TNF a Human, Sf9

What is TNF-α Human, Sf9 and how does it compare to native human TNF-α?

TNF-α Human, Sf9 refers to recombinant human Tumor Necrosis Factor alpha expressed in Spodoptera frugiperda 9 (Sf9) insect cells using a baculovirus expression vector system (BEVS). The mature form consists of amino acids 77-233 of the human TNF-α precursor . The amino acid sequence typically includes the mature human TNF-α sequence with a C-terminal His-tag (HHHHHH) for purification purposes, as seen in the sequence: "VRSSSRTPSDKPVAHVVANPQAEGQLQWLNRRANALLANGVELRDNQLVVPSEGLYLIYSQVLFKGQGCPSTHVLLTHTISRIAVSYQTKVNLLSAIKSPCQRETPEGAEAKPWYEPIYLGGVFQLEKGDRLSAEINRPDYLDFAESGQVYFGIIALHHHHH" . Functionally, TNF-α operates as a soluble homotrimer of approximately 17 kDa per monomer after proteolytic cleavage from its membrane-bound 26 kDa form . Unlike bacterial expression systems, the Sf9 system produces properly folded, soluble protein that more closely resembles the native conformation.

What are the optimal storage conditions for maintaining TNF-α activity?

For optimal preservation of biological activity, TNF-α Human, Sf9 should be stored according to these research-validated conditions:

• Short-term storage (2-4 weeks): 4°C in the original buffer

• Long-term storage: -20°C in aliquots to minimize freeze-thaw cycles

• Storage buffer typically comprises Phosphate Buffered Saline (pH 7.4) with 10% glycerol

• For extended storage periods, addition of a carrier protein (0.1% HSA or BSA) is strongly recommended to prevent adsorption to surfaces and maintain stability

• Multiple freeze-thaw cycles should be strictly avoided as they significantly reduce biological activity through protein denaturation

How is the biological activity of TNF-α Human, Sf9 assessed in laboratory settings?

Biological activity assessment of TNF-α Human, Sf9 typically employs:

• Cytotoxicity assays using sensitive cell lines:

  • Murine L929 fibroblast cells are the gold standard for TNF-α activity testing

  • Cells are typically sensitized with actinomycin D before TNF-α treatment

  • Cell viability is measured after 24-48 hours using MTT, WST-1, or other colorimetric assays

  • Activity is calculated based on the concentration required for 50% cytotoxicity (EC50)

• Anticancer activity evaluation:

  • Human cancer cell lines including Caco-2, HepG-2, and MCF-7 can be used to assess anticancer potential

  • Concentration-dependent cytotoxicity demonstrates biological function

  • Results are typically expressed as percent viability versus TNF-α concentration

• Inflammatory response induction:

  • Measurement of NF-κB activation in reporter cell lines

  • Assessment of downstream cytokine production (IL-6, IL-8, etc.)

  • Evaluation of adhesion molecule expression (ICAM-1, VCAM-1)

What techniques optimize the expression of soluble, biologically active TNF-α in Sf9 cells?

Optimization of TNF-α expression in Sf9 cells involves several critical methodological considerations:

How does cell-free expression compare with Sf9 expression for producing functional human TNF-α?

Cell-free protein synthesis (CFPS) represents an alternative platform with distinct advantages and limitations compared to Sf9 expression:

Cell-free expression shows remarkable speed advantages, producing up to 350 μg/mL in just 4 hours at 35°C, compared to the days required for Sf9 expression . Response surface methodology (RSM) analysis reveals that temperature and incubation time are critical parameters, with the lowest production (7.2 μg/mL) occurring at 6h/20°C and highest production at 4h/35°C . Both systems produce soluble, functionally active protein suitable for research applications, though the choice depends on specific research requirements.

What are the key steps in designing oligonucleotide primers for TNF-α gene assembly?

PCR-mediated gene assembly for TNF-α requires careful primer design following these methodological principles:

• Primer design strategy:

  • Design overlapping oligonucleotide primers covering the entire gene sequence

  • Optimal overlap length of 15-25 nucleotides between adjacent primers

  • Account for codon optimization for the expression system

  • Incorporate restriction sites at termini for subsequent cloning

• Assembly protocol:

  • Two-step PCR process: first assembling overlapping primers, then amplifying the full-length gene

  • Initial PCR includes all designed primers (typically 20 for TNF-α) at 5 pM concentration each

  • Use high-fidelity DNA polymerase with proofreading capability (e.g., Pfu DNA polymerase)

  • Cycling conditions: 35 cycles of 94°C (30s), 58°C (2min), 72°C (2min), followed by final extension at 72°C (10min)

• Verification and troubleshooting:

  • Agarose gel electrophoresis to confirm correct assembly size

  • Sequencing to verify the absence of mutations

  • If assembly fails, analyze primer design for potential secondary structures or problematic regions

How do structural and functional differences between Sf9-derived and E. coli-derived TNF-α affect experimental outcomes?

Understanding the differences between expression systems is crucial for experimental design:

• Structural differences:

  • Sf9-derived TNF-α is expressed as a soluble protein requiring no refolding

  • E. coli typically produces TNF-α in inclusion bodies requiring denaturation with harsh agents (8M urea) followed by complex refolding procedures

  • Sf9 expression supports proper disulfide bond formation and secondary structure

• Functional comparison:

  • Sf9-derived TNF-α demonstrates superior biological activity compared to E. coli-derived protein in standard cytotoxicity assays

  • Higher specific activity correlates with properly formed trimeric structure

  • Tag removal further enhances the biological activity of Sf9-derived TNF-α

• Experimental implications:

  • Higher potency of Sf9-derived TNF-α may require adjustment of working concentrations

  • More consistent lot-to-lot variability with Sf9 expression due to avoidance of refolding

  • Reduced endotoxin concerns with Sf9-derived material compared to E. coli expression

  • Improved stability in complex biological matrices for downstream applications

What is the relationship between TNF-α's role in normal skin physiology versus pathological conditions?

TNF-α demonstrates a complex dual role in skin biology:

• Physiological functions:

  • TNF-α promotes normal skin cell turnover through controlled apoptosis

  • Facilitates shedding of dead cells and stimulates proliferation of new ones

  • Contributes to immune surveillance and maintains skin's functional integrity

  • Supports normal wound healing and tissue remodeling

• Pathological involvement:

  • Dysregulation leads to abnormal skin cell turnover and hyperproliferation

  • Contributes to scaling and thickening conditions like psoriasis

  • Implicated in various inflammatory skin disorders including acne and hidradenitis suppurativa

  • Disrupts melanocyte function in vitiligo by downregulating key transcription factors (MITF) and receptors (MSH-R, MC1-R)

• Paradoxical effects:

  • While TNF-α overproduction drives inflammation in many conditions, it can also play protective roles

  • In vitiligo, TNF-α activates regulatory T-cells (T-regs) that secrete IL-10 and suppress immune activation

  • This dual nature explains why anti-TNF-α therapies may have variable or unexpected outcomes in different skin conditions

How can researchers troubleshoot TNF-α activity loss during purification and storage?

Activity loss is a common challenge requiring systematic troubleshooting:

• Purification-associated activity loss:

  • Monitor protein state at each purification step using analytical SEC

  • Optimize buffer conditions (pH, ionic strength, stabilizers) to maintain trimeric structure

  • Minimize exposure to extreme temperatures, pH values, or harsh chemicals

  • Consider utilizing mild elution conditions from affinity columns

• Storage-related activity loss:

  • Implement a stability program testing multiple storage conditions

  • Add protein stabilizers (trehalose, glycerol, carrier proteins) to prevent aggregation

  • Aliquot protein solutions to minimize freeze-thaw cycles

  • Consider lyophilization for long-term stability

• Activity recovery strategies:

  • Perform buffer exchange to remove potentially inhibitory components

  • Remove fusion tags that may interfere with receptor binding

  • Validate biological activity after each major processing step

  • Establish acceptance criteria for minimum specific activity

How do human and murine TNF-α expressed in Sf9 cells differ in terms of yield and activity?

Comparative studies reveal significant differences between human and murine TNF-α expression:

• Expression yield comparison:

  • Murine TNF-α shows approximately 3-fold higher expression levels compared to human TNF-α in silkworm-BEVS

  • Typical yields: 18.7 mg recombinant murine TNF-α (1.87 mg/mL sera, 0.374 mg/silkworm) versus significantly lower yields for human TNF-α

  • This difference is attributed to variations in secretion efficiency and/or protein stability

• Structural considerations:

  • Human TNF-α (mature form) comprises amino acids 77-233 of the precursor protein

  • Murine TNF-α (mature form) comprises amino acids 80-235 of the precursor protein

  • Both operate as homotrimers but with species-specific receptor binding domains

• Species cross-reactivity:

  • Human TNF-α binds to human TNFR1 and TNFR2 with high affinity

  • Murine TNF-α shows species-specific receptor binding preferences

  • These differences are critical for experimental design when using animal models

What experimental design best evaluates TNF-α's role in skin inflammatory disorders?

A comprehensive experimental approach should include:

• In vitro models:

  • 2D and 3D skin equivalents incorporating keratinocytes, fibroblasts, and immune cells

  • Primary cell cultures from patients with specific conditions versus healthy controls

  • Assessment of TNF-α levels, receptor expression, and downstream signaling

• Ex vivo approaches:

  • Skin explant cultures from affected and unaffected regions

  • Treatment with Sf9-derived TNF-α at physiologically relevant concentrations

  • Evaluation of inflammatory markers, cell death, and proliferation

• In vivo studies:

  • Murine models with tissue-specific TNF-α overexpression or knockout

  • Comparison of wild-type and TNF receptor-deficient animals

  • Testing of anti-TNF-α therapeutics for rescue effects

• Key parameters to measure:

  • TNF-α-induced changes in melanocyte function via MITF, MSH-R, and MC1-R expression

  • Analysis of skin cell turnover and apoptotic pathways

  • Evaluation of T-regulatory cell activation and IL-10 production in response to TNF-α

  • Assessment of barrier function and inflammatory cell infiltration

How can researchers design experiments to investigate the paradoxical protective versus harmful effects of TNF-α in skin conditions?

This complex research question requires sophisticated experimental design:

• Dose-response studies:

  • Titration of TNF-α concentrations from physiological to pathological levels

  • Temporal studies examining acute versus chronic exposure effects

  • Combined treatment with other inflammatory mediators to model complex microenvironments

• Cell-specific responses:

  • Isolate specific cell populations (keratinocytes, melanocytes, fibroblasts, immune cells)

  • Use cell type-specific inducible TNF-α expression systems

  • Compare responses across healthy donors and patients with relevant skin conditions

• Signaling pathway dissection:

  • Selective inhibition of TNFR1 versus TNFR2 signaling

  • Analysis of divergent downstream pathways (NF-κB, MAPK, apoptotic)

  • Investigation of regulatory feedback mechanisms that maintain homeostasis versus drive pathology

• Assessment framework:

  • Dual readouts measuring both protective and harmful effects simultaneously

  • Computational modeling of dynamic responses to identify tipping points between beneficial and detrimental effects

  • Integration of patient genetic background into experimental design

What emerging technologies might improve TNF-α expression and functionality analysis?

Cutting-edge approaches that could advance TNF-α research include:

• Expression system innovations:

  • CRISPR-engineered Sf9 cell lines with enhanced post-translational processing

  • Microfluidic cell-free systems for rapid screening of expression conditions

  • Semi-continuous perfusion systems for improved protein quality and yield

• Structural and functional analysis:

  • Single-molecule biophysical techniques to analyze TNF-α-receptor interactions

  • Cryo-EM structures of the complete TNF-α-receptor signaling complex

  • Advanced imaging approaches to visualize TNF-α distribution in intact tissues

• Applications in precision medicine:

  • Patient-derived organoids for personalized TNF-α response profiling

  • Development of TNF-α variants with tissue-restricted activity

  • Biomarker panels to predict TNF-α pathway dysregulation in skin disorders

How might transcriptomic and proteomic approaches enhance our understanding of TNF-α's role in skin diseases?

Integration of multi-omics approaches offers powerful insights:

• Transcriptomic strategies:

  • Single-cell RNA-seq to identify cell-specific responses to TNF-α in healthy versus diseased skin

  • Spatial transcriptomics to map TNF-α pathway activation across tissue regions

  • Time-course analysis to capture dynamic responses to TNF-α

• Proteomic applications:

  • Phosphoproteomics to map TNF-α signaling networks in different skin cell types

  • Secretome analysis to identify TNF-α-regulated factors in inflammatory microenvironments

  • Interactomics to characterize TNF-α binding partners that modify activity

• Integrated analysis frameworks:

  • Computational models incorporating multiple data types to predict disease progression

  • Machine learning approaches to identify patient subgroups with distinct TNF-α-related pathologies

  • Systems biology approaches to understand how TNF-α functions within complex signaling networks in skin homeostasis and disease