21(DE3), Rosetta, or C41/C43 may improve soluble protein yield. High-throughput screening in multiwell plate formats can efficiently identify optimal expression conditions before scaling up to shake flask or bioreactor production .

What are the recommended purification methods for obtaining high-purity recombinant YeiS?

Purification of recombinant YeiS typically begins with the addition of affinity tags during cloning (His-tag being the most common) . The recommended purification workflow includes:

• Cell lysis using sonication, French press, or enzymatic methods in appropriate buffer systems (typically phosphate or Tris-based buffers with protease inhibitors)

• Initial capture using affinity chromatography (Ni-NTA for His-tagged proteins)

• Intermediate purification via ion exchange chromatography

• Polishing step using size exclusion chromatography

For analytical assessment of purity, SDS-PAGE with Coomassie or silver staining should show >90% purity . Western blotting using anti-His antibodies can confirm identity. Mass spectrometry analysis provides definitive confirmation of protein identity and integrity. Buffer optimization during purification should be conducted to maintain protein stability and prevent aggregation.

How should researchers design experiments to determine the cellular localization of YeiS?

Determining the cellular localization of YeiS requires a multi-method approach:

• Computational prediction: Use algorithms like PSORT, SignalP, or TMHMM to predict potential localization based on sequence features.

• Fluorescent protein fusion: Generate C-terminal or N-terminal GFP/mCherry fusions of YeiS and visualize using confocal microscopy.

• Cell fractionation: Separate E. coli cellular components (cytoplasm, inner membrane, periplasm, outer membrane) through sequential centrifugation and analyze fractions by Western blotting.

• Immunogold electron microscopy: Using antibodies against YeiS or its affinity tag for precise subcellular localization.

Similar periplasmic proteins in E. coli, like YgiS, have been identified as components of transport systems . To confirm periplasmic localization, osmotic shock procedures followed by protein extraction and quantification from different cellular compartments would provide definitive evidence. Controls should include known cytoplasmic, periplasmic, and membrane proteins to validate fractionation quality.

What approaches are recommended for identifying potential interaction partners of YeiS?

To identify potential interaction partners of YeiS, researchers should employ complementary approaches:

Data analysis should include appropriate statistical methods to distinguish specific interactions from background. Validation of identified interactions should be performed using methods like surface plasmon resonance (SPR) or isothermal titration calorimetry (ITC) to determine binding parameters including affinity constants and stoichiometry.

How can researchers assess the effects of yeiS gene knockout on E. coli physiology?

Assessment of yeiS gene knockout effects requires a systematic approach:

• Gene knockout generation: Use CRISPR-Cas9, lambda Red recombineering, or transposon mutagenesis to create ΔyeiS mutants.

• Growth characterization: Compare growth curves under various conditions (different temperatures, pH values, nutrient limitations, stress conditions) between wild-type and ΔyeiS strains.

• Phenotypic microarrays: Screen for metabolic differences using Biolog plates to assess carbon source utilization, chemical sensitivity, and other phenotypes.

• Transcriptomic analysis: Perform RNA-Seq to identify genes differentially expressed in the knockout strain compared to wild-type.

• Metabolomic profiling: Analyze changes in metabolite profiles using LC-MS or GC-MS.

For complementation studies, reintroducing the yeiS gene on a plasmid should restore the wild-type phenotype, confirming that observed effects are specifically due to yeiS deletion rather than polar effects or secondary mutations. Study design should include biological replicates (n≥3) and appropriate statistical analysis (e.g., ANOVA with post-hoc tests) to determine significance of observed differences.

What high-throughput screening methodologies are most effective for optimizing YeiS expression and solubility?

High-throughput screening for optimal YeiS expression and solubility can be implemented through:

• Multiwell plate-based expression: Using 96-well or 24-well formats with varying conditions including:

  • Multiple E. coli strains (BL21, Rosetta, C41/C43, SHuffle)

  • Different promoters and induction systems

  • Range of temperatures (16-37°C)

  • Various fusion tags (His, GST, MBP, SUMO)

  • Buffer compositions and additives

• Automated sampling and analysis: Integration of robotic liquid handling systems with plate readers for OD600 measurements to monitor growth and protein expression levels .

• Fluorescence-based solubility reporters: Fusion of YeiS with GFP variants, where fluorescence intensity correlates with proper folding and solubility.

• Split-GFP complementation assays: For rapid visualization of soluble protein expression without purification.

When scaling up from screening conditions, researchers should be aware that small-scale expression results may not always directly translate to larger production scales due to differences in oxygen transfer, pH maintenance, and nutrient availability . Thus, mid-scale validation (50-100 mL cultures) is recommended before proceeding to production scale. Data analysis should incorporate both expression level and solubility percentage to identify truly optimal conditions.

How can structural biology approaches be applied to determine the three-dimensional structure of YeiS?

Determining the 3D structure of YeiS requires a multi-technique approach:

• X-ray crystallography:

  • Requires high-purity (>95%), homogeneous protein

  • Systematic screening of crystallization conditions (pH, salt, precipitants)

  • Co-crystallization with potential ligands or binding partners

  • Data collection at synchrotron facilities for high-resolution structures

• Cryo-electron microscopy:

  • Particularly valuable for proteins resistant to crystallization

  • Sample vitrification optimization to prevent ice formation

  • Requires advanced image processing for high-resolution reconstruction

• Nuclear Magnetic Resonance (NMR):

  • Suitable for smaller domains (<30 kDa)

  • Requires isotope labeling (15N, 13C) in minimal media

  • Provides dynamic information not available from static techniques

• Integrative structural biology:

  • Combining low-resolution techniques (SAXS, SANS) with computational modeling

  • Homology modeling based on related proteins with known structures

  • Molecular dynamics simulations to understand conformational flexibility

For an uncharacterized protein like YeiS, initial domain prediction and construct optimization are crucial first steps before structural studies. Limited proteolysis experiments can identify stable domains suitable for structural analysis. If similar to YjeQ, which has a unique domain architecture , careful construct design that preserves domain integrity would be essential.

What are the recommended approaches for analyzing the enzymatic activity of YeiS?

Analysis of potential enzymatic activity of YeiS should begin with bioinformatic predictions and follow a systematic experimental workflow:

• Sequence analysis: Search for conserved catalytic motifs and active site residues through multiple sequence alignments with characterized enzymes.

• Activity prediction: Based on related proteins (if YeiS contains domains similar to YjeQ's GTPase domain ), design assays to test predicted activities.

• Substrate screening:

  • For potential GTPase/ATPase activity: Measure phosphate release using malachite green assay

  • For hydrolytic enzymes: Use fluorogenic or chromogenic substrates

  • For transferases: Employ radiolabeled substrates or coupled enzyme assays

• Enzyme kinetics determination:

  • Measure initial rates at varying substrate concentrations

  • Determine kinetic parameters (kcat, Km, kcat/Km)

  • Test effects of pH, temperature, and buffer components on activity

  • Assess potential allosteric regulators or inhibitors

If YeiS shows enzymatic activity similar to YjeQ, both steady state and pre-steady state kinetics should be measured . For steady state measurements, spectrophotometric methods can continuously monitor product formation or substrate depletion. Pre-steady state kinetics using rapid kinetic techniques (stopped-flow or quench-flow) can reveal transient intermediates and rate-limiting steps in the catalytic cycle.

What methods are most effective for determining the physiological role of YeiS in E. coli?

Determining the physiological role of an uncharacterized protein like YeiS requires an integrated approach:

• Comparative genomics:

  • Analyze gene neighborhood conservation across bacterial species

  • Identify co-occurrence patterns with genes of known function

  • Examine evolutionary conservation to assess functional importance

• Transcriptomic profiling:

  • RNA-Seq analysis under various growth conditions to identify conditions where yeiS is differentially expressed

  • Single-cell RNA-Seq to detect potential heterogeneity in expression

  • ChIP-Seq to identify transcription factors regulating yeiS expression

• Growth phenotyping:

  • Compare wild-type and ΔyeiS strains under various stress conditions (temperature, pH, nutrient limitation, antibiotics)

  • High-throughput phenotypic microarrays to identify specific growth conditions affected by yeiS deletion

  • Competition assays to assess fitness effects

• Suppressor mutation analysis:

  • Screen for mutations that suppress phenotypes of yeiS deletion

  • Whole genome sequencing of suppressor strains to identify compensatory pathways

If YeiS functions similarly to other characterized E. coli proteins, such as the deoxycholate-binding periplasmic protein YgiS , specific assays to test transport functions would be appropriate, including monitoring uptake or export of predicted substrates using radioactive or fluorescently labeled compounds.

How can researchers investigate potential roles of YeiS in bacterial stress response?

To investigate YeiS involvement in stress response:

• Expression analysis during stress conditions:

  • qRT-PCR or reporter gene fusions to monitor yeiS expression under various stresses (oxidative, acid, osmotic, antibiotic)

  • Western blotting to quantify YeiS protein levels during stress response

  • Promoter analysis to identify stress-responsive regulatory elements

• Stress sensitivity phenotyping:

  • Compare survival rates of wild-type and ΔyeiS strains exposed to stress conditions

  • Measure growth inhibition zones in disc diffusion assays with various stressors

  • Time-kill curves during stress exposure

• Protein interaction studies under stress:

  • Pull-down assays or co-immunoprecipitation under normal and stress conditions

  • Interactome changes using BioID or APEX proximity labeling during stress

  • Protein localization changes during stress using fluorescent protein fusions

• Multi-omics integration:

  • Combine transcriptomics, proteomics, and metabolomics data to place YeiS in stress response networks

  • Network analysis to identify functional modules where YeiS operates

The experimental design should include appropriate positive controls, such as known stress response genes, and negative controls. If YeiS is involved in bile acid resistance similarly to YgiS , specific assays testing growth in the presence of bile acids or deoxycholate would be particularly informative.

What techniques can be used to study potential involvement of YeiS in bacterial pathogenesis?

To investigate YeiS's potential role in pathogenesis:

• Virulence model systems:

  • Cell culture infection models comparing wild-type and ΔyeiS strains

  • Invasion and adhesion assays with epithelial cell lines

  • Survival within macrophages or other immune cells

  • Animal infection models with appropriate ethical approval

• Host response analysis:

  • Cytokine production measurement following infection

  • Transcriptomics of host cells infected with wild-type vs. ΔyeiS strains

  • Inflammasome activation and pyroptosis assessment

• Virulence factor expression and secretion:

  • Analysis of secretome differences between wild-type and ΔyeiS strains

  • Effects on type III secretion system functioning

  • Biofilm formation capacity assessment

• In vivo expression and importance:

  • In vivo expression technology (IVET) to determine if yeiS is upregulated during infection

  • Transposon sequencing (Tn-Seq) to assess fitness contribution during infection

  • Competitive index determination in mixed infections

If YeiS functions similarly to YgiS in deoxycholate binding , its role in bile resistance during intestinal colonization would be particularly relevant to investigate. Bile acids are important host defense molecules in the gastrointestinal tract, and bacterial mechanisms to resist their effects can be critical virulence determinants.

How can researchers develop site-directed mutagenesis strategies to study structure-function relationships in YeiS?

Developing effective site-directed mutagenesis strategies requires:

• Target residue identification:

  • Sequence conservation analysis across homologs to identify evolutionarily conserved residues

  • Structural modeling to predict functionally important regions

  • Alignment with characterized proteins to identify potential catalytic or binding residues

• Mutagenesis approach selection:

  • QuikChange PCR for single mutations

  • Gibson Assembly for multiple mutations or challenging regions

  • Golden Gate Assembly for systematic mutation libraries

• Rational mutation design:

  • Conservative mutations (similar properties) to test structural importance

  • Non-conservative mutations to disrupt function

  • Alanine scanning of predicted functional regions

  • Cysteine scanning for accessibility and crosslinking studies

• Functional validation pipeline:

  • Expression and solubility testing of mutants

  • Biochemical assays to measure altered activity

  • Binding studies with potential interaction partners

  • In vivo complementation tests in ΔyeiS strains

For proteins with GTPase activity similar to YjeQ , mutations in the G1 motif (such as S-to-A mutations in the P-loop) would be particularly informative to test nucleotide binding and hydrolysis functions. A comprehensive mutagenesis approach would include mutations in predicted catalytic residues, substrate-binding regions, and domain interface residues to understand both function and interdomain communication.

What approaches are most effective for studying the regulation of yeiS gene expression?

To study yeiS gene expression regulation effectively:

• Promoter characterization:

  • 5' RACE to precisely map transcription start sites

  • Reporter gene fusions (lacZ, gfp) with promoter fragments of various lengths

  • ChIP-seq to identify transcription factor binding sites

  • In vitro DNA-protein interaction studies (EMSA, DNase footprinting)

• Transcriptional regulation analysis:

  • RNA-Seq under various conditions to identify expression patterns

  • Quantitative RT-PCR to validate specific expression changes

  • Transcription factor overexpression/deletion effects on yeiS expression

  • Global transcription machinery engineering to identify regulatory dependencies

• Post-transcriptional regulation:

  • mRNA stability measurements through rifampicin chase experiments

  • Identification of potential regulatory small RNAs through co-expression analysis

  • RNA structure probing to identify regulatory elements

  • Translational efficiency assessment using ribosome profiling

• Environmental response characterization:

  • Systematic testing of expression under different conditions (nutrients, temperature, pH, osmolarity)

  • Correlation of expression with specific cellular processes or stress responses

Particular attention should be paid to conditions where related proteins like YgiS or YjeQ show altered expression. The presence of deoxycholate, which affects YgiS expression , might be a relevant condition to test for yeiS regulation as well. Integration of expression data with information about cellular processes affected in ΔyeiS strains can provide insights into the physiological context of gene regulation.

What computational approaches can predict the functional networks involving YeiS in E. coli?

Computational prediction of YeiS functional networks should employ multiple complementary approaches:

• Sequence-based methods:

  • Phylogenetic profiling to identify genes with similar evolutionary patterns

  • Gene neighborhood analysis to find consistently co-located genes

  • Domain fusion analysis to detect functional relationships

  • Protein-protein interaction prediction based on sequence features

• Structure-based approaches:

  • Structural similarity searches to identify proteins with similar folds

  • Protein-protein docking with predicted interaction partners

  • Molecular dynamics simulations to assess dynamic behavior

  • Binding site prediction and comparison with characterized proteins

• Network inference methods:

  • Co-expression network analysis across multiple datasets

  • Bayesian network inference from multi-omics data

  • Text mining of scientific literature for functional associations

  • Metabolic network modeling to predict pathway involvement

• Integrative approaches:

  • Weighted integration of multiple evidence types for function prediction

  • Machine learning models trained on known functional relationships

  • Network clustering to identify functional modules containing YeiS

For validation, predictions should be tested experimentally through targeted approaches such as co-immunoprecipitation, bacterial two-hybrid, or phenotypic analysis of double mutants. If YeiS functions in transport systems similar to YgiS , particular attention should be paid to predicting potential transported substrates and associated components of the transport machinery.