Systems Biology Approaches for Host-Fungal Interactions: An Expanding Multi-Omics Frontier

Perspective on receptor-associated immune response to Candida albicans single and mixed infections: Implications for therapeutics in oropharyngeal candidiasis

Oropharyngeal candidiasis (OPC), commonly known as 'thrush', is an oral infection that usually dismantles oral mucosal integrity and malfunctions local innate and adaptive immunities in compromised individuals. The major pathogen responsible for the occurrence and progression of OPC is the dimorphic opportunistic commensal Candida albicans. However, the incidence induced by non-albicans Candida species including C. glabrata, C. tropicalis, C. dubliniensis, C. parapsilosis, and C. krusei are increasing in company with several oral bacteria, such as Streptococcus mutans, S. gordonii, S. epidermidis, and S. aureus. In this review, the microbiological and infection features of C. albicans and its co-contributors in the pathogenesis of OPC are outlined. Since the invasion and concomitant immune response lie firstly on the recognition of oral pathogens through diverse cellular surface receptors, we subsequently emphasize the roles of epidermal growth factor receptor, ephrin-type receptor 2, human epidermal growth factor receptor 2, and aryl hydrocarbon receptor located on oral epithelial cells to delineate the underlying mechanism by which host immune recognition to oral pathogens is mediated. Based on these observations, the therapeutic approaches to OPC comprising conventional and non-conventional antifungal agents, fungal vaccines, cytokine and antibody therapies, and antimicrobial peptide therapy are finally overviewed. In the face of newly emerging life-threatening microbes (C. auris and SARS-CoV-2), risks (biofilm formation and interconnected translocation among diverse organs), and complicated clinical settings (HIV and oropharyngeal cancer), the research on OPC is still a challenging task.

The Sordariomycetes: an expanding resource with Big Data for mining in evolutionary genomics and transcriptomics

Advances in genomics and transcriptomics accompanying the rapid accumulation of omics data have provided new tools that have transformed and expanded the traditional concepts of model fungi. Evolutionary genomics and transcriptomics have flourished with the use of classical and newer fungal models that facilitate the study of diverse topics encompassing fungal biology and development. Technological advances have also created the opportunity to obtain and mine large datasets. One such continuously growing dataset is that of the Sordariomycetes, which exhibit a richness of species, ecological diversity, economic importance, and a profound research history on amenable models. Currently, 3,574 species of this class have been sequenced, comprising nearly one-third of the available ascomycete genomes. Among these genomes, multiple representatives of the model genera Fusarium, Neurospora, and Trichoderma are present. In this review, we examine recently published studies and data on the Sordariomycetes that have contributed novel insights to the field of fungal evolution via integrative analyses of the genetic, pathogenic, and other biological characteristics of the fungi. Some of these studies applied ancestral state analysis of gene expression among divergent lineages to infer regulatory network models, identify key genetic elements in fungal sexual development, and investigate the regulation of conidial germination and secondary metabolism. Such multispecies investigations address challenges in the study of fungal evolutionary genomics derived from studies that are often based on limited model genomes and that primarily focus on the aspects of biology driven by knowledge drawn from a few model species. Rapidly accumulating information and expanding capabilities for systems biological analysis of Big Data are setting the stage for the expansion of the concept of model systems from unitary taxonomic species/genera to inclusive clusters of well-studied models that can facilitate both the in-depth study of specific lineages and also investigation of trait diversity across lineages. The Sordariomycetes class, in particular, offers abundant omics data and a large and active global research community. As such, the Sordariomycetes can form a core omics clade, providing a blueprint for the expansion of our knowledge of evolution at the genomic scale in the exciting era of Big Data and artificial intelligence, and serving as a reference for the future analysis of different taxonomic levels within the fungal kingdom.

OMICS and Other Advanced Technologies in Mycological Applications

Fungi play many roles in different ecosystems. The precise identification of fungi is important in different aspects. Historically, they were identified based on morphological characteristics, but technological advancements such as polymerase chain reaction (PCR) and DNA sequencing now enable more accurate identification and taxonomy, and higher-level classifications. However, some species, referred to as "dark taxa", lack distinct physical features that makes their identification challenging. High-throughput sequencing and metagenomics of environmental samples provide a solution to identifying new lineages of fungi. This paper discusses different approaches to taxonomy, including PCR amplification and sequencing of rDNA, multi-loci phylogenetic analyses, and the importance of various omics (large-scale molecular) techniques for understanding fungal applications. The use of proteomics, transcriptomics, metatranscriptomics, metabolomics, and interactomics provides a comprehensive understanding of fungi. These advanced technologies are critical for expanding the knowledge of the Kingdom of Fungi, including its impact on food safety and security, edible mushrooms foodomics, fungal secondary metabolites, mycotoxin-producing fungi, and biomedical and therapeutic applications, including antifungal drugs and drug resistance, and fungal omics data for novel drug development. The paper also highlights the importance of exploring fungi from extreme environments and understudied areas to identify novel lineages in the fungal dark taxa.

Nicotine metabolism pathway in bacteria: mechanism, modification, and application

Nicotine is a harmful pollutant mainly from the waste of tobacco factories. It is necessary to remove nicotine via high efficient strategies such as bioremediation. So far, an increasing number of nicotine degrading strains have been isolated. However, their degrading efficiency and tolerance to high content nicotine is still not high enough for application in real environment. Thus, the modification of nicotine metabolism pathway is obligated and requires comprehensive molecular insights into whole cell metabolism of nicotine degrading strains. Obviously, the development of multi-omics technology has accelerated the mechanism study on microbial degradation of nicotine and supplied more novel strategy of strains modification. So far, three pathways of nicotine degradation, pyridine pathway, pyrrolidine pathway, and the variant of pyridine and pyrrolidine pathway (VPP pathway), have been clearly identified in bacteria. Muti-omics analysis further revealed specific genome architecture, regulation mechanism, and specific genes or enzymes of three pathways, in different strains. Especially, muti-omics analysis revealed that functional modules coexisted in different genome loci and played additional roles on enhanced degradation efficiency in bacteria. Based on the above discovery, genomic editing strategy becomes more feasible to greatly improve bacterial degrading efficiency of nicotine.

Aspergillus-related lung disease in people with cystic fibrosis: can imaging help us to diagnose disease?

In people with cystic fibrosis (PwCF), viscous sputum and dysfunction of the mucociliary escalator leads to early and chronic infections. The prevalence of Aspergillus fumigatus in sputum is high in PwCF and the contribution of A. fumigatus to the progression of structural lung disease has been reported. However, overall, relatively little is known about the contribution of A. fumigatus to CF lung disease. More knowledge is needed to aid clinical decisions on whether to start antifungal treatment. In this review, we give an overview of A. fumigatus colonisation and infection in PwCF and the different types of pulmonary disease caused by it. Furthermore, we discuss the current evidence for structural lung damage associated with A. fumigatus in PwCF on chest computed tomography and magnetic resonance imaging. We conclude that radiological outcomes to identify disease caused by A. fumigatus can be important for clinical studies and management.

Top Trends in Multiomics Research: Evaluation of 52 Published Studies and New Ways of Thinking Terminology and Visual Displays

Multiomics study designs have significantly increased understanding of complex biological systems. The multiomics literature is rapidly expanding and so is their heterogeneity. However, the intricacy and fragmentation of omics data are impeding further research. To examine current trends in multiomics field, we reviewed 52 articles from PubMed and Web of Science, which used an integrated omics approach, published between March 2006 and January 2021. From studies, data regarding investigated loci, species, omics type, and phenotype were extracted, curated, and streamlined according to standardized terminology, and summarized in a previously developed graphical summary. Evaluated studies included 21 omics types or applications of omics technology such as genomics, transcriptomics, metabolomics, epigenomics, environmental omics, and pharmacogenomics, species of various phyla including human, mouse, Arabidopsis thaliana, Saccharomyces cerevisiae, and various phenotypes, including cancer and COVID-19. In the analyzed studies, diverse methods, protocols, results, and terminology were used and accordingly, assessment of the studies was challenging. Adoption of standardized multiomics data presentation in the future will further buttress standardization of terminology and reporting of results in systems science. This shall catalyze, we suggest, innovation in both science communication and laboratory medicine by making available scientific knowledge that is easier to grasp, share, and harness toward medical breakthroughs.

Massive Open Online Course (MOOCs) Acceptance: The Role of Task-Technology Fit (TTF) for Higher Education Sustainability

The aim of the present study was to narrow the gap in the literature on the adoption of massive open online courses (MOOCs) and the role of task-technology fit (TTF), which influences student satisfaction, academic performance, and the long-term viability (sustainability) of MOOCs in higher education. While researchers have examined MOOC acceptance in a variety of contexts, the role of TTF as a mediating variable in evaluating education sustainability has not been explored using the technology acceptance model (TAM). As a result, the aim of this study was to create a new paradigm by combining two theories: TTF and TAM. Therefore, this study surveyed 277 university students from public universities using the structural equation modeling (SEM) approach to learn about their perceptions toward MOOCs as a method of achieving higher education sustainability. According to the findings, perceived ease of use had a positive impact on perceived enjoyment, perceived usefulness, and social influence, which in turn had a positive impact on task-technology fit and MOOCs use as a method of sustainability in higher education. Task-technology fit also had a positive impact on MOOC use as a method of sustainability. Finally, the role of task-technology fit and MOOCs in educational sustainability had a positive effect on students satisfaction and academic performance. As a result, the use of MOOCs in learning processes should be encouraged in higher education institutions to ensure their long-term viability (sustainability).

Integration strategies of multi-omics data for machine learning analysis

Increased availability of high-throughput technologies has generated an ever-growing number of omics data that seek to portray many different but complementary biological layers including genomics, epigenomics, transcriptomics, proteomics, and metabolomics. New insight from these data have been obtained by machine learning algorithms that have produced diagnostic and classification biomarkers. Most biomarkers obtained to date however only include one omic measurement at a time and thus do not take full advantage of recent multi-omics experiments that now capture the entire complexity of biological systems.

Multi-omics data integration strategies are needed to combine the complementary knowledge brought by each omics layer. We have summarized the most recent data integration methods/ frameworks into five different integration strategies: early, mixed, intermediate, late and hierarchical. In this mini-review, we focus on challenges and existing multi-omics integration strategies by paying special attention to machine learning applications.

Omics Approaches to Study Formation and Function of Human Placental Syncytiotrophoblast

Proper development of the placenta is vital for pregnancy success. The placenta regulates exchange of nutrients and gases between maternal and fetal blood and produces hormones essential to maintain pregnancy. The placental cell lineage primarily responsible for performing these functions is a multinucleated entity called syncytiotrophoblast. Syncytiotrophoblast is continuously replenished throughout pregnancy by fusion of underlying progenitor cells called cytotrophoblasts. Dysregulated syncytiotrophoblast formation disrupts the integrity of the placental exchange surface, which can be detrimental to maternal and fetal health. Moreover, various factors produced by syncytiotrophoblast enter into maternal circulation, where they profoundly impact maternal physiology and are promising diagnostic indicators of pregnancy health. Despite the multifunctional importance of syncytiotrophoblast for pregnancy success, there is still much to learn about how its formation is regulated in normal and diseased states. ‘Omics’ approaches are gaining traction in many fields to provide a more holistic perspective of cell, tissue, and organ function. Herein, we review human syncytiotrophoblast development and current model systems used for its study, discuss how ‘omics’ strategies have been used to provide multidimensional insights into its formation and function, and highlight limitations of current platforms as well as consider future avenues for exploration.

E-Learning Acceptance: The Role of Task–Technology Fit as Sustainability in Higher Education

The aim of this study was to fill the gap in the literature on e-learning acceptance and its role in the sustainability of learning and the role of task-technology fit (TTF), which influences student satisfaction and academic performance. While researchers have examined e-learning acceptance in a variety of contexts, the role of TTF as a mediating variable in measuring education sustainability has not been explored using the technology acceptance model (TAM). As a result, the goal of this study was to develop a new paradigm by combining two theories: TFF and the TAM. In total, 432 students and researchers from public universities participated in this study. We surveyed students using the structural equation modelling (SEM) approach to learn about their expectations with regard to e-learning adoption. According to the findings, perceived ease of use has a positive impact on perceived enjoyment and usefulness, which in turn has a positive impact on task–technology fit and e-learning use in higher education, resulting in a positive impact on student satisfaction and academic performance as well as sustainability. Finally, the role of task-technology fit and e-learning usage in education sustainability had a positive effect on student satisfaction and learning performance. As a result, the use of e-learning in learning processes should be encouraged as a long-term strategy in higher education institutions.

The impact of the Fungus-Host-Microbiota interplay upon Candida albicans infections: current knowledge and new perspectives

Candida albicans is a major fungal pathogen of humans. It exists as a commensal in the oral cavity, gut or genital tract of most individuals, constrained by the local microbiota, epithelial barriers and immune defences. Their perturbation can lead to fungal outgrowth and the development of mucosal infections such as oropharyngeal or vulvovaginal candidiasis, and patients with compromised immunity are susceptible to life-threatening systemic infections. The importance of the interplay between fungus, host and microbiota in driving the transition from C. albicans commensalism to pathogenicity is widely appreciated. However, the complexity of these interactions, and the significant impact of fungal, host and microbiota variability upon disease severity and outcome, are less well understood. Therefore, we summarise the features of the fungus that promote infection, and how genetic variation between clinical isolates influences pathogenicity. We discuss antifungal immunity, how this differs between mucosae, and how individual variation influences a person's susceptibility to infection. Also, we describe factors that influence the composition of gut, oral and vaginal microbiotas, and how these affect fungal colonisation and antifungal immunity. We argue that a detailed understanding of these variables, which underlie fungal-host-microbiota interactions, will present opportunities for directed antifungal therapies that benefit vulnerable patients.

Next-generation technologies for studying host-pathogen interactions: a focus on dual transcriptomics, CRISPR/Cas9 screening and organs-on-chips

Pathogens constantly interact with their hosts and the environment, and therefore have evolved unique virulence mechanisms to target and breach host defense barriers and manipulate host immune response to establish an infection. Advances in technologies that allow genome mining, gene editing such as CRISPR/Cas9, genomic, epigenomic and transcriptomic studies such as dual RNA-seq, coupled with bioinformatics, have accelerated the field of host-pathogen interactions within a broad range of infection models. Underpinning of the molecular changes that accompany invasion of eukaryotic cells with pathogenic microorganisms at the intersection of host, pathogen and their local environment has provided a better understanding of infectious disease mechanisms and antimicrobial strategies. The recent evolution of physiologically relevant three-dimensional (3-D) tissue/organ models and microfluidic organ-on-chip devices also provided a window to a more predictive framework of infectious disease processes. These approaches combined hold the potential to highly impact discovery of novel drug targets and vaccine candidates of the future. Here, we review three of the available and emerging technologies-dual RNA-seq, CRISPR/Cas9 screening and organs-on-chips, applicable to the high throughput study and deciphering of interaction networks between pathogens and their hosts that are critical for the development of novel therapeutics.

Recent trends in molecular diagnostics of yeast infections: from PCR to NGS

The incidence of opportunistic yeast infections in humans has been increasing over recent years. These infections are difficult to treat and diagnose, in part due to the large number and broad diversity of species that can underlie the infection. In addition, resistance to one or several antifungal drugs in infecting strains is increasingly being reported, severely limiting therapeutic options and showcasing the need for rapid detection of the infecting agent and its drug susceptibility profile. Current methods for species and resistance identification lack satisfactory sensitivity and specificity, and often require prior culturing of the infecting agent, which delays diagnosis. Recently developed high-throughput technologies such as next generation sequencing or proteomics are opening completely new avenues for more sensitive, accurate and fast diagnosis of yeast pathogens. These approaches are the focus of intensive research, but translation into the clinics requires overcoming important challenges. In this review, we provide an overview of existing and recently emerged approaches that can be used in the identification of yeast pathogens and their drug resistance profiles. Throughout the text we highlight the advantages and disadvantages of each methodology and discuss the most promising developments in their path from bench to bedside.

Methodologies and Applications of Proteomics for Study of Yeast Strains: An Update

Yeasts are one of the mostly used microorganisms as models in several studies. A wide range of applications in different processes can be attributed to their intrinsic characteristics. They are eukaryotes and therefore valuable expression hosts that require elaborate post-translational modifications. Their arsenal of proteins has become a valuable biochemical tool for the catalysis of several reactions of great value to the food (beverages), pharmaceutical and energy industries. Currently, the main challenge in systemic yeast biology is the understanding of the expression, function and regulation of the protein pool encoded by such microorganisms. In this review, we will provide an overview of the proteomic methodologies used in the analysis of yeasts. This research focuses on the advantages and improvements in their most recent applications with an understanding of the functionality of the proteins of these microorganisms, as well as an update of the advances of methodologies employed in mass spectrometry.

Dissecting Candida Pathobiology: Post-Translational Modifications on the Candida tropicalis Proteome

Candida tropicalis belongs to the non-albicans group of Candida, and causes epidermal, mucosal, or systemic candidiasis in immunocompromised individuals. Although the prevalence of candidiasis has increased worldwide and non-albicans Candida (NAC) are becoming more significant, there are very few studies that focus on the NAC biology. Proteins and their post-translational modifications (PTMs) are an integral aspect in the pathobiology of such medically important fungi. Previously, we had reported the largest proteomic catalog of C. tropicalis. Notably, PTMs can be identified from proteomics data without a priori enrichment for a particular PTM, thus allowing broad-scale omics analyses. In this study, we developed the "PTM-Pro," a graphical user interface-based tool for identification and summary of high-confidence PTM sites based on statistical threshold of users' choice. We mined available proteomic data of C. tropicalis, and using PTM-Pro identified nearly 600 high-confidence PTM sites. The PTMs identified include phosphorylation of serine, threonine, and tyrosine; acetylation, crotonylation, methylation, and succinylation of lysine. These PTMs reside on biologically significant molecules, including histones, enzymes, and transcription factors. To our knowledge, this is the first report of PTMs in C. tropicalis and lays a foundation for future investigations of C. tropicalis PTMs. In addition, the PTM-Pro offers a graphical user interface tool for research on PTM sites in the field of proteomics.

Transcriptomic and proteomic host response to Aspergillus fumigatus conidia in an air-liquid interface model of human bronchial epithelium

Aspergillus fumigatus (A. fumigatus) is a wide-spread fungus that is a potent allergen in hypersensitive individuals but also an opportunistic pathogen in immunocompromised patients. It reproduces asexually by releasing airborne conidiospores (conidia). Upon inhalation, fungal conidia are capable of reaching the airway epithelial cells (AECs) in bronchial and alveolar tissues. Previous studies have predominantly used submerged monolayer cultures for studying this host-pathogen interaction; however, these cultures do not recapitulate the mucocililary differentiation phenotype of the in vivo epithelium in the respiratory tract. Thus, the aim of this study was to use well-differentiated primary human bronchial epithelial cells (HBECs) grown at the air-liquid interface (ALI) to determine their transcriptomic and proteomic responses following interaction with A. fumigatus conidia. We visualized conidial interaction with HBECs using confocal laser scanning microscopy (CLSM), and applied NanoString nCounter and shotgun proteomics to assess gene expression changes in the human cells upon interaction with A. fumigatus conidia. Western blot analysis was used to assess the expression of top three differentially expressed proteins, CALR, SET and NUCB2. CLSM showed that, unlike submerged monolayer cultures, well-differentiated ALI cultures of primary HBECs were estimated to internalize less than 1% of bound conidia. Nevertheless, transcriptomic and proteomic analyses revealed numerous differentially expressed host genes; these were enriched for pathways including apoptosis/autophagy, translation, unfolded protein response and cell cycle (up-regulated); complement and coagulation pathways, iron homeostasis, nonsense mediated decay and rRNA binding (down-regulated). CALR and SET were confirmed to be up-regulated in ALI cultures of primary HBECs upon exposure to A. fumigatus via western blot analysis. Therefore, using transcriptomics and proteomics approaches, ALI models recapitulating the bronchial epithelial barrier in the conductive zone of the respiratory tract can provide novel insights to the molecular response of bronchial epithelial cells upon exposure to A. fumigatus conidia.

"Omics" of Food-Borne Gastroenteritis: Global Proteomic and Mutagenic Analysis of Salmonella enterica Serovar Enteritidis

Salmonella Enteritidis causes food-borne gastroenteritis by the two type three secretion systems (TTSS). TTSS-1 mediates invasion through intestinal lining, and TTSS-2 facilitates phagocytic survival. The pathogens' ability to infect effectively under TTSS-1-deficient background in host's phagocytes is poorly understood. Therefore, pathobiological understanding of TTSS-1-defective nontyphoidal Salmonellosis is highly important. We performed a comparative global proteomic analysis of the isogenic TTSS-1 mutant of Salmonella Enteritidis (M1511) and its wild-type isolate P125109. Our results showed 43 proteins were differentially expressed. Functional annotation further revealed that differentially expressed proteins belong to pathogenesis, tRNA and ncRNA metabolic processes. Three proteins, tryptophan subunit alpha chain, citrate lyase subunit alpha, and hypothetical protein 3202, were selected for in vitro analysis based on their functional annotations. Deletion mutants generated for the above proteins in the M1511 strain showed reduced intracellular survival inside macrophages in vitro. In sum, this study provides mass spectrometry-based evidence for seven hypothetical proteins, which will be subject of future investigations. Our study identifies proteins influencing virulence of Salmonella in the host. The study complements and further strengthens previously published research on proteins involved in enteropathogenesis of Salmonella and extends their role in noninvasive Salmonellosis.

Transcriptomic response of Debaryomyces hansenii during mixed culture in a liquid model cheese medium with Yarrowia lipolytica

Yeasts play a crucial role in cheese ripening. They contribute to the curd deacidification, the establishment of acid-sensitive bacterial communities, and flavour compounds production via proteolysis and catabolism of amino acids (AA). Negative yeast-yeast interaction was observed between the yeast Yarrowia lipolytica 1E07 (YL1E07) and the yeast Debaryomyces hansenii 1L25 (DH1L25) in a model cheese but need elucidation. YL1E07 and DH1L25 were cultivated in mono and co-cultures in a liquid synthetic medium (SM) mimicking the cheese environment and the growth inhibition of DH1L25 in the presence of YL1E07 was reproduced. We carried out microbiological, biochemical (lactose, lactate, AA consumption and ammonia production) and transcriptomic analyses by microarray technology to highlight the interaction mechanisms. We showed that the DH1L25 growth inhibition in the presence of YL1E07 was neither due to the ammonia production nor to the nutritional competition for the medium carbon sources between the two yeasts. The transcriptomic study was the key toward the comprehension of yeast-yeast interaction, and revealed that the inhibition of DH1L25 in co-culture is due to a decrease of the mitochondrial respiratory chain functioning.

Secretome profiling reveals temperature-dependent growth of Aspergillus fumigatus

Aspergillus fumigatus is a ubiquitous opportunistic fungus. In this study, systematic analyses were carried out to study the temperature adaptability of A. fumigatus. A total of 241 glycoside hydrolases and 69 proteases in the secretome revealed the strong capability of A. fumigatus to degrade plant biomass and protein substrates. In total, 129 pathogenesis-related proteins detected in the secretome were strongly correlated with glycoside hydrolases and proteases. The variety and abundance of proteins remained at temperatures of 34°C-45°C. The percentage of endo-1,4-xylanase increased when the temperature was lowered to 20°C, while the percentage of cellobiohydrolase increased as temperature was increased, suggesting that the strain obtains carbon mainly by degrading xylan and cellulose, and the main types of proteases in the secretome were aminopeptidases and carboxypeptidases. Only half of the proteins were retained and their abundance declined to 9.7% at 55°C. The activities of the remaining β-glycosidases and proteases were merely 35% and 24%, respectively, when the secretome was treated at 60°C for 2 h. Therefore, temperatures >60°C restrict the growth of A. fumigatus.

Eigenvector metabolite analysis reveals dietary effects on the association among metabolite correlation patterns, gene expression, and phenotypes

INTRODUCTION

'Multi-omics' datasets obtained from an organism of interest reared under different environmental treatments are increasingly common. Identifying the links among metabolites and transcripts can help to elucidate our understanding of the impact of environment at different levels within the organism. However, many methods for characterizing physiological connections cannot address unidentified metabolites.

OBJECTIVES

Here, we use Eigenvector Metabolite Analysis (EvMA) to examine links between metabolomic, transcriptomic, and phenotypic variation data and to assess the impact of environmental factors on these associations. Unlike other methods, EvMA can be used to analyze datasets that include unidentified metabolites and unannotated transcripts.

METHODS

To demonstrate the utility of EvMA, we analyzed metabolomic, transcriptomic, and phenotypic datasets produced from 20 Drosophila melanogaster genotypes reared on four dietary treatments. We used a hierarchical distance-based method to cluster the metabolites. The links between metabolite clusters, gene expression, and overt phenotypes were characterized using the eigenmetabolite (first principal component) of each cluster.

RESULTS

EvMA recovered chemically related groups of metabolites within the clusters. Using the eigenmetabolite, we identified genes and phenotypes that significantly correlated with each cluster. EvMA identifies new connections between the phenotypes, metabolites, and gene transcripts. Conclusion EvMA provides a simple method to identify correlations between metabolites, gene expression, and phenotypes, which can allow us to partition multivariate datasets into meaningful biological modules and identify under-studied metabolites and unannotated gene transcripts that may be central to important biological processes. This can be used to inform our understanding of the effect of environmental mechanisms underlying physiological states of interest.

Dissecting Candida albicans Infection from the Perspective of C. albicans Virulence and Omics Approaches on Host-Pathogen Interaction: A Review

Candida bloodstream infections remain the most frequent life-threatening fungal disease, with Candida albicans accounting for 70% to 80% of the Candida isolates recovered from infected patients. In nature, Candida species are part of the normal commensal flora in mammalian hosts. However, they can transform into pathogens once the host immune system is weakened or breached. More recently, mortality attributed to Candida infections has continued to increase due to both inherent and acquired drug resistance in Candida, the inefficacy of the available antifungal drugs, tedious diagnostic procedures, and a rising number of immunocompromised patients. Adoption of animal models, viz. minihosts, mice, and zebrafish, has brought us closer to unraveling the pathogenesis and complexity of Candida infection in human hosts, leading towards the discovery of biomarkers and identification of potential therapeutic agents. In addition, the advancement of omics technologies offers a holistic view of the Candida-host interaction in a non-targeted and non-biased manner. Hence, in this review, we seek to summarize past and present milestone findings on C. albicans virulence, adoption of animal models in the study of C. albicans infection, and the application of omics technologies in the study of Candida–host interaction. A profound understanding of the interaction between host defense and pathogenesis is imperative for better design of novel immunotherapeutic strategies in future.

Interactions of Aspergillus fumigatus Conidia with Airway Epithelial Cells: A Critical Review

Aspergillus fumigatus is an environmental filamentous fungus that also acts as an opportunistic pathogen able to cause a variety of symptoms, from an allergic response to a life-threatening disseminated fungal infection. The infectious agents are inhaled conidia whose first point of contact is most likely to be an airway epithelial cell (AEC). The interaction between epithelial cells and conidia is multifaceted and complex, and has implications for later steps in pathogenesis. Increasing evidence has demonstrated a key role for the airway epithelium in the response to respiratory pathogens, particularly at early stages of infection; therefore, elucidating the early stages of interaction of conidia with AECs is essential to understand the establishment of infection in cohorts of at-risk patients. Here, we present a comprehensive review of the early interactions between A. fumigatus and AECs, including bronchial and alveolar epithelial cells. We describe mechanisms of adhesion, internalization of conidia by AECs, the immune response of AECs, as well as the role of fungal virulence factors, and patterns of fungal gene expression characteristic of early infection. A clear understanding of the mechanisms involved in the early establishment of infection by A. fumigatus could point to novel targets for therapy and prophylaxis.