LGALS9 Mouse

What is LGALS9 and what is its function in mice?

LGALS9 is the gene that encodes galectin-9, a tandem repeat galectin containing two carbohydrate recognition domains joined by a linker with high affinity for β-galactoside residues. In mice, galectin-9 functions as an important immunoregulatory molecule with multiple receptor interactions, most notably with T-cell immunoglobulin and mucin-domain containing-3 (TIM-3) . Functionally, galectin-9 has been shown to attenuate NLRP3 inflammasome activation by promoting protein degradation of NLRP3 in primary peritoneal macrophages of C57BL/6J mice . This immunomodulatory function makes it a critical molecule in various inflammatory conditions and cancer progression models.
The protein plays significant roles in:

• Regulation of immune cell function, particularly T cell responses

• Modulation of inflammatory pathways

• Autophagic degradation processes

• Cancer progression and immune evasion mechanisms

How is LGALS9 expression regulated in mouse models?

LGALS9 expression varies across tissue types and is significantly modulated during inflammatory conditions and disease states. In pancreatic cancer models using KC mice (Pdx1-Cre; LstopL-KrasG12D), researchers have observed elevated expression of LGALS9 in both pancreatic tissue and infiltrating immune cells compared to wild-type mice . The regulation appears to be age-dependent, with expression patterns changing as disease progresses.
Expression analysis reveals:

• Higher LGALS9 expression in pancreatic cancer mouse models compared to wild type mice

• Age-dependent expression patterns with early elevation in disease models

• Expression in both tissue cells (CD45-) and immune cells (CD45+)

• Responsiveness to therapeutic interventions targeting galectin-9

What mouse models are commonly used to study LGALS9 function?

Several established mouse models are employed to study LGALS9 function:

• Transgenic KC mice (Pdx1-Cre; LstopL-KrasG12D): These mice develop the full spectrum of pancreatic tumor progression and are used to study LGALS9 in precancerous and cancer contexts. They mirror early human pancreatic pathology as they carry the KrasG12D mutation found in 75%-95% of pancreatic cancers .

• LGALS9 knockout mice: Generated using CRISPR/Cas9 technology, these models allow for studying the consequences of galectin-9 deficiency. Research shows that LGALS9 deficiency enhances NLRP3 inflammasome activation and promotes NLRP3-dependent inflammation in C57BL/6J mice .

• Orthotopic PDAC models: Used to evaluate the efficacy of galectin-9 blockade in more advanced tumor contexts, these models have demonstrated that neutralizing galectin-9 can slow tumor progression and prolong mouse survival .

How can LGALS9 be effectively knocked out in mouse models?

LGALS9 knockout can be achieved through several approaches, with CRISPR/Cas9 technology being the most efficient current method. Commercial knockout kits utilize dual gRNA vectors and a linear donor approach to maximize knockout efficiency . The methodology typically involves:

• Design of guide RNAs targeting critical exons of the Lgals9 gene

• Delivery of CRISPR components via viral vectors or direct transfection

• Screening and validation of knockout efficiency

• Breeding strategies to achieve homozygous knockout lines
  When designing a knockout strategy, researchers should consider:

• Targeting constitutive exons present in all transcript variants

• Selection of guide RNAs with minimal off-target effects

• Appropriate screening methods to confirm knockout at both genomic and protein levels

• Potential compensatory mechanisms from other galectin family members

What phenotypic changes are observed in LGALS9 knockout mice?

LGALS9 knockout mice display several significant phenotypic changes relevant to inflammation and disease development:

• Enhanced inflammasome activation: LGALS9 deficiency leads to increased NLRP3 inflammasome activation, resulting in higher IL-1β production in response to inflammatory stimuli .

• Exacerbated inflammatory responses: These mice show more pronounced inflammation in various disease models due to the loss of galectin-9's immunoregulatory effects.

• Altered T cell responses: Given galectin-9's role in T cell regulation, knockout mice exhibit changes in T cell differentiation, survival, and function.

• Impact on disease progression: In pancreatic cancer models, alterations in galectin-9 expression affect the rate of progression from precancerous lesions to adenocarcinoma .
  These observations highlight the importance of galectin-9 as an endogenous regulator of inflammation and immune responses in mice.

How can LGALS9 expression be accurately measured in mouse tissues?

Accurate measurement of LGALS9 expression in mouse tissues requires a multi-modal approach combining several techniques:

• Flow cytometry: This method allows for quantification of galectin-9 protein expression at the cellular level. As demonstrated in pancreatic cancer studies, measurements can be reported as relative fluorescence intensity (RFI) compared to isotype controls. In KC mice, researchers observed RFI values of approximately 3.01 in untreated mice versus 2.06 in anti-galectin-9 treated mice .

• RT-qPCR: For mRNA expression analysis, primers specific to mouse Lgals9 can detect transcript levels across different tissues and experimental conditions.

• Western blotting: This technique provides semi-quantitative assessment of galectin-9 protein levels in tissue lysates.

• Immunohistochemistry/Immunofluorescence: These methods enable visualization of galectin-9 expression patterns within tissue architecture and allow for co-localization studies with other markers.
  When reporting expression data, it is important to specify:

• The particular isoform being measured (given the multiple transcript variants)

• The cell population analyzed (e.g., CD45+ immune cells vs. CD45- tissue cells)

• Appropriate normalization controls

• Statistical methods used for comparison

What is the role of LGALS9 in autophagy and how can it be studied in mouse models?

Galectin-9 plays a significant role in selective autophagy, particularly in the context of inflammasome regulation. Research has revealed that galectin-9 functions as an "eat-me" signal for selective autophagy of NLRP3, a key component of the inflammasome . Mechanistically, galectin-9:

• Directly interacts with NLRP3 protein

• Promotes the formation of NLRP3/p62 complex (p62 being an autophagic cargo receptor, also known as SQSTM1)

• Facilitates p62-dependent autophagic degradation of NLRP3 in mouse peritoneal macrophages
  To study this function in mouse models, researchers can employ:

• Co-immunoprecipitation assays to detect NLRP3-galectin-9 interactions

• Confocal microscopy to visualize co-localization with autophagic markers

• LC3 flux assays in the presence/absence of galectin-9

• Lysosomal inhibitors to confirm the degradation pathway

• Comparison of autophagic flux between wild-type and LGALS9 knockout mice
  This research direction represents an important frontier in understanding how galectin-9 contributes to cellular homeostasis through protein quality control mechanisms.

How does LGALS9 influence regulatory T cell function in mouse models of cancer?

LGALS9 has emerged as a critical regulator of regulatory T cell (Treg) function in mouse cancer models, particularly in pancreatic cancer. Studies using KC mice have demonstrated:

• Increased Treg prevalence: KC mice show significantly higher levels of both circulating and tumor-infiltrating Tregs compared to wild-type mice, correlating with increased LGALS9 expression .

• Early and sustained Treg infiltration: Analysis reveals that Treg accumulation is an early and sustained event in pancreatic neoplasia development, with significant increases observed regardless of age .

• Therapeutic targeting potential: Anti-galectin-9 antibody treatment (using clone 1G3) reduced LGALS9 expression in the pancreas and affected tumor progression, suggesting a direct link between galectin-9 levels and Treg-mediated immunosuppression .

• Mechanism of action: Galectin-9 appears to enhance Treg suppressive function, as neutralizing antibodies against galectin-9 can restore conventional T cell proliferation in co-culture systems with Tregs .
  These findings highlight the potential of targeting the galectin-9/Treg axis in cancer immunotherapy strategies.

What are the contradictory findings regarding LGALS9 in different mouse disease models?

Despite growing research on LGALS9, several contradictory findings have emerged across different mouse disease models:

• Pro- versus anti-inflammatory effects: While galectin-9 shows anti-inflammatory properties through NLRP3 inflammasome suppression in some contexts , it can also promote inflammation in others through T cell activation or myeloid cell recruitment.

• Cancer progression effects: In some cancer models, galectin-9 appears to promote tumor growth through immunosuppression, while in others it may induce apoptosis of certain cancer cells, suggesting context-dependent functions.

• Receptor dependency: The effects of galectin-9 vary depending on the receptor engaged (TIM-3, CD44, PDI, etc.) and the cellular context, contributing to seemingly contradictory outcomes in different experimental systems.

• Isoform-specific effects: With 16 different transcript variants reported for LGALS9 , differences in isoform expression and function may account for some contradictory findings when studies do not specify which isoform is being examined.
  Researchers should address these contradictions by:

• Clearly defining the specific disease model and experimental conditions

• Reporting the predominant isoforms present in their system

• Characterizing the receptor engagement mechanisms

• Considering timing of galectin-9 manipulation in disease progression

What are common technical challenges in detecting LGALS9 protein in mouse tissues?

Researchers frequently encounter several technical challenges when attempting to detect LGALS9 protein in mouse tissues:

• Isoform complexity: With 16 transcript variants encoding proteins ranging from 75 to 355 amino acids , antibody selection becomes critical. Researchers must verify which isoforms their antibodies recognize and whether these match the predominant isoforms in their tissue of interest.

• Protein-carbohydrate interactions: Galectin-9's function depends on carbohydrate binding, which can be disrupted during tissue processing, potentially affecting detection of the functionally active form.

• Subcellular localization: Galectin-9 can be found both intracellularly and extracellularly, requiring different extraction methods for comprehensive analysis.

• Cross-reactivity: Some anti-galectin-9 antibodies may cross-react with other galectin family members due to structural similarities.
  Recommended solutions include:

• Using multiple antibodies targeting different epitopes

• Validating antibodies with positive and negative controls (including knockout tissues)

• Optimizing fixation protocols to preserve carbohydrate interactions

• Employing both intracellular and surface staining protocols for flow cytometry

How can researchers differentiate between direct and indirect effects of LGALS9 modification in mouse models?

Differentiating between direct and indirect effects of LGALS9 modification presents a significant challenge in experimental design. To address this challenge, researchers can implement:

• Cell-specific conditional knockout models: Using Cre-lox systems to delete LGALS9 in specific cell populations (e.g., myeloid cells, pancreatic cells, or T cells) can help isolate direct effects in those lineages.

• Rescue experiments: Reintroducing specific LGALS9 isoforms into knockout models can confirm direct causality and identify which domains/functions are essential.

• Temporal control systems: Inducible knockout or overexpression systems allow for time-resolved analysis of primary versus secondary effects.

• Ex vivo and in vitro validation: Isolating cells from mouse models for controlled in vitro experiments can help distinguish cell-autonomous effects from tissue microenvironment influences.

• Receptor blocking studies: Combining LGALS9 manipulation with blocking antibodies against known receptors (e.g., TIM-3) can help delineate specific signaling pathways.
  For example, in studies of galectin-9's role in NLRP3 degradation, researchers complemented in vivo knockout studies with direct protein interaction assays to establish a mechanistic link between galectin-9 and NLRP3 .

What controls are essential when using anti-LGALS9 antibodies in mouse studies?

When using anti-LGALS9 antibodies for therapeutic or research purposes in mouse studies, several essential controls must be included:

• Isotype controls: These are critical to establish baseline and non-specific effects. In anti-galectin-9 treatment studies, IgG1 kappa isotype controls (matching the antibody class) are typically used .

• Dose-response assessment: Testing multiple antibody doses helps establish optimal therapeutic windows and potential off-target effects at higher concentrations.

• LGALS9 knockout mice: These provide the gold standard negative control for antibody specificity testing.

• Cross-species reactivity validation: When using antibodies developed against human LGALS9, validation of cross-reactivity with mouse LGALS9 is essential. For instance, the 1G3 clone antibody targets a sequence with 69% homology between human and mouse proteins .

• Treatment timing controls: Including groups treated at different disease stages helps distinguish preventive versus therapeutic effects.
  In published research, weekly treatment with 10 μg of anti-galectin-9 (1G3 clone) has shown efficacy in modulating galectin-9 expression in pancreatic tissue, with demonstrated differences in relative fluorescence intensity (RFI) between treatment groups (RFI: 2.06 in treated vs. 3.04 in isotype control groups) .

How might single-cell analysis advance our understanding of LGALS9 function in mouse models?

Single-cell technologies offer unprecedented opportunities to dissect the complex roles of LGALS9 in mouse models:

• Cell-type specific expression patterns: Single-cell RNA sequencing can reveal the heterogeneity of LGALS9 expression across diverse cell populations within tissues, identifying previously unrecognized producer and responder cells.

• Temporal dynamics: Single-cell trajectory analysis can map how LGALS9 expression changes during disease progression or development, particularly in cancer models where tumor and immune cell populations evolve over time.

• Receptor co-expression mapping: Single-cell approaches can identify which cells co-express LGALS9 and its various receptors, highlighting potential autocrine signaling mechanisms.

• Response to therapeutic targeting: These technologies can comprehensively assess how anti-LGALS9 therapies reshape the cellular landscape, particularly in immune cell populations.

• Spatial context: Spatial transcriptomics can preserve tissue architecture information, revealing how LGALS9-expressing cells are positioned relative to other cell types in the microenvironment.
  These approaches would be particularly valuable in models like KC mice, where understanding the spatial and temporal dynamics of LGALS9 expression in relation to developing PanIN lesions could identify optimal intervention windows.

What transgenic mouse models would advance LGALS9 research beyond current capabilities?

Several innovative transgenic mouse models could significantly advance LGALS9 research:

• Isoform-specific knockin/knockout models: Given the 16 transcript variants of LGALS9 , developing models that selectively express or delete specific isoforms would help delineate their unique functions.

• Reporter mouse lines: Generating mice with fluorescent proteins or luciferase under control of the LGALS9 promoter would enable real-time monitoring of expression dynamics in living animals.

• Receptor-ligand double transgenic models: Creating mice with modifications to both LGALS9 and its major receptors (like TIM-3) would help dissect the relative contributions of different signaling pathways.

• Humanized LGALS9 models: Replacing mouse LGALS9 with the human ortholog would improve translational relevance for therapeutic development.

• Inducible overexpression models: Tissue-specific, temporally controlled LGALS9 overexpression would help identify sufficient conditions for phenotypic changes versus merely necessary contributions.

• Domain mutation models: Introducing specific mutations in carbohydrate recognition domains would help distinguish between the lectin-dependent and independent functions of galectin-9.
  These models would complement existing resources like the commercially available CRISPR knockout kits to provide a more comprehensive experimental toolkit.

How can multi-omics approaches be integrated to better understand LGALS9 biology in mouse models?

Integrating multiple omics approaches offers powerful insights into LGALS9 biology beyond what any single method can provide:

• Genomics + Transcriptomics: Combining genotyping with RNA-seq can reveal how genetic variation influences LGALS9 expression patterns and splice variant selection across different mouse strains.

• Transcriptomics + Proteomics: Parallel analysis can identify post-transcriptional regulation mechanisms, as mRNA levels of LGALS9 may not directly correlate with protein abundance in some contexts.

• Proteomics + Interactomics: Mass spectrometry-based approaches coupled with proximity labeling can identify novel binding partners of galectin-9 beyond known receptors like TIM-3.

• Glycomics + Proteomics: Since galectin-9 function depends on glycan binding, characterizing the glycome alongside protein interactors can reveal how glycosylation patterns affect galectin-9 activity.

• Metabolomics + Functional Assays: Correlating metabolic changes with galectin-9 function can uncover how this protein influences cellular energy states and metabolic reprogramming in disease models. Implementation of such integrated approaches would be particularly valuable in complex disease models like KC mice, where galectin-9 contributes to multiple aspects of disease progression through diverse mechanisms.