Recombinant Mouse Uncharacterized protein C10orf118 homolog (Otg1), partial

What is Otg1 and where is it localized in mammalian cells?

Otg1 (oocyte testis gene 1) encodes a Golgi-localized protein with a broad tissue distribution in mice. The full-length transcript has 16 exons that encode a 917-amino acid peptide. The OTG1 protein contains several coiled-coil domains that occupy almost half of the peptide sequence. Confocal microscopy studies confirm its predominant localization in the Golgi apparatus with a Pearson's Correlation of 0.7011 compared to 0.3804 in the endoplasmic reticulum . Although the primary sequence contains a KDEL signal at position 677-680 (compatible with ER retention), it shows preferential localization to the Golgi apparatus.

What are the known functions of Otg1/C10orf118?

Current research indicates that Otg1/C10orf118 functions as:

• A vesicle trafficking regulator in mammalian cells

• A regulator of hyaluronan synthesis by acting on the up-regulation of the HAS2 gene in fibroblasts

• A potential controller of hormone secretion affecting glucose homeostasis

The protein structure contains coiled-coil regions reminiscent of golgin coiled-coil proteins, which are known to function as membrane and cytoskeleton tethers. Although it lacks a transmembrane or small GTPase interacting signal typically found in golgins, OTG1 may still participate in similar intracellular activities by serving as a molecular partner to typical golgins .

What phenotypes are observed in Otg1-deficient mice?

Otg1 disruption in mice leads to several significant phenotypes:

Notably, Otg1 mutant mice exhibit lipohypotrophy and typically die before reaching 5 grams in body weight .

How does Otg1 disruption impact vesicle trafficking and hormone secretion?

Otg1 appears to play a critical role in the vesicle trafficking machinery of the Golgi apparatus. Studies of Otg1-deficient mice have revealed:

• Reduced levels of circulating hormones including insulin, leptin, and growth hormone

• Decreased hepatic IGF-1 expression

• Impaired glucose homeostasis

The mechanistic link involves OTG1's coiled-coil domains, which are structurally reminiscent of golgin proteins known to function as tethers in vesicle trafficking. Although OTG1 lacks the transmembrane or GTPase-interacting signals typical of golgins, it likely functions as a molecular partner to these proteins, contributing to vesicle capture and providing specificity to the tethering step. When this function is disrupted, the secretion of multiple hormones is affected, leading to the observed metabolic phenotypes .

What is the relationship between C10orf118 expression and cancer aggressiveness?

Research has revealed an interesting correlation between C10orf118 expression levels and breast cancer aggressiveness:

• Expression analysis across different breast cancer cell lines showed that C10orf118 gene expression was more pronounced in breast cancer cells compared to stromal cells

• The highest expression was found in less aggressive breast cancer cell lines (8701-BC and MCF-7)

• Lower expression was observed in the highly aggressive MDA-MB-231 cell line

• High expression of C10orf118 is positively correlated with patient survival and low metastasis

• C10orf118 expression was associated with the presence of estrogen receptor, which characterizes a good patient survival outcome

These findings suggest that C10orf118 may function as a tumor suppressor in breast cancer, with its expression potentially serving as a prognostic indicator.

How does C10orf118 influence hyaluronan metabolism in the tumor microenvironment?

C10orf118 has been identified as a novel regulator of hyaluronan (HA) synthesis in the tumor microenvironment. Experimental evidence indicates:

• Secreted C10orf118 induces hyaluronan synthase 2 (HAS2) expression in fibroblasts

• Knockdown of C10orf118 in MCF-7 cells reduced the mRNA levels of HAS2 and its epigenetic regulator HAS2-AS1

• C10orf118 silencing increased levels of the HA receptor CD44

• These findings suggest an autocrine effect of C10orf118 on key enzymes and receptors related to HA metabolism

This regulatory role has significant implications for understanding tumor-stromal interactions, as alterations in HA synthesis and size affect tumor growth and metastasis .

What experimental designs are most effective for studying Otg1/C10orf118 function in vitro?

When investigating Otg1/C10orf118 function in vitro, consider the following experimental approaches:

• Gene silencing by siRNA:

  • Use nucleofection with 30 nmol siRNA targeting C10orf118 (as demonstrated in MCF-7 cells with ~65% silencing efficiency)

  • Include appropriate scrambled siRNA controls (30 nmol)

  • Assess knockdown efficiency by quantitative RT-PCR

• Subcellular localization studies:

  • Immunofluorescence with antibodies against C10orf118 and organelle markers

  • Use confocal microscopy with Z-stack imaging

  • Calculate colocalization using Pearson's correlation coefficient

  • High-resolution line-scan analysis on Z-stack images to confirm localization

• Vesicle trafficking assays:

  • Use VSVG protein marker to track protein trafficking through the secretory pathway

  • Temperature-controlled experiments to synchronize cargo movement

  • Time-course analysis of cargo progression through the Golgi apparatus

• Hormone secretion measurements:

  • Culture cells in serum-free media prior to collection of conditioned media

  • Use ELISA assays to quantify secreted hormones

  • Compare secretion rates between wild-type and Otg1-depleted cells

What are the optimal methods for analyzing Otg1/C10orf118 effects on gene expression?

For analyzing the effects of Otg1/C10orf118 on gene expression, implement the following methods:

• Quantitative RT-PCR:

  • Design primers specific for genes of interest (e.g., HAS2, HAS2-AS1, CD44)

  • Use appropriate reference genes for normalization (validated for your cell type)

  • Calculate relative expression using the 2^(-ΔΔCT) method

  • Perform at least three biological replicates

• RNA-Seq analysis:

  • Compare transcriptomes of control and Otg1/C10orf118-silenced cells

  • Analyze differentially expressed genes using DESeq2 or edgeR

  • Perform pathway enrichment analysis to identify affected biological processes

  • Validate key findings with qRT-PCR

• Chromatin immunoprecipitation (ChIP):

  • Investigate potential interactions between C10orf118 and chromatin

  • Use antibodies against C10orf118 or associated transcription factors

  • Analyze enrichment at promoters of regulated genes (e.g., HAS2)

• Promoter reporter assays:

  • Clone promoter regions of target genes into luciferase reporter constructs

  • Co-transfect with C10orf118 expression vectors or siRNAs

  • Measure promoter activity to assess direct transcriptional effects

How should researchers design fractional factorial experiments to study multiple factors affecting Otg1 function?

When designing experiments to study multiple factors affecting Otg1 function, fractional factorial designs can be particularly useful:

• Identify key factors for investigation:

  • Cell type (e.g., fibroblasts, epithelial cells, cancer cell lines)

  • Growth conditions (serum concentration, hypoxia)

  • Protein expression levels (overexpression, knockdown)

  • Stimuli (growth factors, hormones)

• Choose appropriate fractional factorial design:

  • For k factors, a 2^(k-p) fractional factorial design reduces experimental runs

  • Select design resolution based on which interaction effects need to be distinguished

  • Use orthogonal arrays to ensure uncorrelated effect estimates

• Example design for a 4-factor experiment:

  Run	Cell Type	Oxygen Levels	Otg1 Expression	Growth Factor
  1	Fibroblast	Normoxia	Normal	Present
  2	Fibroblast	Hypoxia	Knockdown	Absent
  3	Cancer	Normoxia	Knockdown	Absent
  4	Cancer	Hypoxia	Normal	Present
  5	Fibroblast	Normoxia	Knockdown	Present
  6	Fibroblast	Hypoxia	Normal	Absent
  7	Cancer	Normoxia	Normal	Absent
  8	Cancer	Hypoxia	Knockdown	Present

• Analysis considerations:

  • Use ANOVA or regression methods for effect estimation

  • Consider potential confounding between effects based on design resolution

  • Apply the sparsity-of-effects principle, assuming higher-order interactions are negligible

This approach allows for efficient screening of multiple factors affecting Otg1 function while minimizing the number of experimental runs required.

What controls are essential when studying the effects of recombinant Otg1 on cellular functions?

When studying the effects of recombinant Otg1 on cellular functions, the following controls are essential:

• Expression controls:

  • Empty vector controls for overexpression studies

  • Non-targeting siRNA/shRNA for knockdown experiments

  • Western blot verification of protein expression levels

  • Immunofluorescence to confirm subcellular localization

• Functional controls:

  • Known Golgi-disrupting agents (e.g., Brefeldin A) as positive controls

  • Trafficking assays with well-characterized cargo molecules (e.g., VSVG-GFP)

  • Measurement of secreted proteins unrelated to Otg1 pathways

• Cell-type controls:

  • Compare effects across multiple cell types (e.g., fibroblasts, epithelial cells)

  • Use cells with naturally occurring high and low Otg1 expression

  • Include isogenic cell lines differing only in Otg1 expression

• Rescue experiments:

  • Re-expression of wild-type Otg1 in knockout/knockdown cells

  • Domain-specific mutants to identify functional regions

  • Chimeric proteins to assess domain-specific functions

• Time-course controls:

  • Monitor effects at multiple time points after manipulation

  • Include pre-treatment measurements as baselines

  • Consider both acute and chronic effects of Otg1 manipulation

How should researchers address contradictory findings regarding Otg1/C10orf118 function in different cell types?

When addressing contradictory findings regarding Otg1/C10orf118 function across different cell types:

• Systematic comparison approach:

  • Create a standardized experimental framework to test Otg1 function across cell types

  • Control for variables such as expression level, culture conditions, and passage number

  • Quantify function using identical readouts (e.g., same trafficking assay)

• Cell type-specific factor analysis:

  • Investigate expression levels of potential Otg1 interaction partners in each cell type

  • Assess differences in post-translational modifications of Otg1

  • Compare subcellular localization patterns using co-localization coefficients

• Integrative data analysis:

  • Perform meta-analysis of results across studies

  • Use statistical methods that account for between-study heterogeneity

  • Identify consistent vs. variable aspects of Otg1 function

• Reconciliation framework:

  • Develop models that incorporate cell type-specific factors

  • Test hypotheses that could explain divergent results (e.g., cell type-specific binding partners)

  • Design experiments specifically to distinguish between competing models

For example, the apparent contradictions between Otg1's roles in vesicle trafficking and hyaluronan synthesis may be reconciled by understanding how these pathways interact in different cellular contexts. The differential expression of C10orf118 in aggressive vs. less aggressive cancer cell lines suggests context-specific functions that may explain seemingly contradictory observations .

What statistical approaches are most appropriate for analyzing Otg1 knockout phenotypes in mouse models?

For analyzing Otg1 knockout phenotypes in mouse models, implement these statistical approaches:

• Survival analysis:

  • Kaplan-Meier curves to compare survival between genotypes

  • Log-rank test to assess statistical significance

  • Cox proportional hazards model to account for covariates

  • Example: In Otg1 studies, 46.5% homozygous PB/PB mutants died within P1, while 96.4% wild-type and 94.2% heterozygous littermates survived beyond one month

• Longitudinal growth analysis:

  • Linear mixed models to account for repeated measures

  • Growth curve analysis to compare trajectories between genotypes

  • Power analysis to determine appropriate sample sizes

  • Example: Body weight progression should be tracked and compared to wild-type and heterozygous littermates

• Metabolic parameter analysis:

  • ANOVA with post-hoc tests for comparing multiple groups

  • Non-parametric alternatives (e.g., Kruskal-Wallis) for non-normally distributed data

  • Repeated measures designs for glucose tolerance tests

  • Example: Blood glucose levels in PB/PB Otg1 mice dropped to approximately 25% below normal within two days of birth

• Gene expression analysis:

  • Appropriate normalization of qPCR data

  • Correction for multiple comparisons in genome-wide studies

  • Example: Hepatic IGF-1 expression decreased by 50% at P1 and 87% at P11 in PB/PB mutants

• Sample size considerations:

  • Account for potential early lethality when designing studies

  • Include heterozygotes to assess potential gene dosage effects

  • Match for sex, age, and litter when possible

These approaches enable robust analysis of complex phenotypes while accounting for the unique challenges of working with models that exhibit significant survival and developmental effects.

What are the most promising approaches for identifying Otg1/C10orf118 interaction partners and signaling pathways?

To identify Otg1/C10orf118 interaction partners and signaling pathways, researchers should consider:

• Proximity-dependent labeling approaches:

  • BioID or TurboID fusion proteins to identify proximal proteins in living cells

  • APEX2 proximity labeling for temporal resolution of interactions

  • Comparative analysis across cell types and conditions

• Co-immunoprecipitation coupled with mass spectrometry:

  • Both endogenous and epitope-tagged approaches

  • Crosslinking strategies to capture transient interactions

  • Quantitative proteomics to assess interaction dynamics

• Functional genomics screens:

  • CRISPR-Cas9 screens to identify genes that modify Otg1 phenotypes

  • Synthetic lethal screens in Otg1-deficient backgrounds

  • Targeted screens focused on vesicle trafficking and Golgi function genes

• Structural biology approaches:

  • Domain-specific interaction mapping

  • Cryo-EM analysis of Otg1 in complex with binding partners

  • Structure-function studies with domain deletion mutants

• Signaling pathway analysis:

  • Phosphoproteomic analysis in response to Otg1 manipulation

  • Transcriptional profiling to identify downstream effectors

  • Small molecule inhibitor screens to disrupt Otg1-dependent pathways

These approaches would provide crucial insights into how Otg1/C10orf118 interfaces with cellular machinery to regulate vesicle trafficking, hormone secretion, and hyaluronan synthesis.

How can researchers leverage interdisciplinary approaches to better understand the physiological significance of Otg1/C10orf118?

To fully understand the physiological significance of Otg1/C10orf118, researchers should implement these interdisciplinary approaches:

• Systems biology integration:

  • Multi-omics data integration (transcriptomics, proteomics, metabolomics)

  • Network analysis to position Otg1 within cellular pathways

  • Mathematical modeling of vesicle trafficking and secretion dynamics

• Translational research connections:

  • Correlation of Otg1 expression with disease states in patient samples

  • Analysis of human genetic variants in C10orf118 and their phenotypic associations

  • Development of biomarkers based on Otg1 function or expression

• Advanced imaging technologies:

  • Super-resolution microscopy to visualize Otg1-dependent trafficking events

  • Live-cell imaging with optogenetic control of Otg1 function

  • Correlative light and electron microscopy to link Otg1 localization with ultrastructural features

• Tissue engineering approaches:

  • 3D organoid models to study Otg1 in physiologically relevant contexts

  • Co-culture systems to investigate cell-cell communication involving Otg1

  • Microfluidic platforms to assess dynamic secretory processes

• Collaborations across disciplines:

  • Developmental biologists to study Otg1's role in embryogenesis

  • Endocrinologists to investigate hormone secretion defects

  • Cancer biologists to explore tumor-suppressive mechanisms

  • Glycobiologists to examine hyaluronan metabolism

These interdisciplinary approaches would provide a comprehensive understanding of Otg1/C10orf118's diverse functions and potential therapeutic relevance across multiple biological contexts and disease states.