Your new experience awaits. Try the new design now and help us make it even better

REVIEW article

Front. Neurosci., 16 July 2025

Sec. Gut-Brain Axis

Volume 19 - 2025 | https://doi.org/10.3389/fnins.2025.1622349

This article is part of the Research TopicImmune-gut-brain axis - A Key Player in Overall Human PathologiesView all 6 articles

Research progress on immunometabolism and gut microbiota in cryptococcal meningitis: mechanisms and therapeutic implications

Sha Wen,,,&#x;Sha Wen1,2,3,4Mu Liu,,&#x;Mu Liu1,3,4Chengyu Pan,,Chengyu Pan1,3,4Linhai Zhang,,Linhai Zhang1,3,4Rong Yan,,Rong Yan1,3,4Zucai Xu,,
Zucai Xu1,3,4*
  • 1Department of Neurology, Affiliated Hospital of Zunyi Medical University, Zunyi, China
  • 2Zhejiang Provincial People's Hospital Bijie Hospital, Bijie, China
  • 3Collaborative Innovation Center of Tissue Damage Repair and Regeneration Medicine, Zunyi, China
  • 4Key Laboratory of Brain Function and Brain Disease Prevention and Treatment of Guizhou Province, Zunyi, China

Cryptococcal meningitis (CM) is a fatal central nervous system infection caused by Cryptococcus neoformans breaching the blood–brain barrier (BBB), carrying a mortality rate approaching 100% in untreated individuals, while even survivors following treatment often experience neurological complications including optic nerve atrophy, memory impairment, hydrocephalus, and motor dysfunction. Current research has yet to fully elucidate the complex pathological mechanisms of CM, particularly leaving a significant gap in the systemic analysis within the dynamic interaction network of immunity, metabolism, and the gut microbiota. This article systematically integrates the interplay of immune responses, metabolic reprogramming, and the gut microbiome to reveal the pathogenesis of CM across multiple dimensions: in immune regulation, the phagocytic-inflammatory equilibrium in macrophages and CD4 + T cells defends against pathogen invasion, but hyperactivated immune responses may damage the BBB and exacerbate neural injury; metabolically, host iron overload induces ferroptosis, disrupting the BBB via lipid peroxidation, while inositol metabolism provides substrates for cryptococcal capsular synthesis, enhancing its virulence and promoting CNS invasion; the gut microbiota, meanwhile, modulates immune homeostasis via the “gut-brain axis,” with its metabolites (e.g., short-chain fatty acids) enhancing BBB integrity and suppressing neuroinflammation through immunomodulation. We propose a combined therapeutic strategy of “immunomodulators + metabolic inhibitors + microbiota intervention,” moving beyond traditional single-factor research paradigms to establish a multi-omics integrated framework for the precise treatment of CM—spanning molecular mechanisms to clinical translation—and propelling the field of neuroinfectious diseases towards a host-pathogen-microenvironment systemic regulation paradigm.

1 Introduction

Cryptococcus is a basidiomycete genus comprising over 30 known species. In nature, two primary species, C. neoformans and Cryptococcus gattii, are pathogenic to humans (Elsegeiny et al., 2018; Spadari et al., 2018). Cryptococcus gattii primarily infects immunocompetent hosts (Chen et al., 2014), while C. neoformans mainly affects individuals with HIV infection or other immunocompromised conditions (Baddley et al., 2021; Chen et al., 2023). As a globally distributed opportunistic fungal pathogen, C. neoformans ranks high on the World Health Organization’s Fungal Priority Pathogens List. It primarily enters the human body through the respiratory tract, initially colonizing the lungs (Zhao et al., 2023; Saidykhan et al., 2022), and then disseminating from the lungs in immunocompromised hosts (Alanio, 2020), leading to disseminated disease. C. neoformans is the leading cause of fatal cryptococcal meningoencephalitis (Aaron et al., 2020; Shourian and Qureshi, 2019; Vidal et al., 2016). CM occurs when C. neoformans breaches the BBB and affects the CNS (Zaragoza, 2019), achieved through transcellular traversal, paracellular pathways, and the “Trojan horse” mechanism (Zhou et al., 2024) (Figure 1). CM has been reported in organ transplant recipients, patients with autoimmune diseases on long-term immunosuppressive therapy, individuals with unexplained immunodeficiency, and even healthy individuals (Pappas, 2013; La Hoz and Pappas, 2013; Beardsley et al., 2019). CM is the most common cause of adult meningitis globally, with approximately 250,000 cases annually, resulting in 181,000 deaths. Without treatment, the mortality rate reaches 100% (Zhou et al., 2024). C. neoformans most commonly affects HIV-infected individuals, causing HIV-associated CM (HIV-CM) (Tugume et al., 2023), which is the leading cause of death among HIV patients and the second leading cause of HIV-related deaths globally (Jarvis et al., 2014; Jarvis et al., 2022). The WHO reports that C. neoformans accounts for about 19% of HIV-related deaths, with CM contributing to 10–15% of global AIDS-related mortality (Francis et al., 2024). In HIV-negative individuals, although the incidence of CM is relatively low, the mortality rate is equally high as in HIV-CM (Williamson et al., 2017). CM poses a severe global mortality risk, particularly in resource-limited developing countries. Despite significant research efforts, no effective preventive vaccine has been developed (Ma et al., 2023). Mortality in patients receiving existing combination antifungal therapy remains as high as 24% at 10 weeks (Iyer et al., 2021). Even the latest research showing that a single high-dose regimen of liposomal amphotericin B combined with flucytosine and fluconazole, while superior to the current standard, can only reduce mortality to below 30% (Jarvis et al., 2022). Studies also indicate that antiretroviral therapy (ART) can restore protective immunity by reducing viral load and reconstituting CD4 + T cells, expanding treatment accessibility; however, associated mortality remains persistently high (Eschke et al., 2015). Furthermore, survivors often experience persistent neurological sequelae such as memory loss, visual deficits, hearing and speech impairments, and motor deficits (Neal et al., 2017), highlighting the need to focus on both acute-phase treatment and long-term neurological function preservation.

Figure 1
Diagram illustrating the mechanisms of Cryptococcus neoformans crossing the blood-brain barrier. Shows paracellular transport with MMPs disrupting tight junctions, Trojan horse mechanism involving phagocytes, and transcellular migration. Includes capillary, endothelial cells, astrocytes, pericytes, ZO-1, Claudin-5, RBC, and brain parenchyma. Arrows indicate promotion or inhibition of these processes.

Figure 1. This figure illustrates three mechanisms by which Cryptococcus neoformans crosses the blood–brain barrier (BBB): through paracellular transport, where C. neoformans secretes matrix metalloproteinases (MMPs) to degrade tight junction proteins zonula occludens-1 (ZO-1) and Claudin-5, disrupting endothelial cell junctions to enter the brain parenchyma; in the Trojan horse mechanism, C. neoformans is phagocytosed by phagocytes, and during migration, the phagocyte’s response to endothelial chemokines such as fractalkine (CX3CL1) and colony stimulating factor 1 (CSF-1) is suppressed, slowing cellular migration and facilitating fungal transit across the BBB; transcellular migration involves C. neoformans directly traversing the endothelial cell to enter the brain.

In recent years, the research perspective on CM is undergoing a significant paradigm shift. As a lethal central nervous system infection, its treatment faces challenges such as antifungal drug resistance, limited BBB penetrability, and immune reconstitution inflammatory syndrome (IRIS) (Perfect et al., 2010). The study of its pathological mechanisms requires the integration of prevention, early biomarker identification, and precision diagnosis and treatment strategies. Within the pathological process, the immune system plays a defensive role by regulating blood–brain barrier integrity. The newly discovered “gut-brain axis” mechanism suggests that the gut microbiota can influence CM progression by modulating immune homeostasis. Current research is shifting from a sole focus on pathogen eradication towards analyzing the host–microbe interaction network, with particular emphasis on the heterogeneous mechanisms underlying HIV-CM (characterized by CD4 + T cell depletion) versus CM in immunocompetent hosts (dominated by autoimmune abnormalities). In this review, we focus on analyzing the molecular interaction network of the “immune-metabolism-microbiota axis” and explore multimodal therapeutic strategies combining antifungal treatment with immune modulation and microbiota intervention. This review aims to provide a theoretical basis for targeted treatment strategies addressing key pathological links during CM infection, while also offering novel interventions to improve neurological functional outcomes in survivors.

2 Host-Cryptococcus neoformans immune battle: synergistic defense and immune evasion mechanisms of innate and adaptive immunity

2.1 Innate immunity: frontline defense mechanisms

2.1.1 Intracellular evasion mechanisms of cryptococcus

The pathological progression of CM is closely related to the efficacy of the host’s innate immune response, which establishes a critical barrier through multi-layered defense mechanisms in the early stages of infection. C. neoformans primarily colonizes the lungs via the respiratory tract and can reactivate and disseminate to the CNS in immunocompromised states (e.g., HIV infection) (Zhou et al., 2024; Yu et al., 2021). During this process, the host initiates a precisely regulated innate immune network involving multiple immune cells and molecular pathways (Table 1). The innate immune system, as the first line of defense against C. neoformans infection, employs various immune cells, including macrophages, monocytes, microglia, neutrophils, dendritic cells (DCs), and astrocytes (Campuzano and Wormley, 2018; Mukaremera and Nielsen, 2017). Monocytes/macrophages, neutrophils, and DCs recognize C. neoformans pathogen-associated molecular patterns (PAMPs) through pattern recognition receptors (PRRs) such as Toll-like receptor 2 (TLR2) and C-type lectin receptors (CLRs), initiating phagocytosis and inflammatory cascades (Fu and Drummond, 2020) (Table 1).

Table 1
www.frontiersin.org

Table 1. Immune cell functions and intercellular interaction mechanisms in cryptococcal meningitis.

Cryptococcus neoformans employs sophisticated intracellular survival strategies and immune evasion mechanisms after being phagocytosed by monocytes or macrophages. Its thick polysaccharide capsule serves as the first protective barrier, blocking phagosome-lysosome fusion to prevent exposure to acidic hydrolases. Simultaneously, melanin produced by the fungus exerts potent antioxidant effects, effectively neutralizing microbicidal substances such as reactive oxygen species and nitric oxide released by macrophages, thereby maintaining its intracellular integrity (Feldmesser et al., 2001; de Castro et al., 2023; Johnston and May, 2013). More critically, Cryptococcus secretes specific effector molecules to modulate host cell polarization, promoting macrophage transformation into non-protective M2 phenotypes. This suppresses their microbicidal functions while enhancing tissue repair and immunosuppressive capacity (Davis et al., 2013; Subramani et al., 2020) This ‘Trojan horse’ strategy allows Cryptococcus not only to survive and proliferate safely within macrophages but also to exploit the migratory properties and tissue-penetrating ability of host cells. Carried by infected cells, it traverses physiological barriers. Through these coordinated molecular mechanisms, Cryptococcus invasively breaches the anatomical defense of the BBB, reaches the brain parenchyma to establish colonization, and triggers neuroinflammation mediated by neuronal degeneration and glial cell activation.

2.1.2 Regulation of blood–brain barrier function by glial cells and their dual role in cryptococcal meningitis

Astrocytes and microglia play supportive and regulatory roles in maintaining the structure and function of the BBB: Astrocytes secrete vascular endothelial growth factor and Wnt growth factors to help preserve BBB integrity; Microglia, as resident immune cells of the central nervous system, can directly phagocytose or kill pathogenic microorganisms that enter the brain parenchyma (Haruwaka et al., 2019; Guérit et al., 2021; Proia et al., 2008). Specifically, during CM pathogenesis, microglia dynamically switch between M1/M2 polarization states: M1 microglia directly kill C. neoformans by secreting pro-inflammatory cytokines such as TNF-α and IL-1β, while M2 microglia maintain tissue homeostasis through secretion of IL-10 and TGF-β (Orihuela et al., 2016; Nielson and Davis, 2023). Calcium (Ca2+) signaling between astrocytes constitutes a key mechanism regulating BBB permeability. Through gap junctions forming functional networks, Ca2+ fluctuations rapidly propagate between cells, coordinating the expression and distribution of BBB tight junction proteins (De Bock et al., 2016; Paemeleire, 2002). During C. neoformans infection, astrocytes are activated and produce nitric oxide, which not only exerts direct anti-cryptococcal effects but also modulates vasoconstriction and BBB permeability (Lee et al., 1994). However, excessive activation of the inflammatory response often further damages the BBB, leading to increased infiltration of immune cells and release of neurotoxic inflammatory mediators. This causes brain injury and exacerbates the pathological progression of CM (Woo and Martinez, 2021; Huang et al., 2012). Activated immune cells and the excessive secretion of cytokines (e.g., IFN-γ, TNF-α) may also damage BBB tight junction proteins, increasing its permeability (Mukaremera and Nielsen, 2017; Al-Huthaifi et al., 2024). Although immune cells can resist C. neoformans infection, excessive inflammatory responses may disrupt BBB function. Therefore, in CM treatment and prognosis, besides considering antifungal drugs to eliminate the pathogen, it is essential to regulate immune cell function and inflammatory factor balance to prevent BBB damage and neurological dysfunction (Figure 2).

Figure 2
Illustration showing the process of Cryptococcus neoformans crossing the blood-brain barrier, disrupting inositol metabolism, leading to ferroptosis via iron deposition, lipid peroxidation, and ROS activation. Pro-inflammatory cytokines, TNF-alpha, and IL-1 beta cause brain injury, while tamoxifen activation, TGF-beta, and IL-10 help maintain tissue homeostasis. A section highlights 2,4-dinitrophenol's role in blocking inositol uptake, inhibiting migration. A legend identifies microglia types, astrocytes, Cryptococcus neoformans, inositol metabolism, and transporters.

Figure 2. This figure illustrates the molecular mechanisms of inositol metabolism, ferroptosis, and neuroinflammation in Cryptococcus neoformans infection: C. neoformans enhances its virulence through inositol metabolism, while 2,4-Dinitrophenol, a specific inhibitor of the inositol transporter, blocks fungal inositol uptake and suppresses its migratory activity. Iron deposition induces ferroptosis, characterized by inactivation of glutathione peroxidase 4 (GPX4), accumulation of lipid peroxidation, and reactive oxygen species (ROS) production, which ultimately promotes pro-inflammatory cytokine secretion by activating the NF-κB signaling pathway, thereby disrupting blood–brain barrier (BBB) integrity. Microglial polarization occurs: M1-type microglia release pro-inflammatory factors such as TNF-α and IL-1β, causing tissue damage, while M2-type microglia secrete TGF-β and IL-10 to maintain tissue homeostasis. Tamoxifen activates astrocytes to produce nitric oxide, exerting anti-cryptococcal effects.

2.2 Adaptive immune defense mechanisms and early intervention

The host’s anti-C. neoformans immune defense system forms a synergistic network through PRR-mediated innate immunity and antigen-specific adaptive immunity. DCs act as immune hubs, not only clearing pathogens through phagolysosome maturation but also activating T lymphocyte clonal expansion via MHC-II-dependent antigen presentation, completing the spatiotemporal transition of immune responses (Coelho, 2024; Pacifici et al., 2023; Pishesha et al., 2022). In adaptive immunity, CD4 + T lymphocytes play a central regulatory role by polarizing into Th1-type immune phenotypes, establishing antifungal immune surveillance and pathogen clearance. Adaptive immunity achieves three functions through the synergistic interaction of antigen-presenting cells (APCs) and lymphocytes: antigen presentation triggering specific activation of T and B lymphocytes, CD4 + and CD8 + T cell-mediated cellular immune responses promoting early fungal clearance, memory cell formation providing long-term protection, and dynamic balance between defense responses and self-tolerance through immune regulatory networks (Bonilla and Oettgen, 2010). Triggering adaptive immunity requires the uptake, processing, and antigen presentation by immune cells such as macrophages, DCs, and monocytes (Mukaremera and Nielsen, 2017). CNS immune responses are regulated by dual mechanisms: on one hand, resident immune cells (microglia, astrocytes) and peripheral infiltrating cells (monocytes, T/B lymphocytes) form a dynamic regulatory network, collectively regulating BBB permeability; on the other hand, the BBB strictly maintains CNS immune homeostasis by limiting cell migration and regulating molecular transport (Fu and Drummond, 2020; Mohamed et al., 2022; Hazra et al., 2019). APCs (e.g., DCs and macrophages) present processed C. neoformans antigens to T cells via MHC-II molecules (Mohamed et al., 2022) Studies show that CD4 + T cell-derived IFN-γ significantly enhances macrophage bactericidal function by activating the STAT1 signaling pathway (Leopold Wager et al., 2018). Batf3-dependent classical type 1 DCs (cDC1) play a central role in generating IFN-γ + CD4 + T cells, increasing tissue-resident memory T cell (TRM) numbers by 2–3 times, thereby enhancing antifungal immune defense (Coelho, 2024). Notably, the host has established a multi-layered immune response regulatory network. IFN-γ, as a core mediator of Th1-type immune responses, plays a key role in breaking pathogen immune evasion. The monocyte–macrophage system and neutrophils rapidly secrete IFN-γ through STAT1-dependent signaling pathways. This transcription factor binds to the IFN-γ receptor, activating downstream JAK–STAT signaling cascades and promoting antimicrobial gene expression. This STAT1-mediated early pro-inflammatory response has dual effects: it enhances immune surveillance through mechanisms such as antigen presentation and oxidative burst, but excessive production of inflammatory mediators like TNF-α may increase BBB permeability (Wang et al., 2024).

2.3 Cryptococcus neoformans immune evasion and host countermeasures

In CM’s immune defense mechanisms, C. neoformans has evolved complex immune evasion strategies to counteract host innate immunity. C. neoformans virulence factors primarily include the polysaccharide capsule, melanin, cell wall integrity, thermotolerance, and secreted enzymes (Iyer et al., 2021). Among these, the polysaccharide capsule and melanin are the two most critical virulence factors, aiding C. neoformans survival and growth within the human host (Baker et al., 2024). The polysaccharide capsule modulates host immune responses and enhances pathogenicity, playing a key role in infection. The capsule’s structure, size, and density dynamically change, forming an effective immune evasion mechanism that helps the pathogen evade host immune recognition and clearance (Zaragoza, 2019; Dang et al., 2022; O'Meara and Alspaugh, 2012). Melanin acts as an antioxidant and reactive oxygen species (ROS) scavenger, providing fungal protection against oxidative stress and host defense mechanisms (Cordero et al., 2020; Lee et al., 2019). C. neoformans employs structural defense factors (capsule polysaccharides and melanin) to construct physical barriers and resist oxidative stress, counteracting alveolar macrophage phagocytosis. This immune evasion strategy is a key pathogenic mechanism for lung colonization (Lee et al., 2020).

Cryptococcus neoformans can increase phagolysosome membrane permeability through phospholipase B1 activity, disrupting lysosomal pH homeostasis and significantly impairing phagocytic bactericidal function (Campuzano and Wormley, 2018; Wang et al., 2024). This unique “immune sanctuary” effect not only promotes pathogen survival but also evades immune surveillance by interfering with lysosome fusion and regulating autophagy pathways, allowing C. neoformans to survive and disseminate within the host, creating a microenvironment for latent infection (Mohamed et al., 2022; Wang et al., 2022).

2.4 Clinical significance of immune biomarkers in CM

As research progresses, specific immune biomarkers and their dynamic changes play an important role in assessing CM risk and guiding early intervention (Rajasingham et al., 2017). Among various immune biomarkers, CD4 + T cell count is the most classic and practical predictive indicator. When CD4 + T cell counts drop below 100/μL, the risk of CM significantly increases. Therefore, timely monitoring of this indicator and implementing antifungal prophylaxis have become consensus in global clinical guidelines (Pérez-Jacoiste Asín et al., 2021). The combined application of cryptococcal antigen (CrAg) detection and immune biomarkers holds significant clinical value. Although CrAg positivity does not necessarily progress to meningitis, combining it with CD4 + T cell counts and cytokine levels can more accurately identify high-risk populations (Li et al., 2020; Borges et al., 2019; Hailu et al., 2019; Rajasingham et al., 2022). Beyond total counts, functional differences among CD4 + T cell subsets are also noteworthy. Th1, Th2, and Th17 subsets play distinct roles in antifungal immunity and inflammation regulation. Specifically, Th1-type cytokines (e.g., IFN-γ) activate macrophages to promote C. neoformans clearance, while Th2-dominated immune responses may indicate excessive inflammation risks (Pawlak et al., 2020; Firacative et al., 2018; Shourian et al., 2017; Balasko and Keynan, 2019; Jarvis et al., 2015). Recent studies suggest that CD8 + T cell interactions with the monocyte–macrophage system are also crucial for infection defense, with activated macrophage phenotypic changes reflecting the host’s innate immune status (Subramani et al., 2020; Meya et al., 2015). In the cytokine network, IFN-γ, IL-6, and TNF-α not only participate in infection control but also correlate with disease severity. Detecting cytokine levels in blood or cerebrospinal fluid (CSF) can predict disease progression trends early (Okafor et al., 2024; Mora et al., 2015; Xu L. et al., 2021). As research on immune biomarkers deepens, their application in CM early warning and prevention will become more precise, offering new strategies to reduce disease-related mortality.

2.5 Immunological perspectives on CM prevention and treatment

2.5.1 Immunomodulatory therapy with monoclonal antibodies and cytokines

CM is a severe CNS infection, and immunomodulatory therapy offers new insights and strategies. In recent years, significant progress has been made in exploring CM immunotherapies, including monoclonal antibodies, cytokines, immunomodulators, and vaccines. Monoclonal antibodies and cytokines have shown unique potential in CM treatment. Monoclonal antibodies targeting specific antigens can enhance the immune system’s ability to recognize and clear C. neoformans. For example, monoclonal antibodies against C. neoformans capsule polysaccharides can neutralize its pathogenicity and promote phagocyte uptake (Larsen et al., 2005). Cytokines can modulate immune cell function, restoring immune balance. IFN-γ, for instance, enhances macrophage anti-cryptococcal activity, improves fungal clearance in CSF, promotes protective immune responses, and improves survival in HIV-CM patients (Zhang et al., 2022; Tao et al., 2022). Some immunomodulators can also enhance immune responses while reducing inflammatory tissue damage. A prospective study on the immunomodulator lenalidomide showed it significantly reduced serum TNF-α and IL-6 levels, improving intracranial inflammation (Wan et al., 2023). The efficacy of immunomodulatory therapy is closely related to the patient’s immune status, with patients having higher baseline IFN-γ levels often having better prognoses (Jarvis et al., 2013). Combining this therapy with traditional antifungal drugs may improve outcomes.

2.5.2 Development strategies and immune mechanisms of cryptococcal vaccines

Vaccine development for CM is a strategic direction in immunotherapy, aiming to synergistically activate host innate and adaptive immune responses to establish long-term defense against C. neoformans. Studies have shown that candidate vaccines based on key antigen components such as glucuronoxylomannan and sterylglucoside exhibit dual immune activation properties in animal models: they activate innate immune responses through DC PRRs (e.g., TLR4/MyD88 signaling) and induce Th1-type cellular immunity and memory B cell differentiation through HLA-II molecule presentation, achieving both infection prevention and recurrence control (Colombo et al., 2019). Further research found that a heat-killed prm1 deletion strain vaccine activates alveolar macrophage phagocytosis and promotes Th1/Th17 cell polarization, significantly enhancing CNS immune surveillance, reducing brain fungal load, and extending protection (Li C. et al., 2023). This vaccine design not only avoids the proliferation risks of live vaccines but also demonstrates excellent biosafety, offering an innovative strategy for precise CM immunomodulation with long-term protection and clinical safety.

2.5.3 Astrocyte-based therapeutic targets for neuroprotection

Significant progress has been made in CM immunotherapy target research, such as neuroprotective strategies based on astrocyte function, which have become an important research direction in CM prevention and treatment. These strategies show potential therapeutic value by regulating BBB integrity and inhibiting neuroinflammation (Woo and Martinez, 2021). Studies have explored tamoxifen’s ability to induce astrocyte-specific activation, exerting antifungal activity. Tamoxifen has also been shown to induce astrocyte-specific activation, exerting antifungal effects (Wang et al., 2023).

3 Metabolic and immune interactions in Cryptococcus neoformans infection pathogenesis

3.1 Inositol metabolism-mediated capsule virulence synergistically promotes CM

Inositol metabolism is crucial for fungal virulence, primarily due to its impact on C. neoformans polysaccharide capsule formation (Wang et al., 2021). It interferes with immune recognition, protects newly formed C. neoformans from macrophage phagocytosis, impairs monocyte function, and hinders effective immune cell targeting (Fu and Drummond, 2020; Jang et al., 2022). However, inositol can also induce capsule enlargement and serves as the sole carbon source for C. neoformans, playing a key role in fungal development, mating, and virulence. Inositol catabolism releases inositol, providing energy for C. neoformans and necessary substrates for polysaccharide capsule formation, thereby enhancing fungal virulence (Wang et al., 2021; Liao et al., 2018). Elevated intracerebral inositol levels stimulate blood–brain barrier endothelial cells to increase hyaluronic acid (HA) production (Liu et al., 2013), HA acts as a ligand binding to the CD44 receptor on endothelial cell surfaces (Jong et al., 2008; Jong et al., 2012), promoting C. neoformans adhesion to the vascular side of the BBB (Huang et al., 2011). This enhances the interaction between the fungus and brain microvascular endothelial cells (Chen Y. et al., 2022). Furthermore, HA contributes to BBB disruption by compromising tight junctions between endothelial cells. Collectively, these mechanisms facilitate trans-BBB transport of Cryptococcus, ultimately leading to the development of CM (Figure 2).

3.2 Iron metabolism-immune interactions drive CM pathogenesis

Iron metabolism-immune interactions play a bidirectional regulatory role in CM pathogenesis, involving dynamic competition between host and pathogen for iron and the resulting expression of C. neoformans virulence and host immune defense efficacy. As a key nutrient required by both host immune cells and pathogens, iron uptake determines the course of infection (Do et al., 2020). The host employs a hepcidin-mediated iron restriction strategy to inhibit C. neoformans capsule synthesis by suppressing Lac1 activity, weakening immune evasion. In low-iron microenvironments, the pathogen activates high-affinity iron uptake systems, upregulating capsule polysaccharide synthesis genes to evade host PRR immune recognition, forming a dual metabolic-immune defense barrier (Jung et al., 2010; Li et al., 2024). Notably, this competitive imbalance in iron homeostasis can trigger cascading pathological effects: on one hand, host intracellular iron overload triggers ferroptosis through ACSL4-dependent pathways—a form of iron-dependent programmed cell death characterized by glutathione peroxidase 4 inactivation and abnormal lipid peroxidation accumulation, directly disrupting BBB endothelial tight junctions (Dixon and Olzmann, 2024; Xie et al., 2016). On the other hand, iron metabolism dysregulation, coupled with lipid and amino acid metabolic reprogramming, exacerbates oxidative stress damage associated with ferroptosis, forming a vicious cycle of “iron accumulation-lipid peroxidation-BBB permeability increase” (Xu X. et al., 2021; Chen et al., 2021; Xu et al., 2024). The excessive ROS and lipid peroxidation products generated through this process exacerbate CNS infection through dual mechanisms: first, by disrupting BBB tight junctions through oxidative stress, increasing permeability, and promoting C. neoformans CNS invasion and inflammatory factor diffusion; second, by modulating immune cell functional states, ROS and lipid peroxidation products activate pro-inflammatory signals (e.g., NF-κB), significantly exacerbating CM-related neuroinflammation, forming a “oxidative damage-neuroinflammation” positive feedback loop (Chen X. et al., 2022) (Figure 2). Additionally, microglial immune surveillance function is closely related to iron metabolism balance. Clinical studies show that abnormal increases in CSF ferritin levels impair microglial phagocytic function and cytokine secretion. This iron metabolism-immune regulatory axis dysfunction may create an immune-privileged microenvironment for CNS infections, involving multiple molecular mechanisms such as transferrin receptor signaling pathway abnormalities and iron regulatory protein (IRP) activity changes (Xu X. et al., 2021; Rochette et al., 2022; Latunde-Dada, 2017).

3.3 Oxidative stress metabolism and immune synergistic regulation of Cryptococcus neoformans pathogenicity

During host infection, C. neoformans-immune system interactions are regulated by oxidative stress metabolism. C. neoformans dynamically regulates energy metabolism to adapt to the host microenvironment. Under hypoxic conditions, it relies on transcription factors Pas2 and Rds2-mediated metabolic reprogramming, inhibiting mitochondrial oxidative phosphorylation and activating glycolysis to reduce ROS generation and maintain CNS invasion capability (Zhao and Lin, 2021). Host immune cells (e.g., neutrophils, macrophages) produce large amounts of ROS through respiratory bursts to clear pathogens. However, excessive ROS not only damages host cells, causing oxidative stress, but also chronically activates immune cells, forming a vicious cycle of ROS overproduction. To counteract oxidative damage, C. neoformans employs multi-layered antioxidant mechanisms, including upregulating superoxide dismutase, glutathione systems, and melanin synthesis to neutralize ROS, while utilizing inositol metabolism to maintain membrane integrity and evade immune recognition (Spadari et al., 2018) (Figure 2).

3.4 Metabolic-immune synergistic regulatory network strategies for CM prevention and treatment

In C. neoformans, inositol pyrophosphates (PP-IPs) are key metabolites for adapting to the host environment. Inhibiting their biosynthesis can weaken fungal virulence, making PP-IP metabolic pathways potential targets for antifungal drug development (Kang, 2018). The inositol pyrophosphate pathway, as a key metabolic signaling hub in C. neoformans, regulates fungal cell cycle, virulence factor secretion, environmental stress adaptation, and host immune evasion mechanisms, participating in the dynamic balance of its pathogenic processes (Gogianu et al., 2024). Among these, inositol polyphosphate kinase Kcs1 negatively regulates inositol uptake and metabolism in C. neoformans. Knocking out this gene reduces C. neoformans CNS invasion ability, suggesting its potential as a drug target (Liao et al., 2018) (Table 2). C. neoformans utilizes multiple inositol transporters and host inositol-dependent transport systems to synergistically promote BBB penetration. Dinitrophenol (DNP), a specific inhibitor of inositol transporters, blocks C. neoformans inositol uptake, inhibiting migration activity and significantly reducing pathogenic virulence (Liu et al., 2013; Porollo et al., 2014) (Table 2). In oxidative stress-immune regulation intervention strategies, J-domain proteins Mrj1 and Mar1 regulate mitochondrial respiratory chains and ROS homeostasis, directly impacting fungal virulence and antifungal tolerance, making them potential therapeutic targets (Calderone et al., 2015; Horianopoulos et al., 2020; Telzrow et al., 2023) (Table 2). Basic leucine zipper protein Gsb1 and heat shock factor HSF have been shown to regulate ROS scavenging genes and mitochondrial homeostasis, weakening C. neoformans virulence (Cheon et al., 2017; Gao et al., 2022).

Table 2
www.frontiersin.org

Table 2. Key agents for the triad therapy in cryptococcal meningitis and their experimental/clinical evidence status.

4 Integrated mechanisms of the lung-gut-brain immune-metabolic axis in cryptococcal meningitis (CM)

Following Cryptococcus infection, the fungus first colonizes and rapidly proliferates within the alveoli, activating alveolar macrophages and dendritic cells. The latter recognize cryptococcal components via pattern recognition receptors (such as Toll-like receptors), prompting the secretion of high levels of pro-inflammatory cytokines including IL-6, TNF-α, and IFN-γ (Korkmaz and Traber, 2023; Ye et al., 2025). These inflammatory cytokines enter the intestinal tissue and brain via the circulatory system. In the gut, these factors not only disrupt tight junction proteins (e.g., occludin, claudin-1), weakening the intestinal epithelial barrier and increasing permeability, but also drive a decline in beneficial microbiota (such as Lactobacillus) and an increase in opportunistic pathogens (such as Polymorphobacter), leading to dysbiosis (Barbara et al., 2021; Chelakkot et al., 2018; Kaminsky et al., 2021). Concurrently, via the CCR2-CCL2 signaling axis, inflammatory monocytes are recruited to cross the vascular wall into the brain tissue, further activating microglia and causing neuroinflammation and BBB damage (Dimitrijevic et al., 2006; Dimitrijevic et al., 2007; Geng et al., 2022). This sequence of events establishes the “lung-gut-brain” axis as a highly coordinated immune crosstalk network, creating favorable conditions for the hematogenous dissemination of Cryptococcus and its penetration of the BBB into the central nervous system.

Pulmonary inflammation also activates the IDO-tryptophan-kynurenine pathway, promoting the conversion of tryptophan to kynurenine and its downstream metabolites under IDO catalysis. These metabolites can cross the blood–brain barrier, modulating astrocyte and microglial activity. Simultaneously, by altering intestinal lumen pH and substrate availability, they impact gut microbiota diversity and exacerbate ecological imbalance (Cervenka et al., 2017; Tsuji et al., 2023; Bohn et al., 2024). Changes in the gut microbial community further result in reduced levels of short-chain fatty acids (SCFAs), such as butyrate and propionate. SCFA deficiency severely compromises BBB integrity and neuroimmune homeostasis: On one hand, SCFAs activate G protein-coupled receptors (GPR43/41) to upregulate tight junction protein expression (ZO-1/Claudin-5), while inhibiting histone deacetylase (HDAC) to promote regulatory T cell (Treg) differentiation, thereby preserving BBB integrity through both physical and immune barrier dimensions (Li H. J. et al., 2023); On the other hand, SCFAs (e.g., propionate) drive microglial polarization towards the anti-inflammatory M2 phenotype via the metabolism-immune axis, suppressing the release of pro-inflammatory cytokines like IL-1β and TNF-α. Concurrently, they induce astrocytes to downregulate pro-inflammatory factor secretion and upregulate neuroprotective factors (e.g., GDNF) via the TLR4/NF-κB pathway, creating an immune microenvironment that inhibits Cryptococcus proliferation (Li H. J. et al., 2023; Loh et al., 2024; Fock and Parnova, 2023). This immune-metabolic reprogramming not only reduces damage to BBB endothelial cells by inflammatory mediators but also improves BBB permeability by regulating the dynamic balance of matrix metalloproteinases (MMPs) (Parker et al., 2020; Benakis et al., 2016). SCFAs typically enhance the phagocytic and bactericidal capacity of alveolar macrophages and help maintain BBB integrity via the GPR43-AMPK signaling pathway; SCFA deficiency weakens this immune barrier effect and sustains intracerebral inflammation (Nakajima et al., 2017; Saikachain et al., 2023) (Table 2). Furthermore, the pulmonary inflammatory response significantly alters the interaction between bile acid metabolism and the gut microbiota. Abnormal activation of the FXR-FGF19 signaling axis promotes microglial polarization towards the pro-inflammatory M1 phenotype, and the release of neurotoxic factors further damages tissue (Mulak, 2021; Ma et al., 2024) (Figure 3).

Figure 3
Diagram illustrating the impact of gut and brain inflammation on the body's barriers. The left panel shows mechanisms like SCFAs deficiency and cytokine activation affecting the blood-brain barrier. The right panel depicts intestinal barrier destruction due to PAMPs and cytokines. The center highlights the connection between brain, lung, and gut. Icon labels include molecules and cells involved in the processes, such as cytokines, Treg, microglia, and macrophages.

Figure 3. This figure illustrates the brain-gut-lung axis interactions in Cryptococcus neoformans infection: After colonizing the lungs, pathogen-associated molecular patterns (PAMPs) of C. neoformans activate alveolar macrophages and dendritic cells through Toll-like receptor 2 (TLR2) recognition, inducing secretion of inflammatory cytokines such as TNF-α, IL-6, and IFN-γ. These cytokines disrupt intestinal tight junction proteins (occludin, claudin-1) via the bloodstream, leading to intestinal barrier damage and gut dysbiosis. Altered gut microbiota causes short-chain fatty acid (SCFA) deficiency. SCFAs influence the brain through three pathways: (1) downregulating histone deacetylases (HDACs) to promote regulatory T cell (Treg) differentiation; (2) activating G protein-coupled receptors (GPCRs) to maintain blood–brain barrier (BBB) integrity; (3) driving microglial polarization toward the anti-inflammatory M2 phenotype (suppressing IL-1β and TNF-α release) and promoting astrocytes to upregulate the neuroprotective factor glial cell line-derived neurotrophic factor (GDNF) via the TLR4/NF-κB pathway, establishing an anti-cryptococcal immune microenvironment. Concurrently, inflammatory monocytes are recruited into the brain via CCL2, activating microglia, while neuroactive metabolites from the indoleamine 2,3-dioxygenase (IDO)-kynurenine (KYNA)-quinolinic acid (QA) pathway, such as 3-hydroxykynurenine (3-HKA), impact brain function.

Gut microbiota dysbiosis holds significant clinical implications in CM patients. Studies indicate that this dysregulated state can persist long-term, continuously modulating neuroinflammatory responses and neuroplasticity via the gut-brain axis. Notably, persistent gut microbial imbalance in CM survivors is significantly associated with various neurological sequelae. Clinical data demonstrate a positive correlation between the degree of gut dysbiosis and disease severity/prognosis: patients exhibiting reduced microbial diversity and increased proportions of pathogenic bacteria show markedly worse clinical outcomes, with significantly increased mortality risk (Ma et al., 2023; Panackal et al., 2015; Li et al., 2022). Therefore, dynamic monitoring and timely intervention targeting the gut microecology are crucial not only for acute-phase treatment but also for improving long-term neurological functional outcomes in patients.

5 Evidence base for immune-metabolic-microbiota interventions

The immune-metabolic-microbiota triad therapy is grounded in the theoretical framework of the multi-faceted pathogenesis of CM. It combines the modulation of host immunity, pathogen metabolism, and the intestinal microbiome, creating a novel therapeutic paradigm for refractory fungal infections. Among the existing evidence, immunomodulators represent the most clinically validated component of the triad intervention. A multicenter randomized controlled trial investigating interferon-gamma (IFN-γ) combined with amphotericin B and flucytosine for HIV-associated CM demonstrated an increase in early fungicidal activity (EFA) from −0.49 log CFU/ml/day to −0.64 log CFU/ml/day (p = 0.02) (Jarvis et al., 2012) with efficacy observed after only two doses of IFN-γ. Another study involving 75 AIDS-related cases showed that the 2-week CSF culture conversion rates were 36 and 32% in the 100 μg and 200 μg IFN-γ treatment groups, respectively, significantly higher than the 13% rate in the placebo group (Pappas et al., 2004). Mechanistic studies further confirmed that patients with higher baseline IFN-γ levels had superior clinical outcomes (Jarvis et al., 2015; Jarvis et al., 2013). A phase I trial of the monoclonal antibody 18B7 established its maximum tolerated dose at 1.0 mg/kg. While it significantly reduced serum cryptococcal antigen titers by two- to three-fold, its concentration in the CSF was extremely low (Larsen et al., 2005). In contrast, metabolic inhibitors such as inositol transporter inhibitors and the hepcidin mimetic PR-73 have demonstrated antifungal activity in animal models and significantly improved infection outcomes. However, human safety and efficacy clinical data are currently lacking (Arekar et al., 2024) (Table 2).

Regarding microbiota interventions, although fecal microbiota transplantation (FMT) and probiotic interventions are widely used clinically in conditions like ulcerative colitis, with remission rates ranging from 32 to 53% and good tolerability (Costello et al., 2019; Haifer et al., 2022; Paramsothy et al., 2017), direct data in the context of cryptococcal meningitis are absent. FMT has been shown to improve non-motor symptoms in Parkinson’s disease patients and alter brain dopamine transporter binding in metabolic syndrome patients (Cheng et al., 2023; Hartstra et al., 2020), but these findings cannot be directly extrapolated to CM treatment. Supplementation with probiotics aims to maintain intestinal microecological homeostasis, enhance SCFA production, strengthen the gut barrier, and reduce central nervous system inflammation. Key aspects of the triad therapy, including dose optimization, treatment sequencing, and component synergism, still lack systematic clinical validation. Although novel immunomodulators like lenalidomide can significantly reduce cell-associated HIV RNA, improve chronic inflammation, and lead to significant decreases in serum inflammatory markers such as CRP and IL-6 in patients (Wan et al., 2023; Liu et al., 2022) (Table 2), the efficacy and safety of their combined application with metabolic and microbiota interventions remain to be elucidated. Overall, the triad intervention possesses a solid theoretical foundation and partial clinical support. However, high-quality clinical trials are still needed to systematically validate the efficacy and safety of each component and the integrated intervention strategy, aiming to deliver tangible benefits to patients with cryptococcal meningitis.

6 Outlook

The occurrence of CM is essentially a cascade reaction of pathogens breaching the host’s multi-dimensional defense system, with the immune system playing a central regulatory role in CM’s pathological progression. Its interactions with metabolic dysregulation and gut microbiota dysbiosis are key mechanisms influencing disease progression. The BBB, as the ultimate defense barrier of the CNS, serves as the synergistic hub of the immune-metabolism-microbiota network: overactivation of immune cells (e.g., microglia), oxidative damage associated with ferroptosis, and microbiota dysbiosis-induced BBB permeability increases collectively constitute the “triple hit” of C. neoformans CNS colonization. The neuroimmune unit formed by microglia and astrocytes plays a dual role in BBB dynamic regulation: on one hand, it maintains immune homeostasis through anti-inflammatory factors (e.g., IL-10, TGF-β); on the other hand, it initiates inflammatory responses through PRRs. C. neoformans breaches the BBB through the “Trojan horse” mechanism, transcytosis, and paracellular pathways, reflecting the failure of host immune surveillance. Pathogen capsule polysaccharides can induce microglial M2 polarization, creating an immunosuppressive microenvironment favorable for C. neoformans CNS colonization. Metabolic pathway dysregulation can profoundly reshape immune homeostasis. For example, iron metabolism dysregulation induces BBB dysfunction, inhibits microglial phagocytosis, and exacerbates pro-inflammatory cascades, significantly aggravating CM pathological damage. Meanwhile, C. neoformans inositol metabolism enhances pathogenicity by regulating capsule polysaccharide synthesis, evading host immune recognition. The gut microbiota indirectly influences CM progression by modulating the immune system and maintaining BBB integrity, particularly through regulating the functions of microglia and astrocytes. The tripartite interaction system of the microbiota-immune-neuroglia unit restricts the central dissemination of Cryptococcus by preserving BBB stability.

Future research must first utilize multi-omics technologies to systematically elucidate the dynamic interaction mechanisms of the “immune-metabolism-microbiota axis” in cryptococcal meningitis, with particular focus on the correlation between blood–brain barrier disruption and neuroinflammation. Building upon this foundation, there is an urgent need to develop temporally precise, stepwise combination therapies—acute phase targeting inositol transport (DNP) synergized with immune modulation (IFN-γ) for rapid infection control, recovery phase restoring gut-brain axis homeostasis through probiotics/SCFAs while enhancing central nervous system targeting of drugs (e.g., ferroptosis inhibitors) via nanocarriers. Concurrently, to reverse neurological damage, innovative strategies should be explored including glial cell reprogramming (e.g., tamoxifen derivatives inducing neuroprotective astrocytes) and microbial-mitochondrial axis interventions, combined with high-throughput screening of BBB-protective agents using organoid models. Finally, by integrating cutting-edge technologies such as fungal epigenetic regulation, engineered probiotics for immune activation, and AI-powered prognostic algorithms, a paradigm shift toward precision medicine—transitioning from pathogen eradication to neurological functional restoration—can be achieved.

Author contributions

SW: Formal analysis, Conceptualization, Data curation, Writing – original draft, Investigation. ML: Writing – original draft, Software, Methodology, Project administration. CP: Methodology, Project administration, Investigation, Formal analysis, Writing – review & editing. LZ: Methodology, Conceptualization, Investigation, Software, Writing – review & editing, Resources, Data curation. RY: Methodology, Data curation, Formal analysis, Conceptualization, Supervision, Writing – review & editing. ZX: Validation, Supervision, Visualization, Investigation, Funding acquisition, Writing – review & editing, Project administration.

Funding

The author(s) declare that financial support was received for the research and/or publication of this article. This work was supported by grants from the National Natural Science Foundation of China (Nos. 82360268 and 82471487), the Guizhou epilepsy basic and clinical research scientific and technological innovation talent team project (No: CXTD[2022]013), the Guizhou provincial "hundred" level innovative talents funds (No: GCC-2022-038-1), Zunyi City construction project of innovative talent platform for spatial proteomics research on hippocampal sclerosis in drug-resistant temporal lobe epilepsy (NO:[2023]10).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The authors declare that no Gen AI was used in the creation of this manuscript.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

Aaron, P. A., Vu, K., and Gelli, A. (2020). An Antivirulence approach for preventing Cryptococcus neoformans from crossing the blood-brain barrier via novel natural product inhibitors of a fungal metalloprotease. MBio 11:20. doi: 10.1128/mBio.01249-20

PubMed Abstract | Crossref Full Text | Google Scholar

Alanio, A. (2020). Dormancy in Cryptococcus neoformans: 60 years of accumulating evidence. J. Clin. Invest. 130, 3353–3360. doi: 10.1172/JCI136223

PubMed Abstract | Crossref Full Text | Google Scholar

Al-Huthaifi, A. M., Radman, B. A., Al-Alawi, A. A., Mahmood, F., and Liu, T. B. (2024). Mechanisms and virulence factors of Cryptococcus neoformans dissemination to the central nervous system. J. Fungi 10:586. doi: 10.3390/jof10080586

Crossref Full Text | Google Scholar

Arekar, T., Katikaneni, D., Kasem, S., Desai, D., Acharya, T., Cole, A., et al. (2024) Essential role of hepcidin in host resistance to disseminated candidiasis. Biorxiv [Preprint]. doi: 10.1101/2024.10.29.620511

Crossref Full Text | Google Scholar

Baddley, J. W., Chen, S. C., Huisingh, C., Benedict, K., DeBess, E. E., Galanis, E., et al. (2021). MSG07: an international cohort study comparing epidemiology and outcomes of patients with Cryptococcus neoformans or Cryptococcus gattii infections. Clin. Infect. Dis. 73, 1133–1141. doi: 10.1093/cid/ciab268

PubMed Abstract | Crossref Full Text | Google Scholar

Baker, R. P., Liu, A. Z., and Casadevall, A. (2024). Cell wall melanin impedes growth of the Cryptococcus neoformans polysaccharide capsule by sequestering calcium. Proc. Natl. Acad. Sci. USA 121:e2412534121. doi: 10.1073/pnas.2412534121

PubMed Abstract | Crossref Full Text | Google Scholar

Balasko, A., and Keynan, Y. (2019). Shedding light on IRIS: from pathophysiology to treatment of Cryptococcal meningitis and immune reconstitution inflammatory syndrome in HIV-infected individuals. HIV Med. 20, 1–10. doi: 10.1111/hiv.12676

PubMed Abstract | Crossref Full Text | Google Scholar

Bao, Y., and Cao, X. (2014). The immune potential and immunopathology of cytokine-producing B cell subsets: a comprehensive review. J. Autoimmun. 55, 10–23. doi: 10.1016/j.jaut.2014.04.001

PubMed Abstract | Crossref Full Text | Google Scholar

Barbara, G., Barbaro, M. R., Fuschi, D., Palombo, M., Falangone, F., Cremon, C., et al. (2021). Inflammatory and microbiota-related regulation of the intestinal epithelial barrier. Front. Nutr. 8:718356. doi: 10.3389/fnut.2021.718356

PubMed Abstract | Crossref Full Text | Google Scholar

Beardsley, J., Sorrell, T. C., and Chen, S. C. (2019). Central nervous system cryptococcal infections in non-HIV infected patients. J. Fungi 5:71. doi: 10.3390/jof5030071

Crossref Full Text | Google Scholar

Benakis, C., Brea, D., Caballero, S., Faraco, G., Moore, J., Murphy, M., et al. (2016). Commensal microbiota affects ischemic stroke outcome by regulating intestinal γδ T cells. Nat. Med. 22, 516–523. doi: 10.1038/nm.4068

PubMed Abstract | Crossref Full Text | Google Scholar

Bohn, B., Tilves, C., Chen, Y., Doyon, M., Bouchard, L., Perron, P., et al. (2024). Associations of gut microbiota features and circulating metabolites with systemic inflammation in children. BMJ Open Gastroenterol. 11:e001470. doi: 10.1136/bmjgast-2024-001470

PubMed Abstract | Crossref Full Text | Google Scholar

Bonilla, F. A., and Oettgen, H. C. (2010). Adaptive immunity. J. Allergy Clin. Immunol. 125, S33–S40. doi: 10.1016/j.jaci.2009.09.017

PubMed Abstract | Crossref Full Text | Google Scholar

Borges, M., Filho, A. A., Oliveira, B. J. S., Moreira, I. S., Paula, V., Bastos, L., et al. (2019). Prospective cohort of AIDS patients screened for cryptococcal antigenaemia, pre-emptively treated and followed in Brazil. PLoS One 14:e0219928. doi: 10.1371/journal.pone.0219928

Crossref Full Text | Google Scholar

Burgess, T. B., Condliffe, A. M., and Elks, P. M. (2022). A fun-guide to innate immune responses to fungal infections. J Fungi 8:805. doi: 10.3390/jof8080805

PubMed Abstract | Crossref Full Text | Google Scholar

Calderone, R., Li, D., and Traven, A. (2015). System-level impact of mitochondria on fungal virulence: to metabolism and beyond. FEMS Yeast Res. 15:fov027. doi: 10.1093/femsyr/fov027

PubMed Abstract | Crossref Full Text | Google Scholar

Campuzano, A., and Wormley, F. L. (2018). Innate immunity against Cryptococcus, from recognition to elimination. J. Fungi 4:33. doi: 10.3390/jof4010033

Crossref Full Text | Google Scholar

Cervenka, I., Agudelo, L. Z., and Ruas, J. L. (2017). Kynurenines: tryptophan's metabolites in exercise, inflammation, and mental health. Science 357:794. doi: 10.1126/science.aaf9794

PubMed Abstract | Crossref Full Text | Google Scholar

Chelakkot, C., Ghim, J., and Ryu, S. H. (2018). Mechanisms regulating intestinal barrier integrity and its pathological implications. Exp. Mol. Med. 50, 1–9. doi: 10.1038/s12276-018-0126-x

PubMed Abstract | Crossref Full Text | Google Scholar

Chen, X., Li, J., Kang, R., Klionsky, D. J., and Tang, D. (2021). Ferroptosis: machinery and regulation. Autophagy 17, 2054–2081. doi: 10.1080/15548627.2020.1810918

PubMed Abstract | Crossref Full Text | Google Scholar

Chen, S. C., Meyer, W., and Sorrell, T. C. (2014). Cryptococcus gattii infections. Clin. Microbiol. Rev. 27, 980–1024. doi: 10.1128/CMR.00126-13

PubMed Abstract | Crossref Full Text | Google Scholar

Chen, X., Pang, X., Yeo, A. J., Xie, S., Xiang, M., Shi, B., et al. (2022). The molecular mechanisms of Ferroptosis and its role in blood-brain barrier dysfunction. Front. Cell. Neurosci. 16:889765. doi: 10.3389/fncel.2022.889765

PubMed Abstract | Crossref Full Text | Google Scholar

Chen, J., Shao, J., Dai, M., Fang, W., and Yang, Y. L. (2023). Adaptive immunology of Cryptococcus neoformans infections-an update. Front. Immunol. 14:1174967. doi: 10.3389/fimmu.2023.1174967

PubMed Abstract | Crossref Full Text | Google Scholar

Chen, Y., Shi, Z. W., Strickland, A. B., and Shi, M. (2022). Cryptococcus neoformans infection in the central nervous system: the battle between host and pathogen. J. Fungi 8:69. doi: 10.3390/jof8101069

PubMed Abstract | Crossref Full Text | Google Scholar

Cheng, Y., Tan, G., Zhu, Q., Wang, C., Ruan, G., Ying, S., et al. (2023). Efficacy of fecal microbiota transplantation in patients with Parkinson's disease: clinical trial results from a randomized, placebo-controlled design. Gut Microbes 15:2284247. doi: 10.1080/19490976.2023.2284247

PubMed Abstract | Crossref Full Text | Google Scholar

Cheon, S. A., Thak, E. J., Bahn, Y. S., and Kang, H. A. (2017). A novel bZIP protein, Gsb1, is required for oxidative stress response, mating, and virulence in the human pathogen Cryptococcus neoformans. Sci. Rep. 7:4044. doi: 10.1038/s41598-017-04290-8

PubMed Abstract | Crossref Full Text | Google Scholar

Coelho, C. (2024). Batf3-cDC1 control Th1 and fungicidal responses during cryptococcal meningitis: is this enough to control meningitis? MBio 15:e0037524. doi: 10.1128/mbio.00375-24

PubMed Abstract | Crossref Full Text | Google Scholar

Colombo, A. C., Rella, A., Normile, T., Joffe, L. S., Tavares, P. M., de, S. A. G. R., et al. (2019). Cryptococcus neoformans glucuronoxylomannan and sterylglucoside are required for host protection in an animal vaccination model. MBio 10, e02909–e02918. doi: 10.1128/mBio.02909-18

Crossref Full Text | Google Scholar

Cordero, R. J. B., Camacho, E., and Casadevall, A. (2020). Melanization in Cryptococcus neoformans requires complex regulation. MBio 11:19. doi: 10.1128/mBio.03313-19

PubMed Abstract | Crossref Full Text | Google Scholar

Costello, S. P., Hughes, P. A., Waters, O., Bryant, R. V., Vincent, A. D., Blatchford, P., et al. (2019). Effect of fecal microbiota transplantation on 8-week remission in patients with ulcerative colitis: a randomized clinical trial. JAMA 321, 156–164. doi: 10.1001/jama.2018.20046

PubMed Abstract | Crossref Full Text | Google Scholar

Dang, E. V., Lei, S., Radkov, A., Volk, R. F., Zaro, B. W., and Madhani, H. D. (2022). Secreted fungal virulence effector triggers allergic inflammation via TLR4. Nature 608, 161–167. doi: 10.1038/s41586-022-05005-4

PubMed Abstract | Crossref Full Text | Google Scholar

Das Gupta, K., Shakespear, M. R., Iyer, A., Fairlie, D. P., and Sweet, M. J. (2016). Histone deacetylases in monocyte/macrophage development, activation and metabolism: refining HDAC targets for inflammatory and infectious diseases. Clin. Transl. Immunol. 5:e62. doi: 10.1038/cti.2015.46

PubMed Abstract | Crossref Full Text | Google Scholar

Davis, M. J., and Lionakis, M. S. (2018). B cells protect T cell-deficient mice from Cryptococcal brain invasion. Virulence 9, 25–27. doi: 10.1080/21505594.2017.1393601

PubMed Abstract | Crossref Full Text | Google Scholar

Davis, M. J., Tsang, T. M., Qiu, Y., Dayrit, J. K., Freij, J. B., Huffnagle, G. B., et al. (2013). Macrophage M1/M2 polarization dynamically adapts to changes in cytokine microenvironments in Cryptococcus neoformans infection. MBio 4:e00264-13. doi: 10.1128/mBio.00264-13

PubMed Abstract | Crossref Full Text | Google Scholar

De Bock, M., Van Haver, V., Vandenbroucke, R. E., Decrock, E., Wang, N., and Leybaert, L. (2016). Into rather unexplored terrain-transcellular transport across the blood-brain barrier. Glia 64, 1097–1123. doi: 10.1002/glia.22960

PubMed Abstract | Crossref Full Text | Google Scholar

de Castro, R. J. A., Marina, C. L., Sturny-Leclère, A., Hoffmann, C., Bürgel, P. H., Wong, S. S. W., et al. (2023). Kicking sleepers out of bed: macrophages promote reactivation of dormant Cryptococcus neoformans by extracellular vesicle release and non-lytic exocytosis. PLoS Pathog. 19:e1011841. doi: 10.1371/journal.ppat.1011841

PubMed Abstract | Crossref Full Text | Google Scholar

Dimitrijevic, O. B., Stamatovic, S. M., Keep, R. F., and Andjelkovic, A. V. (2006). Effects of the chemokine CCL2 on blood-brain barrier permeability during ischemia-reperfusion injury. J. Cereb. Blood Flow Metab. 26, 797–810. doi: 10.1038/sj.jcbfm.9600229

PubMed Abstract | Crossref Full Text | Google Scholar

Dimitrijevic, O. B., Stamatovic, S. M., Keep, R. F., and Andjelkovic, A. V. (2007). Absence of the chemokine receptor CCR2 protects against cerebral ischemia/reperfusion injury in mice. Stroke 38, 1345–1353. doi: 10.1161/01.STR.0000259709.16654.8f

PubMed Abstract | Crossref Full Text | Google Scholar

Dixon, S. J., and Olzmann, J. A. (2024). The cell biology of ferroptosis. Nat. Rev. Mol. Cell Biol. 25, 424–442. doi: 10.1038/s41580-024-00703-5

PubMed Abstract | Crossref Full Text | Google Scholar

Do, E., Cho, Y. J., Kim, D., Kronstad, J. W., and Jung, W. H. (2020). A transcriptional regulatory map of Iron homeostasis reveals a new control circuit for capsule formation in Cryptococcus neoformans. Genetics 215, 1171–1189. doi: 10.1534/genetics.120.303270

PubMed Abstract | Crossref Full Text | Google Scholar

Dong, C. (2021). Cytokine regulation and function in T cells. Annu. Rev. Immunol. 39, 51–76. doi: 10.1146/annurev-immunol-061020-053702

PubMed Abstract | Crossref Full Text | Google Scholar

Elsegeiny, W., Marr, K. A., and Williamson, P. R. (2018). Immunology of Cryptococcal infections: developing a rational approach to patient therapy. Front. Immunol. 9:651. doi: 10.3389/fimmu.2018.00651

PubMed Abstract | Crossref Full Text | Google Scholar

Eschke, M., Piehler, D., Schulze, B., Richter, T., Grahnert, A., Protschka, M., et al. (2015). A novel experimental model of Cryptococcus neoformans-related immune reconstitution inflammatory syndrome (IRIS) provides insights into pathogenesis. Eur. J. Immunol. 45, 3339–3350. doi: 10.1002/eji.201545689

PubMed Abstract | Crossref Full Text | Google Scholar

Feldmesser, M., Tucker, S., and Casadevall, A. (2001). Intracellular parasitism of macrophages by Cryptococcus neoformans. Trends Microbiol. 9, 273–278. doi: 10.1016/S0966-842X(01)02035-2

PubMed Abstract | Crossref Full Text | Google Scholar

Firacative, C., Gressler, A. E., Schubert, K., Schulze, B., Müller, U., Brombacher, F., et al. (2018). Identification of T helper (Th)1- and Th2-associated antigens of Cryptococcus neoformans in a murine model of pulmonary infection. Sci. Rep. 8:2681. doi: 10.1038/s41598-018-21039-z

PubMed Abstract | Crossref Full Text | Google Scholar

Fock, E., and Parnova, R. (2023). Mechanisms of blood-brain barrier protection by microbiota-derived short-chain fatty acids. Cells 12:657. doi: 10.3390/cells12040657

PubMed Abstract | Crossref Full Text | Google Scholar

Francis, V. I., Liddle, C., Camacho, E., Kulkarni, M., Junior, S. R. S., Harvey, J. A., et al. (2024). Cryptococcus neoformans rapidly invades the murine brain by sequential breaching of airway and endothelial tissues barriers, followed by engulfment by microglia. MBio 15:e0307823. doi: 10.1128/mbio.03078-23

PubMed Abstract | Crossref Full Text | Google Scholar

Fu, M. S., and Drummond, R. A. (2020). The diverse roles of monocytes in Cryptococcosis. J Fungi 6:111. doi: 10.3390/jof6030111

PubMed Abstract | Crossref Full Text | Google Scholar

Gao, X., Fu, Y., Sun, S., Gu, T., Li, Y., Sun, T., et al. (2022). Cryptococcal Hsf3 controls intramitochondrial ROS homeostasis by regulating the respiratory process. Nat. Commun. 13:5407. doi: 10.1038/s41467-022-33168-1

PubMed Abstract | Crossref Full Text | Google Scholar

Geng, H., Chen, L., Tang, J., Chen, Y., and Wang, L. (2022). The role of CCL2/CCR2 axis in cerebral ischemia-reperfusion injury and treatment: from animal experiments to clinical trials. Int. J. Mol. Sci. 23:485. doi: 10.3390/ijms23073485

PubMed Abstract | Crossref Full Text | Google Scholar

Ginhoux, F., Greter, M., Leboeuf, M., Nandi, S., See, P., Gokhan, S., et al. (2010). Fate mapping analysis reveals that adult microglia derive from primitive macrophages. Science 330, 841–845. doi: 10.1126/science.1194637

PubMed Abstract | Crossref Full Text | Google Scholar

Gogianu, L. I., Ruta, L. L., and Farcasanu, I. C. (2024). Kcs1 and Vip1: the key enzymes behind inositol pyrophosphate signaling in Saccharomyces cerevisiae. Biomol. Ther. 14:152. doi: 10.3390/biom14020152

PubMed Abstract | Crossref Full Text | Google Scholar

Guasconi, L., Beccacece, I., Volpini, X., Burstein, V. L., Mena, C. J., Silvane, L., et al. (2022). Pulmonary conventional type 1 Langerin-expressing dendritic cells play a role in impairing early protective immune response against Cryptococcus neoformans infection in mice. J. Fungi 8:792. doi: 10.3390/jof8080792

Crossref Full Text | Google Scholar

Guérit, S., Fidan, E., Macas, J., Czupalla, C. J., Figueiredo, R., Vijikumar, A., et al. (2021). Astrocyte-derived Wnt growth factors are required for endothelial blood-brain barrier maintenance. Prog. Neurobiol. 199:101937. doi: 10.1016/j.pneurobio.2020.101937

PubMed Abstract | Crossref Full Text | Google Scholar

Guilliams, M., Mildner, A., and Yona, S. (2018). Developmental and functional heterogeneity of monocytes. Immunity 49, 595–613. doi: 10.1016/j.immuni.2018.10.005

PubMed Abstract | Crossref Full Text | Google Scholar

Haifer, C., Paramsothy, S., Kaakoush, N. O., Saikal, A., Ghaly, S., Yang, T., et al. (2022). Lyophilised oral faecal microbiota transplantation for ulcerative colitis (LOTUS): a randomised, double-blind, placebo-controlled trial. Lancet Gastroenterol. Hepatol. 7, 141–151. doi: 10.1016/S2468-1253(21)00400-3

PubMed Abstract | Crossref Full Text | Google Scholar

Hailu, K., Niguse, S., Hagos, K., and Abdulkader, M. (2019). Cryptococcal antigenemia and associated risk factors among ART-naïve and ART-experienced HIV-infected peoples at selected health institutions of Mekelle, northern Ethiopia. Microbiology 8:e00746. doi: 10.1002/mbo3.746

PubMed Abstract | Crossref Full Text | Google Scholar

Hartstra, A. V., Schüppel, V., Imangaliyev, S., Schrantee, A., Prodan, A., Collard, D., et al. (2020). Infusion of donor feces affects the gut-brain axis in humans with metabolic syndrome. Mol. Metabolism 42:101076. doi: 10.1016/j.molmet.2020.101076

PubMed Abstract | Crossref Full Text | Google Scholar

Haruwaka, K., Ikegami, A., Tachibana, Y., Ohno, N., Konishi, H., Hashimoto, A., et al. (2019). Dual microglia effects on blood brain barrier permeability induced by systemic inflammation. Nat. Commun. 10:5816. doi: 10.1038/s41467-019-13812-z

PubMed Abstract | Crossref Full Text | Google Scholar

Hazra, I., Datta, A., Mondal, S., Moitra, S., Singh, M. K., Chaudhuri, S., et al. (2019). T11TS immunotherapy augments microglial and lymphocyte protective immune responses against Cryptococcus neoformans in the brain. Scand. J. Immunol. 89:e12733. doi: 10.1111/sji.12733

PubMed Abstract | Crossref Full Text | Google Scholar

Horianopoulos, L. C., Hu, G., Caza, M., Schmitt, K., Overby, P., Johnson, J. D., et al. (2020). The novel J-domain protein Mrj1 is required for mitochondrial respiration and virulence in Cryptococcus neoformans. MBio 11, e01127–e01120. doi: 10.1128/mBio.01127-20

PubMed Abstract | Crossref Full Text | Google Scholar

Huang, S. H., Long, M., Wu, C. H., Kwon-Chung, K. J., Chang, Y. C., Chi, F., et al. (2011). Invasion of Cryptococcus neoformans into human brain microvascular endothelial cells is mediated through the lipid rafts-endocytic pathway via the dual specificity tyrosine phosphorylation-regulated kinase 3 (DYRK3). J. Biol. Chem. 286, 34761–34769. doi: 10.1074/jbc.M111.219378

PubMed Abstract | Crossref Full Text | Google Scholar

Huang, S. H., Wu, C. H., Chang, Y. C., Kwon-Chung, K. J., Brown, R. J., and Jong, A. (2012). Cryptococcus neoformans-derived microvesicles enhance the pathogenesis of fungal brain infection. PLoS One 7:e48570. doi: 10.1371/journal.pone.0048570

PubMed Abstract | Crossref Full Text | Google Scholar

Iyer, K. R., Revie, N. M., Fu, C., Robbins, N., and Cowen, L. E. (2021). Treatment strategies for cryptococcal infection: challenges, advances and future outlook. Nat. Rev. Microbiol. 19, 454–466. doi: 10.1038/s41579-021-00511-0

PubMed Abstract | Crossref Full Text | Google Scholar

Jang, E. H., Kim, J. S., Yu, S. R., and Bahn, Y. S. (2022). Unraveling capsule biosynthesis and signaling networks in Cryptococcus neoformans. Microbiolo. Spectr. 10:e0286622. doi: 10.1128/spectrum.02866-22

PubMed Abstract | Crossref Full Text | Google Scholar

Jarvis, J. N., Bicanic, T., Loyse, A., Namarika, D., Jackson, A., Nussbaum, J. C., et al. (2014). Determinants of mortality in a combined cohort of 501 patients with HIV-associated Cryptococcal meningitis: implications for improving outcomes. Clinic. Infect. Dis. 58, 736–745. doi: 10.1093/cid/cit794

PubMed Abstract | Crossref Full Text | Google Scholar

Jarvis, J. N., Casazza, J. P., Stone, H. H., Meintjes, G., Lawn, S. D., Levitz, S. M., et al. (2013). The phenotype of the Cryptococcus-specific CD4+ memory T-cell response is associated with disease severity and outcome in HIV-associated cryptococcal meningitis. J. Infect. Dis. 207, 1817–1828. doi: 10.1093/infdis/jit099

PubMed Abstract | Crossref Full Text | Google Scholar

Jarvis, J. N., Lawrence, D. S., Meya, D. B., Kagimu, E., Kasibante, J., Mpoza, E., et al. (2022). Single-dose liposomal amphotericin B treatment for Cryptococcal meningitis. N. Engl. J. Med. 386, 1109–1120. doi: 10.1056/NEJMoa2111904

Crossref Full Text | Google Scholar

Jarvis, J. N., Meintjes, G., Bicanic, T., Buffa, V., Hogan, L., Mo, S., et al. (2015). Cerebrospinal fluid cytokine profiles predict risk of early mortality and immune reconstitution inflammatory syndrome in HIV-associated cryptococcal meningitis. PLoS Pathog. 11:e1004754. doi: 10.1371/journal.ppat.1004754

PubMed Abstract | Crossref Full Text | Google Scholar

Jarvis, J. N., Meintjes, G., Rebe, K., Williams, G. N., Bicanic, T., Williams, A., et al. (2012). Adjunctive interferon-γ immunotherapy for the treatment of HIV-associated cryptococcal meningitis: a randomized controlled trial. AIDS (London, England) 26, 1105–1113. doi: 10.1097/QAD.0b013e3283536a93

PubMed Abstract | Crossref Full Text | Google Scholar

Johnston, S. A., and May, R. C. (2013). Cryptococcus interactions with macrophages: evasion and manipulation of the phagosome by a fungal pathogen. Cell. Microbiol. 15, 403–411. doi: 10.1111/cmi.12067

PubMed Abstract | Crossref Full Text | Google Scholar

Jong, A., Wu, C. H., Gonzales-Gomez, I., Kwon-Chung, K. J., Chang, Y. C., Tseng, H. K., et al. (2012). Hyaluronic acid receptor CD44 deficiency is associated with decreased Cryptococcus neoformans brain infection. J. Biol. Chem. 287, 15298–15306. doi: 10.1074/jbc.M112.353375

PubMed Abstract | Crossref Full Text | Google Scholar

Jong, A., Wu, C. H., Shackleford, G. M., Kwon-Chung, K. J., Chang, Y. C., Chen, H. M., et al. (2008). Involvement of human CD44 during Cryptococcus neoformans infection of brain microvascular endothelial cells. Cell. Microbiol. 10, 1313–1326. doi: 10.1111/j.1462-5822.2008.01128.x

PubMed Abstract | Crossref Full Text | Google Scholar

Jung, W. H., Saikia, S., Hu, G., Wang, J., Fung, C. K., D'Souza, C., et al. (2010). HapX positively and negatively regulates the transcriptional response to iron deprivation in Cryptococcus neoformans. PLoS Pathog. 6:e1001209. doi: 10.1371/journal.ppat.1001209

PubMed Abstract | Crossref Full Text | Google Scholar

Kaminsky, L. W., Al-Sadi, R., and Ma, T. Y. (2021). IL-1β and the intestinal epithelial tight junction barrier. Front. Immunol. 12:767456. doi: 10.3389/fimmu.2021.767456

PubMed Abstract | Crossref Full Text | Google Scholar

Kang, H. A. (2018). Emerging roles of inositol pyrophosphates as key modulators of fungal pathogenicity. Virulence 9, 563–565. doi: 10.1080/21505594.2017.1421832

PubMed Abstract | Crossref Full Text | Google Scholar

Korkmaz, F. T., and Traber, K. E. (2023). Innate immune responses in pneumonia. Pneumonia 15:4. doi: 10.1186/s41479-023-00106-8

PubMed Abstract | Crossref Full Text | Google Scholar

Kwon, H. S., and Koh, S. H. (2020). Neuroinflammation in neurodegenerative disorders: the roles of microglia and astrocytes. Transl. Neurodegenerat. 9:42. doi: 10.1186/s40035-020-00221-2

PubMed Abstract | Crossref Full Text | Google Scholar

La Hoz, R. M., and Pappas, P. G. (2013). Cryptococcal infections: changing epidemiology and implications for therapy. Drugs 73, 495–504. doi: 10.1007/s40265-013-0037-z

PubMed Abstract | Crossref Full Text | Google Scholar

Larsen, R. A., Pappas, P. G., Perfect, J., Aberg, J. A., Casadevall, A., Cloud, G. A., et al. (2005). Phase I evaluation of the safety and pharmacokinetics of murine-derived anticryptococcal antibody 18B7 in subjects with treated cryptococcal meningitis. Antimicrob. Agents Chemother. 49, 952–958. doi: 10.1128/AAC.49.3.952-958.2005

PubMed Abstract | Crossref Full Text | Google Scholar

Latunde-Dada, G. O. (2017). Ferroptosis: role of lipid peroxidation, iron and ferritinophagy. Biochim. Biophys. Acta 1861, 1893–1900. doi: 10.1016/j.bbagen.2017.05.019

PubMed Abstract | Crossref Full Text | Google Scholar

Lee, S. C., Dickson, D. W., Brosnan, C. F., and Casadevall, A. (1994). Human astrocytes inhibit Cryptococcus neoformans growth by a nitric oxide-mediated mechanism. J. Exp. Med. 180, 365–369. doi: 10.1084/jem.180.1.365

PubMed Abstract | Crossref Full Text | Google Scholar

Lee, K. T., Hong, J., Lee, D. G., Lee, M., Cha, S., Lim, Y. G., et al. (2020). Fungal kinases and transcription factors regulating brain infection in Cryptococcus neoformans. Nat. Commun. 11:1521. doi: 10.1038/s41467-020-15329-2

PubMed Abstract | Crossref Full Text | Google Scholar

Lee, D., Jang, E. H., Lee, M., Kim, S. W., Lee, Y., Lee, K. T., et al. (2019). Unraveling melanin biosynthesis and signaling networks in Cryptococcus neoformans. MBio 10, e02267–e02219. doi: 10.1128/mBio.02267-19

PubMed Abstract | Crossref Full Text | Google Scholar

Leopold Wager, C. M., Hole, C. R., Campuzano, A., Castro-Lopez, N., Cai, H., Caballero Van Dyke, M. C., et al. (2018). IFN-γ immune priming of macrophages in vivo induces prolonged STAT1 binding and protection against Cryptococcus neoformans. PLoS Pathog. 14:e1007358. doi: 10.1371/journal.ppat.1007358

PubMed Abstract | Crossref Full Text | Google Scholar

Li, Y., Huang, X., Chen, H., Qin, Y., Hou, J., Li, A., et al. (2020). The prevalence of cryptococcal antigen (CrAg) and benefits of pre-emptive antifungal treatment among HIV-infected persons with CD4+ T-cell counts < 200 cells/μL: evidence based on a meta-analysis. BMC Infect. Dis. 20:410. doi: 10.1186/s12879-020-05126-z

PubMed Abstract | Crossref Full Text | Google Scholar

Li, H. J., Li, D. Q., Zhang, Y. L., Ding, X. F., Gao, H. T., Zhu, Y., et al. (2023). Modulation of gut microbiota alleviates cerebral ischemia/reperfusion injury in rats by inhibiting M1 polarization of microglia. Front. Pharmacol. 14:1123387. doi: 10.3389/fphar.2023.1123387

PubMed Abstract | Crossref Full Text | Google Scholar

Li, C., Meng, Y., Li, H., Du, W., Gao, X., Suo, C., et al. (2023). Immunization with a heat-killed prm1 deletion strain protects the host from Cryptococcus neoformans infection. Emerg. Microbes Infect. 12:2244087. doi: 10.1080/22221751.2023.2244087

PubMed Abstract | Crossref Full Text | Google Scholar

Li, H., Zhang, L., Zhang, K., Huang, Y., Liu, Y., Lu, X., et al. (2022). Gut microbiota associated with cryptococcal meningitis and dysbiosis caused by anti-fungal treatment. Front. Microbiol. 13:1086239. doi: 10.3389/fmicb.2022.1086239

PubMed Abstract | Crossref Full Text | Google Scholar

Li, X., Mara, A. B., Musical, S. C., Kolling, F. W., Gibbings, S. L., Gerebtsov, N., et al. (2024). The hidden functional diversity of macrophages. Nat. Immunol. 25, 953–954. doi: 10.1038/s41590-024-01832-x

Crossref Full Text | Google Scholar

Liao, G., Wang, Y., Liu, T. B., Kohli, G., Qian, W., Shor, E., et al. (2018). Role of the inositol pyrophosphate multikinase Kcs1 in Cryptococcus inositol metabolism. Fungal Genetics Biol. 113, 42–51. doi: 10.1016/j.fgb.2018.01.006

PubMed Abstract | Crossref Full Text | Google Scholar

Liu, T. B., Kim, J. C., Wang, Y., Toffaletti, D. L., Eugenin, E., Perfect, J. R., et al. (2013). Brain inositol is a novel stimulator for promoting Cryptococcus penetration of the blood-brain barrier. PLoS Pathog. 9:e1003247. doi: 10.1371/journal.ppat.1003247

PubMed Abstract | Crossref Full Text | Google Scholar

Liu, X., Zhu, X., Peng, X., Tao, R., Wan, Z., Hui, J., et al. (2022). Lenalidomide potentially reduced the level of cell- associated HIV RNA and improved persistent inflammation in patients with HIV-associated cryptococcal meningitis a pilot study. Front. Cell. Infect. Microbiol. 12:954814. doi: 10.3389/fcimb.2022.954814

PubMed Abstract | Crossref Full Text | Google Scholar

Loh, J. S., Mak, W. Q., Tan, L. K. S., Ng, C. X., Chan, H. H., Yeow, S. H., et al. (2024). Microbiota-gut-brain axis and its therapeutic applications in neurodegenerative diseases. Signal Transduct. Target. Ther. 9:37. doi: 10.1038/s41392-024-01743-1

PubMed Abstract | Crossref Full Text | Google Scholar

Ma, J., Li, M., Bao, Y., Huang, W., He, X., Hong, Y., et al. (2024). Gut microbiota-brain bile acid axis orchestrates aging-related neuroinflammation and behavior impairment in mice. Pharmacol. Res. 208:107361. doi: 10.1016/j.phrs.2024.107361

PubMed Abstract | Crossref Full Text | Google Scholar

Ma, Y., Yang, L., Jiang, M., Zhao, X., and Xue, P. (2023). Connecting Cryptococcal meningitis and gut microbiome. Int. J. Mol. Sci. 24:515. doi: 10.3390/ijms241713515

PubMed Abstract | Crossref Full Text | Google Scholar

Meya, D. B., Okurut, S., Zziwa, G., Rolfes, M. A., Kelsey, M., Cose, S., et al. (2015). Cellular immune activation in cerebrospinal fluid from ugandans with cryptococcal meningitis and immune reconstitution inflammatory syndrome. J. Infect. Dis. 211, 1597–1606. doi: 10.1093/infdis/jiu664

PubMed Abstract | Crossref Full Text | Google Scholar

Mohamed, S. H., Nyazika, T. K., Ssebambulidde, K., Lionakis, M. S., Meya, D. B., and Drummond, R. A. (2022). Fungal CNS infections in Africa: the Neuroimmunology of Cryptococcal meningitis. Front. Immunol. 13:804674. doi: 10.3389/fimmu.2022.804674

PubMed Abstract | Crossref Full Text | Google Scholar

Mora, D. J., Fortunato, L. R., Andrade-Silva, L. E., Ferreira-Paim, K., Rocha, I. H., Vasconcelos, R. R., et al. (2015). Cytokine profiles at admission can be related to outcome in AIDS patients with cryptococcal meningitis. PLoS One 10:e0120297. doi: 10.1371/journal.pone.0120297

PubMed Abstract | Crossref Full Text | Google Scholar

Mukaremera, L., and Nielsen, K. (2017). Adaptive immunity to Cryptococcus neoformans infections. J. Fungi 3:64. doi: 10.3390/jof3040064

Crossref Full Text | Google Scholar

Mulak, A. (2021). Bile acids as key modulators of the brain-gut-microbiota Axis in Alzheimer's disease. J. Alzheimers Dis. 84, 461–477. doi: 10.3233/JAD-210608

PubMed Abstract | Crossref Full Text | Google Scholar

Nakajima, A., Nakatani, A., Hasegawa, S., Irie, J., Ozawa, K., Tsujimoto, G., et al. (2017). The short chain fatty acid receptor GPR43 regulates inflammatory signals in adipose tissue M2-type macrophages. PLoS One 12:e0179696. doi: 10.1371/journal.pone.0179696

PubMed Abstract | Crossref Full Text | Google Scholar

Neal, L. M., Xing, E., Xu, J., Kolbe, J. L., Osterholzer, J. J., Segal, B. M., et al. (2017). CD4+ T cells orchestrate lethal immune pathology despite fungal clearance during Cryptococcus neoformans meningoencephalitis. MBio 8, e01415–e01417. doi: 10.1128/mBio.01415-17

Crossref Full Text | Google Scholar

Nelson, B. N., Beakley, S. G., Posey, S., Conn, B., Maritz, E., Seshu, J., et al. (2021). Antifungal activity of dendritic cell lysosomal proteins against Cryptococcus neoformans. Sci. Rep. 11:13619. doi: 10.1038/s41598-021-92991-6

PubMed Abstract | Crossref Full Text | Google Scholar

Nielson, J. A., and Davis, J. M. (2023). Roles for microglia in Cryptococcal brain dissemination in the zebrafish larva. Microbiology spectrum 11:e0431522. doi: 10.1128/spectrum.04315-22

PubMed Abstract | Crossref Full Text | Google Scholar

Okafor, E. C., Mukaremera, L., Hullsiek, K. H., Engen, N., Tugume, L., Ssebambulidde, K., et al. (2024). CSF cytokines and chemokines involved in cytotoxic cell function and risk of acute 14-day mortality in persons with advanced HIV and cryptococcal meningitis. J. Infect. Dis., 521–531. doi: 10.1093/infdis/jiae421

Crossref Full Text | Google Scholar

Okurut, S., Boulware, D. R., Olobo, J., and Meya, D. B. (2020). Landmark clinical observations and immunopathogenesis pathways linked to HIV and Cryptococcus fatal central nervous system co-infection. Mycoses 63, 840–853. doi: 10.1111/myc.13122

PubMed Abstract | Crossref Full Text | Google Scholar

O'Meara, T. R., and Alspaugh, J. A. (2012). The Cryptococcus neoformans capsule: a sword and a shield. Clin. Microbiol. Rev. 25, 387–408. doi: 10.1128/CMR.00001-12

PubMed Abstract | Crossref Full Text | Google Scholar

Orihuela, R., McPherson, C. A., and Harry, G. J. (2016). Microglial M1/M2 polarization and metabolic states. Br. J. Pharmacol. 173, 649–665. doi: 10.1111/bph.13139

PubMed Abstract | Crossref Full Text | Google Scholar

Pacifici, N., Cruz-Acuña, M., Diener, A., Tu, A., Senthil, N., Han, H., et al. (2023). Vomocytosis of Cryptococcus neoformans cells from murine, bone marrow-derived dendritic cells. PLoS One 18:e0280692. doi: 10.1371/journal.pone.0280692

PubMed Abstract | Crossref Full Text | Google Scholar

Paemeleire, K. (2002). Calcium signaling in and between brain astrocytes and endothelial cells. Acta Neurol. Belg. 102, 137–140

PubMed Abstract | Google Scholar

Panackal, A. A., Wuest, S. C., Lin, Y. C., Wu, T., Zhang, N., Kosa, P., et al. (2015). Paradoxical immune responses in non-HIV Cryptococcal meningitis. PLoS Pathog. 11:e1004884. doi: 10.1371/journal.ppat.1004884

PubMed Abstract | Crossref Full Text | Google Scholar

Pappas, P. G. (2013). Cryptococcal infections in non-HIV-infected patients. Trans. Am. Clin. Climatol. Assoc. 124, 61–79.

Google Scholar

Pappas, P. G., Bustamante, B., Ticona, E., Hamill, R. J., Johnson, P. C., Reboli, A., et al. (2004). Recombinant interferon- gamma 1b as adjunctive therapy for AIDS-related acute cryptococcal meningitis. J. Infect. Dis. 189, 2185–2191.

Google Scholar

Paramsothy, S., Kamm, M. A., Kaakoush, N. O., Walsh, A. J., van den Bogaerde, J., Samuel, D., et al. (2017). Multidonor intensive faecal microbiota transplantation for active ulcerative colitis: a randomised placebo-controlled trial. Lancet 389, 1218–1228. doi: 10.1016/S0140-6736(17)30182-4

PubMed Abstract | Crossref Full Text | Google Scholar

Parker, A., Fonseca, S., and Carding, S. R. (2020). Gut microbes and metabolites as modulators of blood-brain barrier integrity and brain health. Gut Microbes 11, 135–157. doi: 10.1080/19490976.2019.1638722

PubMed Abstract | Crossref Full Text | Google Scholar

Pawlak, M., Ho, A. W., and Kuchroo, V. K. (2020). Cytokines and transcription factors in the differentiation of CD4(+) T helper cell subsets and induction of tissue inflammation and autoimmunity. Curr. Opin. Immunol. 67, 57–67. doi: 10.1016/j.coi.2020.09.001

PubMed Abstract | Crossref Full Text | Google Scholar

Pérez-Jacoiste Asín, M. A., Bisbal, O., Iribarren, J. A., Pérez-Rivilla, A., Mican, R., Dronda, F., et al. (2021). Cryptococcal infection in HIV-infected patients with CD4(+) T-cell counts under 100/μl diagnosed in a high-income country: a multicentre cohort study. Clin. Microbiol. Infect. 27, 1171.e1–1171.e7. doi: 10.1016/j.cmi.2020.09.053

PubMed Abstract | Crossref Full Text | Google Scholar

Perfect, J. R., Dismukes, W. E., Dromer, F., Goldman, D. L., Graybill, J. R., Hamill, R. J., et al. (2010). Clinical practice guidelines for the management of cryptococcal disease: 2010 update by the Infectious Diseases Society of America. Clin. Infect. Dis. 50, 291–322. doi: 10.1086/649858

PubMed Abstract | Crossref Full Text | Google Scholar

Pishesha, N., Harmand, T. J., and Ploegh, H. L. (2022). A guide to antigen processing and presentation. Nat. Rev. Immunol. 22, 751–764. doi: 10.1038/s41577-022-00707-2

PubMed Abstract | Crossref Full Text | Google Scholar

Porollo, A., Sesterhenn, T. M., Collins, M. S., Welge, J. A., and Cushion, M. T. (2014). Comparative genomics of pneumocystis species suggests the absence of genes for myo-inositol synthesis and reliance on inositol transport and metabolism. MBio 5:e01834.

Google Scholar

Proia, P., Schiera, G., Mineo, M., Ingrassia, A. M., Santoro, G., Savettieri, G., et al. (2008). Astrocytes shed extracellular vesicles that contain fibroblast growth factor-2 and vascular endothelial growth factor. Int. J. Mol. Med. 21, 63–67.

Google Scholar

Rajasingham, R., Govender, N. P., Jordan, A., Loyse, A., Shroufi, A., Denning, D. W., et al. (2022). The global burden of HIV-associated cryptococcal infection in adults in 2020: a modelling analysis. Lancet Infect. Dis. 22, 1748–1755. doi: 10.1016/S1473-3099(22)00499-6

PubMed Abstract | Crossref Full Text | Google Scholar

Rajasingham, R., Smith, R. M., Park, B. J., Jarvis, J. N., Govender, N. P., Chiller, T. M., et al. (2017). Global burden of disease of HIV-associated cryptococcal meningitis: an updated analysis. Lancet Infect. Dis. 17, 873–881. doi: 10.1016/S1473-3099(17)30243-8

PubMed Abstract | Crossref Full Text | Google Scholar

Rizzo, M. D., Henriquez, J. E., Blevins, L. K., Bach, A., Crawford, R. B., and Kaminski, N. E. (2020). Targeting cannabinoid receptor 2 on peripheral leukocytes to attenuate inflammatory mechanisms implicated in HIV-associated neurocognitive disorder. J. Neuroimmune Pharmacol. 15, 780–793. doi: 10.1007/s11481-020-09918-7

PubMed Abstract | Crossref Full Text | Google Scholar

Rochette, L., Dogon, G., Rigal, E., Zeller, M., Cottin, Y., and Vergely, C. (2022). Lipid peroxidation and iron metabolism: two corner stones in the homeostasis control of ferroptosis. Int. J. Mol. Sci. 24:449. doi: 10.3390/ijms24010449

PubMed Abstract | Crossref Full Text | Google Scholar

Saidykhan, L., Onyishi, C. U., and May, R. C. (2022). The Cryptococcus gattii species complex: unique pathogenic yeasts with understudied virulence mechanisms. PLoS Negl. Trop. Dis. 16:e0010916. doi: 10.1371/journal.pntd.0010916

PubMed Abstract | Crossref Full Text | Google Scholar

Saikachain, N., Sungkaworn, T., Muanprasat, C., and Asavapanumas, N. (2023). Neuroprotective effect of short-chain fatty acids against oxidative stress-induced SH-SY5Y injury via GPR43-dependent pathway. J. Neurochem. 166, 201–214. doi: 10.1111/jnc.15827

PubMed Abstract | Crossref Full Text | Google Scholar

Shourian, M., and Qureshi, S. T. (2019). Resistance and tolerance to Cryptococcal infection: An intricate balance that controls the development of disease. Front. Immunol. 10:66. doi: 10.3389/fimmu.2019.00066

PubMed Abstract | Crossref Full Text | Google Scholar

Shourian, M., Ralph, B., Angers, I., Sheppard, D. C., and Qureshi, S. T. (2017). Contribution of IL-1RI signaling to protection against Cryptococcus neoformans 52D in a mouse model of infection. Front. Immunol. 8:1987. doi: 10.3389/fimmu.2017.01987

PubMed Abstract | Crossref Full Text | Google Scholar

Spadari, C. C., Vila, T., Rozental, S., and Ishida, K. (2018). Miltefosine has a postantifungal effect and induces apoptosis in Cryptococcus yeasts. Antimicrob. Agents Chemother. 62:18. doi: 10.1128/AAC.00312-18

PubMed Abstract | Crossref Full Text | Google Scholar

Subramani, A., Griggs, P., Frantzen, N., Mendez, J., Tucker, J., Murriel, J., et al. (2020). Intracellular Cryptococcus neoformans disrupts the transcriptome profile of M1- and M2-polarized host macrophages. PLoS One 15:e0233818. doi: 10.1371/journal.pone.0233818

PubMed Abstract | Crossref Full Text | Google Scholar

Sun, L., Su, Y., Jiao, A., Wang, X., and Zhang, B. (2023). T cells in health and disease. Signal Transduct. Target. Ther. 8:235. doi: 10.1038/s41392-023-01471-y

PubMed Abstract | Crossref Full Text | Google Scholar

Sun, M., You, H., Hu, X., Luo, Y., Zhang, Z., Song, Y., et al. (2023). Microglia-astrocyte interaction in neural development and neural pathogenesis. Cells 12:942. doi: 10.3390/cells12151942

PubMed Abstract | Crossref Full Text | Google Scholar

Tao, R., Peng, X., Liu, X., Su, J., Lang, G., Huang, Y., et al. (2022). Lenalidomide improves cognitive function and reduces immune reconstitution inflammatory syndrome in HIV-1-related Cryptococcal meningitis. J. Inflamm. Res. 15, 2891–2899. doi: 10.2147/JIR.S353463

PubMed Abstract | Crossref Full Text | Google Scholar

Telzrow, C. L., Esher Righi, S., Cathey, J. M., Granek, J. A., and Alspaugh, J. A. (2023). Cryptococcus neoformans Mar1 function links mitochondrial metabolism, oxidative stress, and antifungal tolerance. Front. Physiol. 14:1150272. doi: 10.3389/fphys.2023.1150272

PubMed Abstract | Crossref Full Text | Google Scholar

Tsuji, A., Ikeda, Y., Yoshikawa, S., Taniguchi, K., Sawamura, H., Morikawa, S., et al. (2023). The tryptophan and kynurenine pathway involved in the development of immune-related diseases. Int. J. Mol. Sci. 24:742. doi: 10.3390/ijms24065742

PubMed Abstract | Crossref Full Text | Google Scholar

Tugume, L., Ssebambulidde, K., Kasibante, J., Ellis, J., Wake, R. M., Gakuru, J., et al. (2023). Cryptococcal meningitis. Nat. Rev. Dis. Primers 9:62. doi: 10.1038/s41572-023-00472-z

PubMed Abstract | Crossref Full Text | Google Scholar

Vainchtein, I. D., and Molofsky, A. V. (2020). Astrocytes and microglia: in sickness and in health. Trends Neurosci. 43, 144–154. doi: 10.1016/j.tins.2020.01.003

PubMed Abstract | Crossref Full Text | Google Scholar

Vidal, J. E., Toniolo, C., Paulino, A., Colombo, A., dos Anjos Martins, M., da Silva Meira, C., et al. (2016). Asymptomatic cryptococcal antigen prevalence detected by lateral flow assay in hospitalised HIV-infected patients in São Paulo, Brazil. Trop. Med. Int. Health 21, 1539–1544. doi: 10.1111/tmi.12790

PubMed Abstract | Crossref Full Text | Google Scholar

Wan, Z., Tao, R., Hui, J., Liu, X., Peng, X., Guo, Y., et al. (2023). Efficacy and safety of lenalidomide in HIV-associated cryptococcal meningitis patients with persistent intracranial inflammation: an open-label, single-arm, prospective interventional study. J. Neuroinflammation 20:38. doi: 10.1186/s12974-023-02717-w

PubMed Abstract | Crossref Full Text | Google Scholar

Wang, K., Espinosa, V., Wang, Y., Lemenze, A., Kumamoto, Y., Xue, C., et al. (2024). Innate cells and STAT1-dependent signals orchestrate vaccine-induced protection against invasive Cryptococcus infection. MBio 15:e0194424. doi: 10.1128/mbio.01944-24

PubMed Abstract | Crossref Full Text | Google Scholar

Wang, Y., Pawar, S., Dutta, O., Wang, K., Rivera, A., and Xue, C. (2022). Macrophage mediated immunomodulation during Cryptococcus pulmonary infection. Front. Cell. Infect. Microbiol. 12:859049. doi: 10.3389/fcimb.2022.859049

PubMed Abstract | Crossref Full Text | Google Scholar

Wang, J., Pratap, U. P., Lu, Y., Sareddy, G. R., Tekmal, R. R., Vadlamudi, R. K., et al. (2023). Development and characterization of inducible astrocyte-specific aromatase knockout mice. Biology 12:621. doi: 10.3390/biology12040621

PubMed Abstract | Crossref Full Text | Google Scholar

Wang, Y., Wear, M., Kohli, G., Vij, R., Giamberardino, C., Shah, A., et al. (2021). Inositol metabolism regulates capsule structure and virulence in the human pathogen Cryptococcus neoformans. MBio 12:e0279021.

Google Scholar

Williamson, P. R., Jarvis, J. N., Panackal, A. A., Fisher, M. C., Molloy, S. F., Loyse, A., et al. (2017). Cryptococcal meningitis: epidemiology, immunology, diagnosis and therapy. Nat. Rev. Neurol. 13, 13–24. doi: 10.1038/nrneurol.2016.167

PubMed Abstract | Crossref Full Text | Google Scholar

Woo, Y. H., and Martinez, L. R. (2021). Cryptococcus neoformans-astrocyte interactions: effect on fungal blood brain barrier disruption, brain invasion, and meningitis progression. Crit. Rev. Microbiol. 47, 206–223. doi: 10.1080/1040841X.2020.1869178

PubMed Abstract | Crossref Full Text | Google Scholar

Xie, Y., Hou, W., Song, X., Yu, Y., Huang, J., Sun, X., et al. (2016). Ferroptosis: process and function. Cell Death Differ. 23, 369–379. doi: 10.1038/cdd.2015.158

PubMed Abstract | Crossref Full Text | Google Scholar

Xu, Y., Jia, B., Li, J., Li, Q., and Luo, C. (2024). The interplay between ferroptosis and neuroinflammation in central neurological disorders. Antioxidants 13:395. doi: 10.3390/antiox13040395

PubMed Abstract | Crossref Full Text | Google Scholar

Xu, X., Lin, D., Tu, S., Gao, S., Shao, A., and Sheng, J. (2021). Is Ferroptosis a future direction in exploring Cryptococcal meningitis? Front. Immunol. 12:598601. doi: 10.3389/fimmu.2021.598601

PubMed Abstract | Crossref Full Text | Google Scholar

Xu, L., Xu, Y., Zheng, Y., Peng, X., Yang, Z., Cao, Q., et al. (2021). Differences in cytokine and chemokine profiles in cerebrospinal fluid caused by the etiology of cryptococcal meningitis and tuberculous meningitis in HIV patients. Clin. Exp. Immunol. 206, 82–90. doi: 10.1111/cei.13644

PubMed Abstract | Crossref Full Text | Google Scholar

Yang, C., Huang, Y., Zhou, Y., Zang, X., Deng, H., Liu, Y., et al. (2022). Cryptococcus escapes host immunity: what do we know? Front. Cell. Infect. Microbiol. 12:1041036. doi: 10.3389/fcimb.2022.1041036

PubMed Abstract | Crossref Full Text | Google Scholar

Ye, F., Li, L., Wang, J., and Yang, H. (2025). Advances in gut-lung axis research: clinical perspectives on pneumonia prevention and treatment. Front. Immunol. 16:1576141. doi: 10.3389/fimmu.2025.1576141

PubMed Abstract | Crossref Full Text | Google Scholar

Yu, C. H., Sephton-Clark, P., Tenor, J. L., Toffaletti, D. L., Giamberardino, C., Haverkamp, M., et al. (2021). Gene expression of diverse Cryptococcus isolates during infection of the human central nervous system. MBio 12:e0231321. doi: 10.1128/mBio.02313-21

PubMed Abstract | Crossref Full Text | Google Scholar

Zaragoza, O. (2019). Basic principles of the virulence of Cryptococcus. Virulence 10, 490–501. doi: 10.1080/21505594.2019.1614383

PubMed Abstract | Crossref Full Text | Google Scholar

Zha, S., Liu, H., Li, H., Li, H., Wong, K. L., and All, A. H. (2024). Functionalized nanomaterials capable of crossing the blood-brain barrier. ACS Nano 18, 1820–1845. doi: 10.1021/acsnano.3c10674

PubMed Abstract | Crossref Full Text | Google Scholar

Zhang, F., Li, Y., Shen, H., Tao, J., and Wang, J. (2022). Case report: Cryptococcal eosinophilic meningitis in a patient with Hodgkin lymphoma. Front. Neurol. 13:898525. doi: 10.3389/fneur.2022.898525

PubMed Abstract | Crossref Full Text | Google Scholar

Zhao, Y., and Lin, X. (2021). A PAS protein directs metabolic reprogramming during Cryptococcal adaptation to hypoxia. MBio 12:20. doi: 10.1128/mBio.03602-20

PubMed Abstract | Crossref Full Text | Google Scholar

Zhao, Y., Ye, L., Zhao, F., Zhang, L., Lu, Z., Chu, T., et al. (2023). Cryptococcus neoformans, a global threat to human health. Infect. Dis. Poverty 12:20. doi: 10.1186/s40249-023-01073-4

PubMed Abstract | Crossref Full Text | Google Scholar

Zhou, Y., Huang, Y., Yang, C., Zang, X., Deng, H., Liu, J., et al. (2024). The pathways and the mechanisms by which Cryptococcus enters the brain. Mycology 15, 345–359. doi: 10.1080/21501203.2023.2295409

PubMed Abstract | Crossref Full Text | Google Scholar

Keywords: cryptococcal meningitis (CM), immunity, metabolism, gut microbiota, gut-brain axis

Citation: Wen S, Liu M, Pan C, Zhang L, Yan R and Xu Z (2025) Research progress on immunometabolism and gut microbiota in cryptococcal meningitis: mechanisms and therapeutic implications. Front. Neurosci. 19:1622349. doi: 10.3389/fnins.2025.1622349

Received: 03 May 2025; Accepted: 30 June 2025;
Published: 16 July 2025.

Edited by:

A. Raquel Esteves, University of Coimbra, Portugal

Reviewed by:

Van Thi Ai Tran, Sungkyunkwan University, Republic of Korea
Ángel Radamés Rábago Monzón, Autonomous University of Sinaloa, Mexico

Copyright © 2025 Wen, Liu, Pan, Zhang, Yan and Xu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Zucai Xu, ZG9jeHpjQDEyNi5jb20=

These authors have contributed equally to this work

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.