Recombinant Saccharomyces cerevisiae Uncharacterized membrane protein YDL133W (YDL133W)

Protein Characteristics and Expression

Q: What are the basic structural characteristics of the YDL133W protein?

A: YDL133W is a 437-amino acid uncharacterized membrane protein from Saccharomyces cerevisiae with UniProt accession number Q12516 . The full amino acid sequence begins with MGDSNSSQEAYSDTTSTNASRIADQNQLNLNVDLEKNQTVRKSGSLEALQNAKIHVPKHS and contains multiple hydrophobic regions consistent with transmembrane domains . Sequence analysis predicts it contains several transmembrane segments with alternating hydrophilic regions. The protein has a molecular weight of approximately 49 kDa and an isoelectric point in the neutral to slightly acidic range. While its precise function remains unknown, its sequence features suggest it may be involved in membrane transport, signaling, or structural organization of the yeast membrane system.

Q: What expression systems are most suitable for producing recombinant YDL133W protein for structural and functional studies?

A: For recombinant expression of YDL133W, several expression systems should be considered based on experimental goals:

• Homologous expression in S. cerevisiae:

  • Advantages: Native folding environment, appropriate post-translational modifications

  • Vectors: pYES2, pRS series with either constitutive (TEF1) or inducible (GAL1) promoters

  • Expression conditions: 30°C growth temperature, careful optimization of induction time

• Bacterial expression (E. coli):

  • Advantages: High yield, rapid growth, ease of purification

  • Challenges: Membrane protein folding issues, potential toxicity

  • Strains: C41(DE3), C43(DE3) specifically designed for membrane proteins

  • Tags: His-tag, fusion proteins (MBP, SUMO) to enhance solubility

• Insect cell expression:

  • Advantages: Eukaryotic folding machinery, higher yields than yeast

  • Systems: Baculovirus expression system (BEVS)

  • Cell lines: Sf9, High Five

  • Conditions: Optimize infection MOI, harvest time, and temperature

For structural studies requiring high purity, the insect cell system often provides the best balance of proper folding and expression yield for yeast membrane proteins, while functional studies might benefit from homologous expression in S. cerevisiae.

Initial Characterization Methods

Q: What are the recommended first steps for characterizing an uncharacterized membrane protein like YDL133W?

A: Initial characterization of YDL133W should follow a systematic approach:

• Bioinformatic analysis:

  • Sequence homology search using BLAST/HHpred

  • Domain prediction using Pfam, SMART, InterPro

  • Transmembrane region prediction using TMHMM, Phobius, MEMSAT

  • Secondary structure prediction using PSIPRED

  • Evolutionary conservation mapping with ConSurf

• Localization studies:

  • GFP/mCherry-tagging of YDL133W in S. cerevisiae

  • Fluorescence microscopy to determine subcellular localization

  • Co-localization with known membrane compartment markers

  • Immunogold electron microscopy for higher resolution localization

• Expression analysis:

  • RT-qPCR to determine expression patterns under different conditions

  • Western blotting to confirm protein expression and size

  • Proteomics to analyze expression in different cellular fractions

• Phenotypic analysis:

  • Generation of YDL133W deletion strain

  • Growth assays under various stress conditions

  • Metabolic profiling of deletion strain versus wild-type

  • High-throughput phenotypic screening across diverse conditions

These approaches provide foundational data about protein characteristics without requiring prior knowledge of function, creating a framework for more targeted functional studies.

Q: How can I confirm the membrane localization and topology of YDL133W?

A: Confirming membrane localization and topology of YDL133W requires multiple complementary approaches:

• Subcellular fractionation:

  • Differential centrifugation to separate cellular compartments

  • Western blot analysis of fractions using anti-YDL133W antibodies

  • Comparison with known membrane protein markers

  • Quantification of enrichment in membrane fractions

• Fluorescence microscopy:

  • C-terminal or N-terminal fluorescent protein fusions

  • Live-cell imaging to visualize localization

  • Co-localization with organelle-specific markers

• Protease protection assays:

  • Treatment of intact cells or spheroplasts with proteases

  • Analysis of protection patterns to determine topology

  • Western blot detection of preserved domains

• Cysteine accessibility methods:

  • Introduction of cysteine residues at predicted loops

  • Labeling with membrane-impermeable sulfhydryl reagents

  • Determination of cytosolic versus extracellular exposure

A comprehensive topology map typically requires data from multiple approaches, as each method has inherent limitations. The most reliable results come from integrating biochemical, genetic, and imaging techniques to build a consistent topological model.

Bioinformatic Analysis Approaches

Q: What bioinformatic tools can predict potential functions of YDL133W?

A: For functional prediction of uncharacterized proteins like YDL133W, several bioinformatic tools and approaches are particularly valuable:

• Sequence-based tools:

  • BLAST/PSI-BLAST: Identifies distant homologs

  • HMMER: Sensitive profile-based sequence searches

  • InterProScan: Integrated platform for protein signature recognition

  • MOTIF: Identifies short conserved sequence motifs

• Structure prediction tools:

  • AlphaFold2: State-of-the-art protein structure prediction

  • SWISS-MODEL: Homology modeling if templates exist

  • I-TASSER: Hierarchical approach to structure prediction

  • Robetta: Fragment-based protein structure prediction

• Function prediction platforms:

  • SIFTER: Statistical inference of function through evolutionary relationships

  • ProFunc: Combines structure and sequence-based methods

  • COFACTOR: Structure-based function annotations

• Membrane-specific tools:

  • MEMSAT: Membrane protein topology prediction

  • TOPCONS: Consensus prediction of membrane protein topology

  • TMHMM: Transmembrane helix prediction

• Integrated analysis approaches:

  • STRING: Protein-protein interaction networks

  • EggNOG: Orthology prediction and functional annotation

  • Gene Ontology enrichment tools

  • MetaCyc/KEGG pathway association analysis

For uncharacterized membrane proteins, combining predictions from multiple tools provides more reliable results than relying on any single method. Cross-validation of predictions is essential before experimental validation.

Functional Characterization Strategies

Q: What genetic approaches can reveal the function of YDL133W in yeast?

A: Genetic approaches for functional characterization of YDL133W should be systematic and multi-layered:

• Gene deletion and phenotyping:

  • CRISPR-Cas9 or homologous recombination for gene knockout

  • Phenotypic screening under various conditions:

    • Different carbon sources (glucose, glycerol, ethanol)

    • Temperature sensitivity (16°C, 30°C, 37°C)

    • Osmotic/ionic stress (NaCl, KCl, sorbitol)

    • pH variations (pH 4-8)

    • Cell wall/membrane stressors (SDS, calcofluor white)

  • High-throughput phenotypic arrays (e.g., Biolog system)

• Synthetic genetic interaction analysis:

  • Synthetic genetic array (SGA) screening against deletion collection

  • Synthetic lethal screens with chemical or genetic perturbations

  • Dosage suppressor screens to identify genetic rescuers

  • Chemical-genetic profiling with diverse compound libraries

• Complementation and rescue experiments:

  • Expression of homologs from other species

  • Domain swapping with characterized membrane proteins

  • Site-directed mutagenesis of conserved residues

• Conditional expression systems:

  • Tetracycline-regulated promoters for titrated expression

  • Auxin-inducible degron tagging for controlled degradation

  • Temperature-sensitive alleles for rapid inactivation

The integration of genetic data with other experimental approaches is crucial for developing a comprehensive functional model for YDL133W.

Q: How can proteomics approaches be used to investigate YDL133W function?

A: Proteomics offers powerful approaches for elucidating YDL133W function:

• Differential proteomics:

  • Quantitative comparison between wild-type and YDL133W deletion strains

  • SILAC or TMT labeling for precise quantification

  • Analysis under normal and stress conditions

  • Focused analysis of membrane proteome changes

• Protein-protein interaction mapping:

  • Affinity purification coupled with mass spectrometry (AP-MS)

  • Proximity-dependent biotin identification (BioID/TurboID)

  • Cross-linking mass spectrometry (XL-MS) for interaction interfaces

  • Co-immunoprecipitation validation of key interactions

• Post-translational modification analysis:

  • Phosphoproteomics to identify regulatory modifications

  • Ubiquitination profiling for protein turnover assessment

  • Glycosylation analysis for membrane protein processing

• Protein dynamics and turnover:

  • Pulse-chase SILAC for protein half-life determination

  • Thermal proteome profiling for conformational stability

  • Limited proteolysis-coupled mass spectrometry for structural insights

The combination of these proteomic approaches provides a systems-level understanding of YDL133W's role in cellular processes.

Structural Analysis Techniques

Q: What are the challenges and solutions for structural determination of YDL133W?

A: Structural determination of YDL133W presents several specific challenges with corresponding solution strategies:

Challenges:

• Low natural expression levels

• Difficulty in extracting from membranes

• Limited stability outside the membrane environment

• Tendency to aggregate during purification

• Difficulty in forming well-diffracting crystals

Solution strategies by technique:

• X-ray crystallography approach:

  • Extensive detergent screening (DDM, LMNG, GDN, OG)

  • Lipidic cubic phase crystallization

  • Fusion protein approaches (T4 lysozyme, BRIL insertion)

  • Nanobody/antibody co-crystallization to stabilize structure

• Cryo-EM approach:

  • Amphipol stabilization (A8-35, PMAL-C8)

  • Nanodisc reconstitution with optimized lipid composition

  • Phase plate technology for improved contrast

  • Direct electron detectors with high sensitivity

• NMR approach:

  • Selective isotope labeling of specific amino acids

  • TROSY techniques for large proteins

  • Solid-state NMR for membrane-embedded proteins

  • Specific methyl labeling for large proteins

• Hybrid approaches:

  • Integrative structural biology combining low-resolution data

  • Cross-linking mass spectrometry constraints

  • EPR distance measurements

  • AlphaFold2 prediction validated by experimental constraints

Recent advances in membrane protein structural biology, particularly in cryo-EM and computational prediction, have dramatically improved success rates. For YDL133W specifically, a cryo-EM approach combined with computational modeling may offer the most practical path to structural insights.

Q: How can molecular dynamics simulations enhance our understanding of YDL133W?

A: Molecular dynamics (MD) simulations provide valuable insights into YDL133W structure and function:

• Membrane embedding simulations:

  • Proper positioning of YDL133W in lipid bilayers

  • Assessment of protein-lipid interactions

  • Identification of specific lipid binding sites

  • Monitoring membrane deformation effects

• Structural dynamics analysis:

  • Conformational flexibility of transmembrane domains

  • Identification of potential gating mechanisms

  • Water/ion permeation pathways

  • Dynamic coupling between protein domains

• Binding site identification:

  • Potential ligand binding pockets

  • Cryptic sites that appear transiently

  • Electrostatic surface mapping

  • Druggability assessment

• Advanced simulation techniques:

  • Coarse-grained simulations for longer time scales

  • Free energy calculations for binding/transport processes

  • Markov state modeling for conformational transitions

  • Enhanced sampling methods (metadynamics, umbrella sampling)

Simulation protocols for YDL133W should include:

• Proper membrane composition modeling (ergosterol, PI, PE, PS lipids)

• Sufficient equilibration (50-100 ns)

• Production runs of 500+ ns

• Replicates with different starting configurations

• Validation with experimental data when available

MD simulations complement experimental approaches by providing atomistic insights into dynamics that are difficult to capture experimentally, generating testable hypotheses about functional mechanisms.

Comparative Genomics and Evolutionary Context

Q: How can comparative genomics inform functional hypotheses for YDL133W?

A: Comparative genomics provides valuable insights for generating functional hypotheses about YDL133W through several analytical approaches:

• Ortholog identification and analysis:

  • Identify YDL133W orthologs across fungal species

  • Compare presence/absence patterns with known phenotypic traits

  • Analyze co-evolution with functionally characterized genes

  • Assess conservation in specific yeast clades

• Synteny analysis:

  • Examine conservation of gene order around YDL133W

  • Identify frequently co-located genes (potential functional partners)

  • Detect genomic rearrangements affecting YDL133W context

  • Compare with other membrane protein genetic contexts

• Evolutionary rate analysis:

  • Calculate selection pressure (dN/dS ratios)

  • Identify conserved domains under purifying selection

  • Detect rapidly evolving regions (potential species-specific functions)

  • Compare evolutionary rates with proteins of known function

• Phylogenetic profiling:

  • Correlate presence/absence patterns with biochemical pathways

  • Identify co-evolving gene sets

  • Compare with phenotypic trait distribution

  • Detect potential horizontal gene transfer events

• Integration with functional data:

  • Correlate evolutionary patterns with expression data

  • Compare with protein-protein interaction networks

  • Analyze in context of metabolic reconstructions

  • Map known phenotypes onto phylogenetic tree

The strength of comparative genomics lies in its ability to generate functional hypotheses based on evolutionary patterns, which can then be tested experimentally. This approach is particularly valuable for uncharacterized proteins like YDL133W, where direct functional data is limited.

Optimization of Recombinant Expression

Q: What strategies can improve the expression and solubility of recombinant YDL133W?

A: Optimizing expression and solubility of recombinant YDL133W requires methodical troubleshooting:

• Expression system optimization:

  • Test multiple expression systems:

    • E. coli (BL21(DE3), C41/C43, Lemo21)

    • S. cerevisiae (BY4741, W303)

    • P. pastoris (GS115, SMD1168)

    • Insect cells (Sf9, High Five)

  • Compare codon-optimized vs. native sequences

  • Evaluate different promoter strengths

  • Test induction conditions (temperature, inducer concentration, time)

• Construct design strategies:

  • Generate truncation constructs to remove flexible regions

  • Create fusion proteins (MBP, SUMO, Trx) to enhance solubility

  • Optimize tag position (N- vs C-terminal)

  • Consider synthetic stabilizing mutations in exposed loops

• Extraction and solubilization approaches:

  • Screen detergent panel for extraction efficiency:

  Detergent Class	Examples	Strengths	Limitations
  Maltoside	DDM, UDM	Gentle, maintain function	Large micelles
  Glucoside	OG, NG	Easily removable	Harsh, potential denaturation
  Neopentyl glycol	LMNG, GDN	High stability, small micelles	Expensive
  Facial amphiphiles	MNA-C12, FA-3	Novel properties	Limited availability

• Expression condition optimization:

  • Test temperature range (16-30°C)

  • Vary induction timing (early vs. late log phase)

  • Adjust media composition (rich vs. minimal)

  • Add specific membrane protein folding enhancers (glycerol, specific ions)

• Stabilization strategies:

  • Include lipids during purification

  • Add specific ligands if suspected

  • Use nanodiscs or amphipols for detergent-free environments

For YDL133W specifically, a homologous expression system in S. cerevisiae with controlled expression rates often provides the best balance of native folding and sufficient yield.

Membrane Protein Isolation and Purification

Q: What is the optimal protocol for isolating and purifying YDL133W while maintaining its native conformation?

A: Optimal isolation and purification of YDL133W requires careful consideration of membrane protein biochemistry:

• Cell lysis and membrane preparation:

  • Gentle mechanical disruption (glass beads for yeast cells)

  • Differential centrifugation (1,000g → 10,000g → 100,000g)

  • Membrane washing to remove peripheral proteins (high salt, high pH)

  • Storage in buffer with glycerol and protease inhibitors

• Solubilization optimization:

  • Systematic detergent screening protocol:

    • Start with 1% detergent concentration

    • Incubate at 4°C for 1-2 hours with gentle rotation

    • Centrifuge at 100,000g to separate solubilized fraction

    • Analyze by Western blot to determine extraction efficiency

  • Consider mixed micelle approaches (primary/secondary detergents)

  • Test lipid addition during solubilization

• Purification strategy:

  • Initial capture: Affinity chromatography (IMAC for His-tagged YDL133W)

  • Intermediate purification: Ion exchange chromatography

  • Polishing step: Size exclusion chromatography

  • Consider on-column detergent exchange to more stable options

• Quality control assessment:

  • Size-exclusion chromatography profiles (monodispersity)

  • Dynamic light scattering (aggregation state)

  • Circular dichroism (secondary structure integrity)

  • Thermal stability assays (CPM fluorescence, DSF)

  • Negative stain EM for homogeneity

Recommended buffers for YDL133W:

• Extraction buffer: 50 mM Tris-HCl pH 7.5, 150 mM NaCl, 10% glycerol, 1 mM EDTA, protease inhibitor cocktail

• Solubilization buffer: Extraction buffer + selected detergent (0.5-1%)

• Purification buffer: 20 mM HEPES pH 7.0, 150 mM NaCl, detergent at CMC + 0.05%

Throughout purification, maintaining protein stability requires careful temperature control (4°C), minimizing exposure to air/foam, and rapid processing to prevent degradation.

Functional Assay Development

Q: What approaches can be used to develop functional assays for an uncharacterized membrane protein like YDL133W?

A: Developing functional assays for uncharacterized membrane proteins like YDL133W requires a systematic approach:

• Transport function assessment:

  • Liposome reconstitution and substrate transport assays

    • Preparation of protein-reconstituted liposomes

    • Fluorescent substrate uptake measurements

    • Counterflow assays for exchange activities

  • Whole-cell transport measurements

    • Radioligand uptake in cells overexpressing YDL133W

    • Fluorescent substrate accumulation

  • Electrophysiological measurements

    • Patch-clamp if ion channel activity is suspected

    • Solid-supported membrane electrophysiology

• Binding and interaction assays:

  • Thermal shift assays with potential ligands

  • Microscale thermophoresis for interaction studies

  • Surface plasmon resonance for binding kinetics

  • Isothermal titration calorimetry for thermodynamic parameters

• Functional complementation:

  • Expression in deletion strains of related proteins

  • Cross-species functional rescue

  • Chimeric protein construction with characterized domains

  • Heterologous expression in specialized reporter systems

• Activity-based assays:

  • ATPase activity measurements if P-type ATPase features exist

  • Lipid flippase activity assays if transporter features exist

  • Enzyme-coupled assays if metabolic function is suspected

  • Membrane integrity assays if structural role is hypothesized

Assay development workflow:

• Generate initial functional hypotheses based on:

  • Bioinformatic predictions

  • Phenotypic data from gene deletion

  • Localization patterns

  • Interaction partners

• Design targeted assays based on specific hypotheses

• Include proper controls:

  • Empty vector controls

  • Inactive mutant controls

  • Known related protein controls

• Optimize assay conditions for sensitivity and specificity

For membrane proteins without clear homologs like YDL133W, a parallel testing approach with multiple assay types often provides the first functional insights.

Multi-omics Data Integration

Q: How can multi-omics approaches be applied to understand the function of YDL133W?

A: Multi-omics integration provides powerful insights into YDL133W function through systematic data collection and analysis:

• Core omics datasets to generate:

  • Transcriptomics: RNA-seq comparing wild-type vs. YDL133W deletion

  • Proteomics: Quantitative proteomics of deletion strain

  • Metabolomics: Targeted and untargeted metabolic profiling

  • Interactomics: Protein-protein interaction maps

• Specialized membrane-focused approaches:

  • Lipidomics to detect membrane composition changes

  • Membrane proteome enrichment analysis

  • Protein co-expression networks focusing on membrane components

  • Organelle proteomics to pinpoint subcellular effects

• Integration analysis methods:

  • Network-based integration (weighted correlation networks)

  • Bayesian integration of heterogeneous data types

  • Multi-block statistical methods (DIABLO, MOFA)

  • Knowledge-based pathway mapping

  • Machine learning approaches for pattern recognition

• Functional interpretation strategies:

  • Gene Ontology and pathway enrichment analysis

  • Network centrality and module detection

  • Causal reasoning algorithms for mechanism proposals

  • Literature-based discovery methods

The power of multi-omics approaches lies in their ability to detect subtle effects that might be missed in single-technique approaches, particularly important for membrane proteins that often have regulatory or sensing functions rather than enzymatic activities with clear biochemical readouts.

Structure-Function Relationship Analysis

Q: How can computational methods predict structure-function relationships for YDL133W?

A: Computational methods for predicting structure-function relationships of YDL133W include:

• Structural prediction and analysis:

  • AlphaFold2/RoseTTAFold for 3D structure prediction

  • Molecular dynamics simulations in membrane environments

  • Electrostatic surface mapping

  • Cavity and pocket detection for binding site prediction

  • Conservation mapping onto structural models

• Sequence-based functional prediction:

  • Conserved domain analysis

  • Motif recognition

  • Sequence profile comparison with characterized proteins

  • Co-evolution analysis for interacting residues

  • Transmembrane topology optimization

• Integrated structural bioinformatics:

  • Structure-based function prediction (ProFunc, COFACTOR)

  • Ligand binding site prediction (FTSite, SiteMap)

  • Protein-protein interaction surface prediction

  • Transmembrane channel/pore analysis

• Advanced computational approaches:

  • Template-based function transfer

  • Binding site similarity searches against protein structure databases

  • Molecular docking with metabolite libraries

  • Graph-based representation learning

The computational analysis workflow should include:

• Generate high-quality structural models

• Validate models through quality assessment metrics

• Identify potential functional sites

• Simulate protein dynamics in membrane environment

• Generate testable hypotheses for experimental validation

These computational predictions provide a foundation for targeted experimental approaches, significantly narrowing the search space for YDL133W function.

Q: What are the most promising future research directions for understanding YDL133W function?

A: The most promising future research directions for elucidating YDL133W function include:

• Integrative functional genomics:

  • Chemical genomics combined with traditional genetic approaches

  • High-resolution phenomics under diverse conditions

  • Synthetic genetic interaction mapping with other membrane proteins

  • Condition-specific essentiality screening

• Advanced structural biology:

  • Cryo-EM analysis in different membrane mimetics

  • Hydrogen-deuterium exchange mass spectrometry for dynamics

  • Single-molecule studies of conformational changes

  • In-cell structural approaches (crosslinking-MS, in-cell NMR)

• Systems biology integration:

  • Multi-omics data integration

  • Regulatory network mapping

  • Quantitative models of cellular processes affected by YDL133W

  • Network perturbation analysis

• Comparative and evolutionary studies:

  • Functional analysis in diverse yeast species

  • Adaptation experiments under selective pressures

  • Ancestral sequence reconstruction and functional testing

  • Pan-Saccharomycetaceae comparative genomics

• Emerging technologies:

  • CRISPR interference for precise temporal control

  • Single-cell analysis of YDL133W effects

  • Proximity labeling in native contexts

  • Advanced imaging (super-resolution, correlative light-electron microscopy)