Recombinant Human Fibroblast growth factor 19 (FGF19), partial (Active)

What is the structural composition of recombinant human FGF19?

Recombinant human FGF19 is typically derived from E. coli expression systems spanning amino acids Leu25-Lys216 of the native protein. The full-length human FGF19 consists of a 251 amino acid precursor with a 22-amino acid signal peptide and a 229-amino acid secreted mature protein without N-linked glycosylation sites . The protein contains critical structural elements including the N-terminal region (residues 38-42) and heparin-binding regions that significantly influence its receptor specificity and biological activity .

How does FGF19 differ from other members of the FGF family?

FGF19 belongs to the unique FGF19 subfamily that functions as endocrine hormones rather than typical paracrine factors. Unlike most FGFs that activate multiple FGF receptors, FGF19 exhibits remarkable specificity for FGFR4 . While many FGF family members require heparin/heparan sulfate for receptor activation, FGF19 can activate receptors in both heparin-dependent and βKlotho-dependent manners. FGF19 shares approximately 61% amino acid identity with chicken FGF-19 and 51% with murine FGF-15, which is considered its functional ortholog in mice .

What are the primary biological activities of FGF19?

FGF19 demonstrates dual biological activities:

These distinct activities operate through separate structural elements and receptor activation pathways, enabling researchers to potentially separate these functions through targeted mutations .

How should recombinant FGF19 be reconstituted and stored for optimal activity?

For optimal reconstitution of lyophilized FGF19:

• For carrier-containing FGF19: Reconstitute at 100 μg/mL in sterile PBS containing at least 0.1% human or bovine serum albumin .

• For carrier-free FGF19: Reconstitute at 100 μg/mL in sterile PBS .

Storage recommendations:

• Store the reconstituted protein at -20°C to -80°C

• Use a manual defrost freezer

• Avoid repeated freeze-thaw cycles as they may compromise protein activity

• Consider preparing single-use aliquots for long-term experiments

Proper reconstitution and storage are critical for maintaining FGF19 functionality in receptor activation assays, cell proliferation studies, and metabolic experiments.

What are the validated biological assays for measuring FGF19 activity?

Several assays can be employed to assess distinct FGF19 activities:

• Receptor Activation Assays: ERK phosphorylation in L6 cells transfected with specific FGFRs (with or without βKlotho) provides a direct measure of receptor activation. Western blot analysis can quantify phospho-ERK levels as an indicator of downstream signaling .

• Metabolic Activity Assays:

  • Glucose uptake assays in adipocytes

  • In vivo glucose tolerance tests in diabetic mouse models (e.g., ob/ob)

  • Measurement of serum glucose and insulin levels after FGF19 administration

• Mitogenic Activity Assays:

  • BrdU incorporation assays in liver sections to measure hepatocyte proliferation

  • Histopathological examination focusing on pericentral hepatocytes

• Binding Assays:

  • Solid-phase binding assays to measure interaction with FGFRs and co-receptors

  • Surface Plasmon Resonance (SPR) for quantitative binding kinetics

Each assay should include appropriate controls to distinguish FGF19-specific effects from background activity.

What are appropriate in vivo models for studying FGF19 metabolic functions?

When designing in vivo experiments with FGF19, consider these validated models:

• Diabetic mouse models:

  • ob/ob mice: Effective for studying glucose homeostasis effects

  • High-fat diet-induced diabetic models: Useful for investigating insulin resistance

• Administration protocols:

  • Injection routes: Intraperitoneal or intravenous administration is typically used

  • Dosing: 1-5 mg/kg body weight is commonly employed in published studies

  • Timing: Acute (single dose) or chronic (daily dosing for 1-3 weeks) depending on the research question

• Assessment parameters:

  • Fasting blood glucose and insulin levels

  • Glucose tolerance test (GTT)

  • Insulin tolerance test (ITT)

  • Liver enzyme profiles

  • Changes in gene expression related to glucose metabolism

When conducting these studies, researchers should carefully monitor for potential mitogenic effects on hepatocytes, particularly in chronic administration protocols.

How do carrier proteins affect FGF19 activity in different experimental systems?

The presence of carrier proteins like Bovine Serum Albumin (BSA) has significant implications for FGF19 experiments:

• Stability considerations:

  • BSA enhances protein stability, increases shelf-life, and allows storage at more dilute concentrations

  • Carrier-free preparations may be less stable and require more careful handling

• Experimental interference:

  • BSA may interfere with certain assay systems, particularly those involving protein quantification, immunodetection, or where background protein could complicate results

  • For proteomic applications or mass spectrometry, carrier-free versions are strongly recommended

• Receptor binding studies:

  • For precise binding kinetics measurements, carrier-free preparations provide more accurate data

  • For cell-based assays focusing on physiological responses rather than binding, carrier-containing preparations may provide more consistent results

When reporting research findings, the specific preparation used (carrier-free vs. with carrier) should be clearly documented as it may influence experimental outcomes and reproducibility.

What are the critical quality control parameters for verifying FGF19 functionality before experiments?

Before conducting experiments, verify FGF19 quality through these key assessments:

• Biological activity testing:

  • ERK phosphorylation assay in receptor-transfected cells (e.g., L6 cells with FGFR1c/βKlotho)

  • Minimum activity threshold should be established for each new lot

• Protein integrity verification:

  • SDS-PAGE to confirm molecular weight (~24 kDa) and purity

  • Western blotting with specific anti-FGF19 antibodies

• Endotoxin testing:

  • Limulus Amebocyte Lysate (LAL) assay to ensure endotoxin levels are below 1 EU/μg protein

  • Critical for in vivo applications and primary cell culture experiments

• Aggregation assessment:

  • Dynamic light scattering or size-exclusion chromatography to detect potential protein aggregation

  • Important after reconstitution and during storage

Documenting these quality control measures enhances experimental reproducibility and facilitates accurate interpretation of results.

How can researchers distinguish between FGF19 and FGF21 effects in experimental systems?

Differentiating the effects of these related proteins requires specific experimental approaches:

• Receptor specificity exploitation:

  • FGF19 activates FGFR4 strongly, while FGF21 does not

  • Experiments in FGFR4-knockout systems can help distinguish FGF19-specific effects

  • Compare responses in cells with different FGFR expression profiles

• Structural variant utilization:

  • Use chimeric proteins like those described in research (e.g., FGF19-4, FGF19-5) that specifically lack FGFR4 activation capacity but retain metabolic functions

  • These can help separate metabolic from proliferative effects

• Downstream signaling analysis:

  • Monitor receptor-specific signaling pathways

  • Quantify differential gene expression profiles induced by each protein

• Combinatorial approaches:

  • Use specific receptor antagonists alongside FGF19/FGF21 treatment

  • Employ RNA interference to selectively knock down specific receptors

A comprehensive approach combining these methods provides the most reliable differentiation between FGF19 and FGF21 biological activities.

How can researchers separate the metabolic benefits of FGF19 from its potentially harmful mitogenic effects?

Based on structural studies, researchers have successfully developed FGF19 variants with differential activities:

• Strategic mutagenesis approaches:

  • Modify the N-terminal region (residues 38-42): Replace FGF19's 38WGDPI42 with FGF21's 41GQV43

  • Modify heparin-binding domains: Target β1-β2 loop and the β10–β12 segment

  • Combined mutations in both regions most effectively eliminate mitogenic activity while preserving metabolic benefits

• Validated chimeric constructs:
  The following engineered variants have shown separated activities:

  Variant	Modifications	FGFR1c/βKlotho Activation	FGFR4 Activation	Metabolic Activity	Mitogenic Activity
  FGF19-4	N-terminal + β1-β2 loop	Preserved	Abolished	Preserved	Abolished
  FGF19-5	N-terminal + β10–β12	Preserved	Abolished	Preserved	Abolished
  FGF19-6	N-terminal + both HBS regions	Preserved	Abolished	Preserved	Abolished

  These variants maintain glucose-regulating effects without promoting hepatocyte proliferation .

• Experimental validation:

  • Confirm receptor activation profiles in transfected L6 cells

  • Verify metabolic activity through glucose uptake assays and in vivo glucose measurements

  • Assess proliferative potential using BrdU incorporation in liver sections

This strategic engineering approach demonstrates the feasibility of developing FGF19-based therapeutics with improved safety profiles.

What are the molecular mechanisms underlying FGF19's receptor specificity compared to other FGF family members?

FGF19's unique receptor interactions involve multiple structural elements:

• Key structural determinants:

  • N-terminal region (residues 38-42): Critical for FGFR4 interaction and specificity

  • Heparin-binding surface (HBS): Contributes to both heparin-dependent and βKlotho-dependent FGFR4 activation

  • These regions work independently but cooperatively

• Receptor interaction model:

  • The five residues (38WPDPI42) likely directly contact the βC′-βE loop of the receptor D3 domain

  • This region has been associated with receptor specificity determination in paracrine-acting FGFs

  • Structural modeling suggests the extended HBS might interact directly with the receptor

• Co-receptor dependencies:

  • Unlike most FGFs, FGF19 can activate FGFR4 in either a heparin-dependent or βKlotho-dependent manner

  • The βKlotho co-receptor provides specificity for endocrine FGFs (FGF19, FGF21, FGF23)

  • FGF19/βKlotho interaction involves distinct structural determinants from traditional FGF/heparin interactions

Understanding these molecular mechanisms enables rational design of FGF19 variants with tailored receptor activation profiles for specific research or therapeutic applications.

How do FGF19 mutations impact its functional activities in experimental systems?

Structural studies have revealed how specific mutations alter FGF19 functionality:

These mutation studies provide a structural and functional framework for understanding the molecular basis of FGF19 activity, enabling rational design of variants with specific activity profiles.

What are common pitfalls in FGF19 experimental design and how can they be avoided?

Researchers should be aware of these frequent challenges:

• Receptor expression variability in cell models:

  • Problem: Inconsistent results due to varying FGFR expression levels between cell lots

  • Solution: Quantify receptor expression in each cell lot; consider using transfected L6 cells with controlled receptor expression for consistent results

• βKlotho dependency misinterpretation:

  • Problem: Failing to account for βKlotho's role in receptor activation

  • Solution: Include controls with and without βKlotho; verify βKlotho expression in cell models

• Protein storage and stability issues:

  • Problem: Activity loss due to improper handling

  • Solution: Use carrier proteins for stability; prepare single-use aliquots; verify activity before key experiments

• Confounding factors in in vivo experiments:

  • Problem: Background metabolic variability masking FGF19 effects

  • Solution: Use age/sex-matched animals; control feeding status; include appropriate vehicle controls

• Specificity validation:

  • Problem: Attributing non-specific effects to FGF19

  • Solution: Include inactive FGF19 mutants as controls; validate with receptor antagonists or knockdown approaches

Addressing these common pitfalls proactively improves experimental reproducibility and data quality.

How should researchers interpret contradictory results between in vitro and in vivo FGF19 studies?

When facing discrepancies between experimental systems:

• Physiological complexity considerations:

  • In vivo systems involve multiple cell types, metabolic interactions, and compensatory mechanisms

  • Cell-specific responses may be diluted or enhanced in whole organism context

• Systematic reconciliation approach:

  • Compare dosing: In vitro concentrations often exceed physiological levels

  • Examine timing differences: Acute vs. chronic exposure effects

  • Consider pharmacokinetics: Protein stability and distribution differ significantly between systems

  • Evaluate model appropriateness: Some cell lines may lack key signaling components

• Bridging strategies:

  • Use ex vivo approaches (e.g., primary hepatocytes, liver slices) to bridge the gap

  • Employ tissue-specific conditional knockout models to isolate target tissue responses

  • Consider organoid models that better recapitulate tissue architecture

• Technical validation:

  • Confirm protein activity in both systems using the same lot

  • Verify target engagement through receptor phosphorylation or downstream signaling markers

Careful analysis of these factors can often resolve apparent contradictions between experimental systems.

What advanced analytical approaches can resolve complex FGF19 signaling questions?

For investigating nuanced aspects of FGF19 biology:

• Receptor-specific signaling discrimination:

  • Phosphoproteomic profiling to identify differential phosphorylation events

  • Temporal signaling analysis to detect differences in activation kinetics

  • CRISPR-based receptor editing to create clean systems for pathway analysis

• Structural biology approaches:

  • Cryo-electron microscopy of FGF19-FGFR-cofactor complexes

  • Hydrogen-deuterium exchange mass spectrometry to map interaction surfaces

  • Computational modeling to predict effects of mutations on receptor interaction

• Single-cell analysis methods:

  • Single-cell RNA sequencing to identify cell-specific responses

  • Live-cell imaging with FRET-based sensors for real-time signaling visualization

  • Digital spatial profiling to map tissue-specific responses in heterogeneous samples

• Multi-omics integration:

  • Combined transcriptomic, proteomic and metabolomic analyses

  • Network biology approaches to map signaling cascades

  • Machine learning algorithms to identify signaling signatures

These advanced approaches can uncover subtle but important aspects of FGF19 biology that conventional methods might miss, providing deeper mechanistic insights.

What are the emerging applications of engineered FGF19 variants in metabolic disease research?

Engineered FGF19 variants offer promising research avenues:

• Therapeutic potential exploration:

  • Non-mitogenic variants (e.g., FGF19-4, FGF19-5, FGF19-6) provide tools to study metabolic benefits without cancer risk

  • These variants enable longer-term studies of FGF19's effects on obesity, diabetes, and NAFLD

• Tissue-specific targeting strategies:

  • Engineering receptor-specific variants to target particular tissues

  • Developing tissue-specific delivery methods for FGF19 variants

• Combination therapy models:

  • Investigating synergistic effects with established anti-diabetic agents

  • Exploring potential in resistant disease models

• Translational potential assessment:

  • Evaluation in humanized mouse models

  • Comparative studies across species to predict human responses

These applications may lead to both improved research tools and potential therapeutic candidates for metabolic disorders.

How can advanced imaging techniques enhance our understanding of FGF19 biology?

Modern imaging approaches offer unique insights:

• In vivo molecular imaging applications:

  • PET imaging with labeled FGF19 variants to track tissue distribution

  • Intravital microscopy to observe cellular responses in real time

  • CLARITY-based whole-organ imaging to map receptor distribution

• Subcellular localization studies:

  • Super-resolution microscopy to track receptor-ligand interactions

  • Live-cell confocal imaging to monitor receptor trafficking

  • FRAP (Fluorescence Recovery After Photobleaching) to study binding dynamics

• Functional imaging approaches:

  • Calcium imaging to monitor immediate signaling responses

  • Biosensor-based imaging to track metabolic changes in real-time

  • Label-free imaging technologies to study conformational changes

These techniques provide spatial and temporal information about FGF19 activity that complements traditional biochemical and molecular approaches.

What computational approaches can advance FGF19 research?

Computational methods offer powerful tools for FGF19 investigation:

• Structural prediction and analysis:

  • Molecular dynamics simulations to predict effects of mutations

  • Protein-protein docking to model receptor interactions

  • AlphaFold2 and similar AI approaches to predict structural features

• Systems biology frameworks:

  • Pathway modeling to predict effects of FGF19 in complex metabolic networks

  • Multi-scale modeling to bridge molecular and physiological effects

  • Agent-based models to simulate tissue-level responses

• Machine learning applications:

  • Predictive models for FGF19 variant activity based on sequence

  • Pattern recognition in complex datasets to identify response biomarkers

  • Deep learning approaches to integrate multi-omics data

These computational strategies can accelerate hypothesis generation, experimental design, and data interpretation in FGF19 research.