Recombinant Mouse Folliculin-interacting protein 2 (Fnip2), partial

What is the molecular structure and functional domains of mouse Fnip2?

Mouse Fnip2 is a paralogous protein that forms complexes with Folliculin (FLCN) and Fnip1. The protein contains several conserved regions that are critical for its binding interactions. Optimal binding of FLCN to FNIP proteins requires intact conserved blocks 2-5, as demonstrated in binding assays. Deletion mutants containing residues 300-1166 (lacking only conserved block 1) still maintain FLCN binding capacity, indicating that these four conserved regions (blocks 2-5) are essential for proper conformation and interaction with FLCN . When designing experiments with recombinant Fnip2, ensure that these conserved domains remain intact to preserve functional interactions.

How does mouse Fnip2 expression vary across different tissues?

Table 1: Relative Expression Levels of Fnip1 vs. Fnip2 in Mouse Tissues

What are the optimal conditions for expressing and purifying recombinant mouse Fnip2?

For successful expression and purification of recombinant mouse Fnip2:

• Expression system selection: Mammalian expression systems (HEK293 or CHO cells) are preferred over bacterial systems due to the requirement for proper eukaryotic post-translational modifications, particularly phosphorylation events that regulate Fnip2 function.

• Construct design: Include a fusion tag (His, GST, or FLAG) to facilitate purification while ensuring that the tag doesn't interfere with the C-terminus, which is critical for FLCN interaction .

• Purification protocol: Use a two-step purification process combining affinity chromatography and size-exclusion chromatography to obtain highly pure protein preparations.

• Buffer optimization: Maintain protein stability in buffers containing 20-50 mM Tris-HCl (pH 7.4-8.0), 150 mM NaCl, 1-5% glycerol, and protease inhibitors. AMPK inhibitors should be excluded during purification if studying native phosphorylation states.

How can I verify the functional activity of purified recombinant Fnip2?

Verification of recombinant Fnip2 functionality can be accomplished through multiple complementary approaches:

• Binding assays with FLCN: In vitro pull-down assays using recombinant FLCN can confirm binding capacity. Full-length Fnip2 should demonstrate optimal binding compared to truncated variants .

• AMPK interaction: Co-immunoprecipitation assays can verify Fnip2 interaction with AMPK complexes, which is essential for its role in metabolic regulation.

• Functional complementation: Introducing recombinant Fnip2 into Fnip1/Fnip2 null mouse embryonic fibroblasts (MEFs) should suppress elevated Ppargc1a mRNA levels and normalize ATP production, similar to what has been demonstrated with FNIP1 and FNIP2 expression in these cells .

• Phosphorylation analysis: Phosphorylation of recombinant Fnip2 by AMPK in vitro provides further functional validation, as this post-translational modification is critical for its biological activity.

What detection methods are most effective for analyzing mouse Fnip2 in experimental samples?

For sensitive and specific detection of mouse Fnip2:

• Western blotting: Use antibodies targeting conserved epitopes within blocks 2-5. Consider phospho-specific antibodies if investigating regulatory phosphorylation events.

• Immunoprecipitation: For protein complex analysis, perform sequential immunoprecipitation targeting first Fnip2 and then FLCN to isolate the specific complex.

• Immunofluorescence: When localizing Fnip2 in cellular contexts, consider co-staining with FLCN and organelle markers to assess physiological distribution.

• mRNA quantification: For expression analysis, droplet digital PCR (ddPCR) provides absolute quantification of Fnip2 mRNA, allowing direct comparison with Fnip1 levels across tissues .

How does Fnip2 interact with FLCN and what regions are critical for this interaction?

Fnip2, like its paralog Fnip1, binds to the C-terminus of FLCN. This interaction is functionally significant as mutations in BHD patients are predicted to produce C-terminally truncated FLCN proteins unable to bind Fnip1 or Fnip2, compromising FLCN function and leading to the BHD phenotype . The optimal binding of FLCN to Fnip proteins requires four conserved regions (blocks 2-5) of the Fnip protein, likely for proper conformation. When designing experiments to study this interaction:

• Use full-length recombinant proteins for maximum binding efficiency

• Consider the impact of mutations or truncations on complex formation

• Evaluate binding under varying physiological conditions that might affect complex stability

What is the relationship between Fnip2 and AMPK signaling?

Fnip2 forms part of a complex that interacts with AMPK, influencing energy and nutrient sensing pathways. Research indicates that:

• Fnip2 is phosphorylated by AMPK, and this phosphorylation is reduced by AMPK inhibitors

• The FLCN-FNIP complex appears to function downstream of AMPK, as AMPK activation by 2-deoxyglucose can suppress mTOR activity even in FLCN-null cells

• Contradictory reports exist regarding whether the FLCN/FNIP complex positively or negatively regulates AMPK

When designing experiments to investigate this relationship, consider using AMPK activators (AICAR, metformin) and inhibitors (Compound C, AraA) to modulate the pathway and observe effects on Fnip2 phosphorylation and complex formation.

How do Fnip1 and Fnip2 cooperate or compensate for each other in different tissues?

The functional redundancy between Fnip1 and Fnip2 varies significantly across tissues and is correlated with their relative expression levels:

• In kidney tissue, where expression levels of both proteins are comparable, either Fnip1 or Fnip2 can compensate for the other's absence, and only double inactivation produces enlarged polycystic kidneys .

• In tissues with dominant Fnip1 expression (bone marrow, myocardium, skeletal muscle), Fnip1 deficiency alone is sufficient to produce phenotypes similar to those seen in Flcn-deficient animals .

• Experimental evidence demonstrates that expression of either FNIP1 or FNIP2 in Fnip1/Fnip2 null mouse embryonic fibroblasts (MEFs) suppresses Ppargc1a mRNA and normalizes ATP production, confirming their functional redundancy at the cellular level .

When designing tissue-specific studies, consider the relative expression levels of Fnip1 and Fnip2 in your target tissue to properly interpret phenotypes.

How does Fnip2 contribute to kidney tumor suppression in conjunction with FLCN and Fnip1?

Fnip2 plays a critical role in kidney tumor suppression in concert with FLCN and Fnip1. Research findings demonstrate:

• Kidney-targeted Fnip1/Fnip2 double inactivation produces enlarged polycystic kidneys with hyperplastic cells protruding into cystic lumens, with significantly increased kidney/body weight ratio (11.04%, P<0.001) .

• While homozygous deletion of either Fnip1 or Fnip2 alone does not cause kidney tumors, compound heterozygous knockdown of Fnip1 with homozygous knockdown of Fnip2 leads to kidney cancer development .

• The kidney phenotype in Fnip1/Fnip2 double-deficient mice mimics that of kidney-specific Flcn inactivation, and combining all three deletions does not further augment kidney pathology, suggesting they function in the same pathway .

For researchers investigating kidney tumor models, these findings highlight the importance of considering both Fnip proteins and their redundant functions when designing gene knockout experiments.

What role does Fnip2 play in metabolic regulation and mTOR signaling?

Fnip2, as part of the FLCN-FNIP complex, influences metabolic regulation through:

• Modulation of mTOR signaling: FLCN phosphorylation is diminished by rapamycin (an mTOR inhibitor) and amino acid starvation, suggesting that the FLCN-FNIP complex is regulated by mTOR signaling .

• AMPK-mediated energy sensing: Fnip2 interacts with AMPK, potentially serving as a substrate and regulator of this key energy sensor .

• Tissue-specific metabolic responses: The response to metabolic stressors (serum starvation, amino acid deprivation) differs between FLCN-null and FLCN-restored cells, suggesting FLCN-FNIP complex involvement in stress adaptation .

When designing experiments to investigate these pathways, consider using metabolic modulators (rapamycin, amino acid starvation, 2-deoxyglucose) to perturb the system and observe Fnip2-dependent responses.

How can recombinant Fnip2 be used in drug discovery for Birt-Hogg-Dubé syndrome?

Recombinant Fnip2 can be utilized in drug discovery platforms targeting Birt-Hogg-Dubé syndrome through several approaches:

• High-throughput screening assays: Develop binding assays to identify compounds that stabilize mutant FLCN-FNIP2 interactions.

• Functional reconstitution: Assess whether candidate compounds can restore normal FLCN-FNIP complex function in FLCN-mutant cell lines.

• Pathway modulation: Screen for compounds that normalize dysregulated AMPK/mTOR signaling in BHD models.

• Structure-based drug design: Utilize structural information about the FLCN-FNIP interface to design molecules that mimic binding interactions lost through disease-causing mutations.

When developing such platforms, consider the varying expression levels of Fnip1 versus Fnip2 in different tissues, as therapeutic approaches may need to target tissue-specific pathways.

How can I reconcile contradictory data regarding the role of Fnip2 in AMPK regulation?

Contradictory reports exist regarding whether the FLCN/FNIP complex positively or negatively regulates AMPK. To address these inconsistencies:

• Consider tissue specificity: AMPK regulation by the FLCN-FNIP complex may be tissue-dependent, with different outcomes in skeletal muscle versus kidney tissue .

• Evaluate experimental conditions: The metabolic state of the cells (nutrient availability, energy stress) significantly impacts AMPK activity and may explain divergent results.

• Assess relative expression levels: The ratio of Fnip1 to Fnip2 varies across tissues and may influence regulatory outcomes.

• Examine temporal dynamics: Acute versus chronic manipulation of the FLCN-FNIP complex may yield different results due to compensatory mechanisms.

A systematic approach examining multiple readouts of AMPK activity (phospho-AMPK, phospho-ACC, ATP levels) across different tissues and conditions is needed to resolve these contradictions.

What are common pitfalls when analyzing phenotypes in Fnip2 knockout models?

When analyzing Fnip2 knockout models, researchers should be aware of several potential pitfalls:

• Functional redundancy: Due to overlap with Fnip1, single Fnip2 knockout may not display phenotypes in tissues where both proteins are expressed, necessitating double knockout models .

• Developmental compensation: Long-term genetic deletion may trigger compensatory pathways that mask acute phenotypes observable with inducible knockout systems.

• Tissue-specific effects: Phenotypes vary dramatically across tissues based on relative expression levels of Fnip1 and Fnip2, requiring tissue-specific analysis .

• Background strain influence: Genetic background can significantly influence phenotype penetrance and severity, requiring careful control selection.

• Incomplete knockout: Partial expression of truncated Fnip2 proteins may retain some function, confounding phenotypic analysis.

How should I interpret phosphorylation changes in Fnip2 under different experimental conditions?

Fnip2 phosphorylation is a key regulatory mechanism that responds to various cellular conditions:

• AMPK inhibitors (Compound C, AraA) reduce Fnip2 phosphorylation, indicating direct or indirect regulation by AMPK .

• mTOR inhibition (rapamycin) and nutrient starvation alter the phosphorylation pattern of the FLCN-FNIP complex .

• Multiple phosphorylation sites exist, with differential sensitivity to various kinase inhibitors.

When analyzing phosphorylation data:

• Use phospho-specific antibodies to distinguish specific sites

• Compare results across multiple time points to capture dynamic changes

• Consider the effects of cell density, nutrient availability, and stress conditions

• Validate with multiple approaches (Western blotting, mass spectrometry)

• Compare with known AMPK and mTOR pathway substrates as controls

What are emerging technologies for studying Fnip2 protein-protein interactions?

Advanced methodologies for investigating Fnip2 interactions include:

• Proximity labeling techniques (BioID, TurboID) to identify novel interaction partners in live cells.

• Hydrogen-deuterium exchange mass spectrometry (HDX-MS) to map protein-protein interaction interfaces at high resolution.

• Cryo-electron microscopy for structural analysis of the complete FLCN-FNIP-AMPK complex.

• Single-molecule FRET to observe dynamic interactions in real-time.

These approaches can provide insights beyond traditional co-immunoprecipitation methods, revealing transient or context-dependent interactions within the larger FLCN-FNIP complex.

How might tissue-specific functions of Fnip2 be leveraged for targeted therapeutics?

Understanding the tissue-specific functions of Fnip2 opens opportunities for targeted therapeutic approaches:

• Kidney-specific targeting: Since Fnip1 and Fnip2 show functional redundancy in kidneys, therapeutic strategies aiming to boost activity of the remaining paralog could compensate for loss of function.

• Metabolic modulation: Tissue-specific metabolic dependencies regulated by the FLCN-FNIP complex could be exploited to normalize dysregulated energy metabolism in BHD syndrome.

• Pathway-specific interventions: Differences in mTOR responses to nutrient stress between FLCN-null and FLCN-restored cells suggest potential therapeutic windows for pathway modulation .

Research should focus on identifying tissue-specific vulnerabilities created by Fnip2 dysfunction that could be therapeutically targeted.