Recombinant Protein ST7 homolog (F11A10.5)

What is the ST7 homolog (F11A10.5) protein?

The ST7 homolog (F11A10.5) is a protein found in Caenorhabditis elegans that serves as the ortholog to the mammalian suppressor of tumorigenicity 7 (ST7) gene. It is a full-length protein consisting of 536 amino acids (1-536) . The protein demonstrates significant homology to mammalian ST7, with BLAST analysis showing a p-value of 1e-112 and a score of 403, indicating high sequence similarity and evolutionary conservation . This strong conservation suggests important biological functions that have been maintained throughout evolution.

What is the recombinant form of F11A10.5 protein used in research?

The recombinant form of F11A10.5 used in research is typically produced in E. coli expression systems as a full-length protein (amino acids 1-536) with a histidine tag . This recombinant format allows for efficient purification using affinity chromatography and provides a consistent source of the protein for in vitro studies. The His-tagged version enables researchers to conduct various biochemical assays, structural studies, and protein-protein interaction analyses with controlled protein quality and quantity.

What are the known functional associations of F11A10.5?

While the specific biochemical functions of F11A10.5 are not fully characterized, research in mouse models has revealed that ST7 expression correlates strongly with expected lifespan . Lower ST7 expression is associated with higher expected lifespans in mouse models, suggesting it may play a regulatory role in aging processes . Additionally, in C. elegans, RNAi-mediated inhibition of st-7 (F11A10.5) affects lifespan, particularly in long-lived mutant models like glp-1, where it completely suppresses the lifespan extension effect . This suggests a potentially conserved role in longevity regulation across species.

How does F11A10.5 affect longevity pathways in C. elegans and mice?

In mice, ST7 expression demonstrates a robust inverse correlation with lifespan expectancy. Mouse strains with shorter lifespans consistently show higher ST7 expression levels . Unlike other age-associated genes such as Ctsd, ST7 expression remains relatively stable across chronological age, suggesting it may influence biological aging processes through constitutive mechanisms rather than through changes in expression over time . This indicates ST7/F11A10.5 likely functions in a conserved longevity regulatory pathway that intersects with germline-mediated longevity extension in C. elegans.

What methodologies are most effective for studying ST7 homolog (F11A10.5) interactions with aging pathways?

For studying ST7 homolog interactions with aging pathways, a multi-modal approach combining genetic manipulation, transcriptomics, and proteomics has proven most effective. RNAi knockdown in C. elegans provides a straightforward method to assess functional impacts on lifespan in both wild-type and long-lived mutant backgrounds . For deeper mechanistic understanding, researchers should consider:

• Epistasis analysis with known longevity genes (daf-2, glp-1, etc.) to position F11A10.5 within established aging pathways

• Temporal-specific gene knockdown to distinguish developmental from adult-specific effects

• Tissue-specific expression analysis to identify primary sites of action

• Proteomic approaches to identify interacting partners

Meta-analysis of expression data across tissues and experimental conditions can reveal regulatory networks, as demonstrated in BXD mouse studies where ST7 expression correlates robustly across both tissues and independent studies (median r ~ 0.50) . This suggests studying ST7/F11A10.5 in multiple tissues simultaneously may provide insights into its systemic effects on aging.

How do dietary interventions affect ST7 homolog (F11A10.5) expression and function?

Dietary interventions appear to have limited direct impact on ST7/F11A10.5 expression levels, though they may modulate its functional significance. In BXD mouse strains, ST7 expression shows strong correlation across dietary conditions (high-fat diet vs. control diet, rho = 0.66, p = 2e-6), suggesting its expression is primarily determined by genetic factors rather than being significantly modulated by diet .

• Testing interactions between ST7/F11A10.5 manipulation and dietary interventions like caloric restriction

• Examining if ST7/F11A10.5 expression or function changes under metabolic stress conditions

• Investigating whether ST7/F11A10.5 mediates any diet-dependent effects on longevity

• Exploring potential interactions with nutrient-sensing pathways (TOR, AMPK, etc.)

The consistent expression of ST7 across dietary conditions but strong correlation with lifespan suggests it may function as a constitutive regulator whose activity is influenced by metabolic pathways without necessarily changing its expression levels .

What is the relationship between ST7 homolog (F11A10.5) and other known longevity factors?

The relationship between ST7 homolog (F11A10.5) and other longevity factors appears complex and context-dependent. In C. elegans, inhibition of st-7 has dramatically different effects depending on genetic background. While it causes a modest lifespan reduction in control worms, it completely abolishes the extended lifespan phenotype in germline-deficient glp-1 mutants . This suggests st-7 may function downstream of or parallel to the germline longevity pathway.

Unlike cathepsin D (Ctsd), another age-associated gene identified in mouse studies whose expression increases with age, ST7 expression remains stable throughout aging . This different pattern suggests these two genes likely influence aging through distinct mechanisms. The stability of ST7 expression over time, combined with its strong genetic determination (evidenced by cis-eQTLs), positions it as a potential constitutive regulator of aging processes rather than a biomarker of aging progression .

Future research should explore potential molecular interactions between ST7/F11A10.5 and established longevity pathways, including insulin/IGF-1 signaling, germline signaling, mitochondrial function, and proteostasis networks.

What are the best approaches for expressing and purifying recombinant F11A10.5 protein?

For expressing and purifying recombinant F11A10.5 protein, E. coli expression systems have proven effective for producing the full-length His-tagged protein (amino acids 1-536) . The following methodological approach is recommended:

• Expression system: Use BL21(DE3) E. coli strain with T7 promoter-based expression vectors for high-yield protein production

• Induction conditions: Optimize IPTG concentration (typically 0.1-1.0 mM) and induction temperature (16-37°C) to maximize soluble protein yield

• Purification strategy:

  • Primary purification: Immobilized metal affinity chromatography (IMAC) using Ni-NTA resin

  • Secondary purification: Size exclusion chromatography to remove aggregates and contaminants

  • Optional: Ion exchange chromatography for higher purity

• Buffer optimization: Screen various buffer conditions to maximize protein stability and solubility

When working with F11A10.5, researchers should be aware that as a full-length protein of 536 amino acids, it may present solubility challenges. Consider adding solubility-enhancing tags (e.g., MBP, SUMO) if the His-tag alone yields insufficient soluble protein. Verify protein identity and integrity through mass spectrometry and western blotting before proceeding to functional studies.

What methods are most effective for studying F11A10.5 function in aging studies?

For studying F11A10.5 function in aging studies, a multi-organism approach combining C. elegans genetics with mammalian cell culture and mouse models has proven most informative. Key methodological considerations include:

• C. elegans approaches:

  • RNAi knockdown in different genetic backgrounds (wild-type, daf-2, glp-1) to assess lifespan effects

  • CRISPR/Cas9 gene editing for creating null or point mutations

  • Tissue-specific and temporal knockdown/overexpression to dissect site of action

  • Phenotypic analysis beyond lifespan (healthspan measures, stress resistance, etc.)

• Mammalian systems:

  • Genetic manipulation of ST7 in cell culture models of senescence

  • Analysis in mouse models with varying ST7 expression levels

  • Tissue-specific conditional knockout models

• Multi-omic profiling:

  • Transcriptome analysis to identify downstream effectors

  • Proteomics to identify interacting partners

  • Metabolomics to assess effects on cellular metabolism

Given the strong association between ST7 expression and expected lifespan in mouse models, careful quantification of expression levels across tissues is crucial . Additionally, the dramatic effect of st-7 inhibition on glp-1 mutant lifespan suggests examining interactions with germline signaling pathways may be particularly informative .

What techniques can be used to identify proteins that interact with F11A10.5?

Several complementary techniques can be effectively employed to identify proteins that interact with F11A10.5:

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

  • Use His-tagged recombinant F11A10.5 as bait

  • Pull-down experiments with tissue or cell lysates

  • MS identification of co-purifying proteins

  • Quantitative comparison with appropriate controls to filter non-specific binders

• Yeast two-hybrid (Y2H) screening:

  • Screen F11A10.5 against C. elegans or mammalian cDNA libraries

  • Confirm interactions with directed Y2H assays

  • Validate with orthogonal methods

• BioID or APEX proximity labeling:

  • Express F11A10.5 fused to BioID2 or APEX2 in cells

  • Identify proteins in spatial proximity through biotinylation

  • Particularly useful for identifying transient or weak interactions

• Co-immunoprecipitation (Co-IP):

  • Use antibodies against F11A10.5 or epitope tags

  • Western blot analysis for candidate interactors

  • MS analysis for unbiased interactome mapping

• Genetic interaction screening:

  • RNAi or CRISPR screens for genes that modify F11A10.5-associated phenotypes

  • Particularly valuable in C. elegans where genome-wide RNAi is feasible

For F11A10.5 specifically, focusing on interactions with known longevity pathway components would be prudent given its effects on lifespan in C. elegans and correlation with longevity in mice .

How can researchers effectively compare F11A10.5 functions across different model organisms?

Effectively comparing F11A10.5 functions across different model organisms requires a carefully designed comparative biology approach:

• Sequence-function analysis:

  • Conduct detailed sequence alignments of F11A10.5/ST7 across species

  • Identify conserved domains and motifs

  • Generate domain-specific mutants to test functional conservation

• Cross-species complementation:

  • Express mammalian ST7 in C. elegans st-7 mutants to test functional rescue

  • Express C. elegans F11A10.5 in mammalian cells with ST7 knockdown

• Parallel phenotypic analysis:

  • Conduct lifespan studies in multiple models (C. elegans, Drosophila, mice)

  • Assess consistent phenotypes across species (e.g., stress resistance, metabolic parameters)

  • Compare tissue-specific functions

• Conserved pathway analysis:

  • Identify if F11A10.5/ST7 interacts with evolutionarily conserved longevity pathways

  • Compare transcriptional responses to F11A10.5/ST7 modulation across species

Given that ST7 shows strong expression correlation across tissues and studies in mouse models (median r ~ 0.50) and that F11A10.5 has a dramatic effect on longevity pathways in C. elegans, focusing on conserved longevity mechanisms would be most informative . The observed inverse correlation between ST7 expression and lifespan in mice parallels findings in C. elegans, suggesting a conserved function worth exploring systematically .

How should researchers interpret conflicting lifespan data regarding F11A10.5/ST7?

When interpreting seemingly conflicting lifespan data regarding F11A10.5/ST7, researchers should consider several key factors:

• Genetic background effects:

  • In C. elegans, st-7 inhibition had dramatically different effects in different backgrounds (modest reduction in spe-9 controls vs. complete suppression of extended lifespan in glp-1 mutants)

  • This suggests context-dependent functions that may explain apparent contradictions

• Dosage sensitivity:

  • Complete knockout versus partial knockdown may yield different results

  • The correlation between ST7 expression levels and lifespan in mice suggests a dose-dependent rather than binary effect

• Temporal considerations:

  • Developmental versus adult-specific manipulation may have opposite effects

  • Chronic versus acute modulation may engage different compensatory mechanisms

• Tissue-specific effects:

  • The ubiquitous expression of ST7 across tissues suggests potential for tissue-specific functions

  • Effects in one tissue may oppose effects in others

A particularly informative case is the apparently contradictory finding that st-7 inhibition reduces lifespan in control worms but higher ST7 expression correlates with shorter lifespan in mice . This suggests species-specific differences or potentially U-shaped response curves where both too much and too little expression is detrimental. Researchers should design experiments with careful controls and multiple genetic backgrounds to resolve such contradictions.

What statistical approaches are most appropriate for analyzing F11A10.5 expression data in longevity studies?

When analyzing F11A10.5 expression data in longevity studies, several statistical approaches are particularly appropriate:

• Survival analysis:

  • Kaplan-Meier survival curves with log-rank tests for comparing lifespan distributions

  • Cox proportional hazards models to quantify effect size while controlling for covariates

  • Quantile regression to analyze effects on specific portions of the lifespan distribution

• Expression-phenotype correlation:

  • Spearman rank correlation for non-parametric assessment of expression-lifespan relationships

  • In mouse studies, ST7 showed strong correlation with strain median lifespan

• Multi-factor analysis:

  • ANOVA or linear mixed models to assess effects of multiple factors (genotype, diet, age) and their interactions

  • Principal component analysis to identify patterns in multi-omic datasets

• Genetic mapping approaches:

  • QTL analysis to identify genomic regions associated with expression variation

  • ST7 shows significant cis-eQTLs in BXD mouse strains

• Causal inference methods:

  • Mediation analysis to test if F11A10.5/ST7 mediates effects of other factors on lifespan

  • Stability selection techniques as used in the mouse aging study

The approach used in the BXD mouse study demonstrates effective statistical handling, where stability selection combined with regression analysis was used to identify candidates like ST7 that consistently correlated with lifespan across multiple independent variables (diet, age, genotype) .

How can researchers distinguish direct versus indirect effects of F11A10.5 on longevity pathways?

Distinguishing direct versus indirect effects of F11A10.5 on longevity pathways requires careful experimental design and causal inference approaches:

• Temporal manipulation studies:

  • Utilize inducible expression/inhibition systems (e.g., temperature-sensitive or drug-inducible)

  • Establish time course of molecular and phenotypic changes following F11A10.5 modulation

  • Early molecular changes are more likely to represent direct effects

• Epistasis analysis:

  • Conduct double mutant/RNAi experiments with known longevity pathway components

  • Determine whether F11A10.5 acts upstream, downstream, or parallel to known factors

  • The dramatic effect of st-7 inhibition on glp-1 mutants suggests a potential pathway intersection

• Biochemical approaches:

  • Identify direct protein-protein interactions or enzymatic activities

  • Reconstitute potential signaling pathways in vitro

  • Test direct regulatory relationships on target genes

• Multi-omic data integration:

  • Integrate transcriptomic, proteomic, and metabolomic data

  • Use network analysis to distinguish proximal from distal effects

  • Apply causal inference statistical methods like those used in the BXD mouse study

• Tissue-specific analyses:

  • Use tissue-specific manipulation to identify primary site(s) of action

  • Track cell-non-autonomous effects that propagate from primary sites

Given the strong genetic determination of ST7 expression (cis-eQTLs) and its stable expression across aging, focusing on constitutive pathway interactions rather than age-dependent changes may be most productive for understanding its role in longevity regulation .

What are the implications of F11A10.5/ST7 expression patterns across tissues for aging research?

The ubiquitous and consistent expression patterns of F11A10.5/ST7 across tissues have several important implications for aging research:

• Systemic regulation of aging:

  • The relatively constant expression across tissues suggests ST7 may function as a systemic regulator of aging processes

  • Unlike tissue-specific factors, it may coordinate aging across multiple systems

• Genetic determination of aging rate:

  • The strong genetic control of ST7 expression (evidenced by cis-eQTLs) and correlation with strain lifespan suggests it may contribute to heritable aspects of longevity

  • This positions ST7/F11A10.5 as a potential determinant of species-specific or strain-specific lifespan

• Constitutive versus adaptive aging mechanisms:

  • Unlike genes that change expression with age (e.g., Ctsd), ST7 maintains stable expression throughout the lifespan

  • This suggests it may represent a "set point" for aging rate rather than an adaptive response to aging

• Tissue coordination:

  • The correlation of ST7 expression across tissues (median r ~ 0.50) suggests coordinated regulation

  • This may indicate roles in inter-tissue communication relevant to aging

• Conserved longevity mechanisms:

  • The strong conservation from C. elegans to mammals suggests ancient evolutionary roles in lifespan determination

  • The parallel findings in mice (expression-lifespan correlation) and worms (lifespan effects) support conserved functions

Researchers should consider these patterns when designing experiments, potentially focusing on how a constitutively expressed factor like ST7/F11A10.5 could regulate age-related processes without itself changing over time.

What are the most promising future research directions for F11A10.5/ST7 in aging studies?

The most promising future research directions for F11A10.5/ST7 in aging studies include:

• Mechanistic investigations:

  • Determine the biochemical function of F11A10.5/ST7 protein

  • Identify direct interaction partners and signaling pathways

  • Elucidate how it intersects with established longevity pathways, particularly germline signaling given the dramatic effects in glp-1 mutants

• Therapeutic potential:

  • Evaluate whether pharmacological modulation of ST7 activity could impact aging processes

  • Investigate if natural compounds or dietary factors influence ST7 function

  • Assess potential tissue-specific interventions

• Biomarker development:

  • Explore the potential of ST7 expression levels as a biomarker for biological age or longevity prediction

  • The strong correlation between ST7 expression and expected lifespan in mouse models suggests predictive potential

• Evolutionary perspectives:

  • Compare F11A10.5/ST7 function across multiple species beyond C. elegans and mice

  • Investigate if ST7 contributes to differences in longevity between related species

• Integration with other aging hallmarks:

  • Determine how ST7/F11A10.5 relates to established hallmarks of aging (proteostasis, nutrient sensing, etc.)

  • Investigate potential roles in systemic aging coordination

The combination of genetic evidence from both invertebrate and vertebrate models positions F11A10.5/ST7 as a particularly promising target for understanding fundamental aging mechanisms that may be conserved across evolution .

How might research on F11A10.5/ST7 contribute to broader understanding of aging mechanisms?

Research on F11A10.5/ST7 has significant potential to contribute to our broader understanding of aging mechanisms in several key ways:

• Bridging germline and somatic aging:

  • The dramatic suppression of germline-mediated longevity extension by st-7 inhibition in C. elegans suggests it may link reproductive and somatic aging processes

  • This could provide insights into the evolutionary trade-offs between reproduction and longevity

• Genetic determinants of species lifespan:

  • The strong genetic control of ST7 expression and its correlation with strain-specific lifespan suggest it may contribute to heritable aspects of longevity

  • Understanding such factors may help explain why different species and individuals age at different rates

• Constitutive versus adaptive aging mechanisms:

  • Unlike genes that change expression with age, ST7 maintains stable expression throughout lifespan

  • This represents a different class of aging regulators than the more commonly studied age-responsive genes

• Systems integration in aging:

  • The consistent expression across tissues suggests potential roles in coordinating aging processes across the organism

  • This may provide insights into how aging is synchronized across different tissues and systems

• Evolutionary conservation of aging pathways:

  • The parallel findings in C. elegans and mice suggest ST7/F11A10.5 represents an evolutionarily ancient aging mechanism

  • This could help identify the core, conserved pathways that regulate aging across diverse species