DDI2 Antibody

What is DDI2 and what cellular functions does it serve in experimental models?

DDI2 (DNA-damage inducible 1 homolog 2) is a 399-amino acid protein (~45 kDa) containing an N-terminal ubiquitin-like (UBL) domain and a highly conserved retroviral protease-like (RVP) domain. Functionally, DDI2 acts as an aspartic protease that cleaves polyubiquitinated substrates and plays crucial roles in:

• Proteolytic activation of the transcription factor NFE2L1/NRF1, which regulates proteasome gene expression during proteotoxic stress

• Serving as a proteasomal shuttle, linking the proteasome to replication fork proteins such as RTF2

• Maintaining genome integrity by removing RTF2 from stalled replication forks

• Processing high molecular weight ubiquitinated proteins, particularly during proteasome inhibition

• Embryonic development, with knockout causing lethality at E12.5 in mice

• Modulating oxidative stress responses

For reliable detection in experimental systems, Western blot analysis typically shows DDI2 at 45-50 kDa, with rabbit polyclonal antibodies being most commonly used for detection .

What applications can DDI2 antibodies be reliably used for, and what validation steps should be taken?

DDI2 antibodies have been validated for multiple applications with varying degrees of reliability:

Validation should include:

• Testing on both positive (known DDI2-expressing cells) and negative controls (DDI2 knockout cells)

• Verifying that the observed band is at the expected molecular weight (45-50 kDa)

• Examining cross-reactivity with DDI1 homolog (which has functional overlap)

• For critical experiments, validating results with at least two different antibodies targeting distinct epitopes

What are the optimal Western blot conditions for detecting DDI2?

For optimal detection of DDI2 by Western blot:

Sample preparation:

• Lyse cells using NETN lysis buffer (most effective based on comparative studies)

• Include protease inhibitors to prevent degradation

• Load 20-30 μg of total protein per lane for standard cell lines

Antibody conditions:

• Primary antibody dilution: 1:500-1:2000 (titration recommended for each new antibody lot)

• Incubation: Overnight at 4°C or 2 hours at room temperature

• Secondary antibody: Anti-rabbit IgG-HRP at 1:10,000 dilution

Special considerations:

• DDI2 interacts with ubiquitinated proteins; therefore, adding deubiquitinase inhibitors to lysis buffer may affect band pattern

• For detecting DDI2-substrate interactions, consider using mild lysis conditions to preserve protein complexes

• When studying high molecular weight ubiquitin conjugates that interact with DDI2, BioRad 3%-8% Tricine or TGX SDS-PAGE gels provide superior resolution

How can I effectively study DDI2's role in activating the Nrf1 pathway during proteasome inhibition?

To investigate DDI2's role in the Nrf1 activation pathway:

Experimental design:

• Generate cellular models:

  • DDI2 knockout cells using CRISPR/Cas9 (targeting exon 2)

  • DDI2 protease-dead knock-in cells (D252N mutation)

  • Wild-type DDI2 knock-in cells as controls

• Proteasome inhibition protocol:

  • Treat cells with bortezomib (100 nM) or other proteasome inhibitors for 4-16 hours

  • Include time-course experiments to capture the kinetics of Nrf1 processing

• Analysis methods:

  • Western blot to detect both full-length and cleaved forms of Nrf1

  • qRT-PCR to measure expression of Nrf1 target genes (e.g., PSMA3, PSMB5)

  • Chromatin immunoprecipitation to assess Nrf1 binding to proteasome gene promoters

Key controls:

• Compare wild-type, DDI2 knockout, and protease-dead DDI2 cells

• Include E1 inhibitor TAK-243 (1 μM, 1 hour treatment) as a control for ubiquitination inhibition

• Use chemical complementation with purified DDI2 protein to verify rescue of the phenotype

Example data from previous research:
In DDI2 knockout cells and DDI2 D252N knock-in cells, bortezomib treatment leads to accumulation of full-length Nrf1, whereas in wild-type cells, the processed (active) form accumulates . Additionally, the Nrf1-dependent "bounce-back" response (increased expression of proteasome subunit genes) is abolished in DDI2-deficient cells .

What methodologies are most effective for studying DDI2's interaction with high molecular weight ubiquitin conjugates?

To study DDI2's interactions with high molecular weight ubiquitin conjugates:

Sample preparation:

• Generate abundant high molecular weight ubiquitin conjugates:

  • Treat cells with proteasome inhibitors (e.g., 100 nM bortezomib overnight)

  • Include E1 inhibitor-treated cells (1 μM TAK-243 for 1 hour) as negative controls

• Cell fractionation techniques:

  • Use specialized extraction buffers to preserve ubiquitin chains

  • Consider subcellular fractionation to identify compartment-specific interactions

Interaction analysis methods:

• Far-Western blotting:

  • Separate proteins by SDS-PAGE (use 3%-8% Tricine gels for better resolution of high MW conjugates)

  • Transfer to membrane and probe with purified DDI2 protein

  • Detect bound DDI2 with anti-DDI2 antibodies

• Pull-down assays:

  • Use catalytically inactive DDI2 (D252N mutant) to capture substrates without cleaving them

  • Immobilize FLAG-tagged inactive DDI2 on M2 beads

  • Elute bound proteins and analyze by immunoblotting with anti-ubiquitin antibodies

• Proximity labeling:

  • Express BioID or TurboID-DDI2 fusion proteins

  • Label proximal proteins with biotin

  • Purify biotinylated proteins and identify by mass spectrometry

Data analysis:

• Focus on slowly migrating ubiquitinated proteins at the top of the gel

• Compare patterns between wild-type and DDI2 knockout cells

• Analyze both K11/K48-linked ubiquitin chains, which DDI2 preferentially binds

How should I design experiments to study DDI2's role in embryonic development and what phenotypes should I examine?

Based on previous research showing that DDI2 knockout causes embryonic lethality at E12.5 , the following experimental approach is recommended:

Mouse model generation:

• Create two complementary mouse models:

  • Full knockout strain: C57BL/6NCrl-Ddi2tm1b(EUCOMM)Hmgu/Ph (Ddi2KO) lacking critical exon 2

  • Protease-defective strain: C57Bl/6NCrl-Ddi2em1/Ph (Ddi2PD) with mutations disrupting catalytic activity and dimerization

• Breeding strategy:

  • Maintain heterozygous (Ddi2+/-) breeding pairs

  • Collect embryos at various stages (E9.5-E13.5) for phenotypic analysis

  • Genotype all embryos and compare phenotypes across genotypes

Phenotypic analysis:

• Developmental assessment:

  • Gross morphological examination

  • Histological analysis of major organ systems

  • Measurement of crown-rump length and other developmental parameters

• Molecular analysis:

  • Proteasome expression and activity assays

  • Detection of high molecular weight ubiquitin conjugates

  • Assessment of unfolded protein response (UPR) markers

  • Analysis of integrated stress response (ISR) markers

• Cell death and proliferation:

  • TUNEL assay for apoptotic cells

  • Immunostaining for proliferation markers (Ki-67, PCNA)

• Immune response analysis:

  • Type I interferon signature assessment

  • Inflammatory markers measurement

Example findings from previous research:
DDI2 knockout embryos show severe developmental failure by E12.5, with insufficient proteasome expression, accumulation of high molecular weight ubiquitin conjugates, activation of unfolded protein response, and induction of type I interferon signature .

What are the best strategies for investigating DDI2's role in cancer progression, particularly in liver cancer models?

For studying DDI2's role in liver cancer:

Cell models:

• Generate DDI2 knockout lines from liver cancer cells:

  • Use CRISPR/Cas9 to create DDI2-/- and DDI2insG/- variants (as described in )

  • Include rescue experiments with wild-type DDI2 expression

• In vitro assays:

  • Cell proliferation (growth curves, colony formation)

  • Apoptosis assessment (Annexin V staining, caspase activation)

  • ROS measurement (DCFDA assay)

  • DNA damage detection (γH2AX foci, comet assay)

In vivo tumor models:

• Xenograft studies:

  • Inject DDI2-knockout and control liver cancer cells subcutaneously in nude mice

  • Monitor tumor growth rate, size, and weight

  • Perform histological analysis of tumor tissues

• Analysis parameters:

  • Tumor volume measurements

  • Expression of proliferation markers (CCND1)

  • Apoptosis markers (CASP9)

  • ROS and DNA damage markers (8-OHdG)

Molecular mechanism investigation:

• Examine antioxidant pathway involvement:

  • Measure expression of Nrf1 and Nrf2 and their downstream targets

  • Assess ROS levels and oxidative DNA damage

• DNA damage response analysis:

  • Quantify γH2AX levels

  • Analyze DNA repair pathway activation

  • Measure 8-OHdG levels as an indicator of oxidative DNA damage

Example data from previous research:
DDI2 knockout in liver cancer cells leads to:

• Increased ROS levels through downregulation of Nrf1 and Nrf2

• Exacerbated DNA damage

• Inhibited cell proliferation and increased apoptosis

• Reduced tumor growth in xenograft models

How can I effectively analyze the interplay between DDI2 and proteasome function in drug resistance models?

To investigate DDI2's role in proteasome inhibitor resistance:

Experimental models:

• Generate resistant cell lines:

  • Culture sensitive cells (e.g., MM.1S multiple myeloma cells) with sub-lethal concentrations of bortezomib (BTZ) for 4+ weeks

  • Characterize adaptation 48 hours after treatment withdrawal

  • Create DDI2 knockout variants of both sensitive and resistant cells

• Comparative analysis:

  • Compare BTZ sensitivity between wild-type and DDI2-deficient cells

  • Assess proteasome activity recovery after pulse treatment

  • Measure the induction of proteasome subunit expression

Key assays:

• Proteasome recovery:

  • Pulse-treat cells with proteasome inhibitors

  • Monitor proteasome activity recovery using fluorogenic substrates

  • Compare recovery kinetics between wild-type and DDI2-deficient cells

• Transcriptional response:

  • Measure expression of proteasome subunit genes (PSMA3, PSMB5) by qRT-PCR

  • Analyze Nrf1 processing and activation

  • Assess global transcriptional changes using RNA-seq

• Combination therapy approach:

  • Test DDI2 inhibition (e.g., using HIV protease inhibitors like nelfinavir) in combination with BTZ

  • Determine synergistic potential using combination index analysis

  • Evaluate effects on cell viability and apoptosis

Example findings:

• DDI2 knockout sensitizes cells to proteasome inhibitors

• The recovery of proteasome activity after pulse treatment with inhibitors can be DDI2-independent, suggesting multiple recovery mechanisms

• HIV protease inhibitors like nelfinavir can partially inhibit DDI2 and potentiate BTZ efficacy in multiple myeloma

What experimental approaches can distinguish between DDI2's protease-dependent and protease-independent functions?

To differentiate between DDI2's protease-dependent and independent functions:

Genetic models:

• Create a panel of cell lines:

  • Complete DDI2 knockout (all functions lost)

  • Protease-dead mutant (D252N) knock-in (maintaining scaffolding functions)

  • UBL domain mutant (preserving protease activity but disrupting ubiquitin interactions)

  • Domain deletion variants (ΔUBL, ΔRVP, ΔHDD)

• Complementation studies:

  • Rescue experiments with domain-specific mutants

  • Expression of isolated domains to identify dominant-negative effects

Functional assays:

• Protease-dependent processes:

  • Nrf1 processing (Western blot)

  • High molecular weight ubiquitin conjugate processing

  • RTF2 displacement from stalled replication forks

• Potential protease-independent functions:

  • Ubiquitin binding (far-Western blots)

  • Protein-protein interactions (IP-MS analysis)

  • Shuttling activities (cellular fractionation studies)

Inhibitor studies:

• Use HIV protease inhibitors (which may partially inhibit DDI2)

• Compare phenotypic effects to genetic models

• Time-course experiments to identify primary vs. secondary effects

Data interpretation framework:

• Effects observed in knockout but not in protease-dead mutants suggest protease-independent functions

• Effects shared between knockout and protease-dead mutants indicate protease-dependent functions

• Effects that can be rescued by wild-type but not protease-dead DDI2 confirm protease-dependency

What are the appropriate controls and methodology for studying DDI2's role in the innate immune response?

To investigate DDI2's involvement in innate immune signaling:

Experimental models:

• Cell systems:

  • DDI2 knockout cell lines (both immune and non-immune cells)

  • Protease-dead DDI2 knock-in cells

  • Primary cells from DDI2 knockout or conditional knockout mice

• In vivo models:

  • Tissue-specific DDI2 knockout mice (using Cre-loxP system)

  • DDI2 protease-dead knock-in mice

Immune response assays:

• Type I interferon signature analysis:

  • qRT-PCR for interferon-stimulated genes

  • ELISA for IFNα/β production

  • Luciferase reporter assays for interferon signaling pathway activation

• Signaling pathway assessment:

  • Western blot for STAT phosphorylation

  • Analysis of STAT3-dependent proliferative signaling

  • NF-κB activation measurement

• Cell autonomous immune response:

  • Single-cell RNA-seq to characterize cell-specific responses

  • Comparison of immune signatures between cell types

Experimental controls:

• Positive controls:

  • Direct stimulation with IFNα/β

  • Activation with pathogen-associated molecular patterns (PAMPs)

• Negative controls:

  • JAK/STAT pathway inhibitors

  • IFNAR blocking antibodies

• Specificity controls:

  • DDI1 knockout (to exclude potential compensation)

  • Analysis of proteotoxic stress without DDI2 deletion

Example findings:
DDI2 knockout-induced proteotoxic stress activates the cell-autonomous innate immune system, leading to a type I interferon signature. This immune activation may function as a survival mechanism in DDI2-deficient cells through STAT3-dependent proliferative signaling .

How do I troubleshoot non-specific binding or weak signals when using DDI2 antibodies?

Common issues and solutions:

Optimization steps:

• Sample preparation:

  • Test different lysis buffers (NETN works well for DDI2)

  • Include protease and phosphatase inhibitors

  • Avoid freeze-thaw cycles of prepared samples

• Antibody validation:

  • Verify antibody specificity using knockout/knockdown controls

  • Consider using antibodies targeting different epitopes

  • Pre-adsorb antibody with immunogen peptide to confirm specificity

• Detection method optimization:

  • For weak signals, try enhanced chemiluminescence (ECL) detection

  • Consider fluorescent secondary antibodies for quantitative analysis

  • Use signal enhancers for very low abundance detection

What considerations are important when designing DDI2 knockout or knockdown experiments?

Design considerations for DDI2 loss-of-function studies:

• Knockout strategies:

  • Target exon 2 for complete loss of function (as in C57BL/6NCrl-Ddi2tm1b(EUCOMM)Hmgu/Ph)

  • Consider conditional knockout systems for embryonic lethal phenotypes

  • Verify knockout at both DNA, RNA, and protein levels

• Knockdown approaches:

  • Multiple siRNAs targeting different regions to minimize off-target effects

  • Inducible shRNA systems for temporal control

  • Compare phenotypes between knockdown and knockout to identify potential dose-dependent effects

• Critical controls:

  • Rescue experiments with wild-type DDI2 expression

  • Parallel analysis of DDI1 expression (may compensate for some DDI2 functions)

  • Protease-dead DDI2 (D252N) controls to distinguish domain-specific functions

• Potential complications:

  • Embryonic lethality in complete knockout models

  • Compensatory upregulation of DDI1 or alternative pathways

  • Secondary effects due to proteotoxic stress in DDI2-deficient cells

  • Activation of interferon response pathways that may mask primary phenotypes

• Phenotypic analysis timeline:

  • Acute vs. chronic effects may differ significantly

  • Consider time-course experiments to distinguish direct from indirect effects

  • Watch for adaptation mechanisms in long-term knockout cell lines

How can I effectively use DDI2 antibodies to study its interaction with Nrf1 and other proteasome-related substrates?

Methodological approaches:

• Co-immunoprecipitation (Co-IP):

  • Use DDI2 antibodies for IP followed by Nrf1 detection

  • Include proteasome inhibitors (bortezomib, 100 nM) to stabilize interactions

  • Consider cross-linking to capture transient interactions

  • Control: IP with IgG from same species as DDI2 antibody

• Proximity ligation assay (PLA):

  • Detect in situ interaction between DDI2 and Nrf1

  • Requires validated antibodies from different species

  • Provides spatial information about interaction sites

  • Control: Single antibody controls and DDI2 knockout cells

• FRET/BRET assays:

  • Tagged DDI2 and Nrf1 for live-cell interaction studies

  • Monitor real-time dynamics of interactions

  • Control: Non-interacting protein pairs

Sample preparation considerations:

• Use mild lysis conditions to preserve protein-protein interactions

• Include deubiquitinase inhibitors to maintain ubiquitinated substrates

• Fractionate samples to identify compartment-specific interactions (ER membrane vs. cytosol)

Data interpretation:

• Compare interaction profiles before and after proteasome inhibition

• Assess whether interactions depend on DDI2 protease activity (use D252N mutant)

• Determine if substrates require ubiquitination for DDI2 interaction

• Examine temporal relationship between binding, processing, and downstream effects

What are the best experimental designs for studying DDI2's role in DNA damage response and repair?

Experimental approaches:

• DNA damage induction methods:

  • Replication stress inducers: hydroxyurea, aphidicolin

  • DNA crosslinking agents: cisplatin, mitomycin C

  • Oxidative stress inducers: H₂O₂, menadione

  • Ionizing radiation

• Cellular models:

  • DDI2 knockout cell lines

  • DDI2 domain-specific mutants

  • DDI2-overexpressing cells

  • DDI2 and DDI1 double knockout (to prevent compensation)

• DNA damage assessment:

  • γH2AX immunofluorescence to quantify double-strand breaks

  • Comet assay for single and double-strand breaks

  • 8-OHdG measurement for oxidative DNA damage

  • DNA fiber analysis for replication fork progression

• Replication stress response:

  • Analysis of RTF2 localization at stalled replication forks

  • DNA fiber assay to measure fork restart efficiency

  • Chromatin fractionation to assess protein recruitment to damaged DNA

Specific assays for DDI2's role:

• Replication fork restart assay:

  • Pulse-label with nucleotide analogs

  • Induce fork stalling

  • Measure replication restart efficiency

  • Compare wild-type and DDI2-deficient cells

• RTF2 displacement analysis:

  • Chromatin immunoprecipitation of RTF2

  • Assess RTF2 retention at stalled forks in DDI2-deficient cells

  • Rescue experiments with wild-type vs. protease-dead DDI2

• DNA-protein crosslink (DPC) repair assay:

  • Induce DPCs with formaldehyde or cisplatin

  • Measure DPC removal kinetics

  • Compare wild-type and DDI2-deficient cells

Example findings:
DDI2, together with DDI1, removes RTF2 from stalled replication forks, allowing cell cycle progression after replication stress and maintaining genome integrity . DDI2 may also function as a key repair enzyme for DNA-protein crosslinks .

How can DDI2 antibodies be applied in studying the relationship between proteotoxic stress and inflammation?

Recent research has uncovered a surprising link between DDI2-mediated proteostasis and inflammatory responses , offering new research directions:

Experimental approaches:

• Cell-autonomous inflammatory response:

  • Generate DDI2 knockout in various cell types (epithelial, immune, etc.)

  • Profile inflammatory gene expression (RNA-seq, NanoString)

  • Measure type I interferon production and signaling

  • Assess STAT pathway activation

• Mechanistic investigations:

  • Block interferon signaling (IFNAR neutralization) in DDI2 knockout cells

  • Inhibit specific stress response pathways (UPR, ISR) to identify inflammatory triggers

  • Perform time-course analysis to establish causality between proteotoxic stress and inflammation

• In vivo inflammation models:

  • Tissue-specific DDI2 conditional knockout mice

  • Challenge with inflammatory stimuli

  • Assess inflammatory markers and tissue damage

  • Evaluate therapeutic targeting of inflammatory pathways

Analytical methods:

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

• Multiplex cytokine profiling

• Phospho-flow cytometry for signaling pathway activation

• Spatial transcriptomics to map inflammatory responses in tissues

Example findings:
DDI2 knockout-induced proteotoxic stress activates cell-autonomous innate immune signaling, leading to a type I interferon signature. This immune activation may provide a survival advantage through STAT3-dependent proliferative signaling . This link between proteostasis and inflammation represents a novel avenue for therapeutic intervention in inflammatory diseases.

What are the latest methodologies for studying DDI2 as a potential therapeutic target in cancer?

Research indicates that DDI2 may promote cancer cell survival by regulating oxidative stress and DNA damage responses , suggesting potential as a therapeutic target:

Target validation approaches:

• Pharmacological inhibition:

  • Screen for specific DDI2 protease inhibitors

  • Repurpose HIV protease inhibitors (e.g., nelfinavir)

  • Develop peptide-based inhibitors targeting the RVP domain

  • Test in combination with established therapies (proteasome inhibitors, DNA-damaging agents)

• Genetic validation:

  • CRISPR-based screens to identify cancer types dependent on DDI2

  • Patient-derived xenograft models with DDI2 modulation

  • Synthetic lethality screening with DDI2 inhibition

• Biomarker development:

  • Correlate DDI2 expression with patient outcomes

  • Identify downstream markers of DDI2 activity

  • Develop assays to monitor on-target effects of DDI2 inhibition

Cancer-specific applications:

• Liver cancer models:

  • DDI2 knockout inhibits tumor growth by increasing ROS and DNA damage

  • Monitor markers: CCND1 (proliferation), CASP9 (apoptosis)

• Multiple myeloma:

  • DDI2 contributes to bortezomib resistance

  • Combination therapy with DDI2 inhibitors may enhance proteasome inhibitor efficacy

• Colorectal cancer:

  • DDI2 may promote metastasis

  • Target DDI2-dependent DNA repair pathways

Emerging techniques:

• PROTAC-based degradation of DDI2

• Allele-specific inhibition of cancer-associated DDI2 variants

• Antibody-drug conjugates targeting cancer cells with high DDI2 expression

How can I integrate multi-omics approaches to comprehensively study DDI2 function in cellular pathways?

To gain a systems-level understanding of DDI2 function:

Multi-omics experimental design:

• Genomics:

  • CRISPR screens to identify synthetic lethal interactions with DDI2

  • Genetic association studies to link DDI2 variants with disease phenotypes

• Transcriptomics:

  • RNA-seq of DDI2 knockout vs. wild-type cells under various stresses

  • Time-course analysis to distinguish primary from secondary effects

  • Single-cell RNA-seq to capture cellular heterogeneity

• Proteomics:

  • Global proteome analysis of DDI2-deficient systems

  • Ubiquitinome profiling to identify accumulated ubiquitinated proteins

  • Protein turnover studies to identify DDI2-dependent degradation

  • Proximity labeling to map DDI2 interaction network

• Metabolomics:

  • Assess impact on redox metabolism (given DDI2's role in oxidative stress)

  • Measure energy metabolism changes in DDI2-deficient cells

Integrative analysis methods:

• Pathway enrichment across multiple data types

• Network analysis to identify DDI2-centered functional modules

• Causal network inference to establish regulatory relationships

• Multi-omics factor analysis to identify coordinated responses

Validation strategies:

• Targeted experiments to confirm key predictions

• Perturbation studies to test network models

• Temporal analysis to establish causality

Example application:
In a study of DDI2 knockout endothelial cells, proteomics analysis identified alterations in proteins involved in protein metabolism, cell stress response, and immune system pathways . Integration with transcriptomic data could further elucidate the regulatory networks connecting these pathways and identify potential intervention points.

What considerations are important when using DDI2 antibodies in studying models of neurodegenerative diseases?

Given DDI2's role in proteostasis and stress responses, it presents an interesting target for neurodegenerative disease research:

Experimental considerations:

• Model systems:

  • Neuronal cell lines with DDI2 modulation

  • Primary neurons from DDI2 knockout or conditional knockout mice

  • Patient-derived iPSCs differentiated into neurons

  • Animal models expressing neurodegenerative disease proteins (Aβ, tau, α-synuclein)

• Disease-relevant assays:

  • Protein aggregation measurement

  • Proteasome activity in neuronal compartments

  • Oxidative stress and DNA damage assessment

  • Neuronal survival and function evaluations

• Tissue-specific analysis:

  • Brain region-specific DDI2 expression and function

  • Cell type-specific responses (neurons vs. glia)

  • Age-dependent changes in DDI2 activity

Technical approaches:

• Immunohistochemistry optimization:

  • Antigen retrieval methods for brain tissue

  • Multiplexed staining for DDI2 and disease markers

  • Comparison of different DDI2 antibodies for specificity in neural tissues

• Biochemical fractionation:

  • Separate soluble vs. insoluble protein fractions

  • Isolate different neuronal compartments (synapse, soma, axon)

  • Analyze DDI2 association with protein aggregates

Therapeutic implications:

• DDI2 activation potential in proteinopathies

• NGLY1-DDI2-TCF11/NRF1 axis as a drug target

• Balancing proteostasis enhancement without triggering inflammatory responses