There has been a sharp rise in the occurrence of Candida infections and associated mortality over the last few years, due to the growing body of immunocompromised population. Limited number of currently available antifungal agents, undesirable side effects and toxicity, as well as emergence of resistant strains pose a considerable clinical challenge for the treatment of candidiasis. Therefore, molecules that derived from natural sources exhibiting considerable antifungal properties are a promising source for the development of novel anti-candidal therapy. Phenolic compounds isolated from natural sources possess antifungal properties of interest. Particularly, phenolic acids have shown promising in vitro and in vivo activity against Candida species. However, studies on their mechanism of action alone or in synergism with known antifungals are still scarce. This review attempts to discuss the potential use, proposed mechanisms of action and limitations of the phenolic acids in anti-candidal therapy.

Candida albicans , a major opportunistic fungal pathogen, is frequently found together with Streptococcus mutans in dental biofilms associated with severe childhood caries (tooth decay), a prevalent pediatric oral disease. However, the impact of this cross-kingdom relationship on C. albicans remains largely uncharacterized. Here, we employed a novel quantitative proteomics approach in conjunction with transcriptomic profiling to unravel molecular pathways of C. albicans when cocultured with S. mutans in mixed biofilms.

It is well known that pregnancy is under the constant influence of hormonal, metabolic and immunological factors and this may impact the oral microbiota toward pregnancy gingivitis. However, it is still not clear how the oral microbial dysbiosis can modulate oral diseases as oral microbiome during pregnancy is very poorly characterized. In addition, the recent revelation that placental microbiome is akin to oral microbiome further potentiates the importance of oral dysbiosis in adverse pregnancy outcomes. Hence, leveraging on the 16S rRNA gene sequencing technology, we present a snapshot of the variations in the oral microbial composition with the progression of pregnancy and in the postpartum period and its association with pregnancy gingivitis. Despite the stability of oral microbial diversity during pregnancy and postpartum period, we observed that the microbiome makes a pathogenic shift during pregnancy and reverts back to a healthy microbiome during the postpartum period. Co-occurrence network analysis provided a mechanistic explanation of the pathogenicity of the microbiome during pregnancy and predicted taxa at hubs of interaction. Targeting the taxa which form the ecological guilds in the underlying microbiome would help to modulate the microbial pathogenicity during pregnancy, thereby alleviating risk for oral diseases and adverse pregnancy outcomes. Our study has also uncovered the possibility of novel species in subgingival plaque and saliva as the key players in the causation of pregnancy gingivitis. The keystone species hold the potential to open up avenues for designing microbiome modulation strategies to improve host health during pregnancy.

Streptococcus mutans is a biofilm-forming oral pathogen commonly associated with dental caries. Clinical studies have shown that S. mutans is often detected with Candida albicans in early childhood caries. Although the C. albicans presence has been shown to enhance bacterial accumulation in biofilms, the influence of S. mutans on fungal biology in this mixed-species relationship remains largely uncharacterized. Therefore, we aimed to investigate how the presence of S. mutans influences C. albicans biofilm development and coexistence. Using a newly established haploid biofilm model of C. albicans, we found that S. mutans augmented haploid C. albicans accumulation in mixed-species biofilms. Similarly, diploid C. albicans also showed enhanced biofilm formation in the presence of S. mutans. Surprisingly, the presence of S. mutans restored the biofilm-forming ability of C. albicans bcr1Δ mutant and bcr1Δ/Δ mutant, which is known to be severely defective in biofilm formation when grown as single species. Moreover, C. albicans hyphal growth factor HWP1 as well as ALS1 and ALS3, which are also involved in fungal biofilm formation, were upregulated in the presence of S. mutans. Subsequently, we found that S. mutans–derived glucosyltransferase B (GtfB) itself can promote C. albicans biofilm development. Interestingly, GtfB was able to increase the expression of HWP1, ALS1, and ALS3 genes in the C. albicans diploid wild-type SC5314 and bcr1Δ/Δ, leading to enhanced fungal biofilms. Hence, the present study demonstrates that a bacterial exoenzyme (GtfB) augments the C. albicans counterpart in mixed-species biofilms through a BCR1-independent mechanism. This novel finding may explain the mutualistic role of S. mutans and C. albicans in cariogenic biofilms.

The advent of omics technologies has greatly improved our understanding of microbial biology, particularly in the last two decades. The field of microbial biofilms is, however, relatively new, consolidated in the 1980s. The morphogenic switching by microbes from planktonic to biofilm phenotype confers numerous survival advantages such as resistance to desiccation, antibiotics, biocides, ultraviolet radiation, and host immune responses, thereby complicating treatment strategies for pathogenic microorganisms. Hence, understanding the mechanisms governing the biofilm phenotype can result in efficient treatment strategies directed specifically against molecular markers mediating this process. The application of omics technologies for studying microbial biofilms is relatively less explored and holds great promise in furthering our understanding of biofilm biology. In this review, we provide an overview of the application of omics tools such as transcriptomics, proteomics, and metabolomics as well as multi-omics approaches for studying microbial biofilms in the current literature. We also highlight how the use of omics tools directed at various stages of the biological information flow, from genes to metabolites, can be integrated via multi-omics platforms to provide a holistic view of biofilm biology. Following this, we propose a future artificial intelligence-based multi-omics platform that can predict the pathways associated with different biofilm phenotypes.