Recombinant Citrobacter koseri UPF0266 membrane protein CKO_01158 (CKO_01158)

What is the Recombinant Citrobacter koseri UPF0266 membrane protein CKO_01158?

Recombinant Citrobacter koseri UPF0266 membrane protein CKO_01158 is a full-length (152 amino acids) membrane protein expressed in the Gram-negative bacterium Citrobacter koseri (strain ATCC BAA-895 / CDC 4225-83 / SGSC4696). The protein is identified by the UniProt accession number A8AFN6 and is classified as a UPF0266 family protein. The complete amino acid sequence is:
MTVTDLVLVLFIVALLAYAIYDQFIMPRRNGPTLLAVPLLRRGRVDSVIFVGLVAILIYN NVTSHGAQITTWLLCALALMGFYIFWVRAPRIIFKQKGFFFANVWIEYNRIKEMNLSEDG VLVMQLEQRRLLIRVRNIDDLERIYKLLVSSQ

This protein is typically produced recombinantly for research purposes, enabling investigation of its structural properties and functional roles in bacterial membrane biology and potentially in pathogenesis.

What storage conditions are optimal for maintaining CKO_01158 protein stability?

For optimal stability of the Recombinant Citrobacter koseri UPF0266 membrane protein CKO_01158, researchers should store the protein at -20°C for regular use, or at -80°C for extended storage periods. The protein is typically supplied in a Tris-based buffer containing 50% glycerol, which has been optimized for this specific protein's stability requirements .

When working with this protein, it's recommended to:

• Avoid repeated freeze-thaw cycles, as these can significantly compromise protein integrity

• Prepare working aliquots that can be stored at 4°C for up to one week

• When thawing frozen samples, do so gradually on ice to prevent protein denaturation

• Consider adding protease inhibitors to prevent degradation during experimental procedures

These storage recommendations are particularly important for membrane proteins, which typically show greater instability compared to soluble proteins due to their hydrophobic domains.

What is the relationship between Citrobacter koseri and microglial activation?

Citrobacter koseri is a Gram-negative bacterium with tropism for brain parenchyma that can cause severe neonatal meningitis, often progressing to establish multifocal brain abscesses. Research has demonstrated that microglia respond to C. koseri with robust expression of proinflammatory molecules .

This response is primarily mediated through TLR4- and MyD88-dependent signaling pathways. When microglia are exposed to either live or heat-killed C. koseri, they produce several proinflammatory mediators, including:

• Nitric oxide (NO)

• Tumor necrosis factor alpha (TNF-α)

• Interleukin 1 beta (IL-1β)

• Chemokine CXCL2 (MIP-2)

• Chemokine CCL2 (MCP-1)

Experimental evidence indicates that C. koseri infection leads to increased CD14 expression in microglia, while MyD88 expression remains relatively stable. CD14 plays a crucial role in transducing activation signals in response to lipopolysaccharide (LPS), a component of the Gram-negative bacterial cell wall .

While the specific role of the UPF0266 membrane protein CKO_01158 in microglial activation has not been fully characterized, understanding the broader context of C. koseri interactions with host cells provides valuable research directions.

How should I design experiments to study CKO_01158 protein function in vitro?

Designing robust experiments to study CKO_01158 protein function requires careful consideration of variables, controls, and experimental treatments. Follow these methodological steps:

• Define your research question and variables

  • Independent variable: CKO_01158 protein (concentration, mutant variants, etc.)

  • Dependent variable: Measured outcome (e.g., binding affinity, cellular response)

  • Control variables: Temperature, pH, buffer composition, etc.

• Develop specific, testable hypotheses

  • Example hypothesis: "Recombinant CKO_01158 protein interacts with host cell TLR4 receptors to trigger inflammatory responses"

• Design experimental treatments

  • Include appropriate controls:

    • Negative control: Buffer only

    • Positive control: Known TLR4 activator (e.g., purified LPS)

    • Experimental groups: Various concentrations of recombinant CKO_01158

• Measurement methodology

  • Select appropriate assays based on your hypothesis:

    • For protein-protein interactions: Co-immunoprecipitation, ELISA, surface plasmon resonance

    • For cell signaling: Western blot for phosphorylated proteins, reporter gene assays

    • For inflammatory responses: Cytokine ELISAs, qPCR for inflammatory gene expression

• Statistical analysis planning

  • Determine sample size through power analysis

  • Select appropriate statistical tests based on data distribution

  • Plan for biological and technical replicates

This systematic approach ensures your experimental design provides valid, reproducible results while controlling for potential confounding factors.

What methodologies can be employed to study interactions between CKO_01158 and host cell receptors?

To investigate potential interactions between Recombinant Citrobacter koseri UPF0266 membrane protein CKO_01158 and host cell receptors such as TLR4, researchers can employ several complementary methodologies:

• Binding assays

  • Surface Plasmon Resonance (SPR): Measures real-time binding kinetics between purified CKO_01158 and immobilized receptors

  • Microscale Thermophoresis (MST): Detects interactions based on changes in thermophoretic mobility

  • ELISA-based binding assays: Quantifies protein-protein interactions through antibody detection systems

• Cell-based functional assays

  • Reporter cell lines: Cells expressing TLR4 and downstream signaling reporters (e.g., NF-κB luciferase)

  • Receptor blocking experiments: Using antibodies against specific domains of TLR4 or co-receptors

  • Knockout/knockdown approaches: Using CRISPR-Cas9 or siRNA to modulate receptor expression

• Structural biology approaches

  • X-ray crystallography of protein complexes

  • Cryo-electron microscopy for visualization of protein-receptor interactions

  • Computational modeling based on amino acid sequence data

• In vivo validation

  • Comparing wild-type and TLR4-deficient mice responses to CKO_01158

  • Using TLR4 mutant models to identify specific interaction domains

For example, to determine if CKO_01158 interacts with TLR4 similar to other bacterial proteins, you might design an experiment comparing inflammatory responses in wild-type vs. TLR4 mutant microglia when exposed to purified CKO_01158, similar to approaches used in previous C. koseri studies .

How can I establish appropriate positive and negative controls for CKO_01158 functional studies?

Establishing appropriate controls is critical for robust experimental design when studying CKO_01158 function. Consider implementing the following control strategy:

Positive Controls:

• Known TLR4 ligands (if studying TLR4 pathway activation):

  • Purified LPS from E. coli or other Gram-negative bacteria

  • Other well-characterized bacterial membrane proteins with established TLR4 activation capacity

• Complete C. koseri lysate:

  • Provides a reference point for comparing isolated protein effects to whole bacteria

• Related proteins from same family:

  • Other characterized UPF0266 family proteins from related bacterial species

Negative Controls:

• Buffer-only treatment:

  • Contains all components of the protein storage buffer without the protein

• Heat-denatured CKO_01158:

  • Same protein preparation but heat-inactivated to destroy tertiary structure

• Unrelated bacterial protein:

  • Recombinant protein from same expression system but unrelated to CKO_01158

• Inhibitor controls:

  • TLR4 pathway inhibitors or blocking antibodies to confirm specificity

  • MyD88 inhibitory peptides to assess signaling pathway dependence

Validation Controls:

• Dose-response relationships:

  • Multiple concentrations of CKO_01158 to establish effect thresholds

• Time-course experiments:

  • Different exposure durations to map temporal dynamics of responses

• Genetic validation:

  • Wild-type versus receptor knockout cell lines

  • siRNA knockdown of suspected interaction partners

This comprehensive control strategy will help distinguish specific CKO_01158 effects from background or non-specific effects, substantially increasing the reliability and interpretability of your experimental results .

What approaches can be used to investigate the structure-function relationship of CKO_01158?

Investigating structure-function relationships of CKO_01158 requires a multidisciplinary approach combining structural biology with functional assays. Consider the following methodological framework:

• Structural characterization approaches

  • X-ray crystallography: Provides atomic-level resolution of protein structure

  • Nuclear Magnetic Resonance (NMR): Useful for examining membrane protein dynamics

  • Cryo-electron microscopy: Particularly valuable for membrane protein complexes

  • Computational modeling: Prediction of structure based on amino acid sequence using tools like AlphaFold

• Domain mapping through mutagenesis

  • Site-directed mutagenesis: Create point mutations at conserved residues

  • Domain deletion/swapping: Generate constructs lacking specific regions

  • Chimeric proteins: Swap domains with related proteins to identify functional regions

  Domain	Amino Acid Position	Predicted Function	Mutagenesis Strategy
  N-terminal	1-30	Membrane anchoring	Alanine scanning
  Central region	31-100	Potential binding domain	Conservative substitutions
  C-terminal	101-152	Signaling	Domain deletion

• Functional validation of mutants

  • Binding assays: Compare wild-type vs. mutant protein binding to potential partners

  • Cell activation assays: Measure inflammatory responses elicited by different constructs

  • Membrane localization studies: Determine if mutations affect proper cellular localization

• Evolutionary analysis

  • Compare sequence conservation across bacterial species

  • Identify highly conserved regions that may indicate functional importance

  • Phylogenetic analysis to understand evolutionary relationships of UPF0266 family proteins

This systematic approach allows for correlating specific structural features with functional outcomes, providing insights into how CKO_01158 may contribute to C. koseri virulence or immune modulation .

How might CKO_01158 contribute to C. koseri pathogenesis in the central nervous system?

While the specific role of CKO_01158 in C. koseri pathogenesis has not been fully elucidated, its investigation can be approached through several research pathways based on what is known about C. koseri infection of the central nervous system:

• Potential roles in microglial activation

  • C. koseri is known to stimulate microglial activation via TLR4-dependent mechanisms, producing proinflammatory mediators including NO, TNF-α, IL-1β, CXCL2, and CCL2

  • Research hypothesis: CKO_01158, as a membrane protein, may serve as a pathogen-associated molecular pattern (PAMP) that interacts with pattern recognition receptors on microglia

• Investigation methodology

  • Compare microglial responses to:

    • Wild-type C. koseri

    • C. koseri with CKO_01158 gene knockout

    • Purified recombinant CKO_01158 protein alone

  • Analyze inflammatory profiles using cytokine arrays, qPCR, and Western blotting

  • Utilize both primary microglia and microglial cell lines for validation

• Brain barrier interaction studies

  • Assess CKO_01158's potential role in blood-brain barrier penetration

  • Use in vitro blood-brain barrier models to study translocation mechanisms

  • Compare brain invasion efficiency between wild-type and CKO_01158-deficient bacteria

• Animal model validation

  • Develop neonatal meningitis models using:

    • Wild-type C. koseri

    • CKO_01158 knockout strains

    • Complemented strains (knockout with restored gene)

  • Measure outcomes including bacterial burden, inflammatory markers, and brain abscess formation

• Immune evasion potential

  • Investigate whether CKO_01158 helps bacteria survive within host cells

  • Conduct gentamicin protection assays with wild-type vs. mutant bacteria

  • Examine intracellular trafficking and phagolysosomal fusion events

This multifaceted approach would help elucidate whether CKO_01158 plays a significant role in the unique neurotropism and pathogenesis of C. koseri infections .

What bioinformatic approaches can reveal insights about CKO_01158 function and potential interaction partners?

Bioinformatic analysis offers powerful tools to predict CKO_01158 function and interaction partners when experimental data is limited. A comprehensive bioinformatic investigation should include:

• Sequence-based analysis

  • Protein family classification: Confirm UPF0266 family membership and identify related proteins

  • Motif identification: Scan for functional domains using PROSITE, PFAM, or InterPro

  • Signal peptide prediction: Determine presence of secretion signals using SignalP

  • Transmembrane domain prediction: Map membrane topology using TMHMM or Phobius

  • Post-translational modification sites: Predict potential glycosylation or phosphorylation sites

• Structural prediction and analysis

  • Secondary structure prediction: Estimate α-helix and β-sheet content

  • Tertiary structure modeling: Generate 3D models using AlphaFold or I-TASSER

  • Structural alignment: Compare with known structures to infer function

  • Molecular docking: Predict interactions with potential binding partners like TLR4

• Genomic context analysis

  • Operonic structure: Examine neighboring genes for functional relationships

  • Synteny analysis: Compare gene organization across related bacterial species

  • Promoter analysis: Identify regulatory elements controlling expression

• Protein-protein interaction prediction

  • Interolog mapping: Predict interactions based on known interactions of homologous proteins

  • Domain-domain interaction prediction: Identify domains likely to mediate protein binding

  • Text mining approaches: Extract potential interactions from scientific literature

• Evolutionary analysis

  • Phylogenetic profiling: Track presence/absence across species to infer function

  • Selection pressure analysis: Calculate dN/dS ratios to identify conserved regions

  • Coevolution analysis: Identify residues that evolve together suggesting functional coupling

These computational approaches provide testable hypotheses about CKO_01158 function that can guide subsequent experimental design and interpretation .

How should I analyze conflicting data regarding CKO_01158 protein function?

When confronted with conflicting data regarding CKO_01158 protein function, employ a systematic approach to resolve inconsistencies:

• Methodological assessment

  • Critically evaluate experimental designs used in conflicting studies

  • Compare protein preparation methods: Expression systems, purification techniques, and storage conditions

  • Assess assay sensitivity and specificity differences between studies

  • Review statistical approaches for appropriate power and analysis methods

• Reconciliation strategies

  • Perform side-by-side comparisons using standardized protocols

  • Develop a consensus experimental framework that incorporates multiple approaches

  • Consider context-dependent functions (e.g., different cellular contexts, concentration-dependent effects)

  • Design experiments specifically to test competing hypotheses

• Statistical approaches for conflicting data

  • Meta-analysis of available data when multiple studies exist

  • Sensitivity analysis to identify variables that might explain discrepancies

  • Bayesian analysis to incorporate prior knowledge and update understanding with new data

• Molecular explanations for conflicts

  • Protein heterogeneity: Post-translational modifications or conformational differences

  • Reagent specificity: Different antibodies or detection methods targeting different epitopes

  • Environmental factors: Buffer conditions, temperature, or pH affecting protein behavior

• Resolution framework

  • Decision matrix mapping conditions where different functions dominate

  • Hierarchical model testing to determine which hypothesis has strongest support

  • Collaborative cross-validation with other research groups

This structured approach transforms seemingly conflicting data into an opportunity for deeper understanding of CKO_01158's complex functional properties and contextual behavior .

What statistical approaches are most appropriate for analyzing dose-dependent effects of CKO_01158 in cellular assays?

For analyzing dose-dependent effects of CKO_01158 in cellular assays, selecting appropriate statistical methods is crucial for valid interpretation:

When reporting results, include both graphical representations of dose-response relationships and comprehensive statistical parameters including p-values, confidence intervals, and effect sizes to ensure interpretability and reproducibility .

How can I integrate proteomics and transcriptomics data to better understand CKO_01158's role in host-pathogen interactions?

Integrating proteomics and transcriptomics data provides a comprehensive systems biology approach to understanding CKO_01158's role in host-pathogen interactions:

• Data generation and preprocessing

  • Experimental design:

    • Compare host responses to wild-type C. koseri vs. CKO_01158 knockout strains

    • Include purified recombinant CKO_01158 treatment condition

    • Collect samples at multiple time points to capture dynamic responses

  • Quality control and normalization:

    • Apply appropriate normalization methods for each data type

    • Filter low-quality or low-abundance measurements

    • Correct for batch effects using methods like ComBat or RUV

• Multi-omics integration strategies

  • Correlation-based approaches:

    • Calculate Pearson or Spearman correlations between transcripts and proteins

    • Identify concordant and discordant responses

  • Pathway enrichment analysis:

    • Apply Gene Set Enrichment Analysis (GSEA) to both datasets

    • Compare enriched pathways to identify common biological processes

  • Network reconstruction:

    • Generate integrated molecular networks using algorithms like WGCNA

    • Identify key network modules and hub genes/proteins

• Advanced integration methods

  • Multivariate statistical approaches:

    • Canonical correlation analysis (CCA)

    • Partial least squares (PLS) regression

    • Multi-omics factor analysis (MOFA)

  • Machine learning integration:

    • Feature selection to identify key predictive variables

    • Classification models to distinguish response patterns

    • Clustering to identify molecular signatures

• Biological interpretation frameworks

  • Temporal analysis:

    • Map gene expression changes to subsequent protein alterations

    • Identify regulatory cascades and feedback mechanisms

  • Causal inference:

    • Use algorithms like IPA or CARNIVAL to infer causal relationships

    • Validate key predictions with targeted experiments

• Validation and hypothesis generation

  • Cross-validation with independent datasets

  • Functional validation of key predicted interactions

  • Development of testable hypotheses about CKO_01158 function

This integrated approach can reveal underlying mechanisms not apparent in single-omics analyses, such as post-transcriptional regulation, protein-protein interactions, and pathway crosstalk involved in host responses to CKO_01158 .

How can CKO_01158 research contribute to understanding bacterial meningitis pathogenesis?

Research on CKO_01158 can significantly advance our understanding of bacterial meningitis pathogenesis, particularly in the context of Citrobacter koseri infections, through several research applications:

• Mechanistic insights into neurotropism

  • C. koseri has a unique tropism for brain parenchyma, often leading to brain abscesses

  • Investigating whether CKO_01158 contributes to this neurotropism could reveal:

    • Novel mechanisms of blood-brain barrier penetration

    • Interactions with specific neural cell types

    • Potential roles in bacterial survival within CNS microenvironments

• Inflammatory response modulation

  • C. koseri triggers microglial activation through TLR4 and MyD88-dependent pathways

  • Determining if CKO_01158 specifically interacts with these pathways could reveal:

    • Targetable mechanisms of neuroinflammation

    • Specific inflammatory signatures associated with poor outcomes

    • Potential immunomodulatory approaches for treatment

• Comparative pathogenesis studies

  • Comparing CKO_01158 with homologous proteins in other meningitis-causing bacteria

  • Identifying conserved vs. species-specific mechanisms

  • Understanding evolutionary adaptations for CNS infection

• Translational applications

  • Development of biomarkers for early diagnosis

  • Identification of novel therapeutic targets

  • Design of immunomodulatory interventions to limit inflammatory damage

• Experimental model development

  • Creation of CKO_01158 mutant strains for in vivo studies

  • Development of specialized in vitro models that recapitulate key aspects of meningitis

  • Tools for monitoring protein expression and localization during infection

This research direction is particularly valuable given the high morbidity associated with neonatal meningitis caused by C. koseri and the current limitations in treatment options for established brain abscesses .

What is the potential role of CKO_01158 in developing novel diagnostic or therapeutic approaches for C. koseri infections?

The study of CKO_01158 offers several promising avenues for developing novel diagnostic and therapeutic approaches for C. koseri infections:

• Diagnostic applications

  • Biomarker development:

    • Detection of CKO_01158 protein or antibodies against it in patient samples

    • Development of rapid immunoassays targeting CKO_01158 epitopes

    • Multiplexed biomarker panels incorporating CKO_01158 detection

  • Molecular diagnostics:

    • PCR-based detection of the CKO_01158 gene in clinical isolates

    • CRISPR-Cas diagnostic systems targeting the gene sequence

    • Next-generation sequencing approaches for variant identification

• Therapeutic strategies

  • Vaccine development:

    • Evaluation of CKO_01158 as a vaccine antigen

    • Design of recombinant subunit vaccines incorporating key epitopes

    • Development of conjugate vaccines linking CKO_01158 to carrier proteins

  • Immunotherapeutic approaches:

    • Monoclonal antibodies targeting CKO_01158 surface epitopes

    • Passive immunization strategies for high-risk neonates

    • Immunomodulatory interventions targeting downstream pathways

• Drug development targets

  • Structure-based drug design:

    • Identification of small molecule inhibitors of CKO_01158 function

    • Development of peptidomimetics that interfere with protein-protein interactions

    • Computer-aided drug design utilizing the protein's 3D structure

  • Combination approaches:

    • CKO_01158 inhibitors combined with conventional antibiotics

    • Multi-target strategies addressing virulence and survival mechanisms

• Implementation research

  • Point-of-care testing validation in clinical settings

  • Cost-effectiveness analysis of new diagnostic approaches

  • Clinical trial design for therapeutic interventions

The development of these applications requires a comprehensive understanding of CKO_01158's structure, function, and role in pathogenesis, underscoring the importance of basic research as a foundation for translational advances .

How can researchers effectively collaborate on interdisciplinary projects focusing on CKO_01158?

Effective interdisciplinary collaboration on CKO_01158 research requires structured approaches to bridge diverse expertise and methodologies:

• Building collaborative frameworks

  • Assemble complementary expertise:

    • Microbiologists for bacterial characterization

    • Structural biologists for protein analysis

    • Immunologists for host response studies

    • Clinicians for translational perspectives

    • Bioinformaticians for data integration and analysis

  • Establish clear research objectives:

    • Develop a shared research agenda with defined milestones

    • Create a common terminology glossary to bridge disciplinary language barriers

    • Design experiments that integrate multiple perspectives

• Research methodology integration

  • Cross-disciplinary experimental design:

    • Ensure protocols are compatible across research groups

    • Standardize key methodologies for consistency

    • Implement quality control measures across laboratories

  • Shared resources development:

    • Central repository for reagents (antibodies, recombinant proteins)

    • Common cell lines and bacterial strains

    • Standardized assay systems for cross-validation

• Data management and analysis

  • Integrated data infrastructure:

    • Implement FAIR (Findable, Accessible, Interoperable, Reusable) data principles

    • Develop shared databases with consistent metadata

    • Establish data sharing agreements early in collaboration

  • Analytical pipeline integration:

    • Create workflows that connect diverse data types

    • Develop visualization tools accessible to all team members

    • Implement regular data review sessions across disciplines

• Communication strategies

  • Regular structured interactions:

    • Weekly virtual meetings for project updates

    • Quarterly in-person workshops for intensive collaboration

    • Annual retreats for strategic planning

  • Knowledge translation mechanisms:

    • Discipline-specific summaries of key findings

    • Cross-training opportunities between laboratories

    • Collaborative publication strategy with rotating first/last authorship

• Evaluation and iteration

  • Progress assessment:

    • Regular review of milestones against project timeline

    • Identification of knowledge gaps requiring additional expertise

    • Adjustment of research direction based on emerging findings

  • Impact measurement:

    • Track collaborative outputs (publications, grants, patents)

    • Assess translation of findings to clinical applications

    • Document new methodologies developed through collaboration

Successful interdisciplinary collaboration transforms CKO_01158 research from isolated investigations into a comprehensive understanding of this protein's role in bacterial physiology and pathogenesis, accelerating both basic science discoveries and translational applications .