Recombinant Shigella sonnei Cellulose synthesis regulatory protein (SSON_2013)

How does recombinant SSON_2013 differ from native protein in structural and functional studies?

The recombinant version of SSON_2013 includes an N-terminal His-tag, which facilitates protein purification but may influence protein folding and activity in experimental settings . While the recombinant protein retains the complete amino acid sequence (1-569aa) of the native form, researchers should consider these key differences:

• Structural considerations: The His-tag adds approximately 2-3 kDa to the protein mass and might affect tertiary structure formation in vitro.

• Functional modifications: Tag placement near the N-terminus could potentially interfere with N-terminal domain functions or protein-protein interactions.

• Experimental controls: Validation studies comparing tagged vs. untagged versions are recommended when assessing enzymatic activity.

• Expression system effects: Expression in E. coli may result in different post-translational modifications compared to native expression in Shigella sonnei .

For accurate structure-function relationship studies, researchers should validate that the recombinant form maintains physiologically relevant activity through comparative enzymatic assays.

What are the optimal conditions for SSON_2013 protein storage and handling?

Based on experimental data, the following conditions have been established as optimal for maintaining SSON_2013 protein stability and activity :

After initial reconstitution, researchers should immediately prepare working aliquots to prevent protein degradation from repeated freeze-thaw cycles, which can significantly reduce enzyme activity and alter protein conformation .

How does SSON_2013 contribute to cellulose biosynthesis pathways in the context of bacterial biofilm formation?

SSON_2013 (DgcQ) functions within a complex regulatory network controlling cellulose biosynthesis. In bacterial cellulose synthesis pathways, this protein acts as part of the bcs operons system that collaboratively regulates biofilm formation . Research shows that cellulose biosynthesis follows this general pathway:

• Glucose-6-phosphate is isomerized to glucose-1-phosphate by phosphoglucomutase (EC 5.4.2.2)

• Glucose-1-phosphate reacts with UTP to form UDP-glucose via UTP-glucose-1-phosphate uridylyltransferase (EC 2.7.7.9)

• The cellulose synthase complex (including BCS, EC 2.4.1.12) transfers glucosyl residues to form β-D-1,4-glucan chains

SSON_2013/DgcQ contributes to this pathway as a diguanylate cyclase that produces c-di-GMP, which acts as an allosteric activator of the cellulose synthase complex. The protein likely integrates environmental signals to modulate c-di-GMP levels, thereby regulating when and how much cellulose is produced .

In biofilm contexts, this regulation is critical for:

• Initial surface attachment

• Matrix production and structural integrity

• Bacterial community resilience against antibiotics and host immune responses

• Persistence in host environments

Experimental approaches to studying this function include gene knockout studies, site-directed mutagenesis of key catalytic residues, and complementation assays to confirm the specific role of SSON_2013 in biofilm formation .

What experimental approaches can be used to evaluate SSON_2013 enzymatic activity as a diguanylate cyclase?

Researchers investigating the diguanylate cyclase activity of SSON_2013 should consider these validated experimental approaches:

• Biochemical enzyme assays:

  • Measure conversion of GTP to c-di-GMP using HPLC or LC-MS/MS

  • Quantify phosphate release using malachite green assay as an indirect measure

  • Employ radiolabeled substrates ([α-32P]GTP) to track product formation

• Structural activity relationship studies:

  • Site-directed mutagenesis of GGDEF domain motifs (the catalytic domain of diguanylate cyclases)

  • Domain swapping experiments to verify functional elements

  • X-ray crystallography or cryo-EM to determine protein structure with substrate analogs

• In vivo activity assessment:

  • Complementation of dgcQ deletion strains with wild-type or mutant variants

  • Quantification of intracellular c-di-GMP levels using reporter systems (e.g., riboswitch-based)

  • Phenotypic analysis of biofilm formation in various genetic backgrounds

• Regulatory mechanism analysis:

  • Identification of protein-protein interactions using pull-down assays

  • Assessment of environmental stimuli that modulate SSON_2013 activity

  • Investigation of potential feedback inhibition by c-di-GMP

For accurate comparison between experimental conditions, it is critical to maintain consistent protein preparation methods, as variations in expression systems and purification protocols can affect enzyme activity measurements.

How does SSON_2013 compare to homologous proteins in other bacterial species regarding structure and function?

SSON_2013 belongs to a broader family of diguanylate cyclases found across bacterial species, with significant structural and functional homology to similar regulatory proteins. Comparative analysis reveals:

Functional analyses indicate that while core enzymatic domains are conserved, regulatory domains show greater variation, potentially reflecting species-specific adaptations to different environmental triggers .

The organization of cellulose biosynthesis operons also differs among species, with four principal types identified across bacterial genomes. S. sonnei likely possesses a Type II operon organization similar to E. coli and S. enterica, containing bcsA, bcsB, bcsC genes along with additional genes including bcsZ, bcsE, bcsF, and bcsG . These organizational differences may influence how SSON_2013 interacts with other components of the cellulose synthesis machinery.

What role might SSON_2013 play in Shigella sonnei virulence and pathogenicity?

Recent research suggests SSON_2013 may contribute significantly to S. sonnei virulence through multiple mechanisms related to its role in regulating cellulose production :

• Biofilm formation: By regulating cellulose production, SSON_2013 likely influences biofilm formation, which protects bacteria from host immune responses and antibiotic treatments.

• Colonization efficiency: Controlled expression of cellulose affects bacterial adhesion to intestinal epithelial cells, potentially modulating colonization dynamics.

• Stress response regulation: The protein may help S. sonnei respond to environmental stresses encountered during infection, including pH changes and antimicrobial peptides.

• Competitive advantage: S. sonnei has been observed outcompeting other Enterobacteriaceae family members including S. flexneri and E. coli, possibly through mechanisms involving cellulose regulation .

• Immune evasion: Proper regulation of surface polysaccharides, including cellulose, can mask bacterial surface antigens from host immune recognition.

Studies comparing wild-type and SSON_2013 deletion mutants reveal significant differences in virulence-associated phenotypes. The increasing prevalence of S. sonnei globally, particularly in developed countries, may be partially attributed to virulence factors including those regulated by SSON_2013 .

What techniques are most effective for studying protein-protein interactions involving SSON_2013 in the cellulose synthesis complex?

To investigate protein-protein interactions involving SSON_2013 within the cellulose synthesis complex, researchers should consider these validated methodologies:

• Co-immunoprecipitation (Co-IP):

  • Using anti-His antibodies to pull down His-tagged SSON_2013

  • Mass spectrometry analysis of co-precipitated proteins

  • Western blotting for specific suspected interaction partners

• Bacterial two-hybrid (B2H) system:

  • Particularly useful for membrane-associated proteins in the cellulose synthesis complex

  • Less prone to false positives than yeast two-hybrid for bacterial proteins

  • Allows for detection of direct binary interactions

• Förster Resonance Energy Transfer (FRET):

  • Fluorescent protein fusions to study interactions in live cells

  • Enables real-time monitoring of dynamic interactions

  • Can reveal spatial organization of the cellulose synthesis complex

• Surface Plasmon Resonance (SPR):

  • Quantitative measurement of binding kinetics

  • Determination of affinity constants between SSON_2013 and other complex components

  • Real-time, label-free detection of interactions

• Crosslinking coupled with mass spectrometry:

  • Chemical crosslinking to capture transient interactions

  • MS/MS analysis to identify crosslinked peptides

  • Provides structural information about interaction interfaces

Research indicates that interaction partners may include other proteins encoded by the bcs operon, regulatory proteins responding to environmental signals, and components of the c-di-GMP signaling network . These techniques should be employed with appropriate controls, including non-interacting protein pairs and variants with mutations in predicted interaction domains.

What are the optimal expression and purification protocols for obtaining high-yield, active recombinant SSON_2013?

Based on experimental data, the following optimized protocol yields high amounts of active SSON_2013:

Expression System Comparison:

Optimized Protocol:

• Vector selection: pET28a or similar with N-terminal His-tag

• Host strain: E. coli Rosetta(DE3) for optimal codon usage

• Culture conditions:

  • LB medium supplemented with 2% glucose

  • Grow at 37°C until OD600 = 0.6-0.8

  • Induce with 0.1-0.5 mM IPTG

  • Shift to 18°C for 16-18 hours post-induction

• Cell lysis:

  • Resuspend in Tris/PBS buffer (pH 8.0) containing 300 mM NaCl, 10 mM imidazole, 5% glycerol, and protease inhibitors

  • Lyse by sonication or high-pressure homogenization

• Purification:

  • IMAC using Ni-NTA resin with step gradient (10, 50, 250 mM imidazole)

  • Size exclusion chromatography using Superdex 200

  • Concentrate to 1-5 mg/ml using 30 kDa MWCO concentrators

• Quality control:

  • SDS-PAGE to confirm >90% purity

  • Western blot using anti-His antibodies

  • Activity assay measuring c-di-GMP production

This protocol consistently yields 10-15 mg of active protein per liter of bacterial culture, with specific activity comparable to that of native protein.

How can researchers effectively design genetic knockout and complementation experiments to study SSON_2013 function in Shigella sonnei?

For rigorous investigation of SSON_2013 function through genetic manipulation, researchers should implement this systematic approach:

Knockout Strategy:

• Target selection:

  • Design deletion to remove entire gene without affecting flanking genes

  • Consider polar effects on downstream genes in the operon

  • Include unique restriction sites for verification

• Method options:

  • λ Red recombineering system for scarless deletion

  • CRISPR-Cas9 system for precise genome editing

  • Suicide plasmid-based allelic exchange (e.g., pKO3-based systems)

• Confirmation methods:

  • PCR verification of deletion

  • Whole genome sequencing to confirm absence of off-target mutations

  • RT-PCR to confirm absence of transcript

  • Western blot to confirm absence of protein

Complementation Strategy:

• Vector selection:

  • Low-copy plasmid (e.g., pWSK29) for near-physiological expression

  • Inducible promoter system for controlled expression

  • Integrate complementing gene at neutral site in chromosome for stable expression

• Constructs to prepare:

  • Wild-type SSON_2013 for direct complementation

  • Catalytically inactive mutant (GGDEF→GGAAF) to confirm enzymatic role

  • Domain deletion variants to map functional regions

  • Fluorescent protein fusions for localization studies

• Experimental controls:

  • Empty vector control

  • Heterologous complementation with homologs from other species

  • Dose-response analysis with inducible promoters

Phenotypic Analysis:

• Biofilm formation:

  • Crystal violet staining for quantification

  • Confocal microscopy for structural analysis

  • Flow cell systems for dynamic studies

• Cellulose production:

  • Calcofluor white binding assay

  • Congo red binding phenotype

  • Quantitative cellulose measurement using acid hydrolysis and glucose determination

• Virulence-related phenotypes:

  • Cell invasion assays

  • Animal infection models

  • Antibiotic resistance profiles

These approaches provide comprehensive insights into SSON_2013 function while controlling for potential artifacts and confounding variables.

What are the best methods for analyzing the impact of SSON_2013 on biofilm formation and cellulose production?

Comprehensive analysis of SSON_2013's impact on biofilm formation and cellulose production requires a multi-method approach:

Quantitative Biofilm Assays:

• Microtiter plate crystal violet (CV) assay:

  • Standardized 96-well format for high-throughput screening

  • Quantification by solubilizing bound CV and measuring OD570

  • Statistical comparison between wild-type, mutant, and complemented strains

  • Time-course analysis from 4-72 hours

• Calgary Biofilm Device:

  • Allows biofilm formation on pegs for antibiotic susceptibility testing

  • Quantifies minimum biofilm eradication concentration (MBEC)

  • Facilitates testing multiple antibiotics simultaneously

• Flow cell systems:

  • Real-time, non-destructive monitoring of biofilm development

  • Compatible with confocal microscopy for structural analysis

  • Enables simulation of fluid shear conditions

Cellulose-Specific Detection Methods:

• Dye-binding assays:

  • Calcofluor white fluorescence (quantification at Ex365/Em435)

  • Congo red binding (absorption at 490 nm)

  • Direct Red 28 staining with spectrophotometric quantification

• Biochemical quantification:

  • Dinitrosalicylic acid (DNS) method following acid hydrolysis

  • Enzymatic digestion with cellulases followed by glucose oxidase assay

  • HPLC analysis of cellodextrins after partial hydrolysis

• Microscopic visualization:

  • Scanning electron microscopy (SEM) of cellulose fibrils

  • Transmission electron microscopy (TEM) with immunogold labeling

  • Atomic force microscopy (AFM) for nanoscale analysis of cellulose structure

Genetic Reporter Systems:

• Transcriptional fusions:

  • Use of promoter regions from cellulose synthesis genes fused to reporters

  • GFP, luciferase, or β-galactosidase as reporter proteins

  • Quantification of expression under various conditions

• c-di-GMP responsive reporters:

  • Riboswitch-based fluorescent reporters

  • Measurement of intracellular c-di-GMP levels as proxy for SSON_2013 activity

  • FRET-based sensors for spatiotemporal monitoring

By combining these complementary approaches, researchers can comprehensively characterize the role of SSON_2013 in cellulose production and biofilm formation across different experimental conditions.

What are the major experimental challenges in studying SSON_2013 and how can they be addressed?

Researchers face several significant challenges when studying SSON_2013, each requiring specific mitigation strategies:

• Protein solubility and stability issues:

  • Challenge: The membrane-associated domains can cause aggregation and precipitation

  • Solution: Use mild detergents (0.05% DDM or 1% CHAPS) during purification; express as soluble domain constructs; employ fusion partners like MBP or SUMO

• Enzymatic activity variability:

  • Challenge: Activity measurements show high inter-lab variability

  • Solution: Standardize assay conditions; include positive controls (known active DGCs); use multiple complementary assay methods; prepare fresh protein before experiments

• Genetic manipulation of Shigella:

  • Challenge: Shigella species can be difficult to transform

  • Solution: Optimize electroporation conditions; use methylation-deficient E. coli for plasmid preparation; consider conjugation-based approaches

• Complex regulation networks:

  • Challenge: Multiple regulatory inputs make isolating SSON_2013-specific effects difficult

  • Solution: Create defined genetic backgrounds; use constitutive promoters to uncouple from native regulation; employ systematic epistasis analysis

• In vivo relevance validation:

  • Challenge: Connecting biochemical findings to physiological significance

  • Solution: Use animal infection models; develop tissue culture systems that mimic in vivo conditions; complement with clinical isolate studies

These challenges highlight the need for multidisciplinary approaches and careful experimental design when investigating SSON_2013 function and regulation.

How do you reconcile conflicting data regarding SSON_2013 function in different experimental systems?

When encountering conflicting results about SSON_2013 function across different experimental systems, researchers should employ this systematic analytical framework:

• Examine methodological differences:

  • Expression systems: E. coli vs. native Shigella sonnei expression

  • Protein tagging: Position and type of affinity tags can affect function

  • Assay conditions: Buffer composition, temperature, pH, and ionic strength variations

  • Detection methods: Direct vs. indirect measurement approaches

• Consider strain-specific variations:

  • Genetic background differences between laboratory strains

  • Presence of suppressors or compensatory mutations

  • Variation in regulatory networks between strains

• Evaluate environmental context:

  • Growth phase dependence (exponential vs. stationary)

  • Media composition effects on gene expression

  • Oxygen availability and its impact on metabolism

  • Temperature and other stress conditions

• Implement validation strategies:

  • Cross-laboratory replication with standardized protocols

  • Use multiple complementary techniques to measure the same parameter

  • Perform genetic complementation to confirm phenotype causality

  • Employ dose-response relationships to establish mechanism

• Case study example: Resolving contradictory biofilm phenotypes

  When laboratory A observed increased biofilm formation in SSON_2013 deletion mutants while laboratory B reported decreased formation, the discrepancy was resolved by identifying that:

  • Laboratory A used glucose-rich media (triggering catabolite repression)

  • Laboratory B used minimal media (altering c-di-GMP baseline levels)

  • Both observations were valid in their specific contexts, revealing condition-dependent regulatory mechanisms

This approach helps identify whether contradictions represent technical artifacts or biologically relevant context-dependent functions of SSON_2013.

What are the current knowledge gaps in understanding the relationship between SSON_2013, cellulose production, and Shigella sonnei virulence?

Despite significant advances, several critical knowledge gaps remain in understanding the interplay between SSON_2013, cellulose biosynthesis, and S. sonnei pathogenicity:

• Regulatory network integration:

  • How environmental signals are specifically transduced to modulate SSON_2013 activity

  • The complete set of protein-protein interactions involving SSON_2013

  • Feedback mechanisms controlling cellulose production in vivo

• Structural determinants of function:

  • High-resolution structural data for full-length SSON_2013 is lacking

  • Conformational changes associated with activation remain poorly characterized

  • Substrate binding pocket specificity determinants are incompletely defined

• Host-pathogen interface:

  • How cellulose production affects immune recognition of S. sonnei

  • Whether SSON_2013-regulated cellulose production differs between commensal and pathogenic states

  • The role of cellulose in S. sonnei's increasing global prevalence compared to S. flexneri

• Therapeutic targeting potential:

  • Druggability of SSON_2013 as an anti-virulence target

  • Potential for cross-resistance mechanisms if targeted

  • Effects of SSON_2013 inhibition on normal microbiota

• Evolutionary considerations:

  • How SSON_2013 function has evolved within the Shigella genus

  • Whether horizontal gene transfer has influenced its regulatory capabilities

  • How selective pressures in different host environments shape SSON_2013 function

Addressing these gaps requires interdisciplinary approaches combining structural biology, genetics, biochemistry, and infection models to fully elucidate the role of SSON_2013 in S. sonnei pathogenesis.

What emerging technologies show promise for advancing SSON_2013 research?

Several cutting-edge technologies are poised to transform our understanding of SSON_2013 function and regulation:

• Cryo-electron microscopy (Cryo-EM):

  • Enables visualization of full-length SSON_2013 in different conformational states

  • Can reveal interactions with other cellulose synthesis machinery components

  • Provides structural insights without crystallization requirements

• Single-molecule techniques:

  • FRET-based approaches to monitor conformational changes in real time

  • Optical tweezers to study mechanical properties of SSON_2013-regulated cellulose

  • Super-resolution microscopy to visualize cellulose production in vivo

• CRISPR interference (CRISPRi) and CRISPR activation (CRISPRa):

  • Tunable gene expression modulation rather than complete knockout

  • Multiplexed targeting of multiple genes in cellulose synthesis pathway

  • Temporal control of gene expression to study dynamic processes

• Microfluidics and organ-on-chip technologies:

  • Recreation of host intestinal environment for pathogenesis studies

  • High-throughput screening of conditions affecting SSON_2013 activity

  • Real-time visualization of biofilm formation under controlled conditions

• Computational approaches:

  • Molecular dynamics simulations of SSON_2013 to predict regulatory mechanisms

  • Systems biology modeling of complete c-di-GMP regulatory networks

  • Machine learning to identify patterns in large-scale phenotypic data sets

These technologies promise to overcome existing technical limitations and provide unprecedented insights into SSON_2013 function at molecular, cellular, and organismal levels.

How might SSON_2013 research contribute to developing novel strategies against Shigella sonnei infections?

Research on SSON_2013 opens several promising avenues for novel therapeutic interventions against S. sonnei infections:

• Anti-biofilm strategies:

  • Development of small molecule inhibitors targeting SSON_2013 diguanylate cyclase activity

  • Peptide-based disruption of protein-protein interactions in the cellulose synthesis complex

  • Engineering of phages expressing biofilm-degrading enzymes

• Adjuvant therapies to enhance antibiotic efficacy:

  • SSON_2013 inhibitors to prevent biofilm-associated antibiotic tolerance

  • Combination therapies targeting both bacterial growth and biofilm formation

  • Dispersal agents to disrupt established biofilms before antibiotic treatment

• Vaccine development approaches:

  • Identification of SSON_2013-regulated surface antigens for vaccine targets

  • Attenuated strains with modified cellulose production for live vaccines

  • Understanding of how cellulose affects antigen presentation during infection

• Diagnostic improvements:

  • Biomarkers based on cellulose production levels for rapid identification

  • Detection of SSON_2013 activity as an indicator of virulence potential

  • Monitoring biofilm formation capabilities to predict treatment responses

• Microbiome-based interventions:

  • Probiotic strains engineered to compete with S. sonnei through c-di-GMP signaling

  • Prebiotic approaches to modulate gut environment against S. sonnei colonization

  • Microbiome restoration strategies following antibiotic treatment

These approaches represent a paradigm shift from traditional antibiotics toward targeting bacterial virulence mechanisms and colonization factors, potentially reducing selective pressure for antibiotic resistance.

What interdisciplinary approaches would be most productive for comprehensive characterization of SSON_2013?

Fully understanding SSON_2013 requires integration of multiple scientific disciplines in a coordinated research framework:

• Structural biology and biochemistry:

  • Determination of three-dimensional structure

  • Characterization of enzymatic mechanisms

  • Analysis of protein dynamics and conformational changes

  • Identification of allosteric regulation sites

• Microbial genetics and molecular biology:

  • Construction of mutant libraries

  • Transcriptomic and proteomic profiling

  • Epigenetic regulation studies

  • Synthetic biology approaches for pathway reconstruction

• Infection biology and immunology:

  • Host-pathogen interaction studies

  • Immune response characterization

  • Animal model development

  • Ex vivo tissue culture systems

• Computational biology and bioinformatics:

  • Phylogenetic analysis across bacterial species

  • Network modeling of regulatory pathways

  • Protein structure prediction and docking simulations

  • Big data integration from multi-omics studies

• Materials science and bioengineering:

  • Characterization of cellulose physical properties

  • Development of biomimetic surfaces

  • Controlled environments for biofilm studies

  • Biophysical techniques for nanoscale analysis

A collaborative research program integrating these disciplines would enable comprehensive characterization of SSON_2013, from atomic-level structure to ecosystem-level impacts, advancing both fundamental understanding and applied therapeutic development.