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Review

Lipid Antigens: Revealing the Hidden Players in Adaptive Immune Responses

by
Tamana Eskandari
1,2,
Yasamin Eivazzadeh
1,2,
Fatemeh Khaleghinia
1,2,
Fatemeh Kashi
1,2,
Valentyn Oksenych
3,* and
Dariush Haghmorad
2,*
1
Student Research Committee, Semnan University of Medical Sciences, Semnan 35147-99442, Iran
2
Department of Immunology, School of Medicine, Semnan University of Medical Sciences, Semnan 35147-99442, Iran
3
Faculty of Medicine, University of Bergen, 5020 Bergen, Norway
*
Authors to whom correspondence should be addressed.
Biomolecules 2025, 15(1), 84; https://doi.org/10.3390/biom15010084
Submission received: 4 December 2024 / Revised: 31 December 2024 / Accepted: 7 January 2025 / Published: 8 January 2025
(This article belongs to the Section Molecular Biology)

Abstract

:
Traditionally, research on the adaptive immune system has focused on protein antigens, but emerging evidence has underscored the essential role of lipid antigens in immune modulation. Lipid antigens are presented by CD1 molecules and activate invariant natural killer T (iNKT) cells and group 1 CD1-restricted T cells, whereby they impact immune responses to pathogens and tumors. Recent advances in mass spectrometry, imaging techniques, and lipidomics have revolutionized the identification and characterization of lipid antigens and enhanced our understanding of their structural diversity and functional significance. These advancements have paved the way for lipid-based vaccines and immunotherapies through the application of nanoparticles and synthetic lipid antigens designed to boost immune responses against cancers and infectious diseases. Lipid trafficking, CD1 molecule interactions, and the immune system’s response to lipid antigens are yet to be completely understood, particularly in the context of autoimmunity and microbial infections. In the years to come, continued research efforts are needed to uncover its underlying biological mechanisms and to exploit the full potential of therapies directed against lipid antigens.

1. Introduction

The adaptive immune system, which integrates antigen-presenting cells (APCs), B cells, and T cells, produces specific immunity to antigens via cellular and humoral immune responses [1]. Contrary to the innate immune system, it also bestows immunological memory. After a primary response, antibodies produced by long-lived plasma cells in the bone marrow and memory B and T cells in secondary lymphoid tissues provide long-lasting immunity, allowing faster and more potent responses upon re-exposure [2].
Recognition of antigens presented by APCs through the T cell receptor (TCR) is essential for cellular immune responses. T cells can be divided into different functional types based on environmental cues and co-stimulatory or inhibitory signals [3]. Cytotoxic CD8+ T cells, CD4+ T helper cells, regulatory T cells, and memory T cells perform diversified functions such as killing infected cells through the release of perforins and granzymes, providing co-stimulatory signals through direct cell contact or cytokine release, regulating immune responses to prevent tissue damage, and providing faster and more potent responses during re-exposure to antigens (Figure 1) [4,5].
Naïve B cells identify antigens through their BCR and after co-stimulatory interactions with CD4+ T helper cells differentiate into plasma cells and memory B cells [6]. Plasma cells secrete antibodies that circulate throughout the body and tag foreign antigens for elimination.

2. Traditional Focus on Protein Antigens

A protein antigen may be recognized by the immune system and trigger an immune response (i.e., an immunogen). Protein antigens can originate from pathogens (such as viruses or bacteria), allergens derived from the environment, or from the body’s own tissues [7]. Protein antigens vary in structure: linear epitopes consist of short, continuous amino acid sequences whereas those forming conformational epitopes are recognized as three-dimensional structures. Protein antigens are essential in the development of vaccines, diagnostics, and therapies for a variety of diseases [8].
When the immune system encounters protein antigens, it triggers a series of responses aimed at neutralizing or eliminating the perceived threat. This includes the activation of T cells, the production of antibodies, and the generation of memory cells for future immunity [9]. The immune response to protein antigens is a complex and highly regulated process. Antigen processing and presentation are the cornerstones of adaptive immunity. Generally, B cells cannot generate high-affinity antibodies to protein antigens without cognate T cell help, which is typically provided in follicular germinal centers or through extrafollicular interactions [10,11]. CD4+ T cells, which provide such help, recognize short antigen-derived peptides bound to cell surface glycoproteins encoded by polymorphic major histocompatibility class II (MHC-II) genes presented by APCs (Figure 2) [12]. In contrast, eradication of virus-infected cells occurs through the action of cytotoxic CD8+ T cells, which rely on the recognition of peptide–MHC class I complexes for their action [13].
For research and diagnostic purposes, detection reagents with enhanced avidity for antigen-specific TCRs are essential. This is achieved by generating MHC class I–peptide tetramers through the polymerization of MHC molecules, which are then tagged (e.g., via biotinylation) to facilitate signal amplification and precise detection [14].
Researchers utilize a range of techniques to study protein antigens, including mass spectrometry, protein crystallography, ELISA, and various molecular biology methods. While traditional methods have been instrumental in protein antigen studies, they are not without limitations [15]. Technical challenges such as time-consuming protocols, limited detection sensitivity, and cross-reactivity have hindered a comprehensive understanding of certain antigens [16]. Recent years have witnessed significant advancements in protein antigen research, from high-throughput screening techniques to advanced computational modeling; these developments have revolutionized the study of antigens and enabled deeper insights into their structures, functions, and interactions with the immune system [17].
The protein-centric view of immune responses and molecular approaches based thereon have arguably been unfavorable to our understanding of carbohydrates, lipids, and nucleic acids as antigens [18,19]. The immune system is trained to recognize and respond to foreign antigens; nevertheless, it also needs to be tolerant of self-antigens to avoid autoimmune reactions [20]. Immune recognition also involves non-protein-sensing components such as pattern recognition receptors (PRRs) and certain Toll-like receptors (TLRs) which recognize conserved molecular patterns on pathogens. Such components are essential for efficient immune responses but are not directly addressed by protein antigen-based studies [21,22].

3. Introduction to Lipids in Adaptive Immunity

The immune system is stimulated by a wide range of antigenic molecules from both endogenous and external sources [23]. In addition to proteins, lipids, and phosphorylated metabolites can also activate T cells [24]. Lipids are hydrophobic biomolecules that play crucial roles in immune responses. They are essential components of cell membranes, influencing membrane properties and immune cell functions [25].
Lipids also serve as signaling molecules that regulate immune cell activation, differentiation, and effector functions. They can directly activate immune cells through their interactions with specific receptors or co-receptors, such as lipopolysaccharides (LPSs) on innate immune cells [26]. In B cells, signals through TLR4 and the BCR synergize [27]. To initiate adaptive immune responses, lipid antigens are presented by APCs to T helper cells via CD1 molecules [28].
Lipid antigens can originate from various sources, including bacteria, fungi, environmental factors (such as allergens), and endogenous lipid molecules present in host cells and tissues. Additionally, some viruses acquire lipids from host cells during their replication process, forming a lipid envelope [29]. The recognition of lipid antigens by the immune system involves microbial CD1d-restricted lipid-based antigens and NKT cells [30]. Atypical MHC class I proteins of the CD1 family bind and present lipid antigens. Compared to classical MHC class I molecules, which are highly polymorphic, CD1 genes are less diverse in terms of sequence, having very few or no synonymous single-nucleotide polymorphisms [31]. When the TCR of a lipid-specific T cell forms cognate contacts with CD1–antigen complexes on the APC, both cells become activated. This interaction is critical for invariant natural killer T (iNKT) cell maturation, selection, and egress from the thymus. It may also aid in the formation of group 1 CD1-restricted T cells. In the periphery, lipid antigens derived from the body, microbes, and the environment may activate CD1-restricted T lymphocytes (Figure 3) [32].
The quality and amount of complexes present on the surface of APC, TCR affinity, and the successful engagement of co-stimulatory and adhesion molecules with their corresponding ligands all have an impact on the stimulatory interaction of the TCR with CD1–antigen complexes [33]. The ability of CD1-restricted T lymphocytes to migrate through tissues is crucial for their activation. Depending on the strength of the signal received during antigen recognition (determined by the number of CD1 complexes), CD1-restricted T cells release a range of cytokines [34]. The inherent properties of lipids define the physical needs for their presentation mechanism. Lipids exhibit poor solubility in water, which means that they are consistently linked to membranes or lipid-transfer proteins (LTPs) in biological fluids and tissues [35]. Lipid-binding proteins are essential for lipid absorption by APCs, their intracellular transit, and processing prior to CD1 loading [36]. Furthermore, distinct CD1 isoforms exhibit both overlapping and disparate lipid-binding specificities, which directly affect the ability of lipid antigens to elicit T cell activation [30].

4. Discovery of Lipid Antigens

Unraveling the role of lipids as antigens has been a gradual process, marked by significant milestones that have deepened our understanding of immune recognition and immune responses. Two landmark papers described lipid presentation to T cells on CD1 molecules [37,38]. CD1 molecules are a group of glycoproteins structurally similar to MHC class I molecules. While MHC molecules are primarily involved in presenting peptide antigens to T cells, CD1 molecules possess a hydrophobic binding groove capable of accommodating lipid antigens [39]. This discovery provided the first insight into the existence of a specialized pathway for presenting lipid antigens to T cells [40]. Subsequent investigations demonstrated that lipid antigens, such as glycolipids and phospholipids, could indeed stimulate T cell responses. This finding challenged the conventional understanding that immune recognition was solely based on protein antigens [41]. Subsequent studies revealed the presence of specialized T cell subsets, including NKT cells and CD1-restricted T cells, which exhibited unique recognition properties and played critical roles in immune regulation and host defense [42].
The isolation and characterization of lipid antigens from various sources further expanded our understanding of their structural diversity and functional significance. Techniques such as lipid extraction, purification by HPLC, and mass spectrometry enabled researchers to identify specific lipid antigens and elucidate their roles in immune responses [43]. Functional studies using lipid antigens and genetically modified mouse models lacking CD1 molecules provided valuable insights into the mechanisms underlying lipid antigen presentation and immune modulation [28,36,44]. These studies demonstrated that lipid antigens could modulate immune cell activation, cytokine production, and effector functions, thereby influencing the outcome of immune reactions [45,46].
Moreover, the pathophysiological relevance of lipid antigens becomes apparent in various contexts, including infectious diseases, autoimmune disorders, and cancer [47,48,49]. Lipid antigens derived from microbial pathogens, such as mycobacteria and Borrelia burgdorferi, were found to activate immune responses and contribute to host defense mechanisms [50,51]. Conversely, dysregulation of lipid antigen recognition has been implicated in autoimmune diseases, highlighting the importance of lipid-mediated immune regulation in maintaining immune homeostasis [52].

5. Role of Lipid Antigens in T Cell Activation

Understanding lipid recognition by T cells is crucial for understanding host defenses to infections, tumor immune surveillance, and autoimmunity [30]. CD1 antigen-presenting molecules bind lipids to present them to the T cells. It follows that lipids are only T cell immunogenic if they can bind CD1 [53]. Five isoforms of CD1, non-classical MHC class I-like proteins with a narrow, deep hydrophobic cleft binding groove, are called CD1a-e in humans. CD1a-d present foreign and self-lipid/glycolipid antigens to lipid-reactive T lymphocytes, whereas CD1e only takes part in antigen processing but not in presentation [33,54]. T cell responses are only elicited after CD1 lipid presentation on the cell surface after the following steps: antigen uptake, cross-priming and cross-presentation, processing, CD1 assembly and recycling, lipid trafficking, CD1 loading with lipids, and persistence of lipid–CD1 complexes on the cell surface [55,56].
The uptake of lipid antigens primarily involves intracellular loading onto CD1 molecules, although surface loading may occur in specific cases. Glycolipids can activate specific T cells through cross-priming and cross-presentation, where antigens are internalized by CD1d-expressing APCs, processed, and presented. For instance, microbial glycosphingolipids undergo partial degradation in late endosomes, exposing their antigenic head groups before being loaded onto CD1 molecules for engagement with TCRs [57]. The assembly and recycling of CD1 molecules vary across isoforms, with CD1a predominantly trafficked through early recycling endosomes, while CD1b is processed in late endosomes, reflecting their distinct roles in antigen presentation within cellular compartments [58]. Lipid trafficking, mediated by lipid-transfer proteins, influences the distribution and immunogenicity of lipids, with acidic and neutral lipids continuously moving between membrane layers. In the following step, the persistence of lipid–CD1 complexes on APC surfaces is substantial for efficient priming of T cells. CD1b and CD1c have shorter half-lives due to transport in distinct endosomal compartments different from CD1a [59].
T cells recognizing lipids via CD1 molecules fall into two main groups: those restricted by group 1 CD1 molecules (i.e., CD1a-CD1c) and those restricted by CD1d, which resemble peptide-specific T cells and innate immune cells, respectively [60]. The primary CD1d-restricted cells are invariant natural killer T (iNKT) cells, which express NK cell markers and a semi-invariant TCR (an invariant TCRα chain paired with a TCRβ chain and limited Vβ usage) [33,54]. Upon detection of the lipid antigen, iNKT cells produce both Th1 (TNF-α and IFN-γ) and Th2 (IL-4, IL-5, and IL-13) cytokines; this dual functionality allows iNKT cells to support both inflammatory and immune-regulatory pathways. These cytokines rapidly induce DC maturation, which facilitates cytotoxic T cell priming [41,61]. It has also been demonstrated that iNKT cells can secrete anti-inflammatory cytokines such as TGF-β and IL-10 in response to polyclonal TCR activation.
Group 1 CD1-restricted CD4+ T cells, although diverse in their TCRs, respond more slowly to CD1–lipid complexes as compared to iNKT cells, which are more similar to conventional T cells. Most of these T cells recognize combined CD1–self-lipid complexes, while some recognize CD1 molecules alone [62]. Group 1 CD1-restricted T cells release a variety of cytokines in response to infection, inflammation, and tumors. When stimulated with self-antigens, they release IFN-γ, TNF-α, IL-17, and IL-22 [42]. The majority of them do not appear to release Th2 and/or regulatory cytokines in response to antigenic stimulation, in contrast to group 2 CD1-restricted T cells. More research is required to find out if Th2 and/or regulatory cytokines are produced by group 1 CD1-restricted T cells in different infectious or inflammatory settings [61,63,64].

6. Lipids in B Cell Responses

Lipids play essential roles in B cell responses, influencing various aspects of B cell activation, differentiation, and antibody production [65]. Lipids can directly influence B cell activation through interactions with specific receptors or co-receptors on the B cell surface. For example, certain lipid antigens or lipid-derived molecules can bind to TLRs on B cells, triggering signaling pathways that lead to B cell activation and proliferation [66]. Additionally, lipid rafts, specialized microdomains enriched in cholesterol and sphingolipids, play a crucial role in BCR signaling by facilitating the clustering of BCRs and downstream signaling molecules upon antigen recognition [67,68].
Lipids contribute to the process of antibody production by providing essential components for B cell function. Lipids are crucial for the formation and stability of lipid bilayers in membranes, including the membranes of plasma cells, which are responsible for antibody secretion [67]. Furthermore, lipids serve as precursors for lipid mediators that can modulate B cell function and antibody production. For instance, certain eicosanoids derived from arachidonic acid metabolism have been shown to regulate B cell proliferation and antibody secretion [69].
Specific CD1 molecules, such as CD1c and CD1d, are expressed on specific subsets of B cells, including marginal zone (MZ) B cells and memory-like B cells. These molecules play crucial and unique roles in lipid antigen presentation, distinguishing their function from MHC molecules, which primarily present peptides. CD1c and CD1d facilitate the presentation of lipid and glycolipid antigens to CD1-restricted T cells, enabling unique interactions in the immune system. While CD1d predominantly engages iNKT cells, key players in innate immunity, CD1c may interact with other specialized T cell subsets. However, its exact role requires further exploration [70,71].
CD1d expression enables B cells to present lipid antigens and activate NKT cells, leading to rapid cytokine secretion that enhances or modulates immune responses. In contrast, CD1c, highly expressed in MZ B cells, is implicated in broader immune regulation through its ability to present antigens to T cells. However, the expression of these molecules is not static; B cell activation, mainly through CD40L signaling, downregulates both CD1c and CD1d. This dynamic regulation, which creates a limited window for optimal lipid antigen presentation, is an intriguing and engaging aspect of B–T cell interactions in immune regulation that warrants further exploration [70,71].
Notably, retinoic acid receptor (RAR) signaling pathways can reverse the downregulation of CD1d and CD1c induced by activation, suggesting a potential therapeutic target for modulating immune responses. These findings underscore the paramount importance of CD1 molecules in shaping humoral immunity and reveal a complex regulatory mechanism that balances B cell activation with lipid antigen presentation to maintain immune homeostasis. The potential therapeutic implications of these findings in modulating immune responses highlight the practical applications of this research and significantly impact our understanding of immune regulation [71,72].
Lipids may also play a role in antibody class switching, a process by which B cells change the class of antibody they produce, e.g., switching from IgM to IgG [73]. Lipid mediators, such as prostaglandins, have been shown to regulate antibody class switching by modulating cytokine production and B cell activation [74]. Additionally, lipid antigens presented by APCs may influence the cytokine microenvironment, thereby affecting the direction of antibody class switching. Understanding the intricate interplay between lipids and B cells is essential for elucidating the mechanisms underlying immune responses and may offer insights into the development of novel therapeutic strategies targeting lipid pathways in immune-related diseases [75].

7. Impact of Lipid Antigens on the Immune System and Its Relevance to Disease

The identification of lipid molecules by T lymphocytes as antigens was a groundbreaking finding in the field of cellular immunology, leading to novel insights into the immune response against microorganisms, cancer cells, and autoimmunity [37]. Immune-mediated illnesses can develop or worsen as a result of any disturbance to the balance that governs lipid homeostasis in adaptive immune cells [76].
Lipid antigens, including glycolipids and phospholipids, can influence cancer progression by modulating immune responses and affecting the tumor microenvironment. Dysregulation of lipid metabolism is a hallmark of cancer [77]. Highly expressed glycosphingolipids (GSLs) are tumor-associated antigens that trigger antibody responses [78]. GSLs play a role as adhesion molecules for tumor cells during metastasis and are involved in signal transduction. GSLs are exploited to develop antitumor vaccines and are potential targets for cancer therapy [79]. Normal tissue and tumors both contain GSLs, but only when these lipids are on the surface of tumor cells can they function as effective immunogens. In contrast to GSLs found on normal cells, tumor-derived GSLs might react differently to antibodies [80]. GSLs are thought to regulate important molecules involved in signal transduction, specifically gangliosides and the breakdown products of these molecules, to regulate cell development [81]. Patients with melanoma have ganglioside-specific serum antibodies. Melanoma growth may be inhibited by actively immunizing against gangliosides to artificially raise the level of specific anti-ganglioside antibodies [82].
The presentation of M. tuberculosis lipid antigens by group 1 CD1 molecules has been extensively studied. In vitro investigations have revealed that group 1 CD1-restricted T cells exhibit cytotoxicity and produce IFN-γ and TNF-α upon encountering M. tuberculosis antigens [83]. Furthermore, individuals exposed to mycobacteria show higher frequencies of group 1 CD1-restricted M. tuberculosis lipid antigen-specific T cells compared to a control population [84,85]. M. tuberculosis produces a diverse array of lipids, which form stable complexes with CD1 molecules and elicit T cell responses. The structures of these antigenic lipids can vary greatly; each lipid may stimulate unique T cells that are capable of discerning subtle lipid structural changes [86,87]. Certain M. tuberculosis lipid antigens play crucial roles in preventing the emergence of negative mutants capable of evading the immune response. T cells specific for lipid antigens are activated during Mycobacterium tuberculosis infection and contribute to protective immune functions [88].
Several studies have shown that the LPS of some C. jejuni strains causes people with Guillain–Barre syndrome (GBS) to produce antibodies that cross-react with gangliosides from peripheral nerves [89].
Sphingolipids in host cells are used as membrane receptors by a variety of pathogens. Pathogen infection and host defense are regulated by sphingolipid metabolites. For example, a particular glycosphingolipid functions as an endogenous ligand to activate NKT cells [90]. Furthermore, the development of antibodies that cross-react with mammalian sphingolipids is a contributing factor in certain autoimmune disorders that arise after infections [48].

8. Lipid-Based Vaccines and Immunotherapies

Lipid-based immunotherapies, also known as developmental vaccines and cancer immunotherapies, regulate immune system responses by using lipid molecules in the form of adjuvants or vectors. Several lipid-based techniques have been explored in recent years to modulate immune responses and aid in disease treatment [91].
One of these strategies is the use of lipid-based nanoparticles (LBNPs) consisting of liposomes, emulsions, solid lipid nanoparticles, and nanostructured lipid carriers, which can carry and encapsulate immunomodulatory compounds such as small molecules (synthetic drugs) and nucleic acids (e.g., mRNA [92]). Compared to conventional delivery strategies, this new strategy has higher solubility in the aqueous phase and lower toxicity. It also aids the delivered nucleic acid to be released from endosomes and increases the stability of its content [93]. Nevertheless, it has disadvantages such as liver toxicity, cationic lipid cytotoxicity, and a low efficacy of small molecule encapsulation. Thus, we need to put further effort into improving LBNP technology. To increase vaccine efficacy against pathogens, adjuvant strategies employ lipid-based delivery systems such as liposomes and emulsions [94].
Apart from the previously mentioned techniques, synthetic lipid antigens are also employed to modulate immune responses. For example, recent studies have demonstrated that synthetic glycolipids, either by themselves or loaded on DCs, can trigger the production of pro-inflammatory cytokines by iNKT cells. This results in an antitumor effect, through the stimulation of cytotoxic lymphocytes with specificity for tumor antigens and through the inhibition of angiogenesis [95,96]. Similarly, tumor growth inhibition can be achieved through activating NKT cells by the use of the CD1d/glycolipid combination and cancer-specific antibody complex. These applications promise novel techniques in immunotherapies by using lipid antigens to modulate immune responses, leading to fighting a variety of diseases such as cancers and autoimmune disorders [97].

9. Technological Advances in Lipid Antigen Research

Lipids play critical roles in biological systems; thus, deepening our understanding of lipid metabolism may provide novel insights into the diagnosis and pathophysiology of diseases. Recent technological advancements have enabled the development of cutting-edge tools for lipid antigen analysis. Mass spectrometry-based techniques, such as MALDI-TOF and ESI-MS, have revolutionized the identification and characterization of lipid antigens [98]. Additionally, high-resolution imaging modalities, including super-resolution microscopy and cryo-electron microscopy, have provided unprecedented insights into lipid antigen interactions within cellular contexts. These emerging tools offer enhanced sensitivity, resolution, and reproducibility, empowering researchers to unravel the complexities of lipid antigen structures and functions with unprecedented precision [99].
Recent advances in lipidomics, mainly through advanced mass spectrometry techniques, have significantly enhanced our understanding of lipid antigen presentation by CD1 molecules [43]. High-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (HPLC-QToF-MS) has enabled sensitive detection and characterization of a wide range of lipids bound to CD1 molecules, including hydrophobic lipids, glycolipids, and phospholipids [100]. This approach allows for the resolution of ion chromatograms representing diverse lipid species, while collision-induced dissociation (CID)–MS further elucidates their chemical structures. These methods have facilitated the identification of specific lipid-binding motifs and size-dependent antigen display mechanisms across different CD1 isoforms. For instance, structural studies revealed that CD1b can bind two small lipids simultaneously within its cleft, unlike the single-lipid binding observed for CD1a and CD1d, highlighting isoform-specific lipid presentation strategies [101].
Additionally, the integration of lipidomics and bioinformatics has led to the comprehensive mapping of over 2000 lipid species presented by CD1 molecules. This extensive lipidomic resource, offering a wealth of information for identifying new antigens and therapeutic targets, has the potential to revolutionize biomedical research. High-resolution crystallography has further contributed by providing detailed insights into lipid seating mechanisms, such as the dual-chamber arrangement in CD1b that positions lipids for effective T cell receptor interaction [101]. These advances deepen our understanding of the molecular basis of lipid antigen presentation and have implications for biomedical research, including the identification of lipid-based immune regulators and potential interventions for diseases involving lipid-mediated immunopathology [102].
Lipidomics, driven by advancements in mass spectrometry and chromatography, offers deep insights into disease diagnosis and pathophysiology as well. Integrating lipidomics with other biological data sources holds promise for drug development and will indisputably provide clinicians with novel insights into disease biology [103]. Artificial intelligence and machine learning have emerged as indispensable tools in lipid antigen discovery. Advanced algorithms can analyze vast datasets to identify potential lipid antigens, as well as to predict their binding affinities and assess their immunological relevance. The integration of AI technologies with experimental approaches has enabled lipid antigen discovery, thereby offering new avenues for the development of targeted therapeutics and precision medicine strategies [104].

10. Future Directions and Challenges

Understanding the limitations and opportunities of lipid antigen discovery is essential for advancing research and addressing critical issues regarding the role of lipids in immune responses. Current research on CD1-restricted T cell responses, which have the potential to cause skin, respiratory, and intestinal diseases, is limited, partly due to the challenges posed by working with infectious organisms and the absence of CD1 group 1 molecules in mice [104,105]. These responses, associated with various disorders, are further hindered by technological limitations in isolating and detecting lipid antigens. Nevertheless, advancements in CD1 tetramers, 3D-culture methods, and lipidomics offer promising avenues to elucidate CD1-mediated immune responses in the years to come. Furthermore, the high frequency of lipid-specific T cells, which are crucial to immune response modulation, is also associated with autoimmune diseases and defense against infections. Nevertheless, human CD1 polymorphisms preclude lipid-specific immunity, making microbial lipids less susceptible to genetic mutation-driven selection pressures [41,106].
In addition to clarifying the molecular mechanisms of lipid insertion into the CD1 groove, future research in lipid antigen biology should concentrate on defining the cellular sub-compartments where lipid antigens and CD1 proteins interact. Although CD1 protein trafficking has been the focus of previous research, it is imperative to examine lipid trafficking as well. The non-random distribution of lipids presented by CD1 in particular cellular sub-compartments implies complex mechanisms that should be investigated to gain a better understanding of the roles of lipid-specific T cells and their immunological therapeutic implications [107,108].
Recent advancements have shed light on the role of lipid antigens in T cell immunity, particularly through group 1 CD1 molecules. These efforts have been facilitated by CD1 tetramer technology, solving crystal structures of lipid-reactive TCRs, and studies of defined molecular variations enabling diverse lipid-based antigen accommodation [109]. However, further research is needed to explore the impact of these variations on the antigen repertoire, lipid presentation, and T cell immunity. The complexity of CD1-restricted T cell functions, especially when it comes to recognizing lipid antigens, underscores the necessity for continued investigation into lipid processing and presentation, to understand lipid-specific immune responses and to develop therapeutic interventions [110]. Exploring CD1-mediated immune responses in the pathophysiology of mucosal tissues and their connections to cellular metabolism may pave the way for innovative therapeutics targeting a range of disorders [54].
Ultimately, the development of vaccines relies on identifying lipid compounds that contribute to bacterial pathogenicity and leveraging the absence of functional CD1 polymorphisms. A prominent example could be a study of how the use of lipid antigens could enhance anti-mycobacterial immunity [111]. The research asserts the significance of the CD1e polymorphism in regulating microbial antigen processing and enhancing immune responses specific to lipids. Variations in CD1e residues may impact the antigen binding pocket, potentially influencing vaccine development [112]. Preliminary trials using a crude lipid extract from M. tuberculosis as a vaccine have shown promising results in reducing pathology and bacterial burdens in tuberculosis models [113]. Further research into immunization with individual synthetic lipids offers potential as innovative subunit vaccine components, highlighting the promising role of lipids in vaccine development.

11. Conclusions

In summary, the exploration of lipid antigens and their role in adaptive immunity has unveiled significant insights that challenge the protein-centric view of immune responses. Key findings highlight that lipid antigens, presented by CD1 molecules, play a crucial role in immune surveillance and response, particularly through the activation of iNKT cells and group 1 CD1-restricted T cells. This expands our understanding of antigen diversity and the mechanisms through which the immune system recognizes and responds to pathogens and tumors.
The importance of lipid antigens in adaptive immunity underscores the need to consider these molecules in both fundamental immunological research and clinical applications. Technological innovations in mass spectrometry, imaging techniques, and lipidomics have revolutionized the identification and characterization of lipid antigens, offering deeper insights into their structural and functional diversity. These advancements have enabled the development of lipid-based vaccines and immunotherapies, promising novel strategies for enhancing immune responses against cancers and infectious diseases. Therefore, boosting immune responses against lipids may synergize with “classical” immunotherapies targeted against mutated self- or foreign protein antigens.

Author Contributions

T.E., Y.E., F.K. (Fatemeh Khaleghinia), F.K. (Fatemeh Kashi), and D.H. wrote the main manuscript. T.E., Y.E., F.K. (Fatemeh Khaleghinia) and F.K. (Fatemeh Kashi) designed the figures. D.H. and V.O. reviewed the manuscript and figures. All the authors contributed to the writing and editing of the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. McComb, S.; Thiriot, A.; Akache, B.; Krishnan, L.; Stark, F. Introduction to the immune system. In Immunoproteomics: Methods and Protocols; Springer: Berlin/Heidelberg, Germany, 2019; pp. 1–24. [Google Scholar]
  2. Stewart, J.; Weir, D. Innate and acquired immunity. In Medical Microbiology; Greenwood, D., Ed.; Churchill Livingstone: New York, NY, USA, 2012; pp. 109–135. [Google Scholar]
  3. Yokosuka, T.; Saito, T. The immunological synapse, TCR microclusters, and T cell activation. Immunol. Synap. 2010, 340, 81–107. [Google Scholar]
  4. Koike, T.; Fujii, K.; Kometani, K.; Butler, N.S.; Funakoshi, K.; Yari, S.; Kikuta, J.; Ishii, M.; Kurosaki, T.; Ise, W. Progressive differentiation toward the long-lived plasma cell compartment in the bone marrow. J. Exp. Med. 2023, 220, e20221717. [Google Scholar] [CrossRef]
  5. Sharma, S.K. B Cells. In Basics of Hematopoietic Stem Cell Transplant; Springer: Berlin/Heidelberg, Germany, 2023; pp. 87–120. [Google Scholar]
  6. Rastogi, I.; Jeon, D.; Moseman, J.E.; Muralidhar, A.; Potluri, H.K.; McNeel, D.G. Role of B cells as antigen presenting cells. Front. Immunol. 2022, 13, 954936. [Google Scholar] [CrossRef] [PubMed]
  7. Mir, M.A.; Hamdani, S.S.; Mehraj, U.; Qayoom, H.; Sheikh, B.; Nisar, S.; Bhat, B. Antigens and immunogens. Basics Fundam Immunol. 2020, 1, 77–103. [Google Scholar]
  8. Saylor, K.; Gillam, F.; Lohneis, T.; Zhang, C. Designs of antigen structure and composition for improved protein-based vaccine efficacy. Front. Immunol. 2020, 11, 504077. [Google Scholar] [CrossRef]
  9. Rich, R.R.; Chaplin, D.D. The human immune response. In Clinical Immunology; Elsevier: Amsterdam, The Netherlands, 2019; pp. 3–17.e1. [Google Scholar]
  10. Pishesha, N.; Harmand, T.J.; Ploegh, H.L. A guide to antigen processing and presentation. Nat. Rev. Immunol. 2022, 22, 751–764. [Google Scholar] [CrossRef]
  11. Elsner, R.A.; Shlomchik, M.J. Germinal Center and Extrafollicular B Cell Responses in Vaccination, Immunity, and Autoimmunity. Immunity 2020, 53, 1136–1150. [Google Scholar] [CrossRef]
  12. Ostrand-Rosenberg, S.; Pulaski, B.A.; Gunther, V. Processing and Presentation of Antigen for the Activation of Lymphocytes to Tumor Cells. In Tumor Immunology; CRC Press: Boca Raton, FL, USA, 2002; Volume 48. [Google Scholar]
  13. Kedzierska, K.; Koutsakos, M. The ABC of major histocompatibility complexes and T cell receptors in health and disease. Viral Immunol. 2020, 33, 160–178. [Google Scholar] [CrossRef]
  14. Altman, J.D.; Davis, M.M. MHC-peptide tetramers to visualize antigen-specific T cells. Curr. Protoc. Immunol. 2016, 115, 17.13.11–17.13.44. [Google Scholar] [CrossRef] [PubMed]
  15. Büyükköroğlu, G.; Dora, D.D.; Özdemir, F.; Hızel, C. Techniques for protein analysis. In Omics Technologies and Bio-Engineering; Elsevier: Amsterdam, The Netherlands, 2018; pp. 317–351. [Google Scholar]
  16. Mattioli, I.A.; Hassan, A.; Oliveira Jr, O.N.; Crespilho, F.N. On the challenges for the diagnosis of SARS-CoV-2 based on a review of current methodologies. ACS Sens. 2020, 5, 3655–3677. [Google Scholar] [CrossRef]
  17. Gallo, E. The rise of big data: Deep sequencing-driven computational methods are transforming the landscape of synthetic antibody design. J. Biomed. Sci. 2024, 31, 29. [Google Scholar] [CrossRef]
  18. Yazhini, A.; Srinivasan, N.; Sandhya, S. Signatures of conserved and unique molecular features in Afrotheria. Sci. Rep. 2021, 11, 1011. [Google Scholar] [CrossRef]
  19. Lössl, P.; van de Waterbeemd, M.; Heck, A.J. The diverse and expanding role of mass spectrometry in structural and molecular biology. EMBO J. 2016, 35, 2634–2657. [Google Scholar] [CrossRef]
  20. Valdes, A.Z. Immunological tolerance and autoimmunity. In Translational Autoimmunity; Elsevier: Amsterdam, The Netherlands, 2022; pp. 325–345. [Google Scholar]
  21. Zhu, Y.; Deng, J.; Nan, M.-L.; Zhang, J.; Okekunle, A.; Li, J.-Y.; Yu, X.-Q.; Wang, P.-H. The interplay between pattern recognition receptors and autophagy in inflammation. In Autophagy Regulation of Innate Immunity; Springer: Berlin/Heidelberg, Germany, 2019; pp. 79–108. [Google Scholar]
  22. Tennant, I.; Pound, J.; Marr, L.; Willems, J.; Petrova, S.; Ford, C.; Paterson, M.; Devitt, A.; Gregory, C. Innate recognition of apoptotic cells: Novel apoptotic cell-associated molecular patterns revealed by crossreactivity of anti-LPS antibodies. Cell Death Differ. 2013, 20, 698–708. [Google Scholar] [CrossRef] [PubMed]
  23. Storni, T.; Kündig, T.M.; Senti, G.; Johansen, P. Immunity in response to particulate antigen-delivery systems. Adv. Drug Deliv. Rev. 2005, 57, 333–355. [Google Scholar] [CrossRef]
  24. Patrussi, L.; Mariggiò, S.; Corda, D.; Baldari, C.T. The glycerophosphoinositols: From lipid metabolites to modulators of T-cell signaling. Front. Immunol. 2013, 4, 213. [Google Scholar] [CrossRef]
  25. De Libero, G.; Mori, L. How the immune system detects lipid antigens. Prog. Lipid Res. 2010, 49, 120–127. [Google Scholar] [CrossRef]
  26. Di Gioia, M.; Zanoni, I. Toll-like receptor co-receptors as master regulators of the immune response. Mol. Immunol. 2015, 63, 143–152. [Google Scholar] [CrossRef]
  27. Pone, E.J.; Zhang, J.; Mai, T.; White, C.A.; Li, G.; Sakakura, J.K.; Patel, P.J.; Al-Qahtani, A.; Zan, H.; Xu, Z. BCR-signalling synergizes with TLR-signalling for induction of AID and immunoglobulin class-switching through the non-canonical NF-κB pathway. Nat. Commun. 2012, 3, 767. [Google Scholar] [CrossRef]
  28. Dowds, C.M.; Kornell, S.-C.; Blumberg, R.S.; Zeissig, S. Lipid antigens in immunity. Biol. Chem. 2014, 395, 61–81. [Google Scholar] [CrossRef] [PubMed]
  29. Jappe, U.; Schwager, C.; Schromm, A.B.; González Roldán, N.; Stein, K.; Heine, H.; Duda, K.A. Lipophilic allergens, different modes of allergen-lipid interaction and their impact on asthma and allergy. Front. Immunol. 2019, 10, 122. [Google Scholar] [CrossRef]
  30. Cohen, N.R.; Garg, S.; Brenner, M.B. Antigen presentation by CD1: Lipids, T cells, and NKT cells in microbial immunity. Adv. Immunol. 2009, 102, 1–94. [Google Scholar]
  31. Huang, S. Targeting innate-like T cells in tuberculosis. Front. Immunol. 2016, 7, 234371. [Google Scholar] [CrossRef]
  32. Cotton, R.N.; Shahine, A.; Rossjohn, J.; Moody, D.B. Lipids hide or step aside for CD1-autoreactive T cell receptors. Curr. Opin. Immunol. 2018, 52, 93–99. [Google Scholar] [CrossRef] [PubMed]
  33. De Libero, G.; Mori, L. Recognition of lipid antigens by T cells. Nat. Rev. Immunol. 2005, 5, 485–496. [Google Scholar] [CrossRef]
  34. Mori, L.; Lepore, M.; De Libero, G. The immunology of CD1-and MR1-restricted T cells. Annu. Rev. Immunol. 2016, 34, 479–510. [Google Scholar] [CrossRef]
  35. Leshem, Y.Y. Plant Membranes: A Biophysical Approach to Structure, Development and Senescence; Springer Science & Business Media: Berlin/Heidelberg, Germany, 2013. [Google Scholar]
  36. Salio, M.; Cerundolo, V. Regulation of lipid specific and vitamin specific non-MHC restricted T cells by antigen presenting cells and their therapeutic potentials. Front. Immunol. 2015, 6, 150929. [Google Scholar] [CrossRef] [PubMed]
  37. Porcelli, S.; Morita, C.T.; Brenner, M.B. CDlb restricts the response of human CD4− 8− T lymphocytes to a microbial antigen. Nature 1992, 360, 593–597. [Google Scholar] [CrossRef] [PubMed]
  38. Beckman, E.M.; Porcelli, S.A.; Morita, C.T.; Behar, S.M.; Furlong, S.T.; Brenner, M.B. Recognition of a lipid antigen by CD1-restricted αβ+ T cells. Nature 1994, 372, 691–694. [Google Scholar] [CrossRef]
  39. Zeng, Z.-H.; Castano, A.; Segelke, B.; Stura, E.; Peterson, P.; Wilson, I. Crystal structure of mouse CD1: An MHC-like fold with a large hydrophobic binding groove. Science 1997, 277, 339–345. [Google Scholar] [CrossRef]
  40. Ly, D.; Moody, D.B. The CD1 size problem: Lipid antigens, ligands, and scaffolds. Cell. Mol. Life Sci. 2014, 71, 3069–3079. [Google Scholar] [CrossRef]
  41. De Libero, G.; Mori, L. The T-cell response to lipid antigens of Mycobacterium tuberculosis. Front. Immunol. 2014, 5, 96915. [Google Scholar] [CrossRef]
  42. Salio, M.; Silk, J.D.; Yvonne Jones, E.; Cerundolo, V. Biology of CD1-and MR1-restricted T cells. Annu. Rev. Immunol. 2014, 32, 323–366. [Google Scholar] [CrossRef] [PubMed]
  43. Cox, D.; Fox, L.; Tian, R.; Bardet, W.; Skaley, M.; Mojsilovic, D.; Gumperz, J.; Hildebrand, W. Determination of cellular lipids bound to human CD1d molecules. PLoS ONE 2009, 4, e5325. [Google Scholar] [CrossRef]
  44. Salio, M.; Silk, J.D.; Cerundolo, V. Recent advances in processing and presentation of CD1 bound lipid antigens. Curr. Opin. Immunol. 2010, 22, 81–88. [Google Scholar] [CrossRef] [PubMed]
  45. Chancellor, A.; Gadola, S.D.; Mansour, S. The versatility of the CD 1 lipid antigen presentation pathway. Immunology 2018, 154, 196–203. [Google Scholar] [CrossRef] [PubMed]
  46. Adams, E.J. Lipid presentation by human CD1 molecules and the diverse T cell populations that respond to them. Curr. Opin. Immunol. 2014, 26, 1–6. [Google Scholar] [CrossRef] [PubMed]
  47. Horst, A.K.; Kumashie, K.G.; Neumann, K.; Diehl, L.; Tiegs, G. Antigen presentation, autoantibody production, and therapeutic targets in autoimmune liver disease. Cell. Mol. Immunol. 2021, 18, 92–111. [Google Scholar] [CrossRef] [PubMed]
  48. Cutillo, G.; Saariaho, A.-H.; Meri, S. Physiology of gangliosides and the role of antiganglioside antibodies in human diseases. Cell. Mol. Immunol. 2020, 17, 313–322. [Google Scholar] [CrossRef] [PubMed]
  49. Xiang, Y.; Zhang, M.; Jiang, D.; Su, Q.; Shi, J. The role of inflammation in autoimmune disease: A therapeutic target. Front. Immunol. 2023, 14, 1267091. [Google Scholar] [CrossRef]
  50. Kerstholt, M.; Netea, M.G.; Joosten, L.A. Borrelia burgdorferi hijacks cellular metabolism of immune cells: Consequences for host defense. Ticks Tick-Borne Dis. 2020, 11, 101386. [Google Scholar] [CrossRef] [PubMed]
  51. Shafiei, M.; Ghasemian, A.; Eslami, M.; Nojoomi, F.; Rajabi-Vardanjani, H. Risk factors and control strategies for silicotuberculosis as an occupational disease. New Microbes New Infect. 2019, 27, 75–77. [Google Scholar] [CrossRef]
  52. Bagchi, S.; Genardi, S.; Wang, C.R. Linking CD1-Restricted T Cells With Autoimmunity and Dyslipidemia: Lipid Levels Matter. Front. Immunol. 2018, 9, 1616. [Google Scholar] [CrossRef] [PubMed]
  53. Teyton, L. Role of lipid transfer proteins in loading CD1 antigen-presenting molecules. J. Lipid Res. 2018, 59, 1367–1373. [Google Scholar] [CrossRef] [PubMed]
  54. Kim, S.; Cho, S.; Kim, J.H. CD1-mediated immune responses in mucosal tissues: Molecular mechanisms underlying lipid antigen presentation system. Exp. Mol. Med. 2023, 55, 1858–1871. [Google Scholar] [CrossRef]
  55. Collmann, A. Assessing the Response of T Cells to “Mycobacterium Tuberculosis” Lipids; University of Basel: Basel, Switzerland, 2008. [Google Scholar]
  56. Blander, J.M. Regulation of the cell biology of antigen cross-presentation. Annu. Rev. Immunol. 2018, 36, 717–753. [Google Scholar] [CrossRef] [PubMed]
  57. Sugita, M.; Barral, D.; Brenner, M. Pathways of CD1 and lipid antigen delivery, trafficking, processing, loading, and presentation. In T Cell Activation by CD1 and Lipid Antigens; Springer: Berlin/Heidelberg, Germany, 2007; pp. 143–164. [Google Scholar]
  58. Vartabedian, V.F.; Savage, P.B.; Teyton, L. The processing and presentation of lipids and glycolipids to the immune system. Immunol. Rev. 2016, 272, 109–119. [Google Scholar] [CrossRef]
  59. Moody, D.B. The surprising diversity of lipid antigens for CD1-restricted T cells. Adv. Immunol. 2006, 89, 87–139. [Google Scholar]
  60. Schiefner, A.; Wilson, I.A. Presentation of lipid antigens by CD1 glycoproteins. Curr. Pharm. Des. 2009, 15, 3311–3317. [Google Scholar] [CrossRef]
  61. Siddiqui, S.; Visvabharathy, L.; Wang, C.R. Role of Group 1 CD1-Restricted T Cells in Infectious Disease. Front. Immunol. 2015, 6, 337. [Google Scholar] [CrossRef] [PubMed]
  62. Pereira, C.S.; Macedo, M.F. CD1-restricted T cells at the crossroad of innate and adaptive immunity. J. Immunol. Res. 2016, 2016, 2876275. [Google Scholar] [CrossRef] [PubMed]
  63. Brigl, M.; Brenner, M.B. CD1: Antigen presentation and T cell function. Annu. Rev. Immunol. 2004, 22, 817–890. [Google Scholar] [CrossRef]
  64. Rabe, S.Z.T.; Sahebari, M.; Mahmoudi, Z.; Hosseinzadeh, H.; Haghmorad, D.; Tabasi, N.; Rastin, M.; Khazaee, M.; Mahmoudi, M. Inhibitory effect of Crocus sativus L. ethanol extract on adjuvant-induced arthritis. Food Agr. Immunol. 2015, 26, 170–180. [Google Scholar] [CrossRef]
  65. Rawlings, D.J.; Schwartz, M.A.; Jackson, S.W.; Meyer-Bahlburg, A. Integration of B cell responses through Toll-like receptors and antigen receptors. Nat. Rev. Immunol. 2012, 12, 282–294. [Google Scholar] [CrossRef] [PubMed]
  66. Tolar, P.; Won Sohn, H.; Pierce, S.K. Viewing the antigen-induced initiation of B-cell activation in living cells. Immunol. Rev. 2008, 221, 64–76. [Google Scholar] [CrossRef] [PubMed]
  67. Cyster, J.G.; Allen, C.D. B cell responses: Cell interaction dynamics and decisions. Cell 2019, 177, 524–540. [Google Scholar] [CrossRef] [PubMed]
  68. Gupta, N.; DeFranco, A.L. Lipid rafts and B cell signaling. In Seminars in Cell & Developmental Biology; Elsevier: Amsterdam, The Netherlands, 2007. [Google Scholar]
  69. Ji, X.; Wu, L.; Marion, T.; Luo, Y. Lipid metabolism in regulation of B cell development and autoimmunity. Cytokine Growth Factor Rev. 2023, 73, 40–51. [Google Scholar] [CrossRef]
  70. Allan, L.L.; Stax, A.M.; Zheng, D.J.; Chung, B.K.; Kozak, F.K.; Tan, R.; van den Elzen, P. CD1d and CD1c expression in human B cells is regulated by activation and retinoic acid receptor signaling. J. Immunol. 2011, 186, 5261–5272. [Google Scholar] [CrossRef]
  71. Doyon-Laliberté, K.; Aranguren, M.; Poudrier, J.; Roger, M. Marginal zone B-cell populations and their regulatory potential in the context of HIV and other chronic inflammatory conditions. Int. J. Mol. Sci. 2022, 23, 3372. [Google Scholar] [CrossRef] [PubMed]
  72. Batista, F.D.; Harwood, N.E. The who, how and where of antigen presentation to B cells. Nat. Rev. Immunol. 2009, 9, 15–27. [Google Scholar] [CrossRef] [PubMed]
  73. Pone, E.J.; Zan, H.; Zhang, J.; Al-Qahtani, A.; Xu, Z.; Casali, P. Toll-like receptors and B-cell receptors synergize to induce immunoglobulin class-switch DNA recombination: Relevance to microbial antibody responses. Crit. Rev. Immunol. 2010, 30, 1–29. [Google Scholar] [CrossRef] [PubMed]
  74. Duffney, P.F.; Falsetta, M.L.; Rackow, A.R.; Thatcher, T.H.; Phipps, R.P.; Sime, P.J. Key roles for lipid mediators in the adaptive immune response. J. Clin. Investig. 2018, 128, 2724–2731. [Google Scholar] [CrossRef] [PubMed]
  75. Wei, Y.; Huang, C.-X.; Xiao, X.; Chen, D.-P.; Shan, H.; He, H.; Kuang, D.-M. B cell heterogeneity, plasticity, and functional diversity in cancer microenvironments. Oncogene 2021, 40, 4737–4745. [Google Scholar] [CrossRef]
  76. Kim, D.; Chung, H.; Lee, J.E.; Kim, J.; Hwang, J.; Chung, Y. Immunologic Aspects of Dyslipidemia: A Critical Regulator of Adaptive Immunity and Immune Disorders. J. Lipid Atheroscler. 2021, 10, 184–201. [Google Scholar] [CrossRef] [PubMed]
  77. Molendijk, J.; Robinson, H.; Djuric, Z.; Hill, M. Lipid mechanisms in hallmarks of cancer. Mol. Omics 2020, 16, 6–18. [Google Scholar] [CrossRef] [PubMed]
  78. Daniotti, J.L.; Lardone, R.D.; Vilcaes, A.A. Dysregulated expression of glycolipids in tumor cells: From negative modulator of anti-tumor immunity to promising targets for developing therapeutic agents. Front. Oncol. 2016, 5, 300. [Google Scholar] [CrossRef] [PubMed]
  79. Zheng, M.; Zhang, W.; Chen, X.; Guo, H.; Wu, H.; Xu, Y.; He, Q.; Ding, L.; Yang, B. The impact of lipids on the cancer-immunity cycle and strategies for modulating lipid metabolism to improve cancer immunotherapy. Acta Pharm. Sin. B 2023, 13, 1488–1497. [Google Scholar] [CrossRef] [PubMed]
  80. Jin, X.; Yang, G.-Y. Pathophysiological roles and applications of glycosphingolipids in the diagnosis and treatment of cancer diseases. Prog. Lipid Res. 2023, 91, 101241. [Google Scholar] [CrossRef] [PubMed]
  81. Hakomori, S. Sphingolipid-dependent protein kinases. Adv. Pharmacol. 1996, 36, 155–171. [Google Scholar] [CrossRef]
  82. Livingston, P.O. Approaches to augmenting the immunogenicity of melanoma gangliosides: From whole melanoma cells to ganglioside-KLH conjugate vaccines. Immunol. Rev. 1995, 145, 147–166. [Google Scholar] [CrossRef] [PubMed]
  83. Adams, E.J. Diverse antigen presentation by the Group 1 CD1 molecule, CD1c. Mol. Immunol. 2013, 55, 182–185. [Google Scholar] [CrossRef]
  84. Montamat-Sicotte, D.J.; Millington, K.A.; Willcox, C.R.; Hingley-Wilson, S.; Hackforth, S.; Innes, J.; Kon, O.M.; Lammas, D.A.; Minnikin, D.E.; Besra, G.S.; et al. A mycolic acid-specific CD1-restricted T cell population contributes to acute and memory immune responses in human tuberculosis infection. J. Clin. Invest. 2011, 121, 2493–2503. [Google Scholar] [CrossRef]
  85. Moody, D.B.; Ulrichs, T.; Muhlecker, W.; Young, D.C.; Gurcha, S.S.; Grant, E.; Rosat, J.P.; Brenner, M.B.; Costello, C.E.; Besra, G.S.; et al. CD1c-mediated T-cell recognition of isoprenoid glycolipids in Mycobacterium tuberculosis infection. Nature 2000, 404, 884–888. [Google Scholar] [CrossRef] [PubMed]
  86. Chancellor, A.; Tocheva, A.S.; Cave-Ayland, C.; Tezera, L.; White, A.; Al Dulayymi, J.R.; Bridgeman, J.S.; Tews, I.; Wilson, S.; Lissin, N.M.; et al. CD1b-restricted GEM T cell responses are modulated by Mycobacterium tuberculosis mycolic acid meromycolate chains. Proc. Natl. Acad. Sci. USA 2017, 114, E10956–E10964. [Google Scholar] [CrossRef]
  87. Van Rhijn, I.; Iwany, S.K.; Fodran, P.; Cheng, T.Y.; Gapin, L.; Minnaard, A.J.; Moody, D.B. CD1b-mycolic acid tetramers demonstrate T-cell fine specificity for mycobacterial lipid tails. Eur. J. Immunol. 2017, 47, 1525–1534. [Google Scholar] [CrossRef] [PubMed]
  88. De Libero, G.; Singhal, A.; Lepore, M.; Mori, L. Nonclassical T cells and their antigens in tuberculosis. Cold Spring Harb. Perspect. Med. 2014, 4, a018473. [Google Scholar] [CrossRef] [PubMed]
  89. Wucherpfennig, K.W. Mechanisms for the induction of autoimmunity by infectious agents. J. Clin. Invest. 2001, 108, 1097–1104. [Google Scholar] [CrossRef]
  90. Hanada, K. Sphingolipids in infectious diseases. Jpn J. Infect. Dis. 2005, 58, 131–148. [Google Scholar] [CrossRef]
  91. Guevara, M.L.; Persano, S.; Persano, F. Lipid-based vectors for therapeutic mRNA-based anti-cancer vaccines. Curr. Pharm. Des. 2019, 25, 1443–1454. [Google Scholar] [CrossRef]
  92. Zhang, C.; Ma, Y.; Zhang, J.; Kuo, J.C.-T.; Zhang, Z.; Xie, H.; Zhu, J.; Liu, T. Modification of lipid-based nanoparticles: An efficient delivery system for nucleic acid-based immunotherapy. Molecules 2022, 27, 1943. [Google Scholar] [CrossRef]
  93. van den Berg, A.I.; Yun, C.-O.; Schiffelers, R.M.; Hennink, W.E. Polymeric delivery systems for nucleic acid therapeutics: Approaching the clinic. J. Control. Release 2021, 331, 121–141. [Google Scholar] [CrossRef]
  94. Ickenstein, L.M.; Garidel, P. Lipid-based nanoparticle formulations for small molecules and RNA drugs. Expert Opin. Drug Deliv. 2019, 16, 1205–1226. [Google Scholar] [CrossRef] [PubMed]
  95. Bedard, M.; Salio, M.; Cerundolo, V. Harnessing the power of invariant natural killer T cells in cancer immunotherapy. Front. Immunol. 2017, 8, 308005. [Google Scholar] [CrossRef]
  96. Nordly, P.; Madsen, H.B.; Nielsen, H.M.; Foged, C. Status and future prospects of lipid-based particulate delivery systems as vaccine adjuvants and their combination with immunostimulators. Expert Opin. Drug Deliv. 2009, 6, 657–672. [Google Scholar] [CrossRef] [PubMed]
  97. Carreño, L.J.; Saavedra-Ávila, N.A.; Porcelli, S.A. Synthetic glycolipid activators of natural killer T cells as immunotherapeutic agents. Clin. Transl. Immunol. 2016, 5, e69. [Google Scholar] [CrossRef] [PubMed]
  98. Kumar, B.S. Recent advancement and applications of mass spectrometry imaging. ChemRxiv 2024. [Google Scholar] [CrossRef]
  99. Tan, Y. Structural and Functional Characterization of the ESX-3 Secretion System in Mycobacteria. Ph.D. Thesis, University of British Columbia, Vancouver, BC, Canada, 2023. [Google Scholar]
  100. Layre, E.; Sweet, L.; Hong, S.; Madigan, C.A.; Desjardins, D.; Young, D.C.; Cheng, T.-Y.; Annand, J.W.; Kim, K.; Shamputa, I.C. A comparative lipidomics platform for chemotaxonomic analysis of Mycobacterium tuberculosis. Chem. Biol. 2011, 18, 1537–1549. [Google Scholar] [CrossRef]
  101. Huang, S.; Shahine, A.; Cheng, T.-Y.; Chen, Y.-L.; Ng, S.W.; Balaji, G.R.; Farquhar, R.; Gras, S.; Hardman, C.S.; Altman, J.D. CD1 lipidomes reveal lipid-binding motifs and size-based antigen-display mechanisms. Cell 2023, 186, 4583–4596.e4513. [Google Scholar] [CrossRef]
  102. Duong, L.K.; Corbali, H.I.; Riad, T.S.; Ganjoo, S.; Nanez, S.; Voss, T.; Barsoumian, H.B.; Welsh, J.; Cortez, M.A. Lipid metabolism in tumor immunology and immunotherapy. Front. Oncol. 2023, 13, 1187279. [Google Scholar] [CrossRef] [PubMed]
  103. Ahluwalia, K.; Ebright, B.; Chow, K.; Dave, P.; Mead, A.; Poblete, R.; Louie, S.G.; Asante, I. Lipidomics in understanding pathophysiology and pharmacologic effects in inflammatory diseases: Considerations for drug development. Metabolites 2022, 12, 333. [Google Scholar] [CrossRef]
  104. Patel, V.; Shah, M. Artificial intelligence and machine learning in drug discovery and development. Intell. Med. 2022, 2, 134–140. [Google Scholar] [CrossRef]
  105. Iwabuchi, K.; Van Kaer, L. Role of CD1-and MR1-restricted T cells in immunity and disease. Front. Immunol. 2019, 10, 479496. [Google Scholar] [CrossRef] [PubMed]
  106. Leadbetter, E.A.; Brigl, M.; Illarionov, P.; Cohen, N.; Luteran, M.C.; Pillai, S.; Besra, G.S.; Brenner, M.B. NK T cells provide lipid antigen-specific cognate help for B cells. Proc. Natl. Acad. Sci. USA 2008, 105, 8339–8344. [Google Scholar] [CrossRef] [PubMed]
  107. Moody, D.B.; Porcelli, S.A. Intracellular pathways of CD1 antigen presentation. Nat. Rev. Immunol. 2003, 3, 11–22. [Google Scholar] [CrossRef] [PubMed]
  108. Silk, J.D.; Salio, M.; Brown, J.; Jones, E.Y.; Cerundolo, V. Structural and functional aspects of lipid binding by CD1 molecules. Annu. Rev. Cell Dev. Biol. 2008, 24, 369–395. [Google Scholar] [CrossRef] [PubMed]
  109. Gullick, J. Investigating Lipid-Responsive T Cells in Tuberculosis; Paving the Way for New Lipid-Based Vaccines. Ph.D. Thesis, University of Southampton, Southampton, UK, 2021. [Google Scholar]
  110. Bediako, T.Y. The Role of Non-Classical MHC Class I in the Immune Response to Intracellular Bacterial Infection. Ph.D. Thesis, Northwestern University, Evanston, IL, USA, 2012. [Google Scholar]
  111. Weiner, J., 3rd; Kaufmann, S.H. Recent advances towards tuberculosis control: Vaccines and biomarkers. J. Intern. Med. 2014, 275, 467–480. [Google Scholar] [CrossRef]
  112. Paterson, N.M.; Al-Zubieri, H.; Barber, M.F. Diversification of CD1 molecules shapes lipid antigen selectivity. Mol. Biol. Evol. 2021, 38, 2273–2284. [Google Scholar] [CrossRef]
  113. Franco, A.R.; Peri, F. Developing new anti-tuberculosis vaccines: Focus on adjuvants. Cells 2021, 10, 78. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Adaptive immune system responses occur in the mesenteric lymph node. The antigen is presented to T lymphocytes by APCs (such as DCs or B cells), whereby they become activated and differentiate into several T cell types (CTLs and T helper cells). B cells differentiate into plasma cells and memory B cells that produce faster and stronger responses. The T cell’s production of chemokines and cytokines and its effects on neutrophils and macrophages are not described. The figure was designed using Biorender.com.
Figure 1. Adaptive immune system responses occur in the mesenteric lymph node. The antigen is presented to T lymphocytes by APCs (such as DCs or B cells), whereby they become activated and differentiate into several T cell types (CTLs and T helper cells). B cells differentiate into plasma cells and memory B cells that produce faster and stronger responses. The T cell’s production of chemokines and cytokines and its effects on neutrophils and macrophages are not described. The figure was designed using Biorender.com.
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Figure 2. Tumor antigens activate CTLs through autophagy/MHCI for cytotoxicity and T helper cells through cross-presentation/MHCII for antibody production, contributing to tumor eradication through immune responses involving both cytotoxic and antibody-mediated mechanisms. The figure was designed using Biorender.com.
Figure 2. Tumor antigens activate CTLs through autophagy/MHCI for cytotoxicity and T helper cells through cross-presentation/MHCII for antibody production, contributing to tumor eradication through immune responses involving both cytotoxic and antibody-mediated mechanisms. The figure was designed using Biorender.com.
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Figure 3. After the body’s encounter with the pathogen and recognition of bacterial lipid antigens by TLRs on the APC, lipid antigens are picked up and processed by APCs and presented on CD1 molecules to T cells and iNKT. Naïve CD4+ T cells differentiate into Th1 cells (which secrete TNF-α and IFN-γ), Th2 cells (which secrete IL-4, IL-5, and IL-13), Th17 cells (which secrete IL-17 and IL-22), Th22 cells (which secrete IL-22), and Treg cells (which secrete IL-10 and TGF-β). The figure was designed using Biorender.com.
Figure 3. After the body’s encounter with the pathogen and recognition of bacterial lipid antigens by TLRs on the APC, lipid antigens are picked up and processed by APCs and presented on CD1 molecules to T cells and iNKT. Naïve CD4+ T cells differentiate into Th1 cells (which secrete TNF-α and IFN-γ), Th2 cells (which secrete IL-4, IL-5, and IL-13), Th17 cells (which secrete IL-17 and IL-22), Th22 cells (which secrete IL-22), and Treg cells (which secrete IL-10 and TGF-β). The figure was designed using Biorender.com.
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Eskandari, T.; Eivazzadeh, Y.; Khaleghinia, F.; Kashi, F.; Oksenych, V.; Haghmorad, D. Lipid Antigens: Revealing the Hidden Players in Adaptive Immune Responses. Biomolecules 2025, 15, 84. https://doi.org/10.3390/biom15010084

AMA Style

Eskandari T, Eivazzadeh Y, Khaleghinia F, Kashi F, Oksenych V, Haghmorad D. Lipid Antigens: Revealing the Hidden Players in Adaptive Immune Responses. Biomolecules. 2025; 15(1):84. https://doi.org/10.3390/biom15010084

Chicago/Turabian Style

Eskandari, Tamana, Yasamin Eivazzadeh, Fatemeh Khaleghinia, Fatemeh Kashi, Valentyn Oksenych, and Dariush Haghmorad. 2025. "Lipid Antigens: Revealing the Hidden Players in Adaptive Immune Responses" Biomolecules 15, no. 1: 84. https://doi.org/10.3390/biom15010084

APA Style

Eskandari, T., Eivazzadeh, Y., Khaleghinia, F., Kashi, F., Oksenych, V., & Haghmorad, D. (2025). Lipid Antigens: Revealing the Hidden Players in Adaptive Immune Responses. Biomolecules, 15(1), 84. https://doi.org/10.3390/biom15010084

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