Catch the wave: Metabolomic analyses in human pathogenic fungi

The Significance of Fungal Specialized Metabolites in One Health Perspectives

Among the emerging threats in global health, fungal pathogens stand out as some of the most important, causing over 1.6 million deaths annually and destroying a third of all food crops each year, exacerbating food insecurity and economic losses. Climate change further amplifies the threat by enabling pathogenic fungi to survive at mammalian temperatures, increasing risks of zoonotic transmission and antifungal resistance. In this context, interdisciplinary research, particularly the One Health approach, is crucial for understanding the evolution of fungal resistance and improving diagnostic and therapeutic tools. Drawing lessons from agriculture, where integrated pest management strategies successfully mitigate fungal threats, could offer new ways to tackle fungal infections in humans. Advanced metabolomics and diagnostics, including fungal metabolites as biomarkers, hold promise for early detection and personalized treatment. Collaborative efforts between medicine, veterinary science, and plant pathology are essential to develop new antifungal drugs and improve clinical management of fungal diseases, fostering a more resilient global health system.

Diagnosing invasive fungal infections in the laboratory today: It's all good news?

Despite the advances in medical science, invasive fungal infections (IFI) remain a diagnostic challenge. The increasing prevalence of IFI, driven by immunosuppressive therapies, advances in intensive care and emerging pathogens, underscores the need for early and accurate diagnosis. This review evaluates current laboratory methods for the diagnosis of IFI, highlighting their strengths and limitations. Conventional techniques, including fungal culture, direct microscopy, and histopathology, remain the gold standard for the diagnosis of proven IFIs. These methods allow pathogen isolation, species identification and antifungal susceptibility testing. However, these techniques have limitations in terms of sensitivity and turnaround times. Although microscopy is a rapid technique, its sensitivity and species discrimination profile are limited. Modern serological assays, such as β-d-glucan and galactomannan detection, have improved the diagnostic accuracy of probable IFI cases. Integration of these assays with clinical and radiological findings, enables earlier intervention, although this is accompanied by an increased risk of false positives and necessitates careful clinical correlation. Molecular diagnostics, particularly polymerase chain reaction (PCR), allow rapid, species-specific identification directly from clinical samples. The advent of MALDI-TOF mass spectrometry has further improved diagnostic efficiency, particularly for yeast identification, although challenges remain for filamentous fungi. Innovative techniques, such as metagenomic sequencing, lateral-flow assays, and loop-mediated isothermal amplification, offer the potential for rapid and precise detection, even in resource-limited settings. The combination of conventional and innovative methods provides a comprehensive diagnostic framework. The continuous refinement of these tools, in conjunction with multidisciplinary collaboration, is imperative to improve the early diagnostic and targeted treatment of patients with IFI.

Evaluation of the Effects of Epicoccum nigrum on the Olive Fungal Pathogens Verticillium dahliae and Colletotrichum acutatum by 1H NMR-Based Metabolic Profiling

Olive trees are a cornerstone of Mediterranean agriculture but face significant threats from diseases such as Verticillium wilt and olive anthracnose. These diseases, caused by Verticillium dahliae and Colletotrichum spp., respectively, result in significant economic losses and degrade olive oil quality. While traditional chemical treatments present environmental risk, sustainable alternatives such as biological control agents (BCAs) are gaining attention. Epicoccum nigrum, an antagonistic fungus, has shown potential as a BCA due to its production of antimicrobial secondary metabolites. This study aimed to observe whether E. nigrum has an antagonistic ability against V. dahliae and C. acutatum, and to elucidate the metabolic interactions between these fungi using NMR-based metabolomics. E. nigrum showed inhibitory effects on the growth of C. acutatum and V. dahlia of 44.97% and 38.73% respectively. Metabolomic profiling revealed distinct biochemical responses in E. nigrum, V. dahliae, and C. acutatum under mono- and dual-culture. Multivariate statistical analysis highlighted the metabolic shifts in mycelia and identified the primary metabolites, such as glutamine, 4-aminobutyrate, and phenylalanine that are involved in adaption for survival in stress conditions such as the presence of a competitor. The results could be important for a better understanding of the primary fungal metabolism, which is still poorly characterized. Further investigation is needed, but these results suggest that E. nigrum could serve as a BCA, offering a more sustainable approach to managing olive diseases.

Volatilome: Smells like microbial spirit

In recent years, the study of volatile compounds has sparked interest due to their implications in signaling and the enormous variety of bioactive properties attributed to them. Despite the absence of analysis methods standardization, there are a multitude of tools and databases that allow the identification and quantification of volatile compounds. These compounds are chemically heterogeneous and their diverse properties are exploited by various fields such as cosmetics, the food industry, agriculture and medicine, some of which will be discussed here. In virtue of volatile compounds being ubiquitous and fast chemical messengers, these molecules mediate a large number of interspecific and intraspecific interactions, which are key at an ecological level to maintaining the balance and correct functioning of ecosystems. This review briefly summarized the role of volatile compounds in inter- and intra-specific relationships as well as industrial applications associated with the use of these compounds that is emerging as a promising field of study.

Old and new strategies in therapy and diagnosis against fungal infections

Fungal infections represent a serious global health threat. The new emerging pathogens and the spread of different forms of resistance are now hardly challenging the tools available in therapy and diagnostics. With the commonly used diagnoses, fungal identification is often slow and inaccurate, and, on the other hand, some drugs currently used as treatments are significantly affected by the decrease in susceptibility. Herein, the antifungal arsenal is critically summarized. Besides describing the old approaches and their mechanisms, advantages, and limitations, the focus is dedicated to innovative strategies which are designed, identified, and developed to take advantage of the discrepancies between fungal and host cells. Relevant pathways and their role in survival and virulence are discussed as their suitability as sources of antifungal targets. In a similar way, molecules with antifungal activity are reported as potential agents/precursors of the next generation of antimycotics. Particular attention was devoted to biotechnological entities, to their novelty and reliability, to drug repurposing and restoration, and to combinatorial applications yielding significant improvements in efficacy. KEY POINTS: • New antifungal agents and targets are needed to limit fungal morbidity and mortality. • Therapeutics and diagnostics suffer of delays in innovation and lack of targets. • Biologics, drug repurposing and combinations are the future of antifungal treatments.

Establishment of a consensus protocol to explore the brain pathobiome in patients with mild cognitive impairment and Alzheimer's disease: Research outline and call for collaboration

Microbial infections of the brain can lead to dementia, and for many decades microbial infections have been implicated in Alzheimer's disease (AD) pathology. However, a causal role for infection in AD remains contentious, and the lack of standardized detection methodologies has led to inconsistent detection/identification of microbes in AD brains. There is a need for a consensus methodology; the Alzheimer's Pathobiome Initiative aims to perform comparative molecular analyses of microbes in post mortem brains versus cerebrospinal fluid, blood, olfactory neuroepithelium, oral/nasopharyngeal tissue, bronchoalveolar, urinary, and gut/stool samples. Diverse extraction methodologies, polymerase chain reaction and sequencing techniques, and bioinformatic tools will be evaluated, in addition to direct microbial culture and metabolomic techniques. The goal is to provide a roadmap for detecting infectious agents in patients with mild cognitive impairment or AD. Positive findings would then prompt tailoring of antimicrobial treatments that might attenuate or remit mounting clinical deficits in a subset of patients.

Mass spectrometry imaging for biosolids characterization to assess ecological or health risks before reuse

Biosolids are byproducts of wastewater treatment. With the increasing global population, the amounts of wastewater to be treated are expanding, along with the amounts of biosolids generated. The reuse of biosolids is now accepted for diversified applications in fields such as agriculture, engineering, agro-forestry. However, biosolids are known to be potential carriers of compounds that can be toxic to living beings or alter the environment. Therefore, biosolid reuse is subject to regulations, mandatory analyses are performed on heavy metals, persistent organic pollutants or pathogens. Conventional methods for the analysis of heavy metals and persistent organic pollutants are demanding, lengthy, and sometimes unsafe. Here, we propose mass spectrometry imaging as a faster and safer method using small amounts of material to monitor heavy metals and persistent organic pollutants in different types of biosolids, allowing for ecological and health risk assessment before reuse. Our methodology can be extended to other soil-like matrices.

Utilizing Amniotic Fluid Metabolomics to Monitor Fetal Well-Being: A Narrative Review of the Literature

Fetal and perinatal periods are critical phases for long-term development. Early diagnosis of maternal complications is challenging due to the great complexity of these conditions. In recent years, amniotic fluid has risen in a prominent position in the latest efforts to describe and characterize prenatal development. Amniotic fluid may provide real-time information on fetal development and metabolism throughout pregnancy as substances from the placenta, fetal skin, lungs, gastric fluid, and urine are transferred between the mother and the fetus. Applying metabolomics to monitor fetal well-being, in such a context, could help in the understanding, diagnosis, and treatment of these conditions and is a promising area of research. This review shines a spotlight on recent amniotic fluid metabolomics studies and their methods as an interesting tool for the assessment of many conditions and the identification of biomarkers. Platforms in use, such as proton nuclear magnetic resonance (¹H NMR) and ultra-high-performance liquid chromatography (UHPLC), have different merits, and a combinatorial approach could be valuable. Metabolomics may also be used in the quest for habitual diet-induced metabolic signals in amniotic fluid. Finally, analysis of amniotic fluid can provide information on exposure to exogenous substances by detecting the exact levels of metabolites carried to the fetus and associated metabolic effects.

Systematic Metabolic Profiling Identifies De Novo Sphingolipid Synthesis as Hypha Associated and Essential for Candida albicans Filamentation

The yeast-to-hypha transition is a key virulence attribute of the opportunistic human fungal pathogen Candida albicans, since it is closely tied to infection-associated processes such as tissue invasion and escape from phagocytes. While the nature of hypha-associated gene expression required for fungal virulence has been thoroughly investigated, potential morphotype-dependent activity of metabolic pathways remained unclear. Here, we combined global transcriptome and metabolome analyses for the wild-type SC5314 and the hypha-defective hgc1Δ and cph1Δefg1Δ strains under three hypha-inducing (human serum, N-acetylglucosamine, and alkaline pH) and two yeast-promoting conditions to identify metabolic adaptions that accompany the filamentation process. We identified morphotype-related activities of distinct pathways and a metabolic core signature of 26 metabolites with consistent depletion or enrichment during the yeast-to-hypha transition. Most strikingly, we found a hypha-associated activation of de novo sphingolipid biosynthesis, indicating a connection of this pathway and filamentous growth. Consequently, pharmacological inhibition of this partially fungus-specific pathway resulted in strongly impaired filamentation, verifying the necessity of de novo sphingolipid biosynthesis for proper hypha formation. IMPORTANCE The reversible switch of Candida albicans between unicellular yeast and multicellular hyphal growth is accompanied by a well-studied hypha-associated gene expression, encoding virulence factors like adhesins, toxins, or nutrient scavengers. The investigation of this gene expression consequently led to fundamental insights into the pathogenesis of this fungus. In this study, we applied this concept to hypha-associated metabolic adaptations and identified morphotype-dependent activities of distinct pathways and a stimulus-independent metabolic signature of hyphae. Most strikingly, we found the induction of de novo sphingolipid biosynthesis as hypha associated and essential for the filamentation of C. albicans. These findings verified the presence of morphotype-specific metabolic traits in the fungus, which appear connected to the fungal virulence. Furthermore, the here-provided comprehensive description of the fungal metabolome will help to foster future research and lead to a better understanding of fungal physiology.

Metabolic Plasticity of Candida albicans in Response to Different Environmental Conditions

The ubiquitous commensal Candida albicans, part of the human microbiota, is an opportunistic pathogen able to cause a wide range of diseases, from cutaneous mycoses to life-threatening infections in immunocompromised patients. Candida albicans adapts to different environments and survives long-time starvation. The ability to switch from yeast to hyphal morphology under specific environmental conditions is associated with its virulence. Using hydrogen nuclear magnetic resonance spectroscopy, we profiled the intracellular and extracellular metabolome of C. albicans kept in water, yeast extract–peptone–dextrose (YPD), and M199 media, at selected temperatures. Experiments were carried out in hypoxia to mimic a condition present in most colonized niches and fungal infection sites. Comparison of the intracellular metabolites measured in YPD and M199 at 37 °C highlighted differences in specific metabolic pathways: (i) alanine, aspartate, glutamate metabolism, (ii) arginine and proline metabolism, (iii) glycerolipid metabolism, attributable to the diverse composition of the media. Moreover, we hypothesized that the subtle differences in the M199 metabolome, observed at 30 °C and 37 °C, are suggestive of modifications propaedeutic to a subsequent transition from yeast to hyphal form. The analysis of the metabolites’ profiles of C. albicans allows envisaging a molecular model to better describe its ability to sense and adapt to environmental conditions.

Molecular investigations on Candida glabrata clinical isolates for pharmacological targeting

Prevalence of drug resistant C. glabrata strains in hospitalized immune-compromised patients with invasive fungal infections has increased at an unexpected pace. This has greatly pushed researchers in identification of mutations/variations in clinical isolates for better assessment of the prevailing drug resistance trends and also for updating of antifungal therapy regime. In the present investigation, the clinical isolates of C. glabrata were comprehensively characterized at a molecular level using metabolic profiling and transcriptional expression analysis approaches in combination with biochemical, morphological and chemical profiling methods. Biochemically, significant variations in azole susceptibility, surface hydrophobicity, and oxidative stress generation were observed among the isolates as compared to wild-type. The 1H NMR profiling identified 18 differential metabolites in clinical strains compared to wild-type and were classified into five categories, that include: sugars (7), amino acids and their derivatives (7), nitrogen bases (3) and coenzymes (1). Transcriptional analysis of selective metabolic and regulatory enzymes established that the major differences were found in cell membrane stress, carbohydrate metabolism, amino acid biosynthesis, ergosterol pathway and turnover of nitrogen bases. This detailed molecular level/metabolic fingerprint study is a useful approach for differentiating pathogenic/clinical isolates to that of wild-type. This study comprehensively delineated the differential cellular pathways at a molecular level that have been re-wired by the pathogenic clinical isolates for enhanced pathogenicity and virulence traits.

CRISP: a deep learning architecture for GC × GC-TOFMS contour ROI identification, simulation and analysis in imaging metabolomics

Two-dimensional gas chromatography-time-of-flight mass spectrometry (GC × GC-TOFMS) provides a large amount of molecular information from biological samples. However, the lack of a comprehensive compound library or customizable bioinformatics tool is currently a challenge in GC × GC-TOFMS data analysis. We present an open-source deep learning (DL) software called contour regions of interest (ROI) identification, simulation and untargeted metabolomics profiler (CRISP). CRISP integrates multiple customizable deep neural network architectures for assisting the semi-automated identification of ROIs, contour synthesis, resolution enhancement and classification of GC × GC-TOFMS-based contour images. The approach includes the novel aggregate feature representative contour (AFRC) construction and stacked ROIs. This generates an unbiased contour image dataset that enhances the contrasting characteristics between different test groups and can be suitable for small sample sizes. The utility of the generative models and the accuracy and efficacy of the platform were demonstrated using a dataset of GC × GC-TOFMS contour images from patients with late-stage diabetic nephropathy and healthy control groups. CRISP successfully constructed AFRC images and identified over five ROIs to create a deepstacked dataset. The high fidelity, 512 × 512-pixels generative model was trained as a generator with a Fréchet inception distance of <47.00. The trained classifier achieved an AUROC of >0.96 and a classification accuracy of >95.00% for datasets with and without column bleed. Overall, CRISP demonstrates good potential as a DL-based approach for the rapid analysis of 4-D GC × GC-TOFMS untargeted metabolite profiles by directly implementing contour images. CRISP is available at https://github.com/vivekmathema/GCxGC-CRISP.

Developing Functional Genomics Platforms for Fungi

Fungi are responsible for diseases that result in the deaths of over a million individuals each year and devastating crop infestations that threaten global food supplies. However, outside of a select few model organisms, the majority of fungal genes are uncharacterized. The roles of these genes in the biology of the organism, pathogenesis, and mediating interactions with the environment and other microbes are unknown. Historically, fungal gene characterization has primarily relied on classical genetic screens. However, advances in sequencing technology have enabled more rapid methods of gene functional characterization. Large-scale transcriptional profiling projects are one solution to generating hypotheses about fungal gene function. Together with other 'omics techniques and newer tools that enable massively parallel mutant screens, knowledge of fungal gene function will be substantially improved. Understanding the function of fungal genes will be instrumental in increasing global food security, protecting ecosystems, and improving health outcomes.

Tissue/Biofluid Specific Molecular Cartography of Leishmania donovani Infected BALB/c Mice: Deciphering Systemic Reprogramming

Pathophysiology of visceral leishmaniasis (VL) is not fully understood and it has been widely accepted that the parasitic components and host immune response both contribute to the perpetuation of the disease. Host alterations during leishmaniasis is a feebly touched area that needs to be explored more to better understand the VL prognosis and diagnosis, which are vital to reduce mortality and post-infection sequelae. To address this, we performed untargeted metabolomics of Leishmania donovani (Ld) infected, uninfected and treated BALB/c mice’s tissues and biofluids to elucidate the host metabolome changes using gas chromatography–mass spectrometry. Univariate and multivariate data treatments provided numerous significant differential hits in several tissues like the brain, liver, spleen and bone marrow. Differential modulations were also observed in serum, urine and fecal samples of Ld-infected mice, which could be further targeted for biomarker and diagnostic validations. Several metabolic pathways were found to be upregulated/downregulated in infected (TCA, glycolysis, fatty acids, purine and pyrimidine, etcetera) and treated (arginine, fumaric acid, orotic acid, choline succinate, etcetera) samples. Results also illustrated several metabolites with different pattern of modulations in control, infected and treated samples as well as in different tissues/biofluids; for e.g. glutamic acid identified in the serum samples of infected mice. Identified metabolites include a range of amino acids, saccharides, energy-related molecules, etcetera. Furthermore, potential biomarkers have been identified in various tissues—arginine and fumaric acid in brain, choline in liver, 9-(10) EpOME in spleen and bone marrow, N-acetyl putrescine in bone marrow, etcetera. Among biofluids, glutamic acid in serum, hydrazine and deoxyribose in urine and 3-Methyl-2-oxo pentanoic acid in feces are some of the potential biomarkers identified. These metabolites could be further looked into for their role in disease complexity or as a prognostic marker. The presented profiling approach allowed us to attain a metabolic portrait of the individual tissue/biofluid modulations during VL in the host and represent a valuable system readout for further studies. Our outcomes provide an improved understanding of perturbations of the host metabolome interface during VL, including identification of many possible potential diagnostic and therapeutic targets.

Aspergillus Metabolome Database for Mass Spectrometry Metabolomics

The Aspergillus Metabolome Database is a free online resource to perform metabolite annotation in mass spectrometry studies devoted to the genus Aspergillus. The database was created by retrieving and curating information on 2811 compounds present in 601 different species and subspecies of the genus Aspergillus. A total of 1514 scientific journals where these metabolites are mentioned were added as meta-information linked to their respective compounds in the database. A web service to query the database based on m/z (mass/charge ratio) searches was added to CEU Mass Mediator; these queries can be performed over the Aspergillus database only, or they can also include a user-selectable set of other general metabolomic databases. This functionality is offered via web applications and via RESTful services. Furthermore, the complete content of the database has been made available in .csv files and as a MySQL database to facilitate its integration into third-party tools. To the best of our knowledge, this is the first database and the first service specifically devoted to Aspergillus metabolite annotation based on m/z searches.

Metabolomic analysis of Trichophyton rubrum and Microsporum canis during keratin degradation

Keratin is important and needed for the growth of dermatophytes in the host tissue. In turn, the ability to invade keratinised tissues is defined as a pivotal virulence attribute of this group of medically important fungi. The host–dermatophyte interaction is accompanied by an adaptation of fungal metabolism that allows them to adhere to the host tissue as well as utilize the available nutrients necessary for their survival and growth. Dermatophyte infections pose a significant epidemiological and clinical problem. Trichophyton rubrum is the most common anthropophilic dermatophyte worldwide and its typical infection areas include skin of hands or feet and nail plate. In turn, Microsporum canis is a zoophilic pathogen, and mostly well known for ringworm in pets, it is also known to infect humans. The aim of the study was to compare the intracellular metabolite content in the T. rubrum and M. canis during keratin degradation using liquid chromatography system coupled with tandem mass spectrometer (LC-MS/MS). The metabolite “fingerprints” revealed compounds associated with amino acids metabolism, carbohydrate metabolism related to the glycolysis and the tricarboxylic acid cycle (TCA), as well as nucleotide and energy metabolism. The metabolites such as kynurenic acid, l-alanine and cysteine in case of T. rubrum as well as cysteine and riboflavin in case of M. canis were detected only during keratin degradation what may suggest that these compounds may play a key role in the interactions of T. rubrum and M. canis with the host tissue. The metabolomic results were completed by qPCR gene expression assay. Our findings suggest that metabolomic analysis of T. rubrum and M. canis growing in culture media that mimic the dermatophyte infection could allow the understanding of processes involved in the pathogenesis of dermatophytes.