Recombinant Idiomarina loihiensis UPF0042 nucleotide-binding protein IL0393 (IL0393)

What is the taxonomic classification of Idiomarina loihiensis and what environments does it inhabit?

Idiomarina loihiensis is a halophilic gamma-Proteobacterium originally isolated from hydrothermal vents on the Lō'ihi Seamount, Hawai'i. It shares 99.9% 16S rRNA gene sequence similarity with an uncultured eubacterium from sediment at a depth of 11,000 m in the Mariana Trench, suggesting related organisms may be widely distributed in deep-sea environments . Its nearest cultivated neighbor is Idiomarina abyssalis KMM 227(T), with which it shares 98.9% 16S rRNA sequence similarity .

The organism exhibits remarkable adaptability to extreme conditions, capable of growing at temperatures up to 46°C and in media containing up to 20% (w/v) NaCl . Cells of I. loihiensis are Gram-negative rods, 0.35 μm wide and 0.7-1.0 μm long, occasionally extending to 1.8 μm in length. They are motile via a single polar or subpolar flagellum, and the major fatty acid identified is iso-C15 .

What is the predicted structure and function of UPF0042 nucleotide-binding proteins?

UPF0042 (Uncharacterized Protein Family 0042) nucleotide-binding proteins are characterized by conserved domains typically involved in nucleotide interactions. While specific structural information for IL0393 is not directly provided in the search results, proteins in this family generally contain nucleotide-binding motifs that interact with various nucleotides including ATP, GTP, or other nucleotides.

The structure likely includes:

• A conserved nucleotide-binding pocket

• Potential regulatory domains that may change conformation upon nucleotide binding

• Structural adaptations reflecting the halophilic nature of the source organism

Function prediction requires experimental validation, but potential roles may include:

• Involvement in stress response mechanisms

• Participation in nucleotide metabolism or signaling pathways

• Environmental sensing in extreme conditions

What expression systems are suitable for producing recombinant IL0393?

When selecting an expression system for IL0393, researchers should consider the halophilic origin of the protein and its potential structural requirements. The following table outlines appropriate expression systems and their considerations:

For optimal results with E. coli systems, construct design should include:

• N-terminal affinity tags (His6, GST, or MBP) to aid solubility and purification

• Inducible promoter systems with fine control (T7 or tac)

• Codon optimization for improved expression efficiency

What are the optimal conditions for expressing soluble recombinant IL0393?

Optimizing expression conditions is crucial for obtaining functional IL0393 protein. The following methodological approach is recommended based on experience with halophilic proteins:

Expression Optimization Protocol:

• Vector construction:

  • Clone IL0393 into pET28a, pGEX-6P-1, and pMAL-c2X vectors

  • Create constructs with removable affinity tags

• Transformation and starter culture:

  • Transform expression vectors into E. coli BL21(DE3) and Rosetta 2(DE3)

  • Prepare starter cultures in LB medium with appropriate antibiotics

  • Incubate overnight at 37°C with shaking at 200 rpm

• Expression culture optimization:

  • Test multiple media formulations (LB, TB, 2xYT, M9 minimal)

  • Inoculate expression media with 1:100 dilution of starter culture

  • Grow at 37°C to OD600 of 0.6-0.8

• Induction parameter testing:

  • Test IPTG concentrations: 0.1 mM, 0.5 mM, and 1.0 mM

  • Test induction temperatures: 16°C, 25°C, and 37°C

  • Vary induction times: 4 hours, overnight, and 24 hours

Expression Optimization Results Table (Hypothetical Yield Data):

Based on these hypothetical findings, the optimal expression condition would be Rosetta 2(DE3), 16°C, 0.1 mM IPTG for 24 hours, offering the best balance of yield and functional protein.

What purification strategy ensures high yield and purity of functional IL0393?

A multi-step purification strategy is recommended to obtain high-purity, functional IL0393 protein:

Complete Purification Protocol:

• Cell lysis:

  • Resuspend cell pellet in lysis buffer (50 mM Tris-HCl pH 8.0, 300 mM NaCl, 10% glycerol, 1 mM DTT, 1 mM PMSF, protease inhibitor cocktail)

  • Lyse cells by sonication (6 cycles of 30s on/30s off) or using a cell disruptor

  • Clarify lysate by centrifugation at 20,000 × g for 30 minutes at 4°C

• Affinity chromatography:

  • Load clarified lysate onto appropriate affinity resin (Ni-NTA for His-tagged constructs)

  • Wash with 10-20 column volumes of wash buffer (lysis buffer + 20 mM imidazole)

  • Elute with elution buffer (lysis buffer + 250 mM imidazole)

• Tag removal (optional):

  • Add TEV protease (1:50 ratio to target protein)

  • Dialyze overnight against 50 mM Tris-HCl pH 8.0, 150 mM NaCl, 1 mM DTT

  • Remove cleaved tag and protease by reverse affinity chromatography

• Ion exchange chromatography:

  • Dialyze against low salt buffer (50 mM Tris-HCl pH 8.0, 50 mM NaCl, 5% glycerol, 1 mM DTT)

  • Load onto Q-Sepharose column (if theoretical pI < 7.0) or SP-Sepharose (if pI > 7.0)

  • Elute with linear NaCl gradient (50-1000 mM)

• Size exclusion chromatography:

  • Concentrate protein to 5-10 mg/mL using centrifugal concentrators

  • Load onto Superdex 75/200 column equilibrated with 25 mM HEPES pH 7.5, 150 mM NaCl, 5% glycerol, 1 mM DTT

  • Collect fractions containing monomeric protein

Purification Yield and Purity Table:

What analytical methods should be used to characterize purified IL0393?

Comprehensive characterization of purified IL0393 requires multiple analytical methods:

Physical Characterization:

• Mass spectrometry analysis:

  • ESI-MS for intact mass confirmation

  • LC-MS/MS for sequence coverage and post-translational modification identification

• Structural integrity assessment:

  • Circular dichroism (CD) spectroscopy for secondary structure content

  • Thermal shift assays to determine protein stability

  • Dynamic light scattering (DLS) for homogeneity and oligomeric state

• Functional characterization:

  • Nucleotide binding assays (fluorescence-based, ITC, SPR)

  • Activity assays based on predicted function (ATPase/GTPase activity)

How can researchers investigate nucleotide binding properties of IL0393?

To thoroughly characterize the nucleotide binding properties of IL0393, a systematic approach combining multiple complementary methods is recommended:

Comprehensive Nucleotide Binding Analysis:

• Fluorescence-based assays:

  • Intrinsic tryptophan fluorescence quenching upon nucleotide binding

  • MANT-labeled nucleotides for direct binding measurement

  • Protocol: Titrate increasing concentrations of nucleotides (0.1-100 μM) into protein solution (1-5 μM)

• Isothermal titration calorimetry (ITC):

  • Provides complete thermodynamic profile (ΔH, ΔS, ΔG)

  • Determines binding stoichiometry directly

  • Protocol: 10-20 injections of nucleotide (200-500 μM) into protein solution (10-20 μM)

• Surface plasmon resonance (SPR):

  • Measures association and dissociation kinetics

  • Protocol: Immobilize His-tagged IL0393 on NTA sensor chip, flow nucleotides at varying concentrations (0.1-100 μM)

Nucleotide Binding Specificity Data (Hypothetical Results):

From these hypothetical results, one could conclude that IL0393 has highest affinity for ATP, with significant but reduced affinity for ADP and GTP, suggesting a potential role in ATP-dependent processes.

What computational methods can predict IL0393-nucleotide interactions?

Advanced computational methods offer valuable insights into IL0393-nucleotide interactions before or in parallel with experimental studies:

LigandMPNN Application for IL0393:

LigandMPNN is a deep learning method that can be applied to model protein-ligand interactions with high accuracy . This approach explicitly models the full non-protein atomic context using a graph-based representation .

• Model preparation:

  • Generate IL0393 structure prediction using AlphaFold2 or RoseTTAFold

  • Prepare nucleotide ligand structures with appropriate protonation states

  • Define the protein-ligand complex for analysis

• LigandMPNN analysis process:

  • Encode protein backbone geometry into graph edges through pairwise distances between N, Cα, C, O, and virtual Cβ atoms

  • Process using encoder layers with 128 hidden dimensions to obtain intermediate node/edge representations

  • Apply protein-ligand encoder layers to encode protein-ligand interactions

• Binding site optimization:

  • Use LigandMPNN to iteratively optimize binding site residues

  • Generate sequences around the ligands using backbone and ligand coordinates as input

  • Identify key interaction residues for experimental validation

Protein-Ligand Interaction Prediction Table:

This computational approach can guide experimental design by identifying key residues for mutagenesis and predicting binding preferences before experimental validation.

How can contradictory findings in IL0393 functional studies be reconciled?

When encountering contradictory results in IL0393 functional studies, researchers should implement a systematic context analysis approach:

Contradiction Resolution Framework:

• Identify potential sources of contradiction:

  • Incomplete context specification (different experimental conditions)

  • Variations in protein preparation methods

  • Differences in assay sensitivity and specificity

  • Biological variability in different model systems

• Systematic comparison of contradictory studies:

  • Create a detailed comparison matrix of experimental parameters

  • Identify specific variables that differ between contradictory studies

  • Replicate experiments with systematic variation of these parameters

As noted in biomedical literature analysis, most conflicts in experimental data are due to underspecified context, including differences in species, temporal context, and environmental phenomena . For IL0393 specifically, addressing the following context variables is crucial:

Context Analysis for Contradictory IL0393 Data:

What are the current hypotheses regarding IL0393's physiological role?

Several hypotheses can be proposed regarding IL0393's physiological role based on its classification as a UPF0042 nucleotide-binding protein and the extremophilic nature of Idiomarina loihiensis:

Hypothesis 1: Stress Response Regulator

• Rationale: Nucleotide-binding proteins often function in stress response pathways

• Supporting evidence: I. loihiensis inhabits extreme environments requiring sophisticated stress responses

• Testable predictions:

  • IL0393 expression should increase under stress conditions (high temperature, high salt)

  • Knockout/knockdown should reduce stress tolerance

  • The protein likely interacts with known stress response regulators

Hypothesis 2: Nucleotide Metabolism Enzyme

• Rationale: UPF0042 domain suggests nucleotide interaction capacity

• Supporting evidence: Extremophiles often have specialized nucleotide metabolism pathways

• Testable predictions:

  • IL0393 may exhibit ATPase, GTPase, or nucleotide interconversion activity

  • Activity should be affected by environmental conditions relevant to habitat

  • Metabolomic analysis of knockout strains should reveal altered nucleotide pools

Hypothesis 3: Environmental Sensing Protein

• Rationale: Nucleotide binding may trigger conformational changes linked to signaling

• Supporting evidence: I. loihiensis must adapt to fluctuating conditions at hydrothermal vents

• Testable predictions:

  • IL0393 may interact with sensor kinases or response regulators

  • Structure may show conformational changes upon nucleotide binding

  • Localization may change under different environmental conditions

How can researchers develop IL0393 mutants with altered nucleotide specificity?

Developing IL0393 mutants with altered nucleotide specificity can provide insights into structure-function relationships and potential biotechnological applications:

Rational Design Strategy:

• Structure-guided mutagenesis:

  • Identify binding pocket residues through computational modeling

  • Design mutations based on:

    • Conservation analysis across UPF0042 family

    • Comparison with proteins having known specificity

    • Molecular dynamics simulations of protein-nucleotide complexes

• LigandMPNN-guided design:

  • Use LigandMPNN to predict mutations that would alter specificity

  • Test multiple binding site designs in parallel

  • Experimentally validate and refine computational predictions

Directed Evolution Approach:

• Library construction:

  • Create saturation mutagenesis libraries targeting binding pocket residues

  • Generate random mutagenesis libraries using error-prone PCR

  • Construct shuffled libraries from related UPF0042 family members

• Selection/screening strategies:

  • Develop fluorescence-based screening assays for altered specificity

  • Implement bacterial two-hybrid systems linking nucleotide binding to reporter expression

  • Apply phage display with elution using target nucleotides

Mutation Effects Table (Hypothetical):

What potential biotechnological applications exist for engineered IL0393 variants?

Engineered variants of IL0393 could have several biotechnological applications, leveraging the protein's nucleotide-binding properties and extremophilic origin:

Nucleotide-Based Biosensors:

• Design principle: Couple nucleotide binding to detectable signals (fluorescence, FRET)

• Potential applications:

  • ATP/GTP detection in biological samples

  • Environmental monitoring of nucleotide contamination

  • Real-time imaging of nucleotide dynamics in cells

Extremophilic Enzyme Engineering:

• Design principle: Use IL0393 as a scaffold for creating enzymes stable in extreme conditions

• Potential applications:

  • Salt-tolerant biocatalysts for industrial processes

  • Thermostable enzymes for high-temperature reactions

  • Enzymes functional in non-conventional solvents

Protein-Based Data Storage:

• Design principle: Use nucleotide binding states as binary information storage

• Potential applications:

  • Molecular computing elements

  • Protein-based memory systems

  • Biosensing logic gates

Application Development Roadmap: