Recombinant Bovine Transmembrane protein 151B (TMEM151B)

What is the structural characterization of bovine TMEM151B and how does it compare to human TMEM151B?

Human TMEM151B consists of 566 amino acids with two transmembrane domains, a molecular weight of approximately 61 kDa, and a theoretical isoelectric point of 6.72 . The protein composition is notably poor in lysine (1.4%) and arginine (0.8%) . While specific bovine TMEM151B structural data is limited, comparative analysis with the human ortholog can provide insights.

Methodological approach for characterization:

• Perform sequence alignment between bovine and human TMEM151B to identify conserved domains

• Conduct hydropathy plot analysis to confirm the predicted transmembrane domains

• Use tools like Compute pI/Mw for theoretical properties determination

• Apply secondary structure prediction tools (PSIPRED, JPred) to identify potential structural elements

• Consider circular dichroism (CD) spectroscopy to assess secondary structure content experimentally

What is known about the genomic organization of the TMEM151B gene?

The human TMEM151B gene is located on chromosome 6p21.1 (position 44270450 to 44279444), spanning 8,995 base pairs . It contains 3 exons, with a transcribed mRNA length of 4,911 bp and a coding region of 1,701 bp . The gene shares a complex locus with SPATS1 .

Methodological approach for bovine gene analysis:

• Use comparative genomics to identify the bovine ortholog through synteny analysis

• Map exon-intron structures using RNA-seq data and genome assemblies

• Apply gene prediction tools with parameter optimization for bovine sequences

• Consider 5' and 3' RACE to confirm transcript boundaries experimentally

• Use qPCR primers spanning exon junctions to verify splicing patterns, similar to approaches used for other genes

What tissues express TMEM151B and how should expression patterns be analyzed?

RNA-seq data shows high TMEM151B expression in the brain and notable expression in the testes . In mouse brain, high expression is observed particularly in the cerebellum, medulla, and olfactory bulb according to the Allen Brain Atlas .

Methodological approach for expression analysis:

• Design bovine-specific qPCR primers using the NCBI primer blast tool as described in similar studies

• Normalize expression using established reference genes for bovine tissues

• Convert RNA-seq data to standardized formats (TPM or FPKM) for cross-dataset comparisons

• Apply tissue-specific expression analysis similar to methods used in the Bgee database, which transforms heterogeneous expression data into present/absent calls

• Consider single-cell RNA-seq for cell type-specific expression patterns

• Validate key findings with in situ hybridization in tissues of interest

What expression systems are most suitable for producing recombinant bovine TMEM151B?

The choice of expression system depends on research objectives, required protein yield, and post-translational modification needs.

Methodological comparison of expression systems:

Choose based on your specific requirements: S2 cells have been successfully used for expressing complex transmembrane proteins with yields exceeding 10 mg/L , making them a good starting point.

How can I optimize expression and purification of recombinant bovine TMEM151B?

Step-by-step optimization approach:

• Construct design considerations:

  • Include appropriate secretion signal

  • Add purification tag (His, FLAG, etc.)

  • Consider codon optimization for the host system

  • Evaluate transmembrane domain requirements (include or remove)

  • Consider furin cleavage site mutation if protein stability is an issue, similar to approaches used for BLV Env protein

• Expression optimization:

  • Test multiple expression temperatures (lower temperatures often improve folding)

  • Optimize induction timing and duration

  • Test different media compositions and supplements

  • Consider stable cell line generation for consistent expression

• Purification strategy:

  • Implement multi-step purification:

    • Affinity chromatography (IMAC for His-tagged proteins)

    • Size exclusion chromatography to remove aggregates

    • Ion exchange chromatography based on theoretical pI

  • Include appropriate detergents for transmembrane domain solubilization

  • Monitor purification by SDS-PAGE, Western blot, and dynamic light scattering

• Quality assessment:

  • Verify protein identity by mass spectrometry

  • Assess glycosylation pattern using glycoproteomic approaches

  • Analyze protein homogeneity by DLS and SEC-MALS

  • Confirm proper folding through CD spectroscopy and/or antibody recognition

How can I characterize the glycosylation pattern of recombinant bovine TMEM151B?

Glycosylation analysis is critical for transmembrane proteins as it affects folding, stability, and function.

Methodological approach for glycosylation analysis:

• Identification of glycosylation sites:

  • Predict N-glycosylation sites using NetNGlyc or similar tools

  • Confirm experimentally through:

    • PNGase F treatment followed by mass shift analysis on SDS-PAGE

    • LC-MS/MS analysis of deglycosylated peptides

    • Site-directed mutagenesis of predicted sites

• Glycan composition analysis:

  • Use MALDI-TOF MS for released glycans

  • Apply nanoLC-MS/MS for glycopeptide analysis

  • Consider hydrophilic interaction liquid chromatography (HILIC)

  • Note that some glycopeptides may be difficult to detect by direct MS methods due to high hydrophilicity

• Glycan characterization:

  • Compare glycan patterns between different expression systems

  • Assess proportion of oligomannose, paucimannose, and complex glycans

  • Determine core fucosylation levels, similar to findings in BLV EnvFm

  • Quantify glycan occupancy at each site

A study on recombinant proteins expressed in S2 cells showed high glycosylation occupancy at most N-linked sites, although some sites showed partial glycosylation (25-36% unmodified) .

How should I design experiments to identify novel interaction partners of bovine TMEM151B?

Human TMEM151B is known to interact with SREBF2, a transcription factor involved in cholesterol biosynthesis . For bovine TMEM151B, a systematic approach to identify additional interaction partners is recommended.

Methodological approaches for interaction studies:

• Proximity-based labeling methods:

  • BioID: Fuse TMEM151B with BirA* biotin ligase to label proximal proteins

  • APEX2: Use peroxidase-mediated biotinylation for rapid labeling

  • TurboID: Employ evolved biotin ligase with faster kinetics

  • Analyze biotinylated proteins by mass spectrometry

• Affinity purification-mass spectrometry (AP-MS):

  • Express tagged TMEM151B in relevant cell types

  • Use mild detergents to maintain membrane protein interactions

  • Apply stringent controls (tag-only, irrelevant membrane protein)

  • Identify co-purified proteins by LC-MS/MS

• Membrane-specific yeast two-hybrid:

  • Use split-ubiquitin membrane Y2H system

  • Screen against cDNA libraries from tissues of interest

  • Validate hits in mammalian cells using co-IP

• Data analysis considerations:

  • Prioritize candidates based on enrichment over controls

  • Focus on proteins with relevant subcellular localization

  • Consider co-expression patterns across tissues

  • Evaluate evolutionary conservation of interactions

What techniques are most effective for studying transmembrane domain functions of TMEM151B?

TMEM151B contains two transmembrane domains that likely play important roles in its localization and function.

Methodological approach to transmembrane domain studies:

• Topology mapping:

  • Glycosylation scanning mutagenesis to identify luminal domains

  • Cysteine accessibility method to determine membrane-embedded regions

  • Protease protection assays to identify cytosolic versus luminal domains

• Structure-function analysis:

  • Site-directed mutagenesis of conserved residues

  • Domain swapping with TMEM151A (its paralog)

  • Truncation analysis to determine minimal functional units

  • Correlate mutations with phenotypes in functional assays

• Membrane interaction studies:

  • Reconstitute purified protein into artificial membranes

  • Assess lipid preferences using liposome binding assays

  • Evaluate oligomerization state in membrane environment

  • Apply molecular dynamics simulations to model membrane interactions

• Structural approaches:

  • Employ single-particle cryo-EM for full-length protein

  • Use NMR for isolated transmembrane peptides

  • Consider cross-linking mass spectrometry to identify interacting residues

How can I investigate potential roles of TMEM151B in brain function, given its high expression in neural tissues?

TMEM151B shows high expression in brain tissues, particularly in the cerebellum, medulla, and olfactory bulb , suggesting potential neurological functions.

Methodological approach for neurobiological studies:

• Cell-type specific expression analysis:

  • Apply single-cell RNA-seq to identify neuron subtypes expressing TMEM151B

  • Use in situ hybridization to map expression within brain regions

  • Perform co-localization studies with cell type-specific markers

• Functional manipulation in neuronal models:

  • CRISPR-Cas9 knockout in neuronal cell lines

  • shRNA knockdown in primary neurons

  • Overexpression studies with wild-type and mutant constructs

  • Rescue experiments to confirm specificity

• Physiological assessment:

  • Calcium imaging to assess neuronal activity

  • Electrophysiological recordings in cells with altered TMEM151B expression

  • Neurite outgrowth and synaptogenesis assays

  • Evaluate effects on neuronal signaling pathways

• Animal model studies:

  • Generate conditional knockout models targeting specific brain regions

  • Perform behavioral testing related to cerebellum/medulla functions

  • Assess neuroanatomical changes in TMEM151B-deficient animals

  • Correlate molecular findings with behavioral phenotypes

How should I design comparative studies between bovine and human TMEM151B?

Comparative studies can reveal conserved functions and species-specific adaptations of TMEM151B.

Methodological approach for comparative studies:

• Sequence and structure comparison:

  • Perform multiple sequence alignment including additional species

  • Identify conserved motifs and species-specific variations

  • Build structural models for both orthologs

  • Apply evolutionary rate analysis to identify functionally important residues

• Expression comparison:

  • Use standardized RNA-seq analysis pipelines for cross-species comparison

  • Apply transformation methods similar to those in the Bgee database to compare expression across species

  • Normalize gene expression data using appropriate housekeeping genes

  • Compare cellular and subcellular localization patterns

• Functional conservation assessment:

  • Express both orthologs in the same cellular background

  • Perform cross-species complementation studies

  • Compare interaction profiles with conserved binding partners

  • Create chimeric proteins to map species-specific functional differences

• Data integration approach:

  • Apply ontology-based annotations for cross-species anatomical comparisons

  • Use statistical methods that account for species differences

  • Consider evolutionary context when interpreting functional differences

  • Implement visualization tools that facilitate direct comparison

How can I reconcile contradictory data about TMEM151B function from different experimental systems?

When faced with contradictory results, a systematic approach can help identify sources of variation and develop a unified model.

Methodological approach to resolve contradictions:

• Systematic evaluation of experimental differences:

  • Compare expression systems used (insect vs. mammalian cells)

  • Assess effects of different tags or fusion constructs

  • Evaluate purification methods and buffer conditions

  • Consider assay-specific variables that might influence results

• Harmonized experimental design:

  • Standardize protocols across comparison studies

  • Include the same controls across all experiments

  • Test multiple hypotheses simultaneously in the same system

  • Consider blinded analysis to reduce confirmation bias

• Biological context considerations:

  • Test in multiple cell types relevant to natural expression patterns

  • Evaluate potential tissue-specific interacting partners

  • Consider post-translational modifications specific to each system

  • Assess developmental or physiological state dependencies

• Statistical approaches:

  • Perform meta-analysis of multiple datasets

  • Use appropriate statistical tests based on data distribution

  • Apply multiple testing correction for large-scale analyses

  • Consider Bayesian approaches to integrate prior knowledge

• Validation strategy:

  • Confirm key findings with orthogonal techniques

  • Test predictions from each contradictory model

  • Develop experiment to directly test competing hypotheses

  • Consider in vivo validation of in vitro findings

What statistical approaches are most appropriate for analyzing TMEM151B expression data?

Methodological approach for expression data analysis:

• RNA-seq data analysis:

  • Apply appropriate normalization (TPM or FPKM formats)

  • Use DESeq2, edgeR, or limma for differential expression analysis

  • Implement multiple testing correction (FDR or Bonferroni)

  • Consider batch effect correction when integrating multiple datasets

• Correlation analysis:

  • Evaluate correlation between TMEM151B and potential functional partners

  • Use Pearson correlation for linear relationships (studies have shown negative correlation between TMEM151B and AR expression with Pearson r values ranging from -0.71 to -0.32)

  • Apply Spearman correlation for non-linear relationships

  • Consider partial correlation to control for confounding variables

• Classification and grouping:

  • Implement appropriate statistical tests based on data distribution:

    • Chi-square test for categorical variables

    • t-test/ANOVA for normally distributed continuous variables

    • Non-parametric alternatives when normality assumptions are violated

  • For comparing gene expression with clinical parameters, use appropriate statistical methods as seen in published studies (p-values < 0.05 considered significant)

• Data visualization:

  • Generate boxplots or violin plots for group comparisons

  • Use heatmaps for visualizing expression patterns across samples

  • Apply dimensionality reduction (PCA, t-SNE) for pattern identification

  • Present both raw data and statistical summaries for transparency

What are the critical quality control measures for recombinant TMEM151B experiments?

Quality control is essential for ensuring reliable and reproducible results with recombinant proteins.

Methodological approach for quality control:

• Protein identity verification:

  • Confirm sequence by mass spectrometry

  • Western blot with specific antibodies

  • N-terminal sequencing for additional verification

  • Size verification by SDS-PAGE and mass spectrometry

• Purity assessment:

  • SDS-PAGE with Coomassie or silver staining

  • SEC-MALS to determine homogeneity and molecular weight

  • Dynamic light scattering to assess aggregation state

  • Analytical ultracentrifugation for detailed homogeneity analysis

• Structural integrity evaluation:

  • Circular dichroism to assess secondary structure

  • Thermal shift assays to determine stability

  • Conformation-specific antibody binding

  • Functional assays based on known activities or interactions

• Post-translational modification analysis:

  • Glycosylation analysis using methods described in question 2.3

  • Phosphorylation status determination if relevant

  • Other modifications based on prediction and experimental evidence

  • Site-occupancy quantification for each modification

• Endotoxin and contaminant testing:

  • LAL assay for endotoxin detection

  • Host cell protein ELISA

  • Host cell DNA quantification

  • Sterility testing for cell-based applications

How should I design controls for functional studies of recombinant TMEM151B?

Proper controls are critical for distinguishing specific TMEM151B-mediated effects from experimental artifacts.

Methodological approach for experimental controls:

• Expression system controls:

  • Empty vector transfection

  • Irrelevant protein expression (similar size/topology)

  • Tag-only expression to control for tag effects

  • Wild-type versus mutant comparisons

• Protein specificity controls:

  • Heat-denatured protein

  • Concentration titration to demonstrate dose-dependency

  • Competing peptide/protein to demonstrate specificity

  • Pre-adsorption with antibodies when applicable

• Functional redundancy controls:

  • TMEM151A (paralog) expression

  • Rescue experiments following knockdown/knockout

  • Domain deletion variants

  • Species orthologs with different functional properties

• Technical controls:

  • Multiple biological replicates (minimum n=3)

  • Technical replicates to assess method variability

  • Positive and negative controls specific to each assay

  • Inter-laboratory validation for critical findings

This comprehensive control strategy ensures that observed effects can be confidently attributed to TMEM151B function.