Recombinant Human Interferon alpha-inducible protein 27-like protein 1 (IFI27L1)

What is IFI27L1 and how does it relate to the IFI27 family?

IFI27L1 (also known as FAM14B or ISG12C) is a member of the interferon alpha-inducible protein 27 family. This protein belongs to the broader category of interferon-stimulated genes (ISGs) that are induced following type I interferon signaling. The IFI27 family comprises several members including IFI27 (ISG12A), IFI27L1 (ISG12C), and IFI27L2 (ISG12B), which share structural similarities but may have distinct functional roles in immune regulation .

While IFI27L1 is less characterized than IFI27, understanding the related family member IFI27 provides valuable insights. IFI27 has been shown to counterbalance innate immune responses to RNA viral infections through interaction with nucleic acids and pattern recognition receptors like RIG-I . These interactions impair RIG-I activation, suggesting a negative feedback mechanism that prevents excessive inflammatory responses during viral infection .

What is the expression profile of IFI27L1 in different tissues and under various stimuli?

IFI27L1 expression shows tissue specificity and is regulated by various stimuli similar to other interferon-stimulated genes. Based on knowledge about the related protein IFI27, expression is likely induced by type I interferons in most IFN-responsive cells . Studies on IFI27 have demonstrated that both poly(I:C) transfection (mimicking viral dsRNA) and recombinant IFN-α treatment significantly upregulate expression at both mRNA and protein levels .

The expression pattern of IFI27L1 across tissues is indicated in knowledge value metrics showing a relatively high association with tissue samples (0.57) and cell type or tissue (0.47) . Additionally, IFI27L1 shows knowledge connections to virus perturbation (0.64) and transcription factor perturbation (0.54), suggesting its expression may be significantly altered during viral infections and through specific transcriptional regulatory pathways .

What are the most effective approaches for studying IFI27L1 function in vitro?

To effectively study IFI27L1 function in vitro, researchers should consider:

Cell Line Selection: Based on available evidence, human cell lines such as A549 (human lung epithelial carcinoma) and HEK293T are suitable for studying IFI27 family proteins . For IFI27L1-specific studies, the HCT 116 human colorectal cancer cell line has been utilized for knockout models .

Gene Silencing Methods: For transient knockdown, siRNA-mediated silencing has proven effective for studying IFI27 family members. Studies with IFI27 utilized two different siRNAs targeting specific sequences, achieving more than 90% reduction in mRNA expression . This approach should be adaptable for IFI27L1 studies.

CRISPR-Cas9 Gene Editing: For stable knockout models, CRISPR-Cas9 technology can be employed. The methodology involves:

• Selection of appropriate sgRNA sequences targeting the IFI27L1 gene

• Cloning sgRNA sequences into a vector expressing Cas9 and puromycin resistance

• Transfection into target cells and selection with puromycin

• Isolation and validation of clonal populations with confirmed gene knockout

Overexpression Systems: For gain-of-function studies, transient transfection with expression plasmids (such as pCAGGS) encoding IFI27L1 fused to epitope tags (HA or FLAG) facilitates detection and functional analysis .

How can protein-RNA interactions involving IFI27L1 be studied?

Based on findings with IFI27, which contains amino acids predicted to bind RNA (specifically amino acids 60-65, 68, 69, and 82-86), IFI27L1 may also possess RNA-binding capabilities . To investigate potential IFI27L1-RNA interactions, researchers can employ several complementary approaches:

Agarose Bead Pull-down Assays:

• Transfect cells with plasmids expressing tagged IFI27L1

• Expose cellular lysates to agarose beads conjugated to RNA analogs such as poly(I:C)

• Include appropriate controls (e.g., poly(C)-conjugated beads)

• Analyze bound proteins by Western blot using antibodies against the epitope tag

Biotinylated RNA Pull-down:

• Transfect cells with expression plasmids for IFI27L1

• Introduce biotinylated RNA (such as biotinylated poly(I:C)) into cells

• Capture RNA-protein complexes using streptavidin-conjugated agarose beads

• Analyze the presence of IFI27L1 in the captured complexes by Western blot

RNA Immunoprecipitation (RIP):
This method can be used to identify specific RNA species that interact with IFI27L1 in vivo, following similar principles to those used for studying IFI27 .

How might IFI27L1 influence innate immune responses during viral infection?

Based on studies of the related protein IFI27, IFI27L1 may play a regulatory role in innate immune responses during viral infection. IFI27 has been shown to negatively modulate innate immune responses in several experimental systems :

Effects on Antiviral Gene Expression:
When IFI27 is knocked out or silenced, cells show significantly enhanced expression of interferon-stimulated genes (ISGs) like IFIT2 and pro-inflammatory cytokines like IFNL1 and CXCL10 following viral infection or poly(I:C) stimulation . Specifically:

• In IFI27 KO A549 cells infected with IAV, expression of IFIT2, IFNL1, and CXCL10 increased by approximately 2-3 fold compared to infected parental cells

• Similar effects were observed with SARS-CoV-2 infection, indicating this is not virus-specific

Impact on Viral Replication:
The negative regulatory function of IFI27 on immune responses correlates with its effect on viral replication:

• IFI27 expression facilitates IAV and SARS-CoV-2 viral replication

• Silencing IFI27 with siRNAs resulted in approximately 8-fold reduction in IAV titers at 24 and 48 hours post-infection

• In poly(I:C)-transfected cells, the absence of IFI27 enhanced the antiviral state, resulting in approximately 60-fold lower VSV titers compared to control cells

Given the similarity between IFI27 family members, IFI27L1 may exhibit comparable immunomodulatory functions, potentially through similar mechanisms.

What molecular mechanisms might underlie IFI27L1's effect on immune signaling pathways?

Drawing from mechanistic studies of IFI27, potential mechanisms for IFI27L1 function may include:

RNA Binding and PRR Interaction:
IFI27 has been shown to bind RNA and interact with pattern recognition receptors (PRRs) like RIG-I . This interaction appears to impair RIG-I activation, providing a molecular mechanism for downregulation of innate immune responses . Specifically:

• IFI27 contains amino acids predicted to bind RNA (positions 60-65, 68, 69, and 82-86)

• It binds to poly(I:C), an analog of dsRNA produced during viral infection

• This RNA-binding capability enables interaction with RIG-I

• The interaction impairs RIG-I activation and downstream signaling

If IFI27L1 shares these RNA-binding properties, it may similarly modulate PRR signaling pathways during viral infection.

Negative Feedback Regulation:
IFI27 provides a negative feedback mechanism that counteracts excessive inflammatory responses to RNA viral infection . This suggests IFI27 family members, including IFI27L1, may serve as "brakes" on the innate immune system to prevent immunopathology during viral infections.

How can IFI27L1 knockout models be generated and validated for research use?

Based on the methodologies used for IFI27 and available commercial resources for IFI27L1, researchers can generate IFI27L1 knockout models using the following approach:

CRISPR-Cas9 Knockout Generation:

• sgRNA Design: Select guide RNA sequences specifically targeting the IFI27L1 gene. Validated sequences should target conserved exons to ensure complete functional disruption .

• Vector Construction: Clone the sgRNA sequences into appropriate vectors (e.g., pX330) that express both the guide RNA under a U6 promoter and the Cas9 gene along with a selectable marker such as puromycin resistance .

• Transfection and Selection:

  • Transfect target cells (e.g., A549, HCT 116) with the CRISPR-Cas9 vector

  • Select transfected cells using puromycin

  • Isolate single cell clones through limiting dilution

• Knockout Validation:

  • Genomic Validation: Sequence the target region to confirm gene editing

  • mRNA Expression: Perform RT-qPCR to verify absence of IFI27L1 mRNA

  • Protein Expression: Confirm protein knockout by Western blot using specific antibodies

  • Functional Validation: Assess phenotypic changes consistent with the predicted function of IFI27L1

Alternative Approaches:

• Commercial Cell Lines: Utilize commercially available IFI27L1 knockout cell lines like the HCT 116-based model

• Inducible Knockout Systems: For studying essential genes, consider tetracycline-regulated CRISPR systems

What experimental design considerations are crucial when analyzing IFI27L1's role during viral infection?

When designing experiments to analyze IFI27L1's role during viral infection, researchers should consider:

Virus Selection:
Studies with the related protein IFI27 have utilized several virus models:

• Influenza A Virus (IAV)

• SARS-CoV-2

• Sendai Virus (SeV)

• Vesicular Stomatitis Virus (VSV)

Each virus provides distinct advantages: IAV and SARS-CoV-2 represent clinically relevant pathogens, SeV is a potent inducer of innate immune responses, and VSV (particularly GFP-expressing recombinants) offers a convenient readout for antiviral activity .

Cell Systems:

• Select cell types that naturally express IFI27L1 and support viral replication

• Include multiple cell types to ensure observations are not cell-type specific

• Consider primary cells in addition to cell lines for physiological relevance

Experimental Controls:

• Include both gain-of-function (overexpression) and loss-of-function (knockout/knockdown) approaches

• Employ multiple siRNAs or knockout clones to control for off-target effects

• Assess both constitutive and infection-induced expression of IFI27L1

Analysis Timepoints:
Based on studies with IFI27, important timepoints for analysis include:

• Early timepoints (6-12h post-infection) to capture initial innate immune responses

• Intermediate timepoints (24h post-infection) for peak viral replication and immune gene expression

• Later timepoints (48h post-infection) to assess resolution of infection and prolonged effects

How should contradictory data regarding IFI27L1 function be analyzed and reconciled?

When facing contradictory data regarding IFI27L1 function, researchers should:

Consider Context-Dependent Effects:
Studies on IFI27 suggest its role may depend on the types of viral infections and diseases . Contradictory findings may reflect genuine biological variability rather than experimental error. Analytical approaches should include:

• Systematic comparison across experimental variables:

  Variable	Parameters to Compare
  Cell Type	Epithelial vs. Immune cells; Primary vs. Cell lines
  Virus Type	RNA vs. DNA viruses; Respiratory vs. Other tropism
  Infection Parameters	MOI; Time post-infection; Route of infection
  Host Species	Human vs. Mouse models; Species-specific effects

• Dose-response analysis: Evaluate whether IFI27L1 effects are concentration-dependent by using inducible expression systems or varying transfection amounts.

• Temporal dynamics analysis: Assess whether contradictory effects occur at different timepoints during infection, suggesting stage-specific functions.

Validate Key Findings Using Multiple Approaches:
For any contradictory results, employ complementary techniques:

• Combine genetic approaches (knockout, knockdown, overexpression)

• Validate in vivo findings with ex vivo and in vitro models

• Use both loss-of-function and gain-of-function approaches

What bioinformatic tools are most effective for studying IFI27L1 interactions and networks?

For comprehensive analysis of IFI27L1 interactions and networks, researchers should employ a multi-pronged bioinformatic approach:

Protein-RNA Interaction Prediction:

• RNABindRplus has been successfully used to predict RNA-binding residues in IFI27 and can be applied to IFI27L1

• This method combines machine learning and sequence homology-based approaches to improve prediction reliability

Protein-Protein Interaction Networks:

• STRING database analysis to identify high-confidence interaction partners

• Prioritize interactions with components of innate immune signaling pathways (e.g., RIG-I pathway) based on known functions of IFI27

Expression Correlation Analysis:
Based on knowledge values for IFI27L1, particular focus should be given to:

• Virus perturbation datasets (knowledge value: 0.64)

• Transcription factor perturbation data (knowledge value: 0.54)

• Histone modification profiles (knowledge value: 0.51)

Data Integration Framework:
Researchers should integrate multiple data types using the following approach:

• Primary Data Collection:

  • RNA-seq for expression profiling

  • ChIP-seq for transcription factor binding and histone modifications

  • CLIP-seq for RNA-protein interactions

• Knowledge Integration:

  • Pharos database for target knowledge aggregation (IFI27L1 is currently classified as a "dark" protein about which relatively little is known)

  • Gene Ontology enrichment analysis of correlated genes

  • Pathway analysis focusing on interferon and innate immune signaling components

• Visualization Tools:

  • Cytoscape for network visualization

  • R or Python packages for expression data analysis and correlation

What are the critical knowledge gaps regarding IFI27L1 that require further investigation?

Despite growing interest in the IFI27 family, significant knowledge gaps regarding IFI27L1 remain to be addressed:

Structural Characterization:

• Determine the three-dimensional structure of IFI27L1

• Identify key domains responsible for RNA binding and protein-protein interactions

• Compare structural features with other IFI27 family members to identify conserved and divergent elements

Regulatory Mechanisms:

• Characterize the promoter elements driving IFI27L1 expression

• Identify transcription factors regulating basal and inducible expression

• Investigate post-translational modifications affecting IFI27L1 function

Functional Role in Disease:

• Determine the specific contribution of IFI27L1 to antiviral defense versus pathological inflammation

• Investigate potential roles in non-infectious inflammatory conditions

• Explore contributions to cancer development or progression

Therapeutic Potential:

• Assess whether modulation of IFI27L1 activity could serve as a therapeutic strategy

• Investigate drug-IFI27L1 interactions that might affect antiviral therapies

How might IFI27L1 function differ from other members of the IFI27 family?

Understanding the functional differences between IFI27L1 and other IFI27 family members represents an important research direction:

Comparative Expression Analysis:

• Compare tissue distribution and cell-type specificity

• Analyze differential induction by various interferons (type I, II, and III)

• Investigate temporal expression patterns during infection

Functional Comparisons:

• Assess relative contributions to viral replication for different family members

• Compare effects on innate immune signaling pathways

• Evaluate potential redundant versus unique functions

Evolutionary Considerations:

• Conduct phylogenetic analysis of IFI27 family across species

• Identify conserved domains suggesting core functions

• Analyze species-specific adaptations that might reflect pathogen pressures