A CO 2 sensing module modulates β-1,3-glucan exposure in Candida albicans .
Gabriela M AvelarArnab PradhanQinxi MaEmer HickeyIan LeavesCorin LiddleAlejandra V Rodriguez RondonAnn-Kristin KauneSophie ShawCorinne MaufraisNatacha SertourJudith M BainDaniel E LarcombeLeandro J de AssisMihai G NeteaCarol A MunroDelma S ChildersLars P ErwigGordon D BrownNeil A R GowMarie-Elisabeth BougnouxChristophe D'EnfertAlistair J P BrownPublished in: mBio (2024)
Microbial species capable of co-existing with healthy individuals, such as the commensal fungus Candida albicans, exploit multifarious strategies to evade our immune defenses. These strategies include the masking of immunoinflammatory pathogen-associated molecular patterns (PAMPs) at their cell surface. We reported previously that C. albicans actively reduces the exposure of the proinflammatory PAMP, β-1,3-glucan, at its cell surface in response to host-related signals such as lactate and hypoxia. Here, we show that clinical isolates of C. albicans display phenotypic variability with respect to their lactate- and hypoxia-induced β-1,3-glucan masking. We have exploited this variability to identify responsive and non-responsive clinical isolates. We then performed RNA sequencing on these isolates to reveal genes whose expression patterns suggested potential association with lactate- or hypoxia-induced β-1,3-glucan masking. The deletion of two such genes attenuated masking: PHO84 and NCE103 . We examined NCE103 -related signaling further because NCE103 has been shown previously to encode carbonic anhydrase, which promotes adenylyl cyclase-protein kinase A (PKA) signaling at low CO 2 levels. We show that while CO 2 does not trigger β-1,3-glucan masking in C. albicans , the Sch9-Rca1-Nce103 signaling module strongly influences β-1,3-glucan exposure in response to hypoxia and lactate. In addition to identifying a new regulatory module that controls PAMP exposure in C. albicans, our data imply that this module is important for PKA signaling in response to environmental inputs other than CO 2 .IMPORTANCEOur innate immune defenses have evolved to protect us against microbial infection in part via receptor-mediated detection of "pathogen-associated molecular patterns" (PAMPs) expressed by invading microbes, which then triggers their immune clearance. Despite this surveillance, many microbial species are able to colonize healthy, immune-competent individuals, without causing infection. To do so, these microbes must evade immunity. The commensal fungus Candida albicans exploits a variety of strategies to evade immunity, one of which involves reducing the exposure of a proinflammatory PAMP (β-1,3-glucan) at its cell surface. Most of the β-1,3-glucan is located in the inner layer of the C. albicans cell wall, hidden by an outer layer of mannan fibrils. Nevertheless, some β-1,3-glucan can become exposed at the fungal cell surface. However, in response to certain specific host signals, such as lactate or hypoxia, C. albican s activates an anticipatory protective response that decreases β-1,3-glucan exposure, thereby reducing the susceptibility of the fungus to impending innate immune attack. Here, we exploited the natural phenotypic variability of C. albicans clinical isolates to identify strains that do not display the response to β-1,3-glucan masking signals observed for the reference isolate, SC5314. Then, using genome-wide transcriptional profiling, we compared these non-responsive isolates with responsive controls to identify genes potentially involved in β-1,3-glucan masking. Mutational analysis of these genes revealed that a sensing module that was previously associated with CO 2 sensing also modulates β-1,3-glucan exposure in response to hypoxia and lactate in this major fungal pathogen of humans.
Keyphrases
- candida albicans
- cell wall
- cell surface
- biofilm formation
- genome wide
- innate immune
- single cell
- gene expression
- endothelial cells
- dna methylation
- oxidative stress
- drug delivery
- cancer therapy
- poor prognosis
- risk assessment
- machine learning
- escherichia coli
- staphylococcus aureus
- cystic fibrosis
- long non coding rna
- bioinformatics analysis
- binding protein
- big data
- heat shock
- label free